Hedging Housing Risk in London

This paper investigates the benefits of allowing households to compensate the portfolio distortion due to their housing consumption through investments in housing price derivatives. Focusing on the London market, we show that a major loss from over-investment in housing is that households are forced to hold a very risky portfolio. However, the strong performance of the London housing market means that little is lost in terms of expected returns. Even households with limited wealth are better off owning their home rather than renting and investing in financial assets, as long as they are willing to face the financial risk involved. In this context, access to housing price derivatives would benefit most poor homeowners looking to limit their risk exposure. It would also benefit wealthier investors looking for the high returns provided by housing investments without the costs of direct ownership of properties. Comparisons with French, Swedish and U.S. data provide a broader perspective on our findings.     

Pricing and hedging power options

In this paper we study the pricing and hedging of options whose payoff is a polynomial function of the underlying price at expiration; so-called ‘power options’. Working in the well-known Black and Scholes (1973) framework we derive closed-form formulas for the prices of general power calls and puts. Parabola options are studied as a special case. Power options can be hedged by statically combining ordinary options in such a way that their payoffs form a piecewise linear function which approximates the power option's payoff. Traditional delta hedging may subsequently be used to reduce any residual risk.     

Learning minimum variance discrete hedging directly from the market

Option hedging is a critical risk management problem in finance. In the Black–Scholes model, it has been recognized that computing a hedging position from the sensitivity of the calibrated model option value function is inadequate in minimizing variance of the option hedge risk, as it fails to capture the model parameter dependence on the underlying price (see e.g. Coleman et al., J. Risk, 2001, 5(6), 63–89; Hull and White, J. Bank. Finance, 2017, 82, 180–190). In this paper, we demonstrate that this issue can exist generally when determining hedging position from the sensitivity of the option function, either calibrated from a parametric model from current option prices or estimated nonparametricaly from historical option prices. Consequently, the sensitivity of the estimated model option function typically does not minimize variance of the hedge risk, even instantaneously. We propose a data-driven approach to directly learn a hedging function from the market data by minimizing variance of the local hedge risk. Using the S&P 500 index daily option data for more than a decade ending in August 2015, we show that the proposed method outperforms the parametric minimum variance hedging method proposed in Hull and White [J. Bank. Finance, 2017, 82, 180–190], as well as minimum variance hedging corrective techniques based on stochastic volatility or local volatility models. Furthermore, we show that the proposed approach achieves significant gain over the implied BS delta hedging for weekly and monthly hedging.     

EXPORT AND HEDGING DECISIONS UNDER CORRELATED REVENUE AND EXCHANGE RATE RISK

This paper examines the behaviour of a competitive exporting firm under joint revenue and exchange rate risk. The firm can trade unbiased currency futures contracts for hedging purposes. We show that neither the separation theorem nor the full‐hedging theorem holds when the revenue shock prevails. If the correlation between the revenue shock and the random spot exchange rate is non‐positive, the firm optimally produces less than the benchmark level when the revenue shock is absent. If, in addition, the firm is prudent, the optimal futures position is an under‐hedge. Finally, we derive sufficient conditions under which the firm's optimal output level is higher in the presence than in the absence of the revenue shock. Operational hedging and financial hedging as such interact in a complicated way to better cope with the multiple sources of uncertainty faced by the firm.     

死亡率免疫理论及其在长寿风险对冲中的应用

基于死亡率免疫理论探讨保险公司长寿风险的自然对冲问题,研究年龄、性别与保险期限等因素与保单久期和凸性之间的关系,发现保险公司欲达到长寿风险的完全对冲,其寿险业务和年金业务必须达到的最小ρ比例应该等于年金和寿险保单的久期之比,表明保险公司可以通过选择调整寿险和年金业务的比例来对冲长寿风险的影响。     

The untold story of commodity futures in China

We investigate the behavior of commodity futures risk premia in China. In the presence of retail-dominance and barriers-to-entry, the term structure and momentum premia remain persistent, whereas hedging pressure, skewness, volatility, and liquidity premia are distorted by time-varying margins and strict position limits. Furthermore, open interest, currency, and inflation premia are sensitive to institutional settings. The observed premia cannot be attributed to common risks, sentiment, transactions costs, or data-snooping, but are related to liquidity, anchoring, and regulation-induced limits-to-arbitrage. We highlight the distinctive features of Chinese futures markets and assess the challenges posed to theories of commodity risk premia.     

Flight-to-quality and correlation between currency and stock returns

We document that capital flows in and out of emerging or developed markets are sensitive to global equity market conditions. Capital tends to move out of emerging into developed countries in global down markets, leading to depreciation (appreciation) of emerging (developed) currencies. This generates a positive (negative) correlation between currency and equity in emerging (developed) markets which is amplified by the magnitude of the capital movement. We also verify that hedging currency risks may undo the natural hedge and increase the total return volatility under negative correlation.     

Preparing for higher inflation: Portfolio solutions using U.S. equities

Investors have always been interested in reducing inflation risk in their portfolios. However, investors face different types of inflation than those measured by the Consumer Price Index (CPI). Moreover, different asset classes can be used to hedge portfolio inflation. In this paper, we show how individual equities can be used to construct equity portfolios sensitive to customized inflation targets. We illustrate portfolios for three types of inflation: US headline CPI, Forbes Cost of Living Extremely Well Index, and the US Medical Care Price Index. We also show how alternative weighting schemes, such as minimum volatility and maximum inflation beta, can be used to construct inflation‐hedged portfolios.     

股指期货套期保值理论及模型的演进与实证研究

将对股指期货套期保值策略进行比较全面的理论和实证研究。首先,概述了股指期货套期保值的相关理论,综述了套期保值的关键环节是最优套期保值比率的确定的相关的模型;其次,运用协整等分析方法,采用最小二乘回归模型（OLS）、向量自回归模型（VAR）、误差修正模型（ECM）、广义自回归条件异方差模型（GARCH）,分别对中国沪深300股指期货最优套期保值比率进行了实证研究,并对各模型的套期保值绩效做出了评价,得出ECM模型是最优的,是最适合中国沪深300股指期货的套期保值率估计模型。     

石油期货:完善我国石油安全机制的必然选择

国际油价波动通过石油进口对国内经济产生影响,成为我国石油供应安全的隐患。国际油价的形成机制是现货市场与期货市场共同影响市场价格走向,由于没有形成国际化的石油市场体系,转嫁风险机制缺位,我国在国际石油市场采购现货时不得不量价齐升。发展石油期货市场,完善国内石油市场体系,是建立和完善我国石油安全机制的必然选择。