038: Kevin Davey – The Development Process of an Algo Trading Strategy, From Objectives to Live Trading

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chat for more information. Tasty Trade Inc. is a registered broker dealer and member of Finra, NFA and SIPC. The biggest secret of the best traders in the world is that they're just like everyone else. However, they've worked hard to learn the markets and discover what works and what doesn't. But how can you hear about these journeys and get in on the strategy? with traders. Here's your host, Aaron Fei.

What's up guys? What's going on? Hope you're all doing really well. This week on the podcast, I have algorithmic trader Kevin Davey, who like many guests in the past, he comes from a background in engineering. And I don't know what it is, but there's something about these engineers. They just seem to make really great traders.

After getting off to a bumpy start, roughly twenty five years ago, Kevin has come a very long way since then. Between 2005 and 2007, Kevin competed in the World Cup of Futures Trading Championships. where he finished in first place once and second place twice, each time with returns in excess of a hundred percent, so he did very, very well.

Kevin is also the author of Building Winning Algorithmic Trading Systems, a book which has been well received by the trading community and has plenty of five star ratings and reviews on Amazon. During this interview, we cover the great focus Kevin places on trading multiple strategies in multiple markets to achieve a smoother equity curve.

So we kind of hit on a little bit of diversification. It's very interesting. And he also walks us through his development process for taking an algorithmic trading strategy from objectives and initial idea through to total automation. Plus we cover plenty more as well. And even if you're not familiar with this side of trading or this particular style of trading, you shouldn't have too much trouble keeping up because Kevin does an excellent job of explaining everything.

Now guys, just real quick before we get into it, I'm going to ask once again, if you haven't already done so, could you please leave a very brief review on the podcast and iTunes? I can't express how helpful this is. It's just a really easy way that you can support the podcast.

So if you can do this, just go to chattwithtraders.com forward slash iTunes. Again, huge help and I really appreciate it. All right, I'm your host Aaron Feifeld. This is the Chatwith Traders podcast and here is this week's guest, Kevin Davey. Hey Kevin, great to be speaking with you. How's it going? Great. Well thanks for having me, Erin.

Absolutely no trouble. It's my pleasure. I mean, thank you for coming on the podcast. Um, you know, we've been speaking for a little bit beforehand and I mean we're gonna dig into some really interesting topics here. Uh algorithmic trading will of course be the big one. And I know you've got plenty to share on this, so it's gonna be good. But before we get into trading specifics. Let's cover your background and the journey you've been on to getting to where you are now.

So Kevin, tell us about your introduction to trading and if you could, take it back one step further and give us some background about what you were doing before this time also. Okay. Well um My introduction to trading was really uh I I got an ad that came through the mail. that said, uh, hey, you can make a ton of money by trading commodities and, you know, at the time I was a couple of years out of college and I didn't even really know what all that was, you know, I had just started to

in a career I was in engineering, uh actually aerospace engineering. So I was I was working on uh fighter aircraft and um you know, I was just starting to get settled in a career and started to have some money to invest and I saw this about commodities, how you could make all this money. And I think the uh the example that was given was actually sugar.

And it showed, hey, if you bought sugar all the way up here, you would have made, you know, hundreds of thousands of dollars kind of thing. And so at that point I was like, wow, this is pretty cool. And uh so that that kinda started it and started me down the road of you know, doing research and uh of course, you know, opening an account'cause everybody's always excited to open an account as soon as they can. And within I don't know, a few weeks I lost

ten or fifteen percent, twenty percent, something like that. So then I did the reverse of this of the strategy I was trying to trade and I lost a bunch more and all of a sudden my account's down like sixty percent. uh in a very short time. And so you know, but by that time I was kinda Like, wow, well if I can lose money this quickly, I could probably make it this quickly. That was my naive way of thinking. And

Uh that really just had me progress down the road of trying a bunch of different things over the years. Uh, you know, most things didn't work. And then eventually I kinda

started to do more mechanical trading system. I always liked the the rule aspect actually from like day one. But there were times where I did discretionary trading and that type of thing. And uh eventually I just kinda settled on hey, these mechanical algorithmic

trading strategies that you just follow the rules and just execute them and if you've evaluated them right and tested them right, they should produce, you know, some kind of profit over time. And that's where my journeys led and that's what I do today is Just create

strategies and trade a lot of the ones that I have and I always have new strategies waiting to go in case something happens to some of my existing ones and I just continue on that journey. Excellent. Yeah that's really good. So let Let's not brush over those first couple years and I'm keen to hear more about what was going through your head when you you lost sort of around about sixty percent of your initial capital and you decided to You know, take a step aside and reassess things. Like

I mean most people I presume would probably do that once they've run out of capital to actually trade with, th they'd step back and then rethink things. But you sort of notice that This isn't going right, I need to do something here. So what was your what was your next step from there? Like what were you learning? What were you studying and and how did you go about this? Okay. Um well really what happened after you know, I almost blew out that first account, I kinda took a step back and uh

I just started reading as much as I possibly could. So at the time, this is about twenty five years ago, there were the internet didn't exist, so there weren't all these trading websites and forums where you could get information. So a lot of it was just and uh magazines, you know, some of the trading magazines and I was just kinda devouring all that as much as I could possibly

get information wise I did. And it didn't really matter what style of trading was discussed. It was just talking about trading and that's what really interested me is you know, I I was just kinda on a

I guess a fact finding mission. I just wanted to see what other people did and and how other people succeeded and maybe that would help. And you know, I d I looked at things l obviously I uh Elliot wave and Gann theory and all these different things and you know, I kinda said, Well, hey, that doesn't really fit me or this kinda does and Eventually I got to the point where I started testing some of this.

stuff and at the time I don't even know if uh tools like TradeStation uh or anything like that was available to do the testing. So I was doing a lot of the testing uh by hand. I had done some computer programming before. So I got a hold of some data and created my own uh trading systems and a way to evaluate them. And I did that for quite a while.

And, you know, that whole thing led down the road of over optimizing, curve fitting, too many rules, too many parameters and, you know, you'd you'd get these ridiculously good results and it'd be like, Oh, well I didn't even include commissions on that or slippage, you know, didn't even really understand at the time what slippage was'cause they hadn't traded that much. But uh Eventually over time I started to realize that hey most of these systems look so good but they're just

uh bogus, you know, they're not gonna work. I kinda knew that just from my experience getting creamed right at the beginning. So Uh I was just able to to kinda keep on and develop more systems but not actually trade'em right away and just kinda watch'em and eventually I got to the point where I felt comfortable enough to actually start trading some of these things. Now the problem was I was working full time, so I I couldn't

place orders all day long. I had to do like end of day systems. And at the time there really wasn't software to at least for a retail trader to even automate things I that would never even entered my mind. So I was just doing these simple end of day systems. And um you know, on and off I had some success and along the way I did

bunch of other things. You know, I looked at things like uh scale trading where you buy on a scale down and you keep adding to a losing position and I get killed with that.

So I was doing other things along the same time but eventually I just kinda settled on this mechanical type trading and uh make a long story short, eventually I actually had a little bit of success and then Once that happened, then I started to get some confidence in what I was doing and that kind of led me just to where I ended up. Today. Okay. No, that's excellent. So if we had to boil it down to just one or two

of the greatest challenges you experienced earlier on, what would you say these were? I mean, I think it's really good to highlight these because a lot of listeners can really resonate and um perhaps if they're having similar challenges learn about how you overcame these challenges. So I mean you kinda mentioned curve fitting and that, but was there anything else that that you really struggled with early on?

Um, that was probably the biggest thing. Uh I guess I would generalize it a little bit more, learning how to properly test and evaluate a strategy. That was the biggest challenge because uh

there wasn't that a whole ton of information out there about that back when I started doing it. And um, you know, even the stuff I read probably didn't sink in enough'cause you know, until you actually do some of it then y uh you become more experienced with it and then you realize, oh, this this guy in this book was he was making sense and I didn't understand it at the time but uh You know, even when I started using tools like uh Trade Station, which is what I primarily use now.

Unfortunately the way they Set up the software, it makes it really easy to make a lot of bad decisions. You know what the easiest thing to do is you open up a chart, then you insert a couple of strategies and then you optimize it and then you get the best results and then you you go and trade it. And a lot of people still do that.

And uh you know, and I certainly looked at that either in the the stuff I was custom doing or when I actually started doing with Trade Station. So and that's totally the wrong uh approach to take. It it leads to so many bad things that uh I can't even describe them all. But that's probably the biggest challenge. uh knowing how to test and evaluate the right way.

Okay, sure. And you also mentioned um in your previous answer that you were still holding down a job for quite some time um while you were trading. So at what point did you feel comfortable and and confident to to take the leap and and make that transition to trading full time. Um well in I think I did this in two thousand and seven was actually when I uh

Or two thousand eight, I'm sorry, when I actually made the leap. So I've been trading full time for over seven years now. And what happened was in two thousand five, six and seven I finished in the uh World Cup of Futures Trading Championship. I finished in first place. one of the years in second place, the other two years. And so it was three years in a row. I finished in first or second and each of those years I had over a hundred percent return. So That gave me quite a bit of confidence that

Hey, I kinda know what I'm doing. Maybe I should do this full time. And the way it worked out career wise with what I was doing, uh I had an opportunity to leave uh the company I was working with and get uh basically like a lump sum of money uh at that time. And so I thought, well, hey, that'll help keep me going as I start to transition to this full time trading. You know,'cause the last thing you want to do when you're a full time trader

is be sucking off your account to pay for living expenses. And um eventually I had to do some of that, but At least this gave me a little bit of room. But the biggest thing uh you know, with just going full time, uh I probably looking back on it I think I started Not too soon, but with way too little capital.

And uh if I had probably ten times the amount of capital to start with, I would have been a lot better off back then. But, you know, that's one of those things you think you have enough and then you start doing it and you're you realize Ooh, you know, when you start getting into drawdowns and you have to withdraw money too for your for living expenses, uh it becomes psychologically it it really kind of hits you. Yeah, absolutely. And I mean that's that's very impressive that you were able to

um take out the the winning spot on on several competitions there while you're still holding down a part time job. I think that's very cool. And I can definitely see how that would be a huge confidence boost. Um but even still, I mean, did you notice um were there any notable differences in your trading habit?

When you did transition to full time trading, like you didn't have the the regular income any longer that you could rely on and and fall back on, did your trading habits change in any way, shape or form? Um, yeah, especially in the beginning, uh because now I had all day to trade basically and that was part of the problem because I started to do some of that where uh I just started to do some discretionary trading which I really couldn't do.

You know, having a full time job, obviously I couldn't really d trade during the day. Now all of a sudden I had the time to do it, so I said, Hey, why don't why don't I try doing some of this discretionary trading? during the day and um you know that didn't work out too well. Otherwise I'd be still doing it. But uh That was a big thing. And the other thing was just becoming disciplined enough to say, Okay, well now I I have all this extra time but I've gotta be working more on systems and

new strategies and that type of thing and that was something I really wasn't probably wasn't prepared enough for. But uh after a few months I kinda realized that, wow, I've really got a

Step up what I'm doing. You know, I I think I was kinda in the mode in the initially that Yeah, I'm full time trading, but it doesn't mean it has to take up all my time and after a few months I realized well I'm not gonna survive doing that so I gotta be working a lot more and actually now I probably I bet compared to what I used to do career wise with the part time trading I'm sure I'm doing spending more time uh now doing the full time trading.

Right, okay. So let's let's now talk about what has been working really well for you. So Kevin, if you could Tell us how you would describe your style of trading as far as markets, time frames and approach, etcetera. Okay. Well, um What I do now is unlooking any markets, really any time frames, uh, and any kind of strategy. I don't I try not to

pigeonhole myself and say, well I'm only gonna look at the ES or I'm only gonna look at crude oil or something like that. Basically any any liquid market is is fair game. And then time frame wise Uh I'll look to develop strategies that are intraday. I don't have as many of those because those are just harder I think to at least for me to develop. But I have a lot of swing systems that last. days to weeks. I even have some systems that last up to months. So uh

Different markets, different time frames, and then completely different strategies. You know, I I will It's uh if I find something that works in a particular market, I might u try to apply it to different markets and see how it works. But for the most part, uh I don't necessarily expect that to happen or demand that it happens. You know, some people say, well, yeah, I need a strategy that works in ten different markets or I'm not going to trade it.

I think that uh I understand why they're saying that, but my experience is you don't really need that. You can find I've have some strategies that only work in one particular market, but it they work pretty well. And so I will trade'em. So that's kind of where I've gone. So I just develop systems for any market, any time frame and any kind of strategy. And if it as long as it meets certain goals And it was also developed using a the the process the development process I normally use. Then um

good to trade it. And so right now, for example, I think I'm just over eighty different strategies that I'm trading. either automated, some are manual, um, but all different kinds of markets and that type of thing. So for example when the uh ES crashed uh you know and then it went back up a coup a week and a half ago. I was uh short quite a few E S put options and my options'cause I do option selling as part of how I trade and those options accounts got really nailed where they lost

probably just over fifteen percent of their account value in one month. But I was also trading all these other strategies.

that, you know, aren't option strategies, there's plain future strategies and those made up for it. So overall I was able to make money for the the month of August, but uh that really speaks to I think some of the diversification I was doing and and that's kind of just probably where my trading will be going from here is just developing more systems and just trying to diversify more.

Okay, and I know you're obviously very big on diversifying it and having multiple systems, trading multiple markets, um, simultaneously. Um, what's what's the like you've mentioned some of the advantages there but like I think there's additional advantages as well. Like does it also um help smooth out your overall equity curve and is there any other benefit that that make this such a important piece of your trading success.

Um, yeah, absolutely. I mean the the equity curve smoothing has always been one of my goals and uh one way I measure that is just my monthly returns, percentage returns, measuring the standard deviation. of those returns and it's gone down uh by a factor of I think three or four in the last four or five years as I've gone from probably trading five strategies or so to getting up to where I'm at now. So

That's one of the huge benefits of it. The other thing, uh there's a couple of other things that are kind of interesting that people probably don't think about initially, but let's just say you're trading twenty strategies, for example. If w if you allocate capital to each one, each one is five percent of your account roughly. And if one of those strategies breaks It's not gonna kill your account. Yeah, it's gonna hurt, but

You know, you've only allocated so much to it that it's not going to wipe you out. Where people trading one strategy, if that strategy does bad, it just wipes them out. You know, the flip side to that is trading one strategy if it does really well, well then you'll have higher returns. But Um as a full time trader, I'm not really aiming for those super huge returns anymore. I'm aiming for something that's a little more consistent.

and that uh you know will tend what I hope is last longer. So I'm willing to give up some of that upside so I don't have that downside. And the other big thing with trading a lot of strategies that probably not a lot of people realize is it becomes really hard to uh what I would say cheat on a system. And by cheating I mean, you know, you'll see a signal, even if it's automated, and you'll you'll

say, oh, it shouldn't be doing that. You know, there's a Fed announcement in a few minutes, so I'm gonna turn that strategy off and exit that position. That's what a lot of people do with their automated systems or uh or even mechanical systems there, manual. They'll override'em and turn'em on. That's not good because now you're Going against what your historical testing said. You know, it said to do something, now you're doing something else.

Are you gonna make it better or worse? I don't know. Probably you'll make it worse, but the point is it's different. But yet when you have twenty systems, it becomes really hard to cheat on those systems'cause you're You're gonna be overwhelmed. Oh system A, am I following it or not? Uh I don't know. Well system B, I know I'm doing the exact opposite of what I should be.

And you're trying to keep track of all this, it's much easier just to let the systems run and then deal with the consequences of that, uh, which means you know you put things in place to quit those systems that Uh bad. You don't overrule them with what you're doing. So that's one of the uh a big benefit of trading a lot of strategies. Okay, sure. Yeah. Now you hit on a lot of really great points there. Thank you for showing those, Kevin.

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Um now maybe I should have asked this a little bit earlier, but I mean what actually attracts you to algorithmic or systematic trading? And in in your opinion, like what are the major benefits of this actual approach? Well I think the the biggest thing is y i you can evaluate it before you start trading it. And that to me is huge when you start thinking about your confidence in something. You know, uh I know a lot of people will look at a chart

that'll be of two weeks and they'll see a a certain pattern and they'll see five instances of it and you know four of them worked and they'll say, Hey, that's good, I'm gonna go. Well I to me that's just uh Awful. It's an awful habit to do. So I want to evaluate something and I want A hundred trades, two hundred trades, five hundred trades, you know, I have uh some back tests going back that have like uh you know, two or three thousand trades.

That's the the biggest benefit, I think, because I know over history that it's worked. Now, does it mean it's gonna work going forward? Well, absolutely not. But all things being equal, uh, would you rather trade a system that you knew worked in the past and you were hoping it would keep working in the future, or would you want to trade one that

either you didn't know how it did in the past or you knew it lost money in the past. Um, you know, in that case I think the answer's pretty clear. You want to go with what's worse. And take your chances with that. And that's probably the biggest thing I get out of mechanical trading. I can look at history and said, Well, yeah, this has made money in the past and therefore I'm willing to take a chance with it working in the future.

Sure, sure. Okay. Now those are those are some great benefits. Um, but as we're constantly reminded There's there's no such thing as the quote unquote holy grail when it comes to trading. So what are perhaps some of the cons or some of the negatives that come with being an algorithmic trader?

Um, I would say probably the biggest con that uh people tend to fall trap they fall into is they try to make a holy grail uh And the way they do that is they will go through and they'll they'll run a test of, you know, five years, ten years and They'll get some results and the results will look pretty good. You know, the equity curve kind of goes up. And you know, it looks decent, but they'll say, Oh, I can do better.

And they'll go back and they'll add some rules and filters and then they'll they'll look at it, oh, it looks better and then they'll go back and they'll they'll look at the results and say, Oh, you know, if I didn't trade on a Tuesday, my results would be A whole bunch better. Of course the equity curve looks better. And they keep doing that. And they fool themselves into thinking because they made this better looking back test

you know, this historical test that it's gonna continue on into the future. And that's usually not even true and the ex exact opposite is usually true. It it's kinda strange, but the more you try to make something better, the more you try to perfect it, the worse it actually becomes. And um that's probably the biggest trap that I see people falling into and the biggest conda to uh or disadvantage of algorithmic trading is

is people think because they can test, therefore they should do everything possible to make the test great. And um that gets a a lot of people into uh some serious trouble. Okay, but in saying that is there still

To a certain extent, it's a good idea to try and optimize your strategy. Like, is there a thin line between optimizing and then over optimizing and curved fitting? Oh yeah, definitely. I mean I still optimize. Um I just I use What's called walk forward analysis which data out of sample and so I'll optimize over a certain period, but then I'll apply those parameters to brand new data and see how it's done.

And I I'll do that approach and that works a lot better than just traditional optimizing. But even that where people get messed up is they'll get results that are walk forward results, but then they'll go back and change their system five, ten times, and then all of a sudden what they think is out of sample data isn't really out of sample.

they've'cause they've run it so many times. So yeah, there's definitely a a fine line and uh you know, I always tell the story that I've I have some systems where I have two or three uh lines of code almost. Uh I have a line for entry and a line for exit and maybe I'll optimize. There'll be something to optimize on each line, so maybe two variables to optimize.

And if that looks decent, I will stop there. And some people think that's crazy. You know, they'll say, Well well you gotta add more filters and and more, you know, conditions and You know, that doesn't seem to work. I mean I know people who've spent five, six years uh currently working on one particular system and they have thousands of lines of code.

and they're no better off. Uh I mean they've just op over optimized to the nth degree. And you know, m I guess my rule of thumb always with this is If you start to feel a little uneasy that you might be doing too much Optimizing, you've probably already gone past that point where you have. And it's definitely time to stop at that point.

Yeah, that's that's really interesting. Um, just a couple of the the words or the the terms you used in there. I just want to make sure that listeners uh uh understand. Um so there's a couple you mentioned there was out of sample and then walk forward. Would you mind just explaining what those two terms refer to? Okay. Well if you're doing any kind of back testing. Uh normally what most people do is

They will test up until today and optimize and then take those parameters and start trading them. That would be optimization with no, it's all in sample because Uh by in sample I mean they've evaluated they've made their decision based on optimized data. So That's the first one. But then there's some people who said, Well, I'm gonna test uh for five years but then leave the last two years

of history, uh I'm not gonna optimize that. And I'm just gonna apply those parameters to those two years and see how it did. That's an odd of sample. So you optimized on one set of data, but then you applied those parameters to another set of data.

That's an auto sample test. And then the walk forward is actually just a process that kind of takes that to a further degree where you optimize and put it to a set of parameters for a limited amount of time, then you optimize, you move the optimization, you walk the optimization window. And you apply it to another set of time. And basically what you do then at the end is put together all these pieces of

out of sample periods together to get a full out-of-sample curve. And if you do it right, it really is truly out-of-sample data that your system is being evaluated on. And that uh tends to work a lot better than a fully optimized system. Now none of those are as good as Live testing. You know, obviously the the best test always is gonna be live testing. And um you know, you can certainly do that. And a lot of people part of my process actually

I actually do some of that where even though I've done the walk forward testing, I don't go and trade something immediately. You know, if I develop something tonight, I'm not gonna trade it tomorrow. I'm gonna let it sit for a while and see what happens in real time. And that seems to also help eliminate some of those systems that, you know, uh we've all had'em that as soon as you start trading'em

uh they go and start look you know, they go into this huge drawdown uh and you're like, why does this always happen to me? kind of thing. But Excellent. Thanks for explaining those, Kevin. That's really good.

I'd like to talk probably a little bit more about the actual development of a system or an algorithm. Um so if you could maybe just give us an overview of your process for developing an algorithm. Like what are the If you could just briefly hit on each one of the stages involved.

going from maybe initial idea through to actually going live with an algorithm. Well first I mean the first thing even before you come up with the idea you really have to know what your goals and objectives are and and most people just bypass that completely but it helps set expectations because if you're looking for a a strategy that returns say

300% a year with a 10% drawdown, uh, you're never gonna find it. But so you gotta have realistic goals to start. Then, you know, you ideas. Um, I talked a lot about uh what I call strategy factory. Which is kinda describes my whole process. where trading ideas come in the door, come in your factory, you work on'em, and then what either comes out the end is either a full blown strategy that you can actually trade or it's junk, uh which is what most

ideas turn out to be. And you know, it just goes in the scrap heap. But it all starts with ideas. Ideas are your raw material. And if you run out of ideas, Well you have nothing to test, right? And and part of the ha running a factory is having lots of ideas to go through the factory to test. And so I make sure I always have I probably have at any one point in time fifty or sixty ideas of things I want to test. And I honestly I just don't have enough time to test them all. I wish I did, but um

I never lack for testing. I never say to myself, Boy, I wish I had something to test. I can't think of anything. Um So you need that reservoir of ideas. So then usually what I do is um I just run a quick test on it. Uh you don't need to go through the whole process of running these detailed tests. A lot of times just a limited

Period testing, a simple test will tell you if what your idea holds any water, you know, if it has any merit to it at all. Uh and that's a quick way to kind of go through a lot of ideas. So I do that. Then I go into a detailed testing, uh which includes the walk forward testing and and some optimization.

And assuming that passes, then I run some random simulations, some Monte Carlo simulations, because, you know, just because a a certain uh walk forward test equity curve looked a certain way doesn't mean that's the way it it will happen in the future. You know, you can take those trades and just mix'em up and you get so tumps something totally different. So it helps gives you some more probabilities of what's occurring.

So once if that passes in at each of those steps there's certain criteria that I use to say, well, okay, this can go on to the next step or no, it's it's junk, I'm giving up, moving on to my next idea. Uh once it goes through the the random simulations Then I actually just put it in what I call incubation, but it's just it just sits on a shelf basically for a period of time. And I go and check it periodically to make sure to see what it's doing.

But then at the end of it I'll say, Yes, I think I'm gonna trade it, or no, I'm not, or I need to evaluate it longer. And I just evaluate it once a month. And I do that right now probably with uh hundred uh somewhere between a hundred and hundred and fifty strategies that I look at at least once a month. And you know, at that point sometimes I'll bring new ones in and that's probably the l the last step is you say, Well, I've got this portfolio of strategies I'm trading

And I have some extra capital. So either I'm gonna bring in more strategies or maybe I'm gonna increase the size of the ones I already have. You know, it kind of becomes a trade off. Should I increase size? of ones I have or should I just bring in new ones? Um, you know, and there's some criteria that I go through to determine what to do there. And that's pretty much it. You know, and then I'll go live with it and uh But then even once you go live.

The important thing you have to monitor those strategies, make sure they're actually performing. And you also have some cr some criteria in place to Tell you when you're gonna stop. You know, most people don't think of that's one thing most people don't think about. They don't think about when they're gonna stop trading a system.

Uh you know, especially you know, think about it. You just created a system and you're all excited by all the money you're you're gonna make. The last thing you're thinking about is, well, what if this strategy doesn't work? What do I do? Um most people don't think about it and um but that's exactly the time you should be thinking about it. And you should say Hey, if the strategy does this, you know, if it has this kind of drawdown or whatever, I'm gonna quit trading it.

And that kind of completes the process and it's kind of the loop back to monitor your performance. And then it just becomes Uh almost as simple as it sounds, it's just doing that process again and again and again, uh, you know, hundreds of times to create new strategies.

Okay, so have you ever had a situation where Um like similar to what you just described, you you've gone through all this testing and this process, you've gone live with a strategy, um, only to find out that it's not performing anywhere near as well as it was. um during the testing phase and it's actually giving you quite poor results. Have you ever had an experience like that and and how did you treat it, if that's the case? Oh yeah, definitely. I mean um

Whether it's I do something wrong in the testing and I don't even realize it or the markets changed. You know, for example, uh in my book I have a couple Euro systems. that were doing pretty well up until uh mid 2014 when volatility started to reach record lows in the Euro and then those systems stopped. working. Uh they just and they really haven't recovered at all, even though the volatility's picked back up. But the the structure of the market I think has actually changed a little bit.

And but so yeah, I definitely have some that don't quite work out. And the big thing I do is I I just say, well Here's my criteria for when I'm gonna cut that strategy out of the portfolio. And you know,'cause otherwise if you don't do that, you could eventually get to the point where the strategy just

takes over and ruins your account. Uh and you don't want that. You want to cut those. It's just like trading. You want to cut the losers and let the winners run. And whether that's a particular trade or If you look at a bigger picture strategies, you wanna do the same thing. You just wanna cut your losing strategies before they get too bad. Okay, that's an excellent point. Now I I feel as though many people may perceive algorithmic trading as an area that is probably quite daunting.

Do you feel like this is actually an accurate assumption or do you feel like um do you feel like it's probably not that much more difficult to learn than it is to become a good discretionary trader? Um I think it it's there's two different skill sets'cause w you know, if you're you wanna become a discretionary trader, I think it's really important to uh understand the the market and you know uh

you know, understand price action and that type of thing. Where if you're being an algorithmic trader, that might not be as big of a concern. So and what what I mean by that is uh a lot of times I'll see an idea. And I don't know if it's good or bad based on my market knowledge. So what I'll do is I'll just test it. And that will tell me if it's good or bad. So in that respect, you don't necessarily have to be, you know, a deep market theorist.

to be good at algorithmic trading. All you have what you really have to be good at is your approach to evaluating ideas. Uh and and you have to do that properly and if you don't do that properly then, you know, it's that old uh computer phrase, garbage in, garbage out. You know, if you if you don't do things right, you're just gonna get garbage and you you think you're gonna have these great results and you're not.

But normally what I tell people as long as they can program even simple strategies. in whatever trading platform and you know, test if they can test simple strategies, they probably know enough to at least take that next step and learn how to test properly. Um, you know.

As long as you can do that, you're good enough. Uh you know, some people think they need to spend years of coding with their particular software language to to be able to trade algorithmically and actually I think that is more of a a detriment um because you don't need to do a lot of fancy things, you know, uh for example I have systems that the entry is literally if the close is greater than the close of

ten bars ago buy the next bar. I mean that that's can be a simple entry like that and that can work. And you know, you can put an exit or two with it. And those kind of things can actually work pretty good. And um my philosophy always is, well the the simplest things usually tend to work the best going forward because you're what you're doing, you're not putting a lot of demands on the market. for the future. You know, you're just saying, Hey, if this little thing is true

buy. Um, you know, you're not saying, well, hey, if the momentum's up and the RSI is this and the ADX is this and your uh MACD is doing something. You know, y a lot of people think the more conditions they impose, the better off they are. And it's actually the opposite. The less you impose, the better off you are.

Okay. That's that's really good. That's an excellent point. And for someone who might be might be interested in moving towards algorithmic trading but doesn't know how to go about it. What would you suggest to them might be a good first few steps? Thank you. Well, um obviously uh probably reading my book once once uh they get a little familiar at least with the futures markets, uh that's a good one. There's other other good

system development books out there. Bob Pardo wrote a probably the classic book. a while back and that's a good book. And there's uh books by uh Thomasini one it's called uh I can't remember the title offhand. I think it's called uh Trading Systems, uh Jackal and Tomasini. That's that's a good book. So there there's some good books that will give you some of the basics of of testing.

And then the other part of it is to actually just fire up that software, whether it's Ninja or Trade Station Multicharts, Omni Broker, whatever it is. and learn how to program simple systems in that language and, you know, do that, do some simple optimization, be able to look at a performance report and see what's going on. That

the way you start uh getting a feel for this algorithmic trading. And what once you get to that point, then it's okay, well now I'm gonna learn to test the w the correct way. And then it's just a matter of programming lots of ideas and trying them out.

