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At present, computational methods have received considerable attention in economics and finance as an alternative to conventional analytical and numerical paradigms. This Special Issue brings together both theoretical and application-oriented contributions, with a focus on the use of computational techniques in finance and economics. Examined topics span on issues at the center of the literature debate, with an eye not only on technical and theoretical aspects but also very practical cases.

Im Land Mecklenburg-Vorpommern finden sich zwei staatliche (Voll-)Universitäten, drei staatliche Fachhochschulen und eine staatliche Hochschule für Musik und Theater. Im Vergleich zu den Einnahmen des Landes steigen die Finanzmittel der Hochschulen überproportional. Im Rahmen des Forschungsprojektes sollte deshalb die Finanzmittelausstattung und die Leistung der Hochschulen in Mecklenburg-Vorpommern vergleichend untersucht werden. Dabei wurden die Finanzierung der Hochschulen im Allgemeinen, die Verteilung der Finanzmittel sowie die Qualität der Lehre und Forschung sowohl im Ländervergleich als auch gegenüber ausgewählten einzelnen Vergleichshochschulen analysiert.

Earnings forecasts can be useful for investment decisions. Research on earnings forecasts has focused on forecast performance in relation to firm characteristics, on categorizing the analysts into groups with similar behaviour and on the effect of an earnings announcement by thefirm on future earnings forecasts. In this paper we investigate the factors that determine the value of the forecast and also investigate to what extent the timing of the forecast can be modeled. We propose a novel methodology that allows for such an investigation. As an illustration we analyze within-year earnings forecasts for AMD in the period 1997 to 2011, where the data are obtained from the I/B/E/S database. Our empirical findings suggest clear drivers of the value and the timing of the earnings forecast. We thus show that not only the forecasts themselves are predictable, but that also the timing of the quotes is predictable to some extent.

This paper investigates the role of published stock recommendations in print and online media as investor sentiment in the near-term German stock market. In line with extant literature on other sentiment measures, vector autoregressions reveal that past stock returns drive today's sentiment, but not the other way around, and that sentiment is a powerful predictor of itself. In particular, sentiment based on printed analyst recommendations follows reversals, that is, when analysts face a stock market downturn, they see a buying opportunity and become optimistic.

We consider an alternative modelling approach to the mainstream DSGE paradigm, namely basically a Dynamic Stochastic General Disequilibrium model of continuous adjustment processes on interacting real and financial markets. We introduce heterogeneous capital gain expectations (chartists and fundamentalists) and show that the first type of agents tends to destabilise he economy. Global stability can be ensured if opinions favour fundamentalist behaviour far off the steady state. This interaction of expectations and population dynamics is bounding the real-financial market interactions, but allows for irregular behaviour within these bounds. Stability can be further improved by adding suitable policy measures.

We analyse daily lead-lag patterns in US equity and credit default swap (CDS) returns. We first document that equity returns robustly lead CDS returns. However, we find that the CDS-lag is due to common (and not firm-specific) news and arises predominantly in response to positive (instead of negative) equity market news. We provide an explanation for this news-specific price discovery based on dealers in the CDS market exploiting their informational advantage vis-à-vis institutional investors with hedging demands. In support of this explanation we find that the CDS-lag and its news-specificity are related to various firm-level proxies for hedging demand in the cross-section as well measures for economy-wide informational asymmetries over time.

The unparalleled surge of the crude oil price after 2003 has triggered a heated scientific and public debate about its ultimate causes. Unexpected demand growth particularly from emerging economies appears to be the most prominently supported reason among academics. We study the price dynamics after 2003 in the global crude oil market using a structural VAR model. We account for structural breaks and approximate market expectations using a time series for media sentiment in order to contribute to the existing literature. We find that forward-looking demand activities rather than demand arising from current needs have played an important role for the run-up in the price of crude oil after 2003. We additionally find that emerging economies have not majorly contributed to the price surge., Economics Working Paper Series, 12/168

Recent studies have found correlations between risk attitudes and several sociodemographic characteristics. In this paper, we deploy an artefactual fi eld experiment and study whether subjects - non-professionals and financial professionals - are aware of these correlations. This is largely confi rmed by our results for all subject groups. We show that the subjects attach informational value to sociodemographic information when assessing others' risk attitudes. This provides external validity to the correlations found between risk preferences and sociodemographics. A person's self-assessment of risk attitudes is the most helpful device for the subjects' assessments of others, although experienced professionals make use of it to a minor extent than all other subjects.

