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An Introduction to Quantamental Investing

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Document pages: 8 pages

Abstract: Stock selection to construct a portfolio is the eventual challenge for any investment professional and for a commonplace investor too. There are certain tools which assist in the stock selection process, right from fundamental analysis, technical analysis, Markowitz model, Single & Multi-Index models to Traditional & Modern portfolio theories and Black-Scholes Model. All these techniques necessitate gigantic amount of data pertaining to companies and their stocks. Evaluating the available information from various sources and quantum of data poses a great test for investment process. To construct a portfolio with four securities out of a given number, say, nine securities, investors have to evaluate all possible set portfolios which comes approximately ten thousand combinations. In a volatile market conditions, evaluating such a huge amount of data is not an easy task for humans and there will be always risk of ignoring attractive stocks. Therefore, the gap is being filled by a new approach known as ‘quantamental investing’. The term quantamental investment or quant investing refers to the combination of computer driven and human driven research. Artificial Intelligence (AI) and Machine Learning coupled with Big Data Analytics have led to the concept of Quantamental Investing. This paper presents a descriptive analysis of quantamental investing, merits & demerits and approaches in quantamental investing.

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