Listen to Adrian on The Trading With Rayner Podcast!

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Introduction to the Trading with Rayner Podcast Interview with Adrian Reid

In this fascinating interview, Adrian Reid, a seasoned systematic trader and founder of Enlightened Stock Trading, dives deep into his journey from a beginner learning the ropes of investing to mastering systematic trading. Adrian shares how his analytical mindset as an engineer played a pivotal role in shaping his trading philosophy, enabling him to design systems that work across various markets, including stocks and cryptocurrencies. This conversation is packed with insights, practical advice, and actionable steps for anyone looking to enhance their trading approach, especially those frustrated by the unpredictability of discretionary trading.

Rayner Teo and Adrian Reid explore key aspects of trading, from Adrian’s early challenges to his eventual breakthrough with systematic strategies, and how he now helps traders achieve consistent results. Whether you’re a novice or an experienced trader, this episode is a must-listen for gaining clarity and direction in your trading journey.

Key Trading Lessons from the Interview

• The Evolution of a Trader:

  • Adrian started with fundamental and technical analysis but struggled to find consistent success until he embraced systematic trading.
  • Systematic trading provided clarity, consistency, and a data-driven approach, eliminating the emotional rollercoaster common with discretionary methods.

• Building Effective Trading Systems:

  • Adrian emphasizes the importance of backtesting and verifying a trading system to ensure it has a statistical edge.
  • He shares insights on creating systems tailored to different market conditions, allowing for profitability in bull, bear, and sideways markets.

• Lessons from Struggles and Breakthroughs:

  • Consistent risk management and avoiding overcomplicated strategies are key takeaways from Adrian’s journey.
  • He discusses how simplifying trading systems can lead to better outcomes, particularly for those without a coding background.

• Designing Systems for New Markets:

  • Adrian reveals his methodical process for approaching unfamiliar market states, including analyzing data, forming hypotheses, and testing rules objectively.
  • This approach is highly applicable for traders looking to diversify into new asset classes like cryptocurrencies.

• The Power of Objectivity and Rules:

  • By replacing emotions with tested rules, traders can achieve more reliable results and reduce stress.
  • Adrian details a mean reversion system as an example, demonstrating its principles and practical implementation.

• Overcoming Barriers to Systematic Trading:

  • Addressing the common fear of not being able to code, Adrian encourages traders to focus on simple, effective rules rather than complex programming.
  • He argues that simplicity often leads to better performance and less room for error.

• Consistency as the Cornerstone of Success:

  • Adrian’s systems focus on consistent execution rather than chasing large, risky trades.
  • He highlights the importance of adapting systems to personal goals, risk tolerance, and lifestyle.

By the end of the episode, listeners are equipped with practical insights into systematic trading, risk management, and the mindset needed for sustained success. Adrian’s journey serves as both a roadmap and an inspiration for traders looking to transition from inconsistency to mastery.

Transcript of Adrian Reid’s Interview On The Trading With Rayner Podcast

Rayner Teo: [00:00:00] Hey, hey, what’s up, my friend? So, today we have Adrian Reid on the show, baby! So, Adrian is a systematic trader who trades both stocks and cryptocurrencies. And what’s interesting about Adrian is that he wasn’t always a systematic trader. In fact, he started off with fundamental analysis, then he moved on to technical analysis, being a discretionary trader before Finding success as a systematic trader.

So today he trades multiple trading systems across different markets like US, Hong Kong, Australia, etc. And he has trading systems that both goes long and short. In other words, he can make money when the market goes up or goes down. Yeah. So if you want to connect with Adrian, I’ll put his social media profile in the description below.

Now, moving on in today’s conversation, right, you’ll discover firstly, how Adrian got started in trading and it’s really a very unique story and hopefully something that I can inspire my kids you know, to take up as well, right. Then we talk about the struggles he faced as a discretionary trader and how he finds success in systematic trading.

We also spoke about how he developed a trading system for a completely new market state. He has never traded before. He will share his approach to doing that. I thought that was really fascinating because those are principles that you can use, right? Especially if you want to dive in into new markets that you have not explored before.

Then we also spoke about the different type of trading systems that he employs so he can profit in bull and bear markets. And Towards the end, he also shared with us, right, a complete mean reversion trading system, right, that works. He talks about the principles behind it, the lessons learned, and how you can actually implement it on your own.

So all this and more in today’s episode. Sounds good. Then go listen to it right now.

Adrian Reid: All right. So Adrian, welcome. Welcome to the show. Thanks so much for having me. I’m super excited about this. I’ve been looking forward to this for a long time, Rayner.

Rayner Teo: I’m happy to have you as well, Adrian, and as I shared earlier, I actually came across, I mean, I got deeper and know you better through the Better Systems Trader podcast, a fantastic podcast, by the way, and I think, What really I think brought me laughter while listening to the podcast is actually how you got started in trading.

So maybe you can just give us a quick backstory how you got started in trading because I thought that was a great, a great one.

Adrian Reid: Yeah, yeah. Great. Um, look way back at the very, very beginning, um, I was about eight years old and, uh, we’re at my family’s, uh, holiday house and we found this game in there, which wasn’t ours.

Someone had left it there. It was called the stock market game. And, um, in that game, You go around the board and the market moves up and down and you buy and sell stocks, you collect dividends and you become a billionaire very, very quickly. And I thought that was the best thing ever. And, uh, so if you, if there was a good, a positive introduction to the markets, I definitely had it because that was amazing.

Um, of course it was a while before I actually got started trading for real. Um, and when I finished university, uh, graduated and, uh, got my first job, you know, I [00:03:00] discovered what the workforce was like, and, uh, I quickly realized that I didn’t want to do that forever. And so I, uh, I talked to the adults that I knew, I talked to my father and I said, Hey, uh, Dad, I really don’t want to work forever.

What do I have to do so I can, you know, retire, retire early? And of course, he laughed at me. I’m like 20 something and he’s been working for how long and uh, then he said, well, look, if you want to, if you want to, um, retire early and don’t have to work your whole life, you gotta learn to invest. And so we talked about investing, you know, property, shares, other investments, and, uh, I didn’t have the money for property, uh, so I, um, I, I got interested in the stock market, and I started researching, started, uh, started buying stocks that I knew, you know, companies that I thought were good companies, companies with good products, companies that people recommended, and of course, none of that worked, Uh, and then I, um, I tried fundamental analysis, you know, I looked at balance sheets, I looked at, uh, profit and loss and earning statements and dividends and of course that didn’t work.

And, uh, so I tried lots of different things. And then I tried, uh, I came across technical analysis. And I studied engineering, right? So, um, the, the charts, the mathematics of it, the, you know, trend lines, all of that just appealed to me. I thought that was the best thing ever. So I started drawing lines on charts and indicators and had squiggly lines all over the place.

And of course that didn’t work either. You know, I really loved it. And so I was spending four or five hours every single night running scans, drawing trend lines, support and resistance, looking at indicators for confirmation, blah, blah, blah, all the stuff. And, you know, I just wasn’t getting anywhere. And, uh, I was so frustrated because, I knew there was something there.

I knew money could be made, but I just wasn’t making any. I wasn’t losing much. I was very conservative. I had good position sizing, good risk management right from the beginning, but I just wasn’t making any money and, uh, you know, I was sort of at the verge of quitting and, uh, instead of quitting, I decided I’d double down and I started ordering books from Amazon and I’d get boxes and boxes of books.

I was reading all sorts of things and, uh, I came across Amazon. MarketWizards, which is still on my shelf over here. I read all of the MarketWizards books and that was amazing, right? Because I read the interviews in MarketWizards. It’s like, oh, that, that person, they’ve got a horrible life. I would never trade like that.

You know, screens in the bathroom, screens in the bedroom, wake up every, you know, 15 minutes at night to see what was going on. Forget that. And then there was another person that was like doing deep, deep fundamental research. I was like, Oh, you know, I could never do that. It’s so boring. And, uh, so I basically crossed out all of these interviews and I found the ones that really appealed.

And this is where the magic happened is where I sort of turned the corner because the ones that really appealed were the systematic traders. You know, like the turtle trading style, um, a purely objective rules, all backtested and, uh, again, the engineer in me just went, Oh, [00:06:00] that’s it. And so, uh, I just doubled down on, um, systematic trading and I, I read book after book.

I did a few courses and, uh, just went all in on that. And I launched my first system. I took three months off work to build my first system. And, uh, once I launched it, count turned around, started making money. And, uh, It’s been systematic ever since.

Rayner Teo: It was a trend following system. Did I get it right?

Adrian Reid: Yeah, absolutely.

Um, yeah, first system was a trend following system. I remember the trade that changed everything. It was a small mining company, MCR. Uh, it went from, I don’t know, I can’t recall, 13, 14 cents, 14 and a half cents something to 42 cents. Uh, so it was penny stock. And, um, but that, that was a huge profit because I pyramided in a couple of times and that was a trend trade.

And from then on, I was just hooked on systematic trend following and, uh, you know, I did that for a long, long time, seven years, in fact, before I changed anything.

Rayner Teo: And maybe to take a little step back, I was curious, you mentioned the stock market game. I’m very curious. Is it, is that game still around? I think it’s something that I could get I have it actually.

Adrian Reid: Yeah, I, um, I, um, I salvaged it from the, um, the family archives. I, I, I keep it here. Um, I should have brought it in, I could have shown you. But um, I don’t think you can buy it anymore. It’s um, you know, I think it’s delisted.

Rayner Teo: Okay, so it’s probably made by some smaller game production companies and they’re no longer around.

Okay, I definitely want to look for something similar, right, to get my kids involved. Expose them as early as possible, yeah? Oh yeah,

Adrian Reid: absolutely. And the kids get it, right? I mean, I started Actually, I was saying to you earlier, you know, we lived in Singapore from 2014 to 2017. Um, around that time, I started teaching my kids about trading and my daughter was five.

And, uh, so, you know, I showed her charts. I talked about, you know, the long term moving averages. I talked about stop loss, risk management, position sizing, trends, and it’s amazing how much they get, you know, when they don’t have all of the junk that school has taught them, she was very young, you know, I think she was in kindergarten or year one.

And, uh, when they don’t have all of the preconceived ideas and the rules that school kind of beats into them, you teach them traded principles. They’re like, Oh yeah, I’d show her charts. I say, Oh no, you don’t want to own that stuff. That’s trending down. So, you know, the kids

Rayner Teo: get it. Yeah. The school will go along the lines of the efficient market hypothesis.

You can’t beat the markets, you know? So, and then you kind of like, you know, just kill whatever hopes of, you know, profiting from the markets from then on. Absolutely. So, you know, looking back, you know, you’ve, when you share a journey as I’ve, you know, sent a few emails to you, and older brother going through the same journey as me.

