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No blind buying! See the proof for 286 pips in #EURCAD! And you can reach us 24x7, and get more proofs and user reviews for the performance of the real-time, #norepaintindicator #Pipbreaker. Then go for it & make progress in your forex life. https://wetalktrade.com/best-indicator-for-mt4/

No blind buying! See the proof for 286 pips in #EURCAD! And you can reach us 24x7, and get more proofs and user reviews for the performance of the real-time, #norepaintindicator #Pipbreaker. Then go for it & make progress in your forex life. https://wetalktrade.com/best-indicator-for-mt4/ submitted by Wetalktrade to u/Wetalktrade [link] [comments]

http://twitter.com/forex_in_world/status/1169781000194416645#forex #forextrading Top 9 Forexbrokerinc Reviews USA-Regulated & US Clients. »» https://t.co/yfcS5IzFSz pic.twitter.com/xjWSrF80A9— FOREX IN WORLD (@forex_in_world) September 6, 2019

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http://twitter.com/forex_in_world/status/1152869618312196097#forex #forextrading Top 9 Forexbrokerinc Reviews USA-Regulated & US Clients. »» https://t.co/7zIrCTmJWB pic.twitter.com/H0aIukZ7fP— FOREX IN WORLD (@forex_in_world) July 21, 2019

http://twitter.com/forex_in_world/status/1152869618312196097#forex #forextrading Top 9 Forexbrokerinc Reviews USA-Regulated & US Clients. »» https://t.co/7zIrCTmJWB pic.twitter.com/H0aIukZ7fP— FOREX IN WORLD (@forex_in_world) July 21, 2019 submitted by Red-its to forextweet [link] [comments]

http://twitter.com/forex_in_world/status/1146739335364063234#forex #forextrading Top 9 Forexbrokerinc Reviews USA-Regulated & US Clients. »» https://t.co/6IZg85HfBz pic.twitter.com/qcgUwKtEMr— FOREX IN WORLD (@forex_in_world) July 4, 2019

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http://twitter.com/forex_in_world/status/1143780297126928384#forex #forextrading Top 9 Forexbrokerinc Reviews USA-Regulated & US Clients. »» https://t.co/eHPBrBUDVq pic.twitter.com/JecbhMY7ho— FOREX IN WORLD (@forex_in_world) June 26, 2019

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@forex_in_world : #forex #forextrading Top 9 Forexbrokerinc Reviews USA-Regulated & US Clients. »» https://t.co/aHqjhubWII https://t.co/nER8jrZind

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No Agent Taobao Direct Buying Guide! Let's view all baby and determine

