algorithm Archives - アルゴリズムと機械の外国為替戦略

Analyze your Trading Algo with 3D Charts

6 月 28, 2016 によってリオル Alkalay Leave a Comment

These days, any mention of the term 3D is associated with entertainment. But in fact, when it comes to charting, and more specifically to charting your trading algo, 3D charting is not only insightful but provides important practical advantages.

The most common chart to measure a trading algo is profit over time. That lets you know how much money the algo is making over a specific duration, usually from a few weeks to several months. As the chart below illustrates, it gives you a good idea how well your trading algo performs over time and it gives an indication of the periods when it was underperforming.

The thing is that, while profit over time are the two most important dimensions, they leave plenty of dimensions out—dimensions that can help you answer important questions. Such as why, during a specific period, was your trading algo under-performing? Or how much risk are you taking in a given time? 多くの場合, the answers to such questions can be the difference between profit and loss, between success and failure of a strategy.

Trading Algo in 3D

First things first. Before we start running 3D charts on our algo it’s important to go over a few practicalities and make the 3D chart work for you.

Assuming you’ve already exported the data of your algo Profit and Loss to Excel you’re likely to have two columns of data, 例えば. Time and Profit. Adding a third column will allow you to run a 3D chart, whether it’s volatility, risk or whatever additional dimension you deem necessary.

Once you have your three columns you click to generate a chart—you must choose a type called 3D surface chart. As you will notice, almost always, the Time stamp will be the X-Axis, Profit the Y-Axis and our third parameter will be the Z-Axis.

Now comes the important part—making the chart comfortable to work for us.You must remember that our goal in using a 3D chart in the first place was to identify areas of either exceptional profits or exceptional losses to optimize our algo.

As can be seen in the charts below, Excel divides the Y axes into ranges and each range is colored. The best practice is to choose the same color for levels that are not exceptional and select a contrasting color for the highest range and another for the lowest range. This allows us to spot the exceptional.

The Z axes changes the angle of the chart; the steeper the angle, the higher our Z parameter—say risk or whatever else we choose.

そして最後に, make the 3D chart clearer through formatting the Plot area. Play with the Y rotation angle as well as the Debt Level until you are comfortable working with the chart

Trading Algo Case Studies

Once you are clear as to how to make a 3D chart, it’s time to decide which dimension is relevant. 通常, besides time and profit, the following dimensions are worth considering—risk, volatility and duration.

たとえば, the chart above shows a profit over time of a specific strategy; let’s call it Strategy A. 突然, out of the blue, the profit plunges rapidly. It’s not clear why, yet.

Then we add another dimension—risk. リスク, in this case, will be the Dollar amount risked in a given moment. 今のところ, the reason is apparent; just before the profit collapsed, risk was rising, 同様に. Maybe leverage jumped, maybe several positions were opened simultaneously; it depends on the strategy. But by using a 3D chart we were able to easily detect where trouble was coming from.

Using 3D charts is not only good to spot weaknesses in a strategy but strengths. Let’s take a look at another strategy, which we’ll call Strategy B.

We will test how Strategy B performs during volatility. この場合, the volatility will be the standard deviation of each pair we trade. What we see is interesting. When volatility is high, Strategy B performs exceptionally well and not so well when volatility is average to low.

In such a case, we should consider using the strategy only during high volatility to optimize returns.

More uses could be to measure duration per trade. If the duration is getting longer at certain areas perhaps the trigger for the entry or exit is not working well. The benefit with using a 3D chart here is that we put the opening time stamp on the X-Axis and the closing time stamp on the Z-Axis so we can actually analyze duration per trade over time. A 3D chart then is much more accurate than a two dimensional chart where duration is a trailing average.

結論として

There are endless samples and ways in which 3D charts can allow you improve your trading algo and identify both weaknesses and strengths within your strategy. 確認して, you can manage with a 2-dimensional chart. But the benefit of 3D charting is that, many times, it allows you to zoom in and identify areas of change much easier.

Become an Algo trader in Baby Steps

4 月 4, 2016 によってリオル Alkalay 10 コメント

The world of traders is divided into two groups; those who trade using algorithms and those who don’t. Those who trade using algorithms, aka algotraders, are well aware of the advantages of trading with an algo… And for those who don’t use algos? They are equally aware of the algo advantages but are reluctant to dive into its complexity; they are deterred from learning how. But the road to success in trading is not by avoiding challenges, but overcoming them, perhaps in baby steps.

