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In this paper we present results on scalar risk measures in markets with transaction costs. Such risk measures are defined as the minimal capital requirements in the cash asset. First, some results are provided on the dual representation of such risk measures, with particular emphasis given on the space of dual variables as (equivalent) martingale measures and prices consistent with the market model. Then, these dual representations are used to obtain the main results of this paper on time consistency for scalar risk measures in markets with frictions. It is well known from the superhedging risk measure in markets with transaction costs, as in Jouini and Kallal (1995), Roux and Zastawniak (2016), and Loehne and Rudloff (2014), that the usual scalar concept of time consistency is too strong and not satisfied. We will show that a weaker notion of time consistency can be defined, which corresponds to the usual scalar time consistency but under any fixed consistent pricing process. We will prove the equivalence of this weaker notion of time consistency and a certain type of backward recursion with respect to the underlying risk measure with a fixed consistent pricing process. Several examples are given, with special emphasis on the superhedging risk measure.

Choosing a portfolio of risky assets over time that maximizes the expected return at the same time as it minimizes portfolio risk is a classical problem in mathematical finance and is referred to a sthe dynamic Markowitz problem (when the risk is measured by variance)or, more generally, the dynamic mean-risk problem. In most of the literature, the mean-risk problem is scalarized, and it is well known that this scalarized problem does not satisfythe (scalar) Bellman’s principle. Thus, the classical dynamic programming methods are not applicable. For the purpose of this paper we focus on the discrete time setup, and we will use a time-consistent dynamic convex risk measure to evaluate the risk of a portfolio. We will show that, when we do not scalarize the problem but leave it in its original form as a vector optimization problem, the upper images, whose boundaries contain the efficient frontiers, recurse backward in time under very mild assumptions. Thus, the dynamic mean-risk problem does satisfy a Bellman’s principle, but a more general one, that seems more appropriate for a vector optimization problem: a set-valued Bellman’s principle. We will present conditions under which this recursion can be exploited directly to compute a solution in the spirit of dynamic programming. Numerical examples illustrate the proposed method. The obtained results open the door for a new branch in mathematics: dynamic multivariate programming.

Accounting-based models in credit risk have been shown to perform well in predicting a firm's ability to meet its financial obligations, even if they include only a limited number of financial ratios measuring different aspects of the firm's financial health. However, there is little agreement on a specific set of ratios to be incorporated in these models in the existing literature. This study provides guidance on the set of accounting ratios to include in such models based on empirical results obtained for rating implied 1-year probabilities of default for a data set of large U.S. corporations. The analysis performed consists of a predictive Bayesian model averaging approach where the models included are restricted in the number of accounting ratios from different categories. The identified model is shown to provide similar predictive performance as more complex models, while retaining interpretability and simplicity.

This paper empirically investigates a channel through which market uncertainty affects the liquidity premium. Using data at the mutual fund level, I document that increases in market uncertainty are associated with lower performance and more withdrawals. Consequently, funds adjust the composition of their portfolio towards more liquid assets in order to meet potential redemptions. Aggregated over many funds, this `flight-to-liquidity' places significant upward price pressure on the liquidity premium: a one standard deviation increase in my measure of active liquidity management yields a 1.22 standard deviation increase in the return spread between illiquid and liquid stocks.

We study the link between informed trading and co-movement in liquidity. We argue that investors concerned with liquidity and fire sale shocks respond to an increase in informed trading by shifting their portfolios away from stocks with high information asymmetry. Their rebalancing results in a substitution in ownership away from the very same investors that induce financial fragility and co-movement in liquidity. This reduces co-illiquidity of the affected stocks. We exploit a unique natural experiment that increases the incentives of informed traders to trade. Our results suggest that informed traders reduce the exposure to co-movement in liquidity: one of the major problems during the latest global financial crisis.

Fund managers can demand liquidity for their trading ideas or provide liquidity for others’ ideas. We identify the roles of these motives using a database of the individual transactions by Canadian equity funds. Both the cost and subsequent performance of their buys decline after strong inflows, indicating the depletion of ideas and substitution into liquidity provision as funds put new money to work. Sales show little of this substitution, consistent with funds’ narrower latitude to provide liquidity to buyers. In general, the option to provide liquidity makes fund performance positive in the transactions costs of buys, but not of sells.

We investigate the relationship between weather or seasonal affective disorder and the financial market, using a wide variety of financial market data as well as several weather variables and a seasonal affective disorder proxy. We distinguish between a model with a direct effect of the weather and seasonal affective disorder on the financial market and one with an indirect effect via a latent variable mood. Whereas only the latter model is justified by psychological literature, the former model is often used as an approximation. One major innovation of this paper is a consistent econometric implementation of the indirect effects model. We demonstrate that the approximation by direct effects yields inconsistent estimates. Our study supports some weather related, but no seasonal affective disorder related effects on the financial market. We show that, instead of focusing on single market segments, an analysis of various financial market segments is required. We also show that the analysis of individual stock returns or bond spreads reveals additional information, compared to the analysis of aggregate stock or bond indexes.

The overvaluation hypothesis (Miller, 1977) predicts that (a) stocks are overvalued in the presence of short selling restrictions and that (b) the overvaluation increases in the degree of divergence of opinion. We design an experiment that allows us to test these predictions in the laboratory. The results indicate that prices are higher with short selling constraints, but the overvaluation does not increase in the degree of divergence of opinion. We further find that trading volume is lower and quoted bid-ask spreads tend to be higher when short sale restrictions are imposed.

In this paper we examine sovereign bond yield spread (BYS) spillovers between Euro zone countries during a turbulent period encompassing both the global financial crisis and the Euro zone debt crisis. Using the VAR-based spillover index approach of Diebold and Yilmaz (2012) and impulse response analyses, we find that: (i) on average, BYS shocks tend to increase future BYS, and are related to news announcements and policy changes; (ii) BYS spillovers between Euro zone countries are highly intertwined, however, BYS shocks from the periphery have, on average, three times the destabilizing force on other countries than shocks coming from the core. (iii) The within-effect of BYS spillovers is of greater magnitude within the periphery than that within the core; (iv) The between-effect (core vs periphery) of BYS spillovers suggests directional spillovers of greater magnitude from the periphery to the Euro zone core than vice versa. (v) Finally, joint shocks in the periphery and the core reveal decoupling effects between these two groups of countries. Overall, our findings highlight the increased vulnerability of the Euro zone from the destabilizing shocks originating mostly from the Euro zone countries in the periphery and to a lesser extent from the Euro zone core.

In this paper, a parametric simplex algorithm for solving linear vector optimization problems (LVOPs) is presented. This algorithm can be seen as a variant of the multi-objective simplex (Evans-Steuer) algorithm [12]. Different from it, the proposed algorithm works in the parameter space and does not aim to find the set of all efficient solutions. Instead, it finds a solution in the sense of Loehne [16], that is, it finds a subset of efficient solutions that allows to generate the whole frontier. In that sense, it can also be seen as a generalization of the parametric self-dual simplex algorithm, which originally is designed for solving single objective linear optimization problems, and is modified to solve two objective bounded LVOPs with the positive orthant as the ordering cone in Ruszczynski and Vanderbei [21]. The algorithm proposed here works for any dimension, any solid pointed polyhedral ordering cone C and for bounded as well as unbounded problems. Numerical results are provided to compare the proposed algorithm with an objective space based LVOP algorithm (Benson algorithm in [13]), that also provides a solution in the sense of [16], and with Evans-Steuer algorithm [12]. The results show that for non-degenerate problems the proposed algorithm outperforms Benson algorithm and is on par with Evan-Steuer algorithm. For highly degenerate problems Benson's algorithm [13] excels the simplex-type algorithms; however, the parametric simplex algorithm is for these problems computationally much more efficient than Evans-Steuer algorithm., 27 pages, 4 figures, 5 tables

kumulative Habilitationsschrift

Correlated ordinal data typically arise from multiple measurements on a collection of subjects. Motivated by an application in credit risk, where multiple credit rating agencies assess the creditworthiness of a firm on an ordinal scale, we consider multivariate ordinal models with a latent variable specification and correlated error terms. Two different link functions are employed, by assuming a multivariate normal and a multivariate logistic distribution for the latent variables underlying the ordinal outcomes. Composite likelihood methods, more specifically the pairwise and tripletwise likelihood approach, are applied for estimating the model parameters. We investigate how sensitive the pairwise likelihood estimates are to the number of subjects and to the presence of observations missing completely at random, and find that these estimates are robust for both link functions and reasonable sample size. The empirical application consists of an analysis of corporate credit ratings from the big three credit rating agencies (Standard & Poor's, Moody's and Fitch). Firm-level and stock price data for publicly traded US companies as well as an incomplete panel of issuer credit ratings are collected and analyzed to illustrate the proposed framework.

We develop and empirically test a theory of optimal security design under adverse selection accounting for strategic trading by uninformed investors who will liquidate a security in secondary markets only if their idiosyncratic carrying costs exceed the security's expected trading loss. Such investors demand primary market discounts equaling expected carrying costs borne plus trading losses incurred. Issuers minimize the total illiquidity discount by splitting cash-flow into tranched debt claims with liquidity predicted to increase with seniority, while the optimal number of tranches increases with underlying cash-flow risk. Empirical tests confirm our model predictions.

Many numerical optimization methods use scenario trees as a discrete approximation for the true (multi-dimensional) probability distributions of the problem’s random variables. Realistic specifications in financial optimization models can lead to tree sizes that quickly become computationally intractable. In this paper we focus on the two main approaches proposed in the literature to deal with this problem: scenario reduction and state aggregation. We first state necessary conditions for the node structure of a tree to rule out arbitrage. However, currently available scenario reduction algorithms do not take these conditions explicitly into account. State aggregation excludes arbitrage opportunities by relying on the risk-neutral measure. This is, however, only appropriate for pricing purposes but not for optimization. Both limitations are illustrated by numerical examples. We conclude that neither of these methods is suitable to solve financial optimization models in asset–liability or portfolio management.

This article presents joint econometric analysis of interest rate risk, issuer-specific risk (credit risk) and bond-specific risk (liquidity risk) in a reduced-form framework. We estimate issuer-specific and bond-specific risk from corporate bond data in the German market. We find that bond-specific risk plays a crucial role in the pricing of corporate bonds. We observe substantial differences between different bonds with respect to the relative influence of issuer-specific vs. bond-specific spread on the level and the volatility of the total spread. Issuer-specific risk exhibits strong autocorrelation and a strong impact of weekday effects, the level of the risk-free term structure and the debt to value ratio. Moreover, we can observe some impact of the stock market volatility, the respective stock's return and the distance to default. For the bond-specific risk we find strong autocorrelation, some impact of the stock market index, the stock market volatility, weekday effects and monthly effects as well as a very weak impact of the risk-free term structure and the specific stock's return. Altogether, the determinants of the spread components vary strongly between different bonds/issuers.

Using an extensive cross section of U.S. corporate credit default swaps (CDSs), this paper offers an economic understanding of implied loss given default (LGD) and jumps in default risk. We formulate and underpin empirical stylized facts about CDS spreads, which are then reproduced in our affine intensity-based jump-diffusion model. Implied LGD is well identified, with obligors possessing substantial tangible assets expected to recover more. Sudden increases in the default risk of investment-grade obligors are higher relative to speculative grade. The probability of structural migration to default is low for investment-grade and heavily regulated obligors because investors fear distress rather through rare but devastating events.

We consider optimal consumption and (strategic) asset allocation of an investor with uncertain lifetime. The problem is solved using a multi-stage stochastic linear programming (SLP) model to be able to generalize the closed-form solution obtained by Richard (1975). We account for aspects of the application of the SLP approach which arise in the context of life-cycle asset allocation, but are also relevant for other problems of similar structure. The objective is to maximize the expected utility of consumption over the lifetime and of bequest at the time of death of the investor. Since we maximize utility (rather than other objectives which can be implemented more easily) we provide a new approach to optimize the breakpoints required for the linearization of the utility function. The uncertainty of the problem is described by discrete scenario trees. The model solves for the rebalancing decisions in the first few years of the investor's lifetime, accounting for anticipated cash flows in the near future, and applies Richard's closed-form solution for the long, subsequent steady-state period. In our numerical examples we first show that available closed-form solutions can be accurately replicated with the SLP-based approach. Second, we add elements to the problem specification which are usually beyond the scope of closed-form solutions. We find that the SLP approach is well suited to account for these extensions of the classical Merton setting.

This paper describes the financial planning model InnoALM we developed at Innovest for the Austrian pension fund of the electronics firm Siemens. The model uses a multiperiod stochastic linear programming framework with a flexible number of time periods of varying length. Uncertainty is modeled using multiperiod discrete probability scenarios for random return and other model parameters. The correlations across asset classes, of bonds, stocks, cash, and other financial instruments, are state dependent using multiple correlation matrices that correspond to differing market conditions. This feature allows InnoALM to anticipate and react to severe as well as normal market conditions. Austrian pension law and policy considerations can be modeled as constraints in the optimization. The concave risk-averse preference function is to maximize the expected present value of terminal wealth at the specified horizon net of expected discounted convex (piecewise-linear) penalty costs for wealth and benchmark targets in each decision period. InnoALM has a user interface that provides visualization of key model outputs, the effect of input changes, growing pension benefits from increased deterministic wealth target violations, stochastic benchmark targets, security reserves, policy changes, etc. The solution process using the IBM OSL stochastic programming code is fast enough to generate virtually online decisions and results and allows for easy interaction of the user with the model to improve pension fund performance. The model has been used since 2000 for Siemens Austria, Siemens worldwide, and to evaluate possible pension fund regulation changes in Austria.

This paper uses recent legislation in Austria to establish a link between sovereign reputation and yield spreads. In 2009, Hypo Alpe Adria International, a bank previously co-owned by the regional government of Carinthia, had been nationalized by Austria’s central government in order to avoid a default triggering multi-billion Euro local government guarantees. In 2015, special legislation retroactively introduced collective action clauses allowing a haircut on both the bonds and the guarantees while avoiding formal default. We document that legislative and administrative action designed to partly abrogate the guarantees resulted in a loss of reputation, leading to higher yield spreads for sovereign debt. Our analysis of covered bonds uncovers an increase in yield spreads on the secondary market and a deterioration of primary market conditions.

We derive a formula that expresses the expected return on a stock in terms of the risk-neutral variance of the market, the stock's risk-neutral variance, and average stock-level risk-neutral variance. These components can be computed from the prices of index and stock options. We test the formula by running predictive panel regressions at the individual stock level. We conduct joint hypothesis tests and find, in most of our specifications, that the estimated coefficients are significantly different from zero and insignificantly different from the values predicted by our theory; moreover, our predictor variables drive out CAPM beta, size, book-to-market, and momentum in predictive regressions. When coefficients are fixed at the levels implied by our theory, the formula -- which has no free parameters -- outperforms a range of competitors in predicting individual stock returns.

This paper studies time variation in expected excess returns of traded claims on dividends, bonds, and stock indices for US and international markets. We construct dividend risk factors corresponding to the well-known bond risk factors of Cochrane and Piazzesi (2005) and run predictive regressions of one-year annual excess returns on both risk factors. We find both return forecasting factors to be important for the prediction of returns on stock indices and traded dividends, but only the bond risk factor is highly relevant for bond returns. Further analyzing the components of risk, we find global factors to explain the largest part of the variation in index excess returns, while local factors still improve the fit for bond and dividend markets. The return-forecasting factors also predict excess returns for regions and assets that we did not use to construct the risk factors (equity indices in developed and emerging markets, emerging market bonds, corporate bond indices and a volatility selling strategy), suggesting substantial comovement in international risk premia.

By using the 2007 municipality reform in Denmark as an exogenous shock to municipal tax rates, we find that a 1%-point increase in income tax rates lead to a drop in house prices of 7.9% and a 1‰-point increase in the property tax rates lead to a 1.1% drop in house prices. The simple present values of a 1%-point perpetual income tax increase and a 1‰-point property tax increase, relative to the median house price, are 7% and 3.3%, respectively. Our findings are thus in line with the predicted median tax loss. This indicates that the housing market efficiently incorporates taxes into house prices. The exogeneity of the shock to taxes and the size of the data set is an improvement over earlier studies.

This paper examines the impact of local economic conditions on mutual fund preferences for geographically proximate stocks and consequently fund rerformance. Specificcally, we demonstrate that mutual funds favouritism towards firms located within close geographic proximity varies with local housing price shocks. A decrease in local house prices is strongly associated with an increase in mutual fund home bias and results in a portfolio adjustment towards safer and higher quality holdings. This previously undocumented behavioral bias is of first order importance, as the shift in mutual fund preferences towards local stocks induced by deterioration in local economic conditions is associated with mutual fund underperformance: a one percentage point increase in the fraction of local holdings causes a decrease in a fund's characteristic-adjusted 3-month future return by 35.3 bps.