Comparative optimism and risky road traffic behaviors among high‐risk sports practitioners

This study examines the relationship between participation in risky sports, comparative optimism (CO), and risky road traffic behaviors among a sample of adult men. We surveyed high‐risk (n = 313) and low‐risk (n = 53) sports practitioners, and non‐sportsmen (n = 89), assessing their CO, as well as their self‐reported risky behaviors and their accident experiences while driving a car. Results show that high‐risk sports practitioners expressed CO regarding the quality of their reflexes while driving and their vulnerability to traffic accidents. High‐risk sportsmen reported more risky behaviors while driving a car than the members of the other groups, and some of them, namely BASE‐jumpers, have experienced more traffic accidents. High‐risk sportsmen’s risky behaviors and accident experiences did not prevent them from expressing CO regarding their vulnerability to road accidents. Results are discussed, as well as putative psychological mechanisms underlying high‐risk sport practitioners’ CO and risky behaviors while driving.     

Fundamental Economic Variables,Expected Returns,and Bond Fund Performance

In this article, we develop relative pricing (APT) models that are successful in explaining expected returns in the bond market. We utilize indexes as well as unanticipated changes in economic variables as factors driving security returns. An innovation in this article is the measurement of the economic factors as changes in forecasts. The return indexes are the most important variables in explaining the time series of returns. However, the addition of the economic variables leads to a large improvement in the explanation of the cross-section of expected returns. We utilize our relative pricing models to examine the performance of bond funds.     

Potenziale von Telematik-Tarifen in der Kfz-Versicherung in Deutschland

The potential of telematics contracts in motor insurance in Germany is sometimes considered to be limited. In this article we present some theoretical thoughts and empirical results to this. Certain aspects of the acceptance of telematics tariffs will be looked at in an interdisciplinary way (legally, psychologically and economically) and they will be used in considering the assessment of potentials of telematics contracts. This article includes a legal analysis of the effects of the legally prescribed introduction of the emergency call system eCall coming into force in 2018. Additionally, it presents the results of a survey with regard to direct and indirect factors affecting the acceptance of telematics tariffs (regarding, among other things, their willingness to change their individual driving behaviour as well as their interest in telematics services). The empirical results provide evidence of potentials of telematics tariffs in Germany. Furthermore competitive strategies for market penetration will be reconsidered regarding the German insurance market and telematics. Thus this article is supposed to contrast media reports, which are rather negative, and to complete existing literature about telematics, which is still mostly technically and actuarially orientated. An extension of the previous understanding is realised by the selective presentation of interdisciplinary points of view. The overall picture of potentials regarding telematics tariffs in Germany is much more diverse than the picture drawn in most relating discussions.     

Cream Skimming: Innovations in Insurance Risk Classification and Adverse Selection

We demonstrate how innovations in insurance risk classification can lead to adverse selection, or cream skimming, against insurers that are slow to adopt such pricing innovations. Using a model in which insurers with insufficient pricing data cannot differentiate between low‐ and high‐risk policyholders and therefore charge both the same premium, we show how innovative insurers develop new risk classification data to identify overcharged low‐risk policyholders and attract them from rival insurers with reduced prices. Less innovative insurers thus insure a growing percentage of high‐risk customers, resulting in adverse selection attributable to their informational disadvantage. Next, we examine two cases in which “Big Data” innovations in risk classification led to concerns about cream skimming among U.S. auto insurers. First, we track the rapid adoption of credit‐based insurance scores as pricing variables in personal auto insurance markets. Second, we examine the growing popularity of usage‐based insurance programs like telematics, plans in which insurers use data on policyholders’ actual driving behavior to set prices that attract low‐risk customers. Issues associated with the execution of such pricing strategies are discussed. In both cases, we document how rival insurers quickly adopt successful innovations to reduce their exposure to adverse selection.     

Trading strategies based on term structure model residuals

The term structure of interest rates is an important input for basically every pricing model and is mostly calibrated on coupon bond prices. Therefore, the estimated interest rates should accurately explain the market prices of these bonds. However, nearly all empirical papers on interest rate estimation, e.g. Svensson, L.E.O. 1994. Estimating and interpreting forward interest rates: Sweden 1992–1994, IMF Working Paper, International Monetary Fund, report significant pricing errors in their sample. So an important question is what drives these pricing errors of the bonds. One simple explanation would be different tax treatment or different liquidity, but most papers on this research topic, e.g. Elton, E., and T.C. Green. 1998. Tax and liquidity effects in pricing government bonds. Journal of Finance 53: 1533–62, cannot fully explain the observed pricing errors. Therefore, these errors must be at least partially caused by either model misspecification or by the deviation of particular bond prices from general market conditions, i.e. mispricing revealing insufficient market efficiency. We provide empirical evidence for the German government bond market that risk-adjusted trading strategies based on bond pricing errors can yield about 15 basis points p.a. abnormal return compared to benchmark portfolios. Furthermore, the abnormal returns are continuously achieved over the whole time period and not randomly on a few days and show a relation to changes in the level and the curvature of the term structure of interest rates. Therefore, pricing errors contain economic information about deviations of bond prices from general market conditions and are not exclusively caused by model misspecification and/or differences in liquidity and tax treatment of individual bonds.     

Spatial statistical modelling of insurance risk: a spatial epidemiological approach to car insurance

Spatial models, such as the Besag, York and Mollie (BYM) model, have long been used in epidemiology and disease mapping. A common research question in these subjects is modelling the number of disease events per region; here the BYM models provides a holistic framework for both covariates and dependencies between regions. We use these tools to assess the relative insurance risk associated with the policyholders geographical location. A Bayesian modelling approach is presented and an elastic net is used to reduce the large number of possible geographic covariates. The final inference is performed using Integrated Nested Laplace Approximation. The model is applied to car insurance data from If P&C Insurance together with spatially referenced covariate data of high resolution, provided by Insightone. The entire analysis is performed using freely available R-packages. Including spatial dependence when modelling the number of claims significantly improves on the result obtained using ordinary generalised linear models. However, the support for adding a spatial component to the model for claims cost is weaker.     

A Comparison of Option Prices Under Different Pricing Measures in a Stochastic Volatility Model with Correlation

This paper investigates option prices in an incomplete stochastic volatility model with correlation. In a general setting, we prove an ordering result which says that prices for European options with convex payoffs are decreasing in the market price of volatility risk.As an example, and as our main motivation, we investigate option pricing under the class of q-optimal pricing measures. The q-optimal pricing measure is related to the marginal utility indifference price of an agent with constant relative risk aversion. Using the ordering result, we prove comparison theorems between option prices under the minimal martingale, minimal entropy and variance-optimal pricing measures. If the Sharpe ratio is deterministic, the comparison collapses to the well known result that option prices computed under these three pricing measures are the same.As a concrete example, we specialize to a variant of the Hull-White or Heston model for which the Sharpe ratio is increasing in volatility. For this example we are able to deduce option prices are decreasing in the parameter q. Numerical solution of the pricing pde corroborates the theory and shows the magnitude of the differences in option price due to varying q.JEL Classification: D52, G13     

Risky asset pricing based on safety first fund management

We study a portfolio selection model based on Kataoka's safety-first criterion (KSF model in short). We assume that the market is complete but without risk-free asset, and that the returns are jointly elliptically distributed. With these assumptions, we provide an explicit analytical optimal solution for the KSF model and obtain some geometrical properties of the efficient frontier in the plane of probability risk degree z _α and target return r _α. We further prove a two-fund separation and tangency portfolio theorem in the spirit of the traditional mean-variance analysis. We also establish a risky asset pricing model based on risky funds that is similar to Black's zero-beta capital asset pricing model (CAPM, for short). Moreover, we simplify our risky asset pricing model using a derivative risky fund as a reference for market evaluation.     

An Intertemporal International Asset Pricing Model: Theory and Empirical Evidence

We extend Campbell's (1993) model to develop an intertemporal international asset pricing model (IAPM). We show that the expected international asset return is determined by a weighted average of market risk, market hedging risk, exchange rate risk and exchange rate hedging risk. These weights sum up to one. Our model explicitly separates hedging against changes in the investment opportunity set from hedging against exchange rate changes as well as exchange rate risk from intertemporal hedging risk. A test of the conditional version of our intertemporal IAPM using a multivariate GARCH process supports the asset pricing model. We find that the exchange rate risk is important for pricing international equity returns and it is much more important than intertemporal hedging risk.     

