アルゴリズムと機械の外国為替戦略 | OneStepRemoved

2 Painful hits

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December and January were extremely unkind to me. I took a huge loss on 12 月 9 that coincided with the Fed meeting and another big punch in January. In total, I went from a 28% profit to a ~4% net loss.

Deservedly, my inbox quickly flooded with comments and suggestions on the drawdown. The most common of those was to stop trading during news events.

だから… why am I still trading during news events? There are a few answers to that question.

カーブフィッティング

It’s not like the strategy loses money on every single news event. それは、します。 100% true that news events like the Fed meeting can and badly hurt. Say that I’m determined to exclude news events in the future. I’d have to

  1. Collect historical news event data
  2. Create a second algorithm, which selects the news events that forbid and allow trading to continue
  3. Test how the news algorithm interacts with Dominari
  4. Repeat this many times until I’m happy with the final result
Spiraling staircase

Due to the tiny number of news events that impact the markets like the December 9th announcement, my data set is miniature. The risk of overfitting to historical news events is huge.

Working with tiny amounts of data provides little in the way of long run confidence. Focusing my efforts elsewhere is far more likely to improve performance and requires much less work.

Too many trades

Too many trades sounds a bit naive, so let’s dig into what that means. Dominari trades a portfolio of 7 異なる機器. All instruments cross with USD.

  • ユーロドル
  • GBPUSD
  • USDCHF
  • AUDUSD
  • NZDUSD
  • USDJPY
  • USDCAD

Many subscribers correctly observed that the major losses occurred with trades open on all 7 pairs in the portfolio at the same time. A good predictor of trade performance is the number of trades open simultaneously.

1-3 trades seems to be consistently profitable
4-5 trades leads to biting my nails
6-7 trades is neutral to disastrous

Testing and confirming the max open trades rule was quick and easy. 5+ trades is very dangerous.

Accordingly, Dominari now exits all open trades if there are 5 or more trades open at any given time.

The next feature of Dominari will be a reversal strategy. Dominari was clearly prone to sudden equity changes if 5+ trades were open at the same time.

Make the losses work for us

An obvious counter strategy is to open trades in the opposite direction whenever Dominari would otherwise open too many trades. Testing the idea is very easy.

Coding a Dominari reversal strategy, しかし, would require a major reprogramming of the expert advisor’s code.

The number of trades per year would be miniscule. I doubt that it would average even 1 trade per month.

The idea is that Dominari can be the normal trading strategy. Whenever Dominari opens too many trades, the strategy then switches into reversal mode and trend trades with a simple trailing stop.

Switching direction should mostly reverse the negative trade skewness back in the positive direction. Almost all of the offending trades open at exactly the same time.

If the biggest losing trades opened at different times, there would be the risk of being too late to the party. All blowout trades opening at the same time means that the strategy can realistically reverse 100% of would-be losses into profits.

Sitting at the top of the docket are changes to Pilum. You can expect to hear about those soon so that I can incorporate Pilum into the Dominari signals. Once that and 2 other internal projects are finished, I’ll be able to dedicate the time required to fully implement the Dominari Reversal System.

Equity stop loss

Dominari uses emergency stop losses on all tickets. That is appropriate 99% of the time for individual trades. Those emergency losses reset once per hour in line with the concept of the TODS.

A little of the problem was bad luck. My stops came within a handful of pips of being triggered. Then they reset even further away, which made a bad problem worse.

When all trades move at the same time, then clearly the strategy could suffer extreme losses.

The first attempted solution after the Fed announcement was to add a portfolio level stop loss. The way that I wrote it also updated once per hour. When a second negative movement came in January, I stopped trying to be clever. It’s a flat, 単純です, stupid stop loss. If I lose more than 4% on all open trades, the entire Dominari portfolio goes flat.

I’m still trading Dominari

I still have my money trading the Dominari system; my confidence in the long term performance hasn’t changed, but it obviously requires safeguards. The max number of trades and the portfolio level stop loss will go a long way to limiting the impact of big moves in the future. AND, I should get the counter-strategy developed relatively soon to turn potential frowns upside down.

最後に, many of you questioned why I’ve been so quiet. The honest answer is that I needed some time to process what happened. It’s easy to feel overwhelmed and discouraged when you get knocked down. I needed some time to process what happened.

I also needed time to double check the changes that I made to the portfolio were actually beneficial. It’s very easy to appease traders when they’re upset by rushing out features before they’re thoughtfully considered.

My money is on the line (私は失いました 2,000 euros between the two moves). What hurt my subscribers hurt me, あまりにも.

成功したトレーダーを作るもの?

によって 7 コメント

成功外為トレーダーの割合が比較的少ない, まだ彼らはある特定の類似を共有します。: A well-built trading system, plus the right combination of personality traits and learned behaviors.

もちろんです, the tools are important – Regardless of a trader’s personal characteristics, a successful trader always builds, uses or finds a good Expert Advisor (EA). Most people believe that if they just find the one magic bullet, then everything will be fall into place. As Shaun discusses in the forex robot secrets report, that’s almost never the case.

Characteristics of successful traders

Traders and EA developers who succeed are usually found at one of the two extremes of intelligence: Either they’re highly intelligent, or they’re extremely dim witted. There doesn’t seem to be much middle ground in which “average” developers succeed.

1 つの手, it seems easily explainable that sharp developers should be more successful than “average” ones. まだ, those at the other intellectual extreme are often also more successful than the typical developer.

なぜ?

One theory to explain the trading success stories of traders and EA developers who are outside-the-ordinary is illustrated by this anecdotal experiment: If a mouse is placed into a cage where cheese is found on a particular side of the cage 60% 時間の, と 40% of the time on the opposite side, every mouse will eventually learn to choose the side of the cage where cheese is found 60% 時間の.

mouse and cheese

他の言葉で, mice are at least intelligent enough to stop guessing and simply choose the pathway which is more often successful. 対照的に, humans generally try to improve their success by finding and improving on some sort of pattern in randomness, even when it’s not there.

This theory may explain why less-intelligent traders can be successful by sticking to a system based on simple rules that win more often than they lose. もちろんです, “home-run” systems that are over-optimized in an attempt to “win everything every time” usually fail.