First Baby Step to becoming an Algo trader

Let me ask you a question. What do you think is the first thing you’d need to do to become an algotrader? You might respond, “Learn programming, もちろんです! How else?” Well, you’d be wrong.

If you plan to learn programming for the sole purpose of becoming an algotrader, you’re likely to get lost. 最終的に, in despair or frustration, you’ll give up on algotrading.

There are numerous languages, from MQL to R to Python, and you have to decide which one to start with. You might find yourself wasting valuable time learning far too many trivial functions. It may take quite a long time before you even create a trading algo, let alone a profitable one.

But there’s another way, which I call reverse engineering.

The first step is to figure out which trading algo you want to make. 他の言葉で, what are the functions and strategy it should implement? Then you test it and finally, move on to the programming part. This way, you’re focused like a spotlight. You know exactly what your algo should do and can focus on the exact functionalities you need to learn to make it happen.

Everything will just come intuitively; which language, how and in what. All the pieces will fall much quicker into place because you already know what to look for.

The best way to start is by using a flowchart. It is actually one of the first things you learn in programming schools.

And what determines the flow? もちろんです, it’s the conditions. What we call the “ifs.” “Ifs” can be one condition or have many “ands” and “ors.” That’s how you decide what your algo should do in any given circumstances. The conditions to the algo are what the brain is to the body; they do the thinking.

Second Baby Step: Use Excel

Once you’ve made a flowchart of conditions, rather than using a complex tool, use Microsoft Excel or some other spreadsheet software.

ソース: MT4

Extract historical data of a price data; start by using only the closing price. If you want to trade on a daily interval, extract daily data and so on. Use a separate column for each of the conditions in the flowchart, that way it’s easy to write and figure out. Add another column for a buy and sell output to mark when you “opened” and when you “closed” a position. And finally add one column of accumulated profit/ loss.

Use separate columns for each conditions and fill the chart. All you need now is to run a linear chart on one column, accumulated profit/loss, and look at the algo’s historical performance.

Once you master the basics you can move on to move advanced back-testing and curve fitting. But for a start that will do.

最後に, Learn to Program

わかりました, you’re not a “baby” anymore; you have a good idea of what an algo trader needs to do. Now that you’ve got the concept down pat, you’re ready to begin learning programming.

In terms of which language to start with, that will depend on the circumstances. If you are already using an MT4 platform, it’s a no brainer; learn MQL which runs on MT4. The MQL website is filled with “how to” materials. And since you already have a diagram of your algo and an idea what you want to do, finding your way should be simple.

But if you trade with a different broker, you’ll have to decide which best suits. 自ら, I recommend starting with MQL, just because it’s easier. その後、, you can move into Python, which is a rather easy language to learn or C++ if your algo needs to work fast. If you algo is heavy on the math then perhaps R would fit.

Here are some places you can learn online:

または, もちろんです, you can learn from a book. I am more of a book person, but that’s just me.

Then there is another issue—API. API is the mechanism that enables your algo to communicate with your broker and execute your trades. Some brokers work better with certain programming languages than others. Most large brokers have communities and forums that can go into detail as to the best way to use an API.

Unlike the first two baby steps, no one would ever say that learning to program was a baby step. むしろ, it’s more of a giant leap. It takes time to learn and to master, though it is worth it in the long run. Meanwhile, you can always use libraries of codes on the web for more complex algos. The thing is that once you’ve accomplished the first two baby steps, making the final leap into programming is a no brainer.

34 日の EMA との取引外国為替スイング Trendless 市場で勝つ

4 月 29, 2014 によってエディ・花 31 コメント

外国為替スイング取引利益を収穫機械の取引方法は、いくつかの日に 1 つの期間にわたって外国為替ペアから. いくつかの外国為替スイング取引戦略は、trendless 市場で退屈な結果を生成します。. まだ, 34 日間の指数移動平均に基づく戦略がうまく見つけた, 範囲横に市場の中にも.

外国為替スイング取引の戦略は、以下のと, 短期的価格傾向と私逃して可能性がありますそうでなければパターンを活用する私機械的な取引システムを使用してください。.

