Pairs trading with a mean-reverting jump–diffusion model on high-frequency data

This paper develops a pairs trading framework based on a mean-reverting jump–diffusion model and applies it to minute-by-minute data of the S&P 500 oil companies from 1998 to 2015. The established statistical arbitrage strategy enables us to perform intraday and overnight trading. Essentially, we conduct a three-step calibration procedure to the spreads of all pair combinations in a formation period. Top pairs are selected based on their spreads’ mean-reversion speed and jump behaviour. Afterwards, we trade the top pairs in an out-of-sample trading period with individualized entry and exit thresholds. In the back-testing study, the strategy produces statistically and economically significant returns of 60.61% p.a. and an annualized Sharpe ratio of 5.30, after transaction costs. We benchmark our pairs trading strategy against variants based on traditional distance and time-series approaches and find its performance to be superior relating to risk–return characteristics. The mean-reversion speed is a main driver of successful and fast termination of the pairs trading strategy.     

Labor market entry and earnings dynamics: Bayesian inference using mixtures‐of‐experts Markov chain clustering

This paper analyzes patterns in the earnings development of young labor market entrants over their life cycle. We identify four distinctly different types of transition patterns between discrete earnings states in a large administrative dataset. Further, we investigate the effects of labor market conditions at the time of entry on the probability of belonging to each transition type. To estimate our statistical model we use a model‐based clustering approach. The statistical challenge in our application comes from the difficulty in extending distance‐based clustering approaches to the problem of identifying groups of similar time series in a panel of discrete‐valued time series. We use Markov chain clustering, which is an approach for clustering discrete‐valued time series obtained by observing a categorical variable with several states. This method is based on finite mixtures of first‐order time‐homogeneous Markov chain models. In order to analyze group membership we present an extension to this approach by formulating a probabilistic model for the latent group indicators within the Bayesian classification rule using a multinomial logit model. Copyright © 2011 John Wiley & Sons, Ltd.     

Is there an asymmetric effect of monetary policy over time? A Bayesian analysis using Austrian data.

The present paper assesses whether monetary policy effects are asymmetric over the business cycle by estimating a univariate model for GDP including additionally the first difference of the 3-month Austrian interest rate as a measure for monetary policy. The asymmetry of the effects is captured by allowing for state-dependent parameters where the latent state variable follows a Markov switching process. The model is estimated within a Bayesian framework using Markov Chain Monte Carlo simulation methods. Model selection and specification tests are performed by means of marginal likelihood. The results document significant negative effects of monetary policy during periods of below-average growth, while the effect seems insignificant during periods of normal or above-average growth. These results corroborate those derived in theoretical models assuming price rigidities and implying a convex supply curve. Additionally, the concern of using appropriate state-identifying restrictions is raised to obtain an unbiased posterior inference. Finally, the analysis concludes by assessing the robustness of the results with respect to alternative measures of monetary policy. First Version Received: December 2000/Final Version Received: May 2001     

Environmental Liability Law and Induced Technical Change – The Role of Discounting

We analyse the incentives of environmental liability law for inducing progress to emission abatement technology. We consider three liability rules: strict liability, a negligence rule with an emission norm as the due care standard, and a double negligence rule which combines the emission standard with an abatement technology norm. In the case of distortive discounting, i.e. where the private discount rate deviates from the social one, we show, how the level of distortion influences the ranking of liability rules, according to the criterion of generated social cost.     

Type of earnings management and the effect of ownership structure, firm size, and corporate-governance practices: Evidence from Indonesia

The purpose of this study is to investigate whether companies listed on the Jakarta Stock Exchange (JSE) conduct efficient or opportunistic earnings management and to examine the effect of ownership structure, firm size, and corporate-governance practices on it.Using multiple regressions, we find evidence that the type of earnings management selected by JSE listed firms tends toward efficient earnings management. This evidence is inconsistent with the common view that earnings management in Indonesia is opportunistic. Family ownership has a significant influence on the type of earnings management selected. Firms with a high proportion of family ownership and non-business groups are more inclined to choose efficient earnings management than other types of firms. We find inconsistent evidence with regard to the impact of institutional ownership, firm size, and corporate-governance practices on type of earnings management.     

Creating entrepreneurial employees in traditional service sectors

Increasingly companies seek to enhance employee entrepreneurial behaviour. In this study we explore how coaching first reduces role conflicts associated with acting entrepreneurial and at the same time improving efficiency and reducing failure and secondly increases the entrepreneurial self-efficacy of employees. Building on previous conceptual and empirical studies on intrapreneurship, social psychology and human resource management we formulate several hypotheses concerning the relationship between self-efficacy, coaching and entrepreneurial behaviour of account managers that are tested in the context of a large service organization operating in the financial sector. In doing so we confirm and extend our insights on entrepreneurial behaviour in existing companies.