064: Nick Radge – The Casino Edge, Mean Reversion Strategies, and How to Develop Robust Trading Systems

Chat with Traders is brought to you by Trade the Pool. Did you know that every decade the market reinvents itself? Online brokers opened the doors, mobile apps made trading seamless, and commission free trading erased barriers. Now a new era has begun. Meet, trade the pool, limited risk trading. And now you also have unlimited time to reach the profit target. From now on, your trading risk is capped. and your trading opportunities are limitless.

Trade the pool funds home-based stock traders with up to$200,000 in buying power. That means you can trade larger positions and scale your strategies without risking your own savings. It's time to trade with more capital, making it truly worth your time and effort. Ready to trade the pool? Click the link in the description and join the stock trading revolution today.

Are you ready to get serious about trading? Then join Tasty Trade, Investopedia's best platform for options trading in twenty twenty six. Options, futures, and more. Tasty Trade has everything you trade all in one platform. Get low commissions, including zero commissions on stocks. So you can keep more of what you earn. Trade smarter with advanced charting tools, a pre-built strategy selector, risk analysis tools, and more features. Visit Tastytrade.com slash.

Chat for more information. Tasty Trade Inc. is a registered broker dealer and member of FINRA, NFA, and SIPC. Podcast. Hey guys, what is up? Welcome back to another week of the Chatwith Traders podcast. For this episode I spoke with returning guest Nick Raj, who was originally on episode number four. But in case you missed that episode, Nick is a systematic trend follower and momentum trader. He's most active in Australian and US equity markets.

This time around we discussed mean reversion strategies and while they may appeal to certain traders, the importance of trade frequency when developing a system, which then leads us into the characteristics of a robust system. And probably one of the big takeaways for myself from this conversation was hearing about Nick's emphasis on really trying to break and stress test systems. rather than simply trying to find the quote unquote best system.

And like the last few guests, Nick has also offered to answer any trading questions you might have. So if there's something you want to know more about, just go to chatwithraders.com forward slash sixty four and leave your question in the comments area at the bottom of the page. Okay, that's all for now. Let's jump to the interview. I'm your host, Aaron Firefield, and here is my guest for the second time, Nick Raj.

Hey Nick, welcome back to the podcast. How's things? Yeah, all good. Thanks Aaron. Thanks for having me back again. No trouble whatsoever. So for those who don't know, you were originally on episode number four and on that episode we covered plenty of really great topics. But this time around, we're going to talk more of the specifics about taking a systematic approach to trading. So we're just going to jump straight into it. Guys, if you want to hear more about Nick's personal story.

Then do check out episode number four and you can find that at chatwithraders.com forward slash four. That'll take you directly to the episode. Alright Nick, so let's set the scene here. I'm gonna ask you, what type of trader are you? And could you give us just the quick overview of your trading approach? Sure. Well

I have an extensive background in technical analysis and usually technical analysis is associated with discretionary trading. But really there's two sides to that. You've got your discretionary side where you're looking at chart patterns and drawing trend lines and that kind of stuff on your chart. And then you've also got the quantitative side where

you're using mathematical formulas if you like. Um they're all based on technical analysis traits. So, you know, we use price, derivatives of price, we use volatility, uh volume, those kinds of things. So I am a one hundred percent systematic trader. Uh I trade trend following systems uh for the majority of my funds and also a selection of mean reversion systems as well, but purely one hundred percent systematic.

Okay, and you focus on both Australian and US equities, I believe. Do you trade any futures as well? Uh, the only futures I now trade, I traded futures for the first 15 years of my life, but really the only futures I use now are to hedge my US exposure when required.

Okay, and are those hedge positions, are they still a systematic trade or are they somewhat discretionary? Uh somewhat discretionary. It's rule based discretionary though. So I I have specific triggers that tell me to put a hedge on and take a hedge off. Um but it's not systemized per se. Okay. Now you said right at the beginning there that you take

for the most part, a trend following approach to trading. Could you just elaborate on what do you how do you define a a trend following approach and maybe Um how would you differentiate that from momentum trading? Yeah, it's a pretty good question and they are slightly different, although based on the same principles. Obviously the foundation principles

of both trend following and momentum is to cut the losses and let the winners ride. That's that's the founding principle on both of them. The difference between the two of them, however, is that trend following References symbols, whatever a symbol may be, so a stock or a futures contract or a foreign exchange pair in isolation. So we would be say looking at Microsoft on its own. Is it trending up or trending down on its own? And do I put a position on based on the trend of Microsoft itself?

Momentum is slightly different in that it references individual symbols against each other. So for example, let's use the S P five hundred constituent list. And we will say, right, out of these five hundred stocks, which are the twenty strongest and which are the twenty weakest? And you would rank them. And then you would buy the strong ones and if you were trading on the short side you would sell the uh sell the weak ones. Okay, and when you rank stocks in this particular way

What time frames are you looking at? Like are they when you say they're the s the top twenty strongest, the top twenty strongest over sort of what period of time? Well personally I use two hundred days. Uh really anything from well really anything from thirty days outwards pretty robust. Uh generally speaking, under thirty days you tend to get more of a mean reverting principle with uh with stocks.

Um three months is pretty common, six months is common, um and all the way out to one year all works very, very well.

Right, right, okay. Now, as a systematic trader, I guess the goal is to repeat the exact same types of trades over and over again and having strict rules for buying and selling. So why is that Why is that idea so important to you? Well it's very important to me because well at the end of the day there's no point having a systemat systematic approach if you're not going to uh follow the rules and place the trades. Let's get that straight.

