The Quant Revealed
Wednesday, 19th November 2014
By Kris Sayce
- More growth to come
- Inside the Quant Part III
I’ll hand over the lion’s share of today’s Port Phillip Insider to Greg Canavan and Jason McIntosh.
Today is part three of their interview. In this episode, Jason explains how a potentially disastrous trade turned into one of his biggest wins…simply by following his trading rules.
But before I hand over to Greg and Jason, a quick look at the markets…
More growth to come
As I explained on Monday, the oil price will continue to drop as long as OPEC sends the message that it’s in no hurry to cut production levels.
Today, the oil price is back below US$75 per barrel. It’s back roughly where it was before Friday’s bounce.
The vote in the US Senate today not to approve the Keystone XL pipeline from Canada to the Gulf Coast didn’t help things. But even building the pipeline wouldn’t help matters.
In fact, it would probably embolden OPEC to drive the oil price down further. Remember that OPEC members produce around 40 million barrels per day out of the total world supply of around 95 million barrels per day.
So it’s a mistake to think that OPEC is irrelevant. OPEC was merely quiet when it wanted high oil prices. Now it wants to control the supply rather than the price.
That’s why the price has fallen. And that’s why the price will continue to fall.
As for stocks, it was a reasonably good night in the US. The Dow Jones Industrial Average and S&P 500 both closed at new all-time record highs.
The NASDAQ closed at its highest closing price for the year, and its highest level since the 2000 dot-com crash.
Aussie stocks, on the other hand, haven’t done so well. The last three mornings the commentary has suggested that the Aussie market should open higher…except it hasn’t.
Aussie stocks continue to fall since the end of the recent rally in early November.
Is it now time to panic? No. Stocks never rise in a straight line. At the moment, the focus is back on China, and some of the concerns surrounding its credit markets.
As the Financial Times reported yesterday:
‘In some ways, China today resembles Japan in the early to mid-nineties or the US in 2007 to 2008 on the eve of their respective financial crises, both triggered by overvalued property. It is not only that property companies are huge borrowers (in the case of China both domestically and in the offshore US dollar high yield bond market), it is that many other borrowers in China can only take out loans if they have property to serve as collateral.’
Is China a huge bubble waiting to burst?
That’s what the markets are worried about right now. As I see it, all growing economies go through big growth spurts. It’s hard to maintain that growth without faltering.
China is faltering. But does that change the long term dynamics? Not a bit. China is still on track to more than double the size of its economy within 10 years…even at a growth rate slower than today’s.
Also remember that China’s stock market, the CSI 300, is still down 55% from 2007. That tells you investors have already built most of the bad news into China’s stocks.
Folks may be looking for China to crash, but I’m sticking with what I can see, and with what emerging markets analyst Ken Wangdong tells me about his recent visit to China.
China may have grown a lot over the past two decades, but there is plenty of more growth to come.
If you don’t subscribe to Ken’s New Frontier Investor service yet, you can check out the details here.
Now over to Greg Canavan, and quant trader Jason McIntosh…
Inside the Quant Part III
Greg: Before we get to know how your system works, can you tell us a little bit about some of your best and worst trades?
Jason: There are a lot of trades I could pull out and talk about, which I think would offer some good insights. But the best two involve the gold market. Two trades which actually come together quite well.
I’ll start with the worst. We’re going back to 1999. By this stage I was a senior trader at Bankers Trust. I’d been watching the gold market for some time. It had been a bear market. It was probably sometime around late 1998 that it turned down and had been in a pretty consistent decline.
For the last few months, it started to stabilise, and looked like it was forming a good base. The sentiment around gold at the time was extremely negative. For me, those are always good ingredients for a profitable opportunity. Negativity, and a base. But, in my experience, it’s always best to wait for some upward momentum.
I have always found that pre-empting an upward break can be quite an expensive exercise. I waited, and waited, and waited some more. Finally we got some movement. The gold price started to push up. For a couple of nights running it moved up quite nicely, breaking a couple of levels, and the move I was waiting for happened in overnight trade. I think it might have been in the New York time zone. I got the call in the middle of the night, because I got my order in the market. The voice says, ‘OK Jason, you’re filled on your gold order.’ I thought, ‘OK great I’m in.’
