•We present a mixed-integer multistage stochastic model that includes investment opportunities in illiquid and long-term infrastructure projects in the context of renewable energies, which are also ...subject to policy risk.•We present a tailored moving-horizon approach together with suitable approximations and simplifications of the model.•We evaluate these approximations and simplifications in a computational sensitivity analysis.•We derive a final version of the model that can be tackled on a realistic instance by our moving-horizon approach.
Portfolio optimization is an ongoing hot topic of mathematical optimization and management science. Due to the current financial market environment with low interest rates and volatile stock markets, it is getting more and more important to extend portfolio optimization models by other types of investments than classical assets. In this paper, we present a mixed-integer multistage stochastic model that includes investment opportunities in irreversible and long-term infrastructure projects in the context of renewable energies, which are also subject to policy risk. On realistic time scales for investment problems of this type, the resulting instances are by far too large to be solved with today’s most evolved optimization software. Thus, we present a tailored moving-horizon approach together with suitable approximations and simplifications of the model. We evaluate these approximations and simplifications in a computational sensitivity analysis and derive a final model that can be tackled on a realistic instance by our moving-horizon approach.
This paper constructs an estimator for the number of common factors in a setting where both the sampling frequency and the number of variables increase. Empirically, we document that the covariance ...matrix of a large portfolio of US equities is well represented by a low rank common structure with sparse residual matrix. When employed for out-of-sample portfolio allocation, the proposed estimator largely outperforms the sample covariance estimator.
The paper investigates the dynamic risk–return properties of the BRICS (Brazil, Russia, India, China, South Africa) capital markets and models potential time-varying correlations and volatility ...spillover effects with the US stock market. A VAR(1)–GARCH(1,1) framework contributes useful insight into US–BRICS market interactions and expands on a thin past empirical literature. A disaggregated approach pays attention to critical US–BRICS business sectors, namely the industrial and financial sectors. Significant return and volatility transmission dynamics are identified between the US and BRICS stock markets and business sectors. This is a critical input that can affect efficient global portfolio diversification and risk management strategies. Based on this empirical evidence, the study proceeds to assess effective portfolio hedge ratios and to construct optimal portfolio weights for diversified asset allocation to US–BRICS markets and business sectors.
•Global portfolio management strategies consider BRICS as a distinctive asset class and investment style.•Dynamic BRICS-US equity market risk-return properties, correlations and volatility spillover effects are investigated.•A VAR( - Significant return and volatility spillover dynamics between BRICS-US markets and business sectors are identified.•Effective hedge ratios and optimal portfolio weights on BRICS-US stock market and business sector allocation are assessed.
In this paper, we propose a framework for robustifying reward-risk-based portfolio optimization equipped with weak type second-order stochastic dominance constraints that substantially improves upon ...their conventional versions. In particular, relying on stable sub-Gaussian and Student’s t distributions, we extend a robust optimization technique that is very popular among conventional robust statistical estimation methods and consider a new notion of weak second-order stochastic dominance. Furthermore, we study the effects of the distributional assumptions on optimal portfolios while addressing the estimation errors directly in the portfolio optimization process. The empirical analyses show that the robustified formulations improve the performance measures upon their classic versions for out-of-sample portfolios.
•A framework for robustifying reward-risk-based portfolio optimization is proposed.•A new notion of weak second-order stochastic dominance has been adopted.•Estimation errors are directly addressed in the optimization problem itself.•A conventional robust statistical estimation method is extended.•The proposed portfolio selection models yield the best out-of-sample performance.
This paper presents several models addressing optimal portfolio choice, optimal portfolio liquidation, and optimal portfolio transition issues, in which the expected returns of risky assets are ...unknown. Our approach is based on a coupling between Bayesian learning and dynamic programming techniques that leads to partial differential equations. It enables to recover the well-known results of Karatzas and Zhao in a framework
à la
Merton, but also to deal with cases where martingale methods are no longer available. In particular, we address optimal portfolio choice, portfolio liquidation, and portfolio transition problems in a framework
à la
Almgren–Chriss, and we build therefore a model in which the agent takes into account in his decision process both the liquidity of assets and the uncertainty with respect to their expected return.
Analysts strategically allocate more effort to portfolio firms that are relatively more important to their careers. Thus, the other firms the analysts cover indirectly affect a firm’s information ...environment. Controlling for analyst and firm characteristics, we find that an analyst makes more accurate, frequent, and informative earnings forecasts and recommendations for firms ranked higher within her portfolio based on proxies for importance to institutions. A firm’s relative rank widely varies across analysts, but its information environment improves when a larger proportion of analysts consider it to be relatively important. Analysts experience more favorable career outcomes when strategically allocating their efforts.
We evaluate the hypothesis that investors seek portfolios that display attractive return distributions in terms of Prospect Theory (PT). We consider the mutual fund market in the U.S. as an ...interesting testbed because fund investors are known to be return-chasing and about a half of U.S. households own mutual funds. Using monthly flow data from 1999–2019, we find that mutual funds attract higher net flows when they have better PT values. We obtain similar results when PT is replaced with Rank-Dependent Utility, a closely related theory that does not require a particular choice of reference points. Our results are consistent with recent evidence that fund flows exhibit heightened sensitivity to extreme performance measures.
•We study if investors seek mutual funds which are attractive under Prospect Theory.•We use monthly data from the U.S. mutual fund market over the period 1999–2019.•We compute the PT value of each fund’s 60-month excess return distribution.•The fund’s PT value is a positive predictor of its future net flow.•We obtain similar results when PT is replaced with Rank-Dependent Utility.
This article extends the understanding of oil–stock market relationships over the last turbulent decade. Unlike previous empirical investigations, which have largely focused on broad-based market ...indices (national and/or regional indices), we examine short-term linkages in the aggregate as well as sector by sector levels in Europe using different econometric techniques. Our main findings suggest that the reactions of stock returns to oil price changes differ greatly depending on the activity sector. In the out-of-sample analysis we show that introducing oil asset into a diversified portfolio of stocks allows to significantly improve its risk-return characteristics.
This paper studies the vulnerability arising from the corporate loan holdings of collateralized loan obligations (CLOs) using a network reconstruction method and stress tests. Because of the ...portfolio diversification requirement imposed on the management of CLOs, some corporate loans are held by multiple CLOs. This commonality of corporate loans among CLO portfolios suggests the possibility that the diversification of risk in each CLO is not as high as it may appear from the perspective of the entire market. Stress tests show that portfolio diversification of securitization as observed in the CLO loan holdings is not necessarily effective in enhancing system-wide robustness against the idiosyncratic defaults of the underlying assets.
•The vulnerability of CLOs is stress tested using a network reconstruction method.•Due to the portfolio diversification, some corporate loans are held by many CLOs.•CLOs have systemic vulnerability to the idiosyncratic defaults of underlying assets.
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