Anyone Short?

This is my basic ES algo again using NinjaTrader and Bloodhound. As you can see, there were only LONG trades on this whole move up. The FloBot identified the trend and provided signals for entries on pullbacks. This can be traded manually, hybrid or fully auto. The mode that should be used depends on both a traders psychology and finances.

The issue is the EXITS. Finding these entries was not difficult. Avoiding short trades was also not difficult. Working out when to exit was harder. As a discretionary trader, I am VERY short term. I want to enter on the pullbacks and exit as soon as I'm far enough from the EMAs. As a FloBot trader, I need to increase the size of my average trade and so use dynamic exit criteria to keep me in the trend. This is where it starts to get more complicated.

FloBot Auto and Hybrid

This is the ES over the last few days. I programmed Flo using Bloodhound. This is the basic Inside Out trade buying the thrust after the pullbacks in the trend. Not too difficult as you can see.

The Flo logic can be made to be more sophisticated by adding more dynamic exits and even some additional trend filters. The creation of an algo is an iterative process for me. I start with the basics and then build additional logic as I sculp the algo to trade the way I think in my discretionary trading. Bloodhound is particularly useful for this approach as I can immediately see the impact of logic changes on the fly as I "sculpt" and make changes.

Bloodhound also has some nice buttons so I can hybrid change and add/move stops and targets.

Pictures!

I see trades in pictures. Yes, I've backtested my pictures. A trader can have an arsenal of a number of pictures and trade them as they appear. Or they can have just one or two and just trade those.

Today's DAX is one such picture. I remember seeing this so many, many times. We traded it live in original trainning video. Its an Outside in trade with the MP context. I just close my eyes and do it.

Outside In!

The times are still a-changin'. The effects of the governments' activities to "repair" the impact of the events of earlier this century are still causing market participants to act like Pavlov's dogs. While we are in a somewhat artificial environment, its still the same as before - markets react to what is happening.

One aspect of the current "fingerprint" is that markets are perhaps more nervous and watching for the possibility of change even more intently than before.

For me, Outside In ( mean reversion to some) trades can be very effective.

But as for all strategies, Outside In has a trade off. While the markets are in a trading range which is most of the time, Outside In is very profitable. However, when a trend begins, the trades have to be either filtered out or managed.

These are NinjaTrader charts with Bloodhound used to create the flobots.

So how can you filter and how can you manage?

Filtering is a matter of observation and testing. I can filter out trades that would be losers when the market trends using the slope of my EMAs. If the slope is too steep then no trade. Others use the Wells Wilder's ADX but I have found this to be too lagging for my timeframes.

For managing, I double down. My purpose is to average the basis price of my entry. I may have to do this more than once. Yes, I occasionally take a loss because I know that the markets can stay irrational longer than I can stay solvent but again, that "uncle" point is a matter of testing.

Whether I trade with a flobot or as a discretionary trader, the testing I do gives me the metrics I need to be able to maximise profitability. Without that testing, I'd be guessing.

Different Strokes!

There are algos and algos.

Another approach to algo trading is to have a quiver of different algos. Different algos for different market fingerprints.

Often, like yesterday, its possible to see the probabilities. Designing the algo for a specific fingerprint can increase the profitability considerably. I don't have to pick too many fingerprint types. Its just a matter of having 22 or 3 algos, depending on the market, that is suitable for days with different expected ranges. Its the range of the day that determines which algo will perform the best. If I'm wrong, then I'll have a less profitable or a losing day. I can change algos during the day as I see what has developed. In Europe, I can run a different algo in the morning and switch to a different algo for the U.S. day. Market Profile is a great tool for assessing the probabilities. Sometimes I have to wait and not turn my algo on until I see what is developing.

Algos, as I said in the previous post, are not a machine that has data in one end and money out the other but the skills required to be a successful algo trader are different and take less time to acquire than for discretionary trading.

Algos: Data in One End, Money Out the Other?

Kiki and I are working on the next set of flobots as we continue our processs of greater automated diversification.

As part of my due diligence, I had a look around the web for what is going on in the world of algos. Quite a shock. There are many websites offering algos for sale. Some offer some form of "training" to go with them but many are just "Algo For Sale" with no trading logic disclosed. This is quite a frightening prospect for me because I am at a loss as to how people can make money with a dark locked down black box.

The issue is that an algo is NOT "data in one end and money out the other". I wish it was.

There are several issue for me:

1. Psychologically, its very difficult to leave a closed black box turned on after a couple of losing trades
2. An algo is not suited to all markets all the time. 
3. The inputs of an algo will need to be tuned as markets change and evolve.

The issue #1 above is more than just a psychological one I guess. Without knowing why a trade is being entered, its difficult to see when issues #2 and #3 have come into play.

Markets change in both volatility and character. For example, our index markets have changed as the Fed and the ECB became more active in non standard operations due to the dangers to the world economies. There are other changes due to the lower volumes we have been experiencing in recent years. All this means is that if you had bought an algo that was designed for the markets as they were before the above, that algo is unlikely to be profitable now. Take that further, if I was to buy an algo designed for the current markets, is it likely to be profitable as the Fed stops its QE operations and th ECB invokes new and as yet undisclosed non standard operations?

My typical tweaks to algos have been to change bar size or bar type, and to change an indicator input to smooth out chop.

How do you know when an algo needs a tweak? You don't need to "know". Your testing has shown you how often you need to test your algo in the same way as you did when you created it. Walk Forward Analysis tells you how often you need to retune.

The thrust of this post is to say that one should learn how to fish rather than buying fish, fish which may already have gone off or have a very limited shelf life.

Lastly, the learning curve for creating an algo can be much, much shorter than learning how to trade consistently profitably. And you should know on the balance of probabilities that you will be successful BEFORE you risk your money.