I went through some so similar, you know, trying, you know, value investing, you know, checking the fundamentals of the company. It got slower. Oh, it’s even cheaper. It’s a better buy right now, but guess what? It becomes slower. So same process. [00:09:00] Yeah. So you also spoke about, you know, you tried indicators, trend lines and stuff.

So I would like to know, why do you think that didn’t work for you? And then systematic trading worked for you.

Adrian Reid: Yeah. The big, um, I think the big thing about discretionary technical analysis that’s hard is the discretionary piece. Right? You can have indicators and say, okay, well, the, this indicator says it’s going up.

This indicator says it’s going up, but that indicator says it’s going down. And I think this is a support line, but hang on a minute. No, now I need to redraw it now because it’s gone a little lower and just, or maybe it should be a little, like, Maybe it should be a little higher. And this is the trendline.

Oh, hang on. No, this is the trendline. Or maybe this should be the trendline. That’s the problem. You know, it’s not repeatable. And it’s very easy in the middle of the chart. It’s like, Oh yeah, that’s a buy. Yeah, that’s definitely a buy, right? Oh yeah, I would have sold there. No, you wouldn’t. If you look on the far right hand edge of the chart, these things are almost impossible to do with consistency.

And, uh, you know, I, I survived only because I had good risk management, you know, I had very small risk per trade when I was doing discretionary technical analysis. But as soon as I went systematic, all of a sudden the emotions are gone. Um, there’s a consistent process. I can test and evaluate the process.

So hang on a minute, that doesn’t look like a good trade. And the system says buy. So why doesn’t that look like a good trade? Oh, it’s because it’s too volatile. Let’s test a volatility filter and see if that hypothesis is true, you know, and you can get evidence, you know, uh, backtested data to tell you should or shouldn’t kind of trade that sort of stock.

So you can really test and evaluate, um, rather than just be blindly driven by your emotions. And, uh, you know, that, that’s what discretionary traders really struggle with is the inconsistency in the emotion.

Rayner Teo: Right. And also like, you know, because, uh, I have done discretionary trading, systematic trading, I’ve done both sides of it, and I think one of the struggles that many discretionary traders find is that, yeah, I know, you know, systematic trading, there’s benefits to it, but I can’t program, Adrian, you know, I’m not sure how to, you know, write the codes and stuff like that, what would you say to someone who, you know, can’t program for nuts, and they want to be, let’s say, a systematic trader?

Adrian Reid: Look, I hear that so frequently, and to be honest, my belief is that it’s an excuse. Um, and I hate, you know, I hate to sound harsh, but I couldn’t program when I started either, but I had the desire to learn because I knew that I wanted to be systematic so that I could eliminate the emotions. I could be consistent.

I could test my ideas. I could prove that I had an edge. And if you want to do all of those things, and if you could do all of those things, and that could make you hundreds of thousands or millions of dollars, wouldn’t it be worth learning something new? Right. And, you know, I found actually that it’s, it’s not that hard if you’re a somewhat analytical [00:12:00] person to learn to code a strategy.

And the good thing is if you’re a, if you’re not a coder, I’m not a coder, you know, I didn’t do computer science. I didn’t study any coding in school, anything like that. So if you’re not a coder, the tendency is to keep things simple and that works. If you are a coder, the tendency is to make it, you know, really complicated and rocket science and trying to, all of the formulas and rules and, you know, loops and fancy programming, and that doesn’t work, right?

At least not in most cases. So. People who aren’t coders, I would say don’t let that hold you back. Have the vision of being a systematic trader so that you can have consistency. So that you can prove you’ve got an edge. So that you can test your hypotheses and know for sure, one way or the other, is it a good idea or is it not?

And use that as the drive to learn the skill. Yeah. Um, because once you do, it’s just so powerful.

Rayner Teo: Yeah. So for me, for those who are still watching, so for me, the path that I took is that I think maybe I had a little bit of a entrepreneurship background. So I hired a developer, a coder, right, to help me do the testing.

And these days there’s so many marketplaces. Some of them are not really expensive, especially you get it from developing countries like, you know, Indonesia, Vietnam or Philippines, right? Pretty decent price and pretty decent work. So again, options for other non systematic traders to consider if they want to step foot into systematic trading.

Yeah. And maybe let’s talk a little bit about the stock markets, right? I understand that you offer a number of trading systems that covers different markets. If I’m not wrong, it’s Canada, the U. S., Australia. So I’m, I’m, I like to hear, right, you know, what are some concepts that that work in, let’s say, in the US stock market, but maybe not so much in other markets?

Or maybe we kick things off first, like, you know, what are some proven concepts that work for the US stock markets?

Adrian Reid: Well, look, there’s, I sort of, stepping back, I think about systems, trading systems or strategies in a couple of different, uh, buckets, right? We’ve got trend following, we’ve got mean reversion, we have, uh, rotational momentum, uh, which is somewhat similar to trend following, a little bit different.

We’ve got seasonality, right? And then there’s some other strategies as well. So there’s definitely, um, uh, trend following strategies that work. There’s rotational momentum strategies that work. Mean reversion can work, but, um, you know, there’s been some shifts in the U. S. market over time, and so some strategies that worked, say, 10 years ago, don’t work now.

So market behaviors can shift, um, and then there’s definitely some seasonal patterns in the U. S. market that work, yeah? Um, the Santa Claus Rally, for example, there’s, um, the, uh, Ultimo Effect, which is, at different times of the month, the market is, tends to be strong or tends to be weak. So those are tradable as well.

So I would say in most markets, you can find strategies that are either trend following, mean reversion. Uh, rotational momentum or seasonality that work. But what [00:15:00] works specifically in the U. S. versus what works specifically in Australia or Hong Kong may be different. Because the markets have different personalities.

So in the U. S. I’ve got a, I’ve got a trend following system. I’ve got a rotational system. I’ve got a short side system. Um, I’m not trading mean. Oh yes, I am trading mean reversion system in the U. S. right now. Um, so, and I’ve got a seasonality system. So I have the whole set. Um, and I think that’s really powerful because that diversification is what smooths your returns, is what means if there’s not a really great trending period, something else might be making money.

Yeah. Um, the interesting thing, and then one, one. One lesson that I struggled with at the beginning, when I was learning, is I was ordering all of these books I was talking about to you about earlier, and all of the authors, or almost all of them, inevitably, were American, and so I’d get these books, and I’d look at the strategy, and I was only trading Australian stocks, and I’d try the strategy, and it wouldn’t work.

It’s like, this is a famous trader, why doesn’t it work? I hadn’t realized that different markets had slightly different personalities. Because they’ve got, you know, different participants, different exchange rules, different levels of liquidity, different size of companies. And so, I think the big learning is that, yeah, the generic strategies can work in most markets, but they need to be adapted because the markets are a little bit different.

Rayner Teo: Could you maybe give an example of the concepts working, let’s say between the Australian and the US market, but maybe the strategy has to be tweaked. Let’s say something that works for the US has to be tweaked to cater to the Australian market. Maybe something. Yeah. Yeah. Good one. Good

Adrian Reid: question. Um, so look, a trend following system is a good example.

I mean, in Australia, trend following on small cap stocks works really well, long term trend following. So, um, buying a long term breakout, holding for a long, uh, uptrend, With a wide wide trailing stock and if you have a system like that that filters for low volatility stocks and has a portfolio of say 20 different positions managed by the same system, um, that will work very well in the long, over the long run in Australia.

That same system translated directly to the U. S. Um, doesn’t work so well, like just a pure breakout I’ve found, uh, on the U. S. stocks doesn’t work as well. So like, let’s say in Australia, the 200, if the closing price is the highest close in the last 200 days, 200 day high is high. That, um, that breakout entry works pretty well for trend following in Australia.

on its own in the US, it doesn’t work so well. So I found instead that like a volatility breakout where the stock jumps a certain amount within a short space of time, that works well because there were a lot of false breakouts on just the 200 day highest high, for example, in US stocks. So the general concept of these two strategies is very similar, but just the [00:18:00] precise trigger, you know, one, you know, might be a little bit different from one market to the next.

Rayner Teo: Got it. I understand. And I think also like, uh, for example, like Based on my own testing, like mean reversion trading in the US stock market, I think like, you know, 5, 10, 20 day low. It’s possible to make money in mean reversion trading, but if you kind of like do a little bit deeper, like the 50, a hundred day, it kind of stops working.

So I won’t be surprised if let’s say. The 5800A that doesn’t work for the US stock market could work for some other stock market around the world. I’ve, I’ve no idea which market it could be, but I think that’s kind of like expanding on the concept which you shared earlier. The concept works, but I think the parameters or the tactics to execute that concept, that has to be tweaked for the individual.

Yeah.

Adrian Reid: I mean, we’re going to talk about a strategy later on in this, um, in this conversation, which I’ll, I’ll share the details of, but it’s a mean reversion strategy. And that strategy works well on the Canadian market. Works okay on the Australian market. Used to work well in the US market, but not anymore because the market behavior has changed.

And, you know, that’s an example of like certain behavioral patterns or certain price movements. Um, used to be a good signal, but maybe the edge fades over time as too many people are using them. Um, or maybe the edge fades over time or changes if the market rules change, the participants change. For example, high frequency trading comes in, change the dynamics of the market.

So, you know, strategies that just because it doesn’t work in one market, doesn’t mean it might not be a good strategy in another market as well.

Rayner Teo: And since you talk about, uh, Australian and U. S. so far, how about Hong Kong? Are there any certain distinct patterns in the Hong Kong markets that is different from the rest?

Adrian Reid: Yeah, I actually really like the Hong Kong market. It’s probably, um, when I added it to my portfolio, I found it a really powerful addition for a couple of reasons. Firstly, diversification. Um, oftentimes the Hong Kong market will be strong when the U. S. market is weak or vice versa. Um, a really great, uh, side effect of trading the Hong Kong market was, um, it turned around and started dumping during COVID before the U.

S. market. Um, so I got short Hong Kong very early in the COVID decline, which was nice, um, but behaviorally, um, sort of behavior characteristics, the Hong Kong market tends to be more kind of, um, boom and bust, like more pump and dumpy, if you like, I don’t know what the technical term is for that, but I see a lot of stocks rocket up and then kind of, you know, Whereas in Australia, for example, I would see there’s, there’s a lot more instances of very long kind of grinding trends, uh, in the US, probably also more like long grinding moves or step changes between earnings and now, you know, add earnings announcements, that sort of thing.

Um, so the behavior is definitely different between the different markets.

