USDJPY Chart — Dollar Yen Rate — TradingView

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]

I like my numbers how I like my men

Hard.
Following up on my post about trading economic news, here are some hard numbers about news releases. If you can't be bothered to read any further, just know that a high S value means there is money to be made by trading the release of that economic metric.
I collected historical data (consensus and actual) for each of these economic metrics from January 2018 to the present. These are mostly monthly metrics; one is quarterly, one is biweekly, and one is weekly. I did this manually from an economic news aggregation website because I'm too cheap to pay for exported data. I also noted whether each release was the primary (or only) news being released at that precise moment or whether there were other important economic metrics being released at the same time.
Then I wrote software to fetch 2 minutes of USD/JPY price data (in 5 second candles) starting at the time of each release and correlated each candle to the "surprise" in the metric (the difference between the consensus and the actual). That produced data for each metric that looks like this and give you an idea how reliably the news predicts the short-term price move.
Next the software went back through the price history and measured the "coordinated movement" of the currency pair during each candle. By that I mean it measured the size of each candle in pips and then set the sign to be positive if its moving in the same direction as the first candle or negative otherwise, and averaged all those numbers together. These charts look like this and give you an idea how dramatically the price moves in response to the news.
Then, for each candle, the absolute value of the correlation is multiplied against the coordinated movement, creating a "tradeability" score. The idea is that a strong (positive or negative) correlation and a strong coordinated movement yields a high score, and either a weak correlation or a small price movement yields a low score. These charts look like this.
Finally, for each news release I measured the maximum value of the correlation (R) and the maximum value of the tradeability score (S). Since I don't have access to anything with finer granularity than 5 seconds, it's no surprise that candle 0 had the maximum correlation and maximum tradeability for each metric.
I did this process twice for every metric: first over all releases and second over only those releases that were the primary or only release happening at that moment. I kept the results from the one that returned the better net maximum tradeability score. The net maximum tradeability score is just the product of the maximum tradeability score and the number of releases being considered, either all of them or some smaller number. (This helps avoid bias in the results for metrics that are often released at the same time as other metrics.)
In the results linked at the top of this post, the metrics are ordered by decreasing maximum tradeability score (S) with maximum correlation (R) also shown. Remember, R = +1 means perfect positive linear correlation, R = -1 means perfect negative linear correlation, and R = 0 means no correlation. S values less than 3 are essentially untradeable due to the spread.
A couple notes:
It takes me about 15 minutes to scrape 2 years of monthly data by hand and type it up, and then the software takes about 10 seconds to run per metric. If there are regular forecasted economic releases that you'd like to see correlated and scored, let me know! I can do other currency pairs and other country's economic news as well, it's just a matter of data collection.
submitted by thicc_dads_club to Forex [link] [comments]

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submitted by Red-its to maintradingcompany [link] [comments]

Let's Talk Fundamentals (because they might be important this week)