From the perspective of the mice described in the above experiment, it’s not about getting すべて the cheese every time, it’s about getting enough cheese more often than not.

A trading success story is based on more than just brain power

An automated trading success story may begin with brainpower, but it doesn’t end there. Brainiacs tend to build trading systems based on deep technical analysis. Theories are developed and modified as testing reveals strengths and weaknesses in a given system.

If a mouse is placed into a cage where cheese is found on a particular side of the cage 60% 時間の, と 40% of the time on the opposite side, every mouse will eventually learn to choose the side of the cage where cheese is found 60% 時間の.

しかし, there are plenty of intelligent, well-educated traders, and many of them don’t thrive when they’re involved in day-to-day trading. Significantly, winning traders’ ideas tend to become simpler over time instead of more complex.

An EA can be あまりにも powerful

Being too smart is a handicap that can keep traders from winning, and the power of EAs can also work against them. EA-focused traders tend to drift off course instead of remaining focused on the simple pathway toward trading success.

Without consistency, it’s difficult make any progress, nor measure results effectively. Too many indicators and too many pathways to explore may tempt EA traders to go astray, and wander away from the simple, basic rules that win.

Trading is a process, not a destination

When the trader approaches system design as a process rather than as a fixed destination, the outlook becomes much better. Success is relative, and improvement is ultimately more important than perfection.

たとえば, when a trader focuses on a system’s accuracy, the trade-off usually comes in the form of accepting a less-profitable exit point from a given trade. だから, a trader’s urge to win a slightly-higher percentage of trades often erodes the system’s performance.

対照的に, process-oriented system designs let traders assess how making slight changes in the trade-entry protocol affect the system’s efficiency. と, using expert money-management methods can help by reducing the emphasis on entry and exit protocols.

Emotion in trading can’t be denied, yet it can be channeled appropriately

Emotion is impossible to separate from trading. しかし, it shouldn’t be the reason for trying to develop a winning Expert Advisor.

代わりに, rational reasons for building an EA include situations in which a trader has been trading a given system long-term and wants to automate a proven winner, or finding ways to automate one’s trading based on narrowly-targeted indicators that win more often than not, even without generating perfect signals.

The question isn’t how to to remove emotion – Instead, the question is how to channel it appropriately, especially when the trader or EA developer has made a huge investment in time spent developing a system.

The goal is to develop and implement a consistent system – not a perfect system. When traders swing back and forth between winning and losing, the lack of consistency makes them feel less confident in their systems.

When a trader is “married” to a supposedly perfect system, there isn’t likely to be any trading success story in his or her future.

Work with professional EA developers

Designing a winning trading system takes hundreds of hours of time, plus at least a decade of experience. 前述のとおり, system development is a process instead of an endpoint. まだ, there’s a way to expedite the process – work with a professional developer like OneStepRemoved.

Where are you in your trading journey? Share your ideas below for you how “find more cheese” in the markets.

Coppock 曲線 : 取引の成功への直線

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Coppock 曲線, 呼ばれる Coppock インジケーターまたは Trendex 指標, クオンツトレーダーにシンプルでありながら成功した機械的な取引システムを構築するための強固な基盤を提供していますインジケータの種類は、.

以下でより詳細に記載されるように, 私はSで売買シグナルを生成するために、私の機械的な取引システムでCoppock曲線を使用&P 500 または他の流動性の高いインデックス. Coppock曲線はまた、取引iシェアーズETFのとではうまく機能.

Coppock曲線とは何ですか?

Coppock曲線は運動量指標であります. 時間をかけて, 彼らは何度ゼロの下で振動します. Coppockカーブインジケータは、最初に説明しました 1962 エコノミストやトレーダーエドウィンCoppockによって. 実際, それは市場の技術者協会ようにうまく動作します (MTA) 認識博士. 功労賞のあるCoppock 1989.

Spiraling staircase

その値は、株式やインデックスの価格動向の長期的な変化の始まりを示すことにあります, 特に上昇傾向の初めに. このインジケータはまた、先物や外国為替市場の底部に信号を送ることができます, まだ私はそれが信頼性が低いことがわかりました.

あなたは、任意の時間枠にわたって、この指標に基づいて売買シグナルを生成するために、機械的な取引のアルゴリズムをプログラムすることができますが、, 私は、一般的に株式や指数市場の幅広い毎月のチャートで使用. まだ, アクティブなトレーダーは確かに毎日、あるいは時間単位の期間でCoppockカーブを使用することができます.

具体的には, 私は、クマの市場の下部にある「買い」信号を生成するCoppock曲線を使用. このインジケータは、クマの集会や実際の市場底とを区別するために特に良いです.

これは、トレンド追従指標であります, ので、正確に市場の底が表示されません. 代わりに, それは私を示していたときに強いです, 強気の集会を安全に自信を持って取引を十分に定着しています.

すべてのベスト, 私の経験でCoppocks曲線に基づいて、信号からの取引がshakeoutsとwhipsawsにかなり耐性があります. Coppock曲線が遅いです, 彼らは安全です.

Coppock曲線は「喪の期間」の終了を知らせます

背景として、, それは注意することは価値があるという博士が主導し、元のアイデア. Coppock彼の指標を開発するためには、生活の自然のサイクルに基づいていました, 死, そして再び新しい生活に戻る前に、喪.

彼は株式市場の通常の上方行進と思いました (したがって、株価指数) サイクルの「生活」の部分のようでした, もちろん、これはつまり「死」が続きました, 弱気市場の間の価格下落の期間.

Dr. Coppockは、株式市場の「喪」期間の長さを計算する際に特に興味がありました, その後、再び市場「長い」再入力しても安全になります. 論理的に, 喪期間の終了時にこのエントリポイントは次の長期的な上昇トレンドの始まりを表すことになります.

作り話の話は、彼が地元の聖公会で司教に尋ねたことを言います, 彼の投資のいずれかのクライアント, 通常bereavements後に喪に費やさどのくらいの人々. 彼は人間の喪が典型的に必要であることを言われました 11 宛先 14 ヶ月, ので、これらは、株価が再び上昇し始めるとき、彼は彼の元の方程式に採択された値を決定することでした.

