Automated Trading Strategy #70
7 Strategies Created By Generative AI Using A Genetic Algorithm
Important: There is no guarantee that these strategies will have the same performance in the future. I use backtests to compare historical strategy performance. Backtests are based on historical data, not real-time data so the results shared are hypothetical, not real. There are no guarantees that this performance will continue in the future. Trading futures is extremely risky. If you trade futures live, be prepared to lose your entire account. I recommend using these strategies in simulated trading until you/we find the holy grail of trade strategy.
As a quick reminder, our goal is to find the holy grail of automated trade strategy.
We haven’t found the holy grail yet, but we get closer with every strategy. Click here for the most recent performance chart and links to all strategies.
Contact: AutomatedTradingStrategies@protonmail.com.
Random person at event: “What do you do?”
Me: “I trade futures and publish a newsletter on automated strategies.”
Random person at event: “Oh really. That’s cool. So like AI stuff?
Me: “No, not AI.”
Random person at event: “But it’s automated?”
Me: “The A in AI stands for Artificial not Automated.”
Random person at event: “Right, but you’re getting help from your computer?”
Me: “Yes.”
Random person at event: “Right, so you’re using AI?!”
We were both perplexed.
This was an actual conversation I had with someone at a fundraiser. Granted we were drinking wine on a rooftop, but it made me realize that AI is a very loose and overused term. It also shed some light on the fact that I’m just a trader with a finance background. I really don’t know anything about all of this AI stuff. So I decided to conduct a deep dive into AI. If I’m struggling with its definition and application in trading, no doubt others on the hunt are as well. I hope this post provides us all with some clarity around the subject moving forward.
Strategy 70 is actually seven strategies created by Ninjatrader’s generative AI tool. In addition to giving you the downloads for these strategies, I’m also going to do what I can to help explain what applications AI might have for trading now and in the very near future.
First, let me preface by saying that my background is in finance and it’s been a long time since I’ve seen the inside of a classroom. This is just my attempt at trying to get my head around what applications AI might have for us on the hunt.
Let’s start with a few quick definitions of the term AI…
For me, artificial intelligence is the intelligence of machines or software as opposed to biological intelligence. Machine learning (ML) is a subset of AI and takes this definition a step further. Not only does it classify and organize the data, but it then generates something new out of that data. In some cases that something new is a prediction about the future. Those predictions are then used to make trading signals. For example, JP Morgan’s AI solution for FX is called DNA (Deep Neural Network for Algo Execution) and is used, among other things, to advise institutional clients on best execution, order routing and liquidity opportunities.
Going back to the definition of AI, if you do a quick search, you’ll get a definition more like this:
Artificial intelligence leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind.
-IBM
Perhaps the most comprehensive definition comes from the federal government. According to the 10 U.S. Code § 2358, artificial intelligence is defined as follows:
With these definitions in mind, I suppose any machine (including your Roomba) can be AI.
What does this mean for trading? From a trading perspective, I am inclined to agree with SEC Commissioner Mark T. Uyeda’s statement on the use of predictive data analytics by broker-dealers and investment advisers. It was largely in response to the federal government’s announcement two days ago regarding AI compliance. Yes, it seems that the nature of generative AI means the creation of a very large black box, and I get that folks are scared by that, but Pandora’s AI Box was opened a long time ago and any regulation made today concerning AI is probably going to be out of date tomorrow.
Going back to the conversation I had at the fundraiser, I suppose we’re already using AI. I suppose you could even say that this hunt is about leveraging AI to help find the holy grail of automated trading systems. So, where do we go from here?
Before answering that, I want to take a step back to understand how we got here.
The Race: From Zero Latency To Prediction Analytics
My newsletter (ATS) is on the hunt for alpha via automated trading strategies, but in the late 90’s everyone was on the hunt for alpha via Electronic Communication Networks (ECNs), which spawned the use of algorithms and the development of high frequency trading (HFT). HFT algos rely heavily on arbitrage strategies, which require speed. In other words, the race was largely about speed. Who would be the first to spot a mispriced order? This created a latency race from milliseconds to nanoseconds. When the race hit time zero, it had nowhere to go but into the future: enter predictive analytics. Suddenly, the race is less about latency and more about predictions using generative AI.
Click here to read the full article on ATS.
