A quantitative hedge fund (or quant hedge fund) is a hedge fund that relies on statistical models to come up with investment decisions. The statistical models can be systematic or algorithmic strategies. The models can focus on any asset class including commodities, derivatives, equities or foreign exchange. Quantitative models are used to implement trading decisions after volumes of data are analysed by relating them to indicators like the growth of gross domestic products, price to earnings and other economic factors

What is different about a quantitative hedge fund?

Instead of trading rules identified by employees,  a quantitative hedge fund uses automatic trading rules. The style for managing these hedge funds varies from traditional fund managers. They are categorised as alternative investments. Therefore, they can charge high management fees compared to funds employing traditional strategies. A quantitative hedge fund does not use any subjective or qualitative information that cannot be analysed statistically and aggregated systematically.

Market data

Access to a broad range of market data has been increasing due to the fuelling growth of quantitative hedge fund models. As well as technology that offers solutions to use big data. The growing innovation and financial technology development around automation has widened the data sets that quant fund managers are working with. For this reason, there is a broader analysis of time horizons and scenarios creating many trading signals to rely on.

Why use a quantitative fund manager?

The main reason  is because there are diversification benefits in the portfolio of the traditional assets. This includes  equities and bonds. Most fund managers are doing well using quantitative trading models. As a result, these models have gained popularity relative to fundamental strategies.  Quantitative hedge funds embed risk management into the model. As well as respond to changes in quickly and automatically.