Home Backtesting and trading Does Quant Trading Work? Is Being A Quant Worth It? (Strategies and...

Does Quant Trading Work? Is Being A Quant Worth It? (Strategies and Insights with Video Analysis)

Does quant trading work, and if so, how can you make quant trading work for you? Quant trading (quantitative trading) might sound complicated, but don’t let the terms scare you away from trying or digging deeper. Quant trading can be very profitable if done correctly.

Quant trading does work. We believe quant trading is the correct way to approach short-term trading. Even better, we believe it potentially can work for anyone who is a keen learner – you certainly don’t need a Ph.D. to be a quant. Through backtesting, you can develop trading strategies and have a fair chance of making money.  We provide a 5 step plan to make quant trading work for you.

We believe quant trading offers better chances of profits than discretionary trading. How much you make depends on your work ethic, discipline, and creativity.

Why do we believe quant trading can work for you?

Because quant trading has rules that are 100% quantified and testable. As long as you stick to the rules and signals, you’ll be fine.

Many hedge funds and mutual funds are successful at quant trading. But many aspiring traders are wondering if you as a small, independent, and private trader can succeed in quant trading.

We believe you can succeed in quant trading just as likely as any professional institution. We have been trading full-time for 20 years, purely by quantified buy and sell signals. We have hardly done a discretionary trade since the 1990s! If we can do it reasonably well (we are not particularly smart nor intelligent), anyone can. But it for sure requires a lot of work and discipline.

Why does quant trading work?

Discretionary trading is difficult. The number of indicators, news, bells, and whistles is endless. What are you going to base your buy and sell decisions on? You risk going around in circles looking for the Holy Grail.

Opposite, quant trading helps you define your signals to a few clearly defined rules. You download or buy market data of historical quotes, and start looking for patterns, effects, and anomalies. The trading strategies can be based on seasonalities, mean reversion, trends, price action in different markets, etc.

The good news is that trading strategies don’t need to be complex. Quite the contrary, the simpler you make them, the better.

Once you have backtested the rules and checked its profitability, you paper trade before you go ahead and trade it with real money. Pretty simple, at least in theory, but most traders have a tendency to overcomplicate things.

To help you get started we suggest you approach quant trading in this order:

8 simple examples of quant trading strategies – video

5 steps to make quant trading work for you

Victor Niederhoffer explained in Practical Speculation how you can use the scientific method to your advantage as a quant trader:

  1. Induction: Form an idea or hypothesis – something that can be 100% testable with buy and sell signals.
  2. Deduction: Make a prediction based on your idea.
  3. Observations: Make observations – backtest your data.
  4. Verification: test your prediction against your backtest

In practice, as a small and independent trader, the above steps work like this:

Step one: Find a trading idea or strategy – form a hypothesis

As a trader, you need to constantly brainstorm and test ideas. The process of generating ideas and backtesting them should take up at least 80% of your designated trading time. This process is the core of any quant trader.

A trading idea could be a pattern that you observe visually or read about. For example, what happens if the S&P 500 drops two days in a row? What happens in gold if it makes a new high on a Monday? You simply test what happens if you buy on the close and sell after x days (as an example).

The only limitation is your fantasy. You get rewarded for creativity and thinking outside the box. We wrote an article about this process some years ago:

The best strategies are the most unconventional ones. You can’t expect to find the best strategies for free, even though we have compiled a list on this page that provides you with some ideas:

Also, keep in mind that two traders create synergies. Two brains can create more than 2x ideas to test! Even better is if you manage to work with someone that has a proven profitable track record.

Step two: Backtest your idea or strategy

Once you have made 100% quantifiable rules, you backtest your idea, for example by using Amibroker (however, a spreadsheet gets you a long way):

Backtesting involves the process of coding your buy and sell signals and testing the strategy on historical data – how it has performed in the past. This validates or falsifies your hypothesis and trading idea.

Once you find a strategy that has a good equity curve, you continue to the next step.

If the equity curve is sloping upwards from the left to the right, you might be on to something. If not, forget about it or look at ways to improve it.

We recommend keeping a log on every idea you test which is easily done in a spreadsheet. Later you might discover a “missing link” in your original idea.

How often are you likely to find something promising? It’s pretty rare. Looking at our journals it seems we throw away 29 of 30 ideas. Even among those 1 in 30 that we proceed with, only about 4 in 10 ends up going live, perhaps even less.

As you can understand, quant trading requires a lot of work! But certainly an enjoyable process!

Step three: Out of sample testing

Once you believe you have a tradeable quant strategy, it’s tempting to start trading immediately.

Unfortunately, that is something we strongly recommend against.

Why should you wait? Because you are not finished testing. We told you quant trading is a lot of work!

Most price action is randomness and noise, and it goes without saying that you can easily find seemingly good strategies that in reality are curve-fitted or due to chance. Your result could be sheer luck!

To minimize this risk, we recommend testing out of sample:

You can either divide your backtest data into two parts, one for testing and one for testing out of sample, or you can do what we recommend the most: let the strategy run in a demo account for at least 6 months or longer. Let’s call this the incubation period.

Perhaps even better, make sure you divide your backtest into both in and out of sample, and then go ahead with the incubation period.

Most of our strategies fail the incubation period, unfortunately. But the good thing is that no money was lost, as we otherwise would.

How many strategies fail the six-month incubation period? Our statistics suggest 60% don’t make it.

Again, no one told you quant trading is easy money!

Step four: Construct a portfolio of trading strategies

Unfortunately, you are not finished if you manage to find a good strategy that passes the out-of-sample test and/or incubation period.