Rayner Teo: And what comes to mind is that since you mentioned that the behavior is different, if Hong Kong is more pump and dump, then I think the trailing stop loss would probably have to be tighter, right? You risk giving back too much compared to, let’s say, a [00:21:00] market with more stair stepping, you can have like a, I don’t know, maybe a wider trailing stop loss to take into account the, I don’t know, just something that comes to my mind.

Adrian Reid: Yeah, I use quite different exits in Hong Kong than I do in the other markets. Um, so there’s, there’s one that is quite neat where if the stock hasn’t made a new high in a certain amount of time. I’ll get out. So I’m not necessarily waiting for it to hit a trailing stock. I’m just waiting for it to, I want it to keep making new highs, but if it hasn’t made one for a while, then maybe the move is over and I want to get out before it dumps.

Rayner Teo: Okay. So you’re looking for the momentum and if momentum starts to show signs of weakness, bump, you’re out of there.

Adrian Reid: Yeah. So there’s a lot, I mean, when I’m developing systems, I, I try and, um, I try and test all of these different styles of rules in each market. Okay. I don’t want to go into a new market with a preconceived idea about what will work.

I want to kind of do the full investigation, understand all of the different, um, uh, types of strategies or types of entries and exits and, and how do they actually, uh, contribute to the performance of a system. And, uh, that’s really, when I go into a new market, that’s quite a deep investigation. And then once I understand the market, then I can develop systems more quickly, sort of after that.

Rayner Teo: So. How would you then, let’s say, let’s say there’s a new market part of Saudi Arabia or something along those lines and you want to maybe apply a trend following system to it and you don’t have any preconceived bias, so how do you go about doing a test on a market like maybe let’s say Saudi Arabia, right, and, and to see what type of behavior, what type of pattern that you can exploit, right, using a trend following approach?

Adrian Reid: Well, the first thing I do is I, I, I would ideally step back from the trend following hypothesis. And say, okay, I think this market is valuable in terms of diversification for my portfolio. How can I profit from the way that market moves? So I’ll start with a more generic approach. And, um, I have some, let’s call them generic strategies, very simple trend following, very simple mean reversion, very simple rotational momentum.

And I’ve got a short side strategy that works across quite a few different markets. And I’ll start with those strategies on a new market and I’ll just test each of them and say, okay, well. Does it look like there’s any potential for that strategy in this market? And if there is, then I will do the work to investigate and dig further.

But often I’ll discard, uh, uh, the idea of trading. For example, um, I, I tested, um, quite a lot of ideas on the Japanese stock market. And I just, frankly, I just don’t have a good system for Japanese stocks. Uh, I’m sure there are good systems out there, I just don’t have one. But I tested, you know, my generic systems on there.

It’s like, well, there’s clearly nothing there. So I don’t want to just try and optimize it and make it work. It should work. In some way with a very simple generic strategy. And if it does, then I can investigate [00:24:00] further. But if there’s, if there’s no edge and it clearly loses money, then I’m not gonna take it any further.

’cause you just run the risk of over optimizing.

Rayner Teo: Hmm. Makes sense. Yeah. That makes the the of that myself. Right. I think something similar. To, uh, Andreas Klenow. He trades the futures market and he talks about market weather. Does he have a trending behavior or mean reverting behavior? So he’s like, you know, like what I just said, he does a very simple test.

See what type of behavior this market exhibits and then you dig deeper, right? Oh, this market has a trending behavior. Let me apply some trend following strategies, etc. So let’s see. Yeah. So, uh, I think I saw on your website, you have this, uh, system called the US Slippery Deep, right? It’s a trading system, you know.

Yes. Could you maybe give an overview of that, how that one works? I think it’s a short trading system if I’m not

Adrian Reid: wrong. It is a short trading system and actually it’s, it’s my favorite short trading system because it works across a variety of different markets. I have versions for US, Australia and Hong Kong.

Um, and there’s not that many stock markets globally where it’s easy to short a very broad range of stocks. Um, US and Hong Kong are actually two, which are quite neat for, for shorting, um, and also having the two of them on the short side adds a lot to the, to the portfolio. So basically the basic concept is, um, stocks are correlated and when the broad market is dumping stocks will also be, be dumping.

And so what I’m doing is waiting for a clear downtrend in the index. There’s a rally and then it rolls over again. When it rolls over again, you know that there’s downside momentum is continuing. And that means individual stocks are likely to be falling or accelerating downwards. So, um, what I’m going to do at that point is short, short a, um, a broad cross section of weak stocks, uh, based on the indicator on the index rolling over.

When the index rolls over, we get short and then we’re going to ride them down. Any of the stocks show any sign of. Um, ticking up in the medium term or the index starts rallying in the medium term. We’re going to get out because if the index starts rallying, we, um, we don’t want to have, uh, you know, we don’t want to have a short squeeze on our hands.

We don’t want to have to, um, you know, you give back very quickly on the short side, if you’re not careful. And then the other neat aspect of it is on the short side, you know, you can short sell a stock at a hundred. It can only go to zero, right? It can’t go down that far. So generally on the short side, it’s good to take profits.

Uh, so I take profits relatively quickly on the short side, whereas on the long side with trend following, I don’t have profit targets, I just let it run and run and run and run, because it can go from a hundred to a thousand, um, but it can only go from a hundred to zero on the short side. So if you get out partway down, you capture most of the profit, you take the risk off the table.

And, uh, so that gives a, a pretty neat risk return profile. What’s interesting is when you trade the short side in stocks. Often the system on its own isn’t that exciting. Like if I showed you the equity [00:27:00] curve, you’d go, you know, it doesn’t look that great. It makes single digit annual returns, and the drawdown is, you know, certainly double digit, but it’s negatively correlated to everything else in the portfolio.

So it’s making money when everything else is losing, and then when you combine them together, that’s a beautiful thing, you know, that’s, that’s where the magic happens. So, um, having the ability to make money from a bear market when, and combine that with, say, long side trend following, mean reversion, and rotational momentum, has a huge impact on your ability to build wealth, uh, to navigate bear markets without big drawdowns, and to basically smooth out your equity curve and make it psychologically much easier to trade.

Rayner Teo: Yes, I agree. And I think that’s one of the biggest advantage that systematic trader have over discretionary trader in terms of like, you know, having multiple systems that can work in different market conditions, whereas a discretionary trader, they typically would do well in certain market conditions.

And if they can’t adjust, you know, quick enough or adapt, that’s where they, you know, go into a drawdown and stuff like that. Yeah.

Adrian Reid: Yeah. I think you also, as a discretionary trader, there’s only so much ground you can cover. I mean, how many stocks can you look at in one night to find your signals for the next day?

I mean, maybe if you spend four or five hours, you could look at 20, stocks in detail, right? But as a systematic trader, I can have 20 different strategies that each have between 1 and 30 trades within each strategy across Australia, US, Hong Kong, Canada, and crypto. And I can do it by pressing a button on the computer.

So you can come with so much more ground, you can get much more diversification, keep your position sizes much smaller, and, uh, basically the trading becomes a lot easier, a lot safer as well.

Rayner Teo: It’s a good ROI in terms of your time as well, right? Putting a

Adrian Reid: few minutes

Rayner Teo: and then you can just, you know, get everything up and running.

Adrian Reid: Yeah. I mean, I don’t want to, I don’t want to, I don’t want to, I don’t want to sound like it’s easy. There’s a lot of upfront work to do that. The execution is pretty straightforward, as you know, um, but of course you’ve got to do the testing, you’ve got to build the confidence, you’ve got to establish the portfolio, figure out the weighting, so there’s work to do, but once you’ve done it, the work is done, and then the computer, when you run the backtest to generate the signals, it finds the trades very, very quickly, whereas for a discretionary trader, there’s always a large volume of work to do to find the trades to fill the portfolio.

Rayner Teo: And since you trade a number of markets, you know, US, you know, Canadian stuff, let’s say a new trader, new to this, I don’t think he’s going to trade everything all at once. Which markets would you recommend someone new to start with?

Adrian Reid: Look, it depends a little on how much money you’ve got. Um, as an example, the Australian market is not that easy to trade with a small amount of capital because we have a minimum 500 trade size.

And so you, you can’t buy [00:30:00] 200 worth of a stock to open a position. It has to be 500 or more. So if you only had a couple of thousand bucks, it’s pretty hard to get diversification across Australian stocks. Plus our commissions are a little bit higher than other markets. Like in interactive brokers, I think it’s minimum 6 per trade now, um, for Australian stocks.

And 6 as a percentage of 500 is moderately high, right? Way better than when I started. I was paying 40 a side, 40 to buy, 40 to sell. That was hard. It’s easy now, but it’s still harder than say the US market where, you know, 1 or 1 commissions or free commissions and not really any minimum trade size. Um, so Australia is hard with a very small amount of money, U.

S. is easier, uh, Hong Kong is very hard with a small amount of money because the minimum lot size for many stocks is, is big, you know, some, some stocks, uh, you have to buy 2, 000, 4, 000, 12, 000, um, shares as a minimum lot size, and so the positions can be, can be quite large, so you have to have a fairly, uh, decent size account to make that work.

Um, so the capital is a, is one of the constraints as to which market you should, um, consider trading. The other is, do you have a strategy that works? You know, I mean, there’s strategies for US, Canada, Hong Kong, Australia. There’s strategies for all the markets that work, but you need a strategy that works.

So, um, to some extent, you’ve got to find a market you can afford to trade and a strategy that works. And then you’ve got a combination that you can, you can start with. Most of my students, uh, to be honest, start with either Australian stocks or U. S. stocks. The ones who start in Australia typically have a little more capital, um, and they’re Australian.

Uh, the ones who have a little less capital usually start in the U. S.

Rayner Teo: And let’s say, for example, someone like me, I, I trade primarily the U. S. stock markets, and let’s say I want to diversify, which markets would you say is a lower hanging fruit for me to, to tackle once I have the U. S. side kind of settled?

Adrian Reid: Um, the best way to do it, I mean, I’ll give you a direct answer to the question, but the best way to answer the question is to, um, find some strategies for different markets and do a correlation analysis. And, um, when you do do that, you, you’ll see out of all of the markets that you can trade actually Hong Kong has a lot of value to a US portfolio, for example, because the markets have quite different underlying drivers, Hong Kong, obviously very China, um, driven, US quite different, um, uh, both are easy to short sell, so you can go long and short equities in both markets, which is really neat.

Um, helps with the diversification, smoothing the equity curve. Um, and I’ve found that when I combine those two in a portfolio, it makes a big difference.

Rayner Teo: Nice. Thank you. That was the only question that I’m curious myself and something to figure out, right? Yeah. [00:33:00] So, okay, now let’s maybe talk about crypto. So later on, right, uh, we will talk about the specific stock trading system that you want to share with us.