The relationship between awareness of road safety measure and accident involvement in pre-drivers: the basis of a road safety programme

Objectives: This research aims to carry out a first validation of the QAR-Precon screening questionnaire applied in Catalonia during the drivers’ initial training, analyse the differences in risky road user behaviour according to two main variables: whether they had any experience of an accident and sex and examine the different risky road user patterns of pre-drivers. Methods: In order to group the questionnaire variables together, an exploratory factorial analysis (principal component analysis (PCA)) was used. Subsequently, the reliability coefficients of the questionnaire and the subscales were calculated. Lastly, ANOVA models were used to compare differences in the whole sample and a cluster analysis was performed to identify different risky pre-driver groups. Results: The factorial analysis (PCA) reveals the existence of five risk factors (speed and risk, external circumstances, distraction, alcohol and driving and other elements of driving) that explain 44.6% of the variance. More males than females reported that they had a higher tendency to take risks in all the risky factors exposed and injured pre-drivers reported less awareness of road safety than pre-drivers who had not been injured. A two-cluster solution indicated that it was possible to distinguish a group of pre-drivers who engaged in high risky behaviour (high group) from the group who engaged in moderate and low levels of risky road user behaviour (low group). Conclusions: The implications of these findings for programme designs and training initiatives to improve efficiency in reducing the accident rate are discussed.     

Hedging jump risk,expected returns and risk premia in jump-diffusion economies

This article presents a pure exchange economy that extends Rubinstein [Bell J. Econ. Manage. Sci., 1976, 7, 407–425] to show how the jump-diffusion option pricing model of Black and Scholes [J. Political Econ., 1973, 81, 637–654] and Merton [J. Financ. Econ., 1976, 4, 125–144] evolves in gamma jumping economies. From empirical analysis and theoretical study, both the aggregate consumption and the stock price are unknown in determining jumping times. By using the pricing kernel, we determine both the aggregate consumption jump time and the stock price jump time from the equilibrium interest rate and CCAPM (Consumption Capital Asset Pricing Model). Our general jump-diffusion option pricing model gives an explicit formula for how the jump process and the jump times alter the pricing. This innovation with predictable jump times enhances our analysis of the expected stock return in equilibrium and of hedging jump risks for jump-diffusion economies.     

Timing of Sale,Pricing, and Cost Information: Evidence from the Airline Industry*

This study examines the association between when an airline sells its passenger seats and the pricing method (marginal cost or full cost) it employs. Prior literature suggests that when firms are able to change prices during the selling period, the optimality of full cost pricing or marginal cost pricing depends on when demand information is revealed during the period between capacity commitment decisions and time of sale. Full cost‐based pricing is appropriate in determining capacity commitment and prices simultaneously, while marginal cost provides more relevant information for pricing when capacity has been committed. Using the price and cost data from a sample of four U.S. domestic airlines, we find that full cost explains price variations of first‐day sales robustly. The adjusted R² of the marginal cost pricing model is larger in the sample of sales two days prior to departure than in the sample of first‐day sales. In the analysis of the sample of sales two days prior to departure, we find that, based on the adjusted R² of the full cost pricing and marginal cost pricing models, the explanatory power of marginal cost pricing is relatively weaker than full cost pricing. Our results document the use of different cost information along the dynamic change of price and provide implications in understanding the role of cost information in setting prices.     

The psychological effects on tariff choices for car insurance

Insurance customers increasingly choose between conventional flat-rate car insurance tariffs and innovative usage-based car insurance tariffs such as a pay-per-mile tariff. Usage-based car insurance tariffs require traffic telematics. In this paper, we analyze the decision-making behavior of insurance customers concerning tariff choices as well as the psychological effects. In other service areas, it can be observed that customers often prefer a flat-rate tariff even if their billing rate would be lower on a pay-per-use tariff for a given amount of usage. In study?1, we show that the purchase intention of car insurance tariffs is influenced by psychological effects as well as the customer’s personal experience with the insurance provider and that it is higher for a flat-rate car insurance tariff compared to a pay-per-mile tariff. Customers who have had positive experiences with an insurance provider induce a higher purchase intention for car insurance than customers who have had no experience with an insurance provider. In study?2, we show that the probability of choosing a flat-rate car insurance tariff is higher with increasing monthly kilometers.     

Environmental Regulations and Social Norms

The evidence suggests that a surprisingly large number of firms comply with pollution standards even though expected penalties for non-compliance are quite low. This paper establishes an environmental social norm model that embodies collective environmental actions among firms. It provides a plausible explanation for these puzzling empirical findings. In this social norm framework, we also explore how the extrinsic pricing incentive affects the intrinsic environmental morale among firms. By taking into account the crowding-out effect of pricing incentives, we show that pollution taxes may not be an effective tool in fighting pollution.     

