Barclays, RBS and other banks face £1bn forex rigging lawsuit
Barclays, RBS and three other banks are being sued by investors for at least £1 billion over rigging of the foreign exchange market in a test case for US-style class actions in the UK, according to The Guardian. Barclays has been one of the banks subjected to the lawsuit A US law firm that specialises in stock market litigation has filed the claim at the Competition Appeal Tribunal. The claim also targets US investment banks JP Morgan and Citigroup, and Switzerland’s UBS. The legal action follows the European commission’s decision in May to fine five banks more than €1 billion (£910 million) for colluding to reduce competition in markets for 11 currencies, including the US dollar, the euro and the pound. Cartels of traders with names such as the ‘Three-Way Banana Split’ operated on chatrooms to rig the multi-trillion-dollar foreign exchange market. UBS, which informed the commission about the collusion, was not fined but Japan’s MUFG received a penalty. Scott + Scott, the law firm representing the investors, said Barclays, RBS, JP Morgan, Citi and UBS had been fined more than $8.5 billion by regulators globally over foreign exchange manipulation. The firm secured more than $2.3 billion compensation in a US class action suit from banks including Barclays, RBS, UBS and Deutsche Bank. The claim, led by Michael O’Higgins, the former chair of the Pensions Regulator, seeks compensation for investors and companies allegedly damaged by the banks’ actions. O’Higgins has instructed Scott + Scott to carry out work on the case. “Just as compensation has been won in the US, our legal action in the UK will seek to return hundreds of millions of pounds to pension funds and other corporates who were targeted by the cartel,” O’Higgins tells The Guardian. Under a class action a judge rules that all similar claimants will be included in the same claim, reducing litigation costs and sharing damages between claimants who might not have been able to afford to bring their own case. Until the 2015 law change, English law allowed opt-in collective actions, which made assembling a claim far more difficult and costly. The new regime has so far failed to get off the ground because of disagreements about the eligibility of claims. The value of the claim against the banks will depend on the number of foreign exchange trades carried out in London for UK-based operations and is likely to exceed £1 billion, notes O’Higgins. * More Details Here
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.
Helloww So my MLM friend who will never stop moaning about "this is it" in the mlm world is high from a new company called cashfx Their biz model is basically sign up and give all your money to them and boom they will get your invested money growing by 5-15 pct per month trading forex. But! They claim to have high-end trading office in RBS tower in Panama City. I've tried to google streetview it and yes the RBS tower is there but I would loooove to see that they only have a postbox on the wall and no office lol, anyone in Panama that could pop by?
The majority of this sub is focused on technical analysis. I regularly ridicule such "tea leaf readers" and advocate for trading based on fundamentals and economic news instead, so I figured I should take the time to write up something on how exactly you can trade economic news releases. This post is long as balls so I won't be upset if you get bored and go back to your drooping dick patterns or whatever.
How economic news is released
First, it helps to know how economic news is compiled and released. Let's take Initial Jobless Claims, the number of initial claims for unemployment benefits around the United States from Sunday through Saturday. Initial in this context means the first claim for benefits made by an individual during a particular stretch of unemployment. The Initial Jobless Claims figure appears in the Department of Labor's Unemployment Insurance Weekly Claims Report, which compiles information from all of the per-state departments that report to the DOL during the week. A typical number is between 100k and 250k and it can vary quite significantly week-to-week. The Unemployment Insurance Weekly Claims Report contains data that lags 5 days behind. For example, the Report issued on Thursday March 26th 2020 contained data about the week ending on Saturday March 21st 2020. In the days leading up to the Report, financial companies will survey economists and run complicated mathematical models to forecast the upcoming Initial Jobless Claims figure. The results of surveyed experts is called the "consensus"; specific companies, experts, and websites will also provide their own forecasts. Different companies will release different consensuses. Usually they are pretty close (within 2-3k), but for last week's record-high Initial Jobless Claims the reported consensuses varied by up to 1M! In other words, there was essentially no consensus. The Unemployment Insurance Weekly Claims Report is released each Thursday morning at exactly 8:30 AM ET. (On Thanksgiving the Report is released on Wednesday instead.) Media representatives gather at the Frances Perkins Building in Washington DC and are admitted to the "lockup" at 8:00 AM ET. In order to be admitted to the lockup you have to be a credentialed member of a media organization that has signed the DOL lockup agreement. The lockup room is small so there is a limited number of spots. No phones are allowed. Reporters bring their laptops and connect to a local network; there is a master switch on the wall that prevents/enables Internet connectivity on this network. Once the doors are closed the Unemployment Insurance Weekly Claims Report is distributed, with a heading that announces it is "embargoed" (not to be released) prior to 8:30 AM. Reporters type