Nonparametric Analysis of Hedge Funds Lifetimes

Most of hedge funds databases are now keeping history of dead funds in order to control biases in empirical analysis. It is then possible to use these data for the analysis of hedge funds lifetimes and survivorship. This paper proposes two nonparametric specifications of duration models. First, the single risk model is an alternative to parametric duration models used in the literature. Second, the competing risks model consider the two reasons why hedge funds stop reporting. We apply the two models to hedge funds data and compare our results to the literature. In particular, we show that a cohort effect must be considered. Moreover, the reason of the exit is a crucial information for the analysis of funds' survival as for a large part of disappearing funds, exit cannot be explained by low performance or low level of assets.

Trading volume and Arbitrage

Decomposing returns into market and stockspecific components is common practice and forms the basis ofpopular asset pricing models. What about volume? Can volumebe decomposed in the same way as returns? Lo and Wang(2000) suggest such a decomposition. Our paper contributes tothis literature in two different ways. First, we provide a modelto explain why volumes deviate from the benchmark. Ourinterpretation is in terms of arbitrage strategies and liquidity.Second, we propose a new efficient screening tool that allowspractitioners to extract specific information from volume timeseries. We provide an empirical illustration of the relevance andthe possible uses of our approach on daily data from the FTSEindex from 2000 to 2002

Non Parametric Instrumental Regression

The focus of the paper is the nonparametric estimation of an instrumental regression function ϕ defined by conditional moment restrictions stemming from a structural econometric model: E [Y − ϕ (Z) | W] = 0, and involving endogenous variables Y and Z and instruments W . The function ϕ is the solution of an ill-posed inverse problem and we propose an estimation procedure based on Tikhonov regularization. The paper analyses identification and overidentification of this model and presents asymptotic properties of the estimated nonparametric instrumental regression function.

Nonparametric Analysis of Hedge Funds Lifetimes

Most of hedge funds databases are now keeping history of dead funds in order to control biases in empirical analysis. It is then possible to use these data for the analysis of hedge funds lifetimes and survivorship. This paper proposes two nonparametric specifications of duration\ud models. First, the single risk model is an alternative to parametric duration models used in the literature. Second, the competing risks model consider the two reasons why hedge funds stop reporting. We apply the two models to hedge funds data and compare our results to the literature. In particular, we show that a cohort effect must be considered. Moreover, the reason of the exit is a crucial information for the analysis of funds' survival as for a large part of disappearing funds, exit cannot be explained by low performance or low level of assets

Nonparametric Instrumental Regression

The focus of the paper is the nonparametric estimation of an instrumental regression function P defined by conditional moment restrictions stemming from a structural econometric model : E[Y-P(Z)|W]=0 and involving endogenous variables Y and Z and instruments W. The function P is the solution of an ill-posed inverse problem and we propose an estimation procedure based on Tikhonov regularization. The paper analyses identification and overidentification of this model and presents asymptotic properties of the estimated nonparametric instrumental regression function.Nous nous intéressons à l'estimation non paramétrique d'une fonction de régression instrumentale P . Cette fonction est définie à l'aide de conditions de moment provenant d'un modèle économétrique structurel de la forme E[Y-P(Z)|W]=0 où les Y et Z sont des variables endogènes et les W des instruments. La fonction P est alors la solution d'un problème inverse mal posé, et nous proposons une procédure d'estimation utilisant la régularisation de Tikhonov. Le papier analyse l'identification et la suridentification du modèle et donne les propriétés asymptotiques de l'estimateur de la régression instrumentale non paramétrique

Nonparametric Analysis of Hedge Funds Lifetimes

Most of hedge funds databases are now keeping history of dead funds in order to control biases in empirical analysis. It is then possible to use these data for the analysis of hedge funds lifetimes and survivorship. This paper proposes two nonparametric specifications of duration models. First, the single risk model is an alternative to parametric duration models used in the literature. Second, the competing risks model consider the two reasons why hedge funds stop reporting. We apply the two models to hedge funds data and compare our results to the literature. In particular, we show that a cohort effect must be considered. Moreover, the reason of the exit is a crucial information for the analysis of funds' survival as for a large part of disappearing funds, exit cannot be explained by low performance or low level of assets

