Risk management of precious metals

This paper examines volatility and correlation dynamics in price returns of gold, silver, platinum and palladium, and explores the corresponding risk management implications for market risk and hedging. Value-at-Risk (VaR) is used to analyze the downside market risk associated with investments in precious metals, and to design optimal risk management strategies. We compute the VaR for major precious metals using the calibrated RiskMetrics, different GARCH models, and the semi-parametric Filtered Historical Simulation approach. The best approach for estimating VaR based on conditional and unconditional statistical tests is documented. The economic importance of the results is highlighted by assessing the daily capital charges from the estimated VaRs.     

Macroeconomic uncertainty and bank lending: The case of Ukraine

This study investigates the link between bank lending behavior and country-level instability. Our dynamic model of bank's profit maximization predicts a non-monotonic relationship between bank lending and macroeconomic uncertainty. We test this proposition using a panel of Ukrainian banks over the 2003Q2–2008Q2 period. The estimates indicate that banks decrease their lending ratio in times of substantial economic volatility, which could be explained by higher risk aversion of bank managers. Additionally, small and least profitable banks are less likely to be affected by changes in the macroeconomic environment compared to their large and most profitable peers. This outcome is robust with respect to the different measurements of macroeconomic uncertainty.     

Risk shocks and housing supply: A quantitative analysis

This paper analyzes the role of stochastic uncertainty in a multi-sector housing model with financial frictions. We include time varying uncertainty (i.e. risk shocks) in the technology shocks that affect housing production and provide estimates of the time-series properties of risk shocks by using firm level productivity data. The analysis demonstrates that risk shocks to the housing production sector are a quantitatively important impulse mechanism for understanding housing price movements. Specifically, the model can match the volatility of housing prices observed in the data. It is also demonstrated that adjustment costs are important in replicating the contemporaneous correlation of housing prices with GDP and residential investment. Critically, bankruptcy costs act as an endogenous markup factor in housing prices and are an important determinant of house price volatility. However, in comparison to housing demand shocks, risk shocks have low explanatory power for real quantities.     

Do stock markets discipline US Bank Holding Companies: Just monitoring,or also influencing?

This paper presents evidence that bank managers adjust key strategic variables following a risk and/or valuation signal from the stock market. Banks receive a risk signal when they exhibit substantially higher (semi-)volatility compared to the best performing bank(s) with similar characteristics, and a valuation signal when they are undervalued relative to the average bank with similar characteristics. We document, using a partial adjustment model, that bank managers adjust the long-term target value of key strategic variables and the speed of adjustment towards those targets following a risk and/or negative valuation signal. We interpret this as evidence of stock market influencing. We show that our results are unlikely to be driven by indirect influencing by regulators, subordinated debtholders, retail or wholesale depositors. Finally, we show that the likelihood that banks receive a risk and/or valuation signal increases with opaqueness, managerial discretion and specialization.     

Volatility risk and economic welfare

This paper examines the effects of time-varying volatility on welfare. I construct a tractable endogenous growth model with recursive preferences, stochastic volatility, and capital adjustment costs. The model shows that a rise in volatility can decelerate growth in the absence of any level shocks. In contrast to level risk, which is always welfare reducing for a risk-averse household, volatility risk can increase or decrease welfare, depending on model parameters. When calibrated to U.S. data, the model finds that the welfare cost of volatility risk is largely negligible under plausible model parameterizations.     

建设工程项目风险管理与保险

在我国的许多项目中,由于没有风险意识而造成的损失是巨大的,同样,风险和盈利是同时存在的,通常风险大的工程项目才有较高的盈利,降低风险的目的就是减少不必要的成本开支,以实现目标利润,创造良好的经济效益。这样,风险管理就成为项目管理的重点之一。     

State Prices of Conditional Quantiles: New Evidence on Time Variation in the Pricing Kernel

We develop a set of statistics to represent the option‐implied stochastic discount factor and we apply them to S&P 500 returns between 1990 and 2012. Our statistics, which we call state prices of conditional quantiles (SPOCQ), estimate the market's willingness to pay for insurance against outcomes in various quantiles of the return distribution. By estimating state prices at conditional quantiles, we separate variation in the shape of the pricing kernel from variation in the probability of a particular event. Thus, without imposing strong assumptions about the distribution of returns, we obtain a novel view of pricing‐kernel dynamics. We document six features of SPOCQ for the S&P 500. Most notably, and in contrast to recent studies, we find that the price of downside risk decreases when volatility increases. Under a standard asset pricing model, this result implies that most changes in volatility stem from fluctuations in idiosyncratic risk. Consistent with this interpretation, no known systematic risk factors such as consumer sentiment, liquidity or macroeconomic risk can account for the negative relationship between the price of downside risk and volatility. Copyright © 2016 John Wiley & Sons, Ltd.     