最初, 用語「外国為替スイング取引」を定義しましょうそれは短期的な価格の変動 ' に基づく取引を意味します。外国為替ペアの価格移動」スイングポイント間前後,"全体的な価格の範囲またはチャネルの変曲点が.

スイングトレードの方向が長いまたは短いのいずれかをすることができます。. 外国為替スイング取引のポジションは、デイトレードよりも長い期間の通常開催します。, 購入してホールド戦略よりも短い時間を含む数週間または数ヶ月のための位置を保持しているが、.

外国為替スイング取引を提供しています理想的な機械的取引戦略私のような独立したトレーダーのため, 私のアルゴリズムから取引システムすぐに認識しより効果的に大規模な機関投資家よりも短期的な価格変動を利用.

外国為替の基本スイングトレード

一部のトレーダーは、スイングトレード株に適用が, 私の経験で外国為替スイング取引スイングトレードの完璧なフォームは、します。.

と, 外国為替スイング取引はデイトレードや、長期的な傾向の取引よりも良い. ここでは、私の推論: デイトレードは良いことができます一晩のポジションリスク管理業者が保持していないので、, それはまた、潜在的利益を制限します。, 以来、大規模な価格が一晩で発生することができますに移動.

長期的な価格の動きの利益をキャプチャ可能性があります傾向の取引, まだそれはまた傾向の予想の続きを待っている間気になるドローダウンに直面しての位置にトレーダーを置きます.

外国為替スイング取引両方の世界の最高を提供しています: それは傾向の取引日の取引の利点, しかし、いずれかのメソッドの欠点がなく. 通貨市場の 20 4 時間の性質はスイングトレードに最適.

私の機械取引システム, 傾向の取引とデイトレードの 2 つの両極端の間の偉大な妥協案をお楽しみ. 外国為替市場における短期的な動向を見つける, 収益性にそれらに乗る, 私は私の位置を終了し、右価格移動終了時.

私機械的な取引システムは、小さいながらも一貫した利益を時間をかけて追加を収穫します。. どうやら trendless 市場においても, 成功することができます。.

私の取引は、リアルタイムで自動データ分析に基づいています。, 私の取引 algos 提供超高速取引の実行. すべてのベスト, 私の取引の決定は、特定の市場についての私の感情ではなく客観的なパラメーターに基づきます.

外国為替スイング取引ルール

成功した外国為替スイング取引へのキーは、最高のエントリと終了ポイントを知っています。. 最高の指標と効率的なアルゴリズムを使用して機械的な取引システムの魔法を使って, 完璧なタイミングが必要ないです。.

外国為替スイングすることができますに基づいてルールのシンプルなセット, またはよりやや高度な一連のルールを使用する、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。, すれば.

外国為替スイングで, 私機械的な取引システムの forex 通貨ペアを売買することの数学的な規則や指針のセットを使用してください。. 私機械的な取引システムではなくマニュアルでの取引に依存して, 私はいくつかの利点をお楽しみください。.

最も単純なアプローチの中を使用して、外国為替ペアの価格を測定するもの 3 終値に基づく別の移動平均.

貿易外国為替ペア「長い」のときに、機械的な取引システムをプログラムそれら 3 移動平均線は上向きの方向に揃え. 同様に, 外国為替のペアは、「短い」とき取引されて、 3 移動平均線は下向きに向かっています。.

私の外国為替スイング取引戦略のしくみ

かなり短期的な価格の動きを活用することができます戦略取引外国為替スイングを使用してください。, だから私は全体的に trendless 市場においても利益ことができます。. 私は信頼性の高い短期近似曲線ブレイクアウト戦略を持っています。, 典型的な勝ちトレードからのかなりの数のピップが収穫できると.

移動平均線の時間枠の最適な長さを使用するトリックは、します。, 適切な移動平均の種類だけでなく、. 単純な移動平均を使用してではなく (MA または SMA), 指数移動平均を使用する私の機械取引システムをプログラムします。 (EMA).

EMA は普通の MA と同様, それは最も最近のデータをより多くの重量を与えることを除いて. EMA は単純な MA よりもに最新の価格の変化にすばやく反応するので、私はこれを行う.

この種類の移動平均は、私が時間の長い期間にわたって表示されます trendless 市場で勝つことができます。.