up their analyses of the report, including extracting key figures like Initial Jobless Claims. They load their write-ups into their companies' software, which prepares to send it out as soon as Internet is enabled. At 8:30 AM the DOL representative in the room flips the wall switch and all of the laptops are connected to the Internet, releasing their write-ups to their companies and on to their companies' partners. Many of those media companies have externally accessible APIs for distributing news. Media aggregators and squawk services (like RanSquawk and TradeTheNews) subscribe to all of these different APIs and then redistribute the key economic figures from the Report to their own subscribers within one second after Internet is enabled in the DOL lockup. Some squawk services are text-based while others are audio-based. FinancialJuice.com provides a free audio squawk service; internally they have a paid subscription to a professional squawk service and they simply read out the latest headlines to their own listeners, subsidized by ads on the site. I've been using it for 4 months now and have been pretty happy. It usually lags behind the official release times by 1-2 seconds and occasionally they verbally flub the numbers or stutter and have to repeat, but you can't beat the price! Important - I’m not affiliated with FinancialJuice and I’m not advocating that you use them over any other squawk. If you use them and they misspeak a number and you lose all your money don’t blame me. If anybody has any other free alternatives please share them!
How the news affects forex markets
Institutional forex traders subscribe to these squawk services and use custom software to consume the emerging data programmatically and then automatically initiate trades based on the perceived change to the fundamentals that the figures represent. It's important to note that every institution will have "priced in" their own forecasted figures well in advance of an actual news release. Forecasts and consensuses all come out at different times in the days leading up to a news release, so by the time the news drops everybody is really only looking for an unexpected result. You can't really know what any given institution expects the value to be, but unless someone has inside information you can pretty much assume that the market has collectively priced in the experts' consensus. When the news comes out, institutions will trade based on the difference between the actual and their forecast. Sometimes the news reflects a real change to the fundamentals with an economic effect that will change the demand for a currency, like an interest rate decision. However, in the case of the Initial Jobless Claims figure, which is a backwards-looking metric, trading is really just self-fulfilling speculation that market participants will buy dollars when unemployment is low and sell dollars when unemployment is high. Generally speaking, news that reflects a real economic shift has a bigger effect than news that only matters to speculators. Massive and extremely fast news-based trades happen within tenths of a second on the ECNs on which institutional traders are participants. Over the next few seconds the resulting price changes trickle down to retail traders. Some economic news, like Non Farm Payroll Employment, has an effect that can last minutes to hours as "slow money" follows behind on the trend created by the "fast money". Other news, like Initial Jobless Claims, has a short impact that trails off within a couple minutes and is subsequently dwarfed by the usual pseudorandom movements in the market. The bigger the difference between actual and consensus, the bigger the effect on any given currency pair. Since economic news releases generally relate to a single currency, the biggest and most easily predicted effects are seen on pairs where one currency is directly effected and the other is not affected at all. Personally I trade USD/JPY because the time difference between the US and Japan ensures that no news will be coming out of Japan at the same time that economic news is being released in the US. Before deciding to trade any particular news release you should measure the historical correlation between the release (specifically, the difference between actual and consensus) and the resulting short-term change in the currency pair. Historical data for various news releases (along with historical consensus data) is readily available. You can pay to get it exported into Excel or whatever, or you can scroll through it for free on websites like TradingEconomics.com. Let's look at two examples: Initial Jobless Claims and Non Farm Payroll Employment (NFP). I collected historical consensuses and actuals for these releases from January 2018 through the present, measured the "surprise" difference for each, and then correlated that to short-term changes in USD/JPY at the time of release using 5 second candles. I omitted any releases that occurred simultaneously as another major release. For example, occasionally the monthly Initial Jobless Claims comes out at the exact same time as the monthly Balance of Trade figure, which is a more significant economic indicator and can be expected to dwarf the effect of the Unemployment Insurance Weekly Claims Report. USD/JPY correlation with Initial Jobless Claims (2018 - present) USD/JPY correlation with Non Farm Payrolls (2018 - present) The horizontal axes on these charts is the duration (in seconds) after the news release over which correlation was calculated. The vertical axis is the Pearson correlation coefficient: +1 means that the change in USD/JPY over that duration was perfectly linearly correlated to the "surprise" in the releases; -1 means that the change in USD/JPY was perfectly linearly correlated but in the opposite direction, and 0 means that there is no correlation