The popularity of quantitative trading has grown over the years for several reasons:
- Advanced technology: Increased computing power and technological advances have made the processing and analysis of large data sets more accessible and affordable. This enables more players to adopt quantitative strategies.
- Data availability: There is an explosion in the amount and variety of data available to traders, ranging from asset prices to alternative data such as sentiment on social networks, weather data, and more.
- Academic research: Universities and research institutions have produced an increasing volume of work on quantitative strategies, which has fostered greater understanding and acceptance of these methods in the financial industry.
- Disappointment with discretionary strategies: Following the 2008 financial crisis, many investors became disenchanted with the performance of discretionary managers, and sought more systematic, data-driven strategies.
- Automation and speed: Quantitative strategies enable the trading process to be automated, which can reduce costs, increase execution speed and minimize human error.
- Diversification: For institutional investors, quantitative strategies offer an uncorrelated source of return that can diversify a traditional portfolio.
- Market competition and efficiency: Financial markets are increasingly competitive. Inefficiencies are quickly exploited, driving players to adopt quantitative methods to discover and exploit small advantages.
Take your algo trading strategies to the next level
Use our strategy database to develop quantitative strategies faster.
✔️ Research papers
✔️ Trading rules
✔️ Performance metrics
✔️ Python code
👉 Try our Database of Trading Strategies Now →
That said, quantitative trading is not without risk. Strategies can be based on models that fail to account for unforeseen events or "black swans". What's more, as more and more players adopt similar strategies, there is a risk of "congestion" where the potential benefits of certain strategies diminish.
In short, although quantitative trading offers many advantages and has gained in popularity thanks to technological advances, the availability of data and disappointments with traditional methods, it is essential for traders and investors to understand the associated risks.
💡 Read more:
- Trading strategies papers with code on Equities, Cryptocurrencies, Commodities, Currencies, Bonds, Options
- A curated list of awesome libraries, packages, strategies, books, blogs, and tutorials for systematic trading
- A bunch of datasets for quantitative trading
- A website to help you become a quant trader and achieve financial independence