一部のトレーダーが 12 日または 26 日のどちらかの EMA を使用します。, 特に人気のある移動平均収束発散などの指標を作成するには (MACD) インジケーター, または割合価格オシレーター (PPO). と, 比較で, 50 日と 200 日 EMAs 頻繁に使用される信号の長期的な価格動向の変化.

代わりに, 外国為替スイングの取引のため、私は 34 日の EMA を使用します。 (34ema とも呼ばれる) それを見つけたため外国為替市場で中期的に短いトレンドの方向を判断する最良の方法を提供しています。.

もちろんです, あなたは、あなた自身の選ばれた市場期間後部-検定試験別で試すことができます。. 試してみる 7-, 14-, 25-, または彼らはあなたの特定の外国為替のペアの良い仕事かどうか参照してくださいに 50 日 EMAs. まだ, 私自身の長い研究の後, 私にとって、34ema は最適します。.

外国為替のための私の「購入する」ルールスイングトレード

私機械的な取引システムを使用してください。, 近似曲線のブレーク直後後外国為替スイングトレードを入力します。. 34 日の EMA に基づく, 私機械的な取引システムが価格集会または撤退を監視します。. その後、, すぐにつまずくその集会または撤退, 私機械的な取引システムは、貿易を実行します。.

だから, ここでは、使用する手順です。. 私は私の機械的な取引システムをプログラムします。:

1. 近似曲線から下方のブレークのための時計;
2. 価格が 34 日間の EMA より上に移動を確認します。 (34ema);
3. 近似曲線のブレークアウト下後, 後続の燭台の価格の高値を見る;
4. 信号のローソク足を見るを待つ; 前のろうそくの高よりも低いである高いキャンドルになります;
5. そのキャンドルの高が破られた場合, 私のシステムはすぐに市場価格で購入します。;
6. または, 私のシステムは、購入する停止の順序の信号の高のみいくつかのピップを実行できます。; ローソク足; その方法, 価格は、その高さを違反する場合, 私の注文が実行されます。;
7. 私購入する指値注文はトリガーされない場合, および下位の高値を設定するのには、燭台を継続, 私のシステムを形成するそれぞれのローソク足上連続して低高購入ストップ注文価格を移動します。; 最終的に, 価格は上方を移動し、私の注文をトリガー.

外国為替リスクマネージメントの目的でスイングトレード, 私機械的な取引システムが自動的に配置ストップロスオーダー注文を引き起こしたろうそくの低下でちょうど少数のピップ.

私は短期のスイングに乗る, 利益を収穫し、この記事で後述するように、リスクを管理.

私を「売る」ルール外国為替のスイングトレード

私の外国為替スイング取引システムの「販売」ルールは、「購入する」ルールの正反対. 主な指標として、34ema を使用してください。, 私機械的な取引システムが:

1. 近似曲線から上方ブレイクアウトのための時計;
2. 価格が 34 日の EMA の下にあることを確認します。 (34ema);
3. ブレイクアウトの後, 燭台の価格最安値を監視します。;
4. 信号のローソク足になります前のろうそくの低よりも高い低にあるもの; そのキャンドルのローが壊れているとき, 私機械的な取引システムはすぐに市場価格で販売しています。;
5. 別の方法として, 私の外国為替スイング取引プログラムは信号のろうそくの低下のピップのちょうどカップル購入ストップ注文を設定できます。, 価格低に違反した場合、, 私の注文が執行されます。.

と, 優れたリスク管理は外国為替スイングで生存のために不可欠なので, 私機械的な取引システムだけで私のエントリの順序を引き起こしたローソク足の高いストップロスオーダーを設定します。.

利益目標を設定し、外国為替スイングトレードで利益を管理

外国為替スイング取引の作品が最高の私は貪欲ではないとき. 一部のトレーダー, 特にそれらが取引戦略だけ収益性の高い大規模な移動中に, すべての貿易のうちあまり絞るしようと. これにより, 彼らはしばしば貿易からのすべての利益を失うリスクします。.

私は別の哲学があります。. 以来、市場は、trendless または取引横に時間の長い期間のため, 私の取引の機会にたくさんあります。. それぞれの貿易で「殺す」ように急いでではないです。. 多くの取引から少量を得るためではなく、, その方法は私にとってリスクが少ないので.

