Sentiment-scaled CAPM and market mispricing

This study explores the conditional version of the capital asset pricing model on sentiment to provide a behavioural intuition behind the value premium and market mispricing. We find betas (β) and the market risk premium to vary over time across different sentiment indices and portfolios. More importantly, the state β derived from this sentiment-scaled model provides a behavioural explanation of the value premium and a set of anomalies driven by mispricing. Different from the static β–return relation that gives a flat security market line, we document upward security market lines when plotting portfolio returns against their state βs and portfolios with higher state βs earn higher returns.     

Market impact: a systematic study of the high frequency options market

This paper deals with a fundamental subject that has seldom been addressed in recent years, that of market impact in the options market. Our analysis is based on a proprietary database of metaorders—large orders that are split into smaller pieces before being sent to the market—on one of the main Asian markets. In line with our previous work on the equity market [Said, E., Bel Hadj Ayed, A., Husson, A. and Abergel, F., Market impact: A systematic study of limit orders. Mark. Microstruct. Liq., 2018, 3(3&4), 1850008.], we propose an algorithmic approach to identify metaorders, based on some implied volatility parameters, the at the money forward volatility and at the money forward skew. In both cases, we obtain results similar to the now well-understood equity market: Square-Root Law, Fair Pricing Condition and Market Impact Dynamics.     

The maturity effect of stock index futures: Speculation or carry arbitrage?

Using the implementation of trading restrictions on CSI 300 index futures market as a quasi-natural experiment, this paper examines the maturity effect of stock index futures and its determinants. The results show that the maturity effect changes from weakly positive to significantly negative after trading restrictions are implemented. We find that the change in the maturity effect is rooted in the speculative effect, which is measured by the time pattern of price sensitivity to information, while there is a lack of support for the carry arbitrage effect on the maturity effect of index futures. Our findings provide an opportunity to better understand volatility dynamics in the equity futures market.     

INDIFFERENCE PRICES AND IMPLIED VOLATILITIES

We consider a general local‐stochastic volatility model and an investor with exponential utility. For a European‐style contingent claim, whose payoff may depend on either a traded or nontraded asset, we derive an explicit approximation for both the buyer's and seller's indifference prices. For European calls on a traded asset, we translate indifference prices into an explicit approximation of the buyer's and seller's implied volatility surfaces. For European claims on a nontraded asset, we establish rigorous error bounds for the indifference price approximation. Finally, we implement our indifference price and implied volatility approximations in two examples.     

Analytical approximations of local‐Heston volatility model and error analysis

This paper studies the expansion of an option price (with bounded Lipschitz payoff) in a stochastic volatility model including a local volatility component. The stochastic volatility is a square root process, which is widely used for modeling the behavior of the variance process (Heston model). The local volatility part is of general form, requiring only appropriate growth and boundedness assumptions. We rigorously establish tight error estimates of our expansions, using Malliavin calculus. The error analysis, which requires a careful treatment because of the lack of weak differentiability of the model, is interesting on its own. Moreover, in the particular case of call–put options, we also provide expansions of the Black–Scholes implied volatility that allow to obtain very simple formulas that are fast to compute compared to the Monte Carlo approach and maintain a very competitive accuracy.     

Stochastic Frontier Estimation of Market Power in the Food Industries

We use a modified version of the stochastic frontier model to estimate oligopoly markups above the perfectly competitive frontier, separating out deterministic markups from purely stochastic markups. Using data from 42 US food processing industries between 1990 and 2010, empirical results indicate a widespread incidence of oligopoly power, with Lerner indexes averaging approximately 21%. Further, the estimated markups increase with industrial concentration but decrease with price elasticities and imports. Finally, the estimated Lerner indexes are in the range of previous food industry estimates using New Empirical Industrial Organization (NEIO) models.     

Semistatic hedging and pricing American floating strike lookback options

We price an American floating strike lookback option under the Black–Scholes model with a hypothetic static hedging portfolio (HSHP) composed of nontradable European options. Our approach is more efficient than the tree methods because recalculating the option prices is much quicker. Applying put–call duality to an HSHP yields a tradable semistatic hedging portfolio (SSHP). Numerical results indicate that an SSHP has better hedging performance than a delta-hedged portfolio. Finally, we investigate the model risk for SSHP under a stochastic volatility assumption and find that the model risk is related to the correlation between asset price and volatility.     

Option pricing based on hybrid GARCH-type models with improved ensemble empirical mode decomposition

The exploration of option pricing is of great significance to risk management and investments. One important challenge to existing research is how to describe the underlying asset price process and fluctuation features accurately. Considering the benefits of ensemble empirical mode decomposition (EEMD) in depicting the fluctuation features of financial time series, we construct an option pricing model based on the new hybrid generalized autoregressive conditional heteroskedastic (hybrid GARCH)-type functions with improved EEMD by decomposing the original return series into the high frequency, low frequency and trend terms. Using the locally risk-neutral valuation relationship (LRNVR), we obtain an equivalent martingale measure and option prices with different maturities based on Monte Carlo simulations. The empirical results indicate that this novel model can substantially capture volatility features and it performs much better than the M-GARCH and Black–Scholes models. In particular, the decomposition is consistently helpful in reducing option pricing errors, thereby proving the innovativeness and effectiveness of the hybrid GARCH option pricing model.     

土地整治对中国粮食产出稳定性的贡献

研究目的:研究土地整治对粮食产出稳定性的贡献,为制定合理高效的土地整治政策,促进粮食增产稳产提供依据。研究方法:采用H-P滤波法实证分析中国粮食产量的波动性及增长趋势,然后基于C-D生产函数,分别建立趋势产量和波动强度面板回归模型,分析土地整治对粮食产出稳定性的影响。研究结果:(1)粮食作物播种面积、农业机械总动力、农用化肥施用量均对粮食长期趋势产生不同程度促进作用;农业劳动力对主产区粮食长期趋势影响显著为负,对非主产区却有正向影响。(2)土地整治面积和单位面积投资额均降低了全国及主产区粮食产量的波动程度,土地整治规模在全国和主产区的影响系数分别为-1.4162和-2.2215;单位土地整治面积投资额在全国和主产区的影响系数分别为-0.7589和-1.3509。(3)土地整治新增耕地面积对全国和主产区的粮食产量波动强度影响为正,影响系数分别为0.8018和1.3931。可能是通过土地整治新增的耕地质量较低,产出不高,导致了粮食产量波动。土地整治投入在非主产区均表现为不显著。研究结论:应继续推进尤其是主产区的土地整治项目实施,加大土地整治投资强度,建立长期稳定的投入机制,合理使用整治资金,注重提高新增耕地质量和综合生产能力,同时将土地整治投入和管理机制与农业生产系统运行机制、自然因素等有效结合,并制定差别化区域政策,以保障粮食增产稳产和区域协调发展。     

Forecasting value‐at‐risk in oil prices in the presence of volatility shifts

Recent evidence suggests shifts (structural breaks) in the volatility of returns causes non‐normality by significantly increasing kurtosis. In this paper, we endogenously detect significant shifts in the volatility of oil prices and incorporate this information to estimate Value‐at‐Risk (VaR) to accurately forecast large declines in oil prices. Our out‐of‐sample performance results indicate that the model, which incorporates both time varying volatility (without making any distributional assumptions) and shifts in volatility, produces more accurate VaR forecasts than several benchmark methods. We make a timely contribution as the recent more frequent occurrences of unexpected large oil price declines has gained significant attention because of its substantial impact on the financial markets and the global economy.