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Intermediate
Quantitative Analysis is the process of evaluating investments based on the systematic review of financial ratios, momentum measures and style factors across broad groups of securities. These strategies benefit from consistency, minimal human bias, breadth and the ability to evaluate many securities using the speed of a computer. Quant investing is often associated with structured, rules-based, academic and scientific approaches to security selection.
Synonym: Quant Investing
For context, as with many industries, quantitative strategies have disrupted the status quo and taken large market share. Investing in the 20th Century was dominated by long-term buy-and-hold fundamental asset management firms and funds like Fidelity Magellan and Dodge & Cox Stock Fund.
In the 21st Century the volume of information available to investors has climbed exponentially, so quantitative approaches involving alpha models, risk models and algorithmic trading models gained popularity. Not only that, but the marketing blitz of thematic funds through ETFs has made it easier to gain assets without a proven approach and long-term track record. It is for this reason that strategies marketed as smart beta, factor portfolios, tilt funds and minimum variance funds took market share from long-established stalwarts.
Bev: I'd like to see specific risk and more
quantitative analysis measures for our funds.
Ann: I'm good with that, but we don't want
to mention the 'Q' word or we'll be labeled.
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Quantitative
Still unclear on Quantitative Analysis? Check out the Quant 101 Series of 27 video tutorials in Excel with a free-to-use data set.
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