This is more of a brain dump to encourage discussion, so I'd love to hear your thoughts.
Something strange happened this week.
Stocks fell off - mostly Japanese stocks, but equity markets everywhere suffered nasty losses. The S&P 500 shat a nasty reversal candle on Thursday, and the Nikkei posted one of its largest falls in history on Friday.
At the same time bonds fell (yields rose). The US Dollar also fell.
That's not how it's supposed to work.
When stocks fall, bond yields fall (bond prices rise) because more people buy them. Where the hell was the money going?
Into the Yen and the Swiss Franc, mostly. The Yen because most of the action was in Japan. The USD/JPY and Nikkei 225 are HEAVILY correlated. I can't tell if the fall in stocks preceded the fall in USD/JPY (and AUD/JPY, which many say led the way), or if it was the other way around, but either way we had classic risk aversion kicking in.
USD/JPY posted its largest weekly decline since 2011.
There was some jawboning, and data from Japan to suggest that the new QE measures are working.
But wait a second: they've only just started. That money hasn't really filtered down to anywhere where it's actually being used to power the economy. The only real effect so far has been a massive uplift in stocks. This is because a lot of the Nikkei 225 is made up of exporters and multi-nationals, and a falling Yen boosts their expected profits - nobody's actually made any money yet.
The technicals still only say "retracement", not "reversal", but we're hanging in by a thread - especially USD/JPY. If we break Friday's low, 100 is in sight. If this break is for real, this psychological barrier will mean absolutely nothing.
After this 97.00 is next, then 95.00/94.50, then 92. I don't think any fall would get down to 92, or even 94, but 97 is highly possible by the end of this week - and if we get there, it could be in a matter of minutes.
Before I go on, COT data
(For newbie traders, COT means Commitment of Traders, and it's a series of complicated charts showing net speculative futures positioning. When you overly it onto price data, you will find that extremes of short positioning tend to precede massive rallies. This is because a LOT of people get increasingly short as price starts to fall, which reaches an extreme as it continues to fall. Price starts to come back up, and the extreme extends a little bit more, before you get a short squeeze and everyone buys furiously to get out of unprofitable short positions)
Aussie COT showed a massive extreme in short positioning: http://stocktwits.com/message/13774559
So did the Japanese Yen: http://stocktwits.com/message/13774580
The most telling is the S&P500: http://stocktwits.com/message/13774599
The light blue line says that the big money is getting more and more out of stocks (or since it's futures positioning, they're starting to bet it will fall)
All other things being equal, this means these two are probably due a large correction. All other things might not be equal, however. Extremes in quiet times can become the norm in unusual circumstances - bear this in mind.
This is the scenario if Asian stocks lead the fall. Longs are clearly nervous, but the docket is light this week. This alone could be enough - with minor bad news sparking panic selling. The US Dollar could see some initial selling purely on USD/JPY, pushing the majors higher. This will happen during the Asian session. If it happens in the morning, you will see European markets open lower, and we might get early USD weakness as USD/JPY sells off.
But it won't last. The risk aversion will spill into European and US stocks as these markets open, and they may gap significantly lower. In this case the Swiss Franc will strengthen first, followed by the US Dollar. So I don't like USD/CHF so much here. The US Dollar will almost certainly surge once US markets open.
If this is the real deal, (and that is the biggest fucking "IF" ever because many have called this reversal lots of times and have given up after being wrong repeatedly) this dollar surge will be enormous. The world will be waking up from its dream of a fragile recovery that has been overblown by surging stock markets.
Stock markets have been rallying for mixed reasons. Some of it is investor confidence, but most of it is simply the search for yield, which most cash investments can't provide at the moment. Dividend yields in stocks are good, and fund managers have been buying them because they need to beat indices, which are rising more quickly than the values of their portfolios. This cycle has fed itself, and stocks have risen, even though demand for those companies' products and services has remained tepid.
If this happens, the Yen crosses will be blown to bits, as will the majors. But don't just go short everything if you see it falling. It will be difficult to know whether it's the real thing, and you'll have to be in front of your trading screen at the time (unless you want to set breakout orders)
We are seeing all the signs of a minor bubble bursting.
The headlines have been all about markets hitting new highs, and everybody buying stocks. That is usually a sign that the smart money has started selling their large holdings to incoming retail investors, and that a lot of the profit from the bull run has been made. If stocks start to look wobbly up here, the last ones in will be the first ones out.
Look at USD/JPY or the other Yen crosses zoomed out to 2005. The rise is absurd. I showed it to my girlfriend, who doesn't know the first thing about Forex, and she said it looked unnatural and if she had to guess, the next move would be "down a bit". This kind of woke me up a little - it was so obvious because the move up seems to be against the laws of nature, even if backed by fundamentals. Humans are good at pattern recognition, and even she could look at previous price action and recognize that a sharp rise like this almost never happens without a bit of falling.
It all depends on where you bought.
For example, if you had held USD/JPY since 92.00, and you planned to hold it for the rest of the year, you wouldn't worry so much about a drop to 97 (though it would be annoying). If you were long on a break of 100.00, you would be getting the fuck out. Your stop might be at 100, or maybe you'd locked in 50 pips. The point is that longs are now nervous, and bids will be hard to find below 100. Most people are probably prepared to take a chance buying a dip into around 100 (I know I am), but not below there.
Below there are stop losses. Hundreds of millions of them.
So that's my take on things. I'm not saying the world will end this week, but we all know that what goes up very quickly when there isn't a good reason to do so, usually comes down pretty quickly as well.
Others would argue with my fundamentals. I've seen articles saying that the rise in stocks can be attributed to companies holding on to cash reserves and paying high dividends, because they are worried that the recovery might not come. When they finally do see it coming, they will start spending that cash on growing and employing people - so maybe stocks are leading the global economy in this recovery.
I say horse shit. Demand has to precede supply, and right now the powerhouses of the global economy have more supply capacity than there is demand for. We have got into this situation because corporate profits have stayed very good during the last few years, but household incomes have fallen in real terms, and the average consumer is no better off, even though central bank governors are starting to say otherwise.
You and I are still earning far less money than we should be, and spending proportionally more and more of it every year as wage growth struggles to keep up with inflation, which is already low in most developed countries. Corporate profits continue to do well, but this money is not being spent in the real economy and used to create jobs.
I'm not going to go all marxist here for my last thoughts, but it is important to realise that there is a continuing and growing concentration of wealth in the hands of the few. They might say that they are the job creators, and many of them are. But for the most part they are the wealth hoarders. That money goes into things that cause the economy to appear to be growing, but do not actually grow the real economy - company stock, large assets, investments.
They also buy things from companies that are seeing their profits grow faster than the wages they pay. Where a dozen board executives get huge bonuses and a hundred thousand shareholders see their balance sheets grow, the people who are actually spending their portion of that company's profits (the employees) don't have any more money to inject into the economy than they did last year.
These market forces are going to collide sooner or later. Either:
I'm not saying it will happen this week, or at all. All I'm saying is that stocks are rising very quickly on not much at all. There are precedents for this throughout history, and it never ends well. When you hear hoof beats, don't think zebras.
TL;DR Forecast is choppy, with a light chance of apocalypse
submitted by NormanConquest to Forex [link] [comments]

