Before I start, I want you to read this…
‘Have you read Hot Copper’s clients opinions about Algorithmic trading? I could not find one favourable word towards it. They said a few unfavourable words about it. Many of them want ASIC to look into the pricing.
‘Just last Friday I decided that I join you, now I am confused. Thank you for the info, and all that you care and understand.’
— Member Elizabeth
Many people think algorithmic trading is a strategy. This is a mistake. It’s actually a process. It uses a computer to follow a set of rules. You then use the output to place trades.
Algorithmic trading can apply to countless strategies. These range from ultra-short term high frequency systems, to ones that trade off monthly price data. They can be very different.
It’s difficult to give a specific response to Elizabeth’s email. Maybe the problem lies with a particular strategy…or perhaps there’s a dislike of computer generated signals. I simply don’t know.
Everyone is different. It’s OK not to like a certain way of trading. The very reason markets exist is because people have different points of view.
But I can tell you this. Algorithmic trading works for me — I’ve been using it for years.
Algorithmic trading has three big pluses in my view:
- Consistency and ease of use;
- The ability to cover many more stocks than I could manually, and;
- I can test ideas before putting my money on the line.
But not everyone sees it this way. As I said, a market needs different viewpoints.
One of the criticisms I hear involves back-testing. Some people don’t trust the results. And I can understand why — it’s easy to manipulate. I’ve seen some awful examples over the years.
I wrote a report about dodgy back-testing in November. The title is: Lying with statistics — are you being duped? Simply knowing what to look for can help you avoid this trap.
Others dislike the lack of fundamental analysis. They say values should underpin every trade.
Sure, pure algorithmic trading relies on share price history — this is how I trade. But that doesn’t mean you can’t overlay your own financial analysis. Some people do this with great success.
Another complaint is that algorithmic trading doesn’t work all the time. I agree. I’ve yet to see an approach that does. Every trading method goes through periods that aren’t suitable.
Elizabeth also mentions calls for ASIC to investigate pricing.
I believe she’s referring to potential price manipulation by high frequency trading firms. This can have implications for all traders — algorithmic or not. It’s an issue regulators are grappling with globally.
If you talk the talk…
I said earlier that algorithmic trading works for me.
You’ll probably accept this statement at face value. But some people will be sceptical. They’ll want to know how my own trading stacks up. There’s an expectation that I ‘walk the walk’.
And do you know what? That’s fair enough. I always want to know the track record of a person giving me advice. I don’t expect you to be any different.
I’m going to show you some results in a minute. These are for a system I’ve been trading with for the past eight months. This particular strategy has a lot in common with Quant Trader.
First, let me set the scene.
Cast your mind back to the start of October. Doom and gloom was everywhere. The markets were near their lows, and many people were bracing for a crash.
The title of the Quant Trader report that week was: Forget a crash: 16.3% returns are possible in October. The report’s aim was to put some perspective to all the negativity.
Now, I want to make one thing clear. This isn’t an ‘I told you so’ moment. I don’t do those. I know there’ll be many times when I’m wrong. I’m telling you this to make a point.
You see, four days earlier, I’d pushed the ‘go’ button on a new system. I did exactly what I told you to do on 2 October 2015 — ignore the gloom and follow the signals.
Let me tell you a bit about this system.
You’d find it very similar to Quant Trader. In fact, it’s identical in many respects. I’ve mostly made minor adjustment to suit my own situation.
The slight variations also help me avoid trading at the same time as you. I don’t want to be competing with you for a stock. In the event of an overlap, I simply trade the next day. You come first!
The biggest difference is to the exit strategy. I use time exits for unprofitable trades — like we discussed last week. The limit I set is 60 trading days.
The reason for time exits is capital efficiency. Put simply, I want to sell stocks that aren’t performing. This lets me get money into new opportunities faster.
Real time trading
OK, so here’s what I did.
I put $500,000 into a trading account. Then — just as you do with Quant Trader — I’ve been following the signals and managing my exits.
You may be interested to know how I set my trade size. The system allocates 2.5% of capital to each stock. So, on day one, my trade size was $12,500 (this allows for a portfolio of up to 40 stocks).
The advantage of this method is that it’s dynamic. It allows trade size to grow (or shrink) with my capital. Doing this also ensures my position sizing remains consistent.
Let me show you how it’s been going…
My profit, including dividends and costs, on 15 June 2016 was $72,850. — that’s an annualised gain of close to 20%. The system is comfortably beating the All Ordinaries.
You can see it’s not all smooth sailing — it never is. I have good and bad months. That’s the reality of trading. You need patience and discipline to stick it out during the down months.
This graph isn’t an exact replica of my portfolio (although it’s close). You see, this assumes I buy every trade on the open, and sell at the precise exit level.
But, as I’m sure you know, real life doesn’t exactly match a simulation. There’ve been times when I’ve been late to buy or sell. It happens to all of us!
So what about those time exits?
Well, back-testing suggests a lower win rate and more trades. This is proving to be true in live trading. My win rate for all open and closed trades is currently 42.5%.
Trade volume is also relatively high — there’ve been 80 entries in total. But I find this easy to manage. It averages out at eight buy orders per month.
Brokerage isn’t an issue in my situation. It only represents a tiny fraction of the profits. But, as I said last week, commissions will have a greater impact if you trade in $1,000 lots.
So that’s a bit of my story for you.
Algorithmic trading makes all this possible. It allows me to identify trades in stock and futures markets I’d otherwise miss — there are just too many possibilities to analyse manually.
I’ll let you judge for yourself. But in my view, there’s no better way to trade.
Until next week,
Editor, Quant Trader
Editor’s note: Are you falling short of your goals? Do you find it a struggle to consistently make good profits? Don’t worry, you’re not alone. The stock market can be a tough place to navigate on your own.
Here’s something you should do — check out Jason McIntosh’s Quant Trader advisory service. It’s a fully algorithmic trading system for ASX stocks. Quant Trader scans practically every company. It then tells you when to buy and sell. I can just about guarantee you’ve never heard of some of the stocks it identifies.
Try it. See if it makes sense to you. It could change the way you trade forever.