I can’t remember how much it was. But I recall thinking that I’d just bought more gold than some smaller miners actually produce in a year. It was a chunky position. So I went in the next day, the price was up a little bit more…it’s always nice when your trade gets off…the barriers open and off it goes, and so that was all good.
But, the good part of that didn’t last too long. The next afternoon early London time, there was an announcement. The Bank of England comes out, and says they’re going to sell a big chunk of their gold reserve. So, I’m long gold, and the Bank of England is selling. Not a good combination! The market gapped lower. It was an absolute disaster.
I had my stop loss in the market. You’ve always got to have a stop in the market, your exit point, but the problem I had was the market just gapped straight through it, there’s no trade there. So my deal comes back and I’ve lost something like three times what I was expecting to lose on the trade. This was a big trade in the first place. Now I’m sitting there with by far my worst trade of the year, the most expensive and biggest loss. The move down was so violent and so fast, it cracked through all the support and had now broken down.
Sitting there, and looking at it, I’m going, well ‘I’ve been waiting for months to buy it, but now it’s broken down, and I’ve got a rule for this, if the price breaks down, I need to sell it.’ I had a choice. I didn’t have very long to make it, because the markets was moving. I could either go away, and just lick my wounds so to speak, regroup myself, and get ready to come back and look at it with fresh eyes tomorrow, or I could take the signal. I could pull the trigger, and do what my rules say to do and sell.
And that’s what I did. I turned around and I sold. Within the space of only a few minutes, I had sold two big chunks of gold. The first was an exit from a long position which didn’t work, and the second was a new short position. So, I was going to make money, if the price continued to fall.
Fall it did…for another eight weeks. It was a consistent decline, and I made a lot of money there. I made back my initial loss, many times over. I eventually bought the position back on a small upward bounce about a week before it made its final low around $250 an ounce. That’s where I was able to close the position.
It was the best of days, and the worst of days. I got my worst trade, and my best trade for that year. Both bookended together, and it really shows the power of having a disciplined and consistent approach to your rules.
Had I left the playing field and not engaged with what the rules were telling me, I would have missed my biggest trade of the year.
But I was disciplined, I was consistent with the rules. I took the trade, and I made the money. This is all part of what goes into my trading systems.
Greg: How did quantitative analysis play a part in these trades?
Jason: These trades actually predate my move to quantitative trading. But the thing is, all the lessons and the rules from trades like that are deeply embedded into every system I design. Before you can be a good quantitative analyst, you’ve first got to be a good trader. By doing that, you learn how markets work, you get a feel for the market, you understand what the patterns mean, what happens when patterns break down and suddenly reverse — like that gold trade.
Through having that knowledge, that background, it better enables you to build a quantitative system which is tradeable in real time.
Greg: You’ve been trading these various markets for more than 20 years. In your experience, what are the most common trading mistakes made by novices and professionals alike?
Jason: That’s easy. That is cutting winners short, and running losses. It’s basically the opposite of what you’re meant to do. You see, people get really worried that a small profit is going to disappear. They see it’s up 10%, and they’re inclined to take it.
There is this silly saying, ‘You never go broke making a profit.’ Really it’s just not the way to maximise your trading potential. In my experience, you make the really big money when you get the stock that doubles, triples, or more. That is where you really maximise your gains. The problem is, if you’re selling out with a 10% profit, how are you going to get that? It just doesn’t work. You really have to have the discipline to ride those trends, and not be afraid to let a 10% profit disappear and turn into a 2% loss. Take the small loss, it’s not a big deal. You’re going to make your money by getting the big wins, by getting the big gains. That’s where it’s all made.
On the loss side…well, a lot of people don’t like to take a loss. And again I hear another silly statement, that, ‘Look a loss isn’t real until you take it.’ Until you lock in a loss, it hasn’t actually happened. Frankly that’s just a load of nonsense. Your position is worth what it’s worth. If it’s fallen by 50%, you’ve lost 50% of your money. It’s as simple as that.
You need to cut these losses at a relatively early stage. You have got to give the market room to move. You are going to have losses, that’s the nature of the game. But you want to limit these losses to a reasonable, predefined amount, not this, ‘Look we will just hold a little bit longer, maybe it will come good.’
