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2 Painful hits

Februar 13, 2017 von Shaun-Overton 14 Kommentare

December and January were extremely unkind to me. I took a huge loss on Dezember 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.

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

Ausgleichungsrechnung

It’s not like the strategy loses money on every single news event. Es hat 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 verschiedene Instrumente. All instruments cross with USD.

  • EUR/USD
  • GBPUSD
  • USDCHF
  • AUDUSD
  • NZDUSD
  • USD/JPY
  • USDCAD

Many subscribers correctly observed that the major losses occurred with trades open on all 7 pairs in the portfolio zur gleichen Zeit. 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, jedoch, 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, einfache, 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.

Schließlich, 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 (I lost 2,000 euros between the two moves). What hurt my subscribers hurt me, auch.

Abgelegt unter: Herrschaft Markiert mit: Ausgleichungsrechnung, Auszahlungsbetrags, Fachberaterin, portfolio allocation, skew

Handelnde Plattform-Einschränkungen

Oktober 18, 2015 von Shaun-Overton 6 Kommentare

Dieser Beitrag wurde von Ben Fulloon verfasst., ein angesehener Händler und Abonnenten zu OneStepRemoved.

Ich entwickelte eine genial-Strategie mit einem Verlust-Verhältnis von 13.67. Klingt erstaunlich, rechts? Schade, dass meine trading-Plattform übertrieben die Ergebnisse von mehr als verdoppeln!

Es ist wichtig, zu lernen, Ihre Makler und die Plattformen Einschränkungen. Manchmal werden diese Feinheiten nur scheinbare durch Zeit und Erfahrung. Es ist so frustrierend, wenn Ihre Handelsplattform funktionieren nicht oder Berichtergebnisse wie erwartet.

In diesem Artikel werde ich zwei Einschränkungen NinjaTrader hinweisen 7, eine Einschränkung beim schlecht und tatsächlich überraschend ausfallen kann, die besser für den Händler in bestimmten Situationen. Jedoch, Dies ist mehr zu tun mit der Broker, die, den ich verwende, und nicht die Plattform selbst.

NinjaTrader ist definitiv nicht die einzige Plattform, die Beschränkungen hat: MetaTrader, TradeStation, X-Händler, MATLAB, etc.. alle haben Einschränkungen für quantitative finance.

Ich werde nur über NinjaTrader in diesem Artikel, es ziemlich kurz und gut lesbar zu halten schriftlich. Ich bin auch nicht die Absicht, NinjaTrader machen, entweder als eine schlechte Plattform. Aber, Es gibt definitiv einige Verbesserungen, die gemacht werden könnten, zu machen, viel einfacher und bequemer für quantitative Händler zu entwickeln und Strategien zu handeln.

Die erste Besonderheit bezieht sich auf den Broker ich verwende. Speziell, Es ist der Tag-HANDELSSPANNEN, denen mir wichtig. Diese Tag-Handelsspannen zu beenden 15 Minuten vor dem Ende der Sitzung. Zum Beispiel die ES (Emini S&P500) hat eine Handelsspanne von Tag des $500, an endet 4:00PM CT, dann kehrt zurück zu den vollständigen Handel Rand $5060 vor die Sitzung schließt um 4:15Uhr CT. (Genannten Zeiten sind korrekt zum Zeitpunkt des Schreibens, ES schließt jetzt um 4:00PM CT und endet der Tag-Handelsspanne 3:45Uhr CT)

Ich zeige Ihnen einen Screenshot der Ergebnisse eines Tages-trading-Strategie, die ich entwickelt. Diese Strategie handelt ES, NQ (Emini Nasdaq 100) und die YM (Emini Dow) alle zur gleichen Zeit. Am einfachsten mit dem NinjaTrader abbiegen setzt "Beenden schließen" auf True die dann, am Ende der Sitzung beendet wird.

All trades together in the report

Nach den Ergebnissen macht die Strategie insgesamt $332,771.60 mit einer maximalen Verlust von $25,912.27 seit 2008 bis heute. Dies ist ein Verlust-Verhältnis von 12.84. Das ist Außergewähnliche!

