EXTENSIONS OF THE STANDARDIZED CROSS‐SECTIONAL APPROACH TO SHORT‐HORIZON EVENT STUDIES

Strong evidence indicates that short‐horizon event‐induced abnormal returns and volatility vary significantly over event days. Event‐study methods that assume constant event‐induced abnormal returns and volatility over event days have potentially inflated Type I error rates and poor test power. Our simple extensions of the Boehmer, Musumeci, and Poulsen (1991) approach scale abnormal returns with conditional variance, which is estimated with GARCH(1,1) and an indicator of the event in a two‐stage estimation. Our method improves the Boehmer, Musumeci, and Poulsen approach on model specification and test power, even under challenging event‐induced mean and volatility structures, and could standardize short‐horizon event studies.     

Local Trends in Price‐to‐Dividend Ratios—Assessment,Predictive Value,and Determinants

Persistent variations of the log price‐to‐dividend ratio (PD) and their economic determinants have attracted a lively discussion in the literature. We suggest a gradually time‐varying state process to govern the persistence of the PD. The adopted state‐space approach offers favorable model diagnostics and finds particular support in out‐of‐sample stock return prediction. We show that this slowly evolving mean process is jointly shaped by the consumption risk, the demographic structure, and the proportion of firms with traditional dividend payout policy during the past 60 years. In particular, the volatility of consumption growth plays the dominant role.     

APPLICABILITY OF THE FAMA‐FRENCH THREE‐FACTOR MODEL IN FORECASTING PORTFOLIO RETURNS

For the model‐based estimation of the equity cost of capital, evidence shows that the common practice of using the average historical factor premiums as the estimates of the next‐period factor premiums generates inaccurate estimates. I propose an alternative way to estimate factor premiums by using the structural variables that are important predictors of future asset returns. Based on the out‐of‐sample results from a trading strategy with four in‐sample model‐selection criteria, I find that my estimation procedure performs better than the common practice even when transaction costs are considered.     

Measuring Value‐at‐Risk in Project Finance Transactions

Despite the remarkable importance of project finance in international financial markets, no quantitative models to measure and quantify the risk associated with a deal for the project's lenders have been developed yet. The topic has recently become crucial, since the New Basle Capital Accord gives banks a choice of whether to adopt simpler (but possibly higher) standard capital requirements or to develop internal rating models for project finance transactions. The paper proposes how Monte Carlo simulations may be used to derive a Value‐at‐Risk estimate for project finance deals and discusses the critical issues that must be considered when developing such a model.     

DYNAMIC HEDGE FUND STYLE ANALYSIS WITH ERRORS‐IN‐VARIABLES

We revisit the traditional return‐based style analysis in the presence of time‐varying exposures and errors‐in‐variables (EIV). We apply a benchmark selection algorithm using the Kalman filter and compute the estimated EIV of the selected benchmarks. We adjust them by subtracting their EIV from the initial return series to obtain an estimate of the true uncontaminated benchmarks. Finally, we run the Kalman filter on these adjusted regressors. Analyzing EDHEC alternative index styles, we show that this technique improves the factor loadings and allows more precise identification of the return sources of the considered hedge fund strategy.     

Can tail risk explain size,book‐to‐market,momentum, and idiosyncratic volatility anomalies?

We examine the impact of tail risk on the return dynamics of size, book‐to‐market ratio, momentum and idiosyncratic volatility sorted portfolios. Our time‐series analyses document significant portfolio return exposures to aggregate tail risk. In particular, portfolios that contain small, value, high idiosyncratic volatility and low momentum stocks exhibit negative and statistically significant tail risk betas. Our cross‐sectional analyses at the individual stock level suggest that tail risk helps in explaining the four pricing anomalies, particularly size and idiosyncratic volatility anomalies.     

A New Model of Inflation,Trend Inflation,and Long‐Run Inflation Expectations

This paper develops a bivariate model of inflation and a survey‐based long‐run forecast of inflation that allows for the estimation of the link between trend inflation and the long‐run forecast. Thus, our model allows for the possibilities that long‐run forecasts taken from surveys can be equated with trend inflation, that the two are completely unrelated, or anything in between. Using a variety of inflation measures and survey‐based forecasts for several countries, we find that long‐run forecasts can provide substantial help in refining estimates and fitting and forecasting inflation. It is less helpful to simply equate trend inflation with the long‐run forecasts.     

