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A Quant Model is an automated algorithm created and employed by professional investors in their attempt to capitalize on mispriced securities. Quantitative models offer a way to systematically apply trading rules, financial statement analysis, economic signal evaluation and risk measurement in a unbiased fashion to a large number of securities using inexpensive computing power and a glut of financial data.
Synonym: quantitative model, quantitative equity portfolio management
Quant models can be employed by both highly systematized Quant Funds and by less active bottoms-up fundamental analysis firms which rely on humans to make final investment decisions.
Different flavors of quant models can be linked together to form a whole automated process, often termed 'black box' investing. When different models are linked together it is common for investment professionals to perform checks and balances to help mitigate the risk trading errors. Quant models may include:
For context, it's important to realize that quantitative finance has roots that go back to the 1950s and many third-party risk models have been used by the largest pension plan consultants and institutional investment firms for decades.
Since 2000, the wide dissemination of both computers and data has spawned the growth of many quantitative investment strategies, including firms termed smart beta, statistical arb, high frequency, and global macro. The wide adoption of machine learning and artificial intelligence has added new capabilities and marketing sizzle, particularly in the quantitative equity portfolio management segment.
Kim: Our quant model gets more coverage on our
website than our team.
Liz: Yeah, code has more longevity I guess.
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Still unclear on Quant Modeling? Check out the Quant 101 Series where we provide a free data source and 27 videos to help you understand the nuances of stock and portfolio risk measurement used for quantitative equity portfolio management.
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