A background in mathematics and computer coding can help prepare an investor for a career in quantitative trading.
What Is Quantitative Trading?
Quantitative trading relies on mathematical models and statistical analysis to make trading decisions. This type of trading strategy is based on quantitative analysis, where traders look for trends, patterns, or opportunities in financial markets, and in different types of securities and assets, such as stocks, bonds, commodities, and currencies, for potential returns.
A History of Quantitative Trading
Quantitative trading traces its roots to the 20th century, when investors started to make use of quantitative analysis. As early as the 1980s, hedge funds were early adopters of quantitative trading and started implementing trading strategies based on their quantitative analysis research. Hedge fund managers such as James Simons, a former mathematics professor, of Renaissance Technologies used quantitative trading to produce market-beating gains.
Quantitative trading has grown significantly in the past few decades, due in part to advances in technology—specifically computational power—as well as the easy availability of market data and the rapid execution of trades. Traders nowadays can access and analyze vast amounts of historical data—particularly price and volume—to create their models, and their trades tend to be automated.
Large financial institutions and hedge funds tend to be the biggest players in quantitative trading and have the resources to analyze multiple markets at the same time and to be able to quickly implement their trading strategies on large volumes of securities or commodities.
What’s the Difference Between Quantitative Trading and Algorithmic Trading?
While a quantitative trading strategy relies on mathematical or statistical models and algorithms that are based on those models, algorithmic trading relies on the algorithms based on technical analysis and predetermined orders or programs and doesn’t necessarily rely on mathematical or statistical models to execute trades.
How Does Quantitative Trading Differ From High-Frequency Trading?
High-frequency trading doesn’t always rely on quantitative trading strategies to execute trades, but high-frequency trading could be part of a quantitative trading strategy. Algorithms can generate the strategy needed to implement high-frequency trading.
What Are the Limitations of Quantitative Trading?
Quantitative trading requires risk management. There’s no guarantee of achieving the potential returns generated by mathematical or statistical models based on analysis and collection of historical data.
Quantitative trading also tends to be data-driven, so there’s very little in terms of human intuition to guide this type of trading strategy.
How to Become a Quantitative Trader
A background in mathematics or statistics and finance helps in paving the way to become a quantitative trader. A person would need to be comfortable in crunching numbers from a wide range of data on stocks, bonds, commodities, or derivatives. A background in computer coding would also be helpful in developing the algorithms or programs based on mathematical or statistical models to execute trades.