貿易は私の方向に行くし、私は利益をゾーンに, 現在の価格の背後にわずかに沿って移動トレーリングストップを使用する私の機械取引システムをプログラミングによって私の利益をロックインします。.

私は歴代の押し目のそれぞれ上または下のわずか数ピップのトレーリングストップを設定する私の機械的な取引システムを使用し、外国為替スイング取引中に上昇. 私外国為替のアルゴリズムは非常に短期の支持と抵抗のレベルに基づくトレーリングストップを選択します。.

末尾を設定することによってこの方法を停止します。, 私はたいてい途中で停止を避けます. 短期的な傾向が続くなら, 私はしばしば数日間それに乗ることができます。.

と, 私は常に取引の機会の多くがあります。, 私に対してなる限界貿易のままに圧迫感ではないので.

利点と外国為替スイングトレードのリスク管理

大きな利点に短期の近似曲線と価格のアクションを使用してください。. 価格がその近似曲線を突破, それは通常、トレンドを変更する記号です。. 新しいトレンドの先頭に新しい取引を入力する私に役立ちます私機械的な取引システム.

私の 34 日 EMA 外国為替スイング取引戦略私の多くを与える利点限り、適切にリスクを管理. この戦略は、私ことができますいくつかのトレーダー体験を長期的な動向に従ってくださいしようとして大きなドローダウンを回避しながら短期的な傾向との貿易.

私の 34 日間の外国為替スイング取引戦略はほとんど外国為替スイング取引戦略上の重要な利点を提供しています. 移動するので平均は本質的に遅行指標, 成功への鍵は、右の時間枠を選択します。.

多くの外国為替戦略は単純移動平均または長期移動平均に基づいてください。. だから, trendless 市場で通常実行が不十分な. まだ, 私の 34 日間の EMA 戦略は長く MA より有効期間を使用して、.

私のシステムの利点を楽しむために, 適切にリスクを管理する必要があります。. 全体的な, 外国為替スイング取引のリスクは、投機的な取引の他のタイプに匹敵します。.

最短時間の期間にわたって完全に trendless である市場で, それは私私の停止損失がかなりタイトであることを確認するために重要. 反対に, ブルやベア市場では外国為替スイング取引さらに利益することができます。.

時々, 市場は私の機械的な取引システムで「スイングポイント」は検出されません時間のような短い期間で突然の鋭い動きを作る. ギャップアップ、ギャップダウンの吹き出物が私機械的な取引システムが効果的に対応することができるではないので、すぐに起こることができます。.

まだ, 34 日の EMA を使用して, 私は通常ほとんどの市場の動きに参加することができます。, 全体的に trendless または横の市場で偽の信号を回避しながら.

34-日 EMA は私にとってインジケーターの取引最高の外国為替スイング

私にとって, 外国為替スイングの取引の最高の基盤は、34 日 EMA のインジケーターを使用して. 私は開発に使用し、私の機械取引システムのための勝利の戦略を微調整. それは私が「両方の世界の最高の」ご利用いただけます、移動平均線の長いまたは短い期間に trendless ことがあります市場に.

と, 外国為替市場で 34 日 EMA の戦略を使用して唯一のトレーダーではないです。. 過去数年間にされているいくつか研究外国為替について取引指標として 34ema を使用してスイングします。, 十分なだけでなく、記事・トレーダーびびりこのタイプの戦略について.

場合は、深刻な外国為替トレーダー, あなたは少し trendless 見える市場でイライラしていると, 私は外国為替スイング取引のための 34ema 戦略を試してみることをお勧め.

サポートとレジスタンス

9 月 11, 2013 によってティモシー・ Lewkow Leave a Comment

The Limit Order Book is lurking behind every price tick in every market you can imagine. From the ill-liquid real estate market, all the way to high frequency bond trading, the limit order book determines all price movements.

A simple example in my last post of supply and demand demonstrated how price changes in an equity market. I made several arguments justifying the existence of a bid ask spread, and showed how this leads to price formation. My goal in this post is to find clarity in the foggy world of support and resistance using limit order books. Support and resistance information can be used to build confidence when entering or exiting a trade.

Imaginary Price Levels

If you try searching for support and resistance, a wealth of information can be found usually in the form of some article accompanied by several charts with lines claiming to have found the magical levels.