We develop the fundamental theorem of asset pricing in a probability- free infinite-dimensional setup. We replace the usual assumption of a prior probability by a certain continuity property in the state variable. Probabilities enter then endogenously as full support martingale measures (instead of equivalent martingale measures). A variant of the Harrison-Kreps-Theorem on viability and no arbitrage is shown. Finally, we show how to embed the superhedging problem in a classical infinite-dimensional linear programming problem.

This paper presents an empirical approach that combines competing paradigms of modeling in empirical capital market research. The approach simultaneously estimates the explanatory power of fundamentals, expectations, and historic yield patterns, making it possible to test the extent to which the efficient market hypothesis, fundamental data analysis, and behavioral finance contribute to explaining stock market yield. The core of the approach is a dynamic panel model (Arellano-Bond estimator with an MA restriction of the residuals), complemented with an upstream factor analysis to reduce multicollinearity. Due to the complexity of the data set, a great many parameters that influence the yield can be determined. Highly significant parameter estimates are possible even though the information in the data set is interdependent. For the German stock market (the 160 companies listed in DAX, MDAX, SDAX, and TecDAX), the quarterly yield is analyzed for the period between 2004 and 2009. The model has high explanatory power for the entire observation period, even in light of the fact that the period includes the financial crisis of 2008.

This paper presents a Heterogeneous Agent Model of a financial market with chartist and fundamentalist traders that exhibit bounded rationality and short-term thinking to explain the effect of under and overreaction to news. The existence of the Market Maker's finite price adjustment speed leads to the fact that prices do not adjust instantaneously to new information. Chartists use moving average rules to make their investment decisions. Chartist can transform an underreaction-only scenario into a market with overreaction. The use of long moving average rules might even make the market unstable. Furthermore, noise in financial markets can lead to long time decoupling from fundamental value. Higher market efficiency (low deviations from fundamental value), on the other hand, is achieved if high rationality and long-term thinking for the agents is assumed.

Employing a new accounting data set we apply the framework of McGrattan and Prescott (2005) to the Japanese economy in order to assess if Japanese stocks were priced correctly in the period after 1980. We find that the stock market tended to undervalue the fundamental value of installed capital. We also provide a new interpretation of Japanese stock market phenomena during the 'bubble period' and suggest that from a theoretical perspective, stock prices during the 'bubble period' were correctly valued. Changes in the reproducible cost of intangible capital play an important role in our new interpretation.

The Recent crises have seen very large spikes in asset price risk without dramatic shifts in fundamentals. We propose an explanation for these risk panics based on self-fulfilling shifts in risk made possible by a negative link between the current asset price and risk about the future asset price. This link implies that risk about tomorrow's asset price depends on uncertainty about risk tomorrow. This dynamic mapping of risk into itself gives rise to the possibility of multiple equilibria and self-fulfilling shifts in risk. We show that this can generate risk panics. The impact of the panic is larger when the shift from a low to a high risk equilibrium takes place in an environment of weak fundamentals. The sharp increase in risk leads to a large drop in the asset price, decreased leverage and reduced market liquidity. We show that the model can account well for the developments during the recent financial crisis.

This paper empirically models China’s stock prices using conventional fundamentals: corporate earnings, risk-free interest rate, and a proxy for equity risk premium. It uses the estimated longrun stock price misalignments to date booms and busts, and analyses equity market reforms and excess liquidity as potential drivers of these stock price misalignments. Our results show that China’s equity prices can be reasonable well modelled using fundamentals, but that various booms and busts can be identified. Policy actions, either taking the form of deposit rate changes, equity market reforms or excess liquidity, seem to have significantly contributed to these misalignments.