Die Frage ist... und Sie wusste, dass gäbe es ein problem… ist, dass die Strategie bei beendet 4:15Uhr CT. Day-trading am Rand endet 4:00Uhr CT. Die Strategie ist daher sehr wahrscheinlich, dass einen Margin-Call mit einem kleinen Konto-Größe.

Es ist sinnvoll, die Strategie um die Day-trading-Marge nutzen optimieren. NinjaTrader bietet eine benutzerdefinierte Sitzungs-Vorlage, in diesem Fall habe ich auf Ende 4:00Uhr CT. Die Ergebnisse der benutzerdefinierte Sitzungs-Vorlage ist wie folgt.

Day trading with all instruments together

Die exakte gleiche Strategie angewendet an den gleichen Instrumenten einen Margin Call zu vermeiden macht $335,819.30 mit einer maximalen Verlust von $24,560.51. Dies ist ein Verlust-Verhältnis von 13.67.

Ich habe nicht die Strategie mit dem Ziel der Verbesserung des Verhältnisses des Auszahlungsbetrags ändern und den Gewinn. Aber hey, Ich nehme. Eine Einschränkung in der Plattform zu finden tatsächlich profitieren in einigen Situationen Sie.

Diese Strategie basiert auf den Handel 3 verschiedene Instrumente. Die ES, die NQ und die YM. Das Problem ist das ich Backtested es ein Instrument mit in NinjaTrader Liste. Das bedeutet, dass sie alle separat getestet sind. NinjaTrader kombiniert dann die Testergebnisse für Sie als ein Gesamtergebnis wie die Ergebnisse der obigen screenshots.

Hier ist, was es sieht, wie wenn Sie sie als Instrumentenliste testen. Dies zeigt die verschiedenen Gewinne und Rückschläge der einzelnen Instrumente.

Results by instrument

Jetzt auf den ersten Blick liest, dass der Händler gemacht hätte $335,819.30 mit einer maximalen Verlust von $24,560.51 Wenn sie alle drei Instrumente zusammen gehandelt. Findest du nicht?

Das Problem ist, dass dies nicht korrekt ist. NinjaTrader kombinieren nicht tatsächlich die Ergebnisse, wie man denkt. Der Händler noch hätte etwa das Geld. Jedoch, Alle Zahlen sind nicht ganz richtig.

Um das zu zeigen neu ich genaue dieselbe Strategie, aber es wird die ES Handel, NQ und YM alle zur gleichen Zeit statt sie separat zu handeln, wie es standardmäßig tut. Das sind die Ergebnisse beim Programmieren in Eidsvoll-Strategie

Combined trading

Es macht $335,915.30 Das ist ungefähr die gleiche Menge, aber es hat eine maximale Inanspruchnahme der $59,937.60 statt der $24,560.51 Es sah ursprünglich, wie es wäre. Dadurch ist es ein Verlust-Verhältnis von 5.60, Was ist viel schlimmer als das original 13.67.

Wenn der Händler Handel basierend auf die maximale Inanspruchnahme der entschieden $24,560.51, Sie können einen fiesen Schock bekommen, wenn die Inanspruchnahme entpuppt sich als doppelt so schlimm, wie sie erwartet hatten.

Falsche Berechnungen auf solche eine wichtige Kennzahl könnten ein Kontos gefährden. Sie können davon ausgehen, dass Sie mit der Hälfte des Eigenkapitals Weg erhalten können, die tatsächlich erforderlich ist, um die Strategie zu handeln. Hoppla?!?

Die irreführenden Statistiken in NinjaTrader macht diese Strategie wirklich schön aussehen. Aber wann ist die Inanspruchnahme mehr als verdoppeln, was es schien, dass es ursprünglich gewesen wäre, erhalten Sie möglicherweise einen fiesen Schock.

Deshalb ist es wichtig, Ihre Plattformen und die Broker Einschränkungen so früh wie möglich lernen. Sie wollen nicht diese Einschränkungen auf die harte Tour lernen.

In ein paar Wochen Zeit, Ich werde eine einfache Möglichkeit, Eidsvoll Strategien zu erstellen, die eine genauere Messdaten zeigen offenbaren. Stay tuned für meinen nächsten Artikel der Serie.

