Christian Fieberg

On portfolio optimization: Forecasting asset covariances and variances based on multi-scale risk models

Purpose - The purpose of this paper is to show how investors can incorporate the multi-scale nature of asset and factor returns into their portfolio decisions and to evaluate the out-of-sample performance of such strategies. Design/methodology/approach - The authors decompose daily return series of common risk factors and of all stocks listed in the Dow Jones Industrial Index (DJI) from 2000 to 2015 into different time scales to separate short-term noise from long-run trends. Then, the authors apply various (multi-scale) factor models to determine variance-covariance matrices which are used for minimum variance portfolio selection. Finally, the portfolios are evaluated by their out-of-sample performance. Findings - The authors find that portfolios which are constructed on variance-covariance matrices stemming from multi-scale factor models outperform portfolio allocations which do not take the multi-scale nature of asset and factor returns into account. Practical implications - The results of this paper provide evidence that accounting for the multi-scale nature of return distributions in portfolio decisions might be a promising approach from a portfolio performance perspective. Originality/value - The authors demonstrate how investors can incorporate the multi-scale nature of returns into their portfolio decisions by applying wavelet filter techniques.

Is there a priced risk factor associated with conservatism

Purpose - Garcia Lara Design/methodology/approach - The authors form characteristic-balanced portfolios from dependent sorts of stocks on the firm’s degree of conservatism and the firm’s loading on the conservatism-related factor-mimicking portfolio as proposed by Daniel and Titman (1997) and Davis Findings - The tests indicate that it is the conditional conservatism characteristic rather than the factor loading that explains the cross-sectional differences in average stock returns. Consequently, they do not find evidence for a conservatism-related priced risk factor. Originality/value - This finding suggests that investors misvalue the conservatism characteristic and casts doubt on the rational risk explanation as proposed by Garcia Lara

The value relevance of “too-big-to-fail” guarantees

Purpose - – This paper aims to analyze the impact of conjectural “too-big-to-fail” (TBTF) guarantees on big and small US financial institutions’ stock prices during the 2008-2009 banking crisis. Design/methodology/approach - – The paper analyzes shocks to stock market investors’ expectations of government aid to banks in distress and respective spillover effects using an event study approach. We focus on three major events in late 2008, namely, the Lehman bankruptcy, the Citigroup bailout and the first announcement of the Capital Purchase Program (CPP) by the US Government. Findings - – The authors found significant differences in market reactions to the respective events between small and large banks. For both the Lehman and the CPP event, abnormal returns on big banks’ stocks are negative, while small banks’ stocks tend to generate positive abnormal returns. In contrast, large banks strongly outperform small banks in the case of the Citigroup bailout. Results for a control group of non-financial firms indicate that this behavior may be specific to the banking industry. The authors observed significant spillover effects to both competitors and non-competitors of Lehman and Citigroup, and concluded that while the Lehman event shook the widely held belief in an implicit TBTF subsidy to large banks, the TBTF doctrine was reinstated shortly thereafter. Originality/value - – This paper shows that conjectural TBTF guarantees are priced in by equity investors. While government aid to large banks in distress may prevent negative effects on the stability of the financial system, it may also create negative externalities by putting small banks at a competitive disadvantage. The findings suggest that US and European regulators’ recent policy measures directed at establishing reliable bank resolution schemes should be a step in the right direction to level the playing field for small and large financial institutions.

Estimates and inferences in accounting panel data sets: comparing approaches

Purpose - The purpose of our paper is to review and evaluate the methods commonly used in the accounting literature to correct for cointegrated data and data that is neither stationary nor cointegrated. Design/methodology/approach - We conduct Monte Carlo simulations according to Baltagi et al. (2011), Petersen (2009) and Gow et al. (2010) to analyze how regression results are affected by the possible nonstationarity of the variables of interest. Findings - Our results suggest that biases in regression estimates can be reduced and valid inferences can be obtained by employing robust standard errors clustered by firm, clustered by firm and time or Fama-MacBeth t-statistics based on the mean and standard error of the cross-section of coefficients from time-series regressions. Originality/value - Our findings are suited to give researchers guidance as to which estimation methods are the most reliable given the possible nonstationarity of the variables of interest.

An investor’s perspective on risk-models and characteristic-models

Purpose - In capital markets, research risk factor loadings and characteristics are considered as opposing explanations for the cross-sectional dispersion in average stock returns. However, there is little known about the performance an investor would obtain who believes either in the characteristics explanation (CB-investor) or in the risk factor loadings explanation (RB-investor). The purpose of this paper is to compare the performance of CB- and RB-investors. Design/methodology/approach - To compare the competing strategies, the authors propose a simple new approach to equity portfolio optimization in the style of Findings - The results show that investment strategies relying on characteristics (particularly on momentum) outperform risk-based investment strategies in horse races. These findings hold in- and out-of-sample. Furthermore, the characteristics-based investment strategies outperform a value-weighted market portfolio strategy in- and out-of-sample. Originality/value - The authors introduce a portfolio optimization approach that enables investors to directly link portfolio decisions to the firm’s characteristics or risk factor loadings.

The relevance of credit ratings over the business cycle

Purpose - Credit market models and the microstructure theory of the ratings market suggest that information provided by credit rating agencies becomes more relevant in recessions when agency costs are high and less relevant in expansions when agency costs are low. The purpose of this paper is to empirically test these hypotheses with regard to equity markets. Design/methodology/approach - The authors use business cycle identification algorithms to map rating events (credit rating changes and watchlist inclusions) to business cycle phases and apply the event study methodology. The results are backed by cross-sectional regressions using a variety of control variables. Findings - The authors find that the relevance of information provided by credit rating agencies for equity prices heavily depends on the level of agency costs. Furthermore, the authors detect a “flight-to-quality” during recessions in the speculative grade segment and a weakened relevance of rating events in expansions in the investment grade segment. Originality/value - This paper is the first to empirically analyse how equity investors perceive credit rating changes and watchlist inclusions over the business cycle. In the empirical analysis, the authors use a large sample of about 25,000 rating events in all Organisation for Economic Co-operation and Development markets. The presented results underline that credit ratings address the agency problem in financial markets and can thus be regarded as useful for risk management or regulation.

Forecasting Corporate Defaults in the German Stock Market

We estimate and test several default risk models using new and unique data on corporate defaults in the German stock market. While defaults were extremely rare events in the 1990s, they have been a characteristic feature of the German stock market since the early 2000s. We apply the structural Merton (1974) Distance-to-Default as well as several reduced form models. A variety of performance evaluation tools, including ROC-Analysis, calibration tests and loan market simulations, suggests that the Campbell et al. (2008) failure score should be used as a benchmark default risk model in research and also in the industry. We warn of several pitfalls associated with the Altman (1968) Z-Score and the Distance-to-Default.

Relative Performance Persistence of Financial Forecasting Models and Its Economic Implications

This paper addresses the issue of model selection risk by examining whether a models past performance in forecasting expected returns provides an indication of its future forecasting performance. For this purpose, we implement a wide range of different forecasting models and then apply the Aiolfi-Timmermann methodology for relative performance persistence measurement. We find no evidence of performance persistence in forecasting models at the top end of the historical forecasting performance rankings. Economic consequences of this purely statistical study are subsequently quantified by an out-of-sample asset allocation exercise. Simulating an asset allocator, who selects ex ante return forecasting models based on their ex post performance, we show that investors should make portfolio decisions based on forecasting models from the middle of the historical forecasting performance rankings.