Information percolation,momentum and reversal

We propose a joint theory of time-series momentum and reversal based on a rational-expectations model. We show that a necessary condition for momentum to arise in this framework is that information flows at an increasing rate. We focus on word-of-mouth communication as a mechanism that enforces this condition and generates short-term momentum and long-term reversal. Investors with heterogeneous trading strategies—contrarian and momentum traders—coexist in the marketplace. Although a significant proportion of investors are momentum traders, momentum is not completely eliminated. Word-of-mouth communication spreads rumors and generates price run-ups and reversals. Our theoretical predictions are in line with empirical findings.     

The Effect of Auditor Style on Reporting Quality: Evidence from Germany

This paper examines whether the ‘style’ of individual auditors influences financial reporting quality in Germany. Audit quality in Germany should be uniformly high, because of strong reputational needs, strict controls on operating procedures, and quality enforcement mechanisms. An audit partner's style should not affect this quality level. However, our results do not support this expectation. Exploiting a unique dataset comprising the names of the audit engagement and review partners of listed German companies, we find that audit engagement partners in Germany have a significant influence on audit quality, beyond firm‐ and office‐level factors. In contrast, audit review partners do not have a consistent significant influence on audit quality. We measure audit quality by the level of a firm's abnormal accruals and its propensity to meet or beat an earnings target. We also find that the 2005 adoption of a new audit quality enforcement system that includes ‘naming and shaming’ does not reduce the influence of audit partner style on financial reporting quality.     

Short-term predictability of equity returns along two style dimensions

This study uses daily return data on 20 portfolios split along two dimensions, growth/value and market size, over the period of four decades and employs over 12,000 trading rules to investigate the short-term predictability of portfolio returns. It shows that, historically, portfolios of small stocks and value stocks have been more suitable for active trading strategies since returns on value portfolios exhibit more predictability than returns on growth portfolios and returns on portfolios of large stocks appear to be less predictive than returns on portfolios of small stocks. The predictive ability of trading rules is all but gone during the 2000s. Popularization of exchange-traded funds and the introduction of quote decimalization on the exchanges are the most likely reasons behind the lack of predictability.     

Unstable banking

We propose a theory of financial intermediaries operating in markets influenced by investor sentiment. In our model, banks make, securitize, distribute, and trade loans, or they hold cash. They also borrow money, using their security holdings as collateral. Banks maximize profits, and there are no conflicts of interest between bank shareholders and creditors. The theory predicts that bank credit and real investment will be volatile when market prices of loans are volatile, but it also points to the instability of banks, especially leveraged banks, participating in markets. Profit-maximizing behavior by banks creates systemic risk.     

Models of Multi-Category Choice Behavior

Given the advent of basket-level purchasing data of households, choice modelers are actively engaged in the development of statistical and econometric models of multi-category choice behavior of households. This paper reviews current developments in this area of research, discussing the modeling methodologies that have been used, the empirical findings that have emerged so far, and directions for future research. We also motivate the use of Bayesian methods to overcome the computational challenges involved in estimation.     

Improving risk classification and ratemaking using mixture-of-experts models with random effects

In the underwriting and pricing of nonlife insurance products, it is essential for the insurer to utilize both policyholder information and claim history to ensure profitability and proper risk management. In this paper, we apply a flexible regression model with random effects, called the Mixed Logit-weighted Reduced Mixture-of-Experts, which leverages both policyholder information and their claim history, to categorize policyholders into groups with similar risk profiles, and to determine a premium that accurately captures the unobserved risks. Estimates of model parameters and the posterior distribution of random effects can be obtained by a stochastic variational algorithm, which is numerically efficient and scalable to large insurance portfolios. Our proposed framework is shown to outperform the classical benchmark models (Logistic and Lognormal GL(M)M) in terms of goodness-of-fit to data, while offering intuitive and interpretable characterization of policyholders' risk profiles to adequately reflect their claim history.     

On the analysis of a multi-threshold Markovian risk model

We consider a class of Markovian risk models perturbed by a multiple threshold dividend strategy in which the insurer collects premiums at rate c _i whenever the surplus level resides in the i-th surplus layer, i=1, 2, …,n+1 where n<∞. We derive the Laplace-Stieltjes transform (LST) of the distribution of the time to ruin as well as the discounted joint density of the surplus prior to ruin and the deficit at ruin. By interpreting that the insurer, whose gross premium rate is c, pays dividends continuously at rate d _i =c?c _i whenever the surplus level resides in the i-th surplus layer, we also derive the expected discounted value of total dividend payments made prior to ruin. Our results are obtained via a recursive approach which makes use of an existing connection, linking an insurer's surplus process to an embedded fluid flow process.     

Bounds of ruin probabilities

Abstract

Upper and lower bounds are obtained for ruin probabilities with safety margin ρ in the case of known expectation, variance and range for the claim severity function.     

Two-Sided Platforms: Product Variety and Pricing Structures

This paper provides a new modeling framework to analyze two-sided platforms connecting producers and consumers. In contrast to the existing literature, indirect network effects are determined endogenously, through consumers' taste for variety and producer competition. Three new aspects of platform pricing structures are derived.   First, the optimal platform pricing structure shifts towards extracting more rents from producers relative to consumers when consumers have stronger demand for variety, since producers become less substitutable. With platform competition, consumer preferences for variety, producer market power, and producer economies of scale in multihoming also make platforms' price-cutting strategies on the consumer side less effective. This second effect on equilibrium pricing structures goes in the opposite direction relative to the first one.   Third, variable fees charged to producers can serve to trade off producer innovation incentives against the need to reduce a platform holdup problem.