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How Automated Should Your Trading Strategy Be?

12 月 31, 2013 によって アンドリュー ・ セルビー Leave a Comment

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.

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: automated trading, 専門家アドバイザー, manual trading

Automated Trading

12 月 28, 2012 によって ショーンオバートン 2 コメント

Nathan Orange contacted me in early 2012 looking for advice about automating a grey box strategy. Through the course of our conversation, it turned out that he was a profitable trader with a multiyear track record. Nathan has gone on to found his own forex signal service at Global Trend Capital.

Nathan conducted this interview with the intention of informing his readers about automated trading. You’ll have to pardon the vanity of publishing his interview of me, but I believe it’s useful for my own readers.

Nathan Orange

 

(Nathan):
ショーン, good to talk to you again and I appreciate you taking the time to discuss what I consider a very important topic. Before we jump into the specific questions, let’s fill everyone in on your background.

 

ショーンオバートン(ショーン):
I led the sales effort for the Sentiment Fund at FXCM, which was a fully automated strategy based on the market positioning of retail clients. I needed to understand how it worked in order to answer client questions. That interaction with the systems desk gave me access to one of the tiny handful of people in the forex industry that really knew anything about systems trading and analysis.

I tried trading manually during work hours, but as a broker, it was really difficult to manage trading accounts and to squeeze in 100+ attempted phone calls per day. I also suffered from the usual sob story that every trader endures. Account #1 blew up in 3 ヶ月. Account #2 blew up in 6 ヶ月. That was the first $5,000 thrown down the pit.

Technical analysis with its trend lines and other tools are hocus pocus pseudo-science. I traded like that for nearly a year, but I never felt confident or comfortable with the idea that subjectively drawing lines on the chart leads to any useful information.

The idea of quantitatively defining a strategy allows for testing and analyzing an idea to determine whether or not it really held any merit. The first non-technical analysis idea I had was to look at unusually big bars with the idea of fading those moves. Access with the FXCM Systems desk helped shape my idea from a subjective idea like “big bar” into a mathematical parameter like “standard deviation”. They also explained trading platforms to consider and recommended a few programmers to help develop the idea.

My experience working with programmers was uniformly terrible. I tend to dive into projects, so rather than depending on the clown-car brigade to half-develop my ideas, I wanted ultimate control over the development process. That eventually led to 20+ hours per week programming and analyzing strategies at home after working all day. The system design bug bit hard and never let go.

Nathan Orange(Nathan):
One of the most common concerns when discussing back-testing is over-optimization. From your perspective, what are some of the common mistakes that most system developers make? I have my own list, but we can discuss those further when we turn the tables.

ショーンオバートン(ショーン):
The basic kernel of the idea either has merit or it does not. There is no secret set of magical inputs that turns a bad strategy into a good one. Bad inputs, しかし, can turn a good strategy into a bad one.

Optimization fails to differentiate between “profitable” and “good”. I flog this dead horse constantly, but the most confusing thing about trading is that you can trade by flipping a coin and setting a 50 ピップを停止, 50 pip take profit and actually come out a winner – sometimes. Most of the winners will show small profits. A tiny handful of them would show gigantic profits purely as the result of luck. What’s worse is that most of the profitable traders will actually believe that they are the reason for their success when it’s really just dumb luck.

Optimization is usually the process of finding the luckiest accidental winner. It’s no wonder that optimized strategies almost universally fail going forward. The real task is to distinguish between ideas that are inherently non-random versus strategies or expert advisors that coincidentally make money from a random process.

Nathan Orange(Nathan)
Based on your experience and knowledge, if someone sends you a system to code can you quickly determine potential issues with their logic, or even over-optimization red flags? たとえば, you might a get a system a trader or hedge fund wants coded that has so many specific variables that you know immediately it won’t be robust. I can usually spot these issues from my own system development experience, but from your perspective as a coder is it fairly easy to recognize?

What do you do in those cases? Are most clients bull headed, avoiding any feedback or are they more open minded to listen?

ショーンオバートン(ショーン):
We see our primary role as that of a construction worker. If you want to build an ugly house, that’s your affair. 反対側に, if you solicit my opinion, I won’t hold back telling you it’s the ugliest house I’ve ever seen.

People frequently ask, “Do you think this will work?” I almost always answer no, and then they hire us to build it anyway.

興味深いことに, strategy development is very similar to trading in that people get emotionally attached to ideas. Even in the face of strong warnings, they charge ahead. A dear friend of mine opined on the subject, saying, “A handful of people don’t try. An even smaller handful listen to good advice. The rest of us learn the hard way.” Most people require the experience of falling flat on their face before they learn the lesson behind the advice.

If you’re motivated enough to ask a programmer to build a strategy for you, it’s because you already know that it is something that you really want to try. I could bluntly say, “This is going to wind up in tears.” 95% of people go ahead with the project, とにかく.

Despite my knowledge of markets and systems, I’m not an oracle, いずれか. I’ve told people that I thought their ideas were bad, only to have them come back a year later and tell me they’re making money.


…….Stay tuned for Part II when we discuss HFT, more back-testing issues (including those unique to Metatrader) and if there are common themes to successful systems.

