Commodity futures hedging,risk aversion and the hedging horizon

This paper examines the impact of management preferences on optimal futures hedging strategy and associated performance. Applying an expected utility hedging objective, the optimal futures hedge ratio is determined for a range of preferences on risk aversion, hedging horizon and expected returns. Empirical results reveal substantial hedge ratio variation across distinct management preferences and are supportive of the hedging policies of real firms. Hedging performance is further shown to be strongly dependent on underlying preferences. In particular, hedgers with high risk aversion and short horizon reduce hedge portfolio risk but achieve inferior utility in comparison to those with low aversion.     

Adapted hedging

Exponentials of squared returns in Gaussian densities, with their consequently thin tails, are replaced by the absolute return to form Laplacian and exponentially tilted Laplacian densities at unit time. Scaling provides densities at other maturities. Stochastic processes with these marginals are identified. In addition to a specific local volatility model the densities are consistent with the difference of compound exponential processes taken at log time and scaled by the square root of time. The underlying process has a single parameter, the constant variance rate of the process. Delta hedging using Laplacian and Asymmetric Laplacian implied volatilities are developed and compared with Black Merton Scholes implied volatility hedging.The hedging strategies are implemented for stylized businesses represented by dynamic volatility indexes. The Laplacian hedge is seen to be smoother for the skew trade. It also performs better through the financial crisis for the sale of strangles. The Laplacian and Gaussian models are then synthesized as special cases of a model allowing for other powers between unity and the square. Numerous hedging strategies may be run using different powers and biases in the probability of an up move. Adapted strategies that select the best performer on past quarterly data can dominate fixed strategies. Adapted hedging strategies can effectively reduce drawdowns in the marked to market value of businesses trading options.     

Deep hedging

We present a framework for hedging a portfolio of derivatives in the presence of market frictions such as transaction costs, liquidity constraints or risk limits using modern deep reinforcement machine learning methods. We discuss how standard reinforcement learning methods can be applied to non-linear reward structures, i.e. in our case convex risk measures. As a general contribution to the use of deep learning for stochastic processes, we also show in Section 4 that the set of constrained trading strategies used by our algorithm is large enough to ε-approximate any optimal solution. Our algorithm can be implemented efficiently even in high-dimensional situations using modern machine learning tools. Its structure does not depend on specific market dynamics, and generalizes across hedging instruments including the use of liquid derivatives. Its computational performance is largely invariant in the size of the portfolio as it depends mainly on the number of hedging instruments available. We illustrate our approach by an experiment on the S&P500 index and by showing the effect on hedging under transaction costs in a synthetic market driven by the Heston model, where we outperform the standard ‘complete-market’ solution.     

Conditional currency hedging

I propose a simple and robust approach to hedge currency risk that can be directly applied by international investors in diverse asset classes. Compared to current mean-variance approaches, it is robust to overfitting and thus better anticipates risk-minimizing currency positions for global equity, bond, and commodity investors out of sample. Furthermore, correlations among currencies, equities, and commodities can be predicted by lagged implied foreign exchange volatility. This allows investors to dynamically adjust their hedges, resulting in significantly lower risk compared to other hedging alternatives while maintaining or even improving Sharpe ratio, particularly during crisis periods.     

Convex costs and the hedging paradox

Financial theory suggests that hedging can increase shareholder value in the presence of capital market imperfections, including direct and indirect costs of financial distress, costly external financing, and convex tax exposure. The influence of these costs, which are high when profits are low and low or negligible when profits are large, on the extent of firm hedging has not been consistently addressed in the finance literature. In Brown and Toft's (2002) model, more convex costs imply that a firm will decrease the extent of hedging. At the same time, one version of Smith and Stulz's (1985) tax hypothesis implies that a given firm is expected to increase the extent of hedging under a more convex tax exposure. I address this ambiguity in the literature by showing that, in incomplete markets, value-maximizing firms that stand to gain the most from hedging may in fact hedge less than otherwise identical firms with less to gain from hedging. This hedging paradox can partly account for the lack of conclusive evidence to suggest that convex costs can influence both a firm's decision to hedge and the extent of the firm's hedging. Finally, I introduce a new interpretation of empirical relations between potential hedging gains and the extent of hedging.     

