Last Updated on March 6, 2021 by Oddmund Groette
There are many approaches on how to make money in the markets. Some use fundamental factors, others use technical analysis, while others might crunch numbers to get an edge. The latter group is often called quants.
Quants use numbers and time series data to get an edge in the markets while executing their strategies automatically. However, good skills in math and statistics are not enough to succeed. You have to be “street smart” as well.
What is a quant?
Quant is an abbreviation for a quantitative or quantified trader. A quant works with numbers and data, usually time series of stock prices, often using very complex formulas. Most quants are employed by hedge funds, large institutional banks, or proprietary trading firms. These institutions often look for a degree in math, physics, chemistry, etc. The aim is to analyze many factors to find potential edges and base these edges on building new trading strategies or algorithms. The trading world has changed dramatically over the last decades, as trading firms shifted from discretionary methods to purely quantitative models by pouring over huge amounts of data.
While many quants are hired and work for a salary and bonus, which might be smart given the moat surrounding an institution with lots of capital and computer resources, many would rather work or trade for themselves. Is it possible to start a quantified trading business alone, or do you need exceptional math and coding skills to succeed?
Many like to think of quants as someone with a Ph.D. degree in math or physics, but you are just as much a quant if you have no degree but still use lesser advanced formulas and tools. At the end of the day, it’s profits that matter, and you don’t get extra scores for doing it more complex than necessary. The world is full of math quants that have failed. Is it essential to understand value at risk (VaR) and kurtosis? Luckily, no. To be successful, you need more than math skills! We still believe the main element of trading success is about common sense, experience, and being “street smart”.
What is quant trading?
Quants pour over data to find irregularities or inefficiencies not explained by chance or randomness. The process involves automation: when a tradeable strategy is found and passes rigid testing for randomness, the execution is done automatically via software connected to the broker.
A quant is someone who uses math or very strictly defined rules to enter and exit positions. The strategies based on these rules are always developed on backtested data, which can be anything that has a numerical value, like price trends and volume. Later the quant tests the backtested data on so-called “out of sample data” to verify the backtest results. In most cases, the backtest performs worse on future data due to data mining, randomness, and changed market behavior.
The computational power has increased, while the prices of both data and hardware have gone fallen. Hence, technological progress enables many traders to work from home using cheap software, the internet, and VPNs.
Are quants data miners?
To a certain degree, they are. Data mining is when you look for patterns, correlations, and relationships in data sets to predict outcomes. If you try hard enough and test all possible outcomes, you will surely find something that seems to work. The huge increase in computational power means a computer can be fed with hundreds of variables and run billions of simulations looking for patterns during just a few hours. Surely something that works pops up by doing it this way. But is the result due to a real inefficiency, or does it happen because of a specific market cycle, randomness, or chance? Just because something has “worked” in the past doesn’t mean it has any real predictive value and will hold up in the future.
All quants suffer from data mining, but hopefully, the out of sample test can filter out the bad from the good.
How do you become a quant?
The first question you should ask yourself is this: why do you want to become a quant?
You are reading this article and thus likely intrigued by the idea of being a quant, or perhaps you don’t have any aspirations of being a quant, but you want to understand the mindset behind all those people buying and selling stocks and futures for billions of dollars during a trading day.
Many argue you need good skills in math to become a quant. Yes, if you want to work for an institution, you most likely need it. However, working on your own, it’s not necessary. You cannot compete with the combined skillsets of institutions anyway, so you need to implement some skills and strategies that are less likely to be used by them.
Hence, to become an individual quant, you don’t necessarily need any particular good math skills. If you have basic skills, you will come a long way, especially combined with curiosity, interest, and learning. You don’t need to be pretty advanced to succeed in the market. The geniuses behind Long-term Capital Management didn’t prevent them from going broke. What is most important is a basic knowledge of how the markets work, common sense, and a few years of experience:
The Lucid Fallacy – street smart vs. Ph.D. smart:
No matter how smart you are and how many degrees you have, you will not succeed without intuition and smartness in understanding how the markets work. In math and physics, you always have a correct answer, which is not how the markets work. We suspect the correlation between IQ and profits are somewhat low.
Nassim Nicholas Taleb wrote the Lucid Fallacy in The Black Swan. The fallacy refers to quantitative models misused when they don’t apply (the misuse of probabilities to model real-life situations). Models often lead to overconfidence or not knowing that results are based on, for example, randomness. The more academic degrees you have, the more likely you are to suffer from this bias. The financial marketplace is increasingly complex. The demand for PhDs in math and physics is high, but no advanced degree can teach you randomness, confirmation bias, stubbornness, or whatever cognitive bias you might have. It would help if you were “street smart” to succeed as a trader. And this is what the Lucid Fallacy is all about.
Nassim Nicholas Taleb uses a fascinating metaphor in The Black Swan to illustrate this (the following example is taken from the top of our heads, we only vaguely remember the story Taleb made in the book):
Assume you are about to bet on heads or tails in a coin toss. You know that during the last 200 tosses, heads have come up 142 times and tails only 58 times. How do you place your bet on the next coin toss?
