Dominari Archives - Algorithmische und mechanische Forex Strategien

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

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

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.

Arbeiten 8 days a week

Dezember 6, 2016 von Shaun-Overton 22 Kommentare

Reaching an all-time high in my equity curve means it’s time to buckle down and keep improving. My Dominari strategy has done very well over the past 7 months and especially this and last month.

Is the party going to continue?

I certainly expect so. Drawdowns are inevitable, but that’s part of trading. Short-term performance is exciting, but my ambitious goal is to turn my starting balance of €8,000 into €50,000 within the next 3 Jahre. As of this writing, I’m at €9,323.

You’re probably wondering how a 16% profit leads me to extrapolate an annual return of nearly 100%. The answer is that I dramatically changed my leverage at the end of September… just in time for that ugly drawdown. If I was trading on my current leverage, the current live return would be around 40% (d. h., right on track to hit my goal).

What really counts is what I’ve really done. Bisher, I’m up €1,323 with another €40,677 to go by December 6, 2019.

The research for Dominari is effectively finished. It’s been slightly more than a year since I began researching the strategy. Although minor variations of Dominari popped up or came from traders copying my signals, none of them improved the long term outcomes.

One version that improved the risk profile was to trade with limit orders. The original blog post mentioned limit orders, but the variation placed them considerably further from the current market than what I tried previously. I also lacked a system for choosing settings appropriate to every pair, which I’ve more than likely resolved. The problem is that I have a million things on my to-do list and only 8 Stunden am Tag. You’ll see some of my top projects when you scroll down.

Pilum: The latest and greatest

Pilum is a strategy based on a statistical process that identifies momentum. One of the scary elements about most quantitative strategies is that most of them are mean-reverting. They buy when the price drops and sell when the price rises. The approach is favorable (d. h., profitable) in the long run, but it takes some psychological fortitude to trade.

Pilum is a major advancement because now I’ll have a strategy that should profit exactly when Dominari is most vulnerable to a drawdown.

The new strategy uses Limit-orders to enter the market. Something like 90% of these orders never execute. But when they do execute, I win 75% der Zeit. Zusätzlich, my profile of winners to losers is very comfortable.

Most traders understand the ideas even if the statistical jargon is unfamiliar. Pilum’s biggest winner is larger than its biggest loss. The average winner is bigger than the average loser. Und, it wins 77% der Zeit.

Bisher, I’ve done a sort of piecemeal backtest using R. When I finish the Quantilator (see below), I’ll redo the backtest in a fully fledged trading platform. Mehr als wahrscheinlich, I’ll use QuantConnect to test the strategy level approach.

Trading platforms drive me crazy! The biggest problem that I have as a trader is continuously reallocating capital across my portfolio. MetaTrader, NinjaTrader and the likes implicitly assume that I want to trade some percentage of my account balance on every trade. Either that, or that I trade fixed lots.

Trading that way is extremely inefficient. I’m trying to trade 40+ Währungen, so I need to be able to decide which ones need the money for trading and which ones don’t have signals. Dann, among the ones that do have signals, I need to dish out their allocations proportionately. The allocations aren’t the same for each instrument. If you know of any good FX platforms that meet this requirement, then let me know in the comments section.

Testing Pilum on its own is important. More important than the performance of Pilum is how that performance interacts with Dominari. That means taking the daily equity values of each currency. Does Dominari lose when Pilum wins and vice versa? Should I allocate capital 50-50 between the strategies or does one strategy deserve the lion’s share of the portfolio? Is one strategy so good that it should get all of the money?

The main concern with portfolio allocation is how it relates to leverage. Dominari historically make 96% annual returns, inclusive of trading costs. Aber, it’s also trading with leverage of roughly 19:1. It’s possible for markets to rip over stops and create significant losses.

USDCHF lost 40% of its value in one hour in January 2015. Say that the scenario was even more extreme and that nobody could place a trade during that time at any price. Dass 40% move is multiplied by the 19x leverage used. That’s a theoretical 800% Verlust; more than the money in the account.

Everyone loves leverage because they think of profits. Leveraging losses is a lot less exciting.

Also, if you could earn 96% annual returns and only use 5:1 nutzen, that is exponentially superior to earning 96% auf 19:1 nutzen. I need to compare the returns of Pilum to Dominari per unit of risk. That allows me to do cool things like

Minimize the negative variance of the returns
Increase absolute return
Dynamically increase/decrease strategy allocations if I find patterns in their interactions

It’s a lower tech way of averaging strategies, like the litte guy’s version of what Numerai is doing… except that I have to create all of the strategies myself.

Quantilator

I spent the last few months sending surveys to segments of my subscribers asking how I can better serve you. Articles about indicators are overwhelmingly my most popular content. The trouble with that content is that I can’t complete the research fast enough to keep up.

The most valuable thing I’ve learned from the developing algorithms for the past 11 years is my process of deciding whether or not an indicator offers predictive value.

Say that you’re interested in gaps: do gaps predict future returns? What I normally do is code a gap indicator in R, implement my analysis methodology and give a verdict. My methodology is kind of like a system for building systems. Using my approach usually takes an hour for every new idea that comes along.

An hour is pretty short. An hour is REALLY short compared to when I didn’t have a research methodology. I used to waste Monaten on junk strategies.

With Quantilator, I’ll be able to analyze anything in under 5 Minuten. I’ll only have to follow 3 steps:

Run a script in MT4 to export price data and indicator data
Upload the exported data to Quantilator
Analyze the results

This tool will be 100% frei. I’m planning to go through the most popular indicators in MetaTrader to analyze whether or not they offer an edge. I’m building a library of small edges that can be combined into powerful strategies like Dominari and Pilum. Und, in the spirit of open source, I plan to make that library available to you for free.