谁来掌控欧元区

经过长时间的讨论,6月底结束的欧盟峰会,最终取得了"出人意料"的三项成果:一是,欧洲稳定机制(ESM)将可直接向银行注资;二是,稳定机制可通过购买"重债且评级较低的国家(如西班牙、意大利等)"的国债,硬性提升其问题债券的价值;三是,欧盟峰会决定推出1200亿欧元(约合1500亿美元)的"一揽子"计划。如此看来,欧元区的领袖们终于发现,当下已经是欧元存亡的关键时刻,同时也是欧元区的各个国家必须采取一致行动的关键时刻。     

Modeling the Euro overnight rate

This paper describes the evolution of the daily Euro overnight interest rate (EONIA) by using several models containing the jump component, such as a single-regime ARCH-Poisson–Gaussian process, with either a piecewise function or an autoregressive conditional specification (ARJI) for the jump intensity, and a two-regime-switching process with jumps and time-varying transition probabilities. To model the jump intensity, we include the following effects which are significant for the occurrence of jumps: (1) the end of maintenance period effect because of reserve requirements, (2) the end of month effect, also known as the calendar day effect, caused mainly by accounting adjustments and finally, (3) the meeting effect caused by the meetings of the Governing Council of the European Central Bank (ECB). These effects lead to better performance and several of them are also included for the behavior of the transition probabilities. Since the target of the ECB is to maintain the EONIA rate close to the policy rate, we model the conditional mean of the overnight rate series as a reversion process to this policy rate, distinguishing two alternative speeds of reversion, specifically, a different speed if EONIA is higher or lower than the policy rate. We also study the jumps of the EONIA rate around the ECB's meetings by using the ex-post probabilities of the ARJI model. Finally, we develop a volatility forecasting analysis to measure the performance of the different candidate models.     

欧元区债务危机与欧元前景

由于经济结构失衡和制度缺陷,欧元区部分国家爆发了主权债务危机。尽管危机给欧洲经济复苏和欧元前景蒙下了阴影,但欧洲仍可通过积极应对危机,加快结构性改革,扫除一体化进程中的障碍,最终助推欧元在国际货币体系中站稳脚跟。     

另一个战场:欧元与美元的较量

美伊战争于3月20日上午爆发,国际关系紧张气氛愈加浓重.战争不仅具有强烈的政治目的、军事意义,同时也具有明显的金融利益与需求.回想欧元启动初期的科索沃战争,不仅只是国际政治关系意义上的较量,同时也严重打压与伤害着欧元的货币意义与作用,进而导致欧元连续三年的疲软波动,从起步初期的1.17美元一路下跌至0.83美元;科索沃战争间接的打击与油价直接的影响,是欧元磨难的根本原因.而面对如今美国对伊拉克的这场战争,其中除了国际政治与关系层面的矛盾外,对欧元区而言,恐怕最终的结果将会进一步冲击欧元汇率,更多战略意义在于经济利益对金融实际的影响.     

Optimal static quadratic hedging

We propose a flexible framework for hedging a contingent claim by holding static positions in vanilla European calls, puts, bonds and forwards. A model-free expression is derived for the optimal static hedging strategy that minimizes the expected squared hedging error subject to a cost constraint. The optimal hedge involves computing a number of expectations that reflect the dependence among the contingent claim and the hedging assets. We provide a general method for approximating these expectations analytically in a general Markov diffusion market. To illustrate the versatility of our approach, we present several numerical examples, including hedging path-dependent options and options written on a correlated asset.     

Regime switching correlation hedging

This paper investigates the hedging effectiveness of commodity futures when the correlations of spot and futures returns are subject to multi-state regime shifts. An independent switching dynamic conditional correlation GARCH (IS-DCC) which is free from the problems of path-dependency and recombining is applied to model multi-regime switching correlations. The results of hedging exercises indicate that state-dependent IS-DCC outperforms state-independent DCC GARCH and three-state IS-DCC exhibits superior hedging effectiveness, illustrating importance of modeling higher-state switching correlations for dynamic futures hedging.     

