USD/JPY: Live Chart, US Dollar – Japanischer Yen Prognose

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]

Emerging markets: Premature rally

BNP Paribas






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submitted by GiuliettaShop to Popify [link] [comments]

CMC Markets: is everything in CFDs? If so, how do the forward date ones work?

I just started a demo account with CMC Markets, and I was wondering if every single asset listed is traded as a CFD? When learning about forex from BabyPips I had the mentality as if I'm literally trading the currency; as in if it were in person, I'd be giving some coins in one currency and receiving another. I guess since CFDs are linear derivatives it doesn't matter as much, but I still feel like there are some additional considerations when trading CFDs vs "actual currency"? Also, what are the maturities on these? Are there even maturities? All the quotes just say "USD/CAD", "EUJPY" etc, but from my understanding of a CFD, you agree to pay the difference from actual and agreed, much like a future, so why are there no maturities?

Question 2: For CFDs on things like equity indices, they seem to trade the whole day unlike their underlying. Does this mean say at 9pm EST the S&P500 CFD is just people essentially betting on tomorrow's open? And again with the futures thing, does after-market hours trading in these CFDs affect the real opening price the next day? (If markets are efficient and we assume there are people watching CFD prices like future prices, and then tomorrow's early trades become based on what the futures markets seem to say about the S&P, holding news and other things constant).

Question 3: For CFDs with maturity dates like commodities on this platform, how does that work? Again, I'm mostly confused at how CFDs operate without maturities and how they different from futures. On the CMC markets platform, many agricultural commodities come with the suffixes like either "cash" or a maturity date, but currencies and equity indices do not. What does this mean? Those commodities I'm clicking trade on...am I trading a corn CFD? Or a CFD on corn futures? What exactly is the underlying mechanic?
Question 4: yet another example. For the bond indices...what am I looking at on the platform? I just want to get a chart of US treasury yields but I don't think that is available on CMC. What am I looking at when I click UK Gilt Cash or US T-Bond Cash or US T-Bond Jun 2020?

Tl;dr Don't understand the mechanics of CFDs and thus I'm not sure what EXACTLY I'm actually trading when I trade things like currency, equity indices, commodities. Surely I'm not actually trading a physical commodity or actual shares. Please note this is specific to CMC markets.
Thanks :)
submitted by fittyfive9 to Forex [link] [comments]

The GBP is the strongest and the EUR is the weakest as NA traders enter

The GBP is the strongest and the EUR is the weakest as NA traders enter. The GBP is the strongest, but the gains are relatively modest. THe USD is mixed in the morning snapshot with the greenback higher vs the EUR, JPY, CHF, CAD and down vs the GBP and AUD. It is unchanged vs the NZD. The volatility is down in the forex market. Each of the major currency pairs and crosses are trading well below their 22 day averages. The JPY pairs moved lower earlier in the day, but have rebounded with the GBPJPY leading the way (up 55 pips). The USDCAD has given up earlier gains and trades back toward unchanged on the day (up 14 pips after being up around 90 pips at the high)
submitted by Nelvid to Forex [link] [comments]

Saudi Oil Attack

Hey guys just seeing what your ideas are.
I only have a forex trading account. Trade on and off since 2011. Lifetime I’m in the green (or black?) but by no means close to professional.
Anyways JPY holiday I believe Monday.
I’m looking for CAD to have some buying pressure in some pairs.
CAD vs GBP, AUD, NZD, for example and maybe EUR.
I can see JPY and USD strength in most pairs for security with this risk. so hesitant on trading CAD here.
A lot of unknowns. How long oil disrupted. 3 days? 3weeks?
Houthi’s on their own. Iran directing houthis Directly Iran (I cant see this but never say never)
Also I am not a Middle East expert in the slightest.
submitted by wowthatssorude to Forex [link] [comments]

For Beginners: Stablecoins: Explaining what stablecoins are and why they’re so important for the cryptocurrency industry