But for now, let’s, you know, take a leap into the crypto markets and, Let’s talk about maybe what are some, you know, concepts, right, you know, that works in the crypto markets.

Adrian Reid: Yeah, I mean, it’s a good question because, and the answer is the crypto markets have changed quite a lot over time. Yeah, so, um, a few years back, um, there were a lot of, um, fads, you know, so there was the NFTs and then before that there was, you know, whatever it is, I don’t really pay that much attention.

There were fads where certain tokens just took off. And trend following in those tokens with a very large profit target was hugely profitable. It was just insanely profitable. Um, now, at least over the last couple of years, there hasn’t really been fads like that. And so what we’re seeing is that, um, strength in the large caps, let’s say Bitcoin, Ethereum, Um, so if you’re, if you’re holding them when they’re, uh, strong and moving up, then you’re going to make money and then when the, um, the strength of Bitcoin starts to fall, then you’re going to cash.

So basically in and out of the strongest couple of coins based on momentum works now and works very nicely. Um, long term trend following. Um, it can work, but you don’t really get the crypto returns, right? Because you’ve got a filter for lower volatility, um, tickers to make the long term trend following really work well.

So you end up with more of a stock style of return in your portfolio. I mean, it’s a little better than stocks, but it’s not, again, like the triple digit returns that, you know. You know, you used to be able to get from the, um, the, the big fads and memes in crypto. The other thing that works really well, I mean, mean reversion just works beautifully in the crypto markets, particularly if you’re very selective and you wait for, uh, very oversold conditions in a strong trend.

So, um, I’ve got a portfolio of, um, of crypto systems, um, that trade basically each of those different concepts I’ve talked about, you know, relative strength in the large caps. Um, there’s a little bit of trend following in there, a couple of mean reversion strategies, um, and there’s a short side strategy which, um, you know, works well in a, in a big bear market.

So again, all of those same strategies work, same as in stocks, but you’ve just got to adjust them to the personality of the market. I would say the challenge in crypto is that the personality of the market has changed a lot over the last five years and will continue to do so. I think with, um, with the introduction of, uh, the Bitcoin and now Ethereum ETFs, Bitcoin has diverged from the altcoin market.

And while I think there’ll still be altcoin bull markets at some point, the market is clearly dominated by Bitcoin at the moment. Yeah, and holding Bitcoin has been super [00:36:00] profitable. That’s been, that’s particularly recently, right? Um, but, uh, holding a broad basket of altcoins, maybe not so much. So, I think the ETFs have changed.

the dynamics of the market. And it’s also very political now as well. You know, what does the U S president say about crypto and what, uh, you know, there’s a lot of big public figures in policy that, um, that affect the market. Um, and some of them are pro, some of them are against, whereas previously the, the, the regulators were all anti crypto in some way, so I think that’s, that’s shifting as well.

So we need to be on our toes in the crypto market and really monitor, uh, Is the strategy still working? Do we need to turn it off? Do we need to adjust it? And I think that will continue for a while as the market continues to mature.

Rayner Teo: And for crypto, it’s not like stocks where, you know, the S& P 500, you know, you trade the largest 500 stocks.

Whereas crypto, you don’t really have such index to say which are the basket of large cap tokens that you want to trade. So how do you go about defining which large cap tokens you want to trade?

Adrian Reid: Yeah, there’s a couple of ways to do it. Uh, one is just, um, absolute liquidity. You know, only trade tokens that have more than a certain amount of turnover on a certain exchange.

or in aggregate across all of the main exchanges. So you make sure that you’ve got a high liquidity token. The other, uh, other one you can do, the other way you can do it is, um, look at the, rank the tokens by liquidity or turnover and say, okay, I’m only going to trade the top five or the top 10, and I’m going to hold those, uh, according to liquidity.

If they break out, I’m going to hold them, for example. Um, so that’s, uh, that’s another way to do it. You’ve got to be very careful because, you know, in the S& P 500, for example. You know, you’ve heard of survivorship bias. You, you, you, if you develop a system, you have to take into account the fact that the constituents of the S& P 500 change over time.

Yeah. In crypto, it’s very tempting to say, Oh, I’ll only trade the top five tokens. You look at coin market cap, you find the top five tokens, you get a strategy, you test it over those five tokens for the last, you know, five, ten years. And it’s like, wow, that made a fortune, right? But there’s survivorship bias in there.

They’re the ones that became the biggest tokens. And you didn’t know that five years ago or 10 years ago. And so we’ve got to be very cautious of choosing the current biggest tokens for our trading strategy because the backtest will be inaccurate. It cheats because you’re using survivorship bias and also they may not be the top five tokens in five years time.

So how do you then tackle this survivorship bias? Um, well, you’ve got to design the system so that it doesn’t have it. Yeah. There’s no survivorship bias. So one way is to, um, trade a broad universe. So basically trade every token on the exchange and have your system rules, filter them out. Yeah. [00:39:00] So we’re not, um, assuming that we’re only going to trade the best tokens today.

And, and our backtest doesn’t, doesn’t cheat by looking forward to today and finding the best tokens. We know that we’ll trade all of the tokens. And you just have a strong trend filter, a high liquidity filter, a volatility cap, and um, you have the entry and exit rules and you just apply it to the whole market.

So that’s one way to do it. The other way to do it is to rank all of the tokens on a daily basis. So if you want to trade the top 5 liquidity tokens, you have to program your strategy to, for today, what are the top 5? Now, take your rules and apply them to that top five. Tomorrow, rank all of the tokens, find the top five, apply your strategy to the top five.

So you’ve got to sort of redo the ranking every day if you only want to trade the big ones. Because the top five now are different to the top five, five years ago.

Rayner Teo: And going by what you said, then it’s how do you then backtest this using this approach since when you backtest they wouldn’t know what’s the top five like 10 years ago.

Adrian Reid: Yeah, it’s a much more, it’s a much more challenging coding exercise to be honest. I mean, it is doable. Um, because basically what you have to do is get the code to look. On each day of the back test, do the . Right. Okay. On every single day of the back test. And then based on that ranking, you can then make your decision.

So, you know, that’s hard. Harder, yeah. Not impossible, just harder. Um, the simplest solution is to use the broad basket and just have your rules filter out the junk to gappy. Too volatile. I’m not trending strong enough. That sort of thing.

Rayner Teo: And where do you get crypto data? I know for stocks, I use Norelke, but what about crypto?

Adrian Reid: Yeah, so for crypto, um, for, for, for trading, I use the, um, the data straight from the exchanges. So, you know, I’ll download data from Binance. I’ll download data from Kraken, from KuCoin, et cetera. Um, and I just have an automatic downloader that pulls that data. It’s in, in, um, CSV format and it goes into, um, Amibroker.

So I can do the backtesting there. Um, that goes back only so far. Because basically the exchange will have data from when the exchange listed each token, which is maybe not the whole lifespan of that token. Um, so you can buy other data sets separately that, um, separate com different companies have aggregated over time from different exchanges and different data sources to make a longer term time series.

Unfortunately, that data doesn’t work. Tends to be expensive. Um, so I, for example, I paid 450 a month for the data subscription for the, the crypto data. Um, I’m, I’m not comfortable to I don’t want to plug that company, so I’m not going to mention it by name. Um, not that there’s anything wrong with the company, it’s good data, but you know, it’s a, it’s a high cost subscription and I feel like it’s a bit highway robbery to be honest, so.

Okay, I understand.

Rayner Teo: And for stocks, uh, when you say you’re trading Hong Kong stocks, does Norgate provide Hong Kong stocks? I can’t remember. No, it does not.

Adrian Reid: So [00:42:00] Norgate provides, uh, US, Canada, Australia. Um, and I, I think that’s all they’re going to do in stocks. I don’t think they’re going to expand to any other markets.

Um, and so that’s great. I use Norgate for those markets because it gives you, uh, delisted stocks. It gives you the historically accurate index constituents, which is important for, um, for backtesting strategies like on the S& P 500 stocks. You need the historical index constituents. For Hong Kong, I use Metastock data.

And Metastock is neat because for one subscription, which is actually pretty cheap, you get every single stock market in the world. So all stocks currently listed. Um, but that’s the catch. It’s currently listed. So you don’t get the listed stocks and you also don’t get the information on index constituents.

So like, um, let’s say what stocks are in the Hang Seng index, you know, it’s like, Okay. you know today, but you don’t know five years ago. And so outside US, Australia, Canada, I don’t have any strategies that trade stocks in an index. All of my strategies trade the entire market because you have to, you can’t afford to, you can’t backtest a strategy that trades only stocks in the index unless you’ve got the historically accurate index constituents.

And Northgate is the only data provider I’m aware of that provides that. Okay. And it’s only for Australia, U. S. and Canada.

Rayner Teo: So for the U. S. stocks, do you do a backtest till, I mean from 1950s or you take into account the more recent years?

Adrian Reid: Uh, look, generally no. Um, however, uh, I like to understand what happens during different economic conditions.

So, you know, inflation up, inflation down, high interest rates, low interest rates, interest rates rising, interest rates falling. Um, these things like it’s important to understand how stocks move in different macro economic environments. And until recently, you know, most of our lifetime, what were interest rates doing?

Falling, right? And then they started to go up, uh, post COVID, but we didn’t really have a lot of data to say how would the different markets behave. when interest rates were rising and or high or when inflation was out of control. But if you go back a little further in history, then you can see what happened to the stock market.

And I think that’s, you know, I think that can be useful. Um, I have a trend following system for US stocks. And it’s not my best strategy, but it’s a good strategy. It’s solid, right? And, uh, I think it’s, uh, it’s valuable. But the great thing is you can test that back to 1950, including all delisted stocks.

And it worked the whole time, just like grinding up, right? So it didn’t, didn’t shoot the lights out. It’s not making like 30 percent return per year, but it works. And that gives me a lot of confidence. It’s like no matter what happened, interest rates up, [00:45:00] down, inflation up, down, war, famine, you know, pandemic, it worked.

And I just think more data is better than less.

Rayner Teo: And what if, let’s say, a mean reversion trading system, it works the last 20 years, but if you dig back further to the 1960s, 70s, it didn’t work, what would then be your take on that? Yeah,

Adrian Reid: it

Rayner Teo: won’t.

Adrian Reid: Look, quick hint for everyone listening, is mean reversion strategies generally won’t work back that far, at least not in my opinion.

In my experience, I think the market dynamics have really changed a lot over time and, um, so you’ve got to look at the nature of the strategy and say, okay, well, how long do I expect this type of strategy to survive? And I would say a trend following strategy should have a long lifespan. Yeah, trends exist.