That’s how you end up with a 70%, 80% or a bowled-at-the-stumps complete wipe out — by holding on to stocks which you should exit. This is what Quant Trader does, it really helps you turn this around. It gives you the discipline and the consistency to run your profits — because you follow the instructions of the systems. It’s going to run profits and it’s going to cut losses.
If you’ve ever had trouble with letting profits run and cutting losses, this system is going to help you turn that around in a way that will help you make the money.
Greg: Tell us how your system will help prevent people from making some of these common mistakes.
Jason: I think it really helps give traders the discipline to do what you’re supposed to do. Do what you should do. You get that confidence from knowing that the quantitative method that the system is using has worked many times in the past. I know something has worked well in the past, so I’m going to be confident taking those signals in the future.
It’s all about building that confidence and the discipline to do what needs to be done, to maximise your chances of making money in the market. I think the system, the way it’s put together, the way it gives signals and tracks exit points, will really help people do that.
Greg: How will Quant Trader generate recommendations? How effective is it? What have you done to prove it?
Jason: This is the beauty of a fully systematic approach, in that, you’re able to do what we call back-testing. Now, an algorithmic system is basically a collection of computer code working together. What that allows us to do, is put historical data through those algorithms. This means we can find out how they would have reacted, what signals they would have produced in previous times. So we can see the effectiveness of the strategy.
I’ve got ASX data going back to 1993. That’s 21 years’ worth of data. I’ve also included delisted stocks, stocks which have left the boards in that time. To give us the most robust result we can get, we need to include pretty much everything.
We want to recreate, as best we can, the way the market was at a previous point in time. One of the things you can do with back-testing is stress test those algorithms. By that I mean, we’re putting it through a whole range of conditions. Say from 1993, for instance, we have the recovery from the 1980s recession. We have the dot-com boom, the dot-com crash. We had the recovery of value stocks in the early 2000s. We have the mining boom, we have the GFC, the recovery from the GFC — there’s a whole lot of conditions in there.
You’ve got markets going, up, down sideways, you’ve got volatility, and smooth trending…it’s all there. The idea of back-testing is we want to see that our method works consistently across a whole range of different conditions. And not just with one or two stocks. You want to see it work with a large population. That’s why we brought in pretty much every ordinary share in the ASX, since 1993.
It’s through doing this, that we’re able to build confidence around our method. Confidence in seeing that this worked in the past is an indication that we have a robust and effective way of approaching the markets in the future. There’s no guarantee that the markets will do in the future what back-testing said they did over the last 20 years, but it’s the best way that we can go forward using what’s happened in the past.
Greg: Back-testing is key to the development of any successful trading system or trading software package. Why is back-testing even more crucial when it comes to quantitative analysis?
Jason: Well it’s how we test our ideas. If you have a method, you need a way of testing it. The best way we have of doing that is by using data from the past, and putting it through our algorithms. If we don’t do that, we can’t gain any insight into how good a system is. Unless you want to go out and spend 10 years trading, and then come back saying ‘it worked, it didn’t work’.
The best way to do it is you get your past data, and back-test it. The important thing is, it has to be done well. For instance, if you give me any stock in the ASX over the last 12 months, I’m sure I can design something which makes it look like there’s a really good system there. The problem is, if you get another stock and put it in there and overlay it with the same system, it might not work. That’s because the system was designed for one stock over one period.
Good back-testing won’t just look at one stock over one period. It will look at a large period with lots of stocks. That way you can gain confidence that your method works a lot of times, in a lot of environments, with a lot of trading instruments. That’s what you really need to see to build confidence and robustness within the system.
Greg: Your system contains a lot of proprietary information, but can you tell us a little bit about how the filters work and combine to generate the trading signals?
Jason: Yeah, the filters are a really important part of the system. I’ll tell you about the primary filter that we use in the system. It’s called a moving average (MA) crossover system. Here is a chart of it.
What you see on this chart is a broad upward trend, and underneath that trend you have a couple of lines. What I use in the system is a 50 day moving average, and a 100 day moving average. They aren’t magic numbers, they just happen to work for what I’m trying to achieve. Now, a moving average is simply an average of the closing price, over a set period of time.
