How to Make Money Trading Stocks

Has an algorithm rejected you?

Well, if you’re a recent job seeker, the answer may well be yes.

You see, Josh Bersin, principal at HR consulting firm Bersin by Deloitte, says: ‘Most companies have thousands of resumes sitting in a database that they’ve never looked at.

That’s right, a human may never lay eyes on your CV.

In fact, around three-quarters of resumes might never be seen by a real person. Just think about that…your career could hinge on the split-second judgment of a HR bot.

This makes many people uncomfortable — on both sides of the recruitment game.

On the one hand, employers don’t want to cede full control to an algorithm. Computers may well be efficient in creating a shortlist, but humans typically want the final say.

Prospective employees have their own concerns. Many people are uncomfortable with the thought of their careers being in a pair of virtual hands.

So what’s the solution?

Well, one possibility is a hybrid — a human/algo combination. This is where algorithms do all the legwork, and humans make the key decisions.

Now here’s the thing…

This type of human and machine alliance isn’t unique to recruitment. You can apply it to any number of industries. And one that could have real benefits for you is the stock market.

I’ll tell you more about this in a moment.

But first, let me tell you how I trade…

Investment expert’s top picks: The three ASX stocks with the biggest potential for 2018. Get your free report now.

An algorithmic approach to trading stocks

Quant Trader is a completely algorithmic system. The signals my subscribers receive aren’t subject to human judgement. They’re the result of a set of autonomous formulas.

I simply download the daily share price data and let the computer do the rest. Apart from designing and maintaining the system, algorithms do most of the work.

Now I must say, I’m a convert to this style of trading. Rarely do I trade the ‘old way’ anymore. Nowadays, I’m comfortable letting algorithms make most of my decisions.

Such is my confidence, that I don’t research a stock before buying. In fact, I don’t know anything about many of the companies I own.

I’ll give you an example…

Possibly the most obscure stock in my portfolio is Schaffer Corp. Ltd [ASX:SFC]. The company has interests in building materials, automotive leather, and property.

In fact, SFC doesn’t even qualify for the All Ordinaries (the top 500 stocks). At the time of entry, my system ranked it at 941. This put it well beyond the range of most analysts.

Here’s what the trade looks like:

MoneyMorning 31-08-18

[Click to open new window]

SFC is ahead by 125%. This makes it the fifth best performing stock in my portfolio.

Now, I wouldn’t own this company without the direction of an algorithm. With over 2,000 listings on the ASX, I simply wouldn’t have ever found SFC on my own.

But I know following an algorithm without question isn’t for everyone.

Just like many HR departments, humans typically like some input.

So how could a human and machine alliance potentially benefit you?

Well, that’s the topic of the next section.

A filter to the algorithm

I received an interesting email a little while back. It’s from a long-time subscriber, Warwick. He’s been tracking Quant Trader’s signals since the beginning (November 2014).

Now as you might guess, Warwick doesn’t follow the signals without question.

Instead, he applies a quick fundamental filter via a third-party service. The metrics he tracks are the financial strength of a company and the liquidity of the shares.

Warwick says he only considers liquid stocks with a strong balance sheet.

Here’s the table he sent me:

MoneyMorning 31-08-18

According to Warwick’s data (which I haven’t verified), the message is clear. The best signals tend to be for companies with strong financials and liquid stock.

Now, this of course isn’t surprising — I’d expect financially strong stocks to do well.

But it does show how a human/machine pairing could get outstanding results.

You could do something similar…

Last week I told you how Quant Trader identifies an inner market…a select group of high potential stocks from over 2,000 ASX listings. You can read more about this here.

Now if you’re like me, the signals will be all you need — you’ll be comfortable making your stock selections without any further research.

But I know this won’t be for everyone. Some people will want to do their own analyses.

And do you know what?

That’s perfectly OK.

Warwick is a great example of an algorithmic/human combo. He uses Quant Trader to shortlist high potential stocks. He then overlays a fundamental filter to narrow his focus.

And the process seems to be working. Warwick says that the market ‘has been delivering me over 30% returns’. That’s a solid result in anyone’s language.

Hopefully this glimpse into another trader’s process is both interesting and useful.

But no matter what your approach is, I believe algorithms are here to stay.

Make sure you use them to the fullest.

Until next week,

Jason McIntosh
Editor, Quant Trader

PS: If you want to lay down a little money on the hottest corner of the ASX right now…but you don’t know your way around the small-cap sector…this report is for you. Get access now (free).

Money Morning is Australia’s most outspoken financial news service. Your Money Morning editorial team are not afraid to tell it like it is. From calling out politicians to taking on the housing industry, our aim is to cut through the hype and BS to help you make sense of the stories that make a difference to your wealth. Whether you agree with us or not, you’ll find our common-sense, thought provoking arguments well worth a read.

Money Morning Australia is published by Fat Tail Investment Research, an independent financial publisher based in Melbourne, Australia. As an Australian financial services license holder we are subject to the regulations and laws of Corporations Act and Financial Services Act.

Money Morning Australia