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My boyfriend is starting Forex. I think it’s a “get rich quick scheme”. Please teach me about the reality of it.
Hi. So I like to call myself a big skeptic of all things “get rich quick”. I’ve always hated MLM’s and other sorts of marketing businesses. I’ve seen many people and heard many stories of people losing thousands and I’ve always been super skeptical about them. However, my boyfriend, let’s call him Cody, has become interested in Forex. He has been a partner with Primerica for a while now but hasn’t done anything with that. He is a manager at a gym here and makes decent money from that. He was approached by a friend to start working with Forex. When I heard about this, I was shocked, just because I’ve heard horror stories about Forex. When I look up reviews online, all I see is people losing money. When I spoke to his friend to see what this is all about, all I got was attacked and hated on for being a “non-believer”. He essentially just said that people who lose money are lazy and don’t even try. I am genuinely curious in learning more and want to be more educated in this. From what I’ve read, it depends a lot on gambling and knowing a lot about the craft. Cody is convinced he will earn $40,000 (approximately) by February doing 6% everyday excluding weekends (I have no clue what that means but I know that’s what he’s doing). I want to know if and how this is actually a legit endeavor or if he’s just delusional. Please, no attacks, I want serious, informative answers. Thanks so much. TL;DR: my bf is starting Forex and I think it’s a scam, how legit is it? Edit: I told him that if he actually does make that $40,000, I’ll apologize for my skepticism and not question this typa shit anymore. We’ll see 🤷🏼♀️ Edit: He works all day with no break and gets home at 11-12 and gets EXHAUSTED. He goes to sleep at like 1 every night and spends that free time watching tv. Nothing wrong with that I just don’t see how he has time to do this stuff. From what I’ve gathered, this has to be done in the afternoon and takes a while. Update: So I spoke to him and mentioned all the advice y’all have given me here. He said he is already doing research but he’s down to join an MLM. He says “everything is an MLM, college, businesses, everything”, which is ridiculous to me but ok. I’m scared for him but I guess there’s not much I can do. He’s writing all this advice off as idiots that had a bad experience even though most people here have said that they have had ups and downs. He also says I’m being super negative and the least bit supportive. Idk what to do😕
RBI & how its policies can start to affect the market
Disclaimer: This DD is to help start forming a market view as per RBI announcements. Also a gentle reminder that fundamentals play out over a longer time frame than intraday. The authors take no responsiblity for your yolos. With contributions by Asli Bakchodi, Bran OP & dragononweed! What is the RBI? RBI is the central bank of India. They are one of the key players who affect India’s economic trajectory. They control currency supply, banking rules and more. This means that it is not a bank in which retailers or corporates can open an account with. Instead they are a bank for bankers and the Government of India. Their functions can be broadly classified into 6. · Monetary authority · Financial supervisor for financial system · Issuer of currency · Manages Foreign exchange · Bankers bank · Banker to the government This DD will take a look at each of these functions. It will be followed by a list of rates the RBI sets, and how changes in them can affect the market. 1.Monetary Authority One of RBI’s functions is to achieve the goal of “Price Stability” in the economy. This essentially means achieving an inflation rate that is within a desired limit. A monetary policy committee (MPC) decides on the desired inflation rate and its limits through majority vote of its 6 members, in consultation with the GoI. The current inflation target for RBI is as follows Consumer Price Inflation (CPI): 4% Upper Limit: 6% Lower Limit: 2% An increase in CPI means less purchasing power. Generally speaking, if inflation is too high, the public starts cutting down on spending, leading to a negative impact on the markets. And vice versa. Lower inflation leads to more purchasing power, more spending, more investments leading to a positive impact on the market. 2.Financial Supervisor For Financial System A financial system consists of financial markets (Capital market, money market, forex market etc.), financial institutions (banks, stock exchanges, NBFC etc) & financial assets (currencies, bills, bonds etc) RBI supervises this entire system and lays down the rules and regulations for it. It can also use further ‘Selective Credit Controls’ to regulate banks. 3.Issues of currency The RBI is responsible for the printing of currency notes. RBI is free to print as much as it wants as long as the minimum reserve of Rs 200 Cr (Gold 112 Cr) is maintained. The RBI has total assets or a balance size sheet of Rs. 51 trillion (April 2020). (1 Trillion = 1 Lakh crore) India’s current reserves mean our increase in currency circulation is well managed. 4.Manages Foreign Exchange RBI regulates all of India’s foreign exchange transactions. It is the custodian of all of foreign currencies in India. It allows for the foreign exchange value of the rupee to be controlled. RBI also buy and sell rupees in the foreign exchange market at its discretion. In case of any currency movement, a country’s central bank can directly intervene to either push the currency up, as India has been doing, or to keep it artificially low, as the Chinese central bank does. To push up a currency, a central bank can sell dollars, which is the global reserve currency, or the currency against which all others are measured. To push down a currency, a central bank can buy dollars. The RBI deciding this depends on the import/export and financial health of the country. Generally a weaker rupee means imports are more expensive, but are favourable for exports. And a stronger rupee means imports are cheaper but are unfavourable for exports. A weaker rupee can make foreign investment more lucrative driving up FII. A stronger rupee can have an adverse effect of FII investing in markets. 5.Banker’s Bank Every bank has to maintain a certain amount of reserve with the RBI. A certain percentage of a bank’s liabilities (anywhere between 3-15% as decided by RBI) has to be maintained in this account. This is called the Cash Reserve Ratio. This is determined by the MPC during the monetary policy review (which happens every six weeks at present). It lends money from this reserve to other banks if they are short on cash, but generally, it is seen as a last resort move. Banks are encouraged to meet their shortfalls of cash from other resources. 6.Banker to the government RBI is the entity that carries out ALL monetary transactions on behalf of the Government. It holds custody of the cash balance of the Government, gives temporary loans to both central and state governments and manages the debt operations of the central Government, through instruments of debt and the interest rates associated with them - like bonds. The different rates set & managed by RBI - Repo rate The rate at which RBI is willing to lend to commercial banks is called as Repo Rate. Banks sometimes need money for emergency or to maintain the SLR and CRR (explained below). They borrow this from RBI but have to pay some interest on it. The interest that is to be paid on the amount to the RBI is called as Repo Rate. It does not function like a normal loan but acts like a forward contract. Banks have to provide collateral like government bonds, T-bills etc. Repo means Repurchase Option is the true meaning of Repo an agreement where the bank promises to repurchase these government securities after the repo period is over. As a tool to control inflation, RBI increases the Repo Rate making it more expensive for banks to borrow from the RBI with a view to restrict availability of money. Exact opposite stance shall be taken in case of deflationary environment. The change of repo rate is aimed to affect the flow of money in the economy. An increase in repo rate decreases the flow of money in the economy, while the decrease in repo rate increases the flow of money in the economy. RBI by changing these rates shows its stance to the economy at large whether they prioritize growth or inflation. - Reverse Repo Rate The rate at which the RBI is willing to borrow from the Banks is called as Reverse Repo Rate. If the RBI increases the reverse repo rate, it means that the RBI is willing to offer lucrative interest rate to banks to park their money with the RBI. Banks in this case agree to resell government securities after reverse repo period. Generally, an increase in reverse repo rate that banks will have a higher incentive to park their money with RBI. It decreases liquidity, affecting the market in a negative manner. Decrease in reverse repo rate increases liquidity affecting the market in a positive manner. Both the repo rate and reverse repo rate fall under the Liquidity Adjustment Facility tools for RBI. - Cash reserve ratio (CRR) Banks in India are required to deposit a specific percentage of their net demand and time liabilities (NDTL) in the form of CASH with the RBI. This minimum ratio (that is the part of the total deposits to be held as cash) is stipulated by the RBI and is known as the CRR or Cash Reserve Ratio. These reserves will not be in circulation at any point in time. For example, if a bank had a NDTL (like current Account, Savings Account and Fixed Deposits) of 100Cr and the CRR is at 3%, it would have to keep 3Cr as Cash reserve ratio to the RBI. This amount earns no interest. Currently it is at 3%. A lower cash ratio means banks can deposit just a lower amount and use the remaining money leading to higher liquidity. This translates to more money to invest which is seen as positive for the market. Inversely, a higher cash ratio equates to lower liquidity which translates to a negative market sentiment. Thus, the RBI uses the CRR to control excess money flow and regulate liquidity in the economy. - Statutory liquidity ratio (SLR) Banks in India have to keep a certain percentage of their net demand and time liabilities WITH THEMSELVES. And this can be in the form of liquid assets like gold and government securities, not just cash. A lot of banks keep them in government bonds as they give a decent interest. The current SLR ratio of 18.25%, which means that for every Rs.100 deposited in a bank, it has to invest Rs.18.50 in any of the asset classes approved by RBI. A low SLR means higher levels of loans to the private sector. This boosts investment and acts as a positive sentiment for the market. Conversely a high SLR means tighter levels of credit and can cause a negative effect on the market. Essentially, the RBI uses the SLR to control ease of credit in the economy. It also ensures that the banks maintain a certain level of funds to meet depositor’s demands instead of over liquidation. - Bank Rate Bank rate is a rate at which the Reserve Bank of India provides the loan to commercial banks without keeping any security. There is no agreement on repurchase that will be drawn up or agreed upon with no collateral as well. This is different from repo rate as loans taken with repo rate are taken on the basis of securities. Bank rate hence is higher than the repo rate. Currently the bank rate is 4.25%. Since bank rate is essentially a loan interest rate like repo rate, it affects the market in similar ways. - Marginal Cost of Funds based Lending Rate (MCLR) This is the minimum rate below which the banks are not allowed to lend. Raising this rate, makes loans more expensive, drying up liquidity, affecting the market in a negative way. Similarly, lower MCLR rates will bring in high liquidity, affecting the market in a positive way. MCLR is a varying lending rate instead of a single rate according to the kind of loans. Currently, the MCLR rate is between 6.65% - 7.15% - Marginal Standing facility Marginal Standing Facility is the interest rate at which a depository institution (generally banks) lends or borrows funds with another depository institution in the overnight market. Overnight market is the part of financial market which offers the shortest term loans. These loans have to be repaid the next day. MSF can be used by a bank after it exhausts its eligible security holdings for borrowing under other options like the Liquidity adjustment facilities. The MSF would be a penal rate for banks and the banks can borrow funds by pledging government securities within the limits of the statutory liquidity ratio. The current rate stands at 4.25%. The effect it has on the market is synonymous with the other lending rates such as repo rate & bank rate. - Loan to value ratio The loan-to-value (LTV) ratio is an assessment of lending risk that financial institutions and other lenders examine before approving a mortgage. Typically, loan assessments with high LTV ratios are considered higher risk loans. Basically, if a companies preferred form of collateral rises in value and leads the market (growing faster than the market), then the company will see the loans that it signed with higher LTV suddenly reduce (but the interest rate remains the same). Let’s consider an example of gold as a collateral. Consider a loan was approved with gold as collateral. The market price for gold is Rs 2000/g, and for each g, a loan of Rs 1500 was given. (The numbers are simplified for understanding). This would put LTV of the loan at 1500/2000 = 0.75. Since it is a substantial LTV, say the company priced the loan at 20% interest rate. Now the next year, the price of gold rose to Rs 3000/kg. This would mean that the LTV of the current loan has changed to 0.5 but the company is not obligated to change the interest rate. This means that even if the company sees a lot of defaults, it is fairly protected by the unexpected surge in the underlying asset. Moreover, since the underlying asset is more valuable, default rates for the loans goes down as people are more protective of the collateral they have placed. The same scenario for gold is happening right now and is the reason for gold backed loan providers like MUTHOOT to hit ATHs as gold is leading the economy right now. Also, these in these scenarios, it also enables companies to offer additional loan on same gold for those who are interested Instead of keeping the loan amount same most of the gold loan companies. Based on above, we can see that as RBI changes LTV for certain assets, we are in a position to identify potential institutions that could get a good Quarterly result and try to enter it early. Conclusion The above rates contain the ways in the Central Bank manages the monetary policy, growth and inflation in the country. Its impact on Stock market is often seen when these rates are changed, they act as triggers for the intraday positions on that day. But overall, the outlook is always maintained on how the RBI sees the country is doing, and knee jerk reactions are limited to intraday positions. The long term stance is always well within the limits of the outlook the big players in the market are expecting. The important thing to keep in mind is that the problems facing the economy needn’t be uni-dimensional. Problems with inflation, growth, liquidity, currency depreciation all can come together, for which the RBI will have to play a balancing role with all it powers to change these rates and the forex reserve. So the effect on the market needs to be given more thought than simply extrapolated as ‘rates go low, markets go up’. But understanding these individual effects of these rates allows you to start putting together the puzzle of how and where the market and the economy could go.
