Analyst Forecast Skewness And Cross Section Stock Returns
DOWNLOAD
Download Analyst Forecast Skewness And Cross Section Stock Returns PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Analyst Forecast Skewness And Cross Section Stock Returns book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Analyst Forecast Skewness And Cross Section Stock Returns
DOWNLOAD
Author : Cai Zhu
language : en
Publisher:
Release Date : 2015
Analyst Forecast Skewness And Cross Section Stock Returns written by Cai Zhu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
In the paper, we show a significant economic linkage between analyst EPS forecast skewness and cross section stock returns. The effect on stock return of our skewness measure is quite different from that based on skewness calculated from options or high frequency data. Literature shows that, using such skewness as a signal, trading profit is generated mostly from over-valued stocks with high positive skewness, which is consistent with Barberis and Huang (2008)'s lottery arguments. However, we find that for our analyst forecast skewness, trading profit mainly comes from those stocks with negative skewness. Long-short strategy purchasing stocks with low forecast skewness and shorting those with high forecast skewness earns annualized abnormal returns 11% with sharpe ratio 0.64. Our study suggests that negative skewness stocks tend to be undervalued (risk-adjusted returns for negative skewness stocks are significantly positive), while stocks with high positive skewness have fair prices (risk-adjusted returns for positive skewness stocks are not significant). Our empirical results are closely related with investors learning behavior and consistent with Veronesi (1999) theory. In the model, Veronesi shows that when investors cannot observe cash flow growth rate, they tend to overreact to bad news, push current stock price down, such behavior will lead to higher future stock returns. Our results also hold when using robust skewness defined as the gap between analyst EPS forecast mean and median.
Option Implied Volatility Skewness And Kurtosis And The Cross Section Of Expected Stock Returns
DOWNLOAD
Author : Turan G. Bali
language : en
Publisher:
Release Date : 2019
Option Implied Volatility Skewness And Kurtosis And The Cross Section Of Expected Stock Returns written by Turan G. Bali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
We develop an ex-ante measure of expected stock returns based on analyst price targets. We then show that ex-ante measures of volatility, skewness, and kurtosis implied from stock option prices are positively related to the cross section of ex-ante expected stock returns. While expected returns are related to both the systematic and unsystematic components of volatility, only the unsystematic components of skewness and kurtosis are related to the cross section of expected stock returns after controlling for other variables known to be related to the cross section of expected stock returns or analyst forecast bias.
Skewness And Dispersion Of Opinion And The Cross Section Of Stock Returns
DOWNLOAD
Author : Jinghan Meng
language : en
Publisher:
Release Date : 2015
Skewness And Dispersion Of Opinion And The Cross Section Of Stock Returns written by Jinghan Meng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
We show that the degree of dispersion and asymmetry of analysts' earnings forecasts is related to future stock returns. When skewness is negative, future returns are decreasing in the degree of dispersion of analysts' earnings forecasts; when skewness is positive, future returns are increasing in the degree of dispersion of analysts earnings forecasts. We develop a model that incorporates dispersion and asymmetry in agents' beliefs that can account for these empirical facts.
Forecasting Crashes
DOWNLOAD
Author : Joseph Chen
language : en
Publisher:
Release Date : 2000
Forecasting Crashes written by Joseph Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Financial crises categories.
This paper is an investigation into the determinants of asymmetries in stock returns. We develop a series of cross-sectional regression specifications which attempt to forecast skewness in the daily returns of individual stocks. Negative skewness is most pronounced in stocks that have experienced: 1) an increase in trading volume relative to trend over the prior six months; and 2) positive returns over the prior thirty-six months. The first finding is consistent with the model of Hong and Stein (1999), which predicts that negative asymmetries are more likely to occur when there are large differences of opinion among investors. The latter finding fits with a number of theories, most notably Blanchard and Watson's (1982) rendition of stock-price bubbles. Analogous results also obtain when we attempt to forecast the skewness of the aggregate stock market, though our statistical power in this case is limited.
Analyst Forecasts And The Cross Section Of European Stock Returns
DOWNLOAD
Author : Steven K. Todd
language : en
Publisher:
Release Date : 2005
Analyst Forecasts And The Cross Section Of European Stock Returns written by Steven K. Todd and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
We examine revisions to earnings forecasts by equity analysts and their role in predicting stock returns. We provide evidence that European stocks with net upward revised forecasts earn higher future returns than otherwise similar stocks. This effect is not concentrated in small stocks, stocks with low analyst coverage, or stocks with low book-to-market ratios. We find differences in the return continuation patterns of stocks with upward versus downward revisions, namely, bad news travels quickly, but good news travels slowly. This result is consistent with investors' attaching greater significance to poor earnings forecasts, but adopting a wait-and-see approach to good news.
Opposite Sides Of A Skewed Bet
DOWNLOAD
Author : Christian L. Goulding
language : en
Publisher:
Release Date : 2018
Opposite Sides Of A Skewed Bet written by Christian L. Goulding and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
I test the predictions of a new asset pricing model regarding the interaction of ex-ante return skewness and the dispersion of analysts' earnings forecasts on a sample of U.S. stocks. I present evidence that skewness and forecast dispersion have an interactive pricing impact, that forecast dispersion has no marginal impact unless stocks exhibit ex-ante skewness, and that higher risk or risk aversion is associated with a deepening of their joint effect. The averagereturn gap between stocks in the 5th and 95th percentiles by skewness and dispersion is 1.61% monthly (19.3% annualized). These otherwise anomalous discoveries comprise new cross-sectional features of expected stock returns.
Analyst Price Target Expected Returns And Option Implied Risk
DOWNLOAD
Author : Turan G. Bali
language : en
Publisher:
Release Date : 2015
Analyst Price Target Expected Returns And Option Implied Risk written by Turan G. Bali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Motivated by the nature of asset pricing models, we investigate the cross-sectional relation between the market's ex-ante view of a stock's risk and the stock's ex-ante expected return. We demonstrate that an ex-ante measure of expected returns based on analyst price targets is highly related to the market's required rate of return. Using this measure, we show that ex-ante measures of volatility, skewness, and kurtosis derived from option prices are positively related to ex-ante expected returns. We then decompose the risk measures into systematic and unsystematic components and find that while expected returns are related to both systematic and unsystematic variance risk, only the unsystematic components of skewness and kurtosis are important for explaining the cross-section of expected stock returns. The results are consistent using two different approaches to measuring ex-ante risk and robust to controls for other variables related to stock returns and analyst bias.
Forecasting Skewness In Stock Returns
DOWNLOAD
Author : Mariko Fujii
language : en
Publisher:
Release Date : 2006
Forecasting Skewness In Stock Returns written by Mariko Fujii and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Differences Of Opinion And The Cross Section Of Stock Returns
DOWNLOAD
Author : Karl Diether
language : en
Publisher:
Release Date : 2008
Differences Of Opinion And The Cross Section Of Stock Returns written by Karl Diether and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
We provide evidence that stocks with higher dispersion in analysts' earnings forecasts earn lower future returns than otherwise similar stocks. This effect is most pronounced in small stocks, and stocks that have performed poorly over the past year. Interpreting dispersion in analysts' forecasts as a proxy for differences in opinion about a stock, we show that this evidence is consistent with the hypothesis that prices will reflect the optimistic view whenever investors with the lowest valuations do not trade. By contrast, our evidence is inