Could Algorithmic Trading Be For You?

Business charts and markets

I have a confession to make…

I’m always telling my kids to keep an open mind. I say there’s nothing to gain by closing yourself off to new ideas. Flexible thinking can lead to amazing opportunities.

But sometimes I struggle to hold true to my own words.

You see, I can also be a sceptic.

That’s right. There are times when I simply won’t listen. I’ll make an on the spot assessment and move on without a second thought.

Any ideas when that might be?

Well, it’s to do with the financial industry.

You see, I’m often sceptical when I hear claims of astonishing success. I’m talking about the type of success that could turn you into an overnight millionaire.

I recently saw a claim that made my eyes roll back. It was truly extraordinary. The promoter was saying that 50,000 of his clients had seen a 10-fold increase on their investments.

Now, I can’t say this isn’t true. I didn’t make further enquires.

But I do know this: trading is not an easy business.

The suggestion of so many people making 1,000% gains is beyond belief. Such a result would be over 100-times the annual average return of the Australian market.

I began my financial markets career back in 1991. And during that time, I’ve sat alongside some of the best traders in the business. These are smart and highly successful people.

And do you know what?

I can’t recall any of them ever coming close to a 10-fold gain.

You see, gains of this magnitude are a rarity. While these huge payoffs can and do happen, they’re not the easy pickings some people would have you believe.

So be open to new ideas. But be wary of seemingly outrageous claims.

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Many are sceptical of algorithmic trading

I occasionally get emails from people sceptical about algorithmic trading.

One of their concerns is back-testing. Some people simply don’t trust the results. They see what appears to be strong performance, and they wonder if it’s really true.

Others dislike what they believe is ‘black box’ trading. These people find it hard to follow a computer’s entry and exit signals — they’re uncomfortable not having a human’s input.

I can understand both objections. Everyone is different. And 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, and I’ve been using it for years.

This type of trading has three big plusses in my view:

  1. It consistently applies a strategy
  2. It quickly analyses thousands of stocks
  3. It lets you test ideas before putting money on the line

I’d describe algorithmic trading as an evolutionary step. The work I once did by hand is now done faster and more consistently by computer. It really has transformed the way I trade.

I said before, algorithmic trading works for me.

Now, you’ll probably accept this statement at face value. I also hope you’ll agree with the advantages that this type of trading brings.

But some people will still be sceptical.

It gets back to that old question: If it’s so good, why doesn’t he do it himself?

And that’s fair enough.

I always want to know the track record of people advising me. And I don’t expect you to be any different. It’s fair to expect that if I ‘talk the talk’, I ‘walk the walk’.

I’m going to show you some results in a minute. These are for a system I’ve been trading my own money with for the past three years. It’s a system very similar to Quant Trader.

But first, let me tell you a bit about it…

The system is identical to Quant Trader in most respects. It uses the same momentum strategies for entries. It also applies the same initial stop-loss, and a similar trailing stop.

A few algorithmic tweaks align the system to my needs. They also help me avoid trading at the same time as you. In the event of an overlap, I simply trade the next day. You come first!

The biggest difference is my exit strategy. I sell unprofitable trades after 60 days (even if they’re above the exit stop). This helps me move capital into new opportunities faster.

As I’ve said in the past, you could do something similar. You just need to remember the potential downside of time exits — a lower win rate and more trades.

Real results of algorithmic trading

OK, so here’s what I’ve been doing.

I put $500,000 into a new trading account back in September 2015. My aim was to build a real life track record using a system like Quant Trader.

You see, I don’t just talk about trading stocks. I actually do it myself. And there’s no better way to show you this than by having a dedicated ‘Quant Trader’ account.

Now, 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) in line with my capital. Doing this also ensures my position sizing remains consistent.

Let me show you how it’s been going:


MoneyMorning 07-11-18

[Click to open in a new window]

As of Friday 19 October, my profit (including dividends and costs) was $226,336 — that’s a total return of 45.3%, or 14.8% annually. Excluding dividends, the annual rate is 10.5%.

By comparison, the All Ordinaries is averaging 5.7% per annum for the same period. My return (excluding dividends) is beating the market by a margin of 84.2%.

But it hasn’t been all smooth sailing — it never is.

Take the market’s current sell-off for instance. My portfolio’s value has fallen by $45,083 since 4 October. That’s the reality of trading — stocks don’t move higher in a straight line.

The key is to have patience and discipline during the down periods. The traders most likely to come out the other side are the ones who believe in their process, and stick to their plan.

My account’s growth since March 2017 is a case in point. The $146,597 gain wouldn’t have been possible if I’d panicked and sold-up during the previous downturn.

And remember, this isn’t a simulation. The graph closely tracks my actual portfolio.

So what are some of my trading stats?

Well, my win rate for all open and closed trades is currently 42.1%. I don’t pay much attention to this figure. The only number that matters to me is the overall profit or loss.

I’ve had a total of 266 entries over the three years. The time exit strategy makes this higher than it could have been, but it still only averages to about seven buy orders per month.

Brokerage isn’t an issue in my situation. It only represents a tiny fraction of each trade. But commissions will have a greater impact if you trade in $1,000 lots.

My biggest profit is a gain of 199.1% in Kidman Resources [ASX:KDR]. And I own four stocks that are up by over 100%, plus two that are ahead more than 90%.

As I often say, let your profits run.

Of the losses, the largest was a 51.5% hit in Perseus Mining Ltd [ASX:PRU]. This was an occasion when not having a live stop-loss was costly. My exit was a lot worse that it could have been.

Fortunately, there are no such issues amongst my open trades. The largest current loss is just 10.7%.

So that’s a bit of my story.

Algorithms have made my trading more consistent than it’s ever been. They also identify stocks that I’d never find on my own, and greatly reduce the time it takes to manage my portfolio.

I’ll let you judge whether algorithmic trading is for you.

But for me, there’s no better way to trade.

Until next week,

Jason McIntosh
Editor, Quant Trader

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Jason McIntosh

Jason McIntosh

Jason McIntosh is a professional quantitative analyst. Before he graduated in 1991 he joined Bankers Trust — a Wall Street investment bank — to be a trader. These days, he’s a private trader and system developer. In 2014 he launched the wildly successful trading service: Quant Trader.

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