アルゴリズムと機械の外国為替戦略 | OneStepRemoved

  • Articles
  • Sophisticated Web Sites
  • Automated Trading
  • お客様の声
  • お問い合わせ

One line of code makes all the difference

2 月 9, 2017 によって ショーンオバートン 4 コメント

I was really excited about my Pilum strategy two months ago. The research looked great and everything was ready to rock and roll. Demo testing began and then… not much happened.

The Quantilator is (mostly) finished, which finally gave me time to circle back and review what happened with Pilum.

Live demo trading of Pilum

Live demo trading of Pilum. 12月 9, 2016 to Feb 7, 2017

The expected outcome was that I would win 75% 時間の. Trades were infrequent, so I thought maybe I’m just having bad luck. But then my win rate remained stuck around 50%. Simple statistical tests told me this was unlikely to be bad luck.

I used the research time to pour over my research code and to compare it with live trades. What I found was that a single line of code (AHHHHHHHHHHHHHHH!) was incorrectly calculating my entry price, dramatically overstating the profits.

、 flawed code produced this equity curve from a single combination of settings:
Flawed Pilum backtest

When the actual, correct result looks like this with those same settings:

The accurate backtest of Pilum

The accurate backtest of Pilum

I’ll be honest… I like the flawed backtest a lot more!

The new, single-setting backtest isn’t as good, but it’s still trade-worthy. There are some characteristics that I dislike and features that I love. Let’s dig into those.

What I dislike

The frequency of trades is very low. Out of 19 months there were a total of 43 取引. 43 trades to comprise a backtest on 40+ instruments is a very small number.

If it weren’t for the statistical pattern backing up the frequency, I would not consider the test. しかし, there are 20,000 bars each on the 44 instruments. あります。 880,000 total bars used to analyze whether my Pilum pattern offers any predictive value.

The most valuable predictions, しかし, are also exceptionally rare. That’s why I’m not able to get the trading frequency higher, which would potentially smooth the returns.

What I love

My previous systems like QB Pro and Dominari traded actively for relatively small wins. Trading costs exercised a massive impact on the overall performance.

The accurate backtest of Pilum

The accurate backtest of Pilum

Now look again at the correct equity curve (the image to the right). Do you see the final profit of roughly 0.14? That’s a 14% unleveraged return over a 19 ヶ月の期間.

Allocating 2:1 または 3:1 leverage on this strategy could average annual returns of 15-25%.

Detecting hidden risk

A key measure of risk is skewness. You may not use that term yourself, but it’s something most of you already understand. The biggest complaint about people trading Dominari was that the average winner relative to the average loser was heavily skewed towards the losers.

Dominari wins on most months, but when it lost in December it was devastating. I implemented what I thought was a portfolio stop after the December 9th aftermath. Then I had a smaller, but still very painful, loss in January. The portfolio level stop loss of 3% should prevent future blowouts now that I know what goes wrong.

I still believe in Dominari. しかし, I obviously lost the work of most of the year due to those events.

Knowing that skewness is a good measure of blowout risk (even if you’ve never seen it in a backtest, like happened with Dominari), Pilum looks extremely encouraging.

This is a histogram of profit and loss by days. You should notice a few things.

The tallest bar is to the right of 0. That means that the most frequent outcome is winning.

worst and best days

The biggest winning day is dramatically better than the worst losing day. The worst outcome was a loss of 2%. The best outcome is gains near 10% in a single day (unleveraged!).

This is the statistical profile of an idea that’s much more likely to grab an avalanche of profits than it is to get blown out.

It gets even better

low correlation

Would you say that the blue and red equity curves are highly or loosely correlated? Look closely.

Writing this blog post made me think carefully about the Pilum strategy. I decided that maybe I should see if all of the profits are coming from different settings at the same time. There’s very little risk of overfitting the data as my strategy only has 1 degree of freedom.

The blue bars are the equity curve of Setting 1.

The red bars are for Setting 2.

Do you think these are tightly or loosely correlated?

If you said loosely correlated, then you are correct. Notice how each equity curve shows large jumps of profit. Did you notice how those profit jumps occur on different days?

The blue setting skyrockets on a single day in November 2016. It leaves the red equity curve choking in its dust.

But then, look what happens as I advance into December. The red curve dramatically catches up to the blue curve and even overtakes it.

The correlation between the 2 strategies is only 57%.

Combine multiple settings into 1 portfolio

Combined settings Pilum equity curve

This is a much nicer equity curve!

Loose correlations are a GIFT. Combining two bumpy equity curves into a single strategy makes the performance much, much smoother.

The percentages of days that are profitable also increases. Setting 1 is profitable on 58.0% of days. Setting 2 is profitable on 53.5% of days.

しかし… combining them makes Pilum profitable on 68.2% of days. 素晴らしい!

That also provides more data, which puts me in a stronger position to analyze the strategy’s skewness. Look at the frequency histograms below. They’re the same type of histograms that I showed you in the first section of this blog post. As you’ll notice, they look a lot different.

Pilum most probable daily profit and loss

The most probable outcome for any given day is a small winner

The tall green bar is the most probable trading outcome for any given day with filled orders. The average day is a positive return of 0-1%.

The small red bar is the worst trading day of the combined strategy.

The small green bars are the best trading days of the combined strategy.

Look how far to the right the green bars go. The largest winner is more than 3x the biggest loss. と, there are so many more large winners compared to losers.

Giant winners are far more likely than comparable losses.

The Plan

I immediately pushed Pilum into live trading this combination of two strategies. I expect that adding a second degree of freedom and running about 30 different versions of the strategy – all with different settings – will add to the performance and smooth the returns even further.