The smart and rational quant, a Ph.D. graduate named Dr. John, will argue it doesn’t matter. No matter what has happened in the previous 200 tosses, it’s still a 50% chance for each on every toss.
However, Fat Tony, the street-smart kid from Brooklyn, bets on heads. Why? With such a skewed result, many standard deviations away from a normal distribution, he believes the game is rigged.
This is the difference in thinking between a rational, intelligent Ph.D. quant and a not so educated “street-smart” trader.
Why do you need a certain degree of “street smartness”? Ronald N. Kuhn was interviewed in How I Became A Quant, a book by Richard Lindsey and Barry Schachter, and Kuhn’s insights explain a lot:
As a former physicist Al Slawsky put in the early 1990s, “it was a bad year for value investing. In my former life, there was never a “bad year” for gravity…..We do not typically try to solve problems exactly, but aim for caturing the most important elements and getting close. That skill is, if anything, even more important in finance, where there typically are no underlying laws of nature, and the problems are mainly about reasonably approximating reality.
In the book The Man Who Solved The Market, the book about Jim Simons, who was very successful with the Medallion fund, had a problem making money from the start because they didn’t have a deep understanding of how the market worked (in practice). They were academically smart, but they didn’t manage to be profitable at the start because they failed to understand the mentality of the pit traders and how their orders were manipulated. Simons was a mathematician with a limited understanding of practical investing.
A good quant makes things simple
To put it crudely, when you multiply bullshit with bullshit, you don’t get a bit more bullshit – you get bullshit squared.
Alchemy, Rory Sutherland
As you might have understood from the previous paragraphs, a good quant makes it as simple as he or she possibly can. The graph below summarizes the results from compiling data in a book by Richards Heuer, a former intelligence consultant in the CIA:
Richards Heuer writes that once an experienced analyst has the minimum information necessary to make an informed judgment, obtaining additional information generally does not improve the accuracy of his or her estimates. Quantity of info doesn’t mean quality. However, in today’s market, info and data exist in abundance. It’s easy to fool yourself. Nassim Nicholas Taleb once said:
To bankrupt a fool, give him lots of information.
Morgan Housel writes this about investing:
An engineer can have a successful career knowing nothing other than engineering. Same for a chemist, meteorologist, or radiologist. Business and investing don’t work like that. They’re a little math, a little accounting, a little sociology, a little psychology, a few parts marketing, law, politics, game theory, history, statistics, biology, and public relations. That doesn’t make them harder than other fields; just more uncertain, prone to change, and with fewer experts.
We have published many potential articles on our website, completely free of charge. Many of them have stood the test of time and is not complicated at all. For example, the RSI(2) on QQQ has been very profitable for over two decades and still performs well. The strategy is as far away from rocket science as you probably can come.
Even though Jim Simons only hired highly skilled mathematicians, most of their strategies were not complex. In The Man Who Solved The Market, there is an interesting quote on page 112 on when the fund started making money:
Some of the trading signals they identified weren’t especially novel or sophisticated. But many traders had ignored them. Either the phenomena took place barely more than 50 percent of the time, or they didn’t seem to yield enough in profit to offset the trading costs. Investors moved on, searching for jucier opportunities, like fishermen ignoring the guppies in their nets, hoping for bigger cath.
Occam’s razor is applicable in trading
William of Ockham (1285-1347) was a philosopher who stated that if you have two competing theories, the simplest of the two theories is preferred. You can use this theory in many ways in your trading. For example, use fewer assumptions and variables in your strategies. Markets are complex, but you are still unlikely to gain an edge by making complex formulas. Likewise, removing noise like news feeds, social media, TV, etc. will likely improve your trading. It’s easy to get distracted by things and sources that don’t matter. Additionally, simple hypotheses are easier and quicker to trade.
Does a quant need speed and fast execution?
No, you will not be able to compete on speed and execution, unfortunately. That is a game you are guaranteed to lose against better-equipped traders, typically bigger financial institutions like hedge funds, banks, or proprietary trading firms.
You don’t need any sophisticated equipment except trading software, a broker, and an internet connection. Your result is much more likely to come from your creativity and experience and less likely from any fancy tools you might have. You can’t compete on tools and equipment.
Unfortunately, our experience indicates many software developers have a fetish for developing their own software and programs when they start trading. This is, in most cases, a waste of time. You can buy a good platform like Amibroker for only 400 USD and use it for the rest of your life. Why spend time developing software when someone has already done it? You can’t develop better tools than institutions that have billions of dollars under management.
You are unlikely to gain any advantage through software or execution speed. Concentrate on your trading ideas, not tools.
Is quantified trading profitable?
Of course, quant trading can be very lucrative. However, most likely, you will not succeed. Why? Because most short-term trading is a zero-sum game, while long-term investing is not. If you invest for the long-term in a broad basket of stocks, you have a nice tailwind from the return the companies make on their invested capital. Long-term investing is not a zero-sum game, and simply by being patient and regularly invest as you go along, you will highly likely become wealthy. Warren Buffet presumably made 99% of his wealth after turning 50, and 97% after he turned 65. The compounding effect works like a snowball. Simply by being patient, you have a nice chance of building a nest egg.