Corporate hedging and the cost of debt

For a large sample of U.S. firms from 1994 to 2009, we empirically examine the impact of corporate hedging on the cost of public debt. We find strong evidence that hedging is associated with a lower cost of debt. The negative effect of hedging on the cost of debt is consistent across industries, and remains economically and statistically significant under various controls and econometric specifications. A cross-sectional analysis based on propensity score matching suggests that hedging initiation firms experience a drop in cost of debt, while suspension firms sustain a jump. We confirm our findings after employing an extensive array of models to address potential endogeneity. The influence of hedging on cost of debt is mainly through the lowering of bankruptcy risk and agency cost, and the reduction in information asymmetry. Finally, hedging mitigates the negative effect of rising borrowing costs on capital expenditure and firm value.     

Fiscal spillovers in the Euro area

This paper analyses the dynamic effects of fiscal imbalances in a given EMU member state on the borrowing costs of other countries in the euro area. The estimation of a multivariate, multi-country time series model (specifically a Global VAR, or GVAR) using quarterly data for the EMU period suggests that euro-denominated government yields are strongly linked with each other. However, financial markets seem to be able to discriminate among different issuers. Consequently, fiscal imbalances in Italy and in other peripheral countries should be closely monitored by their EMU partners and the European institutions.     

Is operational hedging a substitute for or a complement to financial hedging?

This paper investigates operational hedging by firms and how operational hedging is related to financial hedging by using a sample of 424 firm observations, which consist of 212 operationally hedged firms (firms with foreign sales) and a size- and industry-matched sample of 212 non-operationally hedged firms (firms with export sales). We find that non-operationally hedged firms use more financial hedging, relative to their levels of foreign currency exposure, as measured by the amount of export sales. On the other hand, though operationally hedged firms have more currency exposure, their usage of financial derivatives becomes much smaller than that of exporting firms. These results can explain why some global firms use very limited amount of financial derivatives for hedging purpose despite much higher levels of currency risk exposure. We also show that hedging increases firm value.     

Income hedging and portfolio decisions

We examine whether the decision to participate in the stock market and other related portfolio decisions are influenced by income hedging motives. Economic theory predicts that the market participation propensity should increase as the correlation between income growth and stock market returns decreases. Surprisingly, empirical studies find limited support for the income hedging motive. Using a rich, unique Dutch data set and the National Longitudinal Survey of the Youth (NLSY) from the United States, we show that when the income-return correlation is low, individuals exhibit a greater propensity to participate in the market and allocate a larger proportion of their wealth to risky assets. Even when the income risk is high, individuals exhibit a higher propensity to participate in the market when the hedging potential is high. These findings suggest that income hedging is an important determinant of stock market participation and asset allocation decisions.     

Coherent hedging in incomplete markets

In incomplete financial markets, not every contingent claim can be perfectly replicated by a self-financing strategy. In this paper, we minimize the risk that the value of the hedging portfolio falls below the payoff of the claim at time T. We use a coherent risk measure, introduced by Artzner et al., to measure the risk of the shortfall. The dynamic optimization problem of finding a self-financing strategy that minimizes the coherent risk of the shortfall can be split into a static optimization problem and a representation problem. We will deduce necessary and sufficient optimality conditions for the static problem using convex duality methods. The solution of the static optimization problem turns out to be a randomized test with a typical 0–1 structure. Our results improve those obtained by Nakano. The optimal hedging strategy consists of superhedging a modified claim that is the product of the original payoff and the solution to the static problem.     

Enhancing hedging performance with the spanning polynomial projection

Statistical time-series approaches to hedging are difficult to beat, especially out-of-sample, and are capable of out-performing many theory-based derivative pricing model approaches to hedging commodity price risks using futures contracts. However, the vast majority of time-series approaches to hedging discussed in the literature are essentially linear statistical projections, whether univariate or multivariate. Little is known about the potential hedging capabilities of nonlinear methods. This study describes how least-squares orthogonal polynomial approximation methods based on the spanning polynomial projection (SPP) can be used to enhance standard (linear) optimal hedging methods and improve hedging performance for a hedger with a mean–variance objective. Empirical analyses show that the SPP can be used effectively for hedging and gives better out-of-sample hedging performance than the benchmark VEC-GARCH hedging model. Results are robust to the inclusion of transaction costs and risk-aversion assumptions.