As a result of the 2008 financial crisis, the world credit markets stalled significantly and raised the doubts of market participants and policymakers about the proper and fair valuation of financial derivatives and structured products such as collateralized debt obligations (CDOs). The aim of the paper is to contribute to the understanding of CDOs and shed light on CDO valuation based on data before and during the current financial upheaval. We present the One Factor Model based on a Gaussian Copula and test five hypothesizes. Based on the results we discovered four main deficiencies of the CDO market. For our modelling we used data of the CDX NA IG 5Y V3 index from 20 September 2007 until 27 February 2009 and its quotes we appropriately transform into CDO quotes. Based on the results we discovered four main deficiencies of the CDO market: i) an insufficient analysis of underlying assets by both investors and rating agencies; ii) the valuation model was usually based only on expected cash-flows when neglecting other factors such mark-to-market losses or correlation risk; iii) mispriced correlation; and finally iv) the mark-to-market valuation obligation for financial institutions should be reviewed. Based on the mentioned recommendations we conclude that the CDO market has a chance to be regenerated. However, the future CDO market would then be more conscious, driven by smarter motives rather than by poor understanding of risks involved in CDOs.

This paper investigates how technical trading systems exploit the momentum and reversal effects in the S&P 500 spot and futures market. The former is exploited by trend-following models, the latter by contrarian models. In total, the performance of 2,580 widely used models is analysed. When based on daily data, the profitability of technical stock trading has steadily declined since 1960 and has become unprofitable over the 1990s. However, when based on 30-minutes data the same models produce an average gross return of 8.8 percent per year between 1983 and 2000. These results do not change substantially when trading is simulated over six subperiods. Those 25 models which performed best over the most recent subperiod produce a significantly higher gross return over the subsequent subperiod than do all models together. Over the out-of-sample period 2001-2006 the 2,580 models perform much worse than between 1983 and 2000. This result could be due to stock markets becoming more efficient or to stock price trends shifting from 30-minutes prices to prices of higher frequencies.

This study analyses the interaction between the aggregate trading behaviour of technical models and stock price fluctuations in the S&P 500 futures market. It examines 2,580 widely used trading systems based on 30-minutes prices. The sample comprises trend-following as well as contrarian models. It shows that technical trading exerts an excess demand pressure on the stock market. This is because technical models produce clusters of trading signals that are on the same side of the market, either buying or selling. Initial stock price changes triggered by news are strengthened by a sequence of trading signals produced by trend-following models. Once 90 percent of the models have signalled a particular position, stock prices tend to move in the direction congruent with the position-holding of the models. This phenomenon has to be attributed to the transactions of non-technical traders, perhaps amateurs. Once price movements lose their momentum, contrarian technical models contribute to reversals of the trend.

In this study, we develop a technique for estimating a firm’s expected cost of equity capital derived from analyst consensus forecasts and stock prices. Building on the work of Gebhardt/Lee/-Swaminathan (2001) and Easton/Taylor/Shroff/Sougiannis (2002), our approach allows daily estimation, using only publicly available information at that date. We then estimate the expected cost of equity capital at the market, industry and individual firm level using historical German data from 1989-2002 and examine firm characteristics which are systematically related to these estimates. Finally, we demonstrate the applicability of the concept in a contemporary case study for DaimlerChrysler and the European automobile industry.

Pricing of cap insurance contracts is considered for political mortgage rates. A simple stochastic process for mortgage rates is proposed. The process is based on renewal processes for modelling the length of periods with downward and upward trend respectively. Prices are calculated by simulation of conditional future sample paths. Future conditional quantiles can be obtained to assess the risk of a contract. The method is illustrated by applying it to observed quarterly mortgage rates of the Swiss Union of Raiffeisenbanks for the years 1970 to 2001.

Recent research reveals that hedge fund returns exhibit a range of different,possibly non-linear pay-off patterns. It is difficult to qualify all these patternssimultaneously as being rational in a traditional framework for optimal financial decisionmaking. In this paper we present a simple model based on loss aversion that can accommodatefor all of these pay-off structures in one unifying framework. We provide evidence thatloss-aversion is a likely assumption for management as well as investor preferences.Following the current empirical literature, we solve a static asset allocation problem thatincludes a nonlinear instrument. We show analytically that four different pay-off functionsmay be rationally optimal. The key parameter in determining which of these four to choosein a specific setting, is the financial planner's surplus. The notion of surplus connectshedge fund manager's incentive schemes with the idea of mental accounting as proposed inrecent behavioral finance research.