Um and certain people struggle with that whole concept, you know, they want to think they're in charge. Now I need confidence in what I'm doing. I need to know what I'm doing has a positive is positive expectancy over the longer term. And if I know that then I can trade with complete confidence. I have literally I have no fear.

I have no reason to listen to anybody else's input. Uh noise just has no impact. Uh I've tested the system robustly, which I believe we're gonna get into shortly, but If I have a valid dated system that's proven, then I have complete confidence in every trade I place. Uh whether it's a winner or a loser, it doesn't really matter. So long as I understand that the strategy has a positive expectancy over the longer term, I completely remove um most of the emotion. Most of the emotion.

Right. I like that answer, Nick. I think you explained that really well and we definitely are gonna get into how to test for robustness and um all that good stuff very shortly.

One of the things you mentioned uh as we were speaking beforehand that may be beneficial to talk about is actually sort of digging in a little bit to the mean reversion systems. First of all, can you explain what is a mean reversion system and why would someone trade this type of strategy? Yeah. So in its simplest form, mean reversion is is buying weakness, if you like, and selling strength. Um Let's think Warren Buffett is a mean reversion trader. Essentially that's what he is doing.

He is buying value and waiting for those companies or that value to then come forward. So he is essentially a mean reverting trader, albeit on the long side. Um, why would someone trade this type of strategy? Well, there's a number of reasons. First of all, diversification. And I think if you have a look at some of the top trend followers around the place, you will see that they have slowly over the years

instigated other types of systems um to offer diversification. Trend following can be a little bit lumpy at times and mean reversion tends to be a little bit more consistent. So a mean reversion strategy can offer diversification with other strategies, which is one of the reasons why I do it. Second of all, Mean reversion offers high trade frequency.

And trade frequency is a very, very important part of profitability because you get to exploit your edge more and more and more. If you have a strategy that makes fifty trades a year. Well, there's only so much PL you can pull out of that strategy in the year. But if you have another strategy that does say 500 trades a year, well you can exploit your edge a lot more. And the classic example of this is a casino. Casinos have a very small edge. The goal of the casino is not actually gambling.

The goal of a casino is to get people into the casino in order for them to gamble, which is why they offer. Low priced meals, they offer free alcohol when you're actually in there. They offer all the big glamorous shows, the big shopping malls. The goal is to get people into the casino and then get them gambling. And that's why they're open twenty-four-seven.

Uh so people are open to gambling and therefore the casino can exploit their edge as often as possible. In fact, in Sydney uh is a very good example, in Sydney casino. They don't actually have croupiers now at the roulette table, although they certainly didn't the last time I was there, not that I go there all the time. A croupier slows the game down. The croupier has to collect the money, spin the wheel, move the chips around, do all that kind of stuff. And that slows the game.

So to speed the game up they actually remove the croupier. Instead, the player just puts a credit card straight into a machine. and it's all automated and it speeds the game up and exp it speeds their edge up as well, or they get to exploit their edge that more many times in any given hour of play. So

Mean reversion tends to be shorter term in nature. For example, my strategies, even though they're end-of-day strategies, they have an average hold time of three to four days, and they'll produce anywhere from 200 to 1,000 trades a year. Um a couple of other very good reasons why to trade mean reversions, they tend towards a higher win rate. and they can therefore be a little bit more comfortable for people to trade. You know, obviously

And I've explained this many times before. Uh we are brought up in a society where being right more often than not is rewarded. And it's very difficult for people to run a trend following system that has a win rate of forty percent or forty five percent. uh because it's uh you know, you you have a lot more losing trades and that can be quite difficult. So mean reverting systems tend towards

win rates in excess of sixty percent, sixty five percent somewhere in that area. And that in turn also allows a faster drawdown recovery. because you're exploiting your edge a lot more. I'm not saying the drawdowns is necessarily uh smaller, but you can tend to recover them a lot quicker.

and again with a trend following strategy, you can be in drawdown. Well, you know, some of the great traders, they can be in drawdown for a couple of years. And for the average man in the street, well, that's not really acceptable. So mean reversion can be a lot easier to trade. And let me also say something else that's just come into my mind now is again in in society at least today society is uh very reactionary. We want action all the time. Um we want instant feedback, instant gratification.

Sitting on a trend for six months, eight months is a pretty slow kind of laborious and boring thing, which is good, don't get me wrong. But for for a certain type of person who does require more gratification, more feedback, then a mean reversion system will provide that because there'll be a lot more trade, you'll be in and out, you've got to do a little bit more work, et cetera.

So that's something else that may appeal to a certain kind of person. Okay. That's a that's an awesome answer there, Nick. Couple questions just off your answer there. And this might be a bit of a a newbie question, but so essentially what you're doing is you're trading the price back towards the mean, okay? How do you know where the mean is, or how do you have some idea of where the mean price actually is?

Yep. I guess I'm a little bit different and maybe the term mean reversion is not that applicable but What I'm looking to do is find points where you have a stock that is severely oversold or overstretched, if you like. There's no real mean per se. It's stretched like a a rubber band, it's pulled to its maximum breaking point, and at that point the probabilities suggest it's gonna snap back the other way.