I’ve been looking for a broker that has an API for index futures and ideally also futures options. I’m looking to use the API to build a customized view of my risk based on balances, positions, and market conditions. Searching the algotrading sub I found many API-related posts, but then when I actually read them and their comments, I found they’re often lacking in real substance. It turns out many brokers or data services that have APIs don’t actually support index futures and options via the API, and instead they focus on equities, forex, or cypto. So here’s the list of what I’ve found so far. This isn’t a review of these brokers or APIs and note that I have a specific application in mind (index futures and futures options). Perhaps you’re looking for an API for equities, or you just want data and not a broker, in which case there may be a few options. Also, I’m based in the US so I didn’t really look for brokers or platforms outside the US. If you have experience with these APIs, please chime in with your thoughts. Also, I may have missed some brokers or platforms. If I did or if you see anything that needs correction please let me know.
Broker with a variety of platforms including CQG, Rithmic, TT, some with APIs
Wow, this list grew longer than I originally thought it would be. If you spot a mistake, please let me know and I’ll correct it. Edit: - added Lightspeed API - updated Dashprime to indicate some of the APIs available - added Medved Trader to table - added marketstack to table
First week of live trading and actually having a plan
Been learning forex trading now for about 2 years just reading and practising on demo, in the past 6 months however I've taken a more data driven approach and now I've just completed my first week of live trading (a small amount, nothing too big, just 200). the plan I guess is to reflect on the trades I've taken every week and use this medium as a way of peer reviewing the things I do. Took 3 trades this week, 21/10/2020 - EURAUD and EURNZD sell After identifying these pairs as sells, I viewed the potential sell move that could take place as a broader sell off of the euro rather than individual rising of the AUD or the NZD. For that reason, I decided to split my normal risk per trade amount (2.5%) in half and treat this as one euro sell trade. I closed my trades when they hit the previous days low, however as you can see, price continued moving down for a deeper sell off which is a lilbit depressing to see, knowing I could have made more if I had held, but meh, still bagged 3 times my risk so can't be too sad for the first trades of the first week. Outcome (In RR): EURAUD - 2.9 EURNZD -3.35 23/10/2020 - AUDNZD Buy I was late on my analysis on this trade because I woke up late, however I was still able to fill the limit order after price returned back to my buy zone. The trade looked good going in, however, the moves that I trade on tend to be higher momentum moves, and a few hours into the trade I could tell that there just wasnt any steam, so I moved the stop closer to the entry (but not breakeven, to give it room to breath), anyway, the market moved against me and took me out for 0.5R, saved 50% from the initial risk size so not bad. Outcome (In RR) -0.5 From demo trading this strategy, I know that sometimes the trades can run for a long time. I was curious to know how those of you that have long term swing moves manage the risk and lock in profits but also give the trades room to breath, I've been messing around with using donchians as a trailing stop method however Im eager to know of other methods. p.s lemme know if Im breaking any rules by posting this here, new to reddit and all, also, if there is any interest in it, I can post my reasoning for entering these trades if requested. p.p.s the screenshots of the trades were moderated out, but I've reposted them on my profile
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No, the British did not steal $45 trillion from India
This is an updated copy of the version on BadHistory. I plan to update it in accordance with the feedback I got. I'd like to thank two people who will remain anonymous for helping me greatly with this post (you know who you are) Three years ago a festschrift for Binay Bhushan Chaudhuri was published by Shubhra Chakrabarti, a history teacher at the University of Delhi and Utsa Patnaik, a Marxist economist who taught at JNU until 2010. One of the essays in the festschirt by Utsa Patnaik was an attempt to quantify the "drain" undergone by India during British Rule. Her conclusion? Britain robbed India of $45 trillion (or £9.2 trillion) during their 200 or so years of rule. This figure was immensely popular, and got republished in several major news outlets (here, here, here, here (they get the number wrong) and more recently here), got a mention from the Minister of External Affairs & returns 29,100 results on Google. There's also plenty of references to it here on Reddit. Patnaik is not the first to calculate such a figure. Angus Maddison thought it was £100 million, Simon Digby said £1 billion, Javier Estaban said £40 million see Roy (2019). The huge range of figures should set off some alarm bells. So how did Patnaik calculate this (shockingly large) figure? Well, even though I don't have access to the festschrift, she conveniently has written an article detailing her methodology here. Let's have a look.
How exactly did the British manage to diddle us and drain our wealth’ ? was the question that Basudev Chatterjee (later editor of a volume in the Towards Freedom project) had posed to me 50 years ago when we were fellow-students abroad.
This is begging the question.
After decades of research I find that using India’s commodity export surplus as the measure and applying an interest rate of 5%, the total drain from 1765 to 1938, compounded up to 2016, comes to £9.2 trillion; since $4.86 exchanged for £1 those days, this sum equals about $45 trillion.
This is completely meaningless. To understand why it's meaningless consider India's annual coconut exports. These are almost certainly a surplus but the surplus in trade is countered by the other country buying the product (indeed, by definition, trade surpluses contribute to the GDP of a nation which hardly plays into intuitive conceptualisations of drain). Furthermore, Dewey (2019) critiques the 5% interest rate.
She [Patnaik] consistently adopts statistical assumptions (such as compound interest at a rate of 5% per annum over centuries) that exaggerate the magnitude of the drain
The exact mechanism of drain, or transfers from India to Britain was quite simple.
Drain theory possessed the political merit of being easily grasped by a nation of peasants. [...] No other idea could arouse people than the thought that they were being taxed so that others in far off lands might live in comfort. [...] It was, therefore, inevitable that the drain theory became the main staple of nationalist political agitation during the Gandhian era.
The key factor was Britain’s control over our taxation revenues combined with control over India’s financial gold and forex earnings from its booming commodity export surplus with the world. Simply put, Britain used locally raised rupee tax revenues to pay for its net import of goods, a highly abnormal use of budgetary funds not seen in any sovereign country.
The issue with figures like these is they all make certain methodological assumptions that are impossible to prove. From Roy in Frankema et al. (2019):
the "drain theory" of Indian poverty cannot be tested with evidence, for several reasons. First, it rests on the counterfactual that any money saved on account of factor payments abroad would translate into domestic investment, which can never be proved. Second, it rests on "the primitive notion that all payments to foreigners are "drain"", that is, on the assumption that these payments did not contribute to domestic national income to the equivalent extent (Kumar 1985, 384; see also Chaudhuri 1968). Again, this cannot be tested. [...] Fourth, while British officers serving India did receive salaries that were many times that of the average income in India, a paper using cross-country data shows that colonies with better paid officers were governed better (Jones 2013).
Indeed, drain theory rests on some very weak foundations. This, in of itself, should be enough to dismiss any of the other figures that get thrown out. Nonetheless, I felt it would be a useful exercise to continue exploring Patnaik's take on drain theory.
The East India Company from 1765 onwards allocated every year up to one-third of Indian budgetary revenues net of collection costs, to buy a large volume of goods for direct import into Britain, far in excess of that country’s own needs.
So what's going on here? Well Roy (2019) explains it better:
Colonial India ran an export surplus, which, together with foreign investment, was used to pay for services purchased from Britain. These payments included interest on public debt, salaries, and pensions paid to government offcers who had come from Britain, salaries of managers and engineers, guaranteed profts paid to railway companies, and repatriated business profts. How do we know that any of these payments involved paying too much? The answer is we do not.
So what was really happening is the government was paying its workers for services (as well as guaranteeing profits - to promote investment - something the GoI does today Dalal (2019), and promoting business in India), and those workers were remitting some of that money to Britain. This is hardly a drain (unless, of course, Indian diaspora around the world today are "draining" it). In some cases, the remittances would take the form of goods (as described) see Chaudhuri (1983):
It is obvious that these debit items were financed through the export surplus on merchandise account, and later, when railway construction started on a large scale in India, through capital import. Until 1833 the East India Company followed a cumbersome method in remitting the annual home charges. This was to purchase export commodities in India out of revenue, which were then shipped to London and the proceeds from their sale handed over to the home treasury.
While Roy's earlier point argues better paid officers governed better, it is honestly impossible to say what part of the repatriated export surplus was a drain, and what was not. However calling all of it a drain is definitely misguided. It's worth noting that Patnaik seems to make no attempt to quantify the benefits of the Raj either, Dewey (2019)'s 2nd criticism:
she [Patnaik] consistently ignores research that would tend to cut the economic impact of the drain down to size, such as the work on the sources of investment during the industrial revolution (which shows that industrialisation was financed by the ploughed-back profits of industrialists) or the costs of empire school (which stresses the high price of imperial defence)
Since tropical goods were highly prized in other cold temperate countries which could never produce them, in effect these free goods represented international purchasing power for Britain which kept a part for its own use and re-exported the balance to other countries in Europe and North America against import of food grains, iron and other goods in which it was deficient.
Re-exports necessarily adds value to goods when the goods are processed and when the goods are transported. The country with the largest navy at the time would presumably be in very good stead to do the latter.
