Does Quant Trading Work? (Why, How, Strategies, Analysis)

Quant trading works because it’s based on objective and backtested trading rules. We believe it 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. You can develop trading strategies through backtesting and have a fair chance of making money. 

Does quant trading work, and if so, how can you make quant trading work for you? We provide a 5 step plan to make quant trading work for you. Many hedge funds and mutual funds are successful at quant trading, and this serves as an inspiration for aspiring and independent traders who want to replicate such a business strategy on a smaller scale.

Related Reading: The History of quantitative trading

For example, we believe you can succeed in quant trading just as likely as any professional institution. We successfully day traded for almost 20 years using only quantitative trading strategies. If we can do it reasonably well (we are not particularly smart or intelligent), anyone can. But it for sure requires a lot of work and discipline.

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 profitable if done correctly, but it’s not easy, and you are not likely to get rich by quant trading.

However, we believe quant trading offers better chances of profits than discretionary trading, but success depends on your work ethic, discipline, and creativity.

Can quant trading work for you?

Quant trading can work more or less for anyone because it has trading rules that are 100% quantified and testable. You’ll be fine if you stick to the rules and signals, given that you are trading robust and profitable trading strategies.

Why does quant trading work?

Quant trading works because it’s based on objective and backtested trading rules, and you have the opportunity to build scale via automation. Quant trading helps you diminish trading biases and keep detachment to money.

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 in trading. Please read the comparison of mechanical trading strategies vs. discretionary trading strategies.

Opposite, quant trading helps you define your trading 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. You base the strategies on backtesting because backtesting works.

The good news is that trading strategies don’t need to be complex. Quite the contrary, the simpler you make them, the better. The power of simplicity in trading strategies can’t be emphasized enough.

Summarized, quant trading follows this process: you backtest trading rules and check its profitability, and 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

To give you an idea of what quant trading is, we show you 8 quant trading strategies in this video:

Which 5 steps can make quant trading work?

These 5 steps can make quant trading work for you:

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

The 5 steps above are taken from Victor Niederhoffer’s book Practical Speculation, a book we strongly recommend together with his bestseller The Education of A Speculator.

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

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

As a trader, you need to brainstorm and test ideas constantly. Generating and backtesting trading ideas 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 over the coming trading days if it makes a new 5-day high on a Monday?

The only limitation is your fantasy. You get rewarded for creativity and thinking outside the box. We wrote an article about how I made money day trading.

The best strategies are the most unconventional ones. You can’t expect to find the best strategies for free, so 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 trading 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 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 you are unsure of what is a good trading strategy, please start reading about backtesting.

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, unless it offers diversification.

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 a promising quant trading strategy?

It’s pretty rare. Looking at our journals, it seems we throw away, on average, 29 of 30 ideas. Even among those 1 in 30 that we proceed with, only about 4 in 10 end up going live, perhaps even less.

As you can understand, quant trading requires a lot of work! But it is 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 backtesting out of sample:

You can divide your backtest data into two parts, one for backtesting on past data and one for backtesting 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, divide your backtest into both in and out of sample and then proceed with the incubation period.

Unfortunately, most trading strategies fail during the incubation period. But the good thing is that no money was lost, as you otherwise would.

How many strategies fail during the six-month incubation period? Our statistics suggest that 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, different market directions, 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 backtest 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 the red line in this chart:

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

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

Step five: Trading is all about feedback

When 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 outages, 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 trading 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 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.

What are some of the most famous quant traders?

Some of the most famous quant traders include Jim Simons, Ed Seykota, Ed Thorp, David Shaw, Victor Niederhoffer, and Nassim Taleb.

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 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, so no one knows exactly what kind of trading strategies the Medallion Fund trades.

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 who 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, he 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:

Does quant trading work?

Quant trading works for traders who are systematic and rational, and you are more likely to be profitable than discretionary traders. Discretionary might work for a few, but we doubt it’s a sustainable strategy year after year.

You don’t want to “guess” when to buy and sell, and thus, we believe backtesting and automation are the best ways 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 you might fail. This is the way markets work. If you go for quant trading, we believe it smart to put aside some capital for long-term appreciation to hedge your bets. Perhaps quant trading is not for you at all. Should you trade or invest?

To summarize, quant trading works. But 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 a bonus: it’s fun! It’s a journey where you learn something new every day about the markets and yourself.

FAQ:

– 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.