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In foreign exchange (forex) trading, pip value can be a confusing topic.A pip is a unit of measurement for currency movement and is the fourth decimal place in most currency pairs. For example, if the EUR/USD moves from 1.1015 to 1.1016, that's a one pip movement. Most brokers provide fractional pip pricing, so you'll also see a fifth decimal place such as in 1.10165, where the 5 is equal to ... USD JPY (US Dollar / Japanese Yen) Also known as trading the “gopher” the USDJPY pair is one of the most traded pairs in the world. The value of these currencies when compared to each other is affected by the interest rate differential between the Federal Reserve and the Bank of Japan. Pip value for indirect rates are calculated according to the following formula: Formula: pip = lot size x tick size / current rate Example for 100,000 USD/JPY contract currently trading at 120.50: 1 pip = 100,000 (lot size) x .01 (tick size) / 120.50 (current rate) = USD $8.30 Ein fortgeschrittener Pip Rechner, entwickelt von Investing.com. the definition of the pip, which is not always the same depending on the pair selected (e.g. the pip for the EUR/USD = 0.0001, the pip for the EUR/JPY = 0.001) The exact formula is the following: z pip XXX/YYY =z* S * dPIP expressed in currency YYY Where . z = number of pips as a gain or loss ; S = size of the contract = no. of units of pair ... The USD/JPY pip value can be calculated in high accuracy by taking the example of a 1K lot. In this currency pair, the value of one pip in 0.01. This also translates to 1/100 times the JPY. After multiplying it by the 1K lot, that is 100, you get 10 yen. 1 USD is equivalent to 110 yen according to the current exchange rate. Forex Pip Calculator ... USD/JPY: 105.19 : 950.65 : 95.07 ... The tool below will give you the value per pip in your account currency, for all major currency pairs. All values are based on real ...

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How To Trade USD/JPY Forex Trading Tips 👍 - YouTube

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