I’m writing this tool in Django, which is a Python framework for displaying web content. The initial version will do the analysis. I’m hoping to use this as an education tool. A bit of momentum can justify make it a fully fledged library with sample data, indicators and training videos and more.

Quantilator’s name comes from a key concept in my system analysis methodology; I break data into quantiles. These quantiles calculate average market returns for a given period of time. The quant in Quantilator refers to quantiles, but I really like the implied double entendre of making you a quant. Letztendlich, that is what I’m doing for you!

Update: Die Quantilator is now freely available at http://q.onestepremoved.com/

US Election Insanity

November 7, 2016 von Shaun-Overton Hinterlasse einen Kommentar

This election is a colossal embarrassment. I don’t expect anything to go smoothly tomorrow and the media is priming everyone to believe that Clinton is all but assured. Markets hate surprises. If Trump looks competitive at any point tomorrow, then it can be a major catalyst for unwelcome volatility.

Most Tier 1 banks are reducing leverage ahead of the election. They rarely do that just for show. The chances of volatility popping sky-high are, gut, sky-high. You’d do well to lower your market exposure accordingly.

A quick note for Dominari Traders

I’ve done the same in Dominari. I reduced my account leverage from 18:1 hinunter zu 3.5:1. It’s enough to keep me trading so that I can continue to monitor how Dominari performs. I’d rather miss out on profits that walk in front of a freight train.

Speaking of, I owe everyone a quick update on my trading performance.

You know what sucks about trading? Drawdowns.

You know what’s awesome about trading? Pushing out of drawdowns.

I took a solid punch on the nose right at the end of September, just as my copy-follow traders came on board with my new higher leverage. In a perfect storm for myself and them, I increased the leverage from 7:1 An 18:1 just in time for the drawdown to take hold.

What impressed me most was the 95% of the traders taking my signals stuck through the initial bumpy period. To them I say, “Bravo!”.

The guy that bet on Leicester City every year

September 5, 2016 von Shaun-Overton Hinterlasse einen Kommentar

Leicester City started the 2015 season with terrible odds of winning the Premier League Championship. Bookmakers only game them odds of 5,000:1 of winning.

To put that in context, you are more likely to die riding a bicycle than you were to win a bet on Leicester City. Oder, you can think of betting on Leicester City every year. If you bet on them every single year for 5,000 Jahre, you would expect them to win a grand total of… once.

2014 was hardly an indicator of their pending success. They were nearly relegated to a lower division (d. h., kicked out of the Premier League). And yet, they did win the championship last year.

Leicester City’s Biggest Fan

Meet John Michklethwait. He’s the former editor-in-cheif at The Economist and he’s currently editor-in-chief for Bloomberg. Klar, he’s a very smart man. And yet, despite the odds and repeated disappointments, John bet on his old love, Leicester City, every single year dating back to the 1980s. That’s roughly 30 years of nonstop losing.

It wasn’t a lot of money each year: just £20. We all have our indulgences. I see the value of having skin in the game. £20 on a season is enough to make one care, but not so much that he’s upset about losing it.

Then something disruptive happened. John moved to the US last year for his position at Bloomberg. The chaos of the move threw him out of sorts, and he accidentally forgot to bet on Leicester City in 2015. He bet on them every single year dating back nearly 30 Jahre. And yet the one year that he forgets to bet, not only did Leicester City win, but the bet paid out 5,000:1.

Let’s step back and calculate the cost of that oversight for Mr. Micklethwait.

£20 * 5,000 = £100.000.

A hundred… thousand… pounds. That kind of winning would put a nice dent in your mortgage, wouldn’t it?

The risk of low probability strategies

Everyone hears anecdotes about successful trend traders. Even winning only 30-40% der Zeit, they walk away big winners over time.

You live HERE. Math isn’t good enough. You also need to wonder if your strategy can handle real-world problems.

What if they took that even lower? They could move their stop losses closer to the market. They’d reduce the size of the average loser, but the winning percentage might also drop to 10-20%.

Mathematisch, this could work out identically. 30% winners that earn 5x the average loser make for a profit factor of 1.5. A strategy with nur 10% winners that make 15x the typical loser also have a 1.5 Profit-Faktor.

Mathematisch, this could work out identically. 30% winners that earn 5x the average loser make for a profit factor of 1.5. A strategy with only 10% winners that make 15x the typical loser also have a 1.5 Profit-Faktor.

They’re the same. Aren’t they?

Planet Earth isn’t the same as planet Math. In the real world, people get sick and miss trades. Oder, they move across the Atlantic and forget to place a £20 bet.

People move. They get sick. Computers break. Things can and will go wrong with trading.

Richard Dennis once commented that the Turtle Traders would often make their annual returns off of one, single trade. A single trade!

When your performance depends on positive outliers, you’re massively vulnerable to accidents. What happens if you’re sick that day? Or your internet goes down? Or your broker locks you out of your account on the worst possible day?

Life happens, brother. A plan that depends on perfection is no plan at all. You need to make yourself robust to failure. Or even better, you’d make yourself antifragile.

Winning percentages

I mentioned that you can do really well winning 30-40% of time. Why then, does my own trading strategy, Herrschaft, win 68% der Zeit?

Because I’m exploiting compound, exponentielles Wachstum. It’s not just how much you win, but the order in which you win it.

Let’s take two examples:

A ranging strategy with a profit factor of 1.3 that wins 68% der Zeit.
A trending strategy with a profit factor of 1.3 that wins 30% der Zeit.

