Abstract

This study examines the effectiveness of rotating in and out of a sector based on the stage of a business cycle. Here, we assume that business cycles exist, are part of nature, and neither repeat at a regular intervals nor their intensity or duration are constant. However, we assume that with a perfect set of high-frequency indicators, an investor can perfectly time the business cycle phases. This study divides India's real GDP growth into High, Moderate, Low, and Minuscule growth. GDP Growth is used as an indication of a start/end of a business cycle. In an investor were to create four different portfolios, optimized for each of the business cycle phases, will he/she be able to outperform the SENSEX returns of the buy-and-hold strategy? Here, an attempt to create such four models has been done using Python based on Markowitz Efficient Frontier and Modern Portfolio Theory. Once developed using historical data from September 2005 to March 2020, the study tries to estimate its performance in out-of-sample data, i.e., June 2021-April 2023. Can an investor make higher absolute (not alpha) returns with perfect foresight? We try to evaluate such in this study. Some obvious drawbacks of this model are inapplicability for large investors, mutual funds, etc. However, an investor with small capital and access to data can have an accurate foresight, thus, applying the model in practice can earn higher absolute returns. Even with a tax consideration of moving in and out of sectors, an investor can make a higher absolute return compared to a buy-and-hold strategy.

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