This article aims to implement a portfolio optimization strategy considering two fundamental aspects: the empirical regularities observed in the time series of stock returns, and the views of portfolio managers about these regularities. From an analytical point of view, all the results are examined through an application of the approach of Black and Litterman (1992). In particular, our innovative contribution to the extant literature is the use of the EGARCH-M (exponential GARCH-in-mean) model to formulate a volatility forecast of returns used as an input for determining some subjective views to be included in the Black-Litterman model. The bets of the portfolio manager thus enter into the mechanism of generating expectations about the vector of returns, revealing information about investment opportunities. The results show that the Black-Litterman (BL) model using the EGARCH inputs produces allocations with potentially sizeable benefits. Greater reliance on the implied BL excess returns, in setting the allocations, result in higher risk-return ratio.

The Black–Litterman model: the definition of views based on volatility forecasts

Andi Duqi;TORLUCCIO, GIUSEPPE
2014

Abstract

This article aims to implement a portfolio optimization strategy considering two fundamental aspects: the empirical regularities observed in the time series of stock returns, and the views of portfolio managers about these regularities. From an analytical point of view, all the results are examined through an application of the approach of Black and Litterman (1992). In particular, our innovative contribution to the extant literature is the use of the EGARCH-M (exponential GARCH-in-mean) model to formulate a volatility forecast of returns used as an input for determining some subjective views to be included in the Black-Litterman model. The bets of the portfolio manager thus enter into the mechanism of generating expectations about the vector of returns, revealing information about investment opportunities. The results show that the Black-Litterman (BL) model using the EGARCH inputs produces allocations with potentially sizeable benefits. Greater reliance on the implied BL excess returns, in setting the allocations, result in higher risk-return ratio.
Andi Duqi;Leonardo Franci;Giuseppe Torluccio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/398906
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