at all. For Initial Jobless Claims you can see that for the first 30 seconds USD/JPY is strongly negatively correlated with the difference between consensus and actual jobless claims. That is, fewer-than-forecast jobless claims (fewer newly unemployed people than expected) strengthens the dollar and greater-than-forecast jobless claims (more newly unemployed people than expected) weakens the dollar. Correlation then trails off and changes to a moderate/weak positive correlation. I interpret this as algorithms "buying the dip" and vice versa, but I don't know for sure. From this chart it appears that you could profit by opening a trade for 15 seconds (duration with strongest correlation) that is long USD/JPY when Initial Jobless Claims is lower than the consensus and short USD/JPY when Initial Jobless Claims is higher than expected. The chart for Non Farm Payroll looks very different. Correlation is positive (higher-than-expected payrolls strengthen the dollar and lower-than-expected payrolls weaken the dollar) and peaks at around 45 seconds, then slowly decreases as time goes on. This implies that price changes due to NFP are quite significant relative to background noise and "stick" even as normal fluctuations pick back up. I wanted to show an example of what the USD/JPY S5 chart looks like when an "uncontested" (no other major simultaneously news release) Initial Jobless Claims and NFP drops, but unfortunately my broker's charts only go back a week. (I can pull historical data going back years through the API but to make it into a pretty chart would be a bit of work.) If anybody can get a 5-second chart of USD/JPY at March 19, 2020, UTC 12:30 and/or at February 7, 2020, UTC 13:30 let me know and I'll add it here.
So without too much effort we determined that (1) USD/JPY is strongly negatively correlated with the Initial Jobless Claims figure for the first 15 seconds after the release of the Unemployment Insurance Weekly Claims Report (when no other major news is being released) and also that (2) USD/JPY is strongly positively correlated with the Non Farms Payroll figure for the first 45 seconds after the release of the Employment Situation report. Before you can assume you can profit off the news you have to backtest and consider three important parameters. Entry speed: How quickly can you realistically enter the trade? The correlation performed above was measured from the exact moment the news was released, but realistically if you've got your finger on the trigger and your ear to the squawk it will take a few seconds to hit "Buy" or "Sell" and confirm. If 90% of the price move happens in the first second you're SOL. For back-testing purposes I assume a 5 second delay. In practice I use custom software that opens a trade with one click, and I can reliably enter a trade within 2-3 seconds after the news drops, using the FinancialJuice free squawk. Minimum surprise: Should you trade every release or can you do better by only trading those with a big enough "surprise" factor? Backtesting will tell you whether being more selective is better long-term or not. Hold time: The optimal time to hold the trade is not necessarily the same as the time of maximum correlation. That's a good starting point but it's not necessarily the best number. Backtesting each possible hold time will let you find the best one. The spread: When you're only holding a position open for 30 seconds, the spread will kill you. The correlations performed above used the midpoint price, but in reality you have to buy at the ask and sell at the bid. Brokers aren't stupid and the moment volume on the ECN jumps they will widen the spread for their retail customers. The only way to determine if the news-driven price movements reliably overcome the spread is to backtest. Stops: Personally I don't use stops, neither take-profit nor stop-loss, since I'm automatically closing the trade after a fixed (and very short) amount of time. Additionally, brokers have a minimum stop distance; the profits from scalping the news are so slim that even the nearest stops they allow will generally not get triggered. I backtested trading these two news releases (since 2018), using a 5 second entry delay, real historical spreads, and no stops, cycling through different "surprise" thresholds and hold times to find the combination that returns the highest net profit. It's important to maximize net profit, not expected value per trade, so you don't over-optimize and reduce the total number of trades taken to one single profitable trade. If you want to get fancy you can set up a custom metric that combines number of trades, expected value, and drawdown into a single score to be maximized. For the Initial Jobless Claims figure I found that the best combination is to hold trades open for 25 seconds (that is, open at 5 seconds elapsed and hold until 30 seconds elapsed) and only trade when the difference between consensus and actual is 7k or higher. That leads to 30 trades taken since 2018 and an expected return of... drumroll please... -0.0093 yen per unit per trade. Yep, that's a loss of approx. $8.63 per lot. Disappointing right? That's the spread and that's why you have to backtest. Even though the release of the Unemployment Insurance Weekly Claims Report has a strong correlation with movement in USD/JPY, it's simply not something that a retail trader can profit from. Let's turn to the NFP. There I found that the best combination is to hold trades open for 75 seconds (that is, open at 5 seconds elapsed and hold until 80 seconds elapsed) and trade every single NFP (no minimum "surprise" threshold). That leads to 20 trades taken since 2018 and an expected return of... drumroll please... +0.1306 yen per unit per trade. That's a profit of approx. $121.25 per lot. Not bad for 75 seconds of work! That's a +6% ROI at 50x leverage.