Taobao Direct Guide for users familiar with 3rd party agents and navigating taobao (with chrome google translate on, hence the title)
What is Taobao direct? Basically instead of copying and pasting the item URL into the agent website, you add items to your cart like a regular ecommerce site, check out, wait for items to arrive in the warehouse (similar to what happens when you use an agent) and then when all your items from various sellers are in, you request the logistics company to send everything to you.
Disclaimer: I have no Chinese fluency written or otherwise. I did everything through Google translate and my experience with how tb works through agents. If something goes wrong I will probably write off the item 🤣 if you communicate a lot with the ts who use translators it also helps get your point across. If you type in English in tb live chat they will redirect you to the HK/tw help staff who have medium English. Also I bought items I purchased previously with an agent or vouched for here on RL or had crazy high reviews/ratings.
Pros:
Cons:
I think the ideal usage for taobao direct would be light items like innerwear, jewelry, soft/non fragile goods, generally clothing and shoes although I don’t know if they will include the box by default.
Please see here for the image guide for ordering Sorry in advance if my descriptions are wonky, I'm not great at following OR writing instructions but hopefully the screenshots make it easier to follow along.
  1. Create an account (there are various guides out there for overseas members) and go into your account and add your home address (or the superbuy warehouse address)
  2. Find your items and change the delivery location to "overseas", add to cart
  3. When you're ready to check out hit check out, enter your cc info on the alipay (remember to use a card that doesn't charge foreign transaction fees) and confirm it goes through.
  4. Wait for all your stuff to come in. When its in the tb warehouse it will show up in the "consolidated delivery" section tagged with a weight (usually volumetric or actual). The 20 day countdown will start once its available for international shipping.
  5. After all your items are in, or you can batch up by selecting items on the consolidated delivery page, submit for delivery. Pay again through alipay.
  6. Use the check logistics option to get the tracking info and wait for your haul!
  7. After receiving but before you open, take photos of it on a scale and the lxwxh with a ruler as well. This is because they will overestimate your shipping but there isn't rehearsal shipping like with agents. You can request a refund after the fact with the "refund/complaint" option on the consolidated delivery page (mine says check refund because I've already gone through it)
  8. Getting a refund: select the "only refund" option, "goods received" and "shipping cost does not match" and leave the full shipping amount in. Upload your measurement and weight photos (make sure the file size is not too big). Within 72hr they will reply and ask you to modify your application with the real amount owed (if any). It will go back to your cc through alipay (may take a few days).
Cost comparison: Even after the 5% sales tax and 3% alipay, it cost me $6.20 total from my credit card statement. A 39 yuan top up for sb is $6.53 as of today (if using paypal). For some the qc pictures and the longer storage period are well worth the difference. However a good compromise is the parcel forwarding option in sb. Instead of shipping to your house you can set up superbuy’s warehouse address and pay in taobao and wait for your items to show up in sb. You also have to submit the item link and the tracking # in superbuy so they can find your stuff. There's no sales tax and usually no shipping and you can select the coupons you want. I had a pair of pants make it to the sb warehouse almost 24hr after ordering, and another 24hr after entering my shipping info and item link in sb, it showed up in my account with free (non hd) pictures of the item. Then I cried putting together the shipping parcel lol.
This is a good way to dodge the sales tax and hold items for longer. However then you're at the mercy of the shipping costs (but you do have more options for delivery lines and you can customize how you want your items packaged too). The taobao warehouse will really throw everything in there, probably in a poly envelope.
The taobao shipping rates are 90yuan for the first .5kg and 48 yuan per every .5 after which is very competitive even after accounting for volumetric weight. Sb ems starts at 186 for the first .5kg and 61y every .5kg after. Of course rates and terms are subject to change with the times.
I had a package that came in at 277g when I measured it at home but I was charged for 1.6kg. After sending in the package images they refunded 144yuan (the true volumetric weight was about .97kg.) Taobao volumetric calculation is lxwxh (cm)/6000. Timeline wise I submitted 8/16 and received 8/28 although I think because it was so light they used epacket/china post because it was not an EMS tracking # big sigh. Still less than 10 days can't complain.
Hope this helps! I'm sure I missed something on this guide so feel free to leave any questions and I will update the post accordingly. Apologies this is very us-centric, I also cannot comment on getting a refund or exchange from sellers before you ship out but there is now english support (albeit a bit wonky) through chat and aliwangwang+google translate can get you pretty far.
Ps: highly recommend using the app too as its easier to get chat messages from the seller. You can screenshot and upload images to Google translate to read the text.
submitted by yuchin to RepLadies [link] [comments]

APIs offered by brokers and data platforms

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.