Testing linear factor models on individual stocks using the average F-test

In this paper, we propose the average F-statistic for testing linear asset pricing models. The average pricing error, captured in the statistic, is of more interest than the ex post maximum pricing error of the multivariate F-statistic that is associated with extreme long and short positions and excessively sensitive to small perturbations in the estimates of asset means and covariances. The average F-test can be applied to thousands of individual stocks and thus is free from the information loss or the data-snooping biases from grouping. This test is robust to ellipticity, and more importantly, our simulation and bootstrapping results show that the power of the average F-test continues to increase as the number of stocks increases. Empirical tests using individual stocks from 1967 to 2006 demonstrate that the popular four-factor model (i.e. Fama–French three factors and momentum) is rejected in two sub-periods from 1967 to 1971 and from 1982 to 1986.     

The Cost of Capital of Cross‐listed Firms

This paper analyses the cost of capital of firms with foreign equity listings. Our purpose is to shed light on the question whether international and domestic asset pricing models yield a different estimate of the cost of capital for cross‐listed stocks. We distinguish between (i) the multifactor ICAPM of Solnik (1979) and Sercu (1980) including both the global market portfolio and exchange rate risk premia and (ii) the single factor domestic CAPM. We test for the significance of the cost of capital differential in a sample of 336 cross‐listed stocks from nine countries in the period 1980–99. Our hypothesis is that the cost of capital differential is substantial for firms with international listings, as these are often large multinationals with a strong international orientation. We find that the asset pricing models yield a significantly different estimate of the cost of capital for only 12% of the cross‐listed companies. The size of the cost of capital differential is around 50 basis points for the US, 80 basis points for the UK and 100 basis points for France.     

On accurate and provably efficient GARCH option pricing algorithms

The GARCH model has been very successful in capturing the serial correlation of asset return volatilities. As a result, applying the model to options pricing attracts a lot of attention. However, previous tree-based GARCH option pricing algorithms suffer from exponential running time, a cut-off maturity, inaccuracy, or some combination thereof. Specifically, this paper proves that the popular trinomial-tree option pricing algorithms of Ritchken and Trevor (Ritchken, P. and Trevor, R., Pricing options under generalized GARCH and stochastic volatility processes. J. Finance, , 54(1), 377–402.) and Cakici and Topyan (Cakici, N. and Topyan, K., The GARCH option pricing model: a lattice approach. J. Comput. Finance, , 3(4), 71–85.) explode exponentially when the number of partitions per day, n, exceeds a threshold determined by the GARCH parameters. Furthermore, when explosion happens, the tree cannot grow beyond a certain maturity date, making it unable to price derivatives with a longer maturity. As a result, the algorithms must be limited to using small n, which may have accuracy problems. The paper presents an alternative trinomial-tree GARCH option pricing algorithm. This algorithm provably does not have the short-maturity problem. Furthermore, the tree-size growth is guaranteed to be quadratic if n is less than a threshold easily determined by the model parameters. This level of efficiency makes the proposed algorithm practical. The surprising finding for the first time places a tree-based GARCH option pricing algorithm in the same complexity class as binomial trees under the Black–Scholes model. Extensive numerical evaluation is conducted to confirm the analytical results and the numerical accuracy of the proposed algorithm. Of independent interest is a simple and efficient technique to calculate the transition probabilities of a multinomial tree using generating functions.     

Market forces meet behavioral biases: cost misallocation and irrational pricing

Psychological and experimental evidence, as well as a wealth of anecdotal examples, suggests that firms may confound fixed, sunk, and variable costs, leading to distorted pricing decisions. This article investigates the extent to which market forces and learning eventually eliminate these distortions. We envision firms that experiment with cost methodologies that are consistent with real‐world accounting practices, including ones that confuse the relevance of variable, fixed, and sunk costs to pricing decisions. Firms follow “naive” adaptive learning to adjust prices and reinforcement learning to modify their costing methodologies. Costing and pricing practices that increase profits are reinforced. In some market structures, but not in others, this process of reinforcement causes pricing practices of all firms to systematically depart from standard equilibrium predictions.     

Pricing of innate and discretionary accruals in Australian debt

This paper addresses the conflicting evidence on the role of accruals in debt pricing. We show that the two subcomponents of accruals quality, innate and discretionary accruals, both impact the debt pricing. Higher innate accruals increases cost of debt, consistent with the prior evidence ( Francis et al., 2005 ; Gray et al., 2009 ). However, we also find that higher discretionary accruals reduce the cost of debt. This contrasts with the prior evidence of a positive association between discretionary accruals and cost and debt ( Francis et al., 2005 ), and no association ( Gray et al., 2009 ). We show that noisy measurement of cost of debt reconciles these results.