Make it real
If you want to do this for realsies, you need to run these numbers for all of the major economic news releases. Markit Manufacturing PMI, Factory Orders MoM, Trade Balance, PPI MoM, Export and Import Prices, Michigan Consumer Sentiment, Retail Sales MoM, Industrial Production MoM, you get the idea. You keep a list of all of the releases you want to trade, when they are released, and the ideal hold time and "surprise" threshold. A few minutes before the prescribed release time you open up your broker's software, turn on your squawk, maybe jot a few notes about consensuses and model forecasts, and get your finger on the button. At the moment you hear the release you open the trade in the correct direction, hold it (without looking at the chart!) for the required amount of time, then close it and go on with your day. Some benefits of trading this way: * Most major economic releases come out at either 8:30 AM ET or 10:00 AM ET, and then you're done for the day. * It's easily backtestable. You can look back at the numbers and see exactly what to expect your return to be. * It's fun! Packing your trading into 30 seconds and knowing that institutions are moving billions of dollars around as fast as they can based on the exact same news you just read is thrilling. * You can wow your friends by saying things like "The St. Louis Fed had some interesting remarks on consumer spending in the latest Beige Book." * No crayons involved. Some downsides: * It's tricky to be fast enough without writing custom software. Some broker software is very slow and requires multiple dialog boxes before a position is opened, which won't cut it. * The profits are very slim, you're not going to impress your instagram followers to join your expensive trade copying service with your 30-second twice-weekly trades. * Any friends you might wow with your boring-ass economic talking points are themselves the most boring people in the world. I hope you enjoyed this long as fuck post and you give trading economic news a try!
A Short Story that Describes Imaginary Events and People of Worldwide Calamities and the Aftermath (the 2nd Edition)
The following story, all names, characters, and incidents portrayed in this post are fictitious. No identification with actual persons (living or deceased), places, buildings, and products is intended or should be inferred. However, the LINKS to real-life events and inspiring sources are placed here and there throughout the story. -------- Truth is the Only Light -------- INTRO ☞ [As of 2019] there are plenty of reasons to think the Chinese system will implode spectacularly without Japanese feeling the need to do a thing. — Peter Zaihan, Disunited Nations (Mar 03, 2020) It's apparent that two nations have been engaged in a high-stakes military & economy arms race. The current US admin has been hitting China with waves of tariffs, but that was merely a small part of what's actually going on.         On Oct 11, 2019, when they reached a tentative agreement for the first phase of a trade deal, the fact that China made the concession actually made my jaw drop. From where I sit, it was a worrisome scene. Aren't people saying, when challenging situations are bottled up, they will just grow and mutate into another terrible complications? Admittedly I was not certain how they are going to adhere to the agreement: It left most of the US tariffs (on China's exports) in place, and at the same time, came with an additional USD $200 Billion burden for China over the next two years. This agreement might seem a bit insignificant, but now China would need to purchase almost twice the size of the US products & services they did before the trade war began. With their current economic climate? I murmured, "No way." While watching Trump brag and boast around with said agreement, I expected China would soon come out and fling some improvised excuses in order to delay the document-signing process. It wouldn't be their first time. More importantly, even if China does so, there wouldn't be many (real) counterattack options left for the Trump admin during this year, the US presidential election year. Then, on Jan 16, 2020, the world’s two largest economies actually signed a partial trade agreement aimed at putting the brakes on an 18-month trade war. China would almost surely not sit down but come back to bite, I thought. Enter the worldwide chaos following so called the COVID-19 outbreak. -------- BACKGROUND ☞ Globalists have been heavily investing in China's economy and its components overseas. • Here are a couple of well known names: the Great Old One; George Soros; Koos Bekker; and Bill Gates. • For the sake of convenience, from here on, let's call these globalists, who are foreign investors in China's top tier state-owned/sponsored/controlled enterprises, Team-Z. • Team-Z has adopted big time lackeys like Henry Kissinger or small time ones like Larry Summers, Stephen Hadley, or Bill Browder as matchmakers to court Team-Z for China's top tier enterprises. When Israel's highest echelons chimed in, it has been through Israeli IT companies and the BRI projects. • Naturally, multinational investment