So that's what I would define the way I trade mean reverting. So there's no actual mean. It's not like, okay, Uh it's not like what Warren Buffett does. I mean his mean, for example, would be fair value of the company, correct? So he will be buying a company that is well under fair value and selling a company that he considers well over fair value. But all I'm kind of doing is is looking for price points that are stretched to a maximum.

um and looking for that to snap back by some degree and generate some kind of a profit. Okay, got it, got it. Yeah, that makes sense. Now

Are there are there certain market conditions where a mean reverting strategy may be more effective uh than other strategies? Oh absolutely. Every strategy, regardless of the kind of strategy, whether it be technical or even fundamental, will have periods of time where it works better than others. Um every strategy goes in and out of sync with the market. Okay? Warren Buffett's strategy

is in in sync and out of sync of the market at different points of time. Doesn't matter what you do, that's a fact of life. The unfortunate truth for a lot of people uh is they try and find a strategy that works well all the time in all market conditions and it just doesn't happen. So once you can overcome that and understand that

your strategy doesn't have to be perfect all of the time and you can make very good money regardless, then that's a big step for people moving in the right direction. It's a it's a big step for people to overcome that fact. So mean reverting systems, first of all, I only trade them on the long side. Okay. So uh in the US market.

I will actually stand aside when the market is trending down. So for the last few months, for example, I've actually been in cash just waiting for the market to turn around. In the Australian market, I do trade the mean reversion systems regardless of market direction up or down. So Ideally.

the I guess the ideal situation for a mean reversion system is a market moving sideways or slowly moving up. A market that moves fast on the upside doesn't allow me to actually get in and I will underperform. But a slow creep higher is probably the ideal situation or a sidewards market would be ideal. So for example, last year, twenty fifteen, My US mean reversion system uh produced a return, I think net return of about fourteen and a half or fifteen percent. And what was the S P? I think it was

pretty well flat or down a little bit last year. So um it can work in a sideways market, but I think a slow creep higher is the best. Right, right, okay. Now you made an interesting comment there in your answer about how you will trade both directions on the Australian markets but only long on the uh US markets. So is there any reason behind why you don't go short US equities? Oh sorry, I did make myself clear. Um

I only trade the Australian and US markets on the long side. I don't trade short and I'll explain why I don't in a second. Uh but what I do in the Australian market is I trade long when the market is trending both up and down, if that makes sense. Okay. Yeah. So in the last two or three months, for example, I haven't been trading the US market'cause it's been trending down, but I have been trading the Australian market Because it's been trending down.

Okay. So just to clarify why I don't trade on the short side, I used to and uh I stopped in two thousand and nine. Um there's a couple of reasons. First of all, I've never really come across a strategy that I'm a hundred percent com not confident with, but Happy with if you like. I can find strategies that uh make a profit trading on the short side, but

The risk-adjusted return is such that it really doesn't appeal to me. The second reason, and probably the most important reason, is back in 2008, the Australian regulators banned short selling. Now, what's the point of having a strategy to trade on the short side when you need it the most, you're not allowed to trade it? Um, so I just focus on the long side and another reason why we also trade majority on the long side is

Because it's easy for people to conceptualize. My clients may not be that sophisticated at trade on the short side. They may not be able to do it. Uh, they may not be able to facilitate it. So we just c try and keep it as simple as possible. And when there's no trading, we sit in cash.

Okay, okay, fair enough. Now, another one of the things you'd mentioned to me is those who attempt to trade these types of systems, um still talking about mean reversion systems of course, they often lack robustness, so In your mind, what defines a robust system? Yeah, uh this is very, very important. And um I can't stress this enough. You need to have a robust system.

What is a robust system? Well, the first question is why does your strategy make money? Okay. It's that's an im very important question. If you don't understand why your strategy makes money. You're going to find it very, very difficult to stay with your strategy when it goes a little bit uh pear shaped, which every strategy will at times.

So uh if we go back to the easy version of the momentum or trend following strategy, the foundation is cut your losses, let your winners run. Okay, you create a positive expectancy because you make a lot more money when you win than what you lose when uh when you have a losing trade. Mean reversion again, I guess the uh the analogy of the rubber band, for example. If prices stretch a certain distance

And then stretch a little further, they're going to tend to snap back. You can't really look at any price chart in any instrument. and see it continuously moving without some minor pullback at some stage. Um and and that's the basis of mean reversion. The market noise um tends to move it around a bit more.

So that's the first reason to understand why. If if I was to ask someone the a question, why does your strategy make money? And they said, Oh well When the three day moving average goes across the ten day moving average and the Bollinger band is here and the RSI is there and volume is is big and the moon is up, that's not a reason why a strategy is making money.

is some a strategy that works reasonably well most of the time. Remember, strategies will go in and out of sync with the market. That does not mean it's broken. It will go in and out of sync with the market. A robust strategy is one that will work across a large variety of stocks or instruments. So for example, I trade the exact same strategy.

In both the top 500 US stocks, so the SP 500, and also in the top 500 Australian stocks, I use the exact same rules for every single stock in both those markets. Every single parameter setting is exactly the same. Now that's a robust system. There's a thousand different stocks there, and we use historical constituent data, meaning we completely remove survivorship bias. And we can go back twenty years and we can see

that that strategy works perfectly well. There's no optimization on any individual stock. There's no optimization on any particular market. It's the same rules. So that tells me the strategy is very, very robust. To give you an idea of a non robust strategy, and this is the trap a lot of people fall into, and again they tend to fall into this trap because they want something to work exceptionally well all the time. So they will tend to optimize or curve fit.

So a good example, uh there's a gold ETF strategy that I've written about that's on the internet. And basically Uh it buys the gold ETF if it if it rallies more than one and a half percent on a day, it'll buy on the close. And the next morning it will exit the long and sell short and then get out of that position at the end of the day. Pretty simple kind of rules, and it works exceptionally well on this ETF. However, if you then take that rule, if that was a robust rule,

then we should be able to apply it to the S P 500 constituent list and it should give us some kind of positive outcome. And it doesn't. It's a terrible system. So that's not a robust pattern. It might be a pattern consistent with that particular stock or a particular stock, and that's fine. I'm not really disputing that.

