We have finally got back to writing about finance. After a long break from all writing and the last few months focused on accounting and personal finance, it’s good to be back into a more finance-centred topic. So today, we are going to be looking into the question of what is a quant trader.
What is a Quant Trader?
Trader v Investor
A trader buys and sells financial assets either for themselves or on behalf of another party. The main difference between a trader and an investor is their time horizon or the duration for which they plan on holding the asset. Investors tend to have a longer time horizon, whereas traders tend to hold assets for shorter periods, usually capitalising on short-term price changes.
Most traders rely on intuition or experience. They will either follow the rules they have been taught or rely on specific technical analysis learned over the years. At the same time, quantitative traders don’t tend to rely on intuition as much. Instead, they rely on the quantitative analysis specific to the markets that they trade.
Many trading rules tend to be counter-intuitive, often coming from behavioural finance and buying when the human instinct is to sell or vice versa. One of the benefits of a trading system is that you devise a game plan beforehand and allow a computer to enter the actual trades. And that way, you avoid making the mistake of overriding your system when it feels uncomfortable.
A non-systematic trader might feel, based upon their experience, whenever the market is moving up sharply, they might tend to think that it will continue. Whereas a systematic trader might have a very similar feeling, they will take some market data and then analyse it to see if their instinct was right or wrong.
They might, in addition, analyse the data to work out how best they can risk managing a trade like this. How long should they hold the trade? Should they cut their losses quickly if the trade is not working out? Or should they hold on longer?
Trader Skill Set
What firms are looking for in a quant trader usually value quantitative skills highly. They need people with the skills to analyse all the data that’s available in the market. And there is a lot of data available for analysis.
Quant traders don’t want to build a trading method and let it go off and trade. They usually maintain a healthy scepticism about their trading model. Quants are generally aware that no trade works 100 per cent of the time; even great trades can eventually stop working.
Quants pay attention to events that invalidate their strategies or events not captured in their data sets. For example, a low-interest-rate environment would beg the question of how to manage bond positions. There may be concern about risk skewing against long positions where rises were more likely than falls. We would develop ways to measure and feed in all events, not just interest rates, with this example. Quants are looking for general solutions for the general problems.
What Skills Are Required?
Most quant traders have a good understanding of statistics, financial derivatives, and corporate finance. They often have backgrounds in numeric disciplines like mathematics, engineering or physics. But they also need to learn finance and statistics, which overlay the knowledge they already have.
What Do Quants Trade?
Quant firms generally trade the largest and most liquid markets, such as futures, forwards, large-cap stocks and vanilla options markets. The critical thing is not how large their positions are but how large they are relative to the traded market.
In finance, we use liquidity to describe how easily you can enter or exit your positions without moving the market with your trades. Quantitative investors are usually very focused on transaction costs and liquidity in the assets they trade. Allocations to these assets are typically scaled accordingly.
A focus on data technology allows quant traders to accurately estimate trading costs on any assets in their portfolios and estimate and control the cost of liquidating these positions if necessary.
We sometimes accuse quant traders of trading overly complex strategies that have no basis in reality. But in fact, quants start from the same point as discretionary or fundamental traders, with a hypothesis or a theory about how markets might behave. The view could be, for example, that the interest rates of two different countries predict the exchange rate between the two. Or it could be that the slow reaction of investors to earnings news leads to the momentum of asset prices in markets.
The critical difference is that a quant trader will take the next natural step as a scientist with a hypothesise. They use the wealth of available historical data and statistical techniques to test, validate and refine the hypothesis. Once this process is complete, and only then, they use the knowledge that they’ve gained to invest.
Today there are many quantitative trading firms with really long track records of good performance. You can think of these firms as a collection of scientists constantly collecting evidence supporting their investing style.
Risks Involved for a Quant Trader
Like all investments, quant funds face exposure to surprise market events, such as central bank interventions or geopolitical events. However, they face no more exposure than traditional macro, or fundamental traders are. The world is full of events that are very difficult to predict. A quant trader’s edge might be that they can recognise this difficulty and confront it head-on.
Quants are well versed in recognising the limits of statistical modelling and its ability to predict. Thus, rather than claiming expertise in specific assets, quants usually aim to be diversified. Diversification can reduce the portfolio’s exposure to something like a surprise election result. In contrast, an emerging market currency trader may have extra information about the countries they invest in. But they’re typically more exposed to idiosyncratic events, which they cannot predict reliably.
Quant funds often face criticism for being black boxes, with trading strategies too complex for investors to understand. People may say, “if you can’t understand it, you should stay away from it”. You could argue discretionary firms are equally black boxes. A discretionary firm is a collection of portfolio managers investing based on human intuition, which is neither understandable nor consistent. At least quantitative trading has the advantage that its process is precisely defined and it’s entirely reproducible over history.
Things like the computer or the cell phone use complex mathematics and technology that most of us can’t hope to understand fully. And yet most of us are prepared, for example, to risk our lives travelling in an aircraft – very, very complex machines with technologies. It appears to make little sense to be happy with these technologies and then to baulk at the idea of quantitative investing, which has similar complexity associated with it.
Conclusion
We trust you have found this article a helpful introduction to the world of quantitative trading. If you have some experience in this area, we will welcome your comments and feedback, always most welcome.