Tables Turned, Exclusive Interview with Aaron Fifield | Chat with Traders
Aaron Fifield, founder of Chat with Traders, has hosted over one hundred podcasts with traders ranging from billionaires to retail grinders. Aaron has a background in trading via technical analysis and is now trading as a developing quant. The tables were turned as we had an opportunity to interview him and find out what it means to have an edge in trading, learn some of the top mistakes made by new algo traders, and tips on how to properly backtest.
Grace: Why Chat with Traders? How did you come about choosing that as your pursuit?
Aaron: I didn’t know anyone in the field and I didn’t know anyone who was interested in trading and investing. I’ve always understood the concept of having mentors and speaking to people who have already done what you are trying to achieve; that’s very powerful. And here I was trying to trade which is very difficult in and of itself yet I was trying to do it pretty much all on my own. I didn’t really want to go down the path of trying to search through the Internet and sign up and pay for all of these different courses so I started Chat with Traders. I had always learned a lot from and enjoyed listening to podcasts myself. So I started a platform to speak with people I would otherwise not have the opportunity to speak with and then of course share those conversations with others who may be in the same situation as I am.
Grace: So listening to your podcasts, you focus often on how to empower traders to get an edge. What is your definition of a trading edge?
Aaron: I think every trader is going to think about their edge a little bit differently. I know hand traders and discretionary traders consider their edge to be in their processes whereas traders who take more of a quantitative angle to their trading and are more data driven probably consider their edge to be something which has statistical significance. One of the definitions which I really like comes from Blair Hull who is a trader who I certainly have a great amount of respect for. Blair Hull says something along the lines of “if you do the same trade hundreds of times you’ll have more money than when you started.” That sounds really simple but I think it’s also very powerful. Speaking with Blair, he is someone who doesn’t do anything unless he has an advantage. This definition clicks with me because of the sorts of trading I am interested in and I am doing which is very systematic trading. I think that’s a sound definition of an edge.
Grace: How do you believe you’ve become a better trader after interacting with a lot of thought leaders in the industry and really becoming a thought leader yourself?
Aaron: So it’s a tough question to answer. There’s no doubt I still have a long way to go and I think I’ll probably be saying that for as long as I’m a trader as well. Great traders never stop learning; they are constantly evolving and adapting and changing to suit market conditions and whatnot. I think it’s a lot about developing a deeper understanding of what it takes to become a great trader. The way I am trading now, I am using programming, I am using data, I am using automation and that sort of thing. The podcasts introduced me to new concepts and new approaches and made me aware of how many different ways there are to make money in the market. There is no one blueprint that’s going to put you on the right path.
Great traders never stop learning; they are constantly evolving and adapting and changing…
Grace: In your podcasts with different traders what was the most common mistake new traders make in the algo field?
Aaron: In algorithmic trading, especially if you are new to the concept of algorithmic trading, one of the things that can be very misleading is the whole process of back testing. I have seen in the FinTech space that there are a few different things coming out which allow a retail trader to backtest strategy ideas which can be good but also be very dangerous because there’s many ways that you can backtest and get results which are misleading. There’s just so many factors which can cause a backtest to be pretty much useless. It can range from anything from curve fitting to not splitting your data between in-sample and out-of-sample or having a training in a testing set. We could also get into commissions and slippage. There’s a lot of things which can cause you to get a brilliant result in your backtest but if you try to implement that in real time it’s going to fail. I would say that’s probably the one thing worth mentioning and the biggest trap they may fall into.
In algorithmic trading, one of the things that can be very misleading is the whole process of back testing.
Kurt: What about algorithmic trading really appealed to you?
Aaron: So I guess it goes back to what I mentioned about Blair Hull about how to build an edge. My biggest frustration when I was trying to get better as a trader was that I had one or two strategies which I was trading and sometimes l’d make money sometimes I’d lose money. I had no idea if I was to trade those strategies a hundred times what was the expectancy that I was actually going to make money. I didn’t really understand the concept of having an edge. If I could take a piece of paper and write down the exact rules of the strategy I discovered that those rules could be turned into a code. You could then run the historical data through that code to see if in the past it would have made money. That’s why I started to learn to code so I could actually test before I committed real money to it and start trading it in real time. Otherwise I just feel like I was putting real money behind these strategies which I had no idea whether they were any good or not. I can tell from the amount of backtesting and different strategies that I’ve tried that you don’t get a good strategy very often. I just needed to learn how to program actually test and that would give me a lot more confidence in what I was trading. Just an example, the other day I had a long position on the SPY that I already entered into a day or two before that big selloff last week and I held threw that selloff. And I got out yesterday for a small profit. Now if I hadn’t backtested that strategy and had confidence in that strategy and knowing the stats and knowing how it’s performed in the past I probably would have sold that position right at the low and lost a few hundred dollars. I would have taken quite a loss on that position instead I knew how my strategy reacts during these times and the characteristics of it because I’ve done the research because I’ve backtested it. I had the confidence to hold through that and ended up selling out for a profit. I know I could have easily taken a loss on that still but I let my strategy do it’s thing and I didn’t step in and I override it.
Kurt: Have you found a way to account for commissions and slippage in your back testing?
Aaron: Commissions are quite easy to factor for. I know the commission rate which my broker charges so I can easily put that into my code. Slippage is certainly a lot more difficult and it also depends on what markets you’re trading too. There’s a couple ways that you can go about factoring slippage. For example, you can double your commission. Platforms like Quantopian have an actual slippage model which I think is fairly good and they’ve actually tested it and compared it to live trading. They certainly have research about how to factor in slippage on their website and good discussion in their forums. That’s one of the things that is important to consider when you are doing back testing as well as understanding what markets you’re trading too. You need to have an understanding of market behavior along with an understanding of how to program and use data. It’s not enough to just have those skills; you need to understand some of the nuances of the markets that you’re trying as well.
Grace: You hear a lot of advice from different industry experts and leaders. Is there something that comes up most often over the number of podcasts that you have had?
Aaron: Try to understand what it means to have an edge and trade with an edge. Too many newer traders don’t understand that concept and because of that end up losing money and they don’t understand why. They keep throwing good money after bad and they’re never going to make money because they simply don’t have an edge with a particular strategy or the method they are trading. I also think that some people try and rush in to trading. Especially as a hand trader there is very little barriers to entry. You can get an account funded this week and be trading next week. Take your time and actually try to learn. The podcast is great for this because you can hear from the experiences of so many different traders and how they got to where they are now. One of the things that was quite interesting which I found from doing this is that so many traders took years and years before they saw any success as a trader. So I think some people get into this and think they should be making money in the first three or six months. I think you shouldn’t even be trading in your first six months of starting. Have a willingness to play a long game; that’s what every trader I’ve spoken to who is successful has.
Have a willingness to play a long game; that’s what every trader I’ve spoken to who is successful has.
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