The British historians Phyllis Deane and WA Cole presented an incorrect estimate of Britain’s 18th-19th century trade volume, by leaving out re-exports completely. I found that by 1800 Britain’s total trade was 62% higher than their estimate, on applying the correct definition of trade including re-exports, that is used by the United Nations and by all other international organisations.
While interesting, and certainly expected for such an old book, re-exporting necessarily adds value to goods.
When the Crown took over from the Company, from 1861 a clever system was developed under which all of India’s financial gold and forex earnings from its fast-rising commodity export surplus with the world, was intercepted and appropriated by Britain. As before up to a third of India’s rising budgetary revenues was not spent domestically but was set aside as ‘expenditure abroad’.
So, what does this mean? Britain appropriated all of India's earnings, and then spent a third of it aboard? Not exactly. She is describing home charges see Roy (2019) again:
Some of the expenditures on defense and administration were made in sterling and went out of the country. This payment by the government was known as the Home Charges. For example, interest payment on loans raised to finance construction of railways and irrigation works, pensions paid to retired officers, and purchase of stores, were payments in sterling. [...] almost all money that the government paid abroad corresponded to the purchase of a service from abroad. [...] The balance of payments system that emerged after 1800 was based on standard business principles.India bought something and paid for it.State revenues were used to pay for wages of people hired abroad, pay for interest on loans raised abroad, and repatriation of profits on foreign investments coming into India. These were legitimate market transactions.
Indeed, if paying for what you buy is drain, then several billions of us are drained every day.
The Secretary of State for India in Council, based in London, invited foreign importers to deposit with him the payment (in gold, sterling and their own currencies) for their net imports from India, and these gold and forex payments disappeared into the yawning maw of the SoS’s account in the Bank of England.
It should be noted that India having two heads was beneficial, and encouraged investment per Roy (2019):
The fact that the India Office in London managed a part of the monetary system made India creditworthy, stabilized its currency, and encouraged foreign savers to put money into railways and private enterprise in India. Current research on the history of public debt shows that stable and large colonies found it easier to borrow abroad than independent economies because the investors trusted the guarantee of the colonist powers.
Against India’s net foreign earnings he issued bills, termed Council bills (CBs), to an equivalent rupee value. The rate (between gold-linked sterling and silver rupee) at which the bills were issued, was carefully adjusted to the last farthing, so that foreigners would never find it more profitable to ship financial gold as payment directly to Indians, compared to using the CB route. Foreign importers then sent the CBs by post or by telegraph to the export houses in India, that via the exchange banks were paid out of the budgeted provision of sums under ‘expenditure abroad’, and the exporters in turn paid the producers (peasants and artisans) from whom they sourced the goods.
Sunderland (2013) argues CBs had two main roles (and neither were part of a grand plot to keep gold out of India):
Council bills had two roles. They firstly promoted trade by handing the IO some control of the rate of exchange and allowing the exchange banks to remit funds to India and to hedge currency transaction risks. They also enabled the Indian government to transfer cash to England for the payment of its UK commitments.
The United Nations (1962) historical data for 1900 to 1960, show that for three decades up to 1928 (and very likely earlier too) India posted the second highest merchandise export surplus in the world, with USA in the first position. Not only were Indians deprived of every bit of the enormous international purchasing power they had earned over 175 years, even its rupee equivalent was not issued to them since not even the colonial government was credited with any part of India’s net gold and forex earnings against which it could issue rupees. The sleight-of-hand employed, namely ‘paying’ producers out of their own taxes, made India’s export surplus unrequited and constituted a tax-financed drain to the metropolis, as had been correctly pointed out by those highly insightful classical writers, Dadabhai Naoroji and RCDutt.
It doesn't appear that others appreciate their insight Roy (2019):
K. N. Chaudhuri rightly calls such practice ‘confused’ economics ‘coloured by political feelings’.
Surplus budgets to effect such heavy tax-financed transfers had a severe employment–reducing and income-deflating effect: mass consumption was squeezed in order to release export goods. Per capita annual foodgrains absorption in British India declined from 210 kg. during the period 1904-09, to 157 kg. during 1937-41, and to only 137 kg by 1946.
If even a part of its enormous foreign earnings had been credited to it and not entirely siphoned off, India could have imported modern technology to build up an industrial structure as Japan was doing.
This is, unfortunately, impossible to prove. Had the British not arrived in India, there is no clear indication that India would've united (this is arguably more plausible than the given counterfactual1). Had the British not arrived in India, there is no clear indication India would not have been nuked in WW2, much like Japan. Had the British not arrived in India, there is no clear indication India would not have been invaded by lizard people, much like Japan. The list continues eternally. Nevertheless, I will charitably examine the given counterfactual anyway. Did pre-colonial India have industrial potential? The answer is a resounding no. From Gupta (1980):
This article starts from the premise that while economic categories - the extent of commodity production, wage labour, monetarisation of the economy, etc - should be the basis for any analysis of the production relations of pre-British India, it is the nature of class struggles arising out of particular class alignments that finally gives the decisive twist to social change. Arguing on this premise, and analysing the available evidence, this article concludes that there was little potential for industrial revolution before the British arrived in India because, whatever might have been the character of economic categories of that period,the class relations had not sufficiently matured to develop productive forces and the required class struggle for a 'revolution' to take place.
Yet all of this did not amount to an economic situation comparable to that of western Europe on the eve of the industrial revolution. Her technology - in agriculture as well as manufacturers - had by and large been stagnant for centuries. [...] The weakness of the Indian economy in the mid-eighteenth century, as compared to pre-industrial Europe was not simply a matter of technology and commercial and industrial organization. No scientific or geographical revolution formed part of the eighteenth-century Indian's historical experience. [...] Spontaneous movement towards industrialisation is unlikely in such a situation.
So now we've established India did not have industrial potential, was India similar to Japan just before the Meiji era? The answer, yet again, unsurprisingly, is no. Japan's economic situation was not comparable to India's, which allowed for Japan to finance its revolution. From Yasuba (1986):
All in all, the Japanese standard of living may not have been much below the English standard of living before industrialization, and both of them may have been considerably higher than the Indian standard of living. We can no longer say that Japan started from a pathetically low economic level and achieved a rapid or even "miraculous" economic growth. Japan's per capita income was almost as high as in Western Europe before industrialization, and it was possible for Japan to produce surplus in the Meiji Period to finance private and public capital formation.
The circumstances that led to Meiji Japan were extremely unique. See Tomlinson (1985):
Most modern comparisons between India and Japan, written by either Indianists or Japanese specialists, stress instead that industrial growth in Meiji Japan was the product of unique features that were not reproducible elsewhere. [...] it is undoubtably true that Japan's progress to industrialization has been unique and unrepeatable
So there you have it. Unsubstantiated statistical assumptions, calling any number you can a drain & assuming a counterfactual for no good reason gets you this $45 trillion number. Hopefully that's enough to bury it in the ground. 1. Several authors have affirmed that Indian identity is a colonial artefact. For example seeRajan 1969:
Perhaps the single greatest and most enduring impact of British rule over India is that it created an Indian nation, in the modern political sense. After centuries of rule by different dynasties overparts of the Indian sub-continent, and after about 100 years of British rule, Indians ceased to be merely Bengalis, Maharashtrians,or Tamils, linguistically and culturally.
But then, it would be anachronistic to condemn eighteenth-century Indians, who served the British, as collaborators, when the notion of 'democratic' nationalism or of an Indian 'nation' did not then exist.[...]Indians who fought for them, differed from the Europeans in having a primary attachment to a non-belligerent religion, family and local chief, which was stronger than any identity they might have with a more remote prince or 'nation'.
Chakrabarti, Shubra & Patnaik, Utsa (2018). Agrarian and other histories: Essays for Binay Bhushan Chaudhuri. Colombia University Press Hickel, Jason (2018). How the British stole $45 trillion from India. The Guardian Bhuyan, Aroonim & Sharma, Krishan (2019). The Great Loot: How the British stole $45 trillion from India. Indiapost Monbiot, George (2020). English Landowners have stolen our rights. It is time to reclaim them. The Guardian Tsjeng, Zing (2020). How Britain Stole $45 trillion from India with trains | Empires of Dirt. Vice Chaudhury, Dipanjan (2019). British looted $45 trillion from India in today’s value: Jaishankar. The Economic Times Roy, Tirthankar (2019). How British rule changed India's economy: The Paradox of the Raj. Palgrave Macmillan Patnaik, Utsa (2018). How the British impoverished India. Hindustan Times Tuovila, Alicia (2019). Expenditure method. Investopedia Dewey, Clive (2019). Changing the guard: The dissolution of the nationalist–Marxist orthodoxy in the agrarian and agricultural history of India. The Indian Economic & Social History Review Chandra, Bipan et al. (1989). India's Struggle for Independence, 1857-1947. Penguin Books Frankema, Ewout & Booth, Anne (2019). Fiscal Capacity and the Colonial State in Asia and Africa, c. 1850-1960. Cambridge University Press Dalal, Sucheta (2019). IL&FS Controversy: Centre is Paying Up on Sovereign Guarantees to ADB, KfW for Group's Loan. TheWire Chaudhuri, K.N. (1983). X - Foreign Trade and Balance of Payments (1757–1947). Cambridge University Press Sunderland, David (2013). Financing the Raj: The City of London and Colonial India, 1858-1940. Boydell Press Dewey, Clive (1978). Patwari and Chaukidar: Subordinate officials and the reliability of India’s agricultural statistics. Athlone Press Smith, Lisa (2015). The great Indian calorie debate: Explaining rising undernourishment during India’s rapid economic growth. Food Policy Duh, Josephine & Spears, Dean (2016). Health and Hunger: Disease, Energy Needs, and the Indian Calorie Consumption Puzzle. The Economic Journal Vankatesh, P. et al. (2016). Relationship between Food Production and Consumption Diversity in India – Empirical Evidences from Cross Section Analysis. Agricultural Economics Research Review Gupta, Shaibal (1980). Potential of Industrial Revolution in Pre-British India. Economic and Political Weekly Raychaudhuri, Tapan (1983). I - The mid-eighteenth-century background. Cambridge University Press Yasuba, Yasukichi (1986). Standard of Living in Japan Before Industrialization: From what Level did Japan Begin? A Comment. The Journal of Economic History Tomblinson, B.R. (1985). Writing History Sideways: Lessons for Indian Economic Historians from Meiji Japan. Cambridge University Press Rajan, M.S. (1969). The Impact of British Rule in India. Journal of Contemporary History Bryant, G.J. (2000). Indigenous Mercenaries in the Service of European Imperialists: The Case of the Sepoys in the Early British Indian Army, 1750-1800. War in History
Disclaimer: None of this is financial advice. I have no idea what I'm doing. Please do your own research or you will certainly lose money. I'm not a statistician, data scientist, well-seasoned trader, or anything else that would qualify me to make statements such as the below with any weight behind them. Take them for the incoherent ramblings that they are. TL;DR at the bottom for those not interested in the details. This is a bit of a novel, sorry about that. It was mostly for getting my own thoughts organized, but if even one person reads the whole thing I will feel incredibly accomplished.