Modelling Time‐Variation in the Stock Return‐Dividend Yield Predictive Equation

Using data for forty markets, this paper examines the nature and possible causes of time‐variation within the stock return‐dividend yield predictive regression. The results in this paper show that there is significant time‐variation in the predictive equation for returns and that such variation is linked to economic and market factors. Furthermore, the strength and nature of those links are themselves time‐varying. The inclusion of this time‐variation in the predictive equation increases the predictive power compared to the standard constant parameter predictive model. Evidence is also reported for time‐varying dividend growth predictability. Long‐horizon predictability is also examined with evidence reported that the nature of the factors affecting time‐varying predictability changes with horizon. The results here, while directly contributing to the returns predictability debate, in particular regarding its existence and source, may also inform the discussion that links time‐varying expected returns (and risk premium) to economic factors.     

A Stability Approach to Mean‐Variance Optimization

I jointly treat two critical issues in the application of mean‐variance portfolios, that is, estimation risk and portfolio instability. I find that theory‐based portfolio strategies, which are known to outperform naive diversification () in the absence of transaction costs, heavily underperform it under transaction costs. This is because they are highly unstable over time. I propose a generic method to stabilize any given portfolio strategy while maintaining or improving its efficiency. My empirical analysis confirms that the new method leads to stable and efficient portfolios that offer equal or lower turnover than and larger Sharpe ratio, even under high transaction costs.     

M‐PRESS‐CreditRisk: Microprudential and Macroprudential Capital Requirements for Credit Risk under Systemic Stress

M‐PRESS‐CreditRisk is a novel stress testing approach that can help authorities gauge banks' capital adequacy related to credit risk. For the first time, it combines the assessment of microprudential capital requirements under Pillars 1 and 2 and macroprudential buffers in a unified, coherent framework. Its core element is an advanced credit portfolio model—SystemicCreditRisk—built upon a rich, nonlinear dependence structure for correlated bank portfolios. The model is applied to a sample of 12 systemically important German banking groups and delivers measures for systemic credit risk and the banks' contributions to it in both baseline and stress scenarios.     

An inverted U‐shaped crude oil price return‐implied volatility relationship

We examined the return–volatility relationship for USO ETF oil price return and CBOE Crude Oil ETF Volatility Index, OVX. The data for the USO and OVX covers the period covering May 11, 2007 to February 28, 2013. Our OLS regression results suggest evidence of regular feedback and leverage effects. When we employ linear quantile regression techniques, we find evidence of regular and inverse feedback effects. The inverse feedback effects being noticeable in the upper quantile region of the oil return distribution. There is also support for a regular leverage effect in USO prices. We also examined the return–volatility relationship using quantile regression copula methods for measuring the degree of asymmetry in the relationships between the oil price return and implied volatility. The results of the analysis indicate, first, that there exists a negative relationship between contemporaneous oil VIX and USO ETF oil returns. Second, that the relationship between oil returns and implied volatilities depends on the quartile at which the relationship is being investigated. Third, there exists an inverted U-shaped dependency relationship between returns and implied volatilities across quantiles. Fourth, though an inverted U-shape exists, the shape is different from those observed in stock markets.     

Cross‐market spillovers with ‘volatility surprise’

This article adopts the asymmetric DCC with one exogenous variable (ADCCX) model developed by Vargas (2008), by updating the concept of ‘volatility surprise’ to capture cross-market relationships. Current methods for measuring spillovers do not focus on volatility interactions, and neglect cross-effects between the conditional variances. This paper aims to fill this gap. The dataset includes four aggregate indices representing equities, bonds, foreign exchange rates and commodities from 1983 to 2013. The results provide strong evidence of spillover effects coming from the ‘volatility surprise’ component across markets. Against the background of the recent financial crisis, the aim is to contribute to the literature on the interdependencies of financial markets, both in conditional means and (co)variances. In addition, asset management implications are derived.     