Every such chart I have found, しかし, has one single thing in common. The stock price always, いくつかの時点で, just slightly crosses these horizontal lines. To me, it feels like a slap in the face… the ultimate I told you so from market experts that can apparently see into the future. Here’s a great example I picked up on Google.

フィギュア 1: Support and Resistance levels breached leaving question of imaginary lines.

I realize that mathematical definitions of these levels exist, and I realize that human psychological traits are often correctly considered. それにもかかわらず, they still lack precision! The arguments for true black and white support and resistance levels always must always have a fair amount of uncertainty. Sadly, this is just another part of working in this business.

If I see a price move past a resistance level in real time (すなわち, not being able to see the entire future nicely displayed in front of me like Figure 1), I often question if the level has been breached. This could perhaps leave you in the worst possible position as the market rockets the wrong way. The limit order book can reduce this uncertainty by displaying real information.

If you try searching for support and resistance, a wealth of information can be found usually in the form of some article accompanied by several charts with lines claiming to have found the magical levels.

Suppose a stock is testing a human psychological resistance level of $20.00 and your algorithm has signaled that you initiate a short position. You wish to enter the market at the highest possible price without missing the peak. More importantly though, you wish to confirm a resistance level still exists . If the current order book is displayed as below left, you would have confidence that enough sell pressure is present to hold the resistance.

フィギュア 2: The left side of the image shows more market depth on the offer (オレンジ), which is resistance. The right image shows light depth, which is the absence of resistance.

反対に, if the order book is displayed as above right, it it would take only a moderate collection of market order buyers to break the $20.00 レベル– and break it fast in this example. Short sellers would run to cover, and the market could swiftly move against you.

Measure Support and Resistance

I found some research out of Wharton suggesting an order book metric (cumulative depth), and have heard more advanced ideas shared in my personal research symposiums. ということで, I think this situation is being made too complex.

Translating the above example into math should be straight forward, and customizable to the strength of signal generated by your algorithm. Allow me to suggest a crude, yet effective starting place.

Suppose you are back watching an equity as it approaches what you think to be a $20.00 抵抗レベル. You need a metric to identify the strength of the resistance, and have one of the given order books displayed above in Figure 2. In the order book on the right, you could find the average price it would take a market buyer to pass four levels of depth. This calculation ((2*19.99+8*20+1*20.01+2*20.22)/12) shows resistance strength of 20.0008.

Using an analogous calculation on the left shows resistance strength of 20.0063, a greater value that can act as a metric defining a resistance level.

The more expensive it is to surpass a level of resistance, the less likely it will happen.

Exactly how this metric is created has many degrees of freedom. If you suspect a resistance level exists at $20.00, you could initiate a position that depends on how expensive a set of market orders would have to be to consume past the resistance. You could also alter how far deep to look when calculating the average price.

These two measures involve simple math, and provide a deeper insight to market movements. They are based on the absolute lowest levels of price formation by supply and demand, and are certainly items to consider when building a full system. In my next post, I will provide a more specific strategy to consider implementing.

自動化された取引 Ii

1 月 7, 2013 によってショーンオバートン 1 コメント

The second part in Nathan’s interview series with me focuses on the role of high frequency trading in the markets and testing trading strategies. If you missed the first automated trading interview in the series, you can read it here.

(Nathan):
Do you have any specific thoughts or opinions on HFT (High Frequency Trading)? This is such a hot topic among traders and I would imagine you have a unique insight into algo trading in general.

Do you see machines eventually replacing the “human” trader or could HFT eventually get banned from the markets? At least for day traders it seems to give quite an unfair advantage to the HFT camp for executions?

(ショーン):
There is a huge difference between algorithmic trading and HFT. HFT is obviously automated due to the speeds involved, but that does not imply that all automated trading is HFT. It’s only a subgroup.

(Nathan):
確認して, there are plenty of automated systems that are not HFT. I bring it up under the context that HFT uses deceptive algorithms for their order posting tactics.

(ショーン):
HFT is uniformly destructive to capital markets and their purpose. It nickels and dimes investors and traders through market manipulation. Just last week Nanex detected a single organization that pushed through 4% of all the order flow on US equities quotes. さらに悪いこと, not a single one of the orders executed. Posting orders without the intent to trade is blatantly illegal.