Coppockカーブは最初毎月のチャートに基づいて長期的な指標として使用しました. もちろんです, 毎月の時間枠で生成された信号はかなりまれです. まだ, 私は市場の様々な取引をCoppockカーブを使用しているため, 私は、売買シグナルの多くを受け取ります.

特に, 毎月の時間枠は、株式やインデックス取引のため、非常に信頼性が高いです. 研究があることを示しました, 以来、 1920 米中. 株式市場, Coppock曲線は、約で勝利信号を生成しています 80% 周波数.

この頃, 現代の市場の急速な売上高と, それは取引サイクルが速くなってきているようです. 毎月の時間枠に加えて、, 一部のトレーダーは、毎日の時間枠が成功Coppockカーブ信号を生成する際に非常にうまく機能することを発見しました.

トレーダーは、毎日または毎時時間枠に基づいて認識し、信号に対応するための機械的な取引システムをプログラムすることができます, 追加のアルゴ取引パラメータは放漫経営の機会を減らすために追加する必要がありますが、.

あなたは、より短い時間枠で信号を生成するCoppock曲線を使用する場合, あなたの特定の市場のためのメイクセンス」喪の期間」のさまざまな方法を使って、あなたの機械的な取引システムを実験でした.

Coppock曲線を計算する方法

Coppockインジケータは、三つの変数に基づいています: 変化の短期率 (ROCと略記), やや長期ROC. Coppock曲線は、加重移動平均を使用して開発されています (WMA) 特定の市場指数の選択された時間帯由来.

言葉で述べた古典的な式:

Coppock曲線は、14期間ROCプラス11-期間ROCの10周期WMAを=

または, プログラミングのための式として、:

Coppock曲線= WMA[10] の (ROC[14] + ROC[11])

ときROC = [(閉じる - 閉じるN周期前) / (閉じるN周期前)] * 100

nが時間期間の数であります.

古典的なシナリオでは, 11 と 14 期間. 別々のROC計算を行うようにしてください.

あなたが見ることができます。, 基本的なセットアップは非常に簡単です - 移動に基づき, 私は与えられたインデックスの変化の割合を計算するために、私の機械的な取引システムをプログラム (Sを言います&PまたはDJIA) 14ヶ月前から.

その後、, 私の機械的な取引プログラムは、11ヶ月前から同じインデックスの変化率を算出し、. 次, 機械的な取引システムは、2つの異なるパーセント変化を加算. その後、, それは上記の合計の10-期間加重移動平均を算出し、.

それはあなたがROCの計算とWMAの計算に異なる期間を使用できることに注意することが重要です. 私は時々古典を使用するために私の機械的な取引システムをプログラム 11- ROCおよび14ヶ月の期間古典10ヶ月の期間よりも短いWMAの時間期間を使用している間.

だから, 私は、多くの場合、2ヶ月または3ヶ月のWMAを使用して使用します (代わりに 10 ヶ月) ROCを使用して計算されている間 11- そして、14ヶ月の価格.

または, あなたは、計算の一部またはすべてのためのより短い時間を使用することがあなたの機械的な取引システムを変更することができます, すなわち. 毎日使用したり、毎時価格の代わりに毎月の価格チャート. これは、複数の信号を生成します, あなたは追加のフィルタを追加しない限り、私の経験では、彼らは信頼性が低いです, 以下に説明するように.

同様, あなたがあなた自身のニーズに合わせて追加の装飾を追加することができます. 任意のイベントで, 一般的な方法は同じまま. 基本的な入力をグラフ化すると, あなたは、出力がかなり滑らかな円弧であることがわかります, この指標の名前の由来.

任意のイベントで, 機械的な取引システムをプログラムするための古典的なCoppock曲線の方程式は次のように述べることができます: 変更の14ヶ月のレートと変化の11ヶ月の率の合計, 10ヶ月の加重移動平均を適用することによって平滑化と.

Coppock曲線「買い」信号

Coppock曲線に, ゼロラインはトリガであります. 価格ラインは下から上昇すると 0 ラインは、低リスクの購買機会を知らせます. Coppockインジケータが最初に以下のとき私の機械的な取引システムは、購入を実行 0, その後、トラフから上方に向かいます.

これは強気の指標として最も効果的であるので、, 私は反対を無視 ("売って") 信号. まだ, 一部のトレーダー, 短い時間枠を使用して、特に, 売り信号を生成し、ロング・ポジションを閉じて取引を実行するためにアルゴ取引システムでCoppock曲線を使用. Active traders can both close long trades and open shorts when the Coppock Curve crosses below the zero line.

The figure below shows the classic Coppock Curve trading strategy using monthly time periods. The buy signal came in 1991. The sell signal came ten years later, で 2001. Note that this long time frame helped me avoid the slump in late 2001 と 2002.

The next buy signal came in 2003 and the sell signal was in 2008. This helped me escape the slump in 2008 and into 2009. Note, also that the current “buy” position, signaled in early 2010, continues to remain open, at least through the date of this chart.

Coppock Curve on S&P 500 monthly chart

The Coppock Curve on an S&P 500 monthly chart

次, for more-active traders here’s a screenshot showing the strategy applied with shorter time periods, as shown on a daily S&P 500 グラフ. もちろんです, many more signals are generated, although in general they are less likely to be winners.

Coppock Curve on a daily S&P 500 グラフ

Coppock Curve on a daily S&P 500 グラフ

重要なこと, the longer the time period, the safer the buy signal. Since my mechanical trading system based on Coppock indicators is a trend-following system, I don’t necessarily capture the immediate gains from the exact moment of a trend reversal. 代わりに, my mechanical trading system gets me “long” just before the beginning of a profitable advance in a bull market.

Adjusting and filtering signals from Coppock Curves

I’ve found Coppock Curves to be highly reliable when used for monthly time periods. 私の経験で, using weekly, daily or hourly time periods usually means that my entries and exits aren’t as “tight” as I would like, meaning that I don’t capture all the gains I had hoped for, and I also have more losses.

しかし, active traders can decrease the ROC variables, which has the effect of increasing the speed of fluctuation in Coppock Curves and will therefore generate more trading signals. もちろんです, even though monthly time periods are my favorite, an ultra-long-term trader could also increase the ROC time periods to slow fluctuations even more, thus generating fewer signals.