Abgelegt unter: NinjaTrader Tipps, Testen Sie Ihre Konzepte historisch Markiert mit: Auszahlungsbetrags, ES, Future, margin call, NQ, portfolio allocation, YM

BreakTime

April 28, 2015 von Shaun-Overton Hinterlasse einen Kommentar

Es ist eindeutig etwas los mit den aktuellen Marktbedingungen. Literally every currency pair is blowing out into a single direction. The addition of the recent pairs hasn’t done anything to stop it.

Rather than trying to fight this and hope and hope, it’s best to take a time out and see where the chips fall. I did spot a few issues with my long term trend direction that would have made this pain less bad – there is at least a small improvement that will come out of this.

Sagte, the mantra for now is live to fight another day. It’s clear that the market conditions are beating the snot out QB Pro. I’m going to make the hard decision, which is to go flat and do nothing. This is exactly the reason that I don’t charge management fees – I’d feel awful trying to charge people for this recent performance.

I’ll update everyone in a week or two when we’re ready to evaluate whether or not to flip the switch back on.

 

Abgelegt unter: QB-Pro Markiert mit: Auszahlungsbetrags

Was ist los?

April 22, 2015 von Shaun-Overton 9 Kommentare

Es wurde einen holprigen Monat definitionsgemäß. Wir haben eine Menge Geld im Gefolge der Fed-Ankündigung des letzten Monats, only to give it all back the next week. QB Pro recovered most of the earlier gains, then last week’s drawdown took it all back again. It’s been painful.

The good news is that the new changes to QB Pro are rolled out. Several of you sent in emails asking about new currencies like GBPNZD and AUDCAD appearing in your account. Kudos to you for paying close attention to the trading.

The total currencies traded in the basket is up to 16 pairs. While the max leverage is unchanged at 36:1 (still very, very high), the leverage per pair is only 2.25:1. Future losses like the one from last week will still occur.

The difference is that the size of the positions is reduced by over 2/3. The impact of getting caught in losing trades that are all reflective of USD weakness decreases significantly. We’re now trading a mix of AUD, CAD, CHF, EUR, GBP, JPY, NZD, USD and XAG. No one currency should dominate the performance.

The system also does extremely well on emerging market currencies. I’m holding off on adding RUB, MXN and others until I determine the impact of the spreads on overall profitability. They’d do amazing if we could trade for free!

Short term performance expectations for QB Pro

We’re coming into the summer, which is when the forex market traditionally falls into the doldrums. That’s generally a good thing for QB Pro. The markets whipsaw up and down without really going anywhere.

The alternative is that the Fed hikes rates in June and sends the market into a USD buying frenzy. That’s also good news. Most of the money that QB Pro made over the past 8 months was driven by USD strength. A rate hike would unleash chaos in emerging markets and equities. That’s the kind of condition to push volatility into our new crosses, creating opportunities for us to trade.

QB-Pro 2.0 isn’t happening

I’m extremely disappointed. After several thousand dollars in programming expenses, and not to mention the 100+ hours that I spent coding myself, the QB Pro 2.0 change is a wash.

I had a trusted developer audit my code to make sure I wasn’t doing something stupid like trading on future prices or anything. Neither him nor myself caught anything from December until March.

Towards the end of last month, a single line of code ruined it all. One of my key features was deciding when to bail on trades and go the opposite direction. Gut, it turned out that I accidentally introduced data snooping into the backtesting platform. I pre-calculated when losing trades occurred to calculate probabilities.

In plain English, my goal was to calculate “If today was a big loser, then do the opposite tomorrow.”

What I accidentally coded was “If tomorrow is a big loser, then do the opposite.” If only that were possible!

I don’t want to muddle up the explanation with code examples. Suffice it to say that the idea didn’t work out when I took away the ability to look into the future.

There are some features of the 2.0 system that I wish to analyze in the coming months, but for now it’s going to have to take a back seat.

What’s next?

My plan is to sit tight for a few weeks to ensure that the new pairs are working as intended. Whenever I am personally satisfied with the system behavior, I intend to increase the amount of capital in my account.

Don’t hold my feet to the fire. This part is a subjective process, so I can’t put a precise time frame on it. If and when I am satisfied – and it’s going very well the first few days – then I will make a decision about increasing my capital at risk.