For those of you not familiar, please see the various threads on this trading system here. I can't take credit for this system, all glory goes to ParallaxFX! I wanted to see how effective this system was at H1 for a couple of reasons: 1) My current broker is TD Ameritrade - their Forex minimum is a mini lot, and I don't feel comfortable enough yet with the risk to trade mini lots on the higher timeframes(i.e. wider pip swings) that ParallaxFX's system uses, so I wanted to see if I could scale it down. 2) I'm fairly impatient, so I don't like to wait days and days with my capital tied up just to see if a trade is going to win or lose. This does mean it requires more active attention since you are checking for setups once an hour instead of once a day or every 4-6 hours, but the upside is that you trade more often this way so you end up winning or losing faster and moving onto the next trade. Spread does eat more of the trade this way, but I'll cover this in my data below - it ends up not being a problem. I looked at data from 6/11 to 7/3 on all pairs with a reasonable spread(pairs listed at bottom above the TL;DR). So this represents about 3-4 weeks' worth of trading. I used mark(mid) price charts. Spreadsheet link is below for anyone that's interested.
I'm pretty much using ParallaxFX's system textbook, but since there are a few options in his writeups, I'll include all the discretionary points here:
I'm using the stop entry version - so I wait for the price to trade beyond the confirmation candle(in the direction of my trade) before entering. I don't have any data to support this decision, but I've always preferred this method over retracement-limit entries. Maybe I just like the feeling of a higher winrate even though there can be greater R:R using a limit entry. Variety is the spice of life.
I put my stop loss right at the opposite edge of the confirmation candle. NOT at the edge of the 2-candle pattern that makes up the system. I'll get into this more below - not enough trades are saved to justify the wider stops. (Wider stop means less $ per pip won, assuming you still only risk 1%).
All my profit/loss statistics are based on a 1% risk per trade. Because 1 is real easy to multiply.
There are definitely some questionable trades in here, but I tried to make it as mechanical as possible for evaluation purposes. They do fit the definitions of the system, which is why I included them. You could probably improve the winrate by being more discretionary about your trades by looking at support/resistance or other techniques.
I didn't use MBB much for either entering trades, or as support/resistance indicators. Again, trying to be pretty mechanical here just for data collection purposes. Plus, we all make bad trading decisions now and then, so let's call it even.
As stated in the title, this is for H1 only. These results may very well not play out for other time frames - who knows, it may not even work on H1 starting this Monday. Forex is an unpredictable place.
I collected data to show efficacy of taking profit at three different levels: -61.8%, -100% and -161.8% fib levels described in the system using the passive trade management method(set it and forget it). I'll have more below about moving up stops and taking off portions of a position.
And now for the fun. Results!
Total Trades: 241
TP at -61.8%: 177 out of 241: 73.44%
TP at -100%: 156 out of 241: 64.73%
TP at -161.8%: 121 out of 241: 50.20%
Adjusted Proft % (takes spread into account):
TP at -61.8%: 5.22%
TP at -100%: 23.55%
TP at -161.8%: 29.14%
As you can see, a higher target ended up with higher profit despite a much lower winrate. This is partially just how things work out with profit targets in general, but there's an additional point to consider in our case: the spread. Since we are trading on a lower timeframe, there is less overall price movement and thus the spread takes up a much larger percentage of the trade than it would if you were trading H4, Daily or Weekly charts. You can see exactly how much it accounts for each trade in my spreadsheet if you're interested. TDA does not have the best spreads, so you could probably improve these results with another broker. EDIT: I grabbed typical spreads from other brokers, and turns out while TDA is pretty competitive on majors, their minors/crosses are awful! IG beats them by 20-40% and Oanda beats them 30-60%! Using IG spreads for calculations increased profits considerably (another 5% on top) and Oanda spreads increased profits massively (another 15%!). Definitely going to be considering another broker than TDA for this strategy. Plus that'll allow me to trade micro-lots, so I can be more granular(and thus accurate) with my position sizing and compounding.
A Note on Spread
As you can see in the data, there were scenarios where the spread was 80% of the overall size of the trade(the size of the confirmation candle that you draw your fibonacci retracements over), which would obviously cut heavily into your profits. Removing any trades where the spread is more than 50% of the trade width improved profits slightly without removing many trades, but this is almost certainly just coincidence on a small sample size. Going below 40% and even down to 30% starts to cut out a lot of trades for the less-common pairs, but doesn't actually change overall profits at all(~1% either way). However, digging all the way down to 25% starts to really make some movement. Profit at the -161.8% TP level jumps up to 37.94% if you filter out anything with a spread that is more than 25% of the trade width! And this even keeps the sample size fairly large at 187 total trades. You can get your profits all the way up to 48.43% at the -161.8% TP level if you filter all the way down to only trades where spread is less than 15% of the trade width, however your sample size gets much smaller at that point(108 trades) so I'm not sure I would trust that as being accurate in the long term. Overall based on this data, I'm going to only take trades where the spread is less than 25% of the trade width. This may bias my trades more towards the majors, which would mean a lot more correlated trades as well(more on correlation below), but I think it is a reasonable precaution regardless.
Time of Day
Time of day had an interesting effect on trades. In a totally predictable fashion, a vast majority of setups occurred during the London and New York sessions: 5am-12pm Eastern. However, there was one outlier where there were many setups on the 11PM bar - and the winrate was about the same as the big hours in the London session. No idea why this hour in particular - anyone have any insight? That's smack in the middle of the Tokyo/Sydney overlap, not at the open or close of either. On many of the hour slices I have a feeling I'm just dealing with small number statistics here since I didn't have a lot of data when breaking it down by individual hours. But here it is anyway - for all TP levels, these three things showed up(all in Eastern time):
7pm-4am: Fewer setups, but winrate high.
5am-6am: Lots of setups, but but winrate low.
12pm-3pm Medium number of setups, but winrate low.
I don't have any reason to think these timeframes would maintain this behavior over the long term. They're almost certainly meaningless. EDIT: When you de-dup highly correlated trades, the number of trades in these timeframes really drops, so from this data there is no reason to think these timeframes would be any different than any others in terms of winrate. That being said, these time frames work out for me pretty well because I typically sleep 12am-7am Eastern time. So I automatically avoid the 5am-6am timeframe, and I'm awake for the majority of this system's setups.
Moving stops up to breakeven
This section goes against everything I know and have ever heard about trade management. Please someone find something wrong with my data. I'd love for someone to check my formulas, but I realize that's a pretty insane time commitment to ask of a bunch of strangers. Anyways. What I found was that for these trades moving stops up...basically at all...actually reduced the overall profitability. One of the data points I collected while charting was where the price retraced back to after hitting a certain milestone. i.e. once the price hit the -61.8% profit level, how far back did it retrace before hitting the -100% profit level(if at all)? And same goes for the -100% profit level - how far back did it retrace before hitting the -161.8% profit level(if at all)? Well, some complex excel formulas later and here's what the results appear to be. Emphasis on appears because I honestly don't believe it. I must have done something wrong here, but I've gone over it a hundred times and I can't find anything out of place.
Moving SL up to 0% when the price hits -61.8%, TP at -100%
Adjusted Proft % (takes spread into account): 5.36%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%
Adjusted Proft % (takes spread into account): -1.01% (yes, a net loss)
Now, you might think exactly what I did when looking at these numbers: oof, the spread killed us there right? Because even when you move your SL to 0%, you still end up paying the spread, so it's not truly "breakeven". And because we are trading on a lower timeframe, the spread can be pretty hefty right? Well even when I manually modified the data so that the spread wasn't subtracted(i.e. "Breakeven" was truly +/- 0), things don't look a whole lot better, and still way worse than the passive trade management method of leaving your stops in place and letting it run. And that isn't even a realistic scenario because to adjust out the spread you'd have to move your stoploss inside the candle edge by at least the spread amount, meaning it would almost certainly be triggered more often than in the data I collected(which was purely based on the fib levels and mark price). Regardless, here are the numbers for that scenario:
Moving SL up to 0% when the price hits -61.8%, TP at -100%
Winrate(breakeven doesn't count as a win): 46.4%
Adjusted Proft % (takes spread into account): 17.97%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%
Winrate(breakeven doesn't count as a win): 65.97%
Adjusted Proft % (takes spread into account): 11.60%
From a literal standpoint, what I see behind this behavior is that 44 of the 69 breakeven trades(65%!) ended up being profitable to -100% after retracing deeply(but not to the original SL level), which greatly helped offset the purely losing trades better than the partial profit taken at -61.8%. And 36 went all the way back to -161.8% after a deep retracement without hitting the original SL. Anyone have any insight into this? Is this a problem with just not enough data? It seems like enough trades that a pattern should emerge, but again I'm no expert. I also briefly looked at moving stops to other lower levels (78.6%, 61.8%, 50%, 38.2%, 23.6%), but that didn't improve things any. No hard data to share as I only took a quick look - and I still might have done something wrong overall. The data is there to infer other strategies if anyone would like to dig in deep(more explanation on the spreadsheet below). I didn't do other combinations because the formulas got pretty complicated and I had already answered all the questions I was looking to answer.
2-Candle vs Confirmation Candle Stops
Another interesting point is that the original system has the SL level(for stop entries) just at the outer edge of the 2-candle pattern that makes up the system. Out of pure laziness, I set up my stops just based on the confirmation candle. And as it turns out, that is much a much better way to go about it. Of the 60 purely losing trades, only 9 of them(15%) would go on to be winners with stops on the 2-candle formation. Certainly not enough to justify the extra loss and/or reduced profits you are exposing yourself to in every single other trade by setting a wider SL. Oddly, in every single scenario where the wider stop did save the trade, it ended up going all the way to the -161.8% profit level. Still, not nearly worth it.
As I've said many times now, I'm really not qualified to be doing an analysis like this. This section in particular. Looking at shared currency among the pairs traded, 74 of the trades are correlated. Quite a large group, but it makes sense considering the sort of moves we're looking for with this system. This means you are opening yourself up to more risk if you were to trade on every signal since you are technically trading with the same underlying sentiment on each different pair. For example, GBP/USD and AUD/USD moving together almost certainly means it's due to USD moving both pairs, rather than GBP and AUD both moving the same size and direction coincidentally at the same time. So if you were to trade both signals, you would very likely win or lose both trades - meaning you are actually risking double what you'd normally risk(unless you halve both positions which can be a good option, and is discussed in ParallaxFX's posts and in various other places that go over pair correlation. I won't go into detail about those strategies here). Interestingly though, 17 of those apparently correlated trades ended up with different wins/losses. Also, looking only at trades that were correlated, winrate is 83%/70%/55% (for the three TP levels). Does this give some indication that the same signal on multiple pairs means the signal is stronger? That there's some strong underlying sentiment driving it? Or is it just a matter of too small a sample size? The winrate isn't really much higher than the overall winrates, so that makes me doubt it is statistically significant. One more funny tidbit: EUCAD netted the lowest overall winrate: 30% to even the -61.8% TP level on 10 trades. Seems like that is just a coincidence and not enough data, but dang that's a sucky losing streak. EDIT: WOW I spent some time removing correlated trades manually and it changed the results quite a bit. Some thoughts on this below the results. These numbers also include the other "What I will trade" filters. I added a new worksheet to my data to show what I ended up picking.
