An application of two-stage quantile regression to insurance ratemaking

Two-part models based on generalized linear models are widely used in insurance rate-making for predicting the expected loss. This paper explores an alternative method based on quantile regression which provides more information about the loss distribution and can be also used for insurance underwriting. Quantile regression allows estimating the aggregate claim cost quantiles of a policy given a number of covariates. To do so, a first stage is required, which involves fitting a logistic regression to estimate, for every policy, the probability of submitting at least one claim. The proposed methodology is illustrated using a portfolio of car insurance policies. This application shows that the results of the quantile regression are highly dependent on the claim probability estimates. The paper also examines an application of quantile regression to premium safety loading calculation, the so-called Quantile Premium Principle (QPP). We propose a premium calculation based on quantile regression which inherits the good properties of the quantiles. Using the same insurance portfolio data-set, we find that the QPP captures the riskiness of the policies better than the expected value premium principle.     

Risk-managed industry momentum and momentum crashes

This paper investigates Barroso and Santa-Clara’s [J. Financ. Econ., 2008, 116, 111–120] risk-managed momentum strategy in an industry momentum setting. We investigate several traditional momentum strategies including that recently proposed by Novy-Marx [J. Financ. Econ., 2012, 103, 429–453]. We moreover examine the impact of different variance forecast horizons on average pay-offs and also Daniel and Moskowitz’s [J. Financ. Econ., 2016, 122, 221–247] optionality effects. Our results show in general that neither plain industry momentum strategies nor the risk-managed industry momentum strategies are subject to optionality effects, implying that these strategies have no time-varying beta. Moreover, the benefits of risk management are robust across volatility estimators, momentum strategies and subsamples. Finally, the ‘echo effect’ in industries is not robust in subsamples as the strategy works only during the most recent subsample.     

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.     

Benefits of Downward Earnings Management and Political Connection: Evidence from Government Subsidy and Market Pricing

This paper examines the role of downward earnings management and political connection on the receipt of government subsidies and market pricing of subsidies. Using subsidies data hand-collected from Chinese listed firms over the period 2004–2014, the results show a significantly positive association between downward earnings management and the receipt of government subsidies. The results also reveal that a firm's political connection is conducive to securing subsidies for poor performers, but not for good performers. Market pricing analyses demonstrate that share markets value subsidies positively in general, but the effect is ameliorated in firms conducting downward earnings management. No discernible difference is found between the market pricing of subsidies received by firms with political connections and those without.     

企业养老保险参保决策影响因素实证研究——基于湖北省枣阳市企业调查数据分析

文章以湖北省枣阳市为例探索企业养老保险参保决策影响因素及制度。根据实地企业调研分析影响企业及职工参与养老保险的主要制约因素,从收支两条线、企业和职工双重视角进行了全面的分析。实地调研以湖北省枣阳市相关企业为基础,分别涉及对相关企业的问卷调查、主要负责人的访谈以及对调查企业员工的问卷调查,在数据搜集的基础上进行统计分析和计量回归分析,分析结果显示职工学历、婚姻状况、家庭总人口数、家庭老人数、对养老保险了解程度、是否签订合同、单位性质、职业特征等变量均与其是否参与企业养老保险存在显著的关系。最后,通过对枣阳市养老保险风险评估及在微观层面的主要影响因素实证分析的基础上,提出了全面参保缴费基数不宜过高、避免"五保合一"造成小保险拖累大保险、经办机构应进一步科学设置等政策建议和探索。     

互联网保险公司财务风险研究

互联网保险特殊经营模式使保险公司呈现固定资产占比较小、资产负债率较低、保险产品"场景化、碎片化"、渠道成本低廉等财务特征,也使保险公司面临更为错综复杂的财务风险,如对股东的权益性资金依赖性较强、定价风险加大、盈利空间不定以及骗赔套保和洗钱风险等.鉴此,应拓宽筹资渠道,优化保险产品定价,提高保费收入持续增长能力,降低运营和合作成本,构建第三方保单认证和风险评估体系,加强资金规范化管理,强化外部监管等.     

Optimal insurance in the presence of reinsurance

This paper studies an optimal insurance and reinsurance design problem among three agents: policyholder, insurer, and reinsurer. We assume that the preferences of the parties are given by distortion risk measures, which are equivalent to dual utilities. By maximizing the dual utility of the insurer and jointly solving the optimal insurance and reinsurance contracts, it is found that a layering insurance is optimal, with every layer being borne by one of the three agents. We also show that reinsurance encourages more insurance, and is welfare improving for the economy. Furthermore, it is optimal for the insurer to charge the maximum acceptable insurance premium to the policyholder. This paper also considers three other variants of the optimal insurance/reinsurance models. The first two variants impose a limit on the reinsurance premium so as to prevent insurer to reinsure all its risk. An optimal solution is still layering insurance, though the insurer will have to retain higher risk. Finally, we study the effect of competition by permitting the policyholder to insure its risk with an insurer, a reinsurer, or both. The competition from the reinsurer dampens the price at which an insurer could charge to the policyholder, although the optimal indemnities remain the same as the baseline model. The reinsurer will however not trade with the policyholder in this optimal solution.     

Random sources correlations and carbon futures pricing

For a long time, the correlation between random sources has never been considered in carbon futures pricing, which virtually exists. We document the presence of high correlation between variations in convenience yields of carbon futures with different maturities, whose essence is correlation between random sources. Correlation of random sources arises from the long coverage of convenience yield of carbon emission spot and the complementarity in expiration between carbon futures with different maturities. Since if random sources are correlated will significantly affect the dynamics of convenience yield and finally affect futures prices, we introduce quantum field method to account for the impact of this correlation on futures prices, and proposes the correlation between random sources extended HJM convenience yield model (CRS-HJM-CYM). Empirical results indicate CRS-HJM-CYM performs better than traditional model owing to the role of correlation, which means the correlation between random sources is a pivotal factor in carbon futures pricing.