If and when I choose to increase my capital in the account, I will then re-open QB Pro to new traders.

PS: I hope that the drawdowns encourage some of you to withdraw profits the next time the opportunity presents itself. You don’t want to lose more than you are comfortable risking.

Abgelegt unter: QB-Pro, Testen Sie Ihre Konzepte historisch Markiert mit: Backtesting, Auszahlungsbetrags, QB-Pro

Verwenden Sie maximalen Hebel, wachsen Gewinne und Risiken verringern

Januar 12, 2015 von Eddie-Flower 9 Kommentare

Die Gewinne können schnell ansammeln, wenn ein Stütze-Händler eine Strategie basierend auf Maximaler Hebel mit begrenzten Kontogröße verwendet. Zur Wahrung und bauen diese Gewinne, Es ist wichtig, sie aus der trading-Konto nach einem guten plan.

Wie in früheren Artikeln in dieser Serie beschrieben, die hoch-Hebelwirkung, niedrig-Gleichgewicht-Strategien, die von den führenden Händlern der Stütze können auf mehreren Handelskonten mit verschiedenen Systemen angewendet werden, mit jedem Konto von nicht mehr als ein paar tausend Dollar großgeschrieben.

Der Betrag auf dem Konto beträgt in der Regel zwischen $1,000 bis zu mehreren tausend Dollar. Auf diese Weise, Es gibt keine psychologische Hindernis für die maximale Hebelwirkung auf jedem Handel mit.

Reduzieren Sie die Risiken von Inanspruchnahmen

Wenn Sie ein Gewinnsystem haben, Gewinne anhäufen. Es ist verlockend zu "Reiten lassen" mit dem gleichen System immer größere Positionsgrößen im wachsenden Konto handeln.

Jedoch, Wann steht das gesamte Kapital in der trading-Konto, Das bedeutet, dass die Hauptstadt der unvermeidlichen System "Blow up ausgesetzt ist,"die Ursachen in der Regel eine steile Auszahlungsbetrags. Selbst wenn der Händler finanzielle Katastrophe entgeht, er oder sie kann also danach zu unentschlossen und ineffektiv werden risikoscheu geworden..

Ziehen Sie jeden Monat Geld

Der intelligente Weg zur Vermeidung übermäßiger Inanspruchnahme wegen Handelssystem "Blow-Ups" soll Geld aus dem Konto am Ende des Monats erfolgreich zu ziehen. Auf diese Weise, Wenn eine große Verlust auftritt, Es nehmen nicht Ihr ganzes Geld., nur die paar tausend Dollar, die Sie sich leisten können zu verlieren.

Erfolgreiche Stütze Händler wie Shaun fegen die Gewinne aus jeder trading-Konto monatlich gewinnen und verschieben Sie sie in ein nicht-trading-Konto, wo bleiben sie sicher. Also, jeden Monat öffnen die trading-Konten mit ihren einzelnen Groß-/Kleinschreibung zu einem bestimmten Betrag festgelegt.

Ziehen Sie zumindest genug, um eine abdecken, "blow up"

Sobald Sie Ihr Forex-System gestartet haben, Sie sollten darüber nachdenken Zweckbindung genug Geld, um mindestens einen Handel Systemausfall abzudecken. Nachdem Sie haben diesen Betrag für eine Rekapitalisierung der Ihr trading-Konto verwendet werden gesichert., alle nachfolgenden Gewinn ist "free money,"zumindest in gewisser Weise psychologische.

Der erste Meilenstein ist, genügend Geld aus der trading-Konto mindestens eine Katastrophe decken ziehen. Wenn Sie genossen haben meist Monate zu gewinnen, als nächstes sollten Sie zuordnen 50% Ihre Gewinne für Hochrisiko-Systeme.

Sie können nicht verlieren, was nicht gefährdet ist

Denken Sie daran: Wann ist ein Stütze-Händler maximalen Hebel verwenden., Das einzige Geld, das sicher ist, ist das Geld bereits zog aus der trading-Konto. Gewinne sollte von dem jeder trading-Konto Gewinn gezogen werden, jeden Monat.