上記述べたよう, in order to receive earlier entry signals, I usually decrease the WMA downward from 10 ヶ月, sometimes to 6 ヶ月, and often to as little as 2 ヶ月. By programming my mechanical trading system carefully with just the right WMA period, and filtering the signals, I maximize my profitability in a given market.

If you want to use Coppock indicators for active trading, I recommend that you filter the trade signals generated by your mechanical trading system so that you only accept trades which are in the same direction as the current dominant trend. You’ll find this mechanical trading strategy to be the most profitable, since you can avoid many losing trades by filtering the signals.

Which markets show reliable Coppock Curves?

I use my Coppock curve-powered mechanical trading system to trade a range of indexes, especially those based directly on stocks, など、:

  • Dow Jones Industrial Average
  • S&P 500
  • NASDAQ Composite
  • EURO STOXX 50
  • FTSE 100
  • Nikkei 225
  • Hang Seng

同様, if you’re focused on ETFs you’ll find that a mechanical trading system using Coppock Curves will allow you to catch the beginning of trends in specific market niches, such as biotechnology, energy, and international or regional equities niches.

The key is to make sure you trade only the liquid indexes. それ以外の場合, you may run the risk of being shaken out during “fake” trend changes.

Trading Coppock Curves in non-equity indexes

同様, for the sake of diversification and to avoid issues with correlation, I also program my mechanical trading system to spot and trade Coppock Curves in non-equity indexes as well. もう一度, I focus on markets which have sufficient liquidity.

There are some profitable non-equity indexes, including iShares and ETFs, which can be traded using Coppock indicators:

  • Bloomberg US Treasury Bond Index
  • Bloomberg Canada Sovereign Bond Index
  • Bloomberg U.K. Sovereign Bond Index
  • Bloomberg US Corporate Bond Index
  • Bloomberg GBP Investment Grade European Corporate Bond Index
  • ブルームバーグユーロ投資適格の欧州コーポレート・ボンド・インデックス
  • ブルームバーグ円投資適格コーポレート・ボンド・インデックス
  • iシェアーズバークレイズ 7-10 年財務省債券ファンド
  • iシェアーズバークレイズ 20 年財務省債券ファンド
  • シュワブ短期米. 財務省ETF
  • バンガード短期国債ETF
  • PIMCO 1-3 年米. 財務省インデックスETF

すべての上に挙げた以外の株式インデックスを取引するとき、私はCoppock曲線から信頼性の高い信号を見てきました. いつものように, キーは非常に液体でのみこれらの市場における機械的取引システムを使用することです, そうアルゴリズムが確認された信号は、それを取引する前に正当であることを合理的に確信していること.

Coppock曲線は、成功への直線を示します

近年では, Coppock曲線は、この実証済みトレーディングツールに再び目を向けているトレーダーから新たな関心を描画されています. 見る, たとえば, これらの最近の金融プレスでCoppock指標の言及します: Jay On The Markets, と、 follow up article, as well as in various trader musings.

要約すると, I can say that Coppock Curves can lead you straight to success, as long as you have the patience to let your mechanical trading system do the work for you. If you use the length of variables’ time periods which are most appropriate for your chosen markets, you should do very well with Coppock Curves.

機械取引システムと勝つ方法

によって 13 コメント

多くのインクは、機械的な取引システム故障の原因を特定することに専念してきました, 実際には、特に後. それは矛盾に見えるかもしれませんが (または, 一部のトレーダーに, 単に低能), なぜこれらの取引のシステムが失敗する主な理由はハンズフリーにあまり依存しています。, メカニカルトレーディングの火災を忘れて自然. アルゴリズム自身ない客観的人間監督と市場環境の変化に伴い進化システムのために必要となる介入.

機械的な取引システム障害, またはトレーダーの失敗?

取引システムの障害を嘆くのではなく, 建設的なトレーダーが両方の世界のベストを持つことができる方法を検討するは: それです, トレーダーは、アルゴリズムで管理された機械的な取引システムの利点を楽しむことができます。, 矢継ぎ早の自動実行など取引の決定の感情解放, まだ失敗と成功について客観的な思考の人間に生来の能力を活用しながら.

すべてのトレーダーの最も重要な要素は、人間の能力 進化. トレーダーすることができます変更し、財政的にまたは感情的に壊滅的な損失になる前に勝ち続けるために彼らの貿易システムを適応.

右のタイプと量をテストするための市場データを選択します。

成功したトレーダーは、市場の短期的な非効率から利益を収穫するのに反復的な規則のシステムを使用します。. 小型用, 有価証券及びデリバティブ取引の大きな世界で独立したトレーダー, スプレッドが薄いと競争激しい, 利益のための最高の機会は、スポッティングに基づく市場の非効率性から来る, 簡単に定量化するデータ, 可能な限り迅速に行動し、.

トレーダーが開発し、動作履歴データに基づく機械的な取引システム, 彼または彼女は、現在の市場の非効率性が引き続きアイデアに基づいて将来の利益を望んでいます。. 間違ったデータを設定または不適切なパラメーターを使用して、データを限定トレーダーを選択した場合, 貴重な機会が失われることがあります。. 同時に, 履歴データが存在しなく、非効率で検出されます。, その後、取引システムが失敗します。. なぜそれが消えた理由は機械のトレーダーに重要ではないです。. 結果問題のみ.

mechanical trading rules

作成し、機械的な取引システムをテストするデータ セットを選択するときに最も適切なデータ セットを選ぶ. と, 取引ルールの市場条件の広い範囲の下で一貫した動作かどうかを確認するのに十分な大きさのサンプルをテストするために, トレーダーは、テスト データの最長期間を使用する必要があります。.

だから, 設計パラメーターの最も簡単なセットと同様、両方の可能な最も長く歴史的データ セットに基づいて機械的な取引システムを構築するようにします. 堅牢性は多くのタイプの市場の条件に耐える能力を考慮して一般的に. 堅牢性を過去のデータと単純なルールの長い時間範囲にわたってテスト システムに固有にする必要があります。. 長時間にわたるテストと基本的なルールは、将来的に潜在的な市場条件の広い配列を反映すべき.