They’ve always existed. They will continue to exist. And so a simple, robust trend following strategy should work over decades. You might have to tune it up and whatever a little bit, but the way the market moves in the short term has changed so much. Liquidity has increased massively. The size of companies has increased.

Um, high frequency trading and, Exchange rules, all of that changes over time, and that affects short term strategies much more than long term strategies, I would say. And so, generally, for mean reversion, I’d be looking at much more recent data, yeah? And just to be clear, I don’t optimize and fine tune a trend following strategy on old data, like back post 1990 sort of thing.

Um, that’s just for sort of, for validation and, and understanding of, okay, what could happen if,

So when

Rayner Teo: you talk about trend following strategies that, you know, seems to be robust, right? What about, earlier you spoke about relative momentum. How does that hold up during, you know, the 50s and

Adrian Reid: 60s? Actually, it’s a good question. To be honest, I haven’t taken a rotational momentum system, um, all the way back.

I’m going to do that for homework after this call. Sure.

Rayner Teo: And yeah, so we were talking about mean reversion earlier. So I think now’s a good time. Maybe I think you’ve replied to some. presentation slides for us to talk about a mean reversion trading system. So Adrian, right, let’s, you know, see, you know, what you have prepared for us, for the viewers to learn a simple mean reversion system that they can, you know, account and use.

Okay.

Adrian Reid: Yeah. Let me share my screen here. So what I’m going to do is. Um, I’ve called this presentation. It’s not really a presentation. I’ve got some slides, uh, basically talking through some concepts. But what I’m going to do is draw out some lessons from a mean reversion system. Um, I’ll, I’ll talk about kind of what the system is, how it works and, um, and show you some trades and some individual, uh, lessons I think are useful for people to hear.

Um, and then I’ll show you how you can show everyone how they can get the rules, the exact rules for it. Later on. Awesome. Is that okay? Sound good? Sounds good. Okay, great. So, uh, lessons from a mean reversion system. Let me, um, come over here. So first I’m going to show you a backtest for this, [00:48:00] uh, mean reversion system.

Now, just in case anyone is not familiar with backtesting, what this means is you’ve got your trading rules. This is a system, which means it’s got absolute rules. If certain things are true, you buy. If certain things happen, you sell. And so those rules have been coded into, uh, in this case, Amibroker formula language, and I’ve applied those rules to every stock in the market over the last 30 odd years.

Now, in this case, this is applied to the Canadian stock market, including delisted stocks. So had we followed this strategy over the last however many years, the chart on the left is the equity curve. That’s what, um, that’s how the performance would have looked. The chart on the right is the drawdown profiles.

This is how big a dip. The strategy would have had in your account. So you can see in 2000 and looks like about 2008, the biggest dip here in the account was about 9 percent and that would correspond over on the left hand chart to this big, this dip here, which was right at the start of the global financial crisis.

So as the market turned in the global financial crisis, this system had a few trades on, but then eventually it went to cash and just waited until the bear market was finished and it started trading again. So this is the performance of the system. And it looks, you know, it looks pretty good. Bottom left to top right.

It’s kind of a relatively straight line. There’s some rallies and there’s some flat spots, but it’s a, it’s a system that has clearly worked over time. Right. So how does it work? What are the rules? Well, first of all, there’s a trend filter. Uh, the trend filter basically says we only want to buy stocks that are trending up.

You know, if we’re going long, uh, we only want to do it on stocks that are trending up because that just gives us an increased edge. Um, the, there’s a volatility filter. Volatility. Filters are important for mean reversion because higher volatility stocks tend to perform better with a mean reversion strategy.

Um, you get a bigger move, higher average profit per trade, more chance of overcoming the cost of slippage, slippage and commission. So we’re looking for high volatility stocks here. Liquidity, uh, liquidity is important. We need to have enough liquidity to get in and get out of the system, uh, really easily.

So here, the average daily dollar value, um, dollar turnover is a million dollars or more per day. So imagine if a stock trades a million dollars per day, if you’re trying to get in and get out with a 5, 000 or a 10, 000 position, it’s pretty easy to do it without much slippage. But if the stock was only turning over 100, 000 a day and you’re trying to get in and out with 10, 000, um, a 10, 000 position, Slippage can become a real problem.

And for mean reversion, that’s critical because mean reversion, we typically are small average profit per trade. And we can’t afford to have that eaten up by slippage and commission. We need to make sure that we’ve got high enough liquidity so we can get in and out and preserve that small edge that we’ve got.

Um, the next rule is price. Uh, so we, we want to filter out very low priced stocks and that’s useful because in the Canadian market, [00:51:00] um, you pay commission as a certain amount per share that you buy. So if it’s a 10 cent stock, penny stock, then you pay the same commission per stock as if it was a hundred dollar stock.

And obviously that’s a higher percentage on the 10 cent stock than it is on the hundred dollar stock. So we want to trade slightly higher price stocks. In this case, I’ve got the minimum price filter set to 5. And then there’s an entry and the entry is a fairly typical mean reversion entry. It’s a oversold RSI.

In this case, it’s a three period RSI hitting a very oversold level. So when the stock is tanked heavily, we’re going to buy in anticipation of a bounce. And then there’s two sell rules, one which, uh, gets you out if the stock bounces just a little bit above a short term moving average, and one which gets you out if the stock continues to go down and, um, crosses below the long term trend filter.

So, generically, these are the rules. Now, um, listeners can get access to the exact rules, I just didn’t want to burden people in the, uh, You know, on the show with all of the technicalities of what the rules are because the lessons I want to draw out, um, uh, irrespective of what the exact rules are. So I don’t want to be distracted by, you know, the technical rules.

In any case, people can go to enlightenedstocktrading. com forward slash free and download these rules for themselves so they can, they can get the exact rules. All right. So let’s talk about some of the lessons from this. Does that make sense? Or do you want to ask some questions before we go on? Crystal clear to me.

Crystal clear. All right. So I ran a backtest. And here is part of the backtest results. And the first thing to point out is that the annual return was 7. 34 percent per year on average. And a lot of people will look at that and go, Oh, well, that’s not much money. You know, I could have got better returns doing XYZ.

Why would I trade that system? The annual return is low. And this is a mistake. to think that the return of a system is low, therefore it’s not a good system. Because in this system, the return is low, but the exposure is very low. The exposure is only 1. 45 percent. So what that means is that it’s only invested 1.

45 percent of the time. The rest of the time it’s in cash waiting. And so the return per unit of time invested is really good. You know, we make great returns when we’re invested. Otherwise, we sit in cash. Now, the cool thing about that is we can then combine this with several other strategies very, very easily because this doesn’t use much capital.

We can add it to another strategy that doesn’t use much capital and another strategy that doesn’t use much capital and stack them on top of each other in a portfolio and our returns start to grow. The absolute return of any individual system doesn’t matter that much. It’s how much value does it add to the portfolio of systems?

That’s the important thing. [00:54:00] I find that a lot of traders will look at a strategy on its own and go, yeah, it’s not really good enough for me to trade. I’m going to pass. But looking at a strategy on its own, it’s a huge mistake. You know, we should look at the strategy in terms of how it can contribute to our portfolio strategies, not look at the strategy in terms of how good is it in isolation.

That makes sense.

Rayner Teo: Yep. I think the way I look at it is like, you know, you, we have 24 hours a day. You can spend maybe a strategy, you spend 20 hours a day working to make 500 or would you rather spend five minutes a day and you make maybe, let’s say 50, 50 is smaller than 500, but you only spend five minutes a day spending that 50.

Adrian Reid: Yeah. And if you have 20 different ways to make 50 bucks. And at different times during the day, you end up making really good returns for very little effort.

Rayner Teo: Yep, exactly.

Adrian Reid: And so this is, this is how I think about trading. And I can’t tell you how many times, I mean, I know you get it, right? But I can’t tell you how many times I’ve had a conversation with a trader about a system and they’ve gone, Oh no, I don’t, I don’t like that system.

That’s not good enough. I want a better system. Whoa, hang on a minute. You’re thinking about it all wrong. And, and I think this is the magic. If you can get, if, if, if, if we can get our heads around this, it’s then a very short leap to creating a portfolio of strategies that work really nicely together.

Yeah. So I think that’s the first lesson I want to call out. Just because a strategy has low return doesn’t mean it’s a bad strategy. Actually, another, another good example of this concept, you know, you asked me about the Slippery Dip system. That system has a very low annual return. You know, it’s about, um, I think my version of it’s about eight, eight to 10 percent per year compound return, but it makes all of that return during a bear market.

And during a bull market, it’s completely in cash. So you can combine that eight, eight to 10 percent return per year from bear markets With a long side trend following system that makes money in bull markets and they don’t overlap Because the trend following systems in the market in a bull market the slippery dips in the market in a bear market They can use the same capital.

So the returns are additive, which is kind of magic really when you think about it

Rayner Teo: Yeah, it’s like maybe let’s say if a long only system that does 15 percent a year and this one Let’s say you’re the one you shared it was 8 percent so it’s like 15 plus 8, 23 percent annualized return a year

Adrian Reid: Yeah, absolutely.

And lower drawdowns as well. Oh, yes. So, combining systems is the magic, 100%. Okay, what’s the next lesson? So, this system doesn’t trade very often. You look at the equity curve, there’s long flat spots. You can see flat spot, flat spot, flat spot, you know, all the way up the equity curve. And 13 trades per year.

So the lesson here is this is going to be really boring. If this was your only system and you’re only taking about 13 trades per year, it’s going to be very hard to, you know, maintain focus and attention and do it consistently. So this sort of system is [00:57:00] really great for automation because the computer doesn’t get bored.

You know, so my automation runs every day. It just updates the data, runs the backtest, places the trades, and reports the results. Um, that’s gold because I can have a whole bunch of systems that don’t trade very often and combine them together into a portfolio. And I don’t have to worry about having the discipline to follow those systems every, yeah.

Some systems are very boring to trade, like this one, but it doesn’t mean it doesn’t work. So that’s the sort of lesson two, um, one system in isolation, it might not be very exciting to trade. So combining it into a portfolio will give you more activity and, um, that’ll make it more interesting in your, uh, in your day to day operations, you know, keep you focused, but automation really, really helps for systems like this.

Okay. Um, now I’ve got some trades. that the system generated. So I thought I’d show you the chart and then just talk about the lesson from that chart. Make sense? Um, okay. So here’s a, um, here’s a stock trend that, um, this is a profitable signal that the system picked up. And I’ve just picked this signal at random out of the backtest.

And you can see it’s a strong uptrend. It’s pretty volatile. And then the stock, uh, corrected very sharply. Um, we bought right at the low. And then we sold a couple of days later. The best trades from a mean reversion strategy are often the most uncomfortable. So after several very heavy down days and a big gap down, the system says, buy.