Look at the red circles. Trending strategies are prone to extreme outcomes, both positive and negative.

Each strategy risks about 1% on any given trade. Und, the average of the range and trend strategies are identical in the long run.

Aber… and this is an important “aber”, the expected worst case scenario with the trending strategy is substantially more likely compared to the range trading strategy. In der Tat, the average is more average with a ranging strategy than with a trending strategy.

Warum das so ist? Because unusual losing streaks are devastating to trending strategies. Have you ever had a losing streak? It happens to everyone.

By using a strategy with a higher winning percentage, you’re making yourself robust to streaks of losers. Und, not to mention, your average length of a winning streak is considerably higher.

Even though you’re getting the same mathematical outcome, you’re making things much easier on your trading psychology when you adopt a strategy with a higher winning percentage.

Herrschaft & Exponential Growth

You may have thought to yourself, “68%? That’s kind of a strange number to pick.”

You’d be right. The choice of 68% winners was not a coincidence. Es ist, Tatsächlich, the win rate on my Dominari strategy.

Dominari is about more than just buying and selling. Trading is also about managing a portfolio and position sizing. Position sizing is phenomenally important over your trading career.

My backtest results for Dominari show that for every $2,500, the account increased to $17,855.35 nach 3 Jahre. That kind of compound growth doesn’t happen by accident. That’s why I’d like to share the good news with you in my webinar this week.

I’m going to show you how to put that exponential awesomeness to work in your trading account. Sound good? Klicken Sie hier to register for the FREE webinar.

Flat and happy

Juni 24, 2016 von Shaun-Overton Hinterlasse einen Kommentar

This is the first financial event since 2008 that’s hit the mainstream public. Even my friends from college are talking about the Brexit on Facebook.

My Dominari system only trades during the UK evening, so I felt comfortable leaving my system on overnight. When I woke up, jedoch, I didn’t feel the same. Did you see the GBPUSD chart? Holy cow! 1,300 pips in an hour.

GBPUSD lost more than 1,790 pips in a day from top to bottom on the Brexit.

This is the first time I’ve intervened in a trading system since April of last year. What makes me very happy, Obwohl, is that this intervention is all about protecting profits. I’m up 6.69% since I began trading the finalized version of Dominari on April 15.

My equity curve as of June 24, 2016.

myfxbook.com/members/QuantBar/dominari-pepperstone/1591822 – my results at Pepperstone

Dominari isn’t intended to trade these types of markets. Also, instead of deciding to “see what happens”, I’m flat and happy until we see how the markets open after the weekend. I expect big gaps. I don’t feel like gambling which way the gaps may go.

If you clicked the original link, you noticed that the equity curve is marching straight up. That’s what’s supposed to happen. But like any good system trader, I wanted to see it working in the real world before I upped the capital commitment.

Earlier this month, I decided to trade a second account at FXCM, this time in USD. That brings my total accounts to €8,500 and $5,100. That’s about $14,600 in USD terms between the two accounts.

The FXCM account started live trading on June 6. Before then, I made sure to test it on an FXCM demo account to confirm that my edge wasn’t completely dependent upon broker selection. I’m happy to report that the FXCM results are closely mirroring those at Pepperstone.

myfxbook.com/members/QuantBar/dominari-fxcm-mt4/1679763 – my results at FXCM.

How badly do I want in?

März 22, 2016 von Shaun-Overton 10 Kommentare

You absolutely must check your trading system’s performance on a regular basis. You’re going to miss most of the problems from watching your equity curve alone.

That almost happened to me a few weeks ago. When I observed my account, I noticed that the real results had dramatically underperformed the hypothetical results. A quick review showed me that I only took 271 trades over the prior week, whereas my backtest expected to find 360.

I was only trading 75% of the setups! What could explain the missing trades?

Finding the flaw

One feature that I wrote into the MetaTrader version of the Dominari was a maximum spread feature. I’m paying commissions, so the idea of the rare but possible scenario of paying a 10 pip spread to enter a trade seemed intolerable. I added a maximum spread feature to prevent getting ripped off.

I also didn’t put much thought into what happens if the spread is too wide. My initial instinct was to put the EA into hibernation for a few seconds. It would then wake up and check the spread. If the spread narrowed enough, it would send a market order. But in my haste to start trading, I forgot to also require that the price be near my original requested price. That design would have allowed the market to drift up 10 pips and then, if the spread narrowed, dramatically overpay to get in the trade.

The new method for capping the spread paid uses limit orders if the spread is too wide. The advantage to this method is that it solves two simultaneous problems. The first one is easy to understand. A limit order has a limited price. It’s not possible for the price drift described in the above paragraph to occur. I either get the price I want or the market moves without me and I miss the trade.

Equity curve since I made the execution changes on March 16.

The second advantage to using limit orders on entry is the fact that a limit order rests on the broker’s server. The hibernating method could potentially miss fractions of a second where the spread temporarily narrows to an acceptable price. Limit orders catch all price quotes, improving my theoretical likelihood of a fill.

Reality proved the theory after a week of trading. Instead of taking 75% of all possible signals, I’m now taking 87.5% of signals. That’s a result of the new limit method and my willingness to pay a wider spread to enter a trade.

More improvement

The question at the top of my mind was, “Should I be willing to pay even more to enter these trades?” Like a good quant, I immediately decided to calculate the question instead of haphazardly guessing.

I wrote a script in MetaTrader to search for every limit order in my account which was cancelled. I then looked at what the hypothetical performance of those trades would have been if I had simply paid the exorbitant spread.

It turns out that I should be willing to pay a lot more money to enter these trades.