banks have also been employed; such as Morgan Stanley, Goldman Sachs, Royal Bank of Scotland (RBS), UBS Group AG (formerly Union Bank of Switzerland), Blackstone Group, Canaccord Genuity, BlackRock, Hermitage, or Mirae Asset. ☞ Note: The Great Old One didn't use any matchmakers, something peasants would need. Because the Great Old One's power level is over 9000. • China's Shanghai clique used to keep the nation's state-sponsored enterprises under their firm grip: Enterprises such as Alibaba Group, Tencent, Baidu, Wanda Group, HNA Group, Anbang Group, Evergrande Group, CEFC Energy and Huawei, all of which Team-Z has massively invested in. • Here is how Shanghai clique and Team-Z, esp. Bill Gates, started to get together:[LINK] • However, in the name of anti-corruption campaign, Xi Jinping & his Princelings have been taking those businesses away from Shanghai clique's hand, and transforming those state-sponsored private enterprises into the state-owned enterprises, declaring the 國進民退 movement. • Slaying Shanghai clique's control =       • 國進民退 + Slaying Shanghai clique's control = [A] [B] [C] • Xi's reign didn't arrive today without challenges though: the BRI projects' poor outcome has frustrated Israel's great expectations. And since the US-China trade war has started, the problems of China's economic systems started to surface, not to mention China's economy has long been decaying. • Coupled with the US-China trade war, the current US admin has been trying to block Huawei from accessing the international financial systems that the US can influence, as well as the US banking systems. This is a good time to remind you again that Bill Gates has had a very close-knit relationship with Huawei. -------- TRADE WAR & INTERNET-BASED COMPANIES ☞ It's the trade war, but why were internet-based companies such as Tencent and Baidu suffering losses? Answer: The state-sponsored companies like Tencent, Baidu, or Huawei have heavily invested in international trade and commodity markets, which are easily influenced by aspects that IMF interest rates, the US sanctions, or trade war can create. Example: Let's say, Tencent invests in a Tehran-based ride-hailing company. Then, through said ride-hailing company, Tencent invests in Iran's petroleum industry. Now, China's most valuable IT company is in international petrochemical trade. The business is going to make great strides until the US imposes trade embargoes oand economic sanctions against Iran. -------- TL;DR China's economy going down = Team-Z losing an astronomical amount of money. ★ Wednesday, Sep 26, 2018 ★ "Gentlemen, you guys might want to do something before it's too bloody late, no? Hisspeechlast night was .... (sniggers) Mr. Gates, now is as good a time as any. Mr.Soros, hm, don't look at melikethat." ".... But," "Yes, Mr. Soros, yourHNAis going down, too. .... Ah,Schwarzmanxiansheng, we're very sorry to learn about Blackstone'sIran&SinopecChinasituation. So, we're guessing, you'd be happy to join Mr. Gates's operation, yes? Of course, We already contactedKissingerxiansheng. ....Okaythen,Gentlemen?" • Now you can take a guess why George Soros has recently been sending out confusing messages regarding Xi Jinping. • Wait, how about Wuhan Institute of Virology? Doesn't this story concern the COVID-19 outbreak? Is the Wuhan Institute also associated with Shanghai clique? Yes, indeed. Here's How Wuhan Institute of Virology and Shanghai Clique are related:[LINK] -------- EIGHT OBJECTIVES ☞ Calling for the tide to be turned, Team-Z and Shanghai clique started to devise the plan. The objectives are: ① By shutting down international trade, crashing world economy, and exploiting its aftermath, the plan should produce an outcome letting Team-Z earn back their loss from the trade war & the US sanctions, and collect additional profits from China's BRI projects & stock markets worldwide, including the US stock markets. • Don't forget this: This point number ① also concerns the developing nations on the BRI with the large deposits of natural resources that Team-Z has invested in through China. If everything comes together nicely, Team-Z will pick up trillions of dollars from those nations alone as if they are light as a feather. Ironically this will reinforce the BRI project governance and mitigate fraud & corruption risks inherent to the international development projects. ② By utilizing the aftermath in the US, a new US administration consisted of pro-Beijing personnels should be fostered at the 2020 election. In a worst-case scenario, the aftermath should be abused enough to make Robert Lighthizer to leave the admin. Mr. Mnuchin could stay. ③ Sometime next year, the phase one trade deal must be reassessed with the new US admin. The reassessment should help China take the upper-hand at the second phase trade talk. ④ The pandemic crisis should yield a situation which allows China to delay the payments for its state-firm offshore debts. With the point number ①, this will give China a breathing room to manage its steadily-fallen forex reserves. ⑤ Since their current turf (in China) is education industry & medical science industry, Shanghai clique will have no