Platform Notes
ADM Investor Services No API
Ally Invest Does not support futures instruments
Alpaca Only supports US Equities
Alpha Vantage Does not support futures instruments
AMP Broker with a huge number of platforms available including some with APIs
ApexFutures No API
Arcade Trader No API
AvaTrade Does not support futures instruments
Backtrader Not a data feed; otherwise looks cool but also looks like a one-man shop
Cannon Trading Broker with a variety of platforms, some have API access such as TT
Centerpoint No API
Charles Schwab API does not support futures instruments
Cobra No API
Daniels Trading No API
Discount Trading Broker with a variety of platforms including CQG, Rithmic, TT, some with APIs
Edge Clear Broker with a variety of platforms including CQG, Rithmic, TT, some with APIs
Eroom Now part of Dashprime. Offer a variety of APIs including CQG, TT, CBOE's Silexx, and others via FIX.
ETNA Trader Only supports equities, options (including multi-legs), ETFs, Mutual Funds (Forex with cryptocurrencies coming soon)
ETrade API seems robust but OAuth authorization needs to be refreshed via login once per 24 hours
Futures Online No API
Gain Capital Futures API available, based on .NET; unsure if they are open to retail clients
GFF Brokers Broker with a large number of platforms including some with API access
High Ridge Futures Broker with a variety of platforms including CQG, Rithmic, TT, some with APIs
iBroker API available; contact them for more info
IEX Cloud Looks great but does not support futures instruments
Infinity Futures JSON API available; contact them for more info
Interactive Brokers Client Web API looks promising if clunky
Intrinio Supports futures instruments but is expensive
Koyfin No API
Lightspeed C++ API available
marketstack API for equities available. Does not support futures instruments.
Medved Trader Windows app with a streaming API to various data sources and brokers. See comment below about API beta access.
NinjaTrader Does not support futures options
Norgate Data Not a broker; supports futures data for $270/year
Oanda Forex only; API last updated in 2018
Optimus Futures Broker with a large number of available platforms including some with API access
Phillip Capital Broker with a large number of available platforms including some with API access
polygon.io Expensive but looks slick; does not support futures instruments
Quandl API looks solid; $49/monthly for personal use, does not allow distributing or sharing data; not a broker
Quantconnect Does not expose raw data
Quantopian Does not expose raw data
Quantower Software that connects to multiple brokers and data feeds; API to their software via C# interface
Saxo Markets Broker with extensively documented API
Stage 5 Trading API available through Trading Technologies
Straits Financial Broker with several platforms available including some with APIs such as CQG, R
Sweet Futures Broker with a large number of available platforms including some with API access
TastyWorks There's an unofficial Python API
TenQuant.io Does not support futures instruments
ThinkorSwim Does not support futures instruments via the API
Tiingo Free account tier but does not support futures instruments
TradePro Broker with a number of platforms available; unclear if any are available with API access
Tradier Free developer API account for delayed data but does not support futures instruments
TradeStation Nice looking API docs and supports futures instruments; requires opening an account and a minimum balance of $100k and there’s no trial available
TradeFutures4Less Broker with a variety of platforms including CQG, Rithmic, TT, some with APIs
TradingTechnologies API looks robust; pricing starts at $700/month
TradingView Does not expose data API
Tradovate Technologies API exists, documentation unknown; need to talk to their account team
Wedbush Futures Broker with several platforms offered, a few of which have API access
WEX .NET/COM only; pricing not disclosed on website
Xignite Pricing not disclosed on website but they do support futures instruments
Yahoo Finance API Available through RapidAPI or via direct access; but it’s discontinued and unreliable
Zaner 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
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Forex Signals App on iTunes Read reviews, get customer ratings, see screenshots, and learn more about Forex Signals on the App Store. Download Forex Signals and enjoy it on your iPhone, iPad, and iPod touch. https://itunes.apple.com/us/app/forex-signals/id882296265

submitted by forexsignals246 to forex_trades [link] [comments]

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:
My observations and thoughts are as follows:
  1. 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)
  2. 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)

OlivierDanvel (Olivier Jean Andre Danvel)

rayvahey (Raymond Noel Vahey)
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:

Disclosures:
submitted by investing-scientist2 to StockMarket [link] [comments]

H1 Backtest of ParallaxFX's BBStoch system

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.

Background

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.

System Details

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:

And now for the fun. Results!

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):
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.
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:
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.

Correlated Trades

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.
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):
Looking at the data for these rules, test results are:
I'll be sure to let everyone know how it goes!

Other Technical Details

Raw Data

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.