Total Trades: 75
TP at -61.8%: 84.00%
TP at -100%: 73.33%
TP at -161.8%: 60.00%
Moving SL up to 0% when the price hits -61.8%, TP at -100%: 53.33%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%: 53.33% (yes, oddly the exact same winrate. but different trades/profits)
Adjusted Proft % (takes spread into account):
TP at -61.8%: 18.13%
TP at -100%: 26.20%
TP at -161.8%: 34.01%
Moving SL up to 0% when the price hits -61.8%, TP at -100%: 19.20%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%: 17.29%
To do this, I removed correlated trades - typically by choosing those whose spread had a lower % of the trade width since that's objective and something I can see ahead of time. Obviously I'd like to only keep the winning trades, but I won't know that during the trade. This did reduce the overall sample size down to a level that I wouldn't otherwise consider to be big enough, but since the results are generally consistent with the overall dataset, I'm not going to worry about it too much. I may also use more discretionary methods(support/resistance, quality of indecision/confirmation candles, news/sentiment for the pairs involved, etc) to filter out correlated trades in the future. But as I've said before I'm going for a pretty mechanical system. This brought the 3 TP levels and even the breakeven strategies much closer together in overall profit. It muted the profit from the high R:R strategies and boosted the profit from the low R:R strategies. This tells me pair correlation was skewing my data quite a bit, so I'm glad I dug in a little deeper. Fortunately my original conclusion to use the -161.8 TP level with static stops is still the winner by a good bit, so it doesn't end up changing my actions. There were a few times where MANY (6-8) correlated pairs all came up at the same time, so it'd be a crapshoot to an extent. And the data showed this - often then won/lost together, but sometimes they did not. As an arbitrary rule, the more correlations, the more trades I did end up taking(and thus risking). For example if there were 3-5 correlations, I might take the 2 "best" trades given my criteria above. 5+ setups and I might take the best 3 trades, even if the pairs are somewhat correlated. I have no true data to back this up, but to illustrate using one example: if AUD/JPY, AUD/USD, CAD/JPY, USD/CAD all set up at the same time (as they did, along with a few other pairs on 6/19/20 9:00 AM), can you really say that those are all the same underlying movement? There are correlations between the different correlations, and trying to filter for that seems rough. Although maybe this is a known thing, I'm still pretty green to Forex - someone please enlighten me if so! I might have to look into this more statistically, but it would be pretty complex to analyze quantitatively, so for now I'm going with my gut and just taking a few of the "best" trades out of the handful. Overall, I'm really glad I went further on this. The boosting of the B/E strategies makes me trust my calculations on those more since they aren't so far from the passive management like they were with the raw data, and that really had me wondering what I did wrong.
What I will trade
Putting all this together, I am going to attempt to trade the following(demo for a bit to make sure I have the hang of it, then for keeps):
"System Details" I described above.
TP at -161.8%
Static SL at opposite side of confirmation candle - I won't move stops up to breakeven.
Trade only 7am-11am and 4pm-11pm signals.
Nothing where spread is more than 25% of trade width.
Looking at the data for these rules, test results are:
Adjusted Proft % (takes spread into account): 47.43%
I'll be sure to let everyone know how it goes!
Other Technical Details
ATR is only slightly elevated in this date range from historical levels, so this should fairly closely represent reality even after the COVID volatility leaves the scalpers sad and alone.
The sample size is much too small for anything really meaningful when you slice by hour or pair. I wasn't particularly looking to test a specific pair here - just the system overall as if you were going to trade it on all pairs with a reasonable spread.
Here's the spreadsheet for anyone that'd like it. (EDIT: Updated some of the setups from the last few days that have fully played out now. I also noticed a few typos, but nothing major that would change the overall outcomes. Regardless, I am currently reviewing every trade to ensure they are accurate.UPDATE: Finally all done. Very few corrections, no change to results.) I have some explanatory notes below to help everyone else understand the spiraled labyrinth of a mind that put the spreadsheet together.
I'm on the East Coast in the US, so the timestamps are Eastern time.
Time stamp is from the confirmation candle, not the indecision candle. So 7am would mean the indecision candle was 6:00-6:59 and the confirmation candle is 7:00-7:59 and you'd put in your order at 8:00.
I found a couple AM/PM typos as I was reviewing the data, so let me know if a trade doesn't make sense and I'll correct it.
Insanely detailed spreadsheet notes
For you real nerds out there. Here's an explanation of what each column means:
Pair - duh
Date/Time - Eastern time, confirmation candle as stated above
Win to -61.8%? - whether the trade made it to the -61.8% TP level before it hit the original SL.
Win to -100%? - whether the trade made it to the -100% TP level before it hit the original SL.
Win to -161.8%? - whether the trade made it to the -161.8% TP level before it hit the original SL.
Retracement level between -61.8% and -100% - how deep the price retraced after hitting -61.8%, but before hitting -100%. Be careful to look for the negative signs, it's easy to mix them up. Using the fib% levels defined in ParallaxFX's original thread. A plain hyphen "-" means it did not retrace, but rather went straight through -61.8% to -100%. Positive 100 means it hit the original SL.
Retracement level between -100% and -161.8% - how deep the price retraced after hitting -100%, but before hitting -161.8%. Be careful to look for the negative signs, it's easy to mix them up. Using the fib% levels defined in ParallaxFX's original thread. A plain hyphen "-" means it did not retrace, but rather went straight through -100% to -161.8%. Positive 100 means it hit the original SL.
Trade Width(Pips) - the size of the confirmation candle, and thus the "width" of your trade on which to determine position size, draw fib levels, etc.
Loser saved by 2 candle stop? - for all losing trades, whether or not the 2-candle stop loss would have saved the trade and how far it ended up getting if so. "No" means it didn't save it, N/A means it wasn't a losing trade so it's not relevant.
Spread(ThinkorSwim) - these are typical spreads for these pairs on ToS.
Spread % of Width - How big is the spread compared to the trade width? Not used in any calculations, but interesting nonetheless.
True Risk(Trade Width + Spread) - I set my SL at the opposite side of the confirmation candle knowing that I'm actually exposing myself to slightly more risk because of the spread(stop order = market order when submitted, so you pay the spread). So this tells you how many pips you are actually risking despite the Trade Width. I prefer this over setting the stop inside from the edge of the candle because some pairs have a wide spread that would mess with the system overall. But also many, many of these trades retraced very nearly to the edge of the confirmation candle, before ending up nicely profitable. If you keep your risk per trade at 1%, you're talking a true risk of, at most, 1.25% (in worst-case scenarios with the spread being 25% of the trade width as I am going with above).
Win or Loss in %(1% risk) including spread TP -61.8% - not going to go into huge detail, see the spreadsheet for calculations if you want. But, in a nutshell, if the trade was a win to 61.8%, it returns a positive # based on 61.8% of the trade width, minus the spread. Otherwise, it returns the True Risk as a negative. Both normalized to the 1% risk you started with.
Win or Loss in %(1% risk) including spread TP -100% - same as the last, but 100% of Trade Width.
Win or Loss in %(1% risk) including spread TP -161.8% - same as the last, but 161.8% of Trade Width.
Win or Loss in %(1% risk) including spread TP -100%, and move SL to breakeven at 61.8% - uses the retracement level columns to calculate profit/loss the same as the last few columns, but assuming you moved SL to 0% fib level after price hit -61.8%. Then full TP at 100%.
Win or Loss in %(1% risk) including spread take off half of position at -61.8%, move SL to breakeven, TP 100% - uses the retracement level columns to calculate profit/loss the same as the last few columns, but assuming you took of half the position and moved SL to 0% fib level after price hit -61.8%. Then TP the remaining half at 100%.
Overall Growth(-161.8% TP, 1% Risk) - pretty straightforward. Assuming you risked 1% on each trade, what the overall growth level would be chronologically(spreadsheet is sorted by date).
Based on the reasonable rules I discovered in this backtest:
Date range: 6/11-7/3
Adjusted Proft % (takes spread into account): 47.43%
Demo Trading Results
Since this post, I started demo trading this system assuming a 5k capital base and risking ~1% per trade. I've added the details to my spreadsheet for anyone interested. The results are pretty similar to the backtest when you consider real-life conditions/timing are a bit different. I missed some trades due to life(work, out of the house, etc), so that brought my total # of trades and thus overall profit down, but the winrate is nearly identical. I also closed a few trades early due to various reasons(not liking the price action, seeing support/resistance emerge, etc). A quick note is that TD's paper trade system fills at the mid price for both stop and limit orders, so I had to subtract the spread from the raw trade values to get the true profit/loss amount for each trade. I'm heading out of town next week, then after that it'll be time to take this sucker live!
Date range: 7/9-7/30
Adjusted Proft % (takes spread into account): 20.73%
Starting Balance: $5,000
Ending Balance: $6,036.51
Live Trading Results
I started live-trading this system on 8/10, and almost immediately had a string of losses much longer than either my backtest or demo period. Murphy's law huh? Anyways, that has me spooked so I'm doing a longer backtest before I start risking more real money. It's going to take me a little while due to the volume of trades, but I'll likely make a new post once I feel comfortable with that and start live trading again.
Reviews about forex trading have already pop out mostly on review sites especially this time. If you are considering a different forex trading brand, avoid getting caught out by scammers who are using social media offering unrealistic profits. If they could make the money they are claiming, why are they even advertising on social media? Remember, there are plenty legitimate brokers out there. So you better make a research first before biting to the scammers offers. They might be offering to trade on your behalf or use their own managed or automated trades.
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eToro: impressions, doubts and (ignored) lessons from copy trading
(no promotional content, no affiliate links) Hi, exactly four years ago, I started copying eToro investors / traders that I selected using the broker's built-in search engine (profitable in last two years, already being copied by others), followed by manual filtering, to take into account fluctuations in yearly returns, composition of their portfolios etc. With that, I got a list of 10 people whom I started to copy on a demo account: https://drive.google.com/file/d/1u52f0XHfr-LauIscKcFDYF0yGTTUr6VY/view?usp=sharing In the screenshot you can see that in case of the first two of them the amount invested was $10,000, while for the rest it was just $100. This is because I started copying the first two a couple of weeks earlier; eventually I changed this into $100 the same day I made the screenshot and this is when my calculations start - so this thing is irrelevant, I just cannot travel in time to make another screenshot. What I did after that? Well, within the next six weeks my profits oscillated between -$11 and +$9.50 (the biggest profit was on Nov 9, a day after US presidential elections). I found this "boring" and discontinued experimenting with copy trading. Today I looked back at those ten traders. Here is what I found. Firstly, seven of them are not with eToro anymore; investorNo1, Simple-Stock-Mkt, tradingrelax, 4exPirate, primit, Gallojack, xjurokx. The other three traders are:
toppertrader: not being copied by anyone and for a good reason: his loss this year alone is 61.16%!