履歴データは明らかにすべての将来のイベントを含まれないために、すべての機械的な取引システムは最終的に失敗します。. 歴史データで作成されたすべてのシステムは最終的に歴史に無関心な条件を発生します。. 人間の洞察力と介入からレールを離れて実行している自動化された戦略を防ぎます. 騎士の首都では、人々 が何かを知る ライブ取引混乱状態.

その適応性、シンプルさ勝

成功した機械的な取引システムは生きているようなします。, 生物の呼吸. 世界の地層に満ちている生物の化石を, 自分の歴史の期間の間に短期的な成功に最適ですが, あまりにも適応と長期生存に特化しました。. クイックを受けることができるため、人間指導の単純なアルゴリズムによる機械的な取引システムが最高, 簡単な進化と環境の変化への適応 (市場を読む).

シンプルな取引ルールがデータ マイニング バイアスの潜在的な影響を減らす. データ マイニングからバイアス それは歴史的な規則が将来の条件の下で適用されますどれだけ誇張するかもしれないので問題は, 機械的なトレーディング システムは、短い時間フレームに焦点を当てたときに特に. シンプルで堅牢な機械的な取引システムのテスト用に使用されるタイム フレームで影響を受けるべきではないです。. -履歴データの特定の範囲内にあるテスト ポイント数まだ証明またはテストされている取引ルールの有効性を反証するのに十分な大きさにする必要があります。. 言い方を変えれば, 単純です, データ マイニングのバイアスを上回る強力な機械的な取引システム.

トレーダーは、シンプルなデザイン パラメーターを持つシステムを使用している場合, よう、 QuantBar システム, 最長の適切な歴史的な期間を使用して、テストと, 他に重要なできるタスク システムの取引とその結果を今後監視の分野に固執することになります. 観測により、進化.

反対に, 「事前に進化して」システムの初期絶滅のリスクを実行する複数のパラメーターの複雑なセットから構築された機械的な取引システムを使用するトレーダー.

機械取引の最善を活用する堅牢なシステムを構築します。, 煩わされずその弱点に

機械的なトレーディング システムの堅牢性と適応性を混同しないことが重要です。. システムの開発は '堅牢な' として記述されている多数の歴史的な期間に- と -現在の観測期間中であっても取引を獲得につながったパラメーターに基づいて、します。ないですこのようなシステムが正常に一度調整すること保証彼らは過去の自分の"ハネムーン期間貿易されています。” その中に条件はシステムの基になる、特定の歴史的な期間に合わせて起こる初期取引期間であります。.

単純な機械的な取引システムは簡単に新しい条件に適応, でも、市場変化の根本的な原因は明白でなく残る, 複雑なシステムでは不十分と. 市場環境の変化, 彼らは継続的に行う, 獲得していく可能性が最も高い取引システムは、シンプルで最も簡単に新しい条件に適応; 本当に堅牢なシステムは、とりわけ長寿を持っています。.

クイックを受けることができるため、人間指導の単純なアルゴリズムによる機械的な取引システムが最高, 簡単な進化と環境の変化への適応 (市場を読む).

残念なことに, 過度に複雑な機械的な取引システムを使用する場合の利益の最初の期間を経験した後, 多くのトレーダーが成功にこれらのシステムを微調整しようとしての罠に陥る. 市場の不明, まだ変更, 条件がありますが既に機械的な取引システムの全体の種、絶滅する運命. もう一度, シンプルさと状況の変化への適応性を提供する任意のトレーディング システムの生存のための最善の希望.

成功と失敗を区別する客観的な計測を使用します。

トレーダーの最も一般的な落下は彼または彼女の取引システムへの心理的な添付ファイルです。. 取引システムの障害が発生した場合, それは通常のトレーダーは、客観的ではなく主観的な視点を採用しているので, 特定取引中に停止損失に関しては特に.

人間の本性はしばしば感情的な添付ファイルを特定のシステムを開発する業者を運転します。, 特にときトレーダーに投資している時間とお金のかなりの量機械取引システムを理解することは困難である多くの複雑なパーツ. しかし, それを客観的に検討するためにシステムの外のステップにトレーダーのため極めて重要です。.

いくつかのケースで, 貿易業者になるシステムの予想される成功の妄想, 主観的な分析よりもはるかに長く、明らかに失うシステムを取引を継続することのポイントにも許してしまう. または, 脂肪の wins の期間の後, トレーダーは、可能性がありますになる「結婚」旧歴システムにその美しさが損失の圧力の下でフェードしながらも. 悪化, トレーダーは、テストの期間をまたは既に失うことシステムの統計的パラメーターを選んでの罠に落ちることがあります。, システムの偽の希望を維持するためには、値の継続的します。.

客観的基準, 現在の失敗の確率を評価する標準偏差のメソッドを使用するなど, 機械的なトレーディング システムの真の失敗があるかどうかを決定するための唯一の勝利方法です。. 客観的な目で, 機械的なトレーディング システムで迅速にスポットまたは潜在的な障害にトレーダーの簡単です。, シンプルなシステムは、迅速かつ簡単に新鮮な歴システムをもう一度作成に適応させること、.

機械的な取引システムの障害はしばしば歴史的な損失やドローダウンに対する測定電流の損失の比較に基づいてを定量化します。. このような分析は、主観的につながる可能性があります。, 不正確な結論. 最大ドローダウンは、トレーダーがシステムを放棄するしきい値としてよく使用されます。. 方法システムまでドローダウン レベルを考慮せず, またはそのレベルに達するに必要な時間の長さ, トレーダーは、システムがドローダウンだけに基づいて敗者である結論とせず.

障害の指標としてドローダウンに対する標準偏差

実際, 受賞システムを破棄することを避けるために最善の方法は客観的測定標準を使用して実際にそれを取引しながら得られたシステムからリターンの現在または最近の分布を確認するには. バックテストからリターンの歴史的な分布に対して測定を計算比較します。, 確実性に従って固定しきい値値を割り当てる際の機械的な取引システムの現在の「失う」配布は確かに正常より, 予想される損失, したがって失敗として捨てられるべき.

