アルゴリズムと機械の外国為替戦略 | OneStepRemoved

以下が詳細です: ハロー効果 & グリーンランバー

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それは多くの場合、システムトレーダーはエントリーポイントと終了ポイントを完璧にしようと、あまりにも多くの時間を費やすと言われています. 我々はそのアイデアを拡張し、私たちは、取引活動の全てにあまり力を入れているかどうかを見てみたらどう?

教室で教えられているよりも、実際の取引から学習することがよりがあります. あなたは今、正常に取引することができます, あなたよりもより多くの知識を持っている何千人もの人々があるという事実にもかかわらず、.

二つのことはしていないとき “同じ”

Antifragileの書IVに, ナッシムタレブは、制度の学習から得ることができる実用的な知識の欠如に対処する章のかなりの部分を費やしています. 標準の大学のアプローチとは対照的に、彼は強く、学習の自己指向スタイルを提唱.

体系的なトレーダーとして、, 体系的なトレンド以下の戦略は高価な大学で教えられていないので、我々は、タレブは言及自己指向アプローチに従うことを余儀なくされています.

“あなたが脆弱である場合、あなたはantifragileているときよりもはるかに多くを知っている必要があります. 逆に, あなたはあなたがより多くを知っていると思うとき, あなたは壊れやすいです (ERRORに).” – タレビ

タレブは、トピックに関する知識が必ずしもその分野での成功にはつながらないという彼のポイントを説明するためにハロー効果とグリーン木材誤謬の両方を使用しています. 取引で, それは市場が異なる方法で動作する理由について議論する人気のあります.

何かが増加の脆弱性をなぜ起こるか理解するこの必要性. 多くのトレーディングシステムを作るために antifragile, 私たちは知らないものに私たちが知っているものに、より少ない焦点を合わせる必要があります. 私たちは、未来を知りません.

ハロー効果

“もっと面白い会話, 彼らはより多くの培養, 彼らは、実際のビジネスでやっていることで、彼らが効果的であることを考えることに捕捉されるより (心理学者が呼ぶもの 後光効果, でそのスキルを考えての間違い, 陶器のワークショップや銀行部門の管理にスキーがスキルに確実に変換すると言います, または、良好なチェスプレイヤーは現実の生活の中で良い戦略家であろうと). – タレビ

ハロー効果の最も一般的に使用される例, 最初のエドワード・ソーンダイクによって研究されました, 誰かの文字の特徴の我々の意見は、その魅力の影響を受けている場合に発生します.

ハロー効果は、ブランドマーケティングによく適用されます. アップルのiPodの驚くべき人気は、そのほかの製品の多くに大きな成功をもたらしました. 私は個人的にはApple製品でこの効果を経験しています.

長い時間のiPodユーザーされた後, 私は数年前のiPadを購入し、完全に吹き飛ばされました. iPadのための私の熱意は、私は次のiPhoneを取得するために必要なことを私に確信しました. 半年後, 私は、iPhone 4Sの誇りの所有者でした, 私に話して、それの内部に女性を持っています. 今私は、iPodを持っていたこと, アプリ, iPhone, 購入するノートパソコンの種類の決定は、すでに私のために作られました. 私はMacBook Airのを望んでいました.

ハロー効果は、アップルのためにうまく働いている間, タレブは、脆弱性を増加させることを示唆しています. 上記の引用の最後の部分で, 彼が実際の生活の戦略とチェスをするスキルを比較. 取引への明らかな接続は、取引に関する知識が収益性の高い取引に変換しないことです.

ブラック・ショールズ・モデルの広範な実用的な知識はあなたがディナーパーティーでインテリジェントな音になります, しかし、より多くのことが実際に成功したオプションを取引するために必要とされるがあります. はるかに少ない知識を持つトレーダーは上の彼の取引を考えていないだけで簡単に利益を得ることができます.

彼は裁判で実験し、タレブが示唆するような方法を誤り無料です. あなたはアプローチがはるかにantifragileで行くように学びます. これは、グリーン木材トレーダーがどのように動作するかであります.

グリーンランバー

Green lumber fallacy

あなたはそれを取引する木材産業についてのすべてを知っている必要はありません.