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: アルゴリズム取引, automated trading, FXCM, 最適化

固定小数マネーマネジメント

4 月 10, 2012 によって ショーンオバートン 8 コメント

固定小数お金の管理は、あなたの取引の全体的な結果を変更. 取引は数百の取引の正味の結果であることを忘れないでください. お金の管理のパワーは、数百の取引以上後に場に出ます.

でランダムに完全トレーディング 50% 勝率とのR倍数 1 何の利点が得られません, 私は先週説明したように モデリングお金の管理. R倍数は平均損失に対する平均勝利であることを忘れないでください. このようなシステムは、どちらも利点や欠点を提起. 平均結果は、開始残高に極めて近い出てくる必要があります.

固定小数お金の管理は、ベル曲線のいくつかの部分を伸ばし、それ以外の領域を圧縮. 我々はそれに入る前に, それは小数お金の管理手段を固定するものを覚えておくことが重要です. それはシンプルなコンセプトのための複雑な名前です. これは、現在のアカウントの株式のセット率ではなく、起動株式を危険にさらすの考えを表し.

ほとんどのトレーダーは、次のような設定金額を危険にさらすに注力 $1,000 与えられた貿易. この方法は、一つ一つの取引後にそのドルの数字を更新.

口座残高がで始まり例を考えてみましょう $100,000 危険にさらします 1%. どちらの方法は、最初の取引で同じ量を危険にさらします, $1,000. 次の貿易, しかし, 異なるリスク量を得られます. 以前の貿易上の勝利はにアカウント持分を増加させます $101,000. の1% 101 壮大です $1,010 次の貿易上のリスクの. なんと10ドルの変更.

それは些細に見えるかもしれません. それは長期的に最も確かではありません.

例

コイントスゲームを果たし、次のような特徴を備えたシステムを持っているトレーダーを考えてみましょう:

  • 彼はで始まります $100, 000 勘定残高
  • 彼のR倍であります 1.0
  • 彼が勝利します 50% いいえ取引コストと時間の
  • 彼はリスク 1%

の固定ドルリスクとコイントスを再生する最悪の結果 $1,000 の喪失であります $46,000. その困難なドローダウンの間に固定された分数のお金の管理を追加することの少ない実質的な損失にドローダウンを向上させます $37,500. 最悪ドローダウンがから行きます -46% 宛先 -37.5%. この方法は、絶対的な最悪のシナリオをドラッグし、近い平均にそれを引っ張ります. とき不運, 壊滅的なドローダウンキックで, 技術はトレーダーの経験、その損失を低減.

固定ドルのリスクのための最良のシナリオがあります $58,000 (58%) 戻り値. システムに資金管理を追加すると、劇的にさらに右に最良のシナリオを伸ばします. それはに向上します $76,000 戻り値 (76%). 良い時間は、取引システムについては、まったく何も変更せずにどんどん良くなっ. この方法は、平均から離れてプラスのリターンを伸ばし. トレーダーは、彼のポケットの中にもっとお金を離れて歩きます.

自然な本能は、固定小数のお金の管理を移動するための方法であると結論することです. 賛成です. これは完全にランダム戦略のリスク報酬のプロフィールを改善. ほとんどのトレーダーはドローダウンのような重要な考慮制御パラメータを助けるべきである実際の取引システムに追加し、リターンを最大化.

一定の分数を使用する重要な帰結 お金の管理, しかし, であること幾分下の平均収益の増加を受けてのオッズ. コイントスゲームは平均リターンの下に苦しんで 47% 時間の. 固定小数お金の管理を適用するには、以下の平均リターンの可能性を増加させました 53%. 効果はすべてのことあまりないです. 失う可能性が高いです. しかし、それが発生したとき, 、 “損失” それも破壊と考えることができるように無視できます.

乱数は時折、このような損失勝敗・ウィンなど、一見非ランダムパターンに従います. これが発生した場合, 損失の貿易のサイズは、受賞者の取引サイズよりも大きいです. 勝率は正確に出てくる場合でも、 50%, それらの勝利はわずか敗者の陰に隠れます. 利益よりもわずかに大きい損失のマイクロ効果は期待と同じくらいのお金をしていないのわずかに増加リスクとして表示されます.

すべての結果をグラフ化

Fixed fractional curves

固定小数お金の管理は、リターン曲線の形状を変更します. この例では、効果を強調するために誇張されています

緑地は、受賞者を表している赤の領域は失う結果を表します. お金の管理は、赤の領域に緑の面積の割合を最大化について実際にあります. 利益のない期待してランダムな取引は釣鐘曲線が得られます, 左側に表示されます.

固定小数は少し左にリターンの最高密度を移動. そうすることで無視できる損失のわずかに増加リスクの些細な欠点を作成. 重要なこと, 左端 (最悪の場合の敗者) 平均にかなり近いドラッグます. 右端 (最良のケースの勝者), 平均値からさらに大きく伸ばします. 緑豊かなエリアは現在、赤面積よりも大きいです. ランダムシステムは、プラスのリターンを生成するマイナー期待を持っています!

以下の下でファイルさ: お金を失うことを停止します。, 戦略の取引のアイデア タグが付いて: 勘定残高, アカウントエクイティ, automated trading, 専門家アドバイザー, 固定小数, メタト レーダー, お金の管理, ninjatrader, R multiple, 戦略, 勝率

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