Wenn ein Händler Stütze gewinnt konsequent ein beschränkter Größe-Konto mit hohen leverage, die Gewinne aus relativ kleinen einzelnen Trades können schnell verschlimmern.. Gewinne aus der überfließenden kleinen trading-Konten gesammelt können in große Summen verschlimmern., und es ist wichtig, diese Gewinne effektiv verwalten.

Wenn Sie mehr erfahren möchten Gewinne jeden Monat mit maximaler Hebel ziehen, nur Shaun kontaktieren.

Abgelegt unter: Wie funktioniert der Forex-Markt?, Stop, Geld zu verlieren, Allgemein, Was passiert in den aktuellen Märkten? Markiert mit: sprengen, Auszahlungsbetrags, nutzen, stützen, Handel, Risiko

What Quantitative Value Do Stops Actually Have?

Dezember 20, 2013 von Andrew Selby Hinterlasse einen Kommentar

One of the questions that every quantitative trader must address is whether adding a stop-loss component to their system will help or hinder its performance. I have written a good deal lately about the pros and cons of different types of stops, but haven’t had much actual backtesting data to work with.

When I wrote a post about about Cesar Alvarez’s S&P Rotational Strategy a few weeks ago, I suggested that adding a stop-loss might lower the maximum drawdowns. This would give the strategy a way to exit losing positions during the month, rather than waiting for the monthly redistribution. Theoretisch, this would have reduced some of the big losses that the strategy suffered in 2008.

 

Quantitative Value

We assume that adding a stop loss component has the quantitative value of a safety net, but that isn’t always the case.

In addition to writing about that idea here, I also commented on Alvarez’s post. In response to that, he has written a Follow-up-post addressing my suggestion to implement stops:

Continuing from the post, we are adding a maximum stop loss. The stop is evaluated at the close each day with the exit happening at the close. The tested stops are 5%, 10% und 15%.

Interessant ist, Alvarez finds that adding stops can be helpful in some situations and terrible for performance in other situations. While adding stops may always seem like a logical idea in theory, Alvarez shows that actual performance can prove otherwise.

Best Performing Stocks

The version of the best performing stocks strategy that we looked at in the previous post utilized a market timing indicator and a six month look-back period. That strategy produced a CAR of 10.48% mit einer maximalen Verlust von 42.22%. Here are the numbers when 5, 10, und 15 percent stops were added:

  • 5% Stop: 10.51% AUTO, 26.30% MDD
  • 10% Stop: 10.85% AUTO, 38.05% MDD
  • 15% Stop: 10.84% AUTO, 39.48% MDD

Wie Sie sehen können, adding the stop loss doesn’t do much for the CAR, but it does a great job of reducing the maximum drawdown. When the stops were applied to the version of the strategy with a 12 month look-back period, the impact on maximum drawdown was similar, but the CAR saw a bit more of an increase. When the stops were applied to each of the two versions without the market timing indicator, we saw a slightly less impact on drawdown and a much greater impact on CAR.

Alvarez also commented that in almost all cases, die 5% stop was the best performer, which he thought was unusual:

Normally close stops tend to be the worst but the 5% stop tends to be the best.

Worst Performing Stocks

The worst performing stocks version of the strategy that we looked at used the market timing indicator and a six month look-back period. The strategy without stops had a CAR of 13.05% und ein maximaler Verlust von 27.88%. Here are what the numbers look like when the different levels of stops were applied:

  • 5% Stop: 5.11% AUTO, 28.26% MDD
  • 10% Stop: 8.36 AUTO, 30.90% MDD
  • 15% Stop: 10.47% AUTO, 30.87% MDD

In diesem Fall, adding the stops has really hurt the strategy. While there was some improvement in the maximum drawdowns of some of the versions, adding stops basically crippled the CAR of all of the worst performing stocks strategies.

Alvarez notes that this is the result he expected:

For the worst N-month ranking, stops appear to hurt the all results. These results support previous research that stops on short-term mean reversion hurt results.

Abgelegt unter: Testen Sie Ihre Konzepte historisch Markiert mit: cesar alvarez, Auszahlungsbetrags, quantitative, Stop

Keeping up with the humans

Oktober 10, 2013 von Shaun-Overton 2 Kommentare

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, gut, 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. Dann, 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, etc.. 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.

Abgelegt unter: Was passiert in den aktuellen Märkten? Markiert mit: algorithmic trading, Barclay's, Daniel Fernandez, Auszahlungsbetrags, Fachberaterin

Backtesting Vorurteile und Variationen

Oktober 3, 2013 von Andrew Selby 4 Kommentare

Letzte Woche, I wrote a post discussing how altering the timeframe of a system can change its results. That got me thinking about other ways that backtesting results could be skewed in one way or another based on user defined data such as the date range and market used. These simple differences can have a tremendous influence on the overall returns of any system, so it is important to pay them their proper respect.

When running backtests, it can be very easy to gloss over the down periods and cherry-pick the big return years. The problem is that you won’t have that opportunity when actually trading a system live. You will need to prepare yourself for the possibility that you select the wrong time or the wrong market to trade a given system. Ansonsten, you run the risk of letting these backtesting biases adjust your expected return to values the system cannot possibly deliver.

Adjusting the Date Range

Let’s use our 10/100 Moving Average Crossover System from last week as a base. We tested it from January 1, 2001 bis Dezember 31, 2010 on the Vanguard Total Stock Market ETF (VTI). All of our tests last week used a starting portfolio value of $10,000, ein 10% Trailing stop, und eine $7 Kommission.

Backtesting bias in VTI

MA crosses on VTI returned almost 90% over the last decade.

Based on those settings, our 10/100 MA Crossover System returned 89.8% over ten years. This works out to be an annualized return of 12% mit einer maximalen Verlust von 16.2%.

If we would have started trading this system on January 1, 2003, we would have registered a total return of 39% in the three years of trading until the end of 2005. This would have been good for a 16.4% annualized return with a maximum drawdown of only 6%. Wie Sie sehen können, if we based our strategy on these results, we would be expecting the system to continue to produce these extremely high returns.

Andererseits, if we would have started trading this system on January 1, 2006, we would have seen a total return of only 2.5% in the first three years. We also would have had to sit through a 14.2% Auszahlungsbetrags.

It is also worth noting that while the ten year track record of this system from 2001 durch 2010 is very respectable, we wouldn’t have known that when we started in 2001. If we actually started trading this system in 2001, we would show a total return of -6.2% at the end of 2002. After two full years trading this system, we would not have had a single thing to show for it. The system didn’t find its first big winner until April 15, 2003.

Wie Sie sehen können, the time you chose to begin trading the 10/100 Moving Average Crossover System could have made all the difference over the course of what was a net-profitable decade. It is very important to keep this in mind when you are struggling through drawdowns.

Adjusting the Markets Traded

The market you choose to trade can have the same affect on your trading as the date you start trading. Let’s look at how the exact same system would have performed over the exact same decade if we chose to trade it on different ETFs.

Trading the 10/100 Moving Average Crossover System on the XLF, which represents financials, would have provided a total return of -9.4% for the decade with a maximum drawdown of 30%. It is obvious to us at this point that financials had a rough time during this period, but we would have had no clue about that when we started in 2001.

The XLY, which represents consumer discretionary stocks, also would have underperformed the VTI. Trading the system on the XLY would have returned a total of 39.4, oder 6.4% annually, mit einer maximalen Verlust von 21.3%.

Backtesting bias for xly

XLY shows a 39.4% return over the same decade

If we would have been fortunate enough to trade the XLK, which represents the technology sector, we would have seen a tremendous total return of 95.7%. This works out to be an annual return of 14.2% mit einer maximalen Verlust von 22.3%.

Noch einmal, we see that decisions like what markets to trade and when to start can have a tremendous influence on our results. This is why it is so important to thoroughly backtest any strategy across many different combinations of date ranges and markets.

Abgelegt unter: Testen Sie Ihre Konzepte historisch Markiert mit: jährliche Rendite, backtesting bias, Auszahlungsbetrags, ETF, Verschieben von durchschnittlichen Frequenzweiche, System, Trailing stop, VTI, XLF, XLY

The New Yearly High System

September 25, 2013 von Andrew Selby 2 Kommentare

At the root of most trend following systems is the idea that you want to be long markets that are moving higher or short markets that are moving lower. One of the simplest and most popular ways to identify markets that are trending up or down is to look for ones that are making new 52-week highs or lows. This simple signal can be used as the root of a very simple and easy to follow trend following system.

Über das System

In his book, Unholy Grails, author and trader Nick Radge discusses a number of different systems providing set rules and backtesting results. One of the first systems he describes is based on the concept that stocks making new yearly highs are likely to continue higher, and stocks making new yearly lows are likely to continue trending lower. This is one of the core concepts behind most systematic trend following strategies.

Radge points out that a system that is based on new yearly highs and lows is very user-friendly because most financial resources publish data for stocks making new 52-week highs and lows. This means that we could literally trade this system manually without any trading software.

One way that Radge simplifies the system is by assuming that there are approximately 250 trading days in a year. Daher, any stock making a new 250-day high or low will also be making a new yearly high or low. This means we can treat this system as a very simple 250-day breakout system.

This system establishes a long position on the open the day after a stock makes a new 250-day high and then exits that position on the open of the day after the stock makes a new 52-week low. These 250-day highs and lows are easy to monitor using a price channels overlay, which is available in most charting packages. The solid yellow lines on the chart below represent the 250-day high and low prices.

yearly high and low in BND

BND forms a new 250 day low

Handelsregeln

Geben Sie lange bei:

  • Price Closes At New 250-Day High

Ausfahrt langen bei:

  • Price Closes At New 250-Day Low

Backtesting-Daten

In order to backtest this system, Radge used the stocks in the All Ordinaries Index, which is the most popular stock market index in Australia. He compares his results to the All Ordinaries Accumulation Index, which is a benchmark that represents a buy and hold approach on the Australian equities markets.

His testing period ran from January 1, 1997 through Jun 30, 2011. The account started with $100,000 and sized positions at 5% des Kontos. Commissions and dividends were also taken into account.

Trading the New Yearly High System over those 14 years would have produced a total of 170 Facharbeit. The Compound Annual Growth Rate (CAGR) would have been an impressive 18.21%, more than doubling the 8.78% CAGR of the benchmark buy and hold account. Das System wurde auf profitable 53.3% of its trades and posted a Sharpe Ratio of 0.395.

The glaring negative of the backtesting results would be that the New Yearly High System posted a maximum drawdown of over 50%.

Systemanalyse

One of the most common things you will hear about system development is that traders place far too much emphasis on entry and exit signals. Im Gegensatz dazu, there is generally not enough emphasis placed on risk management and position sizing. This system is a great example for those philosophies because its entry and exit signals appear to work just fine, but its 50% drawdown indicates that it doesn’t do a good enough job protecting its profits.

The New Yearly Highs System has a significant strength in that it works. Its returns actually beat a buy and hold approach by more than double. Jedoch, its weakness needs to be addressed, because it would be an absolutely nightmare to attempt to stick to the system while sitting through a 50% Auszahlungsbetrags.

Verbesserung des Systems

Trend Filter

The first thing I would do to improve this system is introduce a trend filter using the 200 Tag einfacher gleitender Durchschnitt (SMA). This filter would simply require that the general market be in an uptrend in order for the system to enter a long position in any single stock. This would ensure that the system was not taking long positions in stocks that were trying to trend higher against a downtrending general market. We should have more overall success if we consistently trade with the trend of the overall market.

Trailing Stop

Another condition I would add to the system would be an ATR-based trailing stop that would ensure that we locked in profit from any profitable trades. It would also minimize our losses on losing trades. Adding this stop might cut down the overall returns a bit by cutting short trades that would have eventually turned profitable, but the downside protection would likely be worth that sacrifice.

Changing the Universe

One of the things that Radge suggests is trading the system exclusively on the market index as opposed to individual stocks. He suggests that this would cut down on volatility and then proves that concept with backtesting results. This idea lowered the CAGR to 13.92%, but also cut the maximum drawdown down to 36.03%.

Keeping with the line of thinking that trading the system on indexes would reduce volatility, I would be curious to test the system trading across multiple indexes or ETFs. It would be interesting to see how the system performed on the ETFs traded by the Ivy Ten System oder die markets recommended by Andreas Clenow in Following The Trend.

Abgelegt unter: Trading Strategie-Ideen Markiert mit: All Ordinaries, Auszahlungsbetrags, NIck Radge, Trailing stop, Trend-filter, yearly high

Why You Must Design Your Own Trading System

Mai 20, 2013 von Andrew Selby Hinterlasse einen Kommentar

After deciding to explore system trading, many traders are tempted to expedite the process by purchasing someone else’s system. These traders are often met with disastrous results.

In order to successfully trade a system, you must have unshakable confidence in that system and the system must fit your personality. The only way to achieve this is to build your own system.

Confidence In Your System

No trading system is perfect. All trading systems experience drawdowns. The difficult part comes when you try to determine if a drawdown is normal or if markets have fundamentally changed in a way that erases your system’s edge. The only way that you will be able to tell the difference is if you know your system inside and out. That only happens when you build it yourself.

There are many trading systems that you can purchase for a wide range of prices. Some are based on solid strategies. Some are over fitted to a specific style of market. The problem is that if you jump into using someone else’s system, you won’t know how it was designed to handle different markets. When the system experiences a drawdown – it’s going to happen – you won’t know whether or not that drawdown is normal.

Shaun wrote a post earlier this year discussing drawdowns. He referenced how Dustin Pedroia struggled when the Boston Red Sox first called him up to the big leagues. The Red Sox stuck with their young second baseman because they were able to identify that his low average was not sustainable because of his high contact rate.

Shaun compared the Red Sox sticking with Pedroia to a trader sticking with his system during a drawdown. The Red Sox were able to understand Pedroia’s slump because they were able to look deeper into his performance statistics. A system trader can do the same thing if he knows his system well enough to look deeper into its performance statistics.

Pedroia stays in the lineup during a drawdown

The Red Sox stuck with Pedroia during a slump because they knew how good he was

By taking the time to backtest a trading system through different market periods, you will gain an understanding of how the system reacts to different types of markets. Zum Beispiel, if your system creates most of its profits during a trending market, then you won’t have any reason to panic if it experiences a drawdown during a non-trending period. That would be expected. However if the same system was struggling to produce in a trending market, you would be more concerned.

Building A System The Fits Your Personality

Another reason that you must construct your own trading system is that the system needs to fit your personality. The system used by The Turtles is probably the most famous system of all time, and you can purchase software that trades that exact system for less than $1,000. The problem with that approach is that you might not be a good fit to trade the way the Turtles traded.

The amount of trades a system makes, the time frame that those trades are held, and amount of capital risked on each trade are all factors that affect how a system suits your personality. While the Turtle’s system worked for some traders, if that system exposes your capital to more risk than you are comfortable with, then you won’t be able to sleep at night. While each of these factors can be adjusted during the process of building a system, many black box systems do not allow for adjustments. Auch, without backtesting data, you won’t be able to determine how these adjustments will affect the system’s performance.

Going back to Shaun’s Dustin Pedroia reference, the Boston Red Sox were able to have confidence in the numbers of their short, odd-looking prospect because he fit their personality. They also had great success when they acquired corner infielder Kevin Youkilis, who was not an outstanding hitter, but had an exceptional ability to draw walks. If either of these players made the front office feel uncomfortable, they never would have been successful.

Every element of a trading system must reflect your personality

Youkilis is a player that makes the Red Sox comforable. Are you comfortable with each element of your trading system?

Acquiring players like Pedroia and Youkilis fit the personality of the Boston Red Sox, who were obsessed with crunching numbers and didn’t mind looking foolish if they were wrong. I would compare this to trading a system that focused on absolute return that also expects steep drawdowns.

On the opposite end of the spectrum, the New York Yankees are known for acquiring players that are already proven commodities later in their careers for much higher salaries. This approach is more in line with a trading system that trades for smaller profits with much less risk.

OneStepRemoved.com is dedicated to helping traders find a system appropriate for their personalities. Email info@onestepremoved.com and let us know how we can help with your trading.

Abgelegt unter: Trading Strategie-Ideen Markiert mit: Auszahlungsbetrags, Pedroia, System, Youkilis

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