issue with earning hefty profits by managing China's export of medical equipments & health care products which can be supplied worldwide mainly by China. People in the west will bent the knees for the clique's support. ☞ Regarding Jiang Zemin's son and medical science industry in China [LINK] ⑥ The outcome should weaken Xi & his Princelings' political power considerably in favour of Shanghai clique & Team-Z. This will let Jiang's Shanghai clique (A) reclaim some of political status & business interest controls they have lost to Xi & his Princelings. • And once this point number ⑥, with the point number ② , is realized, it would be much easier for the clique to (B) recover their huge assets hidden overseas that the current US admin or Xi & his Princelings have frozen. ⑦ Combining good old bribery with sex, the outcome should support China to re-secure control over the US governors. Once the plan is executed successfully, those governors would desperately need solutions to local economic problems and unemployment. ⑧ Lastly, implementing an e-ID system in the US similar to Beijing's Alipay and WeChat could be the cherry on top of the operation's entire outcomes. Who's supporting such a system worldwide? None other than Microsoft and Rockefeller Foundation. ಠ_ಠ -------- OLD COMRADE BECOMES A NEW RECRUIT ☞ They were afraid more talents were needed. The main target was the world’s largest economy with the most powerful military capability, after all. They ended up asking Mr. Fridman to see Lord Putin about that. The old Vova was going through a lot nowadays, people said. It could be because his nation's energy business to Europeseems to be hitting wall after wall. He is said to have enough on his plate with no end in sight, so maybe he'll join. ★ Monday, Jan 15, 2018 ★ "(pours a drink for himself) I know, but. ... What would happen if Bashar falls? How long you think you can keep it up? .... Erdogan is many things (sniggers) but he's nevergentle. (sips his drink slowly) WhenBenji'sEastMed Pipeline starts to actively compete, then what? They got the Chinamoneynow. ....Vagitand his buddies will be very unhappy. You know that. Not great, Vova." "...." "Ah, you mean what are we going to do? Hm? Hm. I'll tell you what we're going to do. This time, we're going to bankrupt the US shale gas sector. Then, of course, we can maybe convince Benji to take their time with the pipeline. Perhaps for good. (sips his drink slowly) Don't worry, Vova, It'll work. You worry too much. We'll come out the other side stronger." "So, how long until they set it off? "Hahaa, yes. They'll soon put all things in place. While marching in place, they'll play the tune a couple of months before the next sochelnik." "Nearly 20 months to brace things here, then?" "(nod slowly in happiness) Hm. Оторви́сь там, оттопы́рься, Vova" -------- USEFUL IDIOTS ☞ When the directive came, these idiots answered claiming they would be gladly "on it." All in the name of rejuvenating China's economy without grasping the real objective prevailing throughout the entire operation. Thing is, they would never realize what they are to Team-Z & their Asian overlord until it’s too late. Who are they? It's A and B, not A or B: (A) the American corporations that are too big to fail and have suffered a considerable loss because of the US-China trade war. Among those corporations, (B) the ones that have been structured with massive interest-profit relationships in/with China. "We need China in order for the US as a nation to continue being prosper," they've been shouting. No surprise there, because they've enjoyed the strides of extraordinary profits over the years while the US middle class has continued to shrink. But, in 2019 when China's stock markets nosedived for the first time since 2015 and China's authorities in financial stability & resiliency fumbled their response; it wiped that smile off their face. Still, they'll keep behaving not to offend their Asian overlord, nonetheless. -------- PERFECT PLAN ☞ Many crucial components had to come into play all at once in order to cause World War I. If one of the components were missing or different, it is unlikely that the World War I as we know of could be produced. ① The US in 2019: Overbought bubbles + Over borrowed corporations ② The US in 2020: It's an Election Year. ③ Russia has been dumping US Treasuries for the past few years. ④ Russia has been hoarding golds as if they were recreating Inca Empire. ⑤ China in 2019: Immense & long term financial troubles has started to surface. ⑥ China in 2020: The phase-one deal has been signed; leaving most of tariffs on China intact and adding another $200 Billion burden for China. ⑦ Team-Z sets up a situation in the US where some event(s) would freeze the US supply chains & demand for the next three to ten months. • Just like the 9/11, the event will be initiated at the clique's own region. However, unlike in China, the US will report multiple epicentres simultaneously. • And the CDC and the US medical task force will carry on with a number of sabotage acts, to secure enough time for the infected yet untested in those US epicentres to spread plenty.    • Here's a feasible timeline of the operation. ⑧ Then, the BOOM: Team-Z (a) manipulates the markets to make sure MM will have liquidity concerns (b) when they need it most. The (c) bottomed out oil price will be an enforcement, which will also wreck the US energy sector as a kicker. The (d) WHO will also join as a disinformation campaign office. • Then a couple of big name investment managers will lead a movement that (will try to) bring back foreign money back to China.   • Meanwhile, in US, the disinformation campaign will continue to be pushed until the second wave of attack arrives. -------- MEASURABLE SHORT-TERM OUTCOME ☞ We're now going through World War III. The global structure laid down by World War II had been shaken by globalization and the rise of China. This pandemic event will shock the structure further. Human history will be divided into Before 2021 and After 2021. ① Outcome pt. 1: Immediate Aftermath [pt.1] [pt.2] ② Outcome pt. 2: The US economy goes deep dive along with world economy, and the only thing Team-Z has to do is to exploit the aftermath which has been thoroughly calculated and eagerly anticipated. — Favoured assessment: There won't be a V curve ever, unless drastic measures taken within the timeframe of four months. Unprecedented market crash, the rapid unemployment acceleration because of the supply-chain shut down, and the near-death security which in turn forces consumer confidence to plummet. We're looking at a super long L shape curve unless the US prepares fast for the second wave of their asymmetric warfare. ③ Outcome pt. 3: Arguably the most important outcome. — Because of the unprecedented shutdown of international trade, the nations heavily rely on exporting natural resources will face the extreme financial threats. What if some of those are emerging markets AND massively in debt to China? What do you think China would do to said nations while the aftermath is hitting the globe hard? [PDF] Something comparable to Latin American Debt Crisis will happen. ④ Outcome pt. 4: Not that significant compared to the others but still notable outcome. — The world will need Shanghai clique's help to get medical products and equipments. -------- WHAT'S NEXT? ☞ Several analysts have discussed off the record that next it'd be a proxy warfare not using armed conflicts but with spreading a galaxy of counterfeit-currency across every possible channels. Coincidently, on Dec 13, 2017, Business Insider reported in an article "A $100 counterfeit 'supernote' found in South Korea could have been made in North Korea" that:
"It was the first of a new kind of supernote ever found in the world," Lee Ho-Joong, head of KEB Hana Bank's anti-counterfeit centre told Agence France-Presse.
Reporting the same news, The Telegraph published an article on Dec 11, 2017:
"It seems that whoever printed these supernotes has the facilities and high level of technology matching that of a government", said Lee Ho-jung, a bank spokesman from KEB Hana Bank in South Korea. "They are made with special ink that changes colour depending on the angle, patterned paper and Intaglio printing that gives texture to the surface of a note".
05-17 14:24 - 'This has been good so far' (self.Bitcoin) by /u/HeliusNeo removed from /r/Bitcoin within 0-8min
''' Guys, about a year ago, I found a company that is under the european regulation and they sell bots for forex and crypto. But there is something else: the option of using a community arbitrage bot. It has a limit of 5 Btc for person, because of the limitated volume of exchanges and the profits have been slowing down a little bit from 0.8%/day to an average of 0.45%/day, but still a good opportunity. I've been using this for a year and I made a 2x to my btc. So far it does not seem a ponzi at all, I want to know your opinions (better if you talk with a pre-research). In fact, the community bot is going to be shilded, and they will not allow new contributions, neither compounding. This is in order to get a sustainable growth. Bad that it is not for US citizens. You can sign up here: [link]1 ''' This has been good so far Go1dfish undelete link unreddit undelete link Author: HeliusNeo 1: ap*.*rb*star.c*m/signup/**A0DWS**H Unknown links are censored to prevent spreading illicit content.
[Event] Increasing fiscal transparency in the government and financial sector
Capacity Development Strategy for Rwanda
Forward-looking policy priorities will focus on improving fiscal transparency, domestic revenue collection, interest rate-based monetary policy framework, improving and harmonizing statistical reporting which includes real statistics, budget preparation, external sector statistics, and promoting private investment. Rwanda is a high-intensity Technical Assistance (TA) recipient with a good track record for use of IMF technical assistance. The authorities’ proven commitment/ownership mitigates risks, and future success will require continued close coordination between the authorities, TA providers, and the AFR team. In the most recent fiscal year, TA was provided for:
Tax policy: An initial mission to estimate and assess tax expenditures and a model-building workshop took place.