The other negative consequence of HFT comes from the rebates that the dark pools and exchanges pay to “liquidity providers,” which are really the HFT bots. The arrangement tangibly alters the motivation for participating in markets. Rather than investing or even speculating on price, the HFT algos generally do not care about market movements. They just want the liquidity rebate.

(Nathan):
This to me is the bigger issue. The whole arrangement is shady and as you said it alters the motivation for market participation. What steps or changes do you recommend?

(ショーン):
、 Market Ticker blog is one of my favorites on that subject. Karl Denninger advocates a regulatory rule of a two second minimum order time. I support the idea. Nobody can plausibly claim that an order placed for such a short duration is for any trading purpose. If an order is not intended to be filled, it should be not permitted.

(Nathan):
I cannot argue with that logic. Back to testing, how important is accounting for commissions and slippage to the integrity of any back-testing data in your opinion? To me, as you go down the scale from longer term trading to day-trading the importance grows exponentially.

(ショーン):
I fully agree. The consequences of trading costs pile up with increased frequency. Shorter time frames multiply the frequency, which as you pointed out, grows exponentially.

My personal preference is to skip trading costs and commissions on short time frames so that I can obtain a sufficient sample size for my analysis. I do not foresee myself ever trading on one minute charts, but I almost always use one minute tests to analyze randomness within a strategy. Unlike most systems developers, the profitability of a system is a backseat concern.

I read a newsletter this morning written by a multi-million dollar businessman. He concluded today’s article saying that if you start a business to make a lot of money, you’ll more than likely fail. You have to excel at providing a quality product and service in order to succeed over the long run. When the inherent business excels, only then does the long term money follow.

Trading is a business in precisely the same sense. Most traders rush through the system development process to spit out quick profits. They rarely, if ever, consider a strategy’s performance over a lengthy period of time. Everything is about the here and now. さらに, good systems frequently lose money. You need something more in the toolkit besides the random scorecard of profit and loss.

(Nathan):
Good systems do have losing periods, yet many traders seem to be convinced there is a “holy grail” approach out there that will buck this fact. If some of the most successful traders ever have posted losing periods (or even years) and have been around for 20+ years it seems hard to fathom beating their performance from day 1.

Regarding testing platforms, you were one of the first people that really explored the issues with back-testing Forex – can you provide more detail on the problems for those that are interested in developing and back-testing a system for FX (MetaTrader platform)?

(ショーン):
You’re opening a can of worms on this one. MetaTrader is hands down the worst platform available for backtesting. The data is notoriously unreliable. Even when good data is at hand, the instructions for importing it and turning it into something usable fill a dozen pages of instructions.

You’re much better off doing real analysis in NinjaTrader, TradeStation or MultiCharts. The metrics are vastly superior and require a tiny fraction of the effort. I still think that MetaTrader is sufficient for live trading most strategies.

(Nathan):
I am a huge fan of live testing/trading alternate strategies. One of my biggest “A Ha” moments came during live testing alternate exit strategies. I traded my account with my original exit approach but also demo traded alternate exit strategies in real time. There is value gained that you don’t always get from a back-testing print out. How do you compensate for slippage when testing a strategy?

(ショーン):
Forex is thankfully unique in that it doesn’t come with unique problems other than rollover. The markets are the most liquid in the world. As a retail forex trader looking at charts longer than five minutes, you can generally assume that the historical prices are reasonably reflective of executable prices for the strategy.

I compensate for slippage and bad ticks by doubling my expected transaction costs. たとえば, I pay 1.5 pip spread on the EURUSD. When I test a strategy, I demand that it must hold up on 3 pips transaction cost on every trade.

(Nathan):
Before we wrap this up, are there any specific strategies or common parameters that you have noticed in systems that make it? We both know how small of a percentage of traders become successful, but as it relates to mechanical systems are there recurring themes for those that are profitable?

(ショーン):

いいえ, there are no recurring themes that I see. The lowest common denominator is that they do not overtrade and that they use low leverage. Other than those two items, each successful strategy differs substantially from all the others.

The most important ingredient in system development is the developer. I have yet to program a successful trading system for someone without years of full time trading experience under their belt. You have to go through the school of hard knocks if you’re going to make it. Almost all of us are too stubborn to listen to good advice.

(Nathan):
ショーン, I can’t thank you enough for providing such honest responses and sharing your insight. If you are interested in learning more or considering coding your system, go to MetaTrader Programming for more information.