Ambivalence in the regulatory definition of capital adequacy for credit risk has recently stirred the financial services industry to collateral loan obligations (CLOs) as an important balance sheet management tool. CLOs represent a specialised form of Asset-Backed Securitisation (ABS), with investors acquiring a structured claim on the interest proceeds generated from a portfolio of bank loans in the form of tranches with different seniority. By way of modelling Merton-type risk-neutral asset returns of contingent claims on a multi-asset portfolio of corporate loans in a CLO transaction, we analyse the optimal design of loan securitisation from the perspective of credit risk in potential collateral default. We propose a pricing model that draws on a careful simulation of expected loan loss based on parametric bootstrapping through extreme value theory (EVT). The analysis illustrates the dichotomous effect of loss cascading, as the most junior tranche of CLO transactions exhibits a distinctly different default tolerance compared to the remaining tranches. By solving the puzzling question of properly pricing the risk premium for expected credit loss, we explain the rationale of first loss retention as credit risk cover on the basis of our simulation results for pricing purposes under the impact of asymmetric information. Klassifikation: C15, C22, D82, F34, G13, G18, G20

We present an empirical study focusing on the estimation of a fundamental multi-factor model for a universe of European stocks. Following the approach of the BARRA model, we have adopted a cross-sectional methodology. The proportion of explained variance ranges from 7.3% to 66.3% in the weekly regressions with a mean of 32.9%. For the individual factors we give the percentage of the weeks when they yielded statistically significant influence on stock returns. The best explanatory power – apart from the dominant country factors – was found among the statistical constructs „success“ and „variability in markets“. Vorgestellt wird eine empirische Studie, welche die Schätzung eines fundamentalen Multi-Faktor-Modells für ein Universum europäischer Aktien beinhaltet. Als Methode wurde in Anlehnung an die Vorgehensweise im BARRA-Modell der Querschnittsanalyse der Vorzug gegeben. Der Anteil der erklärten Varianz beläuft sich in den wöchentlichen Regressionen auf 7,3% bis 66,3% bei einem Durchschnitt von 32,9%. Für die einzelnen Faktoren wird die Häufigkeit angegeben, mit der sie sich in den Regressionen signifikant erwiesen haben. Den höchsten Erklärungsgehalt im Untersuchungszeitraum hatten Länderfaktoren, aber auch Konstrukte wie „Success“ oder „Variability in Markets“.

Der vorliegende Beitrag zeigt verschiedene Möglichkeiten auf, um repräsentative Renditen für die Anlageklasse Immobilien berechnen zu können. Betrachtet werden Indizes auf der Basis (i) von regelmäßig bewerteter Immobilienportefeuilles, (ii) auf Basis von Markttransaktionen in Immobilien und (iii) auf Basis der Wertentwicklung börsennotierter Immobilienaktiengesellschaften. The purpose of this paper is to compare three different index construction methodologies of commercial property investments. We examine for different European countries (i) appraisal-based indices and methods of „unsmoothing“ the corresponding return series, (ii) indices that trace average ex-post transaction prices over time, and (iii) indices based on Real Estate Investment Trust share prices.

Do financial market analysts use structural economic models when forecasting exchange rates? This is the leading question analysed in this apper. In contrast to other studies we use expectations instead of realised data. Therefore we analyse the implicit structural models forecasters have in mind when forming their exchange rate expectations. Using expected short- and long-term interest rates and business expectations as explanatory variables we estimate latent structural models to explain expected exchange rates. A special hypothesis is whether exchange rate expectations are formed according to monetary models. The currencies included in the study are US dollar, British pound, Japanese yen, French franc and Italian lire, each defined against the German mark. A major finding of the analysis is that expected GDP is the most important variable (from the set of our variables) for the determination of exchange rate expectations. For the DM/US dollar expectations a Mundell-Fleming type model is compatible with the data. This means, that increasing interest rates will led to an appreciation of the corresponding currency. The opposite result have been found for French franc and Italian lire where high expected interest rates indicate a weak currency.

Simple formulas for the price of corporate discount and coupon bonds are found using the Longstaff and Schwartz valuation approach for the debt claims of a firm, where default is triggered by a special State variable: the firm's asset-to-debt-ratio. Instead of keeping the total amount of debt constant over time, it is shown that closed form solutions exist under the alternative assumption that the level of leverage is expected to remain constant over time under the risk-neutralized measure. This encourages a more conservative view on the capital structure policy of the firm which might be appropriate in case the firm is neither willing nor able to reduce its expected level of leverage considerably over time.