Insanely detailed spreadsheet notes

For you real nerds out there. Here's an explanation of what each column means:

Pairs

  1. AUD/CAD
  2. AUD/CHF
  3. AUD/JPY
  4. AUD/NZD
  5. AUD/USD
  6. CAD/CHF
  7. CAD/JPY
  8. CHF/JPY
  9. EUAUD
  10. EUCAD
  11. EUCHF
  12. EUGBP
  13. EUJPY
  14. EUNZD
  15. EUUSD
  16. GBP/AUD
  17. GBP/CAD
  18. GBP/CHF
  19. GBP/JPY
  20. GBP/NZD
  21. GBP/USD
  22. NZD/CAD
  23. NZD/CHF
  24. NZD/JPY
  25. NZD/USD
  26. USD/CAD
  27. USD/CHF
  28. USD/JPY

TL;DR

Based on the reasonable rules I discovered in this backtest:

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!

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.
submitted by ForexBorex to Forex [link] [comments]

New graduate and need advice

Hello, I am a 21 year old who had recently graduated an engineering course last April. I had planned to take the board exams this coming month but a few weeks ago, PRC had announced that all exams that aren't medical related be moved to 2021.
Some of my classmates had decided to get a job (and are planning to quit it a few months before the boards), and this got me pressured into thinking that I must get one too. Though my intentions are more into providing for the family since this quarantine really did hit us bad.
Just a bit of background, I live with my parents and 2 siblings. Only my father works for the family and earns ~28k a month. My mother is a full-time housewife and one of my siblings is a PWD, and is not in the mental capacity to work. My other sibling is starting college this year. With the quarantine, my father earned less than the usual. Really just enough to pay our bills.
Before quarantine, I had 40k saved into my bank account from living frugally for the past 5 years of college and it has been reduced to 10k because I had to pay for the review center, books, and even covered some holes in our finances (debts).
Honestly, when I finished passing all my requirements in March, I had scoured the internet for jobs and listings and was about to jump ship into one of those virtual assistant jobs when my family and friends stopped me. They say that money can wait and I should just focus on my license.
So taking their advice, I continued my studies but also joined financial literacy webinars like stocks and forex trading (all of them are only showing the tip of the iceberg and baiting you to pay for a full course though). I had also tried my hand at game dev since I program as a hobby.
But alas, the exam is moved and we desperately need money and it got me into thinking again.
So my questions now are: 1) Should I continue what I'm doing right now? Focus on my studies and hobbies while learning about financial literacy? Our finances are draining and I do not know how long we can hold. 2) I have zero formal work experience but I love programming. I am quite adept in several programming languages like python, javascript, html, java, c, c++, etc. Is it possible to formally put these skills to the test and also improving them by working remotely? If so, how? I am not 100% confident on my skills yet but I am always willing to learn. 3) What can I do to the 10k in my savings account? I am still unsure on what the future may bring. This could be the only thing that we can classify as an emergency fund. 4) I am at the age where I want to have finances of my own but also want to help my family. In the case that I start working but still want to support my family, is there any financial advice that I must follow if I do this?
Thank you so much for taking your time to read. I am not sure if this is the correct tag but please do tell of I'm wrong and I will correct it. I also apologize if my grammar and tense are off, I am doing my best but please do tell me if something is wrong, it will help me improve.
TL;DR: New graduate, board exams moved to 2021, whole family struggling financially because of quarantine. Should I start working or continue investing in my self first?
Edit: Thank you so much for your words guys! I had decided to start applying for jobs, while still working on expanding my knowledge and skillset through tutorials and courses online! I do still plan to take the boards though just in case I might need it.
I would also like to invite other fresh grads who are unsure of their next steps to read through the comments. The people here really give good advice and their words might help you reach a decision like it did for me.
submitted by Arthur_Cross240 to phinvest [link] [comments]

[META] Recent scam/spam trends.. Or, a peak inside what it's like to moderate /r/forex