For Beginners: Stablecoins: Explaining what stablecoins are and why they’re so important for the cryptocurrency industry

https://preview.redd.it/0rico0vtytz11.png?width=2970&format=png&auto=webp&s=492f4edb6a613249a68f6a97c3fc70eebcac23e9
With the seemingly endless amount of coins entering the market each year, we are beginning to see various categories of digital assets emerge. One of these classifications of coins is known as stablecoins, and although you may see it as ironic that a cryptocurrency is labeled as being “stable,” that’s actually exactly what they are known for. Stablecoins make up a unique category of coins in the market that are poised to bring stability and trust back into the cryptocurrency market. With that being said, let’s go over what stablecoins are and why they are so important for the development of the cryptocurrency industry as a whole.
This is not financial investment advice. This article will touch upon key aspects of what stablecoins are and why they can help the growth of the crypto industry.

Terminology

Blockchain: The easiest way to understand blockchain is to think of it as a fully transparent and continuously updated record of the exchange of information through a network of personal computers, a system which nobody fully owns. This makes it decentralized and extremely difficult for anyone to single-handedly hack or corrupt the system, pretty much guaranteeing full validity and trust in each exchange of information.
Volatility: The rate at which the price of a security increases or decreases for a given set of returns. Volatility is measured by calculating the standard deviation of the annualized returns over a given period of time. It shows the range to which the price of a security may increase or decrease.
Fiat: Currency that a government has declared to be legal tender, but it is not backed by a physical commodity. The value of fiat money is derived from the relationship between supply and demand rather than the value of the material from which the money is made.
Decentralization: Essentially, if something is centralized, there’s a single point that does all of the work involved in any given action. On the flip side, if something is decentralized, there are multiple points that do the work.
Familiarize yourself with these key terms in order to better understand what stablecoins are.

What Are Stablecoins?

To put it simply, stablecoins are cryptocurrencies that are pegged or backed by some other asset. Some forms of stablecoins are tied to assets such as the dollar or a commodity like a bar of gold or a barrel of oil. Other forms of stablecoins are backed by cryptocurrencies, or even exist as self-correcting, algorithmically-controlled systems. Essentially, stablecoins hold the promise of a half-step between traditional assets and crypto assets, taking the best from both worlds while resulting in a much more accessible and efficient form of finance.
The concept of having a stablecoin of stable currency isn’t new, as governments have been considering the implementation of this idea for quite some time now. National governments have the same motivation as crypto economies to deal in stable assets, as volatility in any kind of currency scheme can lead to wild speculation and boom and bust values. Historically, there have been a few different ways of implementing currency pegs at the national scale. Some countries just start using another country’s currency in lieu of their own as legal tender. Other governments have decided to set a fixed peg, while others determine an acceptable range and let their currency float within a range in relation to the peg.
Even within the cryptocurrency world, people have been experimenting, with mixed results, with stablecoin design and setup. Tether is one of the most prominent stablecoins, which is a blockchain-based cryptocurrency whose coins in circulation are backed by an equivalent amount of traditional fiat currencies, like the dollar, the euro or the Japanese yen, which are held in a designated bank account. Tether tokens, the native tokens of the Tether network, trade under the USDT symbol.
Stablecoins are cryptocurrencies that are backed by another asset, such as fiat money or another algorithmically-controlled system. This keeps the value of that coins stable and lowers the threat of high volatility.

How Can They Impact The Crypto industry?

By definition, stablecoins are inherently different than the rest of the cryptocurrencies in the industry, as their value is determined and derived differently. With all the criticism and skepticism surrounding the industry today, many people have pointed to stablecoins as being one of the biggest proponents in legitimizing the cryptocurrency market as a viable asset class.
Stablecoins could quickly become the universally accepted, international currency of the future. They have the potential to empower everyone to take part in an evolving crypto-economy, without compromising security and freedom. If implemented at scale, they are poised to become a foundational component of the next-generation economy. One of the biggest attacks against the cryptocurrency market is that the coins are too volatile and that they have no safe backing. Stablecoins solve both of those issues while still serving as a digital asset that can perpetuate excitement for the market as a whole.
Stablecoins solve the issue of volatility and lack of inherent value by having an actual asset which determines its value. At this point, they can serve as mediums of payment and monetary value while maintaining a stable price.

