Measuring potential market risk

We argue herein that there is a fundamental and an important difference between the market risk and the potential market risk in financial markets. We also argue that the spectrum of smooth Lyapunov exponents can be used in (λ,σ²)-analysis, which is a method to measure and monitor these risks. The reason is that these exponents focus on the stability properties (λ) of the stochastic dynamic system generating asset returns, while more traditional risk measures such as value-at-risk are concerned with the distribution of asset returns (σ²).     

Electricity spot price modelling with a view towards extreme spike risk

Sums of Lévy-driven Ornstein–Uhlenbeck processes are appropriate for modelling electricity spot price data. In this paper we present a new estimation method with particular emphasis on capturing the high peaks, which is one of the stylized features of such data. After introducing our method we show it at work for the EEX Phelix Base electricity price index. We also present a small simulation study to demonstrate the performance of our estimation procedure.     

Ratings-based credit risk modelling: An empirical analysis

Banks have recently developed new techniques for gauging the credit risk associated with portfolios of illiquid and defaultable instruments. These techniques could revolutionise banks' management of credit risk and could in the longer term serve as a more risk-sensitive basis for calculating regulatory capital on banks' loan books than in Basel 2, the new regulatory capital framework. In this paper we implement a popular credit risk model that exploits the information in credit ratings to determine a portfolio's value-at-risk. Using price data on large eurobond portfolios, we assess, on an out-of-sample basis, how well the model tracks the risks it is supposed to measure.     

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.     

Inflation and price setting in a natural experiment

We analyze the behavior of price setters in Poland during the transition from a planned to a market economy, using a large disaggregated data set. The size and frequency of price changes, as well as relative price variability, all increase as inflation rises. The effect of expected inflation on relative price variability is much stronger than the effect of unexpected inflation. Despite the unusual economic environment, the results are qualitatively identical, and quantitatively stronger, than those in Lach and Tsiddon [1992. Journal of Political Economy 100, 349-389].     

'Accounting talk' in a caring setting

An action research study, designed to investigate the effects on cost control of individually designed cost reports, uncovered indications that the use of financial information may be socially, rather than cognitively, determined. For financial information to be used sensibly it has to be given meaning in context, i.e., in the professional discourse. The financial language, related to a different conceptual framework, and dealing with secondary effects of professional activities, was assumed to be blocked from entering into the learning processes of professionals. Therefore, a 'modest' intervention was designed. It was oriented towards conceptual training and design, and redesign, of reports. The effects of the intervention would be monitored in regular interviews about the problem solving process in professional groups. As the study proceeded over a 1 year period it gradually became evident that the interviews, or 'talks' as we prefer to call them, played a more important role than the individually adapted financial reporting.     

A fully parametric approach to return modelling and risk management of hedge funds

This paper examines the empirical properties of hedge fund returns and proposes a fully parametric model capable of adequately describing both univariate and multivariate return properties. The suggested model is based on the multivariate extension of the Normal Inverse Gaussian (NIG) distribution and will be shown to be capable of capturing the characteristic distributional features of hedge fund returns. Drawing on recent research in the area of Generalized Hyperbolic distributions and their calibration, we will elaborate on the application of the NIG-model for risk management purposes, and highlight the differences between the NIG and the Gaussian model.      

Measuring portfolio credit risk correctly: Why parameter uncertainty matters

Why should risk management systems account for parameter uncertainty? In addressing this question, the paper lets an investor in a credit portfolio face non-diversifiable uncertainty about two risk parameters – probability of default and asset-return correlation – and calibrates this uncertainty to a lower bound on estimation noise. In this context, a Bayesian inference procedure is essential for deriving and analyzing the main result, i.e. that parameter uncertainty raises substantially the tail risk perceived by the investor. Since a measure of tail risk that incorporates parameter uncertainty is computationally demanding, the paper also derives a closed-form approximation to such a measure.     

Demand for insurance in a portfolio setting

This paper takes an additional step toward analyzing the demand for insurance in the context of a portfolio model. An investor is endowed with a portfolio containing a risky and riskless asset that can be augmented by purchasing insurance. Here, insurance is paid for by reducing the quantity of the risky insurable asset, holding the quantity of the riskless asset fixed. In the standard insurance demand model, insurance is paid for by reducing the amount of the riskless asset. This distinction leads to a different insurance demand function because the opportunity cost of purchasing insurance is now random.     

Traditional versus non-traditional reinsurance in a dynamic setting

We consider a stochastic risk reserve process whose risk exposure can be controlled dynamically by applying proportional reinsurance and by issuing CAT Bonds. The CAT Bond payments are only partly correlated with the insurers losses. The aim is to minimize the probability of ruin. Using a two-dimensional diffusion approximation we obtain a controlled diffusion problem which can be solved explicitly with the help of the HJB equation. We present some numerical results and discuss to which extend the proportional reinsurance can be replaced by issuing CAT Bonds.     

Measuring private information in a specialist market

Since the reduced forms of the popular measures of asymmetric information in the price formation process are not nested within larger models we cannot evaluate their fit using standard statistical tools. Furthermore, pairwise correlations amongst the measures are small. We benchmark these measures cross-sectionally to realized specialist loss rates (using alternatively volume and number of trades) in the TORQ data. While five of the six measures are significantly correlated with this benchmark, this is only because they are correlated with the specialist participation rate. We infer that the measures do not measure private information in order flow, even in the setting for which they are designed.     

Equilibrium earnings management and managerial compensation in a multiperiod agency setting

To investigate how the possibility of earnings manipulation affects managerial compensation contracts, we study a two-period agency setting in which a firm’s manager can engage in window-dressing activities to manipulate reported accounting earnings. Earnings manipulation boosts the reported earnings in one period at the expense of the reported earnings in the other period. We find that the optimal pay-performance sensitivity may increase and expected managerial compensation may decrease as the manager’s cost of earnings management decreases. When the manager is privately informed about the payoff of an investment project to the firm, we identify plausible conditions under which prohibiting earnings management can result in a less efficient investment decision for the firm and more rents for the manager.     

Premium setting and bank behavior in a voluntary deposit insurance scheme

This study analyzes the effect of premium rates on banks’ incentives to join a deposit insurance scheme and their incentives to invest in risky projects under a voluntary deposit insurance scheme. We find that in order to maximize social welfare, the insurance agency must either set the premium rate to be low so as to attract all banks to join the insurance scheme, or not to have the deposit insurance at all. However, the low premium rate in the voluntary scheme does not balance the budget of the deposit insurance. We also show that in the compulsory deposit insurance scheme, however, it is possible to impose an optimal premium rate that can balance the insurance agency’s budget and achieve the highest social welfare. The results also present the dominance of the compulsory scheme over the voluntary scheme in terms of maximizing social welfare and balancing the budget.

Leading indicator variables and managerial incentives in a dynamic agency setting

This paper studies, in a dynamic agency setting, how incentives and contractual efficiency are affected by leading indicators of firms’ future financial performance. In our two-period model, a leading indicator variable provides a noisy forecast of the uncertain return from the manager’s long-term effort, and both contracting parties cannot refrain from renegotiating contract terms based on updated information. We find that the leading indicator can reduce the manager’s long-term effort incentive, as it allows the firm owner to capture more of the resulting return through renegotiated wages (i.e., the manager is held up). By reducing the uncertainty about future aggregate cash flows, the leading indicator also exacerbates the “ratchet” effect and discourages the manager’s short-term effort. In equilibrium, as the leading indicator becomes more accurate in forecasting future cash flows, the first-period contract attaches higher explicit weights to both the forward-looking leading indicator and backward-looking cash flow, and yet the manager may find it optimal to reduce both the short- and long-term efforts. We further show that with a more accurate leading indicator variable, the explicit incentive on the lagging cash flow may increase more than that on the leading indicator, and the equilibrium firm profit may decrease and diverge from the manager’s equilibrium efforts.     

The cost of capital and optimal financing policy in a dynamic setting

This paper revisits the Modigliani–Miller propositions on the optimal financing policy and cost of capital in a dynamic setting. In an environment without taxes and bankruptcy costs, the results are generally consistent with the Modigliani–Miller Propositions 1 and 2. However, the first proposition should be presented and interpreted more carefully, as given firm characteristics, there is only one optimal capital structure. Thus, a firm’s capital structure is relevant. A relaxation of assumptions about either taxes or bankruptcy costs leads to conclusions that are generally different from those in Modigliani and Miller (1958). The model predicts that leverage and sales-to-capital ratios decrease but firm size and capital stock increase with the subjective discount factor of the firm’s manager if there are taxes and bankruptcy costs. The empirical analysis supports these predictions.     

Voluntary disclosure in a bargaining setting: A research note

We conduct an experiment on voluntary disclosure within a simple bargaining setting wherein a proposer must choose one of two possible offers and a responder chooses whether to reject or accept that offer. In one treatment the proposer has the option to disclose whether a fairer (more equal) offer was available relative to the one chosen. Under standard economic theory, a responder will interpret no disclosure to mean the proposer's offer was the less fair alternative, and so a proposer who is making the fairer offer will disclose. In consequence, voluntary disclosure should perform as well as mandatory disclosure in motivating proposers to make fair offers. Given their rejection rates, we find responders properly infer the meaning of non-disclosure. However, despite the correct inferences made by responders, proposers submit twice as many fair offers with mandatory disclosure than with voluntary disclosure. Our results suggest that the choice of voluntary versus mandatory disclosure has consequences for resource allocation within the firm even though under standard assumptions about preferences it should not.     

Analyzing the impact of credit migration in a portfolio setting

Credit migration is an essential component of credit portfolio modeling. In this paper, we outline a framework for gauging the effects of credit migration on portfolio risk measurements. For a typical loan portfolio, we find credit migration can explain as much as 51% of volatility and 35% of economic capital. We compare through-the-cycle migration effects, implied by agency rating transitions, with point-in-time migration, implied by EDF? (Expected Default Frequency) transitions, and find that migration of point-in-time credit quality accounts for a greater fraction of total portfolio risk when compared with through-the-cycle dynamics. In a stylized analytic setting, we show that, when controlling for PD term structure effects, higher likelihood of moving away from the current credit state does not necessarily imply greater risk. Finally, we review methods for generating high-frequency transition matrices, needed for analyzing instruments with cash flows or contingencies whose frequencies are asynchronous to an available transition matrix. We further demonstrate that the naïve application of such methods can result in material deviations to portfolio analytics.     

The influence of voice and explanation on performance in a participative budgeting setting

This paper examines the relationship between the use of a fair budgeting process and subordinate performance. Organizational justice theory is used to define a fair budgeting process as having two components: the subordinate’s involvement in the budgeting process, voice; and the communication of a rationale for the subordinate’s lack of influence over the final budget target the superior sets, explanation. Results indicate significant performance improvements when voice and explanation are combined as compared to voice alone.