Dominari hasn’t been working on my FXCM account, which is very difficult to accept because the lacking performance seems to be a buried execution issue. Pilum, しかし, trades very infrequently. It’s unlikely that execution quality will make a dramatic difference in the long term outcomes.

だから, I’m going to convert the FXCM account to trading Pilum exclusively. That will be offered as a strategy on Collective2 within the next few weeks, a company with whom I’ve been working closely. Their users are more investor rather than trading oriented – they’re far more likely to view low trading frequency as a good thing. I suspect that most people here have a different opinion and want to see a lot of market action.

I’ll write an update on Dominari shortly.

以下の下でファイルさ: Pilum, 戦略の取引のアイデア タグが付いて: 相関関係, カーブフィッティング, 自由度, ルール, equity curve, 周波数, FXCM, histogram, レバレッジ, QB プロ, リスク, スキュー, 統計情報

Deeper Analysis For Comparing Trading Systems

8 月 22, 2013 によって アンドリュー ・ セルビー Leave a Comment

When first introduced to systems trading, a lack of knowledge and experience leaves many traders with limited options on which system to trade. As they expand their knowledge, these traders can soon become overwhelmed by the number of systems that are out there. Deciding which system is the best fit for a trader can require a tremendous amount of analysis, and many traders don’t consider all of the proper variables when making these decisions.

Many novice traders assume that the system with highest overall return is the best system. This is almost never the case, しかし. 何度も, incredibly high returns are the product of a level of risk that most retail traders are not comfortable with. No amount of money is worth losing sleep over. The same case can be made for a system that either trades too often for the trader to keep up with, or not often enough to make any money.

When reviewing different trading systems, we want to consider their returns with respect to profitability, ボラティリティ, and risk. We also need to consider the frequency of their trading signals to make sure that all of the system’s components will mesh well with our personality.

Compare trading systems

Criteria for comparing trading systems

Profitability

The most commonly used profitability metric is Compounded Annual Growth Rate (CAGR). This takes the long term return of your system and averages it out as if it occurred in a straight line. 明らかに, the fatal flaw here is that no system is capable of producing returns on a perfectly steady basis. しかし, CAGR does give us a convenient way to quickly compare systems. You will certainly want to dive deeper before investing real money!

Another interesting profitability metric is the number of winning trades, or the Win Ratio. This is simply a percent that measures how many of a system’s trades are winners versus how many are losers. The interesting thing about Win Ratio is that systems can be profitable overall with incredibly low Win Ratios. They can also be unprofitable despite very high Win Ratios.

For that reason, Win Ratio is very closely tied to Profit Ratio. This is the average return of a winning trade divided by the average return of a losing trade. Breaking down these two components is a good way to find out how a system is achieving its CAGR.

Systems like the 3 Day HIgh/Low Mean Reversion System can be profitable despite a low Profit Ratio of 0.64 because almost 74% of its trades are winners. 反対側に, a system like the スパイ 10/100 Long Only System is profitable despite only winning on 41% of its trades because its winners are more than four times the size of its losers.

ボラティリティ

While profitability is the end goal of just about every trading system, it may come at a cost. A prudent trader will identify what that cost is and then make an educated decision regarding whether the value is worth it.

One of those costs is volatility. Some systems, like the Moving Average Crossover with RSI System または、 50 EMA の単位系 provide an excellent combination of Win and Profit Ratios at the cost of severe volatility. These systems are known to experience drawdowns of 40-50%. At that steep of a drawdown, even the most seasoned systematic trader will begin to question his system and whether markets have fundamentally changed.

Even systems with less severe drawdowns can cause traders to lose sleep. As a general rule, you should estimate the maximum drawdown you believe you can tolerate, and then cut that number in half.

リスク

Another cost of high returns can be excessive risk. Most trading systems provide the option of dialing up or down returns based on adjusting risk through leverage. Taking on too much risk in order to chase higher profits has been the nail in the coffin of many formerly successful traders.

The amount of risk you expose yourself to is one of the few things that you can actually control when it comes to trading. It is essential to your success that you constantly monitor your exposure and always keep your risk of ruin at an acceptable level.

Frequency

It is also important to consider the frequency of the signals generated by your system. This is a two-fold issue. 最初, you have to make sure that your backtesting results contain a significant sample size. If you backtest over a ten year period and your system only generates three signals, the odds are pretty good that your results will be skewed.

You also want to make sure that the system trades at a frequency that matches your lifestyle. A profitable system with low volatility and risk won’t help you if it never trades. 反対に, the same system will be equally as useless if it forces you to monitor trades 24 一日あたりの時間.

The bottom line is that there are no right answers, and there are hundreds of different approaches to systems trading. The key is to find a system that works for you and stick to it.

以下の下でファイルさ: 戦略の取引のアイデア タグが付いて: 周波数, profitability, リスク, system trading metrics, ボラティリティ

メールで無料の取引戦略

トレンド分析

申し訳ありませんが. No data so far.

アーカイブ

  • ルール
  • 外国為替市場のしくみ?
  • インジケーター
  • メタト レーダーのヒント
  • MQL (オタクのため)
  • NinjaTrader ヒント
  • Pilum
  • QB プロ
  • お金を失うことを停止します。
  • あなたの概念を歴史的にテストします。
  • 戦略の取引のアイデア
  • 未分類
  • What's happening in the current markets?

翻訳


無料の取引戦略

プライバシー ポリシーRisk Disclosure

著作権 © 2021 OneStepRemoved.com, (株). すべての権利予約.