Conclusion

Sure, the cryptocurrency market may be filled with coins that are highly volatile and may not have the backing of inherently valuable assets, but what if there were coins that could satisfy all of these points? Well, with stablecoins, all of these issues are solved and the possibility of using these coins as mediums of payments becomes real. Imagine having the ability to use a cryptocurrency that is essentially valued the same as other widely-used assets like fiat money, oil, or even gold? The digital asset economy is quickly revolutionizing the world, so keep an eye out for this category of cryptocurrencies to one day become the future of the industry.
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Have you used stablecoins before? What are some of our favorite stablecoins in the market? Let us know why in the comments!
submitted by CoinBundle to coinbundle [link] [comments]

FXPA White Paper: Sources of FX Market Liquidity During the Brexit Vote

The (brief and simple) whitepaper offers a behind-the-scenes look at liquidity flows during the Brexit vote. This isn't a topic that has garnered much attention, given the spot market had fairly minimal dysfunction during Brexit, and the paper itself doesn't offer the same level of highly detailed insight into bank trader activities that the criminal trial of HSBC FX trader Mark Johnson did.
What it does contain though is a very peculiar pearl of information, through its analysis of bank vs non-bank flows during the unfolding of the event.
Over the sample window, banks were responsible for 66.6% of Cable flow, 67.25% of EUGBP flow, 64.9% of EUUSD flow, 64.1% of USD/JPY and 61.7% of EUJPY
compare this to:
The proportion of flow in GBP/JPY was wild – with non-bank participants in one hour responsible for 96% of flow and in another, just 9%.
That non-bank participants should completely dominate flows for that cross seems notable.
One contributing factor is highlighted earlier in the paper.
The non-bank proportion rose in EUGBP and EUJPY, but could be because the data suggest the non-banks are more active in crosses than the “legs”. Several of these firms construct a price in the cross using the legs and because their technology is often nimbler and quicker, they are top of book in the more complex pairs.
(Emphasis mine)
What does all this mean for your trading?
For most people, it means nothing at all, as most retail traders get no further than the chart as printed and a series of set criteria.
For traders who work with market feel, or the lower timeframes, it raises some interesting question about whether or not non-bank liquidity feels different from bank dominated markets.
Non-bank liquidity providers are certainly working with a different agenda, different tech, and different liquidity networks from banks. And whilst not necessarily behaving unethically, they are also less likely to have a prudential-oriented client focus - banks in theory are trying to get best price for clients without disrupting the market, non-bank actors don't necessarily operate by these principles.
They also are more likely to operate with different risk parameters - high turnover, 'hot potato' providers have less depth of pocket than banks, so perhaps there might be more churn and candle-wick-y-ness, especially on thinner liquidity networks.
This is very subjective, and speculative, of course, but that is the nature of the way some of us play the game!
Here is the direct download link for the full text: https://fxpa.org/wp-content/uploads/2017/10/FXPA-brexit1B-FINAL.pdf
(The FXPA is the Foreign Exchange Professionals Association, an industry group whose founders include Bloomberg, CME, ICE, State Street and Virtu. It's an organisational body, so does not take membership from individuals).
submitted by alotmorealots to Forex [link] [comments]

Japanese Yen Declines After Trade Figures Miss Expectations

This is an automatic summary, original reduced by 11%.
The Yen declined against the US Dollar following poor Japanese trade balance figures January's trade balance was - ¥1086.9b vs -¥625.9b expected and ¥640.4b previously February's FOMC minutes serve as top event risk for USD/JPY in the week ahead. See how retail traders are positioning in the majors using the DailyFX SSI readings on the sentiment page.
The Japanese Yen fell against the US Dollar as trade balance figures missed expectations.
The data showed the nation's trade balance for January was - ¥1086.9b versus -¥625.9b expected and ¥640.4b recorded in December.
While there was an initial USD/JPY climb, the excitement seemed to dwindle rather swiftly as these figures have limited implications for BOJ monetary policy.
With a rather quiet week ahead, the release of February's FOMC meeting minutes will serve as top event risk for the USD/JPY pair.
Learn forex trading with a free practice account and trading charts from IG. The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc..
Summary Source | FAQ | Theory | Feedback | Top five keywords: trade#1 balance#2 USD/JPY#3 figures#4 February's#5
Post found in /news and /worldnewshub.
NOTICE: This thread is for discussing the submission topic. Please do not discuss the concept of the autotldr bot here.
submitted by autotldr to autotldr [link] [comments]