But I would never trade it because it's not robust. If it's not robust, it will tend to fail in the future. So the more likely success over the longer term is to find a robust system. The other important piece of information with a robust or defining a robust system is it must operate over a very large sample of trades. So for example one of the main reversion systems that I trade uh across Australia and the US. Um

I can trade it on the Russell 2000 and it still shows the same profitability. It does about six hundred, seven hundred trades a year.

Um so going back, you know, fifteen, twenty years, you get a lot of trades in there and you still get the same kind of equity slope growth that that you have with a robust system. So as opposed to a strategy that's curve fitted and you might only get twenty trades in twenty years, that's just not robust at all because at the moment it's just luck that that pattern is profitable.

Okay, now in your answer there you brought up survivorship bias. Now um can we just expand on that for for listeners who may not be familiar with that term? Yeah. So Survivorship bias refers to stocks that have survived. So for example, Microsoft is in the S P five hundred these days.

and it was in the S P five hundred, say back in nineteen ninety eight. Enron Is not in the S P five hundred these days because it's now bankrupt, but it was back in the S P five hundred back in nineteen ninety eight. So Enron has not survived. Microsoft has survived. Now obviously you can think of the price patterns of Microsoft versus that of Enron will be completely different. One has gone up and one has gone down to the point it's bankrupt.

So what we wanna do when we test our strategies, we wanna do two things. We wanna test those stocks that are delisted to make sure our strategy has worked on those because those stocks are now gone. Um but we also want to ensure that we're trading the same universe today as what we would have traded back in nineteen ninety eight. So for example, using a historical constituent list

We can see what stocks were in the S P five hundred back in nineteen ninety-eight and make sure we're trading those stocks. So if I have a universe that I trade, which I do, the S P five hundred, I want to know that The SP 500 I'm testing on back in 1998 was the actual 500 stocks in that list back then, including all the ones that are delisted. So survivorship bias will tend to dramatically in certain circumstances overstate your simulated performance. And you want to get uh very accurate.

performance data as much as you can. And the only way to do that is remove survivorship bias. Okay. Okay. So Does that make sense? Yeah, yeah, no, that definitely makes sense. This may begin a little bit technical, but So as companies are introduced to let's say the S P five hundred, how do you actually build that into your data? Like you need to know the date that they came into um that index, is that right? That's correct.

And out, and back in again. Some stocks come in and out of an index a number of times. Um for example, uh Regis Resources is one such stock that um came into the top one hundred in the Australian market and then has gone out again as it went as it fell away. So if we're trading a specific universe, then that is important. If you're trading any stock for the heck of it, then it's not really important. Uh but we want to ensure that we have that information and it is available. Um

Uh we use a a data provider that makes that available and uh it's it's very beneficial, absolutely very beneficial. And there's only certain software packages that can cope with that as well. Um and it does become quite technical because there's a few other bits and pieces in the programming code that you actually have to put into place to ensure that um those stocks are removed for whatever reason at the at the right time.

Yeah, so I mean that was going to be my next question. Do you actually have to um put these companies in and out of the data as the as the dates line up, or is that something that your data provider actually does for you? That's what the data provider does for us. Okay, okay, sure. And just going just adding on to this

Do you double check that data? Is that something that's required or I guess it comes down to the quality of the the data provider? Yeah, look we use a very good quality data provider. We've used them for a long, long time. They're excellent. If if any of your listeners wanna drop me an email later on and uh and ask, I'm happy to point them in the right direction. It's not overly expensive. There are a f you know, there's numbers of data suppliers out there, but

Uh the people that we use are exceptional. We use them and have used them. uh constantly and You know, we constantly track our real time trading a against our simulated performance literally on a week to week basis. So we have no hesitation in knowing that, you know, the data is doing what it's supposed to do. Excellent. Okay. So it's fair to say that you do need to be a little bit selective on who you choose as a d data provider. Look, it's it's if you're gonna take this seriously.

then you really can't skimp on things like data. You know, it's it's an old saying that I have. Do you wanna make money or do you wanna save money? If you wanna make money, well you've gotta make a conscious decision. to choose quality data, quality systems, quality software. If you want to save money, okay, maybe you can get away with using free Yahoo data, but you have a bad data point in that or uh you have some incorrect data, non non adjusted data, whatever it may be, then

The cost in a trading having a trading error is extensive. It can be significantly more than the cost of buying or acquiring good quality data. Mm-hmm. Yeah, no those are really great points.

Now I want to pick up on something that you mentioned just a couple questions back, and that was the number of trades that a strategy produces. Um and you said that it's very important that, you know, it it has enough trades to have a large enough data sample. Do you have a personal preference about what may be too few or too many trades in a strategy?

Well, I certainly don't think there can be too many. Um the more data you have, the more likely the strategy is going to be robust. Okay, so The fact that the strategy does eight hundred trades a year is good. it might produce two thousand trades a year, which is good, but um the more is better, the less uh

How can I explain this? Um robustness is a function of how often or the occurrence of a particular setup or a pattern if you like. The more it occurs, the more robust it is. Think about The sun rising and setting. Okay, I mean effectively that is a pattern at the end of the day. We know it happens at the same kind of day, time of day, um and it's been happening for a long, long time, so we can be fairly certain that it's going to happen again tomorrow, right?

Um so the more of the occurrences we have in history then the greater the evidence that the pattern will continue to reoccur and most likely continue to occur the same way as it has in the past. Without the that frequency Or without that evidence, then we can start erring on the side of maybe, just maybe, it was a flute.

Okay, maybe there's just a fluke pat So one of the biggest uh lessons I ever learned, and it's a little bit of a a sad story, um I knew a guy, this is going back fifteen years now, and he had this trading tr trading strategy that had generated about two hundred and fifty trades in I think a ten or fifteen year period.

And the results looked a little too good to be true, which is always a bit of a red flag. Um I didn't know the ins and outs of the strategy itself, um, but it you know, it looked okay. Well, he went and started trading that, and in one night he lost he had a fifty thousand dollar account and he lost sixty thousand dollars in one night, and he has never traded since. And it turns out that that strategy was in fact about twenty different patterns.

in the S P five hundred futures, all of which had only ever happened a handful of times, and he put them all in together. And so basically what he had done is he had data mined the SP 500 futures and found all these patterns with 90% win rates, but they were basically random patterns. And uh as soon as one of those disproved itself, it blew his system up. Now obviously in his testing he has

he would have removed any patterns that blew themselves up in the past. Um and that's part of the curve fitting and the data mining that takes place. It's very difficult to have that same occurrence if you've got ten thousand trades of sample. You know, it's it's gonna be a lot more robust. So whenever I see a system that's firstly based on a single market, that's a red flag right there. A single market system tends to be not all the time but tends to be optimised.

And then if the performance metrics are through the roof, then that is a major red flag. And performance metrics would be Percentage winning trades. If that really starts to move above seventy five percent, I'd really start to question. If the system is only got twenty-five trades in a ten year period, well that's also a big red flag. Um and other metrics like the profit factor, for example. If that's in excess of three, then again, you've really got to ask a serious question

When you see a profit factor of sixteen, you know it's just an absolute curve fit data mining thing. And the only thing with those systems are they sell well to the public. That's what they're basically used for. Um, I understand there are people out there that trade single market systems and that's fine, but it's not something that I would do because I don't think they'd be robust enough to to actually trade that.

Unless of course they've got, you know, thousands of trades in their sample, then yes, but uh usually that's not the case. Sure, sure. Okay. No, that's that's an awesome answer again, Nick. Thank you very much. Now continuing on the path of robustness here, I'd like to ask you about Monte Carlo simulations. Um

How does this help with your analysis? So what is a Monte Carlo simulation? What role does it play in your analysis? Sure. So a Monte Carlo simulation is basically the question, what if? What if? The past was slightly different to what is showing. Okay. And a Monte Carlo allows us to go and get uh an idea of the variance of what may have happened in the past if it had slightly been different. So for example,

We do a lot of stress testing on our trading strategies and some of this includes Monte Carlo. So for example, one of the things we do is trade skipping. Let's say you've got a strategy that produces uh so for example, a classic problem with a mean reversion strategy is clustering of trades. You might get a big cluster of trades at certain points of time. And if you've got a big cluster of trades, then you can't take every trade because you don't have enough capital.

So with trade skipping Monte Carlo simulations, what we do is we say, what happens if we take these 10 trades instead of those 10 trades? So it will give us an output of uh a different number of scenarios. And the tighter that output is, the more robust the system is going to be. So

Trade skipping is not so much of an important issue with mean reversion strategies or higher frequency strategies. It is with trend following strategies because if you miss the one big trend, it can make or break your year.

With mean reversion where we're looking to take um small bites at the cherry all the time, it's it's not so much important, but it still has to be tested. So For example, let's say my mean reversion strategy does 500 trades a year, but there are 3,000 signals, I need to know if I'd taken those 500 trades instead of these 500 trades, what would the outcome be?

Uh and that's what we're looking at when we're doing trade skipping in the Monte Carlos. Um so That's basically what Monte Carlo is saying is what if the past is slightly different to what you've got there?

Mm-hmm. Yeah, yeah, absolutely. Are you ready to get serious about trading? Then join Tasty Trade, Investopedia's best platform for options trading in twenty twenty six. Stocks, options, futures, and more. Tasty Trade has everything you trade all in one platform. Get low commissions, including zero commission on stocks.

so you can keep more of what you earn. Tasty Trade is packed with advanced charting tools, backtesting, a pre-built strategy selector, risk analysis tools, and more features to help you trade smarter. See equities and derivatives with high trading volumes, dividends, upcoming earnings reports, and more with their pre built watches. Or create a custom watch list to keep an eye on the companies and sectors that matter to you. Manage your positions with speed and precision using Active Trader Mode.

one click trading and smart order tracking. Plus Tastytrad's Stellar Trade Desk team offers live support during trading hours if you need it. Visit Tasty Trade dot com slash chat for more info. KC Trade Inc. is a registered broker dealer and member of Finra, NFA and SIPC. Yeah. Have you ever watched a stock explode and thought, if only I had the capital? or sat on the sidelines because your account balance felt too small to matter. Good news

With Trade the Pool's limited risk platform, you don't need millions or even thousands to start trading the US stock market. Bypass the PDT and tap into over twelve thousand US listed equities. From penny stocks to big caps, ETFs, even the newest IPOs, and short anything you like, with zero locate or hard to borrow fees.

Start your evaluation, get funded with up to$200,000 in buying power so you can go big without risking your own savings. And now you can also have unlimited time to reach the profit target. It's a game changer. Not ready to trade yet? Trade the pool offers a free demo and educational resources. Practice on live data, master the platform, and build confidence risk-free before you even pay a cent. Click the link in the show notes to start trading with Trade the Pools Capital.

All right Nick, well let's move on a little bit and start to talk some more about um actually live trading some of these uh systems. So to what extent is your systematic trading approach automated? Um so To give an example, um our US main reversion strategy. Uh so what we w the where we where we start is it's it's fully programmed and we literally push a button and it will generate the buy and sell signals. But

We can put our account balance. Well, here's the process I use. I put my account balance in my software and I push the button and it will generate the orders for me. Do all the position sizing, generate the orders for me. Then what we do is upload that into an API. and the API is connected to my broker. So again, another push of another button and it will place those orders. It doesn't matter if there's one order or a hundred orders, it will place those orders instantly at the push of a button.

And then that API will manage the positions during the night. So I'm asleep, I've got exposure to the market, and the API will manage that exposure for me. So I say to the API, right. I only want to have 20 positions. I've just placed a hundred orders, but I only want to be filled on 20. So when I'm filled on 20, cancel any other pending orders. So I'm only exposed to those 20.

Now the API also has a um uh uh the functionality to exit any additional fills that might occur. So say for example I place a hundred orders and I only want twenty filled. But on the open the market gaps down two percent. In that situation. You might get, say, 30 fills, and you only want 20. So automatically and instantly, the API will cancel all remaining orders.

And then those ten additional fills that you've got that you don't want, it will automatically, and I'm talking within one second, turn around and exit those positions immediately. So it will always ensure that my exposure is managed through the night even though I'm sleeping. So that's about as automated as I am. I can actually manage the positions direct from my initial software, but I don't choose to do that. I manage it with the API.

Okay, okay, awesome. That's really cool to know. Now, in a live trading scenario, is there ever a time when fundamentals or macro events would cause you to step in and override your systems? I would say that if I was to override a system, it's not because of any macro or fundamental view, it's because of an emotional input.

Um have I done it? Yeah, look, of course I have. Even though I've been trading for thirty years, there's always that time where you think, Oh, this is not gonna be this is not gonna be good. But that rarely, rarely happens. Um, very rarely happens. Um But it certainly does happen to less experienced traders, probably uh quite regularly. It will tend to happen more to people who doubt their strategy. Um but if you have a complete hundred percent confidence in your strategy.

then you just gotta stand up to the plate and swing that bat and put your trades in. That's that's the bottom line. I mean I've had situations where, you know, I've seen China down six and Japan down six percent or something and US futures are down two percent in the night market and I've got a hundred buy orders to put in the market, there's certainly lingering doubt in my head, Oh gosh, this is gonna hurt.

Um, you know, nine hundred and ninety nine times out of a thousand I will go ahead and place those trades.'Cause usually that one time when I don't, it's gonna be a stonker of a night and I've missed it. So You're gonna be damned if you do and damned if you don't. So you may as well follow the system. That's what it's designed for. Okay. I like that answer. That's really good.

When you go live with a system, how long do you actually expect it to last for? Like continue to give you an edge, uh a trading edge? Like do you anticipate that it may only be good for a certain amount of time, whether that's, you know, a couple years or If it's truly robust, should it continue to work for, I don't know, maybe ten or more years? If you have a truly robust system It should continue to work extensively. Now, that's not to say that.

you can't learn more things about the market, you can't learn more things about your system, you can't learn more things about yourself. And therefore you can make adjustments to that system. Um I think every strategy is a work in progress. Uh we rarely make adjustments, but we certainly have made adjustments in the past to our systems because we've learnt new things or technology has changed which has enabled us to test our systems in different ways.

Um so for ex a very good example of that, I can now strip out resource stocks from industrial stocks as an example. and I can test those different segments of the market because they're very, very different kinds of stocks. Most resource stocks, um, you know, they they act very, very differently from uh

industrial stocks. We even see that in the fundamental world. There's a lot of fundamental investors, Warren Buffett being one, who will not touch resource stocks as an example. They will only touch industrial stocks. So With the technology and data that we now have, which we didn't have ten years ago, we can now test that and we may be able to draw conclusions that, oh, you know what?

I really shouldn't be trading resource stocks with my trend following strategy because, you know, they act very, very differently to industrial stocks. Now, to some extent, that is a little bit of curve fitting, if you like, but again, I stress that so long as we have a significant sample of trade. uh across all sorts of different stocks and we're using a robust system, then that's should be okay. Um the more you curve fit, the more you optimise, the more likely that the system is going to fail.

You tend to hear people are saying that all trading systems will break. That's generally because they've optimized it to start with. Um and uh you know, it's a work of art. It's an ongoing process, if you like, of maybe making a slight adjustment here or a slight adjustment there. But you've got to look at the evidence of what's out there. I mean you've got People like Salem Abraham, you've got to

Eka, you've got Dunn, you've got all these guys that have been trading trend based systems. Jerry Parker, I know you I think you've had him on your show, I'm not quite sure. You know, he's been trading the same style system, albeit slightly adjusted here and there, for 30 years. So there's no reason why a good, solid, robust system cannot uh last a whole lifetime. Yeah, Jerry Parker um hasn't been on the podcast just yet. Um he I know he's been on Better System Trader Podcast.

Um but I've actually got an interview locked in with Jerry uh later this week. So by the time this comes out it'll be it'll be a few weeks out. So I'm really looking forward to that one. It should be good. I think I think an important thing here is that Too many people are trying to find the best system, and that's the wrong way to approach it all. What you've got to do is try and break your system.

