Stochastic volatility modelling in portfolio selection via sequential Monte Carlo simulation
by Igor Ferreira Do Nascimento; Pedro Henrique Melo Albuquerque; Yaohao Peng
International Journal of Portfolio Analysis and Management (IJPAM), Vol. 2, No. 3, 2021

Abstract: This paper uses particle filter to estimate daily volatility in the Brazilian financial stocks market and obtain an optimal allocation of assets via Monte Carlo approach. Our volatility model outperforms the Kalman filter besides overcoming non-additivity and non-Gaussian disturbance pattern. The historical statistics use an optimist Black-Litterman priori view to systematise our analysis in a rolling window. Our proposed method has better out-of-sample metrics than Markowitz, Naive (equal assets weight) and Bovespa Index benchmark.

Online publication date: Tue, 15-Jun-2021

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