だから, たとえば, 貿易業者が現在のドローダウン レベルでシグナル状態に問題あり、彼の調査をトリガーを無視することを前提としてください。. 代わりに, 歴史的テスト期間中そのシステムの取引中に発生と歴史的な損失に対して現在の連敗を比較します。. どのように保守的なトレーダーがによってください。, 彼または彼女は現在または最近の損失が超えていることに気付く場合があります。, 言う, 、 95% 「普通の」歴史的な損失レベルからの 2 つの標準偏差によって暗黙的に指定確実レベル. これは確かに強力な統計記号は、システムのパフォーマンスが低下するだろう, したがって失敗しましたと. 対照的に, リスクの大きい食欲と異なるトレーダーことがあります 3 つのことを客観的に決めることの規範からの標準偏差 (すなわち. 99.7%) 確実に適切なレベルとして取引システムを判断するため「失敗」

任意のトレーディング システムの最も重要な要因’ 成功, 手動または機械かどうか, 人間の意思決定能力は、常に. 良い機械的な取引システムの値は、します。, すべての良いマシンのような, 彼らは人間の弱点を最小限に抑え、マニュアルの方法をはるかに超えて達成可能な達成に力を与える. まだ, 正しく作成されたとき, 彼らはまだトレーダーの判断に従ってしっかりした制御を許可して、彼または彼女が障害物と潜在的な障害の明確な舵取りをできるように.

トレーダーが損失するかどうかを評価する標準分布の統計計算の形で数学を使用できますが、通常、歴史的な記録によると許容, 彼または彼女はまだ作る純粋な機械ではなく人間の判断に依存します。, 単独でのアルゴリズムに基づく数学ベースの意思決定.

トレーダーは、両方の世界のベストを楽しむことができます。. アルゴリズムとメカニカルトレーディングの力は、発注・施工に関する人間の感情や遅刻の影響を最小します。, ストップロスの規律を維持することに関しては特に. それはまだ取引のシステムを人間の制御を保持するために標準偏差の客観的な評価を使用してください。.

変更のために準備します。, 取引システムを変更しておいて

ときに検出する客観性とともに、機械的な取引システムは、敗者に勝者から変更します。, トレーダーでは、規律と先見性に進化し、彼らは新しい市場環境に勝つために続けることができますので、システムを変更する必要があります。. どのような環境変化でいっぱいに, シンプルなシステム, その進化になります迅速かつ容易に. 複雑な戦略が失敗した場合, 簡単にそれを変更するよりも交換することがあります。, いくつかの最も簡単な最も直感的なシステムの, よう、 QuantBar システム, 比較的容易に将来の市場状況に適応するためにその場でを変更.

要約すると, 正しく作成された機械的な取引システムはシンプルかつ適応可能であるべきといえよう, さまざまな市場条件の下で利益を生成するのに十分な堅牢なされるように、右のタイプとデータ量によるとテストと. と, 受賞システムは成功の適切な基準によって判断しなければなりません。. アルゴリズム取引ルールや最大ドローダウンのレベルに依存するだけではなく, システムが失敗したかどうかについての決定は、トレーダーの人間の判断によるとすべきであります。, システムの現在のパフォーマンスの歴史的なテスト損失に対して測定した場合の標準偏差の数の評価に基づいて. 機械的なトレーディング システムは実行に失敗した場合, トレーダーは、失うシステムにしがみつくのではなく必要な変更をする必要があります。.

How Automated Should Your Trading Strategy Be?

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One of the most attractive things about quantitative trading approaches is that many of them have the capability to be completely automated. That leads many traders to believe that they will be able to simply program a strategy into their platform and turn their computer into a virtual ATM.

As with most things in life, automated trading isn’t as simple as it appears. The performance of different strategies changes over time as markets adjust. Continually evolving technology exposes our strategies to continually evolving biases. The fact that a strategy worked well last year is no guarantee that it will work well this year.

With all of the different ways that markets could fundamentally change, do you really feel comfortable designing a fully automated strategy?

automated trading

Completely automated trading sounds like a great idea, but you may see some advantages to keeping some manual aspects in your strategy.

An article that appeared on Forex Crunch earlier this month discussed the pros and cons of automated and manual trading. After breaking down both sides, the article concluded that the best approach is usually to develop a strategy that lies somewhere between the two extremes.

The fact that you want to build a fairly automated strategy does not have to mean that you can’t override that strategy if markets suddenly change. 反対に, the discretionary approach you are working on might be improved with an 専門家アドバイザー to help you identify setups.

Advantages of Automated Trading

The biggest advantage of using an automated trading approach is the reduction in slippage through flawless execution. If your strategy doesn’t have to wait for you to confirm an entry, it can jump into a position the instant that it sees a signal. This improvement in order entry also allows a trader to avoid being glued to a computer screen all day.

Some of the other advantages of automated trading that the article covered include the ability to process large amounts of data と、 ability to trade around-the-clock. The article points out that automated strategies can monitor far more markets than humans can, and automated strategies never have to sleep.

Advantages of Manual Trading

The biggest advantage of manual trading, according to the article, is having the ability to call and audible. The article suggests that if a crash in Japanese Yen is due to a large typhoon, a manual trader can simply shut down his strategy until the weather clears up.

Another advantage that manual traders have is the ability to scale the aggressiveness of their strategy up or down depending on gut feelings or discretionary judgements. This may not be helpful if your gut feelings are not very accurate, but traders with extensive experience will be much more comfortable trusting their instincts.

あなたが見ることができます。, there are advantages to both sides of this discussion. The best approach for any trader is to find an approach that works well with their own personality.

3 Forex Expert Advisors to Build Your System Around

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Many of the traders interviewed in the Market Wizards books expressed concern that too many traders place too much emphasis on entry and exit signals. They suggest that topics like position sizing and risk management are far more important.

しかし, quantitative traders still have to decide on some criteria to properly define their entry and exit signals. With so many options out there, it can be more difficult than those Market Wizards books suggest to find and decide on a decent entry and exit strategy that has an edge.

Even after you find and develop your system, 改善の余地は常にあります. For that reason, many forex traders are constantly looking for new ideas, エッジ, and expert advisors. Babypips.com published their ページのトップへ 3 Featured Expert Advisors for November 2013 at the beginning of this month.

forex expert advisor

Babypips.com has profiled three different forex expert advisors that might be useful in creating profitable trading systems.