When Market Illiquidity Generates Volumes

We develop a model of the daily return-volume relationship which incorporates information and liquidity shocks. First, we distinguish between two trading strategies, information-based and liquidity-based trading and suggest that their respective impacts on returns and volume should be modeled differently. Second, we integrate the microstructure setting of Grossman-Miller (1988) with the information flow perspective of Tauchen-Pitts (1983) and derive a modified MDH model with two latent factors related to information and liquidity. Our model explains how the liquidity frictions can increase the daily traded volume, in the presence of liquidity arbitragers. Finally, we propose a stock-specific liquidity measure using daily return and volume observations of FTSE100 stocks.Volatility-volume relationship; mixture of distribution hypothesis; liquidity shocks; informed trading; liquidity arbitrage

Non Parametric Instrumental Regression

The focus of the paper is the nonparametric estimation of an instrumental regression function ϕ defined by conditional moment restrictions stemming from a structural econometric model: E [Y − ϕ (Z) | W] = 0, and involving endogenous variables Y and Z and instruments W . The function ϕ is the solution of an ill-posed inverse problem and we propose an estimation procedure based on Tikhonov regularization. The paper analyses identification and overidentification of this model and presents asymptotic properties of the estimated nonparametric instrumental regression function

The role of Myostatin polymorphisms in the Finnhorse and Shetland pony breeds

Myostatin, encoded by the MSTN gene, is a member of the transforming growth factor β that normally acts to limit skeletal muscle mass by regulating both the number and growth of muscle fibers. Natural mutations that decrease the amounts of myostatin and/or inhibit its function have been identified in several cattle, sheep and dog breeds, where loss-of-function mutations cause increased skeletal muscle mass and produce a phenotype known as “double-muscling”. This gene has also been associated with racing performance in Thoroughbreds, where studies have found two Myostatin polymorphisms (PR3737 and PR8604) to be strongly associated with genetic potential and athletic phenotype, affecting both speed and muscularity, although no such associations have been found in harness-racing breeds such as the Swedish-Norwegian Coldblooded trotter. Single nucleotide polymorphisms have also been shown to have an effect on conformation, where these SNPs have been found to have different genotype distributions between horse breeds with different origin, morphology and uses. Such is the case with Icelandic horses, where significantly different genotype distributions for another SNP, PR5826, were observed between horses used for different purposes. This study investigated the association of these MSTN polymorphisms with harness racing performance in the Finnhorse and body conformation in the Shetland pony. Finnhorses used for different disciplines were genotyped for three SNPs (PR5826, PR3737 and PR8604) and were divided into three categories based on their use: harness racing horses (n=223), representing those horses with at least one start in harness racing; riding horses (n=79) used for recreational riding of which owner questionnaire information was available and horses with no performance data (n=112). An association analysis was performed on the raced group, where the genotypes were evaluated for association with life-time racing performance results for: number of starts, victories, placings (1-3) and unplaced, along with proportions for each of these traits, as well as earnings, earnings per start and race times for volt- and autostart. Additionally, the genotypes were evaluated for association with these performance results obtained between 3 and 6 years of age (n=207) and 7 to 10 years of age (n=183). Significant associations were found in the 3 to 6 years of age group as well as the 7 to 10 group. In both cases, TT horses for PR3737 earned more money, were faster for both racing methods and presented a lower number of disqualifications than the CT horses. Concerning PR8604, a similar effect was observed, where the TT horses also earned more money, were faster in auto start racing method and presented a lower number of disqualifications. This study concluded that MSTN sequence polymorphisms seem to have an effect on harness racing performance in the Finnhorse. Concerning body conformation on the Shetland pony, a breed which presents a “Heavy” body type and a “Light” body type, no significant associations were found between conformation and MSTN genotype. However, further investigation is needed before drawing the conclusion that MSTN has no effect on Shetland pony conformation. This is due to the small sample size and classification method, which could be expanded to include morphological measurements