Jean-marcLenfant: copied by only 67 people; his loss this year is -1.09% but in general he is quite successful, with yearly profits ranging from 3.57% to 7.32%.
Girem2: he has no copiers, his profit this year is 41.45% but in 2018 he experienced a loss of 83.15%!
My observations and thoughts are as follows:
Seven out of ten traders are not with eToro anymore, which makes me wonder why. I have no proof but my guess is they simply performed poorly, lost their copiers and closed their accounts. This is already alarming but what if they opened another account? Or, even worse, multiple accounts? They could be investing small money and try different risky approaches, hoping that at least one account will turn out profitable in the long turn, attracting potential copiers. (I'm not claiming that those 7 particular traders did this, it's just my general suspicion regarding some of eToro traders)
I'm unable to calculate what would be my profit if I never stopped copying them, because I cannot check at what day and with what profit those seven traders left eToro. I'm guessing this would be an immense loss. On the other hand, considering the three traders who are still with eToro, I would lose more than a quarter of my assets!
What now? I must be a quite adventurous person or at least an incorrigible optimist, because a month ago (exactly on Aug 26th) I started copying three traders with real money. Here is who they are. rubymza (Heloise Greeff)
invests in stocks, with GOOG, INTC, BLDP, MA, MSFT, AMZN, V, MU, IBM and NXPI making up 50.3% of her portfolio (allocation of each of them is in between 3.02% and 6.85%)
active since 2016 (only the year 2016 ended with a loss)
has 3044 copiers and $2M-$5M of copy assets under management
strategy (her own words): "My investing strategy focusses mostly on US indices, tech and pharma, promising future (5-10years) growth. My trades are based on technical analysis using machine learning to understand patterns and trends in the markets. I prefer to keep a diverse portfolio to spread risk while achieving great returns."
he is a Forex trader, making typically 21 trades per week; his favorite currency pairs are EURCHF (12% of trades), CADCHF and GBPUSD; the trades, however, typically make up below 5% of his portfolio (at least whenever I'm checking it), making most of my funds unused
active since January 2017: surprisingly enough, he has every single month profitable, though monthly profits are in the range of 0.03% to 3.34% only
has 8977 copiers and more than $5M of copy assets under management
strategy (his own words): "I monitor currency pairs all day to find the best entry. There is some management/scaling position for perfect entry. The risk control is a big part of my strategy," (quite vague, to be honest)
commodities compose 76% of his portfolio and his favorite assets are Gold and Oil (at the moment, Gold makes up half of invested amount)
active since July 2016, with the following yearly profits, starting from 2016: 6.56%, 10.05%, 13.09%, 32.26% and -2.03% (the current year)
has 1493 copiers and $1M-$2M of copy assets under management
strategy (his own words): "My system is based on patterns, and a variety of technical analysis tools and some fundamental analysis. I primarily trade in commodities. " (quite vague as well)
own experience: my profit with rayvahey is 2.56%
What was my strategy to hand-pick these particular traders? First I did some basic scanning using eToro's built-in search engine. The most important filter was that the trader was profitable within the last two years: unfortunately, eToro does not allow to reach details of earlier performance automatically. To know how the trader performed before 2019, I had to look at stats in the profile of each of them. I was also taking into account how often they trade (to avoid those who do only a couple of trades yearly), whether they were trading recently and whether they write posts regularly in their feed. With this, I got a list of fifteen candidates to copy:
As you already know, I finally chose three of them. Rubymza seemed to be the most trustworthy stock trader, based on profits, posts feed and regular trading, among other things. Regarding OlivierDanvel, his uniqueness is the ability to record continuous profits with the Forex market. Finally, with rayvahey I wanted to increase my exposure to the commodities market. Wish me good luck! Michael P.S. You might find those copy-trading related readings interesting:
Managers face a new challenge–managing a remote forex trader team with more and more Forex companies looking out for outsourcing. Events such as motivational tactics, task control and Communications still require a specialist approach even if this has been simplified using technology and a high-speed Internet. The advantages of employing people on a distance are endless and make your competitive edge easy. Your company can help create a talented team of the best specialists in the market because you can not just hire people from everywhere in the world. This is why a remote employment type will continue to gain momentum in the future. It’s all the challenges that value it. Remote job is very easy–output, autonomy and flexibility. You influence the manner you operate your team, the smoothness and achievement of the company procedures. And although most individuals still think that remote employees are not as productive as usual in office, the reality of the matter is that most remote employees actually see an increase in productivity equal to a complete additional working day. So how do you efficiently handle a distant team? How can you contribute to its growth, commitment and coordination? Below are some tips that we have collected to assist you find the response. TIP 1 – Maintain high performance If your team scatters throughout the world, productivity can be impacted, unless certain measures are taken to keep it. It is not only difficult to say in a virtual environment how much time your staff spend on assignments and how successful they are, but also it is essential to be evident how the entire team handles the workload. Therefore, it is essential that a business process is well thought-out and that several software tools are used. Training tools such as Toggl or Clockify can help you to really understand the processes underway, the amount of time spent on these projects, and the number of breaks taken in real time. This allows executives to identify the weaknesses of each worker and attempt to solve them. This doesn’t imply that you need to overuse these applications and develop stringent procedures. If you work remotely, you are likely to choose this due to the flexibility it provides you. Managers need to strike a balance between liberty and coherent timescales for their staff. For instance, they must decide which communication instruments they use to discuss issues of great significance–Chat with urgent subjects, Email with stuff to wait and Video Calls. Furthermore, all project information must be available to every member of the team (instruments like Google Drive and DropBox may assist). It must also ensure complete transparency and transparency. They also need to bear in mind always that distant workers can all operate in distinct time zones, so that everyone can tune in to a video call, it is essential to discover a time window. Also, when employing persons, you need to ensure that your location time differences are not more than 3 hours from the time zone of your office. Due to time differences, for each conference you always have to have a very clear agenda and must stick to it. Finally, you need to measure the yield to always have your hand on the pulse. Try to list all the main points in the work of each team member that indicate the performance. Set clear objectives with measurable outcomes so you can see clearly what is anticipated and how well your staff are responding to these expectations. Hold monthly reviews in the team to see how all people work together and whether everyone handles them properly. However, do not be scared to give honest feedback, remember that individuals almost always concentrate more on beneficial than adverse points. This is why executives have to be frank and always attempt to discover something useful at the end. TIP 2 – Strengthen communication skills For each team, good communication between employees is essential, but for distant teams in particular. The absence of physical attendance and distinct working schedules can all lead your team members to operate as people instead of a united front. Remote teams effectively need to interact twice if not three times the ordinary team. And executives must support these communications by creating more possibilities. Set some of your team’s prompters. Say you always mark the time places if you are on your schedule for calls. Select and ensure your team uses the primary communication instruments. Implement instruments like Slack, WebEx and Skype and let your staff know that they are available all the time. Agree on the duration of an email reply so that you understand when to expect answers to your message. Try as much as necessary to integrate video calls. IMCCAs have found that, when they actively use video conference instruments, 90% of remote personnel feel more linked with their team. Video enables your team to make a name face and bind better. When you see a individual, it’s always simpler to speak to than just by messaging. Video calling helps your distant team feel moved and isolated less. Share your screen with your team members to facilitate and clarify clarifications. Create distinct channels for sharing of interesting stuff, such as fun stories, suggestions for films or updates on TV shows that you all view. Your purpose is to create a virtual environment that fosters and enhances communication between your team. TIP 3 – Engaging, Inspiring And Motivating The main element of effective teamwork is motivation. Entrepreneur says company costs 450 to $550 billion per year in losses of productivity for an unmotivated or de-engaged employee. Managers who work with remote teams have to invest in them and work hard every day to increase morality. In distant teams it is even more essential to build a powerful corporate culture than in the physical. Begin with transparency, one of the basic elements of a driven team. You need to make sure that all of your team know precisely what the business is doing, its goals and its role. Share corporate news and updates, celebrate your own accomplishments and attempt to make your team feel real. Be frank and let them know you as their leader. Discuss yourselves with them and share your private vision. Describe the stuff you handle at the moment, so they know that you do as difficult as you do. Request your advice on various issues and opinions. Be in keeping with feedback and with your praise in particular. Don’t just ask them to do a nice job, but to highlight certain accomplishments and duties. In corporate public chats, try also to praise your distant staff for their accomplishments throughout the whole business. Create your team’s rituals and traditions. Celebrate the birthdays and unique occasions of your distant staff. Why doesn’t every team member ask for a brief video that you wish to edit later and send to your partner celebrating? Improve camaraderie with true private communication through investments at least once a year in corporate retreats where your distant team can meet in reality. Find out more here about motivating your team. TIP 4 – Select your team with wisely Hiring individuals with the correct distance to work is your halfway to achievement. It’s all about everything else. You can also influence your entire team with a lazy or unprofessional distant worker. This is why certain precautions are essential during the recruitment process. First and foremost, nobody claims you have to employ the individual from the beginning. Test your skills and abilities for a number of months by employing them part-time and giving them the opportunity to work long term when you’re sure they’re a nice addition to your staff. Don’t be stingy with salaries. Just because your employee is working remotely doesn’t mean that they aren’t doing more than your typical office worker does. In most cases, remote workers are actually doing more, so their salaries have to reflect this. Make sure your fresh remote staff can function from home. Do you have a good working environment where you can concentrate without distractions? Otherwise, it may be better to propose either paying for co-working space or buying equipment to build that room at home for them. Take into consideration that your staff can all come from distinct nations and cultures. Learn how to talk obviously and broadly convey your message. Ask your team in their message to use easy phrases and a neutral tone. Maintain a calendar of all global holidays affecting and planning your team members. Make sure fresh staff are quick to retire. Create a guide with all the primary information about your job and the instruments you use. Ask your team members to share their finest advice on remote working. Recall the faster the better they adjust. Managing distance teams can be challenging, but actually you can create a skilled, loyal, hard-working team with a few simple rules to assist your company to succeed.
Fueling The Us Economy's Middle Market Growth Engine
It has a major presence in New York and different world monetary facilities both out and in of Europe. And if you are the owner of a privately held firm and this data has peaked your interest or even led you to have more questions, then attending a Generational Equity M&A seminar can be a sensible next step. A few hours of your time will provide you with substantial ideas to pursue in order so that you can take advantage of our present seller’s market.