Forex Technical Analysis: USD.JPY USD/JPY and AUD/USD Forecast April 20, 2020 How To Trade USD/JPY  Forex Trading Tips 👍 - YouTube Forex Technical Analysis: USD.JPY USD/JPY Technical Analysis for May 25, 2020 by FXEmpire USD/JPY and AUD/USD Forecast April 6, 2020

USD/JPY ist der Forex-Ticker, der den Wert des US-Dollar gegenüber dem Japanischen Yen angibt. Dollar - Yen ist eines der am häufigsten gehandelten Währungspaare – es nimmt direkt nach EUR ... The USD/JPY pair retains its bullish stance in the short-term, and according to the 4-hour chart. In the mentioned time-frame, it continues developing above all of its moving averages, with the 20 ... USD/JPY is the forex ticker that shows the value of the US Dollar against the Japanese Yen. It tells traders how many Yen are needed to buy a US Dollar. The Dollar-Yen is one of the most traded ... USD/JPY represents the amount of Japanese yen that can be purchased with one US dollar. At the time of the Breton Woods System the yen was fixed to the US dollar at 360JPY per 1USD, but the exchanged only lasted until the US abandoned the gold standard in 1971. Since then the yen has appreciated significantly against the US dollar. The yen is the third most traded currency in world, behind the ... USD/JPY represents the amount of Japanese yen that can be purchased with one US dollar. At the time of the Breton Woods System the yen was fixed to the US dollar at 360JPY per 1USD, but the exchanged only lasted until the US abandoned the gold standard in 1971. Since then the yen has appreciated significantly against the US dollar. The yen is the third most traded currency in world, behind the ... Source: Tradingview, FOREX.com. If you are looking to trade USD/JPY, you may want to watch the S&P 500! TAGS: Dollar FOMC Forex USD. Share: Disclaimer: The information on this web site is not targeted at the general public of any particular country. It is not intended for distribution to residents in any country where such distribution or use would contravene any local law or regulatory ... Statistically, only 11-25% of traders gain profit when trading Forex and CFDs. The remaining 74-89% of customers lose their investment. Invest in capital that is willing to expose such risks. Forex Brokers > Live Charts > USD JPY Live Chart . USD JPY Chart Exchange rate US Dollar vs Japanese Yen . Popular charts. Euro Dollar Live Chart; USD JPY Live Chart; USD CAD Live Chart; GBP JPY Live ...

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Forex Technical Analysis: USD.JPY

How to trade Forex: US Dollar vs. Japanese Yen This signal was sent to Team FXG on February 18th 2019 Visit www.forexgentleman.com to join for free with a 7 ... How To Trade USD/JPY Forex Trading Tips 👍 - Duration: 5:58. UKspreadbetting 15,477 views. 5:58 . EUR/USD and GBP/USD Forecast April 21, 2020 - Duration: 1:36. DailyForex 587 views. 1:36. The ... Trading the USD/JPY Currency Pair http://www.financial-spread-betting.com/forex/spread-betting-usd-jpy.html PLEASE LIKE AND SHARE THIS VIDEO SO WE CAN DO MOR... Live Forex Trading USD/JPY: Watch the Trade Start to Finish! 📈📉 - Duration: 10:02. TraderNick 7,468 views. 10:02. Investment & The Global Economy - Live Q&A - Duration: 1:05:56. ... USD/JPY Technical Analysis for April 02, 2020 by FXEmpire - Duration: 1:11. FX Empire 568 views. 1:11. Live Forex Trading USD/JPY: Watch the Trade Start to Finish! 📈📉 - Duration: 10:02. ... How to trade Forex: US Dollar vs. Yen This signal was sent to Team FXG on March 11th 2019 Visit www.forexgentleman.com to join for free with a 7 day free trial!

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