There have been 50 cancelled limit orders within the past week, 44 of which were theoretically profitable. The average theoretical profit per trade was €1.28 compared to €0.33 for all executed trades. That’s a massive 287% difference in profitability!

The other shocker was the percent accuracy. 44 von 50 implies an accuracy of 88%, im Vergleich zu 64% accuracy on executed trades. 50 signals isn’t a lot. Am I getting too excited about missed profits or is that bad luck?

Basic statistics gives an answer with a high degree of precision. If the real accuracy is 64%, then you would expect to see 50 * 0.64 = 32 winning trades in a random sampling. My observed, theoretical accuracy with these limit orders was 44 orders out of 50, Das ist 88% die genaue.

It turns out that I should be willing to pay a lot more money to enter these trades.

Die Standardabweichung für 64% accuracy on 50 orders is 0.48, which we can then use to calculate the standard error. The standard error on 50 orders is sqrt(50) * 0.48 = 3.42 Bestellungen.

And finally, the standard error gives us enough information to compute the z-score. The z-score is the observed values-expected values/standard error, Das ist (44-32) / 3.42 = 3.5. A Z-Ergebnis der 3.5 has a probability of 0.000233 occurring due to random chance, or about 1 in 4,299 Prüfungen.

Fazit: The statistics say with high confidence that my non-executed orders are substantially more accurate than my executed orders.

With the orders being both more accurate and having a higher per trade value, I increased the maximum spread that I’m willing to pay by 53%. While that sounds oddly precise, the per trade value might be substantially overestimated. I ball parked a guess that paying 40% in trade costs for a high quality trade seems reasonable. That number may have to go higher in order for me to measure the details.

Ideas for exploration

The amazing extrapolation from the live order analysis is that the spread seems to predict my likelihood of success. Wider spreads make me more likely to succeed and with a better risk:reward ratio. My project over the next few days will be to start logging my spreads at signal generation time to evaluate whether the spread predicts the profitability of my signals.

Oddly enough, there might even be a paradoxical outcome where narrow spreads predict my failure. More on that when I have enough data to answer the question.

Große Veränderung zu Dominari

März 9, 2016 von Shaun-Overton 24 Kommentare

I said it Hier und Hier und Hier. The biggest issue with my Dominari is trading costs. Things aren’t going to really take off until I do one of two things.

Reduce the trading costs
Make more money on each trade

I’ve been working on Dominari since around September or October of last year. After racking my brain for months, I more or less wrote off the idea of improving the trade profitability.

That suddenly changed last week on Friday after the market closed. The best reason to trade my own systems live is that the agony of underperforming forces creativity. The feeling reminds me a lot of Daymond John’s (the guy from Shark Tank) new book the Power of Broke. When life isn’t going your way, it’s the resourceful and creative who are best able to get to the top.

Nobody wants to feel broke or under extreme stress. As much as we hate those feelings, they’re often the strongest drivers of performance. That’s how I feel right now with Dominari. I’m so close to getting there and wasn’t sure how to fix that missing ingredient.

If it weren’t for that stress, I would not have had my simple but very powerful insight last Friday.

And please don’t laugh. The change is so dumb and obvious that you’re going to wonder what’s wrong with me. When you’re in the thick of designing a system, the ugly truth is that sometimes you get lost in the weeds. Or to use another botany metaphor, you only see the trees instead of the forest.

My key insight was to slightly modify the exit strategy to use limit orders, whereas previously I only exited based on the close of the bar. I noticed two repeated behaviors that finally beat me over the head enough that the point finally sank in.

The number of occasions where my trade closed in the optimal location seemed to be significantly outweighed by the amount of money left on the table. The key insight for me was realizing where to optimally place that limit order. And for those of you on my newsletter, it happens to be closely related to the Auto Take Profit that I’ve been talking about all week.

Backtest assumptions and results

My operating mantra when doing backtests is to minimize the number of assumptions. Spreads for retail traders have changed dramatically from 2008 to today. I remember working as a broker at FXCM when our typical spread on GBPCHF was something like 8-9 Zacken. I now routinely pay something like 2 Zacken. It’s impossible to model what happened in the middle without haphazardly guessing.

I find it far more convincing to analyze the raw signal, both on historical and recent market data, then to interpret whether trading costs are likely to be favorable in today’s markets. “Raw signal” is the ideal signal, one which assumes perfect execution, no slippage, no rollover, no spreads and no commissions. The natural result is that you’re overstating historical performance, but the benefit is that you have a very clear idea whether the core idea is a system capable of predicting the market with reasonable risks.

The total leverage employed in the portfolio is 7:1. If I have a $50,000 trading account and held a position in every currency pair in the portfolio, then the notional value of those trades would equal $350,000 (50k * 7).

Another key point is that I used a fixed position size of $12,500 pro Handel. The size of the trade never increases or decreases during the backtest, which allows me to isolate the impact of the raw signal without adding the variable of money management.

Here are my trade metrics with version 1 of Dominari. Click the images to view them in full size.

The first version of Dominari had a profit factor of 1.26.

After here’s the change with Dominari version 2.0.

My new version of Dominari increases the profit factor to 1.59 with a significantly lower drawdown.

My best case scenario was to hope that the profit factor would jump another 10 points or thereabouts, maybe stretching the profit factor to 1.35 or thereabouts. It’s incredibly exciting to see the edge over breakeven more than double (going from a $0.26 edge to a $0.59 cent edge).

What I’m most excited about is the skew in the returns. Most mean reversion systems look for an edge but are overwhelmed with the impact of losing trades. That was the case with version 1.

The largest losers outweighed the largest winners in version 1.

