Semiparametric Conditional Factor Models PDF Download
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| Author | : Qihui Chen |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2023 |
| Genre | : |
| ISBN | : |
Download Semiparametric Conditional Factor Models Book in PDF, ePub and Kindle
This paper introduces a simple and tractable sieve estimation of semiparametric conditional factor models with latent factors. We establish large-N-asymptotic properties of the estimators without requiring large T. We also develop a simple bootstrap procedure for conducting inference about the conditional pricing errors as well as the shapes of the factor loading functions. These results enable us to estimate conditional factor structure of a large set of individual assets by utilizing arbitrary nonlinear functions of a number of characteristics without the need to pre-specify the factors, while allowing us to disentangle the characteristics' role in capturing factor betas from alphas (i.e., undiversifiable risk from mispricing). We apply these methods to the cross-section of individual U.S. stock returns and find strong evidence of large nonzero pricing errors that combine to produce arbitrage portfolios with Sharpe ratios above 3. We also document a significant decline in apparent mispricing over time.
| Author | : Szymon Borak |
| Publisher | : |
| Total Pages | : 149 |
| Release | : 2008 |
| Genre | : |
| ISBN | : |
Download Dynamic Semiparametric Factor Models Book in PDF, ePub and Kindle
| Author | : Liyan Yang |
| Publisher | : |
| Total Pages | : 39 |
| Release | : 2014 |
| Genre | : |
| ISBN | : |
Download Testing Conditional Factor Models Book in PDF, ePub and Kindle
Recent studies of conditional factor models do not specify conditioning information but use data from small windows to estimate the time series of conditional alphas and betas. In this paper, we propose a nonparametric method using an optimal window to estimate time-varying coefficients. In addition, we offer two empirical tests of a conditional factor model. Using our new method, we examine the performance of the conditional CAPM and the conditional Fama-French three-factor model in explaining the return variations of portfolios sorted by size, book-to-market ratios, and past returns, for which recent literature has generated controversial results. We find that, although in general the conditional FF model outperforms the conditional CAPM, both models fail to explain well-known asset-pricing anomalies. Moreover, for both models, the failure is more pronounced for the equally-weighted portfolios than for the value-weighted ones.
| Author | : Andrew Ang |
| Publisher | : |
| Total Pages | : 57 |
| Release | : 2011 |
| Genre | : Economics |
| ISBN | : |
Download Testing conditional factor models Book in PDF, ePub and Kindle
Using nonparametric techniques, we develop a methodology for estimating conditional alphas and betas and long-run alphas and betas, which are the averages of conditional alphas and betas, respectively, across time. The tests can be performed for a single asset or jointly across portfolios. The traditional Gibbons, Ross, and Shanken (1989) test arises as a special case of no time variation in the alphas and factor loadings and homoskedasticity. As applications of the methodology, we estimate conditional CAPM and multifactor models on book-to-market and momentum decile portfolios. We reject the null that long-run alphas are equal to zero even though there is substantial variation in the conditional factor loadings of these portfolios.
| Author | : Petra Burdejová |
| Publisher | : |
| Total Pages | : |
| Release | : 2017 |
| Genre | : |
| ISBN | : |
Download Dynamic Semi-parametric Factor Model for Functional Expectiles Book in PDF, ePub and Kindle
| Author | : |
| Publisher | : |
| Total Pages | : |
| Release | : 2008 |
| Genre | : |
| ISBN | : |
Download Dynamic Semiparametric Factor Models in Risk Neutral Density Estimation Book in PDF, ePub and Kindle
| Author | : Enzo Giacomini |
| Publisher | : |
| Total Pages | : 19 |
| Release | : 2017 |
| Genre | : |
| ISBN | : |
Download Dynamic Semiparametric Factor Models in Risk Neutral Density Estimation Book in PDF, ePub and Kindle
Dimension reduction techniques for functional data analysis model and approximate smooth random functions by lower dimensional objects. In many applications the focus of interest lies not only in dimension reduction but also in the dynamic behaviour of the lower dimensional objects. The most prominent dimension reduction technique - functional principal components analysis - however, does not model time dependences embedded in functional data. In this paper we use dynamic semiparametric factor models (DSFM) to reduce dimensionality and analyse the dynamic structure of unknown random functions by means of inference based on their lower dimensional representation. We apply DSFM to estimate the dynamic structure of risk neutral densities implied by prices of option on the DAX stock index.
| Author | : Likai Chen |
| Publisher | : |
| Total Pages | : |
| Release | : 2017 |
| Genre | : |
| ISBN | : |
Download Dynamic Semiparametric Factor Model with a Common Break Book in PDF, ePub and Kindle
| Author | : Thomas B. Fomby |
| Publisher | : Emerald Group Publishing |
| Total Pages | : 407 |
| Release | : 2006-03-01 |
| Genre | : Business & Economics |
| ISBN | : 0762312742 |
Download Econometric Analysis of Financial and Economic Time Series Book in PDF, ePub and Kindle
Talks about the time varying betas of the capital asset pricing model, analysis of predictive densities of nonlinear models of stock returns, modelling multivariate dynamic correlations, flexible seasonal time series models, estimation of long-memory time series models, application of the technique of boosting in volatility forecasting, and more.
| Author | : Wolfgang Karl Härdle |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 317 |
| Release | : 2012-08-27 |
| Genre | : Mathematics |
| ISBN | : 364217146X |
Download Nonparametric and Semiparametric Models Book in PDF, ePub and Kindle
The statistical and mathematical principles of smoothing with a focus on applicable techniques are presented in this book. It naturally splits into two parts: The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers. The material is easy to accomplish since the e-book character of the text gives a maximum of flexibility in learning (and teaching) intensity.