And the more stress you can place on your system when you're testing it, try and break it, you'll get a lot more out of it. So for example, um Uh testing your parameter stability. Let's let's use an example. Um in my book Unholy Grails we use uh an index filter which defines the broader market. Now let's say that index filter is a hundred days.

Well, what we want to test is what's the result if we change that by a certain amount? What if we change that to ninety or make it a hundred and ten or make it one hundred and fifty? How much would that change the result? So you can increase the signal variance. So changing all the inputs in your signal and seeing what impact that has. So you might say, right, what if I move my signals uh input parameters by fifteen percent.

Uh what if I move them by twenty percent? What kind of an impact is that gonna have on the bottom line? The other thing you can do to try and break your system is increase the data variance as an example. So let's say you've got a system that Uh so some of my systems, for example, uses the opening price to exit a position. What happens if I randomize that open price by 10%? and test back for twenty years on each single day.

the the opening price is adjusted up or down randomly by ten percent, what impact's that gonna have? And that's the whole idea of trying to break the system, trying to disprove it rather than prove it. And if you can't break it, if you can't disprove it,

chances are you're probably onto something that's reasonably good and reasonably robust and will continue to work reasonably well into the future. Yeah, that's an excellent point you bring up there, Nick. I think I think that's very, very important. So thanks so much for sharing that with us.

How long does it take you? How long does it take for you to realize that a system you're trading is not performing as expected from your backtesting and analysis? Yeah, it's a great question. Um one thing that we do constantly, well the first thing to understand

is that a mar uh that a system will move in and out of sync with the market. Okay, I've said this before. The fact that your system is out of sync with the market does not mean it's broken. Let's let's use a simple analogy for that, right? Let's say you've got a long-only trend following system. A long-only trend following system is not going to do particularly well in a sideways market.

or a downwards market. Okay? That's a fact of life. It is designed specifically to profit extensively when the market is trending up. And again, this comes back to why your system works. And it won't work if the market is going sideways or the market is going down, but that does not mean it's broken.

It's like buying a Porsche, driving it up the beach and then taking it back to the guy, the dealership and saying, Mate, this Porsche doesn't work on the beach. I mean you just wouldn't do that. It's not designed to go on the beach. And same with a long only trend following system. It is designed To make money. When the market is trending higher, which most stock markets tend to trend over the longer term to the upside.

But there are certainly periods of time where it won't. That does not mean the system is broken. It means you go into drawdown. So when your system is out of sync of the market, you go into drawdown. That's that's the payoff. Simple as that. So that's the first thing to understand. If you can't ask or answer the question why my system is not making money, then you have a problem.

So if I'm trading a trend following system and I'm in drawdown, but I can see that the market is moving sideways, then I have nothing to worry about. That's just a fact of life. But if the system is if the market is trending up and I'm using a trend following system and I'm losing money, well then you've got a serious question right there. And if you can't answer that question, well you've got a problem and you probably should stop trading it. So

That's a philosophical way to look at it. Um technically what we do is we're always constantly running simulations side by side with our real time trading. I literally do it weekly. I wanna see that I'm getting the same number of trades, the same kind of general return that I'm getting every single week from the simulation and from my real time trading. And I'll give you an example of where this has helped me in the past. Back in um

It was about 2011. I was trading a shorter term momentum style strategy. And my simulated results were or my real time results were diverging from my simulated results. And I did all the calculations. I went all the way back and had a look at about three years worth of trading. And I realized that slippage had started to increase so much so it was costing me eleven percent per annum. And that eleven percent basically meant the system was not viable anymore.

So and that was a liquidity issue rather than a system issue. Now I worked hard to try and find a solution and I couldn't. Um and basically one of the things we've seen in the Australian market and uh and you know over the last well since the GFC really is uh significant drop in liquidity. And that increased slippage so much so it invalidated my strategy.

So that's that's an example, a real time example of of where the strategy basically fell over was not tradable. Now I could have taken that and put it into the US market where there's a lot more liquidity. So we're always running the simulations along the real time. Uh if there is a divergence, you've got to try and figure out why. If you can if you can figure out why, then then you are in a better decision. If it was a one off event

Um, such as the nineteen eighty seven stock market crash, well, you know, there's probably nothing intrinsically wrong with the strategy. It's just one of those one off events that will impact everybody. Um what you don't want to see is a slow divergence away from the simulated results over time. So you will have set benchmarks. uh using your historical performance metrics and when you start to deviate away from those then you know you've probably got a problem.

Excellent, excellent. Okay. Brilliant answer there, Nick. Thank you very much. Now, I know listeners are gonna want to know what software are you using for all this? So can you share some insight on that? Sure. We use Amy Broker. Um I have a programmer on staff. And uh we together will develop systems and and whatever. But Amy Broker, it's look, it's inexpensive. It can pretty well do absolutely anything you want.

It can automate processes, it can do explorations, it can do almost anything. As I said to you before, uh we are able to do position sizing inside Amy Broker. It is able to format our orders so they can be sent straight to the broker platform. Uh we had a corporate client as an example who wanted their own trend following strategy built, which we did.

and they were managing money for clients. Now one of their requests was that they had their dealer running the system on a day to day basis, but their compliance department Wanted to do an audit of the orders the system was generating and the orders that the dealer was placing for his clients. So Amy Broker. uh enabled us to do a um CSV file dump straight into the compliance department's um drop box. And that way they had every time the dealer pushed the order button

They were sent the orders and then they could go back and see what orders the dealer had actually placed for the client. So there's quite a lot of things you can do with it. Um I'm sure we haven't touched half of what it can do. It's a very powerful piece of software.