They went through the trouble of backtesting each of these EAs from October 2010 through October 2013. Here are the highlights:

The Linear Weighted Moving Average Strategy

This expert advisor was suggested to me by a kind forum user bobbillbrowne in the Expert Advisors and Automated Trading section.

In a nutshell, it makes use of the linear weighted moving averages (LWMA) on the short-term time frames such as 1-min, 5-min, and 15-min charts.

This strategy signaled a total of 23 trades over the course of the backtesting period. The average profit on a trade was 0.43%, the win rate was 56.52%, 最大ドローダウンはありました 13.45%.

The AUD/USD MACD Cross Strategy

My search for profitable EAs also led me to the MLQ4 Codebase via the MT4 trading platform.

I stumbled upon this MACD Cross system by author ilkyulee, who specified that this robot must be used on AUD/USD’s daily chart.

This strategy signaled a total of 46 trades over the course of the backtesting period. The average profit on a trade was 1.16%, the win rate was 26.09%, and the maximum drawdown was only 5.69%.

The MACD Sample EA Strategy

I also took a look at the sample systems included in MT4 and found an updated version of the MACD Sample EA.

The currency pair and time frame weren’t specified so I just decided to run the tests on my favorite pair and time frame, which is EUR/USD 1-hour.

This strategy signaled a total of 190 trades over the course of the backtesting period. The average profit on a trade was 0.59%, the win rate was 73.68%, and the maximum drawdown was only 0.39%. Not a bad start for an out-of-the-box sample strategy.

Proceed With Caution

The article then goes on to remind traders that automated trading can be dangerous:

Before you trust a robot with your life (or in this case, your hard-earned cash), make sure that it’s a good autobot and not a bad decepticon.

他の言葉で, you gotta do your homework and additional research to figure out if the EA is consistently profitable or not.

The author also cautions that past performance does not guarantee future results. He also explains that just because an expert advisor does not initially have a great P&L does not mean that it will never be profitable. It may just need to be adjusted in a certain way to become profitable.

 

Retail trader disadvantage

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Michael Halls-Moore invited a reply to one of my tweets last week, “Retail traders have an advantage over the pros? Me thinks not.” He wrote a great overview of why the institutional traders look longingly at the retail crowd and all the hoops that they don’t have to jump through.

His points are all valid, but he overlooked the big picture. Pricing is everything to a trader. Retail traders get the short end of the stick when it comes to the cost of doing business.

The cost of trading is massively disproportionate

Let’s say that you’re a would be quantitative trader and that you’re looking for opportunities. Let’s say you trade mini lots in the forex market with 60% accuracy and 1:1 risk reward ratios. If you’re not familiar with what a typical trading system looks like, those numbers means that you have an enormous edge.

Some of the less reputable forex brokers out there charge 3 pip fixed spreads. If you’re trading with a broker offering fixed spreads, I urge you to start price shopping. Fixed spreads are wildly overrated. You pay a huge premium for the certainty of a fixed spread. I can’t think of anything remotely plausible to justify them.

The larger forex brokers charge typical spreads in the neighborhood of 2 pips on the largest majors. Although most seem to find this reasonable, the comparison between a 2 pip average spread and institutional spreads is night and day.

Do you know what the average EURUSD spread looks like on the interbank market? It’s often 0.2-0.5 ピップ. Retail traders pay an average markup of over 300% on their trades.

retail trader pricing

Retail traders facing the institutions is a bit like David and Goliath.

Retail forex prices have declined in recent years. A few brokers like MB の取引 と Pepperstone offer raw spreads with commissions tied to the dollar volume traded. These are, 私の意見で, are about the fairest prices available to low balance traders running an expert advisor.

The best deal available to semi-institutional forex traders (CTAs, large balance retail traders, など) is Interactive Brokers. The customer support is famously poor; they’re cheap for a reason. IB also offers raw spreads with a commission.

My experience with IB has been excellent, but you need to trade size for the economics to work. A 0.5 pip typical spread is great, しかし、 2 mini-lot minimum trade size and $2.50 minimum commission really adds up. Trading with IB doesn’t approach institutional type pricing until your average trade size approaches 1 標準ロット.

だから, how does pricing affect the final outcome with our 1:1 risk reward strategy that wins 60%?

  • Free trading: 後 100 取引, you’ve earned $600 and lost $400. The hypothetical net profit is $200.
  • Fixed spread: You’ve spent $300 in spread costs to enter 100 取引. The total net profit is -$100 ($200-$300).
  • Average retail: You’ve spent $200. There is no profit because you breakeven ($200 hypothetical profit – $200 コストの). しかし, your broker loves you for doing that many trades.
  • Good retail pricing: Let’s say the average cost of a trade is 1.3 pips after commissions. You’ve spent ~$130 placing 100 取引. The total profit is $70.

Even with good strategies, the profitability of your algorithm is as simple as choosing the cheapest broker.

Equities pricing

Trading stocks is even more expensive than forex. I remember back in the day when I thought Scottrade was cheap for offering $7 手数料. It gets worse and worse when you go through the list of stock brokers. Most of them try to get away with charging $7-10 1 トレード当たり. If customer service is important to you, then those are the shops to look at.

If your top priority is trading profitably, then again, broker selection is critical. The only way that a small guy can make it is by chipping away at the costs. Interactive brokers is again a great option, charging fractions of a penny per share traded. If you decide to trade 2 shares of Google (GOOG: $1,017 per share) または 1,000 shares of Fannie Mae (FNMA: $2.35 per share), the transaction costs are tiny. Two ticks in your favor is all it takes to cover the trade.

You might be thinking that I said two ticks in forex is expensive. How can I say that two ticks in equities is reasonable?

ボラティリティ. Two ticks in the stock market is a little hiccup. It’s not at all uncommon to see highly liquid stocks move 2-3% in a single day. Forex is only interesting because of the leverage. The currency pairs themselves rarely move more than 1%, and that’s usually on major news.

リスク管理

Every employee knows that they’re only one mistake away from getting fired. That’s the reason that everyone hates having a boss. There’s a single person with unilateral authority to financially murder you. Who’s going to look upon that as a good thing?

まあ, the truth is that bosses exist for a reason. It’s someone that calls you out when you do something stupid. もっと重要なこと, the boss has the power and influence to ensure that you stop doing stupid things.