グリーン木材誤謬は、タレブは、取引商品のトレーダーになります参照です “緑の製材” 首尾よく, それがいることを呼ばれた理由を彼は知らなかったにもかかわらず、. この例の背後にある理論は、一般的に市場に関連付けられている情報は、その市場には関係のほとんどを持っているかもしれないということです. タレブも誰スイスフラン業者の例を示します “地図上スイスを置くことができませんでした。”

“だから、私たちは状況で1ミスに必要な知識の源緑の製材誤謬を呼びましょう – 木材の緑 – 別のもの, 外から見えにくいです, 少ない扱いやすいです, 以下narratable。” – タレビ

再びここに, 我々はそれの豊富よりも成功は知識の欠如からより多くの来るのを見ます. この考えは、テレビで議論された問題と戦略の多くは、単に私たちのトレーディング成績には関係がないことを思い出させてくれる. むしろデータに自分自身を溺死より, 成功したシステムを構築するための正しい方法は、以下のデータを見ることです. 少ない本当に多いです.

Making Trading Systems More Antifragile

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In order to make trading systems more antifragile, we must focus on changing their risk exposure. If your primary concern in trading is your system’s profitability, then you are setting yourself up for an epic failure. The first and foremost concern of any trading system absolutely must be the risk within a system.

破滅のリスク

In Book III of Antifragile, Nassim Taleb presents the argument that profit is a secondary goal in business. He argues that anyone who primarily focuses on profit is underestimating their risk exposure.

This concept applies directly to trading systems. Far too many traders use potential returns as the measuring stick for a trading system. Following Taleb’s argument, traders should put far more emphasis on the nature of the system.

“This fragility that comes from path dependence is often ignored by businessmen who, trained in static thinking, tend to believe that generating profits is their principal mission, with survival and risk control something to perhaps consider – they miss the strong logical precedence of survival over success.” – タレビ

While generating profits is certainly the end goal of any system, the ability to generate those profits requires the survival of the system. If the system goes bust at any point, then those future profits mean nothing.

Even if the system generates huge profits for years, if there are significant risks that could eventually catch up to it, then the system is just trading on borrowed time. The most important criteria for assessing a system’s fragility is its risk of ruin.

risk reward comparison

Risk and reward should be balanced against the long term objective of continuing to trade.

、 least desirable way to protect against risk of ruin is to decrease the fragility of the system. This may sound like common sense, but far too many traders never make the connection.

As I covered earlier this week, there are three way of doing this: increasing the system’s win rate, increasing the system’s profitability, or decreasing trading size. Of these options, the only one that is completely in the trader’s control is the amount of risk their capital is exposed to.

Sensitivity to failure is best analyzed by adjusting the accuracy percentage and payout ratios. If you trade a trending system and the average payout drops by 20%, what happens to the system? Many trending systems completely fall apart.

時々, a difference of 10% between the historical returns and future observations makes the difference between decent profits and huge losses. This is far more true when the expected percent accuracy falls and the payoff falls, あまりにも. Minor errors in observation lead to drastically different outcomes.

Fragility is Relative to Upside/Downside Risk

In the preceding chapter, Taleb explains that fragile systems have more to lose than they can gain. The opposite is true for antifragile systems. They have more to gain than to lose. They have a limited downside.

“You are antifragile for a source of volatility if potential gains exceed potential losses (その逆).” – タレビ

This further supports the argument that risk of ruin should be the primary concern when evaluating a trading system. Regardless of the system’s apparent upside, if the downside is too great, the system is no good. If the potential exists to lose everything, there is no possible upside that can balance that.

Long Term Capital Management

Taleb uses the example of a gambler to illustrate that no matter how good his strategy is, if he is exposed to the risk of losing everything then nothing else matters. The same can be said of anyone who’s trading system exposes them to too much risk.

It doesn’t matter how efficient the strategy is or how impressive the returns are if the risk of losing everything is too great. Risk of ruin trumps all other factors because it has the ability to end the game.

Long Term Capital Management (LTCM) provided an excellent example of this concept in the late 1990s. The fund was believed to have superior strategies implemented by brilliant traders and many investors expected the strong returns to continue indefinitely. The problem is that no one was concerned with the downside risk, leaving the fund vulnerable to a Black Swan event, which happened in 1998.

