We have finally got back to writing about finance. After a rather long break from all writing and the last few months being focused on accounting and and personal finance, its good to be back into a more finance centered topic. So today we are going to be looking into the question what is a Quant Trader.

What is a Quant Trader?

A trader is simply a person who buys and sells financial assets in any financial Market either for themselves or on behalf of another person or institution. 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 where as l traders tend to hold assets for shorter periods of time usually to capitalise on short term price changes.

Most traders rely on intuition or experience. They will either follow rules that they have been taught or they might rely on specific technical analysis learned over the years. Where as 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.

A lot of the trading rules tend to be counter intuitive, often coming from behavioural finance and involve buying when the human natural instinct is to sell or vice versa. One of the benefits of trading systematically is that you devise a game plan before hand 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-semantic trader might feel based upon their experience, whenever the market is say moving up sharply, they might tend to think that it will continue. Where as a systematic trader might have a very similar feeling, but they will instead 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 manage a trade like this. How long they should for? Should they cut their losses quickly if the trade is not working out? Or should they hold on longer.

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 the analysis that needs to be done.

Quant traders don’t want to just build a trading method and let it go off and trade. They usually maintain a healthy skepticism about their trading model. Quants are generally aware that no trade works 100 of the time, even great trades can eventually stop working.

Quants pay attention to events that invalidate their strategies or events that are not captured in their data sets. For example a low interest rate environment would beg the question of how to risk manage bond positions. There may be concern about risk being skewed against long positions that were large rises more likely than falls. In this example we would develop ways to measure and optimally feed into all events, not just interest rate, a general solution is found for general problem.

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 then they usually also need to learn how to finance and statistics to over lay that on top of 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 key thing is not so much how large their positions are, but how large they are when compared to the market being traded.

In finance we use the term 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 things like transaction costs and liquidity in the assets that they trade. Allocations to these assets are usually scaled accordingly.

A focus on data technology allows quant traders to accurately estimate trading costs on any assets in their portfolios and to estimate and control the cost of liquidating these positions if necessary.

The quant trader are sometimes accused of trading what would appear 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 hypothesis 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 momentum of asset prices in markets.

The key difference is that given a hypothesis a quant trader will take the next natural step as scientists do. They use the wealth of available historical data and statistical techniques to test, to 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 firm with really long track records of profitable performance. You can think of these firms as a collection of scientists constantly collecting evidence in support of their style of investing.

Risks Involved for a Quant Trader

Like all investments quant funds are exposed to surprise market events, such as central bank interventions, geopolitical events or of course global events we see unfolding before us now. They are however no more exposed than traditional macro or fundamental traders are to market surprises like these. The world is full of events that are very difficult or even impossible 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 a little extra information about the countries they invest in. But they’re typically much more exposed to idiosyncratic events, which they cannot hope to predict reliably.

Quant funds are often accused of being black boxes where the trading strategies are too complex for investors to understand. People may say “if you can’t understand it you should stay away from it”. It could be argued though that discretionary firms can be equally seen as black boxes. A discretionary firm is simply 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 fully reproducible over history,

Things like the computer or the cell phone use complex mathematics and technology that most of us can’t hope to fully understand. And yet most of us are prepared let’s say for example to risk our lives travelling in an aircraft that are now days very complex machines using very advanced 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 useful introduction into the world of quantitative trading. If you have some experience in this area we would very much welcome your comments and feedback, always most welcome.

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