Dynamic risk spillovers and portfolio risk management between precious metals and global foreign exchange markets

This study examines portfolio management and risk spillovers between four major precious metals (gold, silver, palladium and platinum) and 20 important U.S. exchange markets. To this end, we employ the multivariate DECO-GARCH model and the spillover index developed by Diebold and Yilmaz (2014, 2016) to examine the spillovers between those metal prices and the exchange rates and design portfolios and hedging strategies using different risk measures. The results show evidence of weak average conditional equicorrelations among the considered markets over time, excluding the turbulent 2008–2010 period. Furthermore, the precious metals (excluding platinum) and the currencies (with the exception of the Australian, Brazilian, Denmark, Euro, Mexican, Norwegian, New Zealand and Swedish currencies) are net receivers of shocks. Finally, the four precious metals provide strong risk and downside risk reductions, underscoring the usefulness of including precious metals in a traditional foreign exchange-dominated portfolio.     

Is bitcoin a safe haven or a hedging asset? Evidence from China

Based on daily data about Bitcoin and six other major financial assets (stocks, commodity futures (commodities), gold, foreign exchange (FX), monetary assets, and bonds) in China from 2013 to 2017, we use a VAR-GARCH-BEKK model to investigate mean and volatility spillover effects between Bitcoin and other major assets and explore whether Bitcoin can be used either as a hedging asset or a safe haven. Our empirical results show that (i) only the monetary market, i.e., the Shanghai Interbank Offered Rate (SHIIBOR) has a mean spillover effect on Bitcoin and (ii) gold, monetary, and bond markets have volatility spillover effects on Bitcoin, while Bitcoin has a volatility spillover effect only on the gold market. We further find that Bitcoin can be hedged against stocks, bonds and SHIBOR and is a safe haven when extreme price changes occur in the monetary market. Our findings provide useful information for investors and portfolio risk managers who have invested or hedged with Bitcoin.     

股指期货的套期保值问题

中国金融市场即将推出股票指数期货。本文吸收和借鉴了国外的研究成果,对股指期货的套期保值问题进行了系统研究,采用方差法和β系数法对风险最小化的套期保值比率进行了充分论证,并结合案例进行了模拟计算。本文根据资本资产定价模型,建立了一元线性回归方程,对流行的β系数法进行了检验和重要修正,对套期保值实践具有重要的指导意义。     

最优动态汇率风险套期保值模型研究

构建一个最优动态汇率风险套期保值理论模型,并将其套期保值效率与静态策略进行实证对比.采用对角BEKK模型来捕捉货币现货与期货市场的交互影响,从而刻画风险最小化套期比率的动态特征,结果表明,套期保值能减少汇率风险,但具体的套期保值策略的效率高低排序与避险频率相关.     

Information,hedging demand,and institutional investors: Evidence from the Taiwan Futures Exchange

This paper examines the effect of hedging demand by various types of institutional investor on subsequent returns and volatility. Using data from the Taiwan Futures Exchange, empirical results indicate that the hedging demand of foreign investors has a significant negative impact on subsequent returns and volatility. In addition, trading strategies based on the extreme hedging demand of foreigners are positively correlated with trading performance. Furthermore, there is evidence to show that returns (volatility) also affect the subsequent hedging demand of foreign investors, suggesting a feedback relation. Finally, the hedging demand of foreign investors has a greater impact on subsequent returns and volatility after global financial turmoil. Accordingly, this paper concludes that foreign investors are informed hedgers in the Taiwan futures market, especially after global financial turmoil.     

The generalized value at risk admissible set: constraint consistency and portfolio outcomes

Generalized value at risk (GVaR) adds a conditional value at risk or censored mean lower bound to the standard value at risk and considers portfolio optimization problems in the presence of both constraints. For normal distributions the censored mean is synonymous with the statistical hazard function, but this is not true for fat-tailed distributions. The latter turn out to imply much tighter bounds for the admissible portfolio set and indeed for the logistic, an upper bound for the portfolio variance that yields a simple portfolio choice rule. The choice theory in GVaR is in general not consistent with classic Von Neumann–Morgenstern utility functions for money. A re-specification is suggested to make it so that gives a clearer picture of the economic role of the respective constraints. This can be used analytically to explore the choice of portfolio hedges.     

GARCH options via local risk minimization

We apply a quadratic hedging scheme developed by Föllmer, Schweizer, and Sondermann to European contingent products whose underlying asset is modeled using a GARCH process and show that local risk-minimizing strategies with respect to the physical measure do exist, even though an associated minimal martingale measure is only available in the presence of bounded innovations. More importantly, since those local risk-minimizing strategies are in general convoluted and difficult to evaluate, we introduce Girsanov-like risk-neutral measures for the log-prices that yield more tractable and useful results. Regarding this subject, we focus on GARCH time series models with Gaussian innovations and we provide specific sufficient conditions concerning the finiteness of the kurtosis, under which those martingale measures are appropriate in the context of quadratic hedging. When this equivalent martingale measure is adapted to the price representation we are able to recover the classical pricing formulas of Duan and Heston and Nandi, as well as hedging schemes that improve the performance of those proposed in the literature.     

Pricing options on illiquid assets with liquid proxies using utility indifference and dynamic-static hedging

This work addresses the problem of optimal pricing and hedging of a European option on an illiquid asset Z using two proxies: a liquid asset S and a liquid European option on another liquid asset Y. We assume that the S-hedge is dynamic while the Y-hedge is static. Using the indifference pricing approach, we derive a Hamilton–Jacobi–Bellman equation for the value function. We solve this equation analytically (in quadrature) using an asymptotic expansion around the limit of perfect correlation between assets Y and Z. While in this paper we apply our framework to an incomplete market version of Merton’s credit-equity model, the same approach can be used for other asset classes (equity, commodity, FX, etc.), e.g. for pricing and hedging options with illiquid strikes or illiquid exotic options.