Job Openings Related To Middle Market Investment Bank
It is a mix of equity, mounted deposits, company bonds, liquid funds and authorities funds, among others. Based in your danger urge for food, you can determine how a lot of your cash may be invested in equities via NPS. Debt mutual fund schemes are suitable for traders who want regular returns. They are much less unstable and, therefore, thought of less risky compared to equity funds. Some of the middle-market banks resemble regional boutiques in that they concentrate on providing services to a specific trade or sector. For instance, one of the extra acknowledged center-market investment banking companies is KBW, an investment bank that focuses on working with monetary services sector companies. Some of the more well-recognized middle-market corporations are Piper Sandler Companies, Cowen Group, and Houlihan Lokey. National full-service center market corporations – Expand their companies to mix funding banking, wealth management, equity analysis, and brokerage and personal fairness companies. Banks are financial institutions offering a breadth of products and services, together with managing deposits, lending, wealth management, forex trade, and funding banking. Examples of properly-identified elite boutique funding banks are Lazard LLC, Evercore Group LLC, and Moelis & Company. The smallest of the investment banks, each when it comes to agency size and typical deal dimension, are the banks known as regional boutique banks. This lack of a succession plan, coupled with impending retirement, creates an urgency for these companies to alter arms, and bodes well for traders and corporations to amass, consolidate and develop them. Most senior debt suppliers will wrestle to supply all of the money wanted to fund an acquisition. It is comprised of corporations that are not giant enough to receive massive bank loans, yet it's too giant to receive small enterprise loans. Upstream movement from a microbusiness to being a center market entity necessitates that you just turn into a manager and learn to manage managers. Therefore, administration and hiring expertise are very important within the lower center market. put their give attention to the decrease center market section and improve proficiency in doing deals in the segment. The most amount that may be invested in the scheme Rs 15 lakh. At maturity, the investment amount is repaid to the senior citizen. In the occasion of death of senior citizen, the money will be paid to the nominee. SCSS has a five-yr tenure, which could be additional prolonged by three years as soon as the scheme matures. if you are able to leverage your skills to get an fairness stake someplace you need to be on the trail to more wealth. I'm just curious, but how does the efficient tax come out to 50%? Is it the AMTI that causes each marginal dollar to be so low or what? On December 1, 2005, Stifel Financial closed on the acquisition of the Legg Mason Capital Markets business from Citigroup Inc. The LM Capital Markets business acquired included investment banking, fairness and glued earnings analysis, equity gross sales and buying and selling, and taxable fastened income gross sales and buying and selling . These assets gave the company substantial research and capital market capabilities and reworked the corporate from a regional agency to a national one. Each of the bulge bracket banks operates internationally and has a large world, in addition to home, presence. Most bulge bracket banks also have industrial and retail banking divisions and generate extra income by cross-promoting monetary merchandise. The Public Investment Fund of Saudi Arabia is that nation's sovereign wealth fund. A hedge fund is an aggressively managed portfolio of investments that makes use of leveraged, lengthy, short and by-product positions. Credit Suisse came underneath fireplace from U.S. regulators for allowing its nicely-identified consumer confidentiality to help others avoid paying taxes. The firm has CHF 796 Billion in assets, equivalent to about $800 billion USD. The company has a serious U.S. presence, partially pushed by its merger with First Boston with a relationship going back to 1978. Eric Rosenberg lined small business and investing products for The Balance. Information Generational Group publishes on the World Wide Web may include references or cross references to other products, applications and providers that are not announced or out there in your nation. Lower middle market companies principally use mezzanine finance as a capital supply for acquisitions, although it can also be used for development capital, in addition to other monetary needs. It offers an a variety of benefits, similar to little to no dilution and a comparatively larger funding amount. One fascinating product for a non-US company is its focus in U.S. municipal finance . The bank also works in conventional investment banking services like M&A and fairness and debt market points. Most regular shoppers received’t want investment banking companies, but for rising companies and excessive-net-value individuals, an funding financial institution may supply distinctive financial services to meet your needs. An investment associate should deliver a spread of experience to the desk including a really strong observe report of execs who have successfully built center market corporations throughout a variety of industries. In an age the place capital has become a commodity, alignment round values quite than valuation alone is more and more essential to the profitable outcome of partaking non-public fairness. Investment banking compensation could not range all that much between working for one of many largest bulge bracket banks as in comparison with a smaller, elite boutique bank. While the bigger banks commonly handle bigger offers, those offers are few and much between smaller deals.
Stifel Employee Reviews
are monetary establishments or intermediaries that deal mostly with mid-market corporations, particularly for raising debt or fairness capital in addition to mergers and acquisitions.
Today, massive banks cater to their traditional clients, which incorporates particular person prospects and both massive and small corporations by providing savings and checking accounts, certificates of deposit, loans and similar companies.
Many of them also have companies that operate as funding banks, and work with corporate and institutional shoppers by offering underwriting of inventory offers, brokerage, and M&A advisory.
The definition of a business financial institution has advanced dramatically up to now a number of decades.
Middle market firms are mid-size companies having annual revenues from $10 million up to $500 million and one hundred to 2,000 staff.
Bank Of China focuses primarily on industrial banking actions similar to deposits and withdrawals, and international exchange. The bank also is even licensed to issue banknotes in Hong Kong and Macau. We specialize in delivering dependable, creative and compelling financing options to middle market corporations backed by personal equity sponsors. The firm’s credit experience also forms the inspiration of our Late Stage Lending enterprise and our Broadly Syndicated Loan funding program.
Are Investment Bankers Rich
I’m presently 21yrs old & finally transferred into a high 5 undergraduate enterprise program right here in Toronto, previously was learning biology for the mistaken causes. I tend to main in Accounting & Finance + Minors in Computer Science and Applied Statistics + Will be going by way of a rigorous coding bootcamp program. Yes, you might get extra consumer publicity and responsibilities in some teams, but you can additionally get stuck working on a lot of boring, normal sell-facet auctions and personal placements. Like other funding banks, the advisory companies of Bank of America Merrill Lynch are necessary for corporations looking to increase funds in public markets. When going public, funding bankers help decide the preliminary share value while balancing liquidity and demand. However, a excessive-return, low-risk mixture in a investment product, unfortunately, does not exist. Most buyers need to make investments in such a method that they get sky-high returns as shortly as potential with out the risk of dropping principal cash.
Middle Market Investment Bank Salaries In The United States
On the downside, there was an especially negative individual within the division who received together with no one. Pay was also mergers and acquisitions advisory very low, with only small cost of residing changes annually. While bonuses increased with longevity, you couldn't construct your salary. In a mezzanine loan, there might be collateral within the type of a pledge inventory. Step by step instruction on how the professionals on Wall Street worth an organization. certification program, designed to remodel anyone into a world-class financial analyst. In an actively traded fund, the returns are largely depending on a fund manager's capacity to generate returns. Index funds and trade-traded fund are passively managed, and these observe the underlying index. Equity schemes are categorised based on market-capitalisation or the sectors during which they make investments. The Central Bank with impact from July 1, 2020 has launched Floating Rate Savings Bond, 2020 . The biggest distinction between earlier 7.seventy five% financial savings bonds and the newly launched floating fee bond is that the interest rate on the newly launched financial savings bond is topic to reset in every six months. While they typically have locations spanning a single nation, center market banks are rarely found internationally. Full-service funding banks supply a variety of business and funding providers. Chief Executive’s publications are designed to assist CEOs do their jobs better and run their businesses more effectively. Those that begin doing so now will set up themselves fully in a market that, by design, is much more difficult to oversaturate as a result of its sheer volume.
Ok, so I want to get into trading as I've been stalking this trader for a while now on social media and honestly it seems too good to be true. I've done intensive research into his life but I can't quite see why or how he is making so much money... let's start with the basics, he grew up in a city 30mins away from me, he failed school dropped out and apparently started trading at an early age of around 18. Heres where it gets weird: him and 2 of his (what seems like) childhood friends created and owns a company, let's call it "GO-forex" and the company seems to be a signal giving forex company (I'm not sure how it all works) but apparently he sends messages to other forex trades when to make trades. Apparently he does this for free as he gets paid by "another company" to do this as his job. What's sketchy is the way he recruits people and how the business model works, basically when I asked if I could work for him he said "you need more followers" on Instagram. I looked at his workers, a group of 10-15 people and they all had 5k+ followers on Instagram an continuously keep posting things like motivation, why forex is the best, flexing and importantly, telling people to get on this free forex signals thing. That's how I found out about him, a mutual friend was working for him promoting forex lifestyl and that but suddenly left and became a mechanic... what's also sketchy is that he keeps saying "minimum £300 is what the broker will take for you to start and you can withdraw money at any time" I know a broker gets commission and stuff but whats going on here? He posts daily messages he gets from his customers making £90 or £120 and them thanking him, and his always like "join now!!!". I think the app he uses is metatrader and he always flexes when he makes a lot of pips, making anywhere between £1000 to £7000 profit per day. He is also constantly promoting his masterclass and shows that he is into real estate investing too. I really have no clue what is going on with this, what's the business model? Does he make more money off the company or trading himself? Is he faking it till he makes it? Is he secretly the broker? Is he stealing his customers money and using it for his own trades? Why does he want to give people signals? Why is his business so reliant on social media? Is he a fraud? I have too many questions but not any answers. He is living the life I always wanted yet he looks like he hasn't worked hard or isn't that smart....
Hello Fellow Redditor Traders, I realized that trading a particular system is not about the system itself but on the approach of the user, an infinite amount of strategies exist out there and if a user is littered with a negative, inpatient, impulsive, loss averse, etc mindset than not even the "top" performing strategies would be of use. Thus, to me it seems that I get into this negative mindset from time to time, going into frequent draw-downs and consistent losses (low success rate) but fortunately with adequate risk management (to an extent) which kept my capital alive for this past year of actively trading the Forex market (-15% thus far). I am detail oriented and have a very detailed journal of every trade I take/ took (>500 trades mainly Forex) with statistical calculations on the different strategies that I have formulated, implemented, and back-tested manually (and have mostly failed due to user error in live markets). I can help with providing reflection on the trade setups technically and fundamentally, formulating a trading plan from scratch, formulating strategies, establishing adequate risk management and provide self-reflection as I fully know how it could be when stuck in a negative cycle. I need someone to reciprocate accountability with (Currently at GMT +4 but wont mind the time difference in effort to make this work), I have a trend continuation based strategy that can work if I have the right mindset towards it, thus I would like to find someone to hold me accountable for the trades I enter during the week (end of week review) and also share ideas with back and forth on the different setups that are provided during the week. Anyone serious about trading is welcome! Regards, Z
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The Next Crypto Wave: The Rise of Stablecoins and its Entry to the U.S. Dollar Market
Author: Christian Hsieh, CEO of Tokenomy This paper examines some explanations for the continual global market demand for the U.S. dollar, the rise of stablecoins, and the utility and opportunities that crypto dollars can offer to both the cryptocurrency and traditional markets. The U.S. dollar, dominant in world trade since the establishment of the 1944 Bretton Woods System, is unequivocally the world’s most demanded reserve currency. Today, more than 61% of foreign bank reserves and nearly 40% of the entire world’s debt is denominated in U.S. dollars1. However, there is a massive supply and demand imbalance in the U.S. dollar market. On the supply side, central banks throughout the world have implemented more than a decade-long accommodative monetary policy since the 2008 global financial crisis. The COVID-19 pandemic further exacerbated the need for central banks to provide necessary liquidity and keep staggering economies moving. While the Federal Reserve leads the effort of “money printing” and stimulus programs, the current money supply still cannot meet the constant high demand for the U.S. dollar2. Let us review some of the reasons for this constant dollar demand from a few economic fundamentals.
