Es mini futures algorithmic trading system. The systems that trade the ES mini futures contract, DAX futures, with both long and short positions. Some systems trade using exchange traded funds with a focus on trading the indexes, sectors and the volatility index. We also have stock trading systems for those how prefer active stock trading. Trades vary in length.

Es mini futures algorithmic trading system

LV Daytrade System fully automated ES E-Mini SP 500 trading system.

Es mini futures algorithmic trading system. Even though the stock market shows no sign of the trend reversing down, traders are jumpy and quick to lock in gains with any negative new. Sounds like a “Wall Of Worry” to me. Taking a look at the ES mini futures chart below which is a ten minute intraday chart. It is clear the recent pop in price is testing.

Es mini futures algorithmic trading system


Trading futures involves substantial risk of loss and is not appropriate for all investors. Past performance is not necessarily indicative of futures results. Unlike the results shown in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under-or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity.

Simulated or hypothetical trading programs in general are also subject to the fact that they are designed with the benefit of hindsight.

No representation is being made that any account will or is likely to achieve profits or losses similar to these being shown. Okay, so first, I would like to go over our disclaimer. We are not registered with the CFTC as a commodity trading advisor. We create algorithms and we license them for use on a personal computer through Trade Station, and they can also be auto-executed through NFA-registered brokers.

Keep in mind that trading futures and options involves substantial risk of loss. These algorithms are really not for everyone. They should be traded with risk-capital only in our opinion, and lastly, the data that we show, unless otherwise noted, is based on hypothetical back-tested models, and it does have certain limitations, per the disclaimer here.

Feel free to read this. You can pause the video and read it more carefully. Just keep all that in mind as we go through the data in this video. It does have limitations. At times, we do mention the live returns on the website or in the video, and when we do, that is from live data, and we note it as such. This is the average gain that this strategy saw during up months, and you can see the momentum algorithm does the best in up-moving markets. We categorize that as sideways.

The momentum algorithm is the one that does good when the market is going higher. This is the TradeStation platform that I used for the development, and each chart shows one of the strategies. This is the treasury note algorithm. This is the Iron Condors. This is the gap short.

This is our breakout day trade algorithm, and this is our short day trade algorithm, the breakdown. If we look at the momentum algorithm, again, this is the one that is designed to do well when the market is going higher. Now, most of you are aware that futures trade, for the most part, 24 hours a day. This does have this session enabled to represent more like the equity market sees.

The reason why we do that is because in the evening session, usually the volume is pretty low until Europe opens. A lot of algorithm traders like myself and my company will not trade during those overnight periods. Eastern, which is when the futures market closes for about an hour and then it reopens.

But again, this is the momentum algorithm only. Keep in mind, this algorithm or this package trades seven algorithms. The reasons why we trade seven is again, so that each algorithm targets a different market condition so that our goal is to have one to two algorithms doing well for each market condition. But let me look at the performance report from TradeStation. We can begin talking about this. So, this one has the smallest profit factor of any of the algorithms that we use.

This is the average trade. Now, remember that when we look at this data, it is subject to limitations. Back-testing has significant limitations. This algorithm is a swing trade. This is an example of a losing trade.

We would have gotten in on the 20th of February and then got stopped out a few days later. We can also look at a few of the more recent trades. This is just actually from this last week where the market was going higher. This algorithm did exactly what it was designed to do. It got in, it got out, and in this week, it had four winning trades. But again, with TradeStation, we have all the performance reports for the back-testing.

We have equity curves. This is an equity curve of how this algorithm did in the back-testing. What really matters is the ratio to gain to loss. Is it positive, and does that look good? In this case, it does. This algorithm is also designed to do well in up markets. Again, our design methodology is not to create one algorithm that does good for every market condition, but to have one to two that do good for each market condition.

As long as these other algorithms do better in down conditions, which they do, then we have a positive expectation for down-moving markets. So, this right here is the chart of the breakout day trade, and it trades on nine-minute candles. On the seventh of November this year, it actually got in right here and got out at the close. This is an example of where it got stopped out. It got in right up here and then got stopped out somewhere in here.

And then a few days ago, we had a decent breakout trade where it got in at the open and got out at the close. It has trades, has a decent profit factor , 1. Average profit per trade, Half the trades are profitable, half are winners, but what you notice is that the average winning trade is quite a bit bigger than the average losing, which is why this algorithm is still profitable, why we have it in our portfolio.

We do expect this one to pop out of that. But the, you know, so you have the trade list, the performance summary, just all kinds of data that TradeStation provides. But this algorithm, again, is designed to do well in upmarket conditions, and to not lose too much in downmarket conditions and then to be, you know, break even during sideways-moving markets. And by the way, this algorithm is our best algorithm that we have, in my opinion. It has a very high win rate. It has trades, which is decent, given how long it holds, and the average win or the average trade profit is Those are just periods where it got stopped out.

Maybe it had a rally, got stopped out again. Overall, this algorithm is, in my opinion, the best one we have back-tested. This is actually back in August also of last year when the market sold off, this algorithm rallied.

Sometimes they both rally together. Sometimes they both sell off. It also does good in sideways market conditions as well. But it also does have a limit target that it will get out of its limit, and then it has a stop as well. It has a pretty high profit factor , 1. The only negative about this algo is it only has trades in the back-testing. We usually like to see at least It has a pretty good average trade net profit.

You can see the winners are quite a bit bigger than the losers. It also requires very little margin to trade. Now, of course, you know, none of these are perfect. They will have losers. That was another winner there. Trying to look for a loser. Maybe I passed it. Nope, that was a winner.

Anyway, it does have losing trades as well. Zoom in and show you that one. So, here was a trade where you had a gap up. All right, so, if I go back to… To this graphic, that was the gap short that we were looking at, the morning gap day trade. The other algorithm I want to look at is this breakdown short day trade. And so, you know, this… Kind of zoom in and try to find a trade. The market was going higher. This, I guess this was the last trade we had, which was on the 11th of October, and it went short when the market opened, about 18 minutes after the market opened, and then got out at the close.

We went short, the market rallied, and we got out at the close.


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