That’s not going to feel good. That’s going to feel like trying to catch a falling knife. But what I’ve learned is that the vast majority of the time, my best trades didn’t feel good putting them on. And this is true in mean reversion, and it’s true in trend following, and it’s true on the short side.

They don’t feel good, but that doesn’t mean they’re not profitable. And so here, our lesson is we’ve got to be really careful to not let our emotions get in the way of the system, of the strategy. You know, we’ve got a system, we’ve backtested it, we’ve proven that it’s, uh, profitable, we’ve built confidence in it, now we need to follow it.

And if you hadn’t have taken this trade because it really looked like the stock was going down and it was going to keep going, then you would have missed out on a big profit that happened very, very quickly over just two and a bit days. So we’ve got to take the signals even if they look uncomfortable.

Um, here’s another one. Um, this, uh, this stock, uh, had a very long, uh, strong uptrend in, this was in 2024. You can’t see the, the numbers at the bottom, uh, the scale at the bottom probably, but, um, That would have been a pretty difficult trend trade because the stock was very volatile and most trend following systems probably would have kicked you out.

But we do get large retracements pretty frequently in strong trends. And you can see on the left hand side, this is the [01:00:00] trade. So we’ve entered after this very strong retracement. We bought right at the bottom. The system gave us this signal and then a couple of days later, we sold out here. Um, and if on the right hand side, I’ve just zoomed out on that chart.

And again, this is a trade where you looked at it and thought, Oh, you know, that trend is over at this point where it’s highlighted in green, you would have thought, you know, very likely on the day of the signal, that would have been pretty scary to take. because the trend line is clearly broken and it’s been very volatile.

It’s gapped down a couple of times. You’re not going to, you’re not going to feel good taking that trade, but this is a very common, um, mean reversion trade that tends to perform well. It doesn’t feel good, but, uh, after a very heavy period of selling, the market does tend to bounce just a little bit and you can get out and make a profit.

So, this was a moderately good trade, but it would have been scary to take as well. Here’s another one, and this is, um, this is a really important lesson. Um, this stock rallied really hard, and then rolled over and collapsed. The first wave of the collapse was a sudden sell off, and then it bounced. And collapsed again.

And as the stock sold off heavily the first time, we got, this system got an entry, a signal to enter. So it bought long, right at this low here, at the open. And then two days later, it rallied. And we got a signal to exit. A lot of people at this point are going to be hoping it comes back to previous highs.

Cause maybe that was just bad news. Maybe it was overdone. Maybe it’s not over. What if it keeps going? What if it takes the next leg up and I don’t want to miss out. So it’s tempting to not take the exit. And so here the lesson is you have to take the exit because This is the strategy. It captures small bounces.

We can’t turn it into a trend trading strategy because that’s not what it is. If you don’t take this exit, you would have ended up holding all the way down. And psychologically, that’s very, very damaging, but easy to do. So, the lesson out of this one is if you get an exit, take it. Take it on time every time, right?

Because if you don’t, who knows what pain you’re going to end up finding yourself in. Yeah? What else we got? Okay, here’s a example of a losing trade, right? Um, this stock was trending up. Um, couple of weeks it went down very, very heavily and we got a signal to, to, to buy. But sometimes in mean reversion, you buy the dip.

It does keep dipping, right? You’ve seen the meme online. I bought the dip, but it kept on dipping. Um, that does happen, right? Uh, so what do we do about that? We can’t predict which ones, uh, which, which trades are going to keep dipping and which trades are going to bounce and give us big profits. We just don’t know in advance.

You only know after the event. So the way you, you, um, resolve this [01:03:00] is firstly, understand what’s possible, right? So do the backtest, look at all of the worst trades and see what can happen. That’s the first step. Second step is run the backtest and sorry, is, um, run the backtest and look at your position size.

And what you’ll see is that if you size too aggressively, trades like this really, really hurt. But if you have a broad, um, portfolio where you’re sizing very conservatively on each individual stock, a trade like this doesn’t hurt that much. And so the big lesson is size small. Smaller than you think. Make sense?

Yep. Alright, then we got, uh, another loss. This was a, this was a good one. Um, so the trade, um, the trade bought here. So, so the system bought here. And the next day It, um, the stock dumped and it had a really long lower week on the candle. And if you had an in market stop loss, this trade would have been really, really bad, but often the market overreacts during market hours.

And so on this sort of system, I really don’t like to have an in market stop loss. I rather have a next bar and open stop. So if it gets touched today, we get out next bar and open because that way I’m not locking in the extreme of emotion that’s happening during the trading day when the market is, is, um, really, uh, really collapsing.

Often overnight there’s a bit of a breather. People go, Oh, it wasn’t that bad. The stock tends to, um, tends to recover a little bit and you can get out at a better price. That’s not always true, obviously, but if you backtest a in market stop versus a next bar and open stop for every strategy that you use, often you’ll find that a next bar and open stop is more profitable, and I think that’s useful information to know.

Uh, is this useful?

Rayner Teo: Yep. That’s really insightful. Thank you.

Adrian Reid: Okay, cool. Um, here’s another losing trade. Um, this was a 20, 20, um, 20. 5 percent loss. So we had, um, a big decline and then the market gapped down and we, and the system, um, system bought, uh, that wasn’t, that was a pretty reasonable entry, but it kept going down on the day of entry.

So there’s a red candle. We entered at the open, it kept going down. So it wasn’t the perfect entry. Um, and the market did rally the next day. And so we got out, but sometimes the rally is just not big enough to give us a profit. Um, and if we’d have just held a little longer, you could see there’s this big green candle that would have been magic, but the system already got us out.

And I think the, you know, the lesson here is FOMO is Firmware is really a big problem for traders. You know, you could look at this and go, Oh, you know, I should have held on. Next time, I’ll hold on a little bit longer and just see if it bounces a little more. That way, I’ll make more money, right? This is the emotional rationalization that’s going on.

But, if you [01:06:00] did that and you held on a little longer, what would have happened on this trade? You know, we would have ended up down here somewhere waiting for a big bounce. And so, we’ve got to take the exit and And then not worry about what happened after the exit. Like the system doesn’t know, the system doesn’t care, it just got out.

So, you know, don’t, I, I actually very, I don’t want to say never. I very rarely look at the charts of stocks that I’ve exited. Why? Because I’m out of it. You know, I don’t, I don’t want to have that emotional reaction coulda, you know. I’d rather just follow the system and move on. It’s emotionally much, much easier.

What else? Oh, here’s a good one. Um, this shows you, uh, the time between equity highs. So, the system made a high, and then how long was it before it made a new high above that, um, above that level. So, basically, how long do you have to wait to feel like you’re making money? And I, I think the, the lesson here is interesting in that as, um, as people in the out, in the non trading world, We’re trained to go to work, get paid, go home, go to work, get paid, go home, but the market’s not like that, obviously, you know, the market gives us money, takes it away, gives us money, takes it away, and sometimes we go to work in the market for months on end and we don’t make any money, the market doesn’t pay us, uh, and we, we have to learn to be okay with that because we have to keep doing it so that eventually we can come out the other side and go on to new equity hires.

And this is one of the powerful things about backtesting, right? If you didn’t backtest your strategy, how would you know that there could be this many months between, from one equity high to the next? You, you wouldn’t. You’d be getting, you know, five or 10 months in thinking, Oh, this is not working. You know, I’m not making money.

I, you know, maybe I should do some, maybe I should go get a job. Maybe I should do something else. But if you test your strategy, you know, what’s, what’s normal, what’s possible, what’s happened in the past. And that’s really powerful knowledge. So we’ve got to be patient and be willing to sit through flat spots and draw down.

Um, I also looked at the distribution of trades, right? So this is a histogram plot of how often or how many trades there were in the backtest in each of these different buckets. And this is a mean reversion strategy. So most of the trades are in the plus 5 to 10 percent profit bucket, right? There’s a few trades in the minus 45 percent bucket.

And we should look at this and go, okay, every now and then there’s going to be a trade That cuts in half, where we have a 50 percent loss or more, and we need to be prepared for that. We need to accept that that’s real. We need to accept that, you know, with enough time, that’s going to happen to us, right?

And so, you know, we, we, uh, we need to position size and manage our [01:09:00] risk accordingly. So we don’t bet the farm on each trade. We don’t use a little leverage because if one of these bad trades came along, it’s going to, going to wipe you out. But if your size is small, it doesn’t matter. Um, Oh, this one’s interesting.

I think this is the last one. It shows the time in trade, where this, this column here is one day in trade, all the way up to 10, 11, 12, uh, 13 days in trade. Versus profit. So with Mean Reversion, the most of our profits come from very quick trades. And then the trades that drag on for longer and longer tend to be losing trades because they haven’t bounced, they’re just dribbling down.

And so often with a mean aversion strategy, it’s really useful to have a time based exit that just says if it hasn’t bounced after 5 days or 10 days or 12 days, just get out because it’s, you know, it’s not going to bounce. The signal is passed. Uh, we now need to just, you know, cut our loss and move on and go to the next trade.

Yeah. So a few good lessons out of backtesting this strategy, which I think are really powerful. Um, I do have the entire rules for the strategy. I just didn’t want to, as I said, I don’t want to burden the whole conversation with, you know, this indicator and that indicator. You can scan the QR code and, um, and get, uh, the complete code fully, um, fully coded for you in, um, Amibroker formula language so you can backtest it for yourself and play with it.

So I think that hopefully that’s useful anyway for the, for the group.

Rayner Teo: Yep. It is. And I also put it in the, uh, the link in the description below the video. So people who, uh, don’t have the QR code or whatsoever, just go to the description. You should be able to find the link to access the, uh, the rules. Yeah.

Adrian Reid: Brilliant. So, I mean, that’s the strategy I thought I’d share. What do you think? Uh, questions, comments?

Rayner Teo: Yeah, so that was very insightful. Thank you for that, Adrian, and definitely a lot of, uh, quite a bit of preparation on your part, right? To actually deliver that short presentation. So, thank you for that.

Uh, question, yeah, question that comes to mind, it’s, uh, Oh, just one point to add, right, where you mentioned earlier that some of the best trades are the most uncomfortable trades. And I really can relate to that. I remember Covid, stock market dropped 30 percent and then one of my momentum strategies says it’s time to long because the v shape recovery was very fast.

Gosh, I didn’t want to click the buy button, but hey, guess what? System says buy. Okay, I’ll just buy just before the all time highs where you know, who knows, it could double top and goes back down lower. It bloody paid off, man, I’m sure you know, right? Just, we’re not, so yeah, so I can really relate to that.

