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- W4285220646 abstract "Portfolio construction by selecting the right combination of securities is the subject matter of portfolio optimization, making efforts to optimize expected return on risk. The investors are risk averse, and they always make an effort to select those combinations of securities in the portfolio which will lead to minimization of risk and maximization of expected return. Thus, risk budgeting is one of the common phenomena in portfolio optimization. With the passage of time, a number of mathematical techniques have been developed for risk budgeting in the ting portfolio construction. In this paper, a gradient-based optimization (GBO) approach, which is a newly established technique, has been proposed for risk-budgeting portfolio optimization to maximize expected return. An effort has been made to do experiment by using GBO on the real dataset collected from the S&P BSE Sensex of Bombay Stock Exchange (30 stocks) to make a comparison with the results of genetic algorithms. Study confirms the superior performance of proposed approach to its considered peer." @default.
- W4285220646 created "2022-07-14" @default.
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- W4285220646 date "2022-01-01" @default.
- W4285220646 modified "2023-09-28" @default.
- W4285220646 title "A Risk-Budgeted Portfolio Selection Strategy Using Novel Metaheuristic Optimization Approach" @default.
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- W4285220646 doi "https://doi.org/10.1007/978-981-16-9416-5_14" @default.
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