In this case, let’s say 50 days. What I want to see is the short term moving average, the 50 day MA cross over the hundred day. Once that happens, we say, ‘Well that’s the conditions necessary for an upward trend.’ When the system analyses that, it will then move that stock onto the potential buy list.
There are still a whole lot of other filters it has got to go through, but that’s our primary one. It separates stocks that are going down, from stocks that are going up. It’s a really important filter. It’s a bit like a rudder on a boat — the boat will only go in the direction of the rudder. In the same way, the system will only signal in the direction that the moving averages are heading. I think a mistake a lot of traders make is that they really look at this sort of filter and say, ‘Look it’s a really simple filter of moving averages, there’s nothing too high tech in this.’
Instead lots of people are looking to pick the top, or trying to buy the bottom. The problem is they’re often swimming against the tide. In my experience the best way to make money in the market is to trade with the trend. That is what the moving average is. It shows you the trend. That’s what the trading system does. It identifies the trend and then goes accordingly.
Now another system, another filter that we use within the system, is called a breakout system. Here’s another chart.
Here you’ll see there’s a stock price, and you’ll see there’s a line above the price. That line above the price is the 70 day high for that particular stock. What we want to do is buy when the stock breaks to a 70 day high. Again 70 days is no magic number. You could use a 20 day, 50 day, or a 100 day…it doesn’t really matter. It’s just the fact that we need to do something consistently, and 70 is a number which I happen to use in this system.
We buy on a breakout to a 70 day high. This stops us from buying dips during pullbacks. Who knows how big a dip’s going to be? It might dip 50%, and you buy on a 20% pullback, not a good deal. You want to buy into strength. People talk about buy low, sell high. Yeah, I know what they’re saying, but you want to buy into strength and sell into weakness. You are going with the tide, not trying to be too clever, not trying to fight it.
These are two ways that the system will analyse data, to come up with what it can calculate as the highest probability signals within the market.
Greg: If I start receiving and acting on the trades generated by Quant Trader, what can I expect results wise? What kind of edge will I have over regular traders?
Jason: Quant Trader is going to help you trade like a professional. A key objective of the system is to get on board the big winners. Let them run, and run, and run. That’s a key part of the system.
Another key aspect is to cut your losses in a consistent and calculated manner. This is really important. The system is all built around doing these two things.
Let’s talk about performance. I’ll give you an example of something. Let’s say we do a coin toss. It’s 50/50. Heads you win a dollar, tails you lose a dollar. Statistically, you’re going to come out even in the long range. You’re not going to make any money. You have no edge, it’s an even game.
Let’s change the rules a little bit. Let’s say, if it comes up heads, you win $2, if it comes up tails, you just lose a dollar. It’s still a 50/50 game, but now there’s a $2 payoff for a win, and only a $1 loss. What do you think? Would you play this game? Tell you what, I’d queue around the street, around the corner to play this game, and I would play all day long, as long as I could. Because statistically, it’s telling you that, over time, you can’t help but make a lot of money. The odds are in your favour. So Quant Trader, with statistical history through back-testing, is actually quite similar for this loaded coin toss.
We know through back-testing, for instance, with our long trades that a little over 50% of these make a profit. We know that the average profit on these trades is a bit over 30%. Now the losses, they average out at around 14%. We have this situation where basically, you’ve got a 50% chance, of a 2–to–1 pay off. That’s the sort of edge I’m looking for, when I’m looking at the trading system. I want something that statistically tells me that I have a strong chance of doing well over time if I follow those signals.
That’s what Quant Trader is doing. Now I need to point out that these are of course back-tested results, and they’re not a guarantee of what’s going to happen in the future. And I’m also dealing with averages. Any individual trade is going to be unique, and it may differ substantially from the average.
Nonetheless, in my eyes, there’s a very clear and present edge with trading with a system like this. This is the sort of edge I want to make available, and this is the sort of edge I want Port Phillip Publishing clients to benefit from.
Port Phillip Publishing is pleased to announce the launch of Quant Trader. This service is run by quant analyst and former Bankers Trust trader, Jason McIntosh.
To find out more about this groundbreaking new trading service (a first in Australia), click here for details…