Models for realized covariance matrices may suffer from the curse of dimensionality as more traditional multivariate volatility models (such as GARCH and stochastic volatility). Within the class of realized covariance models, we focus on the Wishart specification introduced by C. Gourieroux, J. Jasiak, and R. Sufana [2009. The Wishart autoregressive process of multivariate stochastic volatility. Journal of Econometrics 150, no. 2: 167-81] and analyze here the forecasting performances of the parametric restrictions discussed in M. Bonato [2009. Estimating the degrees of freedom of the realized volatilityWishart autoregressive model. Manuscript available at http://ssrn.com/abstract=1357044], which are motivated by asset features such as their economic sector and book-to-market or price-to-earnings ratios, among others. Our purpose is to verify if restricted model forecasts are statistically equivalent to full-model specification, a result that would support the use of restrictions when the problem cross-sectional dimension is large.

To estimate the bid-ask spread, we propose a new method that resembles the Roll measure (1984) but has some key advantages: it is fully independent of bid-ask bounces and benefits from a wider information set, namely, close, high, and low prices, which are readily available. Assessed against other low-frequency estimates, our estimator generally provides the highest cross-sectional and average time-series correlations with the TAQ effective spread benchmark. Moreover, it delivers the most accurate estimates for less liquid stocks. Finally, our estimator improves the measurement of systematic liquidity risk and commonality in liquidity for individual stocks and sorted portfolios.

We propose a new method to estimate the bid-ask spread when quote data are not available. Compared to other low-frequency estimates, it utilizes a wider information set, namely, close, high, and low prices, which are readily available. In the absence of end-of-day quote data, it generally provides the highest cross-sectional and average time-series correlations with the TAQ effective spread benchmark. Moreover, it delivers the most accurate estimates for less liquid stocks. Our estimator has many potential applications including an accurate measurement of transaction cost, systematic liquidity risk, and commonality in liquidity for U.S. stocks dating back almost one century.

We propose a new method to estimate the bid-ask spread when quote data are not available. Compared to other low-frequency estimates, this method utilizes a wider information set, namely, readily available close, high, and low prices. In the absence of end-of-day Quote data, this method generally provides the highest cross-sectional and average time-series correlations with the TAQ effective spread benchmark. Moreover, it delivers the most accurate estimates for less liquid stocks. Our estimator has many potential applications, including an accurate measurement of transaction cost, systematic liquidity risk, and commonality in liquidity for U.S. stocks dating back almost one century.

Most ETF indexes offer active management in disguise, Angelo Ranaldo and Rainer Haeberle argue. This applies to plain vanilla indexes, which provide momentum strategies on the sly, as well as to smart beta indexes

In this paper, we construct the three-factor model introduced by Chen et al. (2010) for a European sample covering 10 countries from the European Monetary Union and the period from 1990 to 2006. Two key findings result. First, we show that the properties of the European factors are comparable to those of the U.S. factors. Second, we show that the alternative three-factor model's explanatory power is either equal or superior to the explanatory power of traditional models when applied to five commonly known stock market anomalies. Our results thus suggest the use of international versions of the Chen et al. (2010) factor model in addition to traditional factor models in international empirical finance research.

We show how employee stock options can be valued under the new reporting standards IFRS 2 and FASB 123 (revised) for share-based payments. Both standards require companies to expense employee stock options at fair value. We propose a new valuation model, referred to as Enhanced American model, that complies with the new standards and produces fair values often lower than those generated by traditional models such as the Black-Scholes model or the adjusted Black-Scholes model. We also provide a sensitivity analysis of model input parameters and analyze the impact of the parameters on the fair value of the option. The valuation of employee stock options requires an accurate estimation of the exercise behavior. We show how the exercise behavior can be modeled in a binomial tree and demonstrate the relevance of the input parameters in the calibration of the model to an estimated expected life of the option. http://www.springerlink.com/content/ynm870p38rj57226/

The article examines strategies for making financial investments by using a decomposition of the non-central tracking error variance to indicate how actively assets are managed. This method examines how much risk the asset manager takes in investments by analyzing positive and negative returns. Two mathematical models are presented to analyze the active management of investments. The authors believe that their decomposition method and tracking error variance generate data that is not formally found by traditional analysis methods. [http://www.manuel-ammann.com/pdf/Ammann_Tracking_Error_Variance_Decomposition_Final.pdf]

This paper investigates the announcement effects of CoCo bonds issued by global banks between January 2009 and June 2014. Using a sample of 34 financial institutions, we examine abnormal stock price reactions and CDS spread changes before and after the announcement dates. We find that the announcement of CoCos correlates with positive abnormal stock returns and negative CDS spread changes in the immediate post-announcement period. We explain these effects with a set of theories including the lowered probability of costly bankruptcy proceedings, a signaling framework based on pecking order theory and the cost advantage of CoCos over equity (tax shield).

We investigate the pricing of convertible bonds on the French convertible bond market using daily market prices for a period of 18 months. Instead of a firm-value model as used in previous studies, we use a stock-based binomial-tree model with exogenous credit risk that accounts for all important convertible bond specifications and is therefore well suited for pricing convertible bonds. The empirical analysis shows that the theoretical values for the analyzed convertible bonds are on average more than 3% higher than the observed market prices. This result applies to both the standard convertibles and the exchangeable bonds in our sample. The difference between market and model prices is greater for out-of-the-money convertibles than for at- or in-the-money convertibles. A partition of the sample according to maturity indicates that there is a positive relationship between underpricing and maturity with decreasing mispricing for bonds with shorter time to maturity.