Demand for U.S. Dollars
Firstly, most of the world’s trade is denominated in U.S. dollars. Chief Economist of the IMF, Gita Gopinath, has compiled data reflecting that the U.S. dollar’s share of invoicing was 4.7 times larger than America’s share of the value of imports, and 3.1 times its share of world exports3. The U.S. dollar is the dominant “invoicing currency” in most developing countries4. https://preview.redd.it/d4xalwdyz8p51.png?width=535&format=png&auto=webp&s=9f0556c6aa6b29016c9b135f3279e8337dfee2a6 https://preview.redd.it/wucg40kzz8p51.png?width=653&format=png&auto=webp&s=71257fec29b43e0fc0df1bf04363717e3b52478f This U.S. dollar preference also directly impacts the world’s debt. According to the Bank of International Settlements, there is over $67 trillion in U.S. dollar denominated debt globally, and borrowing outside of the U.S. accounted for $12.5 trillion in Q1 20205. There is an immense demand for U.S. dollars every year just to service these dollar debts. The annual U.S. dollar buying demand is easily over $1 trillion assuming the borrowing cost is at 1.5% (1 year LIBOR + 1%) per year, a conservative estimate. https://preview.redd.it/6956j6f109p51.png?width=487&format=png&auto=webp&s=ccea257a4e9524c11df25737cac961308b542b69 Secondly, since the U.S. has a much stronger economy compared to its global peers, a higher return on investments draws U.S. dollar demand from everywhere in the world, to invest in companies both in the public and private markets. The U.S. hosts the largest stock markets in the world with more than $33 trillion in public market capitalization (combined both NYSE and NASDAQ)6. For the private market, North America’s total share is well over 60% of the $6.5 trillion global assets under management across private equity, real assets, and private debt investments7. The demand for higher quality investments extends to the fixed income market as well. As countries like Japan and Switzerland currently have negative-yielding interest rates8, fixed income investors’ quest for yield in the developed economies leads them back to the U.S. debt market. As of July 2020, there are $15 trillion worth of negative-yielding debt securities globally (see chart). In comparison, the positive, low-yielding U.S. debt remains a sound fixed income strategy for conservative investors in uncertain market conditions. Source: Bloomberg Last, but not least, there are many developing economies experiencing failing monetary policies, where hyperinflation has become a real national disaster. A classic example is Venezuela, where the currency Bolivar became practically worthless as the inflation rate skyrocketed to 10,000,000% in 20199. The recent Beirut port explosion in Lebanon caused a sudden economic meltdown and compounded its already troubled financial market, where inflation has soared to over 112% year on year10. For citizens living in unstable regions such as these, the only reliable store of value is the U.S. dollar. According to the Chainalysis 2020 Geography of Cryptocurrency Report, Venezuela has become one of the most active cryptocurrency trading countries11. The demand for cryptocurrency surges as a flight to safety mentality drives Venezuelans to acquire U.S. dollars to preserve savings that they might otherwise lose. The growth for cryptocurrency activities in those regions is fueled by these desperate citizens using cryptocurrencies as rails to access the U.S. dollar, on top of acquiring actual Bitcoin or other underlying crypto assets.
The Rise of Crypto Dollars
Due to the highly volatile nature of cryptocurrencies, USD stablecoin, a crypto-powered blockchain token that pegs its value to the U.S. dollar, was introduced to provide stable dollar exposure in the crypto trading sphere. Tether is the first of its kind. Issued in 2014 on the bitcoin blockchain (Omni layer protocol), under the token symbol USDT, it attempts to provide crypto traders with a stable settlement currency while they trade in and out of various crypto assets. The reason behind the stablecoin creation was to address the inefficient and burdensome aspects of having to move fiat U.S. dollars between the legacy banking system and crypto exchanges. Because one USDT is theoretically backed by one U.S. dollar, traders can use USDT to trade and settle to fiat dollars. It was not until 2017 that the majority of traders seemed to realize Tether’s intended utility and started using it widely. As of April 2019, USDT trading volume started exceeding the trading volume of bitcoina12, and it now dominates the crypto trading sphere with over $50 billion average daily trading volume13. https://preview.redd.it/3vq7v1jg09p51.png?width=700&format=png&auto=webp&s=46f11b5f5245a8c335ccc60432873e9bad2eb1e1 An interesting aspect of USDT is that although the claimed 1:1 backing with U.S. dollar collateral is in question, and the Tether company is in reality running fractional reserves through a loose offshore corporate structure, Tether’s trading volume and adoption continues to grow rapidly14. Perhaps in comparison to fiat U.S. dollars, which is not really backed by anything, Tether still has cash equivalents in reserves and crypto traders favor its liquidity and convenience over its lack of legitimacy. For those who are concerned about Tether’s solvency, they can now purchase credit default swaps for downside protection15. On the other hand, USDC, the more compliant contender, takes a distant second spot with total coin circulation of $1.8 billion, versus USDT at $14.5 billion (at the time of publication). It is still too early to tell who is the ultimate leader in the stablecoin arena, as more and more stablecoins are launching to offer various functions and supporting mechanisms. There are three main categories of stablecoin: fiat-backed, crypto-collateralized, and non-collateralized algorithm based stablecoins. Most of these are still at an experimental phase, and readers can learn more about them here. With the continuous innovation of stablecoin development, the utility stablecoins provide in the overall crypto market will become more apparent.
In addition to trade settlement, stablecoins can be applied in many other areas. Cross-border payments and remittances is an inefficient market that desperately needs innovation. In 2020, the average cost of sending money across the world is around 7%16, and it takes days to settle. The World Bank aims to reduce remittance fees to 3% by 2030. With the implementation of blockchain technology, this cost could be further reduced close to zero. J.P. Morgan, the largest bank in the U.S., has created an Interbank Information Network (IIN) with 416 global Institutions to transform the speed of payment flows through its own JPM Coin, another type of crypto dollar17. Although people argue that JPM Coin is not considered a cryptocurrency as it cannot trade openly on a public blockchain, it is by far the largest scale experiment with all the institutional participants trading within the “permissioned” blockchain. It might be more accurate to refer to it as the use of distributed ledger technology (DLT) instead of “blockchain” in this context. Nevertheless, we should keep in mind that as J.P. Morgan currently moves $6 trillion U.S. dollars per day18, the scale of this experiment would create a considerable impact in the international payment and remittance market if it were successful. Potentially the day will come when regulated crypto exchanges become participants of IIN, and the link between public and private crypto assets can be instantly connected, unlocking greater possibilities in blockchain applications. Many central banks are also in talks about developing their own central bank digital currency (CBDC). Although this idea was not new, the discussion was brought to the forefront due to Facebook’s aggressive Libra project announcement in June 2019 and the public attention that followed. As of July 2020, at least 36 central banks have published some sort of CBDC framework. While each nation has a slightly different motivation behind its currency digitization initiative, ranging from payment safety, transaction efficiency, easy monetary implementation, or financial inclusion, these central banks are committed to deploying a new digital payment infrastructure. When it comes to the technical architectures, research from BIS indicates that most of the current proofs-of-concept tend to be based upon distributed ledger technology (permissioned blockchain)19. https://preview.redd.it/lgb1f2rw19p51.png?width=700&format=png&auto=webp&s=040bb0deed0499df6bf08a072fd7c4a442a826a0 These institutional experiments are laying an essential foundation for an improved global payment infrastructure, where instant and frictionless cross-border settlements can take place with minimal costs. Of course, the interoperability of private DLT tokens and public blockchain stablecoins has yet to be explored, but the innovation with both public and private blockchain efforts could eventually merge. This was highlighted recently by the Governor of the Bank of England who stated that “stablecoins and CBDC could sit alongside each other20”. One thing for certain is that crypto dollars (or other fiat-linked digital currencies) are going to play a significant role in our future economy.
There is never a dull moment in the crypto sector. The industry narratives constantly shift as innovation continues to evolve. Twelve years since its inception, Bitcoin has evolved from an abstract subject to a familiar concept. Its role as a secured, scarce, decentralized digital store of value has continued to gain acceptance, and it is well on its way to becoming an investable asset class as a portfolio hedge against asset price inflation and fiat currency depreciation.Stablecoins have proven to be useful as proxy dollars in the crypto world, similar to how dollars are essential in the traditional world. It is only a matter of time before stablecoins or private digital tokens dominate the cross-border payments and global remittances industry. There are no shortages of hypes and experiments that draw new participants into the crypto space, such as smart contracts, new blockchains, ICOs, tokenization of things, or the most recent trends on DeFi tokens. These projects highlight the possibilities for a much more robust digital future, but the market also needs time to test and adopt. A reliable digital payment infrastructure must be built first in order to allow these experiments to flourish. In this paper we examined the historical background and economic reasons for the U.S. dollar’s dominance in the world, and the probable conclusion is that the demand for U.S. dollars will likely continue, especially in the middle of a global pandemic, accompanied by a worldwide economic slowdown. The current monetary system is far from perfect, but there are no better alternatives for replacement at least in the near term. Incremental improvements are being made in both the public and private sectors, and stablecoins have a definite role to play in both the traditional and the new crypto world. Thank you. Reference:  How the US dollar became the world’s reserve currency, Investopedia  The dollar is in high demand, prone to dangerous appreciation, The Economist  Dollar dominance in trade and finance, Gita Gopinath  Global trades dependence on dollars, The Economist & IMF working papers  Total credit to non-bank borrowers by currency of denomination, BIS  Biggest stock exchanges in the world, Business Insider  McKinsey Global Private Market Review 2020, McKinsey & Company  Central banks current interest rates, Global Rates  Venezuela hyperinflation hits 10 million percent, CNBC  Lebanon inflation crisis, Reuters  Venezuela cryptocurrency market, Chainalysis  The most used cryptocurrency isn’t Bitcoin, Bloomberg  Trading volume of all crypto assets, coinmarketcap.com  Tether US dollar peg is no longer credible, Forbes  New crypto derivatives let you bet on (or against) Tether’s solvency, Coindesk  Remittance Price Worldwide, The World Bank  Interbank Information Network, J.P. Morgan  Jamie Dimon interview, CBS News  Rise of the central bank digital currency, BIS  Speech by Andrew Bailey, 3 September 2020, Bank of England
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