You are unlikely to be successful if you only trade one strategy.

Even worse, if you trade just one strategy in one instrument (S&P 500, gold, bitcoin, etc.), we can almost guarantee your failure. The perfect strategy doesn’t exist.

The advantage of quant trading and automation is that you can trade almost an unlimited number of strategies at the same time. The computer takes care of the execution, while you spend your time finding quantitative trading strategies.

As a rule of thumb, the more strategies you have, the better. The reason comes down to diversification and correlation:

You want to trade different markets, different types of strategies, and different time frames.

That’s why you are not finished testing when you have made a trading strategy that passed the out-of-sample test successfully. You need many quant strategies to succeed!

Moreover, you need to test how your strategies perform together.

For example, if you have three different mean-reversion strategies in the S&P 500 they might not work very well together. They might have many overlapping trades, and thus adding a second or third strategy might not add much value – it can even make the sum of the strategies worse.

Always keep this in mind: The less correlated the strategies are, the easier it’s to trade bigger size and compound because drawdowns get smaller.

You want to have an equity chart like this:

Brummer & Partner’s return. Source: Website.

The red line is the Multi-Strategy of Brummer & Partner and the grey line is the Swedish Total Return Index.

All things being equal, you want to have a straight line like the red one. The reason is simple: almost all traders react adversely to drawdown and commit behavioral mistakes like selling on the bottom and buying at the top.

Step five: Trading is all about feedback

Now that you have several quant strategies in different markets and time frames, you are not finished.

As a matter of fact, you never finish testing and rest on your laurels as a quant trader.

Quant trading needs feedback all the time and we recommend you keep a trading journal. Keep detailed records of all your trades for further review.

This is important because of three reasons:

First, there might be a discrepancy between the backtest and live trading. A backtest is nothing more than a simulation, and live trading might yield different results. Different executions, slippage, power outage, computer breakdowns, lagging quotes, etc. might contribute to the overall results, usually to the detriment compared to the backtest.

Second, you might skip trades because of mental reasons, for example, a recent loss makes you hesitate and skip a signal.

Three, all good things normally come to an end: strategies eventually stop working and you need to measure the performance. This is something we return to later.

How do you know when a strategy stops working?

Unfortunately, there is no way you can tell. All strategies go into drawdowns that could be the end or just another dip.

Be careful to stop trading a strategy that has served you well. If you stop and later resume when it works again, you risk going around in circles.

Hence, we recommend looking for structural inefficiencies or strategies you understand or have some logic. This way, it’s easier to determine if they stop working or if it’s just a dip. A trading log helps you diagnose the problem.

The most famous quant traders:

We end the article by writing a few words about successful quant traders and speculators that we have covered on this website. We mention them to give you a boost and motivation to show you that quant trading works, although it certainly requires a lot of work:

Jim Simons and the Medalion Fund – An unbeatable (?) track record

The Medallion Fund, managed by the famous and secretive Jim Simons, has arguably the best track record ever for any fund in the money management history: 66% annual returns for over 30 years with no down year!

The fund’s secret is quant trading. They trade many markets and time frames and enter and exit trades only by quantified rules. God forbid discretionary trading!

Most large quant firms are notoriously secretive about their trading strategies but we wrote about Medallion’s strategies in a separate article:

Ed Seykota – the trend following wizard

One of the early pioneers of quant and rule-based trading was Ed Seykota. He is most famous for being an avid trend follower, but more importantly, he was one of the few first quants that used computers to look for patterns.

Victor Niederhoffer – the boom and bust quant

Niederhoffer was once ranked number one in the hedge fund world until he “blew up” twice. Then why do we mention him?

Because we regard Niederhoffer as one of the first quants. His books The Education Of A Speculator and Practical Speculation are very good reads and should be in the library of any aspiring quant trader.

Edward Thorp – the first quant?

Edward Thorp, the author of the best-selling Blackjack book Beat The Dealer and later Beat The Market, has an outstanding track record: from 1969 to 1988 he managed a quant hedge fund that returned 19.1% annually – more than double that of the S&P 500.

In 1988 in quit the hedge fund business to start managing his own money. We recently read his book called A Man For All Markets and we summarized our key takeaways here:

Conclusion: does quant trading work?

We would suggest quant trading is the only type of trading that works. Discretionary might work for a few, but we doubt it’s a sustainable strategy year after year. You don’t want to guess, and thus we believe backtesting and automation is the best way to go for almost all traders. The 5 steps we provided should help you make quant trading work for you.

However, to make quant trading work for you, you must prepare for hard work, and that you might fail. This is the way markets work. If you go for quant trading we recommend you put aside some capital for long-term appreciation to hedge your bets.

Does quant trading work? Yes, quant trading works. Is it worth it? If you put in the effort and time we believe you stand a fair chance of entering a scalable career. Quant trading has an added bonus: it’s fun! It’s a journey where you learn something new every day, both about the markets and yourself.


– Why is quant trading considered better than discretionary trading?

Quant trading is considered better than discretionary trading because it involves rules that are 100% quantified and testable. Stick to these rules and signals, and you increase your chances of success. Discretionary trading, on the other hand, can be subjective and emotional.

– Why is simplicity important in trading strategies?

Simplicity is crucial in trading strategies because complex strategies are prone to curve-fitting and over-optimization. The simpler the strategy, the easier it is to understand and implement, leading to better long-term results.

– Is quant trading suitable for small, independent traders?

Yes, quant trading is suitable for small, independent traders. The provided content emphasizes that with dedication, anyone can succeed in quant trading. It’s not limited to institutional traders or those with advanced degrees.