I think even for discretionary traders, I’m not sure how discretionary traders, you guys can take into account the uncomfortable feeling that you have, but if you maybe journal your trades, you realize times where you feel the most uncomfortable, those are usually where your trades really do pretty darn well in that circumstance of your feeling.

So that was a very good point that, you know, click with me. Yeah.

Adrian Reid: My solution to that is automation. You know, I, I, um, I know myself enough to know that my emotions will get in the way if I let them. And so, uh, I’ve, I’ve found a lot of benefit in just automating all of my strategies. The capital allocation is automated and, um, it just runs and I [01:12:00] monitor everything.

So monitoring is far easier than executing, right? And so, you know, I’ve basically got myself out of the way. And, uh, I develop strategies, I plug them in, and then I monitor them, and that, that helps a lot too.

Rayner Teo: Speaking of automation, maybe could you give me an overview of how the automation work? Because I think that

Adrian Reid: you, you

Rayner Teo: just a few clicks a day and your system just kind of like run on its own.

Did I get it right?

Adrian Reid: Well, no, not even a few clicks. It’s, um, it’s fully, fully automated. So the way our, um, we, we developed our, um, our API and automation engine. So it replicates what we would, what I would do, right? So the automation, um, uh, application will update the data, open Amibroker, run the backtest.

Find the signals, talk to interactive brokers, find what trades I’ve got on, place the exits, size the entries, place the entries, report back, um, what trades it took and what the current positions are, and then close down Amibroker and turn off. So the whole thing happens and it will look at the position, the, um, the account balance in, uh, the net liquidity and interactive brokers.

And it applies the capital allocation percentages to all of the different strategies and then automatically does the sizing and everything. So everything I previously did on the spreadsheet, it does. And the great thing about that is I can now diversify far more broadly than I would want to if I was doing it manually.

Because I don’t want to do so much work, you know, I’m, I’m a little bit lazy. It’s not that I’m lazy. It’s just that I’ve got other things to do, you know, I prefer to talk about trading than to click buttons and place trades. That’s kind of boring. You know, I like to develop systems. I like to work with traders.

And so I spend a lot of time doing that. I don’t really like to spend a lot of time just placing trades. I rather the automation does it. Um, the other thing is I found that, you know, as your account grows, uh, I, I became more and more concerned about, um, you know, risk, uh, like external events, power failure, internet failure.

Um, I got locked, get locked out of the house, you know, I’m away on holidays, my laptop gets stolen. These sorts of things start to become very troubling. And it all really came home to me one day when I, um, this was just before I went live with my automation. I pulled up at the house, pressed the garage door opener, nothing happened.

Power’s out. Couldn’t get into the house. Computer’s in the house. Laptop’s in the house. It’s like, okay, I haven’t done my trading for today. This is a problem, right? And so, um, it’s like, clearly I need a better plan. So the first plan was to have a key instead of a garage door opener. So I implemented that plan straight away.

But then beyond that, it’s like, well, clearly things can go wrong. I need to, um, make my trading a bit more robust. So I put it on a VPS, virtual private server in [01:15:00] the cloud, all of the software is up there, always on. backup power, backup internet, and it will run whether I have access or not, whether I’m in Australia or Bali or Africa.

Rayner Teo: Nice. It’s like a ATM machine that just keeps printing money, right? Ah,

Adrian Reid: look, if only that was true, right? Yeah. I mean, if, if only that were true, I, it’s not the magic plug into algo and get rich. Like, you know, obviously, you know, tongue in It’s, it’s not, it’s not like that because you have to monitor it. You know, automate, Kevin Davey, who, um, you know, I’m sure many of your listeners know, he, he says, um, automated trading does not mean unattended trading.

And I think that’s a really great saying, right? We have to monitor it to make sure it’s working. We have to check the trades are executing right. We have to stay, um, on top of the performance of our strategies to make sure they’re still working, nothing’s going wrong, you know, the drawdown isn’t too big.

So we have to be attentive. Anyone who tries to sell you a plug in algo where you just say, plug it in, put your money there, you’ll get rich. That’s a scam. That’s not real. Obviously, um, automation just makes it easier to have discipline and easier to be consistent. And I think that’s key. And it also unlocks a level of diversification, which is very, very hard to achieve if you trade manually.

Rayner Teo: And from what I’m hearing, there’s this automation engine you mentioned. It’s kind of like a robot that replicates what you have done. You would click this, open this file, calculate position size manually on Excel. It kind of like does all that for you. Automatically, that particular software, whatever you call it.

Adrian Reid: Yeah, yeah. So it’s, it’s, it’s a, it’s a Python program. It’s been custom developed to do basically all of those steps. You know, it’s Amibroker. It updates Norgate. It refreshes all of the watch lists and everything. Opens the, um, the batch file. It has all of the systems in it. Runs them, gets the results, does all the calculations, everything.

Yeah.

Rayner Teo: And because you trade like multiple systems across different time zones, you need to update your Norgate at different times of the day as well, I’m guessing. Oh yeah, absolutely.

Adrian Reid: Yeah,

Rayner Teo: yeah.

Adrian Reid: Yeah, so it will run, it’ll run the Norgate update before each system that it runs to make sure it’s got the most recent data.

It’ll also update the Metastock data. And, um, and run that. So I’ve downloaded for the Hong Kong, which I use Metastop for, um, and it’ll pull that into the Amibroker database. So yeah, basically we’ve developed it to, um, to automate all of the steps that a systematic trader with Amibroker and Interactive Brokers, um, would, would do all of the steps that we would have to take.

Rayner Teo: Nice. Because right now I. I’m not automated. I’m still like, I have to spend like five minutes a day doing that clicking. So whenever I’m overseas, I got to say, darling, what’s the time? I’ve got to be there to do my clicking, right? At the hotel, you know, wifi, I need all this. Yeah. We had this

Adrian Reid: problem. We had this problem, right?

Um, and you know, my wife tells this story because my wife is involved in our business as well, she’s, [01:18:00] um. It does a lot of the psychology coaching. She’s a high performance coach, but anyway, she, uh, brought us a weekend away for my birthday one year and we were driving and I was like, um, I’ve got to do my trading.

Are we almost there? Oh no. It’s like so far. It was a surprise. Right. And I said, okay, I can wait. Is there wifi? Oh, I don’t know. Didn’t check. It’s like, well, Cause it was a long weekend. It was Friday. Right. Um, and. Ended up being no wifi. So it’s okay. Well, I’ll attach my computer to my phone. I’ve sort of got a cell phone signal.

Um, you know, that sort of thing was, was horrible because, you know, I’ve also, I’ve also been driving down the freeway, not driving, but in the passenger seats. Like, I got to do my trading. Cause we’re like, we’re not there yet. We’re late. We’re, we’re late. Traffic. So, you know, cell phone signal, laptop, trying to get it working.

I mean, it’s just, I mean, that’s not the way to run a trading business, right? So, um, yeah, we had a similar thing, but now automated, right? Last year, my son and I went to Africa. We climbed Mount Kilimanjaro together and. I didn’t even take a laptop. I just took my phone and the VPS in the cloud runs the trading.

I’ll get, you know, local cell coverage. I just log into my VPS on my phone and check everything’s working. I get the email notification. So I was away for a couple of weeks, didn’t even have a laptop.

Rayner Teo: It’s amazing. Wow.

Adrian Reid: Yeah. I mean, it’s a different level. It’s just, I mean, I think she loves automation more than I do because now, you know, we don’t have to rush back from the beach in the morning.

We go out for breakfast very often down at the beach. And, um, I used to have to rush home to make sure that my trades were going in right and everything. Don’t have to do that now. And, um, we go away. Don’t have to worry about it. It’s I resisted for a long time. It’s like, oh, my trading only takes five minutes a day.

Like, why do I need to automate? It’s only five minutes. But it’s every single day. But it’s every single day, exactly, right? And so the, um, the automation, honestly, I say to my students, it’s life changing. Like it really is. And it’s not because it makes you way more money. Although it does help because it reduces mistakes.

But it just, you know, that, that worry like, oh, my laptop’s not starting up. Or, oh, I’m overseas. Or, oh, well, I have internet. Or, oh, I’m stuck in traffic. You know, all of that goes away, which is, whoa, that’s next level.

Rayner Teo: Yep. Next level. And just to touch a little bit about risk management before we, we know we conclude today’s session.

So, um, you know, you trade multiple trading systems across different markets. So how do you then manage this capital allocation across these different markets and systems?

Adrian Reid: Yeah. Solid question. I think it’s really important. Um, cause the, it’s a complicated decision, right? How much money do I put into each [01:21:00] system?

How much risk do I take on each trade? So the way I do it is I, I let the numbers tell me. So I run a back test for all of my strategies, and then I have a model which pulls all of the equity curves together in different weightings. And so I can say, okay, let’s give this one 5%, this one 10%, this one 1%, this one 15%, and see how they would combine together.

And that model takes into account. returns, but also exposure. So what you can do is say, okay, if I have 50 percent this strategy and 50 percent that strategy, you can say, all right, how much money would I have made? But also you see, oh, they don’t use their money at the same time. So there’s a lot of cash sitting around just wasted.

So I can add another strategy that uses cash when these strategies don’t use cash. And I can give that a bit of a waiting and you can, you can play with the capital allocations to find the best combination that meets your objectives. So I do this, um, Amibroker can’t do that. So I do this in, um, in Excel.

There is software that can do it. So for example, in Realtest, you can combine multiple systems together. Um, but you know, I’ve got a lot of legacy in Amibroker and it’s all working. So I’m, I’m, I’m using that primarily. So, um, yeah, I’ll, I’ll, I’ll combine the different systems. And what’s interesting is it’ll often be surprising when you’ll find, oh, this strategy adds a lot of value, but it didn’t look like a very good strategy.

Like my short, you know, we talked about Slippery Dip earlier, low returns, high drawdown, doesn’t look very good in isolation. But because of the negative correlation, you can see, oh, it should have quite a high weighting, quite a high capital allocation. Compared to if I just add another trend following system, that would have quite a low capital allocation.

And, uh, and, and the, the model will tell you that.

Rayner Teo: And when do you decide to restock trading a trading system?

Adrian Reid: Yeah, I mean, again, that’s probably one of the biggest challenges that systematic traders have is when do I turn it off? Um, and the best way, the best way I found to have that is to have absolute rules going when you start up a strategy.

All right, I’m going to turn this off if this, this or this happens. Um, a lot of people don’t have that. So what I will also do is monitor a system on a very regular basis. So I’ll run a backtest of all of my strategies. So I have a batch file in Amibroker. That runs 57 strategies, so it’ll backtest all of them.

I don’t trade them all, but I monitor them all, right? And so it’ll spit out the equity curves of all of those strategies, and I can quickly look through and say, Okay, how are they all performing? I can look at the recent performance stats. And if the drawdown is getting beyond what is historically normal, I’ll have a really close look at it.

