Optimal Asset Allocation Subject to Withdrawal Risk and Solvency Constraints

This paper investigates the optimal asset allocation of a financial institution whose customers are free to withdraw their capital-guaranteed financial contracts at any time. In accounting for the asset-liability mismatch risk of the institution, we present a general utility optimization problem in a discrete-time setting and provide a dynamic programming principle for the optimal investment strategies. Furthermore, we consider an explicit context, including liquidity risk, interest rate, and credit intensity fluctuations, and show by numerical results that the optimal strategy improves both the solvency and asset returns of the institution compared to a standard institutional investor’s asset allocation.

Testing the Dimensionality of Policy Shocks

This paper provides a nonparametric test for deciding the dimensionality of a policy shock as manifest in the abnormal change in asset returns' stochastic covariance matrix, following the release of a macroeconomic announcement. We use high-frequency data in local windows before and after the event to estimate the covariance jump matrix, and then test its rank. We find a one-factor structure in the covariance jump matrix of the yield curve resulting from the Federal Reserve's monetary policy shocks prior to the 2007-2009 financial crisis. The dimensionality of policy shocks increased afterwards due to the use of unconventional monetary policy tools.

A Bayesian Semiparametric Realized Stochastic Volatility Model

This paper proposes a semiparametric realized stochastic volatility model by integrating the parametric stochastic volatility model utilizing realized volatility information and the Bayesian nonparametric framework. The flexible framework offered by Bayesian nonparametric mixtures not only improves the fitting of asymmetric and leptokurtic densities of asset returns and logarithmic realized volatility but also enables flexible adjustments for estimation bias in realized volatility. Applications to equity data show that the proposed model offers superior density forecasts for returns and improved estimates of parameters and latent volatility compared with existing alternatives.

An Empirical Assessment of COVID-19 Pandemic on Asset Market Responses in India

The study investigates the financial market’s response during the period of last nine months starting from the day when first COVID-19 case was confirmed in India. This paper attempts to gauge the impact of rise in COVID-19 confirmed number of cases on stock market as well as commodities market returns. A multi-model approach is used in the current research to assess the relationship between daily number of confirmed cases of COVID-19 and movement of asset returns from January 2020 to September 2020. The findings reveal that though financial markets exhibited asymmetric volatility clustering, it could not be traced to COVID-19 pandemic for the period under study in India.

The Log-Asset Dynamic with Euler–Maruyama Scheme under Wishart Processes

This article deals with Wishart process which is defined as matrix generalization of a squared Bessel process. We consider a single risky asset pricing model whose volatility is described by Wishart affine diffusion processes. The multifactor volatility specification enables this model to be flexible enough to describe the market prices for short or long maturities. The aim of the study is to derive the log-asset returns dynamic under the double Wishart stochastic volatility model. The corrected Euler–Maruyama discretization technique is applied in order to obtain the numerical solution of the log-asset return dynamic under Bi-Wishart processes. The numerical examples show the effect of the model parameters on the asset returns under the double Wishart volatility model.

Analisis Pengaruh Manajemen Risiko Terhadap Kinerja Keuangan Perbankan yang Terdaftar di BEI

Banks have a strategic role in national economic development. The large number of funds managed by banks causes the risks faced are also very large. Very supportive if the risk affects the bank's performance, therefore banks are required to implement risk management. After being selected using the purposive sampling method, the sample banks were 21 banks. Tests carried out with multiple regression analysis show that bad loans and operating expenses on operating income negatively affect asset returns. In contrast to the loan to deposit ratio which does not affect the return on assets. Based on the results of this study, it is necessary to optimize credit and operational risks which are considered capable of maintaining the stability of bank profitability.

Implied Ambiguity: Mean-Variance Inefficiency and Pricing Errors

We investigate the optimal portfolio choice problem for an investor who has a utility function of the smooth ambiguity model. We identify necessary and sufficient conditions for a given portfolio to be optimal for such an investor. We define the implied ambiguity of a portfolio as the smallest ambiguity aversion coefficient with which the portfolio is optimal, and the measure of ambiguity perception as the part of the variability in asset returns that can be attributed to the ambiguity. We show that there are one-to-one relations between the implied ambiguity, the Sharpe ratio, and the pricing errors when the portfolio is taken as the pricing portfolio, and that the measure of ambiguity perception is determined by the Sharpe ratio and the alpha. Based on the U.S. stock market data, we assess how ambiguity averse the representative investor is and what types of stocks the investor perceives as having more ambiguous returns than others. This paper was accepted by Manel Baucells, behavioral economics and decision analysis.