Um and it can pretty well do anything you want. Okay. Now you mentioned you've got a programmer on staff there. Um what's what language is he working in? Is it the proprietary language of Amy Broker? Yeah, that's correct. Which is kind of Similar to C. Okay, okay. So is it for someone who hasn't um touched that sort of thing before, i is it difficult to learn like What would the learning curve of that be like? Um well we run uh it's a good question. Um

It certainly can be a little bit daunting, okay? But all good things are a little bit daunting to start with. And if you want to progress, if you if you make the choice that you want to become a good systems trader. then you will automatically make the choice to learn how to do it. If if you don't think you want to learn how to do it, then you haven't committed yourself to making that choice of becoming a good systems trader.

So, as an example on how long it takes, uh we run a high-end mentoring course, which is a six-month one-to-one trading system mentor course. And the first part of that course is learning everything about AMI Broker, learning not only how to use it, but also how to program it. Now we've got students in that course who have never even owned Ammy Broker, never programmed computers before.

And within two months they're pretty well able to do it. So it certainly can be done. For some people who are a little bit more IT savvy, a little bit techie minded, well, it won't take that long. Uh but we've got guys there who've come straight from the mines, they've never played with computers before per se, and they're up and running and programming that in two months. Okay. Now with Amy Broker we sort of spoke about data providers um earlier.

Does Amy Broker have their own data or do you use a a third party broker source? Uh I don't use a broker source, I use a data provider. Yeah, that's what I meant to say. Well a lot of people do use a broker source. I mean you can you can source data out of your broker. Um but we don't do that. We use a data provider. So yeah, it plugs straight into Ambi Broker and we use um premium data. Um they're based here in Australia but they are clients uh worldwide and they have a lot of

hedge funds and a lot of institutional clients use their data as well around the world. So that's premium data.net. Very, very good product. As I said, we've used them for a long time and highly recommend that. Excellent. Okay. And with the API management, do you use any other software for that side of things? Uh we had our own API built. Uh it was built in Europe.

Um and yeah, so that's proprietary to us. We uh you know, we do sell turnkey trading strategies. We have one mean reversion system which Um I'll give you a link to shortly and people can uh can look at that system. But You can use an API for that as an example, and we can provide our proprietary API as part of that purchase to trade that if anyone wanted to. So we had it built um we can have it

built to do whatever we want to do. There's some pretty smart people out there, uh, but this one was built in Europe. Okay, excellent. All right, Nick, well last question. Now I've had this come through on email um a couple of times in the last few weeks.

I think you might be a good person to ask this question too. What do you do for your retirement accounts? And is this separate from your, you know, active day to day trading? Uh yeah, good question. The answer's yes. So Our retirement account we f use um a trend following strategy and that accounts for about eighty five percent of the value of my retirement account.

And that's just in the Australian market. So pretty straightforward, long only, trend following, trades about fifty times a year. Then in our family trust, uh we operate a couple of different accounts which operate about four different other strategies.

both bean reversion and momentum. Um and the reason why we do that in the family trust is uh generally um You know, because it's more income oriented, it's more active, uh one of the mean reversion systems I trade does about eight hundred trades a year. I don't think the Australian Tax Office would be overly happy to see that happen in my retirement account. Um so yes, uh we have two different kinds of setups across multiple different accounts.

Okay. Excellent. And just to be clear that that trend following approach is something that you developed yourself? Yeah, that's correct. So the trend following approach that I use, um We offer it uh within our service. Uh it's called the growth portfolio. And if anyone has read my book, Unholy Grails. There is a strategy in there called the Bollinger Band Breakout. Now the growth portfolio is loosely, loosely based on that exact same strategy. We use the same principles as in the book.

And people can actually follow the signals within our service. So you can trade right alongside me. We disclose our positions to our clients. You can see exactly what I've got. Um and you can see exactly the kinds of trades I'm taking. So, you know, we're trying to be as transparent as possible with that.

Right, okay. All right, Nick, well let's bring this to a close. So where can listeners go to find out more about you? Well, saying we've been talking about mean reversion today, um, I do have an e book on mean reversion which is been downloaded uh four or five thousand times. So Uh if people are interested in taking a look at that ebook, it has a fully disclosed strategy at the end of that ebook, and that strategy is very similar to the one I trade.

You can go to thechartist.com.au forward slash chat. C-H-A-T. Thechartist.com.au forward slash chat. You can download that ebook and you can take a look at that trading system. Um and as I said, very, very similar to the one that I personally trade both here in Australia and the US. Great. And you're also on Twitter? Also on Twitter at the Chartist. Um and that's a good place to contact me. Um so yeah. Come along.

Good stuff. Well last question. Nick, would you be open to answering questions that any listeners may have in the comments um on the website? Definitely. By all means. Any questions you have, um By all means happy to answer them. A lot of the time with this kind of stuff there there does require a little bit more clarification. And so more than happy to answer any questions anyone has. Good stuff. Well, I really appreciate that, Nick. And guys listening, if you want to ask Nick any questions.

Go to chatwithraders.com forward slash sixty-four, scroll to the bottom of the page and leave a comment, uh leave a question in the comments area. Alright, Nick, well awesome to have you back on. Uh it's it's been a lot of fun. Thank you very much for doing this, and let's talk again soon. All right, that's great. Thanks, Aaron. You've reached the end of this episode of Chat with Traders, but rest assured there are more episodes. And zero high. Chat with traders.