If it’s had a lot of losing trades in a row, I’ll have a really close look at it. If the average profit per trade is dropping compared to the [01:24:00] original backtest, I’ll have a close look at it. Um, so basically on a regular basis, I’m, I’m investigating, is this system still good? And then I’ll look to turn it off if it’s not.

Most of the time it’s just a, yep, it’s okay, yep, it’s okay, it’s ticked the box. Every now and then I’ll look a little deeper and then every now and then I’ll turn something off. Right. Got it. What’s, sorry, what’s, just one last thing. What’s interesting is the more strategies you have, the more diversified you are, the easier it is to turn something off.

If you have only one system as a trader, it’s like, Ooh, you know, it’s my only system. If I turn it off, I’m not a trader anymore. Right? If you have 20. Turning one off. You’re still a trader. It’s okay. That’s just a bad strategy. Just turn it off. Put a new one

Rayner Teo: in.

Adrian Reid: Many people cling to their one or two strategies they love, but that actually makes it much harder because what if one of those strategies stops performing well?

You need to get overly

Rayner Teo: attached to it then.

Adrian Reid: Yeah, right. Exactly.

Rayner Teo: It’s like having a 20 20 girlfriend and one leaves you, hey, you still got 19, man.

Adrian Reid: It’s not like that at all. That’s stressful. 20 systems is not stressful. 20 systems helps you sleep at night. So I’m gonna, I’m gonna, I’m gonna beg

Rayner Teo: to differ on that example.

And, and where do you get new trading ideas to, you know, to test on?

Adrian Reid: Yeah, um, Um, look a lot of places. I spend a lot of time looking at charts, um, just because I kind of debrief what’s happened in my trading. I look at different, um, trades in, in, um, from different systems and that stimulates ideas. I have a subscription to, um, to technical analysis of stocks and commodities.

So I kind of every now and then I’ll see some ideas in there. Um, I look at lots of trading websites. Um, I have spent a fair bit of time on your website. I look at, uh, uh, Kevin Davey. He’s a great example of, um, you know, good system developer. I really like his stuff. He trades futures. I trade stocks. But some of the ideas are transferable.

Um, so I look at competitors like other educators, other traders. Um, I look at Twitter. Uh, you know, a lot of people are just sharing ideas on Twitter. A lot of them are not good, but it stimulates ideas. Um, what else? Books. I’ve got a lot of, a lot of strategies from books over the years and a lot, you know, a lot of no good, like they used to work, but they don’t anymore, but that then sparks new ideas.

Um, I think the best one is, you know, looking at charts for yourself. Okay, what sort of move is happening on this chart? You know, how could I capture that? And could I capture that over and over again? And put, if I put that into a system, would there be enough positive moves to offset the negative moves?

Um, I really like the creativity of that process. Okay.

Rayner Teo: And we’re going to move on to the closing section now. And maybe this question is something that I’m curious about. What are some formative moments in your life? It doesn’t have to be [01:27:00] trading, right? So what comes to mind?

Maybe I can talk a little bit first, right? While you have some time to think. So for me, I think one of my formative moments is, uh, In Singapore, all of us have to serve the army. So I was enlisted into, uh, commandos. But pretty brutal two years, but it taught me a lot about discipline. Taught me a lot about perseverance.

It taught me a lot about mind over matter. And basically equipped me with all the tricks to handle trading now today. So, I don’t know, looking back, maybe I was destined for this, right? So, so that was definitely one of my formative moments, right? During the two years. And during the two years, I hated every moment of it, but looking back right now, I’m glad I went through every moment of it.

Funny how life, you know, teaches us new things.

Adrian Reid: Yeah. Wow. That’s such a good one. And I’ve actually, you know, I’ve heard that from a few people that military experience has done that. I didn’t have, we don’t have military service in Australia. Um, look, a big one for me was my university studies. Um, I, I studied chemical engineering.

It’s not an easy course. Uh, in fact, there’s some subjects there that are incredibly difficult. And I saw a lot of people really struggle and the people that struggled didn’t ask for help and like I was pretty good at asking questions and putting my hand up and looking stupid in front of 300 people and on all of that, but I saw this big divide between the ones that learnt and and grew and the ones that really fell behind and struggled.

And I think observing that was, was one big thing. And, you know, when I’m working with trading students now at the beginning, before I even accept someone as a student, one of the most important things is I, I, I make sure they, they have to be willing to ask questions. They have to be willing to look dumb.

Like they have to be willing to admit they don’t know because you’ll never make it if you don’t. And I think that’s true of many things in life, right? The people that succeed are the ones that are willing to keep going and ask and ask and ask and ask until they get it. The other, the other part of university, which really got me.

Is, um, I thought I was pretty smart, right? I did pretty well at school and I, I got into a good course. I got a scholarship and all of that, and that was great. But I got in and it’s like, all of a sudden I’m not, I wasn’t the best anymore. You know, there were people who are way smarter than me doing the same course as me.

I was thinking, Oh, it’s a bit confronting, right? I thought I was pretty clever. Um, and so I sort of accepted that and I went through the first couple of years. I was doing well. I was trying to do well, but then I set myself a real goal. Like a really clear goal and it was absolute. So my goal was. I want to get the university medal, which means I have to come first in the course, and not just first in the course, but do really well.

And, um, I basically decided that at the end of second year of uni in a four year course. [01:30:00] And, um, at that time, I was nowhere near it. There were people are getting way better grades than me. And even though I was doing well, um, but that clear, absolute goal, it was absolutely measurable. I was either going to get it or I didn’t.

There was no in between, there was no shades of grey and it was time bound, obviously, you know, at the end of the course I have to be first, right? And, um, so that was a really great goal, it was a really big goal and I really wanted it. I don’t know why I wanted it, like it doesn’t really mean that much, but I just decided that’s what I wanted and that was my thing and that’s what I’m going for.

And I didn’t even tell anyone, right? I just decided internally with conviction that that’s what I wanted. And, you know, long story short, with a goal that big, that clear, with conviction, things align around it. And I did the work, I found the support, I got the grades, I made, you know, I achieved the goal.

And that was like, oh wow, I did that. And I only did that because I decided two years earlier, I was going to do that. And this is relevant for traders, right? Because a lot of people come to the, you know, market going, Oh, you know, I’d like to make a bit of extra money. I’d like to, you know, get some extra income on the side, or, you know, I kind of want to retire early, but they’re all weak goals.

There’s no conviction. Maybe I should trade. I should learn to trade. You know, that’s a, that’s a weak intention. It’s not even a goal. The people that succeed have absolute firmly held goals that are crystal clear, held with conviction, and they run after them. And when I, that was the, That was the first really big goal that I achieved.

And when I was like, oh, it worked right? It’s like, hmm. It was kind of unexpected even. And I, I, I think that’s the power of having really good goals and most people don’t have them. And I think that’s a shame because that means most people are underachieving what they’re, you know, underachieving their potential.

Rayner Teo: And I believe that when you reach that goal of your, so it kind of like open up a lot of opportunities to you. ’cause you now you have the mindset of. What can’t I achieve? What can’t stop me? You just keep, you know, hitting all the different goals that you’ve set for yourself since you know you’ve achieved it before.

Yeah. What’s next? Yeah.

Adrian Reid: Exactly, right? Yeah, that’s really

Rayner Teo: powerful.

Adrian Reid: That, having that, that optimism about life is if I want something, I can, I can go do it, you know, as opposed to, oh, you know, I’ve never really achieved anything. Yeah.

Rayner Teo: And you’ve proven to yourself that you can do it based on your Exactly.

So-called back test. Yeah, back test.

Adrian Reid: That’s right. Absolutely right. So I think, I think that’s, that’s, that was really important to me. Not, not so much achieving the thing. Like that was great. Right. A good in the moment. But the lesson from that, that was what was powerful.

Rayner Teo: And before we sum up, is there anything that you know, you’d like to add [01:33:00] that you didn’t have a chance to talk about earlier?

Adrian Reid: Yeah, we haven’t talked about the typical trader’s journey. You know, most people come to the markets. And they go, Oh yeah, I’ll learn about stocks. And they read some books and they do some stuff and they trade a little bit. They take some tips, they do some things. And typically it takes three to five years for someone to figure it out if they’re lucky.

And most people never figure it out and they give up, but some people do, but it takes long. That learning journey is really costly because that’s three to five years of lost compounding and in 10 years time, in 20 years time, that’s worth a fortune. If you could just have those three to five years back because you learned quickly and you, you got to mastery by following someone who knew how to do it, then that’s worth, you know, millions.

I worked out how much my three year learning journey cost me and it was millions. Yeah. If I’d have just. You know, learn quicker and then start at the compounding at the beginning, uh, I would be so much better off now. I mean, I’m all right. I’m doing okay, but you know, so much better. And so I really want to encourage people to throw themselves into it, to find someone who can teach you to, um, to shorten the learning curve, um, and go for it, like actually put in the work.

Don’t tinker because that, you know, that’s a, that’s a decision that will change your life. All right. And where can the audience find and connect with you? Um, yeah, anyone who wants to talk to me, I mean, I think the best thing to do, we talked about that system today. Go to enlightened stock training.com/free.

Um, put in your details there. You’ll get an email from me and then we can start up a conversation. You’ll also get all of the details for that system and a bunch of other goodies, which is kind of cool. Um, so enlightened stock trading.com is my website. I’ve got a lot of trading articles, videos and everything on there.

Um, Facebook Enlightened Stock Trading. Um, YouTube and Twitter, same thing. So, um, basically I’m, I’m, I’m everywhere. If you Google Adrian Reid, Enlightened Stock Trading, you’ll definitely find me. So, um, I, you know, I’m very happy to receive emails with, um, you know, questions, comments, challenges, all of those things.

So, uh, we’d love to hear from the, from the audience.

Rayner Teo: Awesome. And I’ll put your social media profile and website in the description somewhere below the video, right? In case the audience want to find the real Adrian. Nowadays, so many scammers and imports. Yeah. You know,

Adrian Reid: I have someone whose job every month is to look for the scammers and report them and have them removed.

Like literally this is a standing recurring task for someone in my team. Um, so be careful out there. We’ll have the real links. Uh, I’ll give them to you so you can put the real links underneath. There’s not many scammers because we’re pretty good at taking them down, but every now and then one, one creeps through.

So, yeah, okay.

Rayner Teo: Thank you so much for your time, Adrian. I appreciate you. Happy to have you on the show. It was a pleasure, right? Speaking with you. [01:36:00]

Adrian Reid: Absolute pleasure. Thanks so much for having me.