Thus, your advantage in long-term investing is by being patient. Being patient sounds pretty easy, but history shows many find it hard to sit still on their ass and do nothing.
In trading, you need some competitive advantage over the other traders. How are you going to become a predator and not the prey? What is your edge? How are you going to profit in a zero-sum market?
You can read more in this article (reverse thinking):
How much can a quantified trader make?
Trading is a scalable profession. If you’re good, you can quickly scale up your business by using leverage. The downside is that the profits are highly skewed to just a few players. The majority’s main role is to get eaten and support the livelihood of smart and adaptive traders.
What makes it scalable? You can use leverage and turn over your capital fast. As a small individual trader, you most likely don’t face constraints in size, and you can easily scale your trades, obviously depending on how well you deal with profits and losses.
Is being a quant worth it?
You have to consider the effort and time it takes to succeed. No matter if you trade full-time or part-time, you need to dedicate a lot of time. The good thing about automation is that you can let your software buy and sell while doing your ordinary job.
What is your opportunity cost? The opportunity cost is an alternative way to invest your capital. The opportunity cost could, for example, be to invest your money in mutual funds and “forget about it”. The long-term risk premium for owning stocks has been a few percentage points above the inflation rate (you just need to have patience and wait). Your opportunity cost should be as high as possible. The famous investor Charlie Munger once said that his opportunity cost is his investments in Berkshire Hathaway and Costco, at the right price.
Don’t waste your best years chasing the dream of striking it rich as a quantified trader. Make a timeline and see your progress. As long as you are making money and making progress, you might be on the right track. Nevertheless, in trading, you easily derail, so be careful not to waste your time.
Is quantified trading stressful?
Any trading is stressful, but much of it depends on your personality. Are you fine with taking financial risk? Our experience tells us the best traders are those that are cautious. The balance between risk-taking and risk-aversion is a delicate one. Will a loss make you hesitate and stop trading? Will profits make you feel invincible and turn you into a monster of risk-taking? These are all questions it’s impossible to answer until you have tried.
Do successful quants code?
Yes, a quant trader needs to code. However, you don’t need to have any specific background as a programmer. We at Quantified Strategies have no coding background, but we can still run about 100 strategies via our computers. You don’t need to be a rocket scientist to become a quant. As we wrote above, we have yet to see that complex models make more money. One dollar earned is one dollar earned, no matter how many variables you are using. Don’t turn a good system into a perfect one – you’ll only end up data mining and making the strategy unsuitable for future predictions.
What is a successful quantified trader?
Obviously, trading is about making money. A good trader should, therefore, be a very profitable trader?
Not necessarily. Don’t make the mistake of judging someone very profitable as skillful. As Annie Duke writes in Thinking In Bets: A good outcome can happen despite a bad decision, and a bad outcome can happen despite a quality decision. We all suffer from what Duke calls “resulting”. Many are successful traders due to luck. The luck can result from a bull market, a certain style that fits the current market, or a trader might ride a specific market cycle.
We all fall prone to survivorship bias. There are so many traders trying, and there are many successful traders just because of the markets’ random nature.
You are unlikely to read about the best traders in the news. Why is that? They are most likely happy being anonymous and not making amounts that many would consider striking it “rich”, but enough to live a comfortable life and put money aside for the future. A good quant trader is someone who has managed to make money over many decades through both recessions, expansions, and different markets. These traders are few and far between.
To give an example: A famous Norwegian trader, Einar Aas, made huge amounts of money by trading power derivatives in the Nordic markets. For about 17 years he was regarded as extremely skilled and successful, even one year making it to the top of the nation’s highest earners before he blew it all in a black swan event in 2018 and faced bankruptcy. To make a lot of money, you need to take a lot of risk. Instead, aim for the slow and steady.
What is important for a quant to succeed?
You need a basic understanding of how to code. But more importantly, you need to understand pretty well the following:
- Randomness and noise in the markets
- Understanding of probabilities
- Which factors influence the markets, being “street smart”
- Be creative, think outside the box
The best advice is to start small and diversify your capital. Trade many markets, different time frames, and perhaps set aside money in mutual funds for long-term investing (the latter serves as a buffer). If you don’t make any progress, make sure you don’t waste your time.
Another practical tip is to have income not related to trading. Start with trading as a hobby, and only scale when you are certain this is not due to luck or randomness.
Learn from profitable traders
One of the best advice we can give is learning from older and more experienced traders. We at Quantified Strategies most likely would have failed if we weren’t so lucky to meet and learn from a few individuals when we started.
Quantitative trading strategies example
We have published many articles containing strategies. Admittedly, they are not our best strategies (those we like to keep to ourselves). But many of them can give you valuable input:
Trading doesn’t need to be advanced or complex. When you start, make it as simple as you can. Nevertheless, you need software, both for testing and live trading. Thus, the ability to code is required. Luckily, anyone can learn basic coding by spending some hours in the evening now and then.
Moreover, trading should only be a hobby or something you do in addition to a regular job when you start.
Disclosure: We are not financial advisors. Please do your own due diligence and investment research or consult a financial professional. All articles are our opinions – they are not suggestions to buy or sell any securities.