The combination of some unexpected events with a big appetite for leverage proved to be disastrous for LTCM and its investors. LTCM believed that it had smoothed out volatility and could provide consistent returns. As we all learned, the short-termist obsession with pretty Sharpe ratios on high leverage came at the cost of making a blowup inevitable..

Naive Intervention – Noise & データが多すぎ

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The best way to improve your trading system is to leave it alone. The best way to increase your returns is to turn off the TV and stay off of the internet. The best way to trade is from a cabin in the mountains with data that is a week old. That’s not what you’re used to hearing, is it?

Overwhelmed With Data

“A very rarely discussed property of data: it is toxic in large quantities – even in moderate quantities.” – Nassim タレブ

We have more data at our fingertips than any generation before us could have ever imagined. We can pull real time market information out of thin air in any small town that has a coffee shop. We can watch multiple 24 hour cable news networks from a hotel room anywhere in the world. Not only is data accessible, it’s surrounding us, and closing in fast.

The problem with all of this data is that it can be too much. We can have trouble seeing the forest because we’re too busy staring at the trees. This is especially true in the trading world. It is far more exciting to trade every hour than every month. According to your television, trades should depend on the next non-farm payroll report. But what if they’re all missing the point. What if simpler is better?

Simpler は better. Find a trading system with a long term track record, and then only track your returns over the long term. しかし, this is easier said than done.

Naive Intervention

In Book II of Antifragile, author Nassim Taleb presents his concept of naive intervention. This happens when we unnecessarily interfere in an attempt to help, but end up doing more harm than good.

Naive intervention

I *never* mess with my open trades… ever… I promise.

The most classic example of naive intervention is Alan Greenspan continually interfering with the economy in an attempt to smooth out the cycles. Despite his intentions, by smoothing out the bumps along the way, Greenspan dramatically increased the fragility of our economy. The result was a complete financial meltdown in 2008.

Many traders attempt to do the exact same thing with their trading systems. In an effort to avoid taking any losses, many traders either overtrade or constantly tweak their systems. This can lead to missing out on the big moves because of focusing too much on the smaller moves. I have fallen into this trap many times throughout my trading career. I lost count of the number of times that I have interfered with or adjusted systems based on what turned out to be insignificant data points.

The Neurotic Fellow vs The Mafia Boss

Taleb uses examples of a neurotic coworker who freaks out over everything and a calm mafia boss who chooses his words very carefully. The neurotic fellow overreacts to even the slightest changes, while the mafia boss almost never reacts to anything. He waits for only the most important times to speak up.

This is the attitude we need to take with our trading systems. There will be ups and downs, but we shouldn’t rush in to save the day and fix all of the problems at the first sign of a slight loss. We need to wait for the most significant places to intervene. It can be very difficult at times to tell the difference between the general noise and a signal that something needs to be adjusted.

My Struggle To Fight The Noise

Throughout my evolution as a trader, I have had my struggles with overexposure to data. I have been suckered by cable networks that scream “購入します。, Buy Buy!” but never tell you when to sell. I have tried trading systems that I didn’t understand, only to question them at the first sign of weakness. I have bought on insider tips as well as expert analyst recommendations. None of this worked because it was all noise.

Once I evolved past that level of noise, I was introduced to the next level of noise. Every time I opened a position, I became addicted to refreshing the web browser to calculate my up-to-the-second return. I then found myself making decisions based on the price movement over the past five minutes even though I established the position based on the last five months. This was a cruel addiction.

The struggle for me today is in determining the difference between the real signals and the noise. I have gotten dramatically better at focusing on the big movements and tuning out the tv networks and penny stock twitter experts.

Focusing On The Big Stuff

“The best solution is to のみ look at very large changes in data or conditions, never at small ones.” – Nassim タレブ

In almost any career or hobby, it can be very easy to lose yourself in the details. It happens to everyone, everywhere. The power of the urgent issue at hand to consume our entire world can lead us to spend all of our time obsessing over things that aren’t important in the long run. We have a passion for the moment, and many times, the moment is just a head fake.