Valuing lead time

When do short lead times warrant a cost premium? Decision makers generally agree that short lead times enhance competitiveness, but have struggled to quantify their benefits. Blackburn (2012) argued that the marginal value of time is low when demand is predictable and salvage values are high. de Treville et al. (2014) used real-options theory to quantify the relationship between mismatch cost and demand volatility, demonstrating that the marginal value of time increases with demand volatility, and with the volatility of demand volatility. We use the de Treville et al. model to explore the marginal value of time in three industrial supply chains facing relatively low demand volatility, extending the model to incorporate factors such as tender-loss risk, demand clustering in an order-up-to model, and use of a target fill rate that exceeded the newsvendor profit-maximizing order quantity. Each of these factors substantially increases the marginal value of time. In all of the companies under study, managers had underestimated the mismatch costs arising from lead time, so had underinvested in cutting lead times.     

基于CVaR与平均离差波动限制的投资组合模型

提出了一种基于CVaR的投资组合模型,对组合资产收益率不做正态分布假设,用MAD模型作为一个约束条件,实现波动性度量限制,用上凸效用函数作为一个约束条件,表示风险资产交易费用。实验结果表明,该模型满足实际投资要求,符合实际投资规律,与M-V模型和原始CVaR模型相比具有波动性和风险价值最小化的优势。     

Controlling risks to ensure financial stability and reducing volatility

The 11th International Risk Management Conference was held at the University of Paris‐Dauphine and the EM LYON Business School (Paris Campus) in June 2018. The conference theme “1968–2018: From Z‐Score to Contemporary Risk Management, 50 Years of Risk Measurement and Management” was selected as a means to showcase the many ways that financial risk measurement has evolved and impacted financial risk management in banks and corporations as well as the tools used by asset managers and market regulators. The four papers included in this special issue of the Journal of International Financial Management and Accounting focus on a wide range of issues: How small differences in credit ratings effect the speed of adjustment in corporate leverage, the impact of using soft variables to assess default probabilities in European corporations, a new approach to measuring a company's intrinsic risk, and the effectiveness of short sale circuit breaker rules to limit stock price volatility. Our Foreword highlights the main findings of these papers and offers our assessment of the lessons they provide for financial managers and policymakers.     

Downside risk management and VaR-based optimal portfolios for precious metals,oil and stocks

Value-at-Risk (VaR) is used to analyze the market downside risk associated with investments in six key individual assets including four precious metals, oil and the S&P 500 index, and three diversified portfolios. Using combinations of these assets, three optimal portfolios and their efficient frontiers within a VaR framework are constructed and the returns and downside risks for these portfolios are also analyzed. One-day-ahead VaR forecasts are computed with nine risk models including calibrated RiskMetrics, asymmetric GARCH type models, the filtered Historical Simulation approach, methodologies from statistics of extremes and a risk management strategy involving combinations of models. These risk models are evaluated and compared based on the unconditional coverage, independence and conditional coverage criteria. The economic importance of the results is also highlighted by assessing the daily capital charges under the Basel Accord rule. The best approaches for estimating the VaR for the individual assets under study and for the three VaR-based optimal portfolios and efficient frontiers are discussed. The VaR-based performance measure ranks the most diversified optimal portfolio (Portfolio #2) as the most efficient and the pure precious metals (Portfolio #1) as the least efficient.     

Price uncertainty and the effect of capital costs in a point in-point out inventory investment

This paper analyzes a point in-point out inventory investment under price uncertainty. The optimal quantity is determined by maximizing the expected value of the investor's risk preference function, which is a function of profit. Using an exponential risk preference function, the adjustment in the optimal quantity stemming from a change in the interest rate is investigated. The main conclusion is that the sign of the adjustment depends both on how profit is expressed and on the type of price distribution applied. Contrary to what is assumed in conventional managerial control practices, a rise in the interest rate might lead to an increase in the optimal quantity when present value serves as a measure of profit.     

中国银行业绩高增长背后的风险因素分析

本文首先用一个简单的垄断竞争模型分析了各种因素对银行业绩的影响,然后用面板回归分析模 型对具有代表性的14家银行进行了回归分析,揭示了银行利润与各种因素的关系。分析表明,规模扩张和利差是中国银行利润增长决定因素,不良贷款率和存贷比对银行利润有负面作用,但利率、法定准备金率等变量与利润的关系与静态理论的预测相反,表明货币政策操作往往是顺周期的,对货币政策的滞后效应估计不足,需要加强对经济周期规律性研究,提高货币政策的前瞻性。本文还分析了当前经济增长结构性减速、利率市场化给银行带来的可能影响,从道德风险、国内外利差和汇率波动角度分析了银行和宏观经济面临的风险。     

Stock market reactions to upside and downside volatility of Bitcoin: A quantile analysis

We investigate how sensitive developed and emerging equity markets are to volatility dynamics of Bitcoin during tranquil, bear, and bull market regimes. Intraday price fluctuations of Bitcoin are represented by three measures of realized volatility, viz. total variance, upside semivariance, and downside semivariance. Our empirical analysis relies on a quantile regression framework, after orthogonalizing raw returns with respect to an array of relevant global factors and accounting for structural shifts in the series. The results suggest that developed-market returns are positively related to the realized variance proxy across various market conditions, while emerging-market returns are positively (negatively) correlated with realized variance during bear (normal and bull) market periods. The upside (downside) component of realized variance has a negative (positive) influence on returns of either market category, and the dependence structure is highly asymmetric across the return distribution. Additionally, we document that developed and emerging markets are more sensitive to downside volatility than to upside volatility when they enter tranquil or bull territory. Our results offer practical implications for policymakers and investors.     