Revenue administration: A mission to improve the Integrity of Taxpayer Register took place; assistance with the Revenue forecasting tool was provided.
Public Financial Management: The blueprint on the move to accrual accounting was reviewed, with recommendations on phasing, defining intermediate milestone, and a monitoring system; cash management and budget execution missions.
Government Finance Statistics: Compilation and dissemination of high frequency fiscal and debt data and moving to GFS-2014 format reporting.
Data standardization: To improve adherence to the data standards initiative, an e-GDDS mission took place.
Real sector statistics: Refinements were made to quarterly indicators and quarterly GDP estimates.
Money and FX Market Operations: Further measures to facilitate the development of the repo market.
Financial sector supervision and regulation: The central bank received training on risk-based supervision and formalizing its macroprudential policy framework and strengthening Basel II implementations and corporate governance as well as supervisory framework for forex bureau sectors.
Rwanda will begin implementing Forward-Looking TA Agendas into action to further develop the country's economical infrastructure.
Improve Transparency of Government Spending
Fiscal Transparence Evaluation; improving frequency and coverage of fiscal and debt data, implementing GFS-2014 formal fiscal data, and development of IPSAS accounting manual and providing IPSAS training
Improve domestic revenue mobilization through reducing and better targeting exemptions and improving revenue administration core functions
Follouw up TA on tax expenditures, reviewing the integrity of the taxpayer reigster, strengthening tax audi capacity of telecommunications sector, devloping a domestic taxes department headquarters function with its process flow and staff roles and responsibilites, as well as evaluation of revised property tax law.
Enable comprehensive, credible, and policy based budget preparation
Developing a roadmap for the implementation of performance based budgeting throughout the government sector
Enhance the effectiveness of monetary policy implementation
Training on Forecasting and Policy Analysis (FPAS)
Enhance financial sector supervision
Assisting in implementing a risk based supervision (RBS) including for insurance companies, adopiting IFRS, enhanscing RBS for MFIs and SACCos, and implementing Basel II/III
Establish an effective macroprudential policy framework and reofm and develop national payment system
Enhancing macroprudential oversight of non-bank insurance companies and pension firms, enhancing oversight policy framework, and oversight training.
RBS’s key Q3 success was continued retail lending and deposit growth, whilst excluding a 50bp PPI hit, Tier 1 ratio at 15.7% portrays stable capital strength that keeps dividend plans on track, though not much better. New CEO Alison Rose, a 30-year RBS veteran, will be more familiar than most with where the remaining fat lies. RBS is the most sensitive bank in the UK to interest rates. Whilst NII is up 3% qoq, it is down 6% yoy. Conclusion: Whilst the RBS comeback story is playing out well, there remain significant headwinds from lower margins and Brexit related political uncertainty which could keep any recent gains capped. A row has broken out between a prominent City broker and Royal Bank of Scotland over the UK lender’s attempt to lure away lucrative foreign exchange clients. NatWest Markets, which houses the remnants of RBS’s once-sprawling investment bank, sent an email to a small number of JB Drax Honoré’s corporate clients last week pitching its full ... RBS, which is 79 per cent owned by the Government, launched an internal review into its forex activities after it was one of six major international banks fined a combined £2.6 billion last month ... Ex-RBS Forex Trader Still Not Sure Why He Was Fired. And he wants RBS thrown in jail. Author: Jon Shazar Updated: Jan 14, 2019 Original: Sep 30, 2015. As pure as the driven snow.
On 12 November 2014, we fined five banks - Citibank, HSBC, JPMorgan Chase, Royal Bank of Scotland and UBS - £1.1 billion for failing to control business practices in their G10 spot foreign ... Resistance Becomes Support and Support Becomes Resistance 8 videos Play all Trading Forex alex rio Webinar: Potret Rumah Sakit di Era New Normal - Duration: 2:57:01. Fakultas Kesehatan Masyarakat Universitas Airlangga 1,018 views Up Next: How do bankers trade forex? Part 2: Capital Management https://youtu.be/NDIByRE-qLQ Tap into 28 Years of experience in the Forex Market and find out... AUD/USD sell opurtunity 01-05-2010 fx-rbs forex simplified advisory.