Antifragile Trading – Enhanced By Volatility

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In Antifragile, author Nassim Nicholas Taleb presents the argument that the opposite of fragile is not simply something that is unaffected by stress or pressure. He argues that there is a quality called antifragile where something actually improves as a result of that stress or pressure. Taleb categorizes things on a scale from fragile to antifragile, with a mid-point he calls robust.

When this idea is applied to trading, the first comparison that jumps out at us is between buy and hold investors and systematic trend following traders. Systematic trend following traders excel under extremely volatile situations, are virtually ignored by intellectuals in their field and are capable of handling deviations because they are not predictive in nature.

An Illustration of The Antifragile Concept

Taleb illustrates his concepts of fragile, robust, and antifragile through Greek and Roman mythology.

Fragile is represented by the story of Damocles, who was invited to a dinner at which there was a sword hanging over his head that was held up by a horse’s hair. Damocles is considered fragile because at any second the hair could snap dropping the sword onto him.

The concept of robust is represented by the Phoenix, which is a bird that is able to be reborn from its own ashes. No matter how many times you attempt to destroy the Phoenix, it continues to return to its original state, unharmed.

Antifragile is represented by the Greek Hydra, which had multiple heads. Every time one of its heads was chopped off, two more would grow back. Any attempt to hard this creature actually made it grow stronger. This is the core concept of antifragile.

An Application To Trading

One of the characteristics that can help measure the fragility of something is how it responds to volatility. This allows us to easily apply this concept to trading, because volatility is actually measured in most markets.

VIX Monthly shows antifragile periods of strength

A monthly VIX chart dating back to 1985

If we look at a long term chart of the VIX, we can see four distinct areas of extreme volatility: The Market Crash in 1987, The Asian Currency Crisis in 1997-98, The Dot-Com Bubble & Crash from 1998-2002, and the Financial Collapse in 2008. These highly volatile periods were high stress situations that would have made antifragile trading strategies better while making fragile strategies worse.

It is no coincidence that it was during these exact periods that systematic trend following traders posted some of their best years, and at the same time, buy and hold investors lost fortunes.

Systematic trend following strategies are not only built to handle these kinds of high stress, high volatility situations. They become stronger from them simply because they provide traders with a way to change direction. This ability to go with the flow during even the most chaotic times is a stark contrast to the rigidity of a buy and hold strategy where the investor has no choice but to sit and watch their portfolio crumble.

Overcompensation & Overreaction

“Intellectuals tend to focus on negative responses from randomness (fragility) rather than the positive ones (antifragility).” – タレビ

再びここに, we can see a clear application of this with respect to trading during high volatility periods. In each of our four high volatility trading periods from the past 25 年, most of the intellectuals and so-called market experts were focused on the negative responses, which were the buy and hold investors who were losing their fortunes left and right.

During each of these periods, there was very little focus on traders who were benefiting from the increased volatility. The antifragile traders seemed to go unnoticed, and we know now that systematic trend following traders where the ones who were benefiting from these volatile markets.

Layers & Deviation

Taleb also discusses the complexities that can arise when looking at fragility through different layers and dimensions. He illustrates that since what is good for the antifragile is bad for the fragile, then what is good for the fragile is likely bad for the antifragile.

We have already discussed the huge success that antifragile trend following strategies have seen during times that were terrible for fragile buy and hold strategies. When the inverse situations occurs where markets have little volatility, we have seen that systematic trend followers and buy and hold investors can produce rather similar results. The key difference though, is that the antifragile systematic trend followers have the ability to adjust when a black swan shows up.

“When you are fragile, you depend on things following the exact planned course, with as little deviation as possible – for deviations are more harmful than helpful.” – タレビ

He continues to explain that the fragile is very predictive and that being so predictive is exactly what causes fragility. This is the problem with buying and holding with the expectation that a position will go up over time. The entire strategy is predictive in nature, and that is exactly why it becomes fragile. It can’t handle a deviation from what it predicts.

それどころか, a systematic trend following approach can, by definition, handle any deviation from what is expected because it simply goes along with that deviation. This ability to adapt and change is magnified during periods of high volatility, which is when systematic trend following is at its best.