Non‐Monotonicity of the Tversky‐Kahneman Probability‐Weighting Function: A Cautionary Note

Cumulative Prospect Theory has gained a great deal of support as an alternative to Expected Utility Theory as it accounts for a number of anomalies in the observed behavior of economic agents. Expected Utility Theory uses a utility function and subjective or objective probabilities to compare risky prospects. Cumulative Prospect Theory alters both of these aspects. The concave utility function is replaced by a loss‐averse utility function and probabilities are replaced by decision weights. The latter are determined with a weighting function applied to the cumulative probability of the outcomes. Several different probability weighting functions have been suggested. The two most popular are the original proposal of Tversky and Kahneman and the compound‐invariant form proposed by Prelec. This note shows that the Tversky‐Kahneman probability weighting function is not increasing for all parameter values and therefore can assign negative decision weights to some outcomes. This in turn implies that Cumulative Prospect Theory could make choices not consistent with first‐order stochastic dominance.     

Measuring Inflation Expectations Uncertainty Using High‐Frequency Data

Inflation expectations play a key role in determining future economic outcomes. The associated uncertainty provides a direct gauge of how well‐anchored the inflation expectations are. We construct a model‐based measure of inflation expectations uncertainty by augmenting a standard unobserved components model of inflation with information from noisy and possibly biased measures of inflation expectations obtained from financial markets. This new model‐based measure of inflation expectations uncertainty is more accurately estimated and can provide valuable information for policymakers. Using U.S. data, we find significant changes in inflation expectations uncertainty during the Great Recession.     

Do welfare‐to‐work programmes work for long?

Evidence that welfare‐to‐work programmes in the USA succeed in boosting welfare recipients' earnings at modest cost has helped shape policy in Britain since 1997. So too has the belief that programmes that prioritise moving people into work quickly are more effective than ones that seek to enhance human capital. However, there is little evidence on how long the beneficial effects of programmes persist after individuals leave them. The analysis reported draws on the experience of 64 US welfare‐to‐work programmes that have all been evaluated using random assignment. It concludes that, on average, these programmes have a positive effect on participants' earnings for five to six years. The effects of ‘work first’ interventions are most marked early on and decline more rapidly than those of programmes emphasising human capital. Nevertheless, work first interventions typically increase earnings received over six years by more than two‐and‐a‐half times that achieved by human capital approaches.     

What Makes the Output–Inflation Trade‐Off Change? The Absence of Accelerating Deflation in Japan

It is standard to model the output–inflation trade-off as a linear relationship with a time-invariant slope. We assess empirical evidence for two sets of theories that allow for endogenous variation in the slope of the short-run Phillips curve. At an empirical level, we examine why large negative output gaps in Japan in the late 1990s did not lead to accelerating deflation but instead coincided with stable, albeit moderately negative inflation. Our results suggest that this episode is most convincingly interpreted as reflecting a gradual flattening of the Phillips curve. We find that this flattening is best explained by models with endogenous price durations. These models imply that in any economy where trend inflation is substantially lower (or substantially higher) today than in past decades, time variation in the slope of the Phillips curve has become too important to ignore.     

Forecasting National Recessions Using State‐Level Data

We investigate whether there is information useful for identifying U.S. business cycle phases contained in subnational measures of economic activity. Using a probit model to forecast the National Bureau of Economic Research expansion and recession classification, we assess the incremental information content of state‐level employment growth over a commonly used set of national‐level predictors. As state‐level data adds a large number of predictors to the model, we employ a Bayesian model averaging procedure to construct forecasts. Based on a variety of forecast evaluation metrics, we find that including state‐level employment growth substantially improves nowcasts and very short‐horizon forecasts of the business cycle phase. The gains in forecast accuracy are concentrated during months of national recession.     

FINANCIAL CONTRACTING BETWEEN MANAGERS AND VENTURE CAPITALISTS: THE ROLE OF VALUE‐ADDED SERVICES,REPUTATION SEEKING,AND BARGAINING POWER

I analyze manager and venture capitalist bargaining over the financial contract in the face of double‐sided moral hazard problems. The allocation of cash flows depends on the combined effects of value‐added services, reputation seeking, and bargaining power. Welfare is maximized when the venture capitalist has high value‐adding capabilities, the market for reputation is informationally efficient, and the manager has bargaining power. Furthermore, I consider the effect of exit strategies on the financial agreement. I also consider bidding between venture capitalists of differing abilities. Generally, the superior venture capitalist wins with a lower bid, but in some cases the inferior venture capitalist can win.