Thursday, 1 February 2018

It's the Numbers that Count in an Algo

The reports below are for another one of my algos. This one is for the DAX using 18 minute bars,  It was created using the last 3 years of data.

Interesting stats in the extract below, the last almost 6 months of trading,  is that has a nice average trade profit that can handle any slippage that is likely to occur, the Profit Factor is robust and the win rate is unlikely to make me turn off the algo after 3 losing trades in a row. Also, the drawdown is quite acceptable. When I look at the month by month stats I see that the profits are spread evenly over each of the almost 6 months.

However, all this is not enough. Its not hard to create a set of stats that show a great historical result. It's easy! Just curve fit the algo to the data and it looks great. What I do after creating an algo is the robustness tests, more than seven of them. The final one is the walk forward analysis. Here is the WFA summary that was the final PASS to go live.

I use three platforms for my algo trading: NinjaTrader, MultiCharts and TradeStation. All are great platforms but have some differences in how they do the various testing and optimizations.

Wednesday, 24 January 2018

This Algo Trades Intra Day off Daily Data.

This Algo Trades Intra Day off Daily Data is the title of this post and that's exactly what I want to highlight.

Some more volatile markets trade very well of daily data and I only need to trade intra day and take the sweet spot out of the trend. I must confess that I could only discover this by data mining, using genetic code creation software.

Using genetic programming technology has an added benefit: I am more disciplined in not turning the algo off and on as I don't really understand the algo's logic. This is by design. I believe in the process I went through to create the metrics behind the algo and satisfied with the results of the robustness I built into it.

Once again, the harder I work the luckier I get.

Tuesday, 16 January 2018

An Algo Creation in Progress

To create an algo, I reverse engineer it to get the results profile I want. The results below show an algo for the DAX that trades 3 minute bars but can only enter during the first 2 hours of the session. I have identified this time as one that has opportunities. I then looked at the metrics of the results I wanted. This is how far I have gotten so far. There are 3 years of data in the results.

The next step can be to just do a Monte Carlo analysis to test for robustness as well as to test the algo with different periodicity data. Or, I can add rules to reduce risk or drawdown by eyeballing a chart. The risk is curve fitting. I rather accept risk than do anything that curve fits. My goal is to ensure robustness and there are a number of things that can be done to check for robustness.

I've been getting quite a few emails regarding algos. People are beginning to understand that algo trading is a lot easier than discretionary trading for most people because instead of the decision making process using discretion, you are using a tested algorithm whose past results you know and which give you expectations (but not a guarantee) of future possible profitability. See the disclaimer. Adding a number of algos into a portfolio is designed to further add robustness and smooth out the equity curve.

Saturday, 13 January 2018

Different Ways of Trading an Algo

Today I am posting the results of a different type of algo. This algo is one that I use on many different markets. It was created by me using momentum and trend indicators. No genetic creativity but purely observation and test based logic.

As you can see, the algo has a little less than 3 years of data in its test results. The reason for this is that, after testing, I discovered that the algo works best by using that shorter amount of data to optimize and then trade it for a month before a new re optimization. In the Periodic Returns Report  you can see the Out of Sample profitability for January so far.

This algo is optimized every month and uses that almost years of data for that reoptimization. During that month the algo trades fully automatically. This means that my expectation is that the algo will trade more consistently than the historical statistics show, particularly that the drawdown is expected to be much less.

Its important that proper testing is done. Its not just a matter of pressing the OPTIMIZATION button and taking the most profitable result. The internal results of the optimization, such as symmetry, distribution of trades, average trade, ratio of draw down to profit are critical. I've posted links in this blog to the books that I recommend if you're interested in this way of trading. I'll be writing more on this theme.

Saturday, 6 January 2018

Fully Auto Algos

There are lots of ways of using algos. The benefit is that after creating a fully tested algo you have not only a fully tested and walked forward strategy but you have a trading plan built into the process as well.

The strategy below is a very good example. It is an algo based on the ES and uses DAILY RTH data. It only trades at the open so is very easy to follow.

This strategy was created over 5 years ago by using genetic programming technology. The out of sample profitability for the last 5 years or so is:

I can trade this algo in different ways, with futures and let it run fully auto or with options and choose from different strategies such as credit spreads or butterflies. The algo takes away the difficult decision making process. Its robustness having been profitable for more than 5 years may change if the market changes from being so unidirectional. However, the data used to create the algo goes back to the year 2000.

Algo trading is an important part of my trading arsenal and complements my discretionary and option trading. It does take work to find and test the right algos.

Tuesday, 12 December 2017

What are "THEY" Doing?

Reading this blog and if you've done any of my training or mentoring sessions there's one prominent thought that I have tried to ingrain in everyone when they are trading.  Always ask yourself: "What are THEY Doing". The "THEY" of course is the balance of the market. This is the nett order flow. Its also sometimes questioned as "who's in charge".

This is the very basis of trading. Everything I do, every mark on my charts, every thought in my head is designed to answer that question. Once I have that answer I know, on the probabilities but not absolutely, what should happen next. But I have to keep on asking myself that question as every tick unfolds so I know when to get out if I'm in or when to get in if I'm out.

The above is a Crude chart of 3333 contracts. The reds are the deltas of sells and the greens are the deltas of buys and the width describes the relative volume traded at that price.

This chart has no bells and whistles, no zimmer frame, nothing to take your attention away from what THEY are doing. Trading the right edge of the chart requires a lot of practice and observation. Adding a couple of indicators helps in the early stages but perhaps they become a hindrance as time goes on. The jury is still out on that.

But rest assured, the only thing that counts in trading is knowing what THEY are doing!

Tuesday, 5 December 2017

Lets Not Forget Discretionary Trading

I thought it would be a good time before the end of the year to show my updated discretionary trading workspace.

The key, the so-called holy grail, the magic or whatever you want to call it is looking at what orderflow is doing at support and resistance areas.

This is now and always. Nothing has changed in what we look for although the tools we use have been updated considerably with the technology.

I now manually trade only for an hour or two a day. Its usually the DAX when I'm in the European time zone but can be the ES and CL or 6E in other time zones.

I still use Market Profile, Volume Profile as well as the indicators you see on the chart below to find the areas where orderflow will reverse or breakout. The arrows around the bars on the NinjaTrader chart reveal what is happening inside that bar.

I keep it simple. No complications. The context is king and I make a trade when the orderflow is interpreted as favourable in each particular context. This is understanding what is PROBABLE when certain things happen and understanding that the action will happen X% of the time. When it is clear that the action will not happen then I exit. If the market moves against me but I was too early and the trade is still probable, I will double down at certain distances from my original entry. I will then cut if the trade is invalidated. I do this because mathematically it works for me.

The bottom indicator is the Squeeze. It helps identify breakouts with momentum after a pullback or sideways action. But its the orderflow that's the trigger.