The dream of entrepreneurship is not having a boss. You go on vacation when you can, you don’t have to play office politics, you don’t have to waste time selling good ideas. You just go out and do them.

Even with good strategies, the profitability of your algorithm is as simple as choosing the cheapest broker

I can tell you as a small business owner that the negatives stand out strongly in my mind. When you don’t have someone to hold you accountable, even if it’s a mentor, you make many more dumb mistakes than you should. It takes incredible discipline to hold the line consistently. Knowing that I’m not going to look stupid or have to explain myself to anyone probably gives me a lot more false confidence than I really need.

Self-employed traders working at home experience the same thing. Who calls you out when you’re trading just because you’re bored?

The decline in the trading account points out the obvious, but that’s not enough to necessarily stop the bad behavior. We’re social creatures. Most people need to speak with other people to maintain their sanity. When you’re trading at home alone, it takes a lot of effort to ensure that you’re getting enough social contact. A good boss prevents you from indulging in bad behaviors.

結論

Selecting the right broker is enough to determine whether or not a good strategy will wind up making money or not. It’s expensive to trade. The bigger you are, the better your pricing.

Retail trading prices have reached a point where it’s at least possible to trade profitably. それにもかかわらず, the number of strategy types out there is limited because the lower, shorter term strategies are prohibitively expensive to trade.

The quantitative traders and hedge funds get the more active strategy space to themselves. Their trading costs are so low that they’re really the only people that can afford to trade actively.

私のブローカーは、私のエキスパートアドバイザーを盗むことができます。?

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私はよくインターネット上これを出すに十分なそれの時間この質問を取得します。. There are plenty of reasons for traders to remain wary or suspicious of their broker. If you’re using the broker’s software, can they steal the expert advisors in your account that are making money?

Steal MT4 expert advisor

Can the broker steal your EA for MT4 or MT5?

The answer is an emphatic no. I started my career working as a broker and have been involved with forex for 7 years this month. I’ve seen the backend systems and tools that the MT4 brokers use to manage clients and their positions. I’ve also seen them on the floor of one of the MetaTrader bridge companies.

The brokers use a piece of software called the MetaTrader Manager. The manager is basically a database that tracks the open positions and equity for clients. It does not have a button for sucking MT4 expert advisors from client accounts.

Testing Shaun’s Euro Currency Scalping Strategy

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Back in March, Shaun published a Scalping Expert Advisor that traded the Euro-USD five minute chart using moving average envelopes. In case you missed it, here is the video Shaun made explaining the strategy:

Shaun’s strategy was recently featured for an in-depth post by Jeff from System Trader Success. その記事で, Jeff attempted to test and develop Shaun’s simple scalping strategy. Here is how Jeff described Shaun’s strategy:

Shaun noticed that extreme price moves as defined by 1% distance from a 200-period simple moving average (SMA) occurred very rarely. Going with the premise that price will soon retreat from such an extreme, this might be a potential location to open a trade. 要するに, Shawn’s Simple Scalping System (SSS) is a mean reverting strategy that utilizes a SMA envelope. When price closes beyond the envelope a trade is opened. The trade is closed when price returns to the envelope.

Jeff’s rules were exactly the same as Shaun’s. He tested the strategy from May 2001 12 月まで 2011 starting with $10,000. The first thing he noticed was the severe impact slippage and commissions would have on the returns. After testing a few different combinations, he settled on using a $5 commission and 1 Tick slippage on each trade.

Jeff’s results show the system to have a profit factor of 1.10. He notes that the profit factor is 1.38 on the long side and 0.88 on the short side. そのため, he elects to focus exclusively on the long side trades from that point forward.

currency scalping

Shaun’s simple currency scalping strategy has an edge.

The open ended downside of the system leaves Jeff thinking that adding a stop component may improve performance:

Notice that many of the trades that experience a 1000 or larger drawdown end up being red points on the chart. These are very expensive drawdowns that turn into large losers. Somewhere between $600 と $1,000 might be a good place to put a hard stop to limit those large losses.

しかし, finding the right stop proves to be challenging:

Stop values up through $2,000 really push our net profit down. Can anyone really trade a scalping system that might require a $2,000 or more catastrophic stop loss? This makes me wonder if we need to find an additional filter to help reduce unprofitable trades. Instead of simply applying a hard stop we might want to test trading only during certain hours, trading only during a bull market or adding a volatility filter. These are all good ideas and we’ll continue to explore this trading system in a future article.

Much like Shaun originally suggested, Jeff comes to the conclusion that this strategy has merit, but needs further development. He suggests a number of potential components that could improve the returns.

 

 

Keeping up with the humans

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Daniel Fernandez posts a nice summary of some of the problems algorithmic traders have experienced over the past few years. If you’ve been wondering why your expert advisor isn’t making money, まあ, you’re not alone.

Daniel points out the terrible performance of the Barclays systematic trading index and its nearly three years of continuous losses. Even the pros are losing money consistently.

Tough Times with Algorithmic Trading

Barclays system traders return

The performance of professional systems traders has fallen over the past two years

Key sections:

It is no secret that algorithmic trading had some “golden years” between 2008-2011. Through this period – most notably due to the high directional volatility of the financial crisis – systems based on a wide variety of market characteristics were able to obtain high amounts of profit, with an almost completely negative correlation with equity markets. Among the high-performers found during this period, trend followers were perhaps the most impressive, with some systems achieving returns of more than 100% of capital within this period, with little drawdown whatsoever. During these years everyone trading algorithms was making a killing. その後、, change happened.

 

The answer seems to be simple and at the same time incredibly complex: fundamental influence and uncertainty. Algorithmic trading systems are all designed with the idea that some historical assumption will continue to be true in the future. This assumption can be that price tends to break at a certain hour, that momentum created in one direction leads to continuations, that two instruments are co-integrated, など. When these assumptions break, the algorithms fail because they have no way to know that under current market conditions their assumptions are no longer valid. This “breaking up” of algorithms means that we usually need to take loses to realize that something has changed – to remove or modify our strategy – and this makes us invariably less reactive than human traders. The strength of algorithmic trading, it’s high capacity to exploit structural characteristics, becomes its weakness when the underlying structure changes.