Bond risk, bond return volatility, and the term structure of interest rates

This paper explores the time variation in the bond risk, as measured by the covariation of bond returns with stock returns and consumption growth, and in the volatility of bond returns. A robust stylized fact in empirical finance is that the spread between the yields on long- and short-term bonds forecasts future excess returns on bonds at varying horizons positively; in addition, the short-term nominal interest rate forecasts both the stock return volatility and the exchange rate volatility positively. This paper presents evidence that movements in both the short-term nominal interest rate and the yield spread are positively related to changes in the subsequent realized bond risk and bond return volatility. The yield spread appears to proxy for business conditions, while the short rate appears to proxy for inflation and economic uncertainty. A decomposition of bond betas into a real cash flow risk component and a discount rate risk component shows that yield spreads have offsetting effects in each component. A widening yield spread is correlated with a reduced cash-flow (or inflationary) risk for bonds, but it is also correlated with a larger discount rate risk for bonds. The short rate only forecasts the discount rate component of the bond beta.     

Is small beautiful? Size effects of volatility spillovers for firm performance and exchange rates in tourism

This paper examines the size effects of volatility spillovers for firm performance and exchange rates with asymmetry in the Taiwan tourism industry. The analysis is based on two conditional multivariate models, BEKK–AGARCH and VARMA–AGARCH, in the volatility specification. Daily data from 1 July 2008 to 29 June 2012 for 999 firms are used, which covers the Global Financial Crisis. The empirical findings indicate that there are size effects on volatility spillovers from the exchange rate to firm performance. Specifically, the risk for firm size has different effects from the three leading tourism sources to Taiwan, namely USA, Japan, and China. Furthermore, all the return series reveal quite high volatility spillovers (at over 60%) with a one-period lag. The empirical results show a negative correlation between exchange rate returns and stock returns. However, the asymmetric effect of the shock is ambiguous, owing to conflicts in the significance and signs of the asymmetry effect in the two estimated multivariate GARCH models. The empirical findings provide financial managers with a better understanding of how firm size is related to financial performance, risk and portfolio management strategies that can be used in practice.     

Conditional value-at-risk forecasts of an optimal foreign currency portfolio

This study provides daily conditional value-at-risk (C-VaR) forecasts for a foreign currency portfolio comprising the USD/EUR, USD/JPY, and USD/BRL currencies. To do so, we estimate multivariate stochastic volatility models with time-varying conditional correlations using a Bayesian Markov chain Monte Carlo algorithm. Then, given the model-specific currency return density forecasts, we make the optimal portfolio choice by minimizing the C-VaR through numerical optimization. According to out-of-sample experiment, including emerging markets into the currency basket is essential for downside risk management, and considering model uncertainty as well as the parameter uncertainty can improve the portfolio performance.     

Switching interest rate sensitivity regimes of U.S. Corporates

We study interest rate sensitivities of U.S. investment grade BBB-rated and high yield corporate bonds over the period of 2001–2016. Our methodology assesses the capital gains of corporate bond portfolios and risk-free government bond portfolios, using average coupon and blended yield indices for the U.S. market. For both, U.S. BBB and high yield corporate bonds, we evidence the switching, from positive to negative interest rate sensitivity, occurring over the transition from the normal economic conditions to the periods of economic distress and vice-versa. The proposed theoretical explanation of such binary behavior posits an interrelation between interest rate and creditworthiness of issuers, which varies according to the phases of the business cycle. This research advances an economic understanding of interest rate risk management and sheds light on how financial institutions may develop strategies that hedge against downside risk.     

COVID-19 and asymmetric volatility spillovers across global stock markets

In this study, I improve the assessment of asymmetry in volatility spillovers, and define six asymmetric spillover indexes. Employing Diebold-Yilmaz spillover index, network analysis, and my developed asymmetric spillover index, this study investigates the time-varying volatility spillovers and asymmetry in spillovers across stock markets of the U.S., Japan, Germany, the U.K., France, Italy, Canada, China, India, and Brazil based on high-frequency data from June 1, 2009, to August 28, 2020. I find that the global markets are well connected, and volatility spillovers across global stock markets are time-varying, crisis-sensitive, and asymmetric. Developed markets are the main risk transmitters, and emerging markets are the main risk receivers. Downside risk dominates financial contagion effects, and a great deal of downside risk spilled over from stock markets of risk transmitters into the global markets. Moreover, during the coronavirus recession, the total degree of volatility spillover is staying at an extremely high level, and emerging markets are the main risk receivers in the 2020 stock markets crash.