After a few...especially trying...interactions with unhappy ban recipients today, I thought it would be fun to share a little info on what moderators do to keep this place clean. :)
The forex industry is full of shady characters. Any industry sitting on the intersection of financial independence, work, and money, is bound to attract them. There are many reasons for this; the lower barrier to entry compared to other markets, the lack of public knowledge on the subject, and greedy human nature to name a few.
Moderating a subreddit dedicated to forex (or anything trading realted for that matter,) presents extra challenges beyond your regular sub. Marketers and scammers are super motivated, and MLM / referral marketing is extremely popular right now, which can turn everyday regular users into sources of spam.
How we currently tackle this problem involves technology (scripts, bots, and automod,) a mod review workflow, and some smart sleuthing when needed.
The mod team and our scripts aren't perfect though... but the few false positives we get are a very, very small fraction of all mod actions taken (~1%.) Unfortunately, that means some otherwise sincere members get handled roughly, and that can really suck.. I wish there was a better way, but the alternative is this place becomes a wild west and starts looking like your gmail spam folder.
That said, here's my personal stats for JUST the last 24 hours:
And I'm just one of the mods. . .
So what scammer and marketing trends are we seeing lately?
Honestly, it can be really frustrating at times.. luckily the scripts we have in place make weeding out ~80% of these jokers quite easy and quick. Heck, we had one scammer who blew through 12+ accounts over the last few days trying to scam people but none of their posts ever saw the light of day thanks to the spam triggers I've written.
What motivates the mod team to keep this place clean? That's an easy answer: The majority of users here are new to trading. Making sure they aren't food for the wolves is important.
But even with all the measures we take, some bad actors still get through.
So here's where you can help: Use the report button! Anytime you see something that you think fits the descriptions listed above, or violates our sidebar rules, just report it. Even if you're not 100% sure, don't be afraid to use the report tool.. The worst thing that can happen is the mod team reviews and approves it, but the best outcome is you directly help keep this place clean and humming! :)
And the mod team is always looking to improve where it can: I've already talked about what we do to scrub away bad actors, but one place we could do better is education. The plan is to rewrite a good portion of the wiki to include the following sections:
(Titles above are a work in progress ;P)
Are you a good writer and want to help out with this? Think you can write up a killer wiki article on spotting scam artists? Message the mods and let us know!
Finally, a reminder, we are still interested in taking on more moderators and will be revisiting that very shortly. If you'd be interested, read through this post and reply accordingly: https://www.reddit.com/Forex/comments/h7ok6k/seeking_more_mods_recruitment_thread/
submitted by finance_student to Forex [link] [comments]

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
Moving on:
The exact mechanism of drain, or transfers from India to Britain was quite simple.
Convenient.
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.
- Chandra et al. (1989)
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.
Dewey (1978) points out reliability issues with Indian agriculutural statistics, however this calorie decline persists to this day. Some of it is attributed to less food being consumed at home Smith (2015), a lower infectious disease burden Duh & Spears (2016) and diversified diets Vankatesh et al. (2016).
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.
A view echoed in Raychaudhuri (1983):
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 see Rajan 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.
or see Bryant 2000:
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'.

Bibliography

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
submitted by GaslightEveryone to u/GaslightEveryone [link] [comments]

Forex Daily Review: US Economic Data to hint on the QE Trigger

This article gives an update on, how the US Federal Reserve could start printing more dollars, which would have the effect of devaluing the currency. This follows the weaker than expected employment data from March. Also included is a technical observation of the AUD/CAD pair.
submitted by jomarreyes to Forex [link] [comments]

Review: US Forex Traders dedicated: eToro

submitted by xavierus911 to reddit.com [link] [comments]

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First, fill out the quick online form with a few questions with regards to your trading experience than by using our instant online verification to identity simple and effectively you are then able to fund your account and withdraw money anytime.
I have found that Bitorex believes in the highest standards and look to raise the bar every day. The team pledges to deliver the best service they can and use cutting edge technology to find solutions with a team of people who have integrity, impeccable values, and strive to achieve their optimal performance every day.
When choosing an online broker you need to find a company that values ethics and transparency to help build trust with clients and global markets. By always putting clients and partners first to deliver the value of money and finding new ways to understand and serve them in this industry.

Bitorex Trading Platform

Bitorex platform uses many assets that can be traded at the same time which offers major benefits because many trading platforms do not odder these features.
You can translate to different languages and use on all devices from your laptop, PC, Tablet, or smartphones. Trading and many options to choose from available to you where ever you are with cross-platform devices.
In conclusion, Bitorex is one of my favorite trading platforms when trading cryptocurrency and forex. Bitorex reviews was already featured on BusinessModuleHub and BusinessCaseStudies.co.uk
So easy to build experience and user friendly and no fees, unlike its competitors. A massive range of educational resources to enable you to take your trading experience to the next level and see results fast.
Bitorex is flawlessly designed and a must for any trader.
Get on board today!
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The Next Crypto Wave: The Rise of Stablecoins and its Entry to the U.S. Dollar Market

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.

Institutional Developments

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.

Future Opportunities

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:
[1] How the US dollar became the world’s reserve currency, Investopedia
[2] The dollar is in high demand, prone to dangerous appreciation, The Economist
[3] Dollar dominance in trade and finance, Gita Gopinath
[4] Global trades dependence on dollars, The Economist & IMF working papers
[5] Total credit to non-bank borrowers by currency of denomination, BIS
[6] Biggest stock exchanges in the world, Business Insider
[7] McKinsey Global Private Market Review 2020, McKinsey & Company
[8] Central banks current interest rates, Global Rates
[9] Venezuela hyperinflation hits 10 million percent, CNBC
[10] Lebanon inflation crisis, Reuters
[11] Venezuela cryptocurrency market, Chainalysis
[12] The most used cryptocurrency isn’t Bitcoin, Bloomberg
[13] Trading volume of all crypto assets, coinmarketcap.com
[14] Tether US dollar peg is no longer credible, Forbes
[15] New crypto derivatives let you bet on (or against) Tether’s solvency, Coindesk
[16] Remittance Price Worldwide, The World Bank
[17] Interbank Information Network, J.P. Morgan
[18] Jamie Dimon interview, CBS News
[19] Rise of the central bank digital currency, BIS
[20] Speech by Andrew Bailey, 3 September 2020, Bank of England
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Copy trading with eToro: impressions, doubts and (ignored) lessons

(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:
My observations and thoughts are as follows:
  1. 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)
  2. 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)

OlivierDanvel (Olivier Jean Andre Danvel)

rayvahey (Raymond Noel Vahey)
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:

Disclosures:
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Forex Binary Options - Trading strategies and broker reviews for US traders

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Funding transferwise thru Peso Debit Mastercard

Hi there, just want to pool some reviews if anyone had an experience with this?
I verified my USD wallet (Multi-currency account) thru my payroll debit card - SecB for $20.
I got credited 979.48 pesos which is surprisingly low, not that I'm mad about it. just curious because people here attest to having as high as 8% of total fees for the conversion cost?
It also boggles me because SecB's USD selling rate today was 49.15 but mine was converted at 48.97.
Can anyone share their experience below as well? TIA!
Edit: Figured out using a mastercard currency converter that SecB didn't impose any bank fees for the forex conversion, what a time to be alive! https://imgur.com/ouItyMT https://imgur.com/DZznMip
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Fueling The Us Economy's Middle Market Growth Engine

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Stifel Employee Reviews

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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.

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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.
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BEST FOREX BROKERS 2020  TOP 8 HOTTEST 🔥 FOREX BROKERS ... Best Forex Broker For Americans - Top Recommendation Forex.com Review by FX Empire - YouTube Forex Reviews - YouTube TOP 100 forex scam brokers 2019 - YouTube

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