Sure, excellent. Okay. Well I'll make sure to put links to um all those books you just mentioned there in the show notes. So if anyone wants to check those out, just go to uh chatwithtraders.com forward slash thirty eight and you'll find links uh on that page.

Um now this is a question that actually came in through the Chatwith Traders site. Um and I thought it was a really good one and you're probably the the right person to ask. Um Can you survive as a trader over the next 30 years without learning much about code? Well that's a good question. Um I personally would not want to, but uh I think if you are willing to

spend the time sitting in front of your computer day after day and, you know, I'm assuming you're gonna be a discretionary trader. You might be able to to do to do okay. Um I don't really know because My my world I know a lot more algorithmic type, mechanical type traders and, you know, a lot of them have had success. I don't know a lot of discretionary traders to begin with. Uh so

you know, knowing that they are having success, I don't really know for sure. So yeah, that's uh I guess if you if you decide hey I'm gonna go to discretionary trading um Yeah, that's possible, but obviously if you want to do any kind of algorithmic, mechanical type trading and any kind of testing evaluation, I think you really have to learn to do some coding.

Hm. I think that's a good answer and I mean it is quite a quite a tricky question really. Um but I mean, Kevin, this has been this has been really good. So let's just do one last question, then we'll probably wind things down. So I like to ask this to pretty much everyone who comes on the show, so if you had to sum it up for us, what's the main reason why you believe most traders never succeed? Oh boy. Um

There's probably a couple of reasons, so I don't know if I'll be able to give you one, but psychology and uh having an edge. And and the ironic thing is those two go together. So Uh some people think it's all about psychology. Gotta have the right psychology. I gotta journal my feelings, blah, blah, blah. Well, that's great, but if you don't have an edge

all the psychology in the world isn't gonna make you profitable. Okay. Um, but even if you do have an edge, if you don't have the right psychology You know, so for example, if you're a mechanical trader and your psychology is such that you have to overrule the system, you're not gonna be successful doing that. So

Uh you need both of those pieces and if you only have one and not the other, you're still gonna fail. Uh and a lot of people don't get that. They think it's either all about psychology or it's all about finding an edge. And really the truth is you gotta have both. And that's probably the the biggest key out there.

One hundred percent. That's a brilliant answer, Kevin, and an awesome way to take us out. So before you go, can you share with listeners where they can go to find out more about you and connect with you? Sure. Uh my website w dot kj Trading Systems dot com and uh you can go there and read a bunch of stuff and you can also uh Most of the pages have contact forms at the bottom where you can contact me. Or you can just send me an email at uh it's K Davey K-D-A-V-E-Y at KJ Trading Systems dot com.

uh just send me an email on the you know, I'm just here trading Pretty much full time, so uh I see all the emails, no one else answers any of my emails or anything like that. So they can reach me that way too. Really good. And do you want to share the title of your book? Sure, it's called uh bid building winning algorithmic trading system.

It's kind of a a big title and then there's a nice subtitle. It's A Traders Journey from Data Mining to Monte Carlo Simulation to Live Trading. And in that book I talk more about the the process we kinda talked about today, Aaron. And in the beginning of the book I kinda lay out uh my

uh trading history. So it's more of a narrative in the beginning. And uh I what a lot of people have told me is they kind of identify with a lot of the the struggles I went through. But I think it's kind of important to see the struggles before you see

Yeah, the ultimate success. Um because a lot of people think trading's just all hey, I'm gonna start trading, it's gonna be easy and it's really anything but it's I always tell people it's the hardest uh hardest way to make easy money that's out there. I like that. Um yeah, I mean that's a book I'm really keen to check out for myself. So anyone who wants links of course everything will be at chatwithraders.com forward slash thirty-eight um including a link to Kevin's book.

Um and last of all, you're on Twitter as well, aren't you? Yeah, it's uh my Twitter is K J Trading and um Yeah, people can reach me that way too. Awesome. All right, very good. So go follow Kevin on Twitter and Kevin, take care and let's speak very soon. All right, well hey, thanks for having me here today, Aaron. My pleasure. Thank you very much. All right. You've come to the end of this episode of Chat with Traders, but don't worry, more great episodes are on the way.

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