Your money: Quant strategies for your portfolio
By Karthik Kumar
Most investors tend to get petrified when they look at the term ‘Quant’. The truth, however, is that quant is no rocket science. Sure, there are algorithms and numbers at play here, but it is not entirely different from the discretionary style of investing, that involves an in-depth analysis across a smaller range of companies.
Technically speaking, the quantitative approach uses several algorithms to analyse massive amounts of data. These analyses are used to systematically make trades basis a predefined set of rules. These models, powered by statistical and mathematical models to predict outcomes, use historical data patterns to develop minutely defined rules. These rules are tested to generate alpha or risk adjusted returns.
That is not to say that the fund manager does not have an active role to play, or that quant is purely ‘passive’ in nature relying on historical data only. Essentially, it enables a systematic approach to portfolio construction and fund managers have the liberty to analyse forward-looking data (growth in EPS), concurrent data (price and volume analysis) or historical data (financial statements) Further, rebalancing reduces human interference and portfolio manager biases from seeping in. The processes and portfolios are constantly reviewed and re-evaluated as markets are dynamic in nature.
Given the on-going volatility in the market, quant strategies have an important role to play in an investor’s portfolio. Since quant funds have a different approach to portfolio management wherein, they leverage data to understand exposure to various styles, companies, or industries, they typically end up investing in a portfolio that has limited correlation to their purely actively managed
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