This new version of Dominari is the very first bedeutet Umkehr strategy that I’ve ever developed where the winning tails (ie, the biggest winners) nearly equal the losing tails (the biggest losers). It’s almost always the opposite with mean reversion strategies. Anders gesagt, the risk profile of the extreme outcomes significantly improved with version 2.

The impact of the biggest winners is nearly identical to the biggest losers with version 2.

And the metric that most traders care about the most, Auszahlungsbetrags, is wildly improved. Version 1 showed a drawdown of 5.72%. The new version is a fraction of that at 1.77%.

Out of sample backtest for Dominari version 2

The out of sample performance is nearly identical to the in sample performance, despite significantly different market conditions.

When I walked my test out of sample onto recent data, covering 2013-2015, the performance characteristics of version 2 are nearly identical to the in-sample test. The profit factor was identical at 1.59, and the max drawdown was 2.01% für 2013-2015.

Translating the theoretical into expected performance parameters

Wieder, those metrics above are in the ideal world of perfect execution and no trading costs. The real world performance will have lower returns and higher drawdowns. The advantage to having live trade data is that I can now make some kind of intelligent estimate of my expected trade accuracy and profit factor. Just how overstated are the idealized returns likely to be?

The process that I went through to calculate the expected profit factor in the real world is a 5 Schritt Prozess. I don’t think it’s going to make any sense if I try to write out the steps in conversational English. Stattdessen, I’ve chosen to share a spreadsheet where you can view the step by step process for how extrapolating live trading data into expected performance with the new strategy. Klicken Sie hier to view the spreadsheet.

The expected profit factor for my live trading is expected to be between 1.29 An 1.39. The expected percent accuracy for live trades should jump from 62.55% An 70.8%.

The traders who will get first crack at the Total Access Apprenticeship are those are subscribed to the free newsletter. If you’re not signed up, make sure to fill in your email address in the orange box at the top right of this page.

Monitoring my live trade execution

Februar 10, 2016 von Shaun-Overton 29 Kommentare

Dominari’s biggest risk is its trading costs. In the midst of losing 6 days in a row, I found myself extremely concerned about Dominari’s performance. Did the signals go bad all of a sudden or is this a normal drawdown? Is Dominari losing because of trading costs?

I decided to start analyzing my FXCM account. Part of the nerves were driven by the fact that it took 2 weeks to setup the account. The compliance process took far longer than usual because I’m a former employee. Two weeks later, I turned on the account just in time to a) miss the biggest equity growth and b) to catch the biggest drawdown.

I felt more hostile to the FXCM account performance because I didn’t have any profits to pad the losses. This is all coming from my original risk capital. And I’m having my third child soon. Giving birth to kids in the US is incredibly expensive. I’ve got better uses for the money than to throw it away in the markets!

Also, the real question is: am I losing because it’s just a rough patch or because FXCM is eating my lunch?

backtest-equity-fxcm

This image is a backtested equity curve over the same period of my live performance. I’ve traded live since January 28, but the trading didn’t begin until the afternoon. Wie Sie sehen können, I again missed another patch of strong performance.

The rest shows something of a fairy tale. The backtest shows a return of 19.13% over that period, whereas my live performance is down 10%. How much of that is due to commissions, Verbreitung, rollover and slippage?

The backtest shows a profit of $956.65 with no trading costs.

My real results, die 1) show a profit on the backtest but 2) are actually showing a loss in real life, can be used to estimate a floor for my trading costs. The formula for that is
( Total profit and loss + Kommissionen + rollover) / total trades, which is currently $1.58 in costs per trade.

The commissions and rollover are easy to separate out using either Myfxbook or the FXCM account report. The grand total spent so far on commissions is -$239.80 und -$3.05 on rollover.

The hardest part to separate is the spread paid. I’m not recording the spread paid on every trade (maybe that’s a mistake and I need to add it). But I’m going to use the table below to estimate. I took a random sample of 30 trades from the 501 trades completed at the time of my analysis.

Spread Paid	Slippage
0.000198523	1.49E-05
0.000153951	-5.13E-05
0.000455823	0.000227912
9.98E-05	0
0.000161242	-0.00313413
2.76E-05	-9.19E-06
5.55E-05	6.94E-06
0.000110898	-1.01E-05
9.24E-05	0
9.91E-05	-1.57E-16
6.55E-05	1.31E-05
4.85E-05	2.08E-05
8.22E-05	-1.67E-16
6.87E-05	0
6.95E-05	-1.65E-16
0.00015173	-2.17E-05
9.43E-05	-2.36E-05
9.38E-05	-0.00225922
7.61E-05	-0.0024735
0.000160038	1.00E-05
0.00013502	0
0.003542625	4.52E-05
0.000222978	-0.00376275
7.62E-05	0
0.000432797	7.73E-06
2.61E-05	0

The average slippage (the right column) is a stunning -0.044%. I’m getting negative slippage on average with FXCM. That’s outstanding! FXCM is improving my fills even though my entries are requested at a worse price. Whatever misgivings I’ve had about FXCM in the past are alleviated. That’s impressive execution.

Estimating the spread paid is much more difficult. I’ve chosen to take my average trade profit on a $5,000 account as the starting point. The trouble is that the value of an average winner can depend on the account performance. If I use stagnant position sizing, then the drawdown doesn’t effect the value of the average winner. Under that assumption, the average winner is $3.48 pro Handel.

But if I use compound position sizing, the drawdown eats away most of the profits. That drops the average trade value down to $1.70.

I converted the spread paid from pips into percentages. Using EURUSD as an example, ein 1 pip spread works out to 0.0001/1.12727 = 0.000089. The reason for doing this is so that I can compare the spread on EURUSD to something with a much wider spread like AUDNZD. The spread is wider on AUDNZD, but the value of a NZD pip isn’t the same as a USD pip. Percentages allow for an apples to apples comparison.

The average spread paid in my sample was 0.00026157605, Das ist 0.026%. Putting that back into terms relative to my account balance, I’m paying 0.026% * $5,000 = $1.31 per trade in spread. Across 420 Facharbeit, Das heißt -$550.20 in spreads.

Total costs are spread, commissions and rollover:
$550.20 + $239.80 + $3.05 = $793.05

On a per trade basis, Das heißt $1.78 in costs per trade from my estimates.

The total profit on the backtest was $956.65, but I missed about $550 of it because trading didn’t start until 17:00 on the 28th of January. That leaves the backtest profit somewhere around $406.65.

That puts the re-estimated profit and loss at $406.65-$793.05 = -$386.40. The actual loss is -$469, which I feel is a reasonable discrepancy based on the fact that I’m estimating how much profit was contributed on January 28 instead of knowing for certain.

The conclusion is that I need to turn off this trading at FXCM. Even if I joined their active trader program and traded in the top tier, it would only save me half the commissions. Most of the trading costs are in the spread and not commissions. I’m seriously considering a move to a broker that will allow me to make a market by posting limit orders. Aber zuerst, I’ll need to go over my Pepperstone account to review the trading costs for myself and clients.

The Big Switch

Februar 1, 2016 von Shaun-Overton 60 Kommentare

I moved all of my trading funds into Dominari this month.

I’ve been talking about this system ever since I start live demo testing back in November. Unnötig zu sagen, I’ve been extremely satisfied with the live results.

My initial live account started trading on January 4 with a starting balance of €1,000 at Pepperstone. Once I saw that the live trades matched my expectations, I quickly kicked that account balance up to a total of €10,000.

And because I want to test the effect of broker selection, I threw another $5,000 in an FXCM account. Die Pepperstone account contains the bulk of the money and runs the MT4 version of the strategy. The FXCM version uses Seer, which has been more of a pain to get running smoothly, though I can say that it’s still my favorite platform for testing ideas.

The cost non-problem

The equity curve of the Dominari without trading costs from 2013-2015.

My biggest concern about launching the strategy live was trading costs. Some back of the envelope math suggested that everything would be ok. Live demo testing indicated that it would be ok. But you never really know until you start trading live.

Through the month of January, I’ve consistently monitored the commissions relative to the profit. I fluctuates up and down with the trading account, but I estimate that the spread commission costs are approximately 20-25% des Gewinns. That’s a relatively high percentage, although it’s nowhere near as bad as it could be given the extreme trading frequency.

Dominari is a high-frequency strategy that averages about 49 trades per day on 28 Währungspaare. Everything happens so fast in the account that I’m hard pressed to remember any individual trades. Dominari executed more than 900 trades in the month of January alone. It’s dizzying watching the equity fluctuate up and down. The important thing is that the trend moves from the lower left to the upper right.

QB-Pro?

It’s not dead. I still believe it’s a great strategy and totally worthy of your trading. Tatsächlich, both Dominari and QB Pro depend critically on one of my favorite indicators, die SB Score.

The reason I got into algorithmic trading is that it emotionally separates me from the responsibility for the outcome. If I have a losing month, it’s just the strategy. There’s not much to do about that.

When there’s an element of discretion, it’s difficult to separate the random component. Sometimes you win, sometimes you lose, but you generally expect to make money. When there’s discretion in an algorithmic strategy, it’s very difficult to know whether losses are my fault or simple bad luck.

QB Pro depends on the manual portfolio selection. Nicht überraschend, I heavily favor Dominari because the portfolio selection is static. I can say with my hand over my heart that Dominari is a black box, fully algorithmic strategy.

I’m still updating the portfolio over at Seer Hub and will continue making the selections for clients. For clients that are in the managed account at Pepperstone, I switched the strategy in the middle of the month. I feel responsible as the manager to give clients the best possible performance. And since that’s where I’m placing ~$16,000 of my own money, I feel a fiduciary duty to do the same for my customers. Dominari is where I believe the best opportunity lies.

How you can get Dominari

I plan to offer Dominari as trading signals to anyone with a MetaTrader account within the next month or so. A lot of hard work has gone into developing the strategy. And while I’m confident to the tune of $16,000 of my own money, I want to be even more certain before I release Dominari to a wider audience.

What do you think of the results so far? Leave your thoughts in the comments area below.

Live-Demo der Prüfung eine neue Strategie mit Limit-Orders

November 24, 2015 von Shaun-Overton 17 Kommentare

Ich komme mit erstaunlichen Blick Backtests die ganze Zeit. Dies ist das jüngste Beispiel für die Verwendung SB-Partitur.

Die Equity-Kurve der neuen Strategie, ohne die Handelskosten.

Die freie und hypothetischen Version der Strategie ergab $79,618.82 für eine unzusammengesetzt Rückkehr der 796.19% über einen Zeitraum von 3 Jahre. Die Strategie handelt alle wichtigen Währungspaare. Wie Sie sehen können, die Signalqualität über mehrere Marktbedingungen nahezu konstant bleibt. Das sieht großartig aus.

Das Problem ist, die Handelskosten. Es ist immer der Handel Kosten, die das Leben schwer machen.

Handelskosten fallen auch Gewinne 98.22%

Ich nehme immer eine stark pessimistische Sicht, wenn es um unter der Annahme, Handelskosten und Rutschen kommt. Es erfordert eine Menge der intellektuellen Redlichkeit, aber bemüht, rosigen Annahmen zu vermeiden, spart eine Menge Schmerz und Enttäuschung auf der Straße. Die Annahmen sind wirklich schwere Kreuz auf Währungen, in denen wir davon ausgehen, Spreads und Rutschen Norden 5 Zacken.

Leistung mit pessimistischen Handelskostenannahmen sinkt auf nur machen $1,000 im Ergebnis. Die Strategie muss nicht in die Mülltonne zu gehen, aber es ist weit von bereit für die Prime Zeit. Es gibt kein Szenario, wo es Sinn macht, mit Market Orders Handel.

Allgemeine Charakteristiken

Durchschnittliche Trades pro Tag: 39
Währungspaare gehandelt: 27
Prozent Genauigkeit: 66.52%
Stil: Mean-Reversion-
Charts: Stündlich

Wie man auf die billige Tour zu handeln

Ich bin bekanntlich sparsam. Einer meiner Fraternitätsbrüdern in der Schule erzählt noch immer Geschichten über mich zu zählen Kleingeld und die Verfolgung in MS Money.

Diese Art von Mentalität, fährt meine Frau verrückt… aber es ist eine echte Bereicherung für einen Händler! Händler verdienen ihr Geld auf die Margen wie jeder andere Unternehmer.

Ich verbrachte gestern Nachmittag Codierung diese neue Strategie mit einer leichten Drehung. Anstelle der Zahlung der Ausbreitung auf jeder einzelnen Handels, was ist, wenn ich Limit-Orders, um zu versuchen und verdienen die Ausbreitung?

Die aktuelle raw Spread auf EURUSD ist 0.3 Zacken, Das lohnt sich $0.03 pro microlot. Die Trading-Kommissionen sind $0.03 pro microlot. Wenn ich verdienen eine zusätzliche $0.03 pro microlot, , dass das zumindest die Handelskosten. Auf Paare wie NZDCHF wo die rohen Spread 1 Bib, dass fügt eine zusätzliche $0.04 ($0.10 – $0.03) je Seite. D.h., das Einstiegssignal macht eine zusätzliche $0.04 und die Austritts macht auch eine zusätzliche $0.04 auf jeder einzelnen Handels.

Selbst ruhigen Paaren auf NZDCHF weisen immer noch ein gewisses Maß an Rauschen in jeder Bar. Ich habe keine Forschung, um es wieder getan, aber meine subjektive Erfahrung sagt, dass die Dochte aus 90% oder mehrere der Balken zumindest so lange, wie die Ausbreitung ist breit.

Händler verdienen ihr Geld auf die Margen wie jeder andere Unternehmer.

Anders gesagt, wenn die Ausbreitung auf EURUSD ist 0.3 Zacken, dann wird die Differenz zwischen der offenen und niedrigen Preis auf 90% Bars sollte mindestens 0.3 Zacken, auch. Das ist meine Vermutung,, auf jeden Fall.

Ein Beispiel für das Drehen der Strategie, Limit-Orders verwenden

Sagen, dass mein Signal der Markt gerade aufgetaucht zu geben. Der aktuelle Preis für EURUSD ist 1.06457 x 1.06462, Das ist 0.5 Zacken. Die Backtests davon ausgehen, dass ich traf die 1.06462 Preisvorstellung und zahlen die Ausbreitung.

Die Idee für meine Prüfung ist mein Limit-Order zu setzen 1.06457. Da ich ein Einzelhändler, das bedeutet, dass ich frage den Markt nach unten zu bewegen halben pip, bevor ich bekommen, um eine Position haben. Erfordern einen kleinen Schritt zu meinen Gunsten theoretisch verdient mehr als einen Sprung in den Markt mit beiden Füßen.

Live-Demo Testen beginnt

Ich könnte theoretisch zu modellieren die Idee, in einem Backtest, aber es gibt kritische Annahmen, dass es keinen Sinn machen,.

1) Die durchschnittliche breitet sich in meinem verfügbar 2009-2011 Backtest Periode waren viel weiter als heute
2) Der Spread variiert erheblich im Laufe des Tages. EURUSD ist routinemäßig so günstig wie 0.2 Pips in der Europäischen sesssion, kann aber mühelos über 1.0 Noppen in den langweiligsten Teile des asiatischen Handel.

Das zweite Element konnte in einem Backtest komplett schädlich sein. Es ist besser, die Idee auf einer Live-Demo testen und etwas näher an realen Handelsdaten.

Die erste 15 Stunden Live-Demo-Tests.

Ich bin nur 15 Stunden in die Test, aber zumindest alles, was zu einem guten Start ist.

Das Ziel für den Test ist einfach: Platzieren Sie mindestens 300 Trades auf dem Konto. Das sollte nur etwa 2 Wochen, da die Strategie ist so hyperaktiv.

Das Kriterium für den Erfolg ist ebenso einfach: ist die Echtzeit-Demo-Trading-Performance erfüllen oder die Backtesting-Performance gegenüber dem gleichen Zeitraum überschreiten?

Ich begann den Handel in den Abend im November 23, was bedeutet, dass ich auf meinen sollte 300 Handelsschwelle um das 10. Handelstag. Das Handelsfrequenz hat schwanken, aber das sollte irgendwann um 4. Dezember auftreten.

Auch wenn ich Live-Demo Daten, Ich werde eine Markteintrittsbacktest von November laufen 23 bis Dezember 4. Wenn der Demo-Handel, die Limit-Orders verwendet, übersteigt den Markteintritt Backtest, dann habe ich eine angemessene Grundlage für die Annahme, dass die Strategie ist bereit, auf einer kleinen Live-Konto zu handeln.

Ich bin auch ein Bügeleisen aus Fehlern, die während der Live-Simulation angezeigt. Mehr als wahrscheinlich, diese Termine werden nach hinten geschoben werden. Ich habe bereits gefunden 2 Fragen, die Untersuchung nach nur verlangen, 22 Facharbeit. Es hat keinen Sinn in der Beurteilung einer Strategie, wenn es nicht genau wie angegeben durchführen.

Code die gleiche Strategie zweimal?

Sie haben wahrscheinlich bemerkt, dass die Vorwärtstest Equity-Kurve ist von MetaTrader. Warum sollte ich in einer Plattform zu testen, aber in einem anderen auszuführen? Alle meine Backtests wurden in Seer getan.

Wenn zwei Menschen arbeiten auf einem Problem und sie beide zur gleichen Antwort zu gelangen, dann werden sie wahrscheinlich das Problem richtig beantwortet. Die gleiche Logik gilt für die Programmierung. Wenn ich zu programmieren, eine Version der Strategie und Jingwei Programme eine Version der Strategie, sie sollen genau die gleichen Trades zu platzieren sind. Etwaige Abweichungen bedeuten, dass jemand die Programmierung ist falsch.

Ich routinemäßig verwenden diese Methode, weil die geringste Fehler in der Logik kann drastisch unterschiedlichen Handels Ergebnissen führen. Es ist der Unterschied zwischen machen eine Menge Geld und verlieren eine Menge Geld. Ja, Ich opfern Effizienz. Die Ausgangslage für eine Strategie so hoch, dass es besser ist, zu machen sind 2 Menschen, die gleiche Arbeit im Austausch für das Vertrauen zu wissen, dass es richtig gemacht.

MetaTrader ist schlechter als von jeder Maßnahme Seer. Der einzige Grund, dass ich meinen Code in MetaTrader schrieb, war, dass ich bin gespannt, um die Idee zu testen. MQL4 ist einfach für mich zu codieren – Programmierung für MetaTrader ist eine unserer wichtigsten Dienstleistungen.

Nach Jingwei beendet die Programmierung des Seer-Version der nächsten Woche (sie ist off für Thanksgiving), Ich werde die Grundlage für den Vergleich meiner MT4 Version gegen Aussage haben. Es ist schrecklich ineffizient, aber ich weiß auch, wie wahrscheinlich bin ich aufgestellt, um Wochen auf die Analyse Trades verschwenden nach Regeln, die Sie meine Strategie nicht genau. Sicher ist sicher!!!

Wie, um die Ränder zu mästen

Eine Sache, die ich hasse über Einzelhandels ist, dass nur sehr wenige Veranstaltungsorte bieten eine wahre ECN. Handel an einem traditionellen Retail-Forex-Broker bedeutet, dass ich warten müssen, bis die Ausbreitung herabgekommen, um meinen Auftrag zu berühren. In dem Beispiel mit EURUSD gab ich, es, dass sich der Markt erfordert 0.5 Pips zu meinen Gunsten, bevor ich eine Füllung.

Handel an einem ECN würde die Wahrscheinlichkeit der Aufnahme einer Füllung auf der Limit-Order deutlich erhöhen. Verwenden des EURUSD Beispiel, in dem die aktuellen Preise 1.06457 x 1.06462, Ich würde eine Buy Limit Order über das Angebot zu platzieren 1.06457. Wenn jemand auf dem Markt verkauft zu diesem Zeitpunkt, es bedeutet, dass mindestens ein Teil des Auftrages würde fast sofort gefüllt werden.

In der Tat, Handel an den Einzelhandelsspreads im schlimmsten Fall zur Ausführung enthält. Der Preis muss passen 0.5 Pips zu Ihren Gunsten, um gefüllt zu werden. Wenn Sie den Handel auf einem ECN und der Preis fiel 0.5 Zacken, würden Sie jedes Mal gefüllt bekommen. Sondern Sie erhalten auch die Chance, früher und schneller gefüllt, weil, wenn jemand kommt und geht kurz auf den Markt zu bringen, die Reihenfolge sitzt auf dem Buch auf jemanden warten, es zu treffen.

Smart-Händler tun alles in ihrer Macht Stehende zu mästen, die Ränder

Ich bin mit der Demo-Test jetzt fortfahren. Wenn sie erfüllt oder übertrifft die Backtest-Ergebnisse, Ich werde dann mit dem höchsten Grad des Vertrauens möglich, dass das Verfahren bereit für die Live-Trading ist. Wahrscheinlich werde ich mit ein paar tausend Dollar zu starten für den ersten Monat. Dann, wenn es gelingt,, Ich werde wirklich anfangen, es zu skalieren.

Es gibt keinen Grund, dass alle Gewerke muss auf H1-Charts auftreten. Ich kann immer die Handels Intervallen verschieben um eine Minute, zwei Minuten… 59 Minuten. Und auch dort, es ist möglich

Meine ideale Szenario ist es, auf einem ECN Veranstaltungsort Handel der Strategie, was eine Mindestguthaben von $250,000. Das Geldbetrag ist weit höher als ich komfortablen Risikoabbau. Die alte Regel des Handels ist, dass Sie nie Gefahr, mehr als Sie bequem verlierst.

Das heißt, ich werde wahrscheinlich nach einem Partner suchen, um sicherzustellen, dass die Strategie, läuft in der besten Umgebung möglich sein (ein ECN). Sind Sie vielleicht, dass Partner? Wenn ja, senden Sie eine Email an info@onestepremoved.com~~V und sich vorstellen. Nichts wird für mehrere Monate geschehen, aber es dauert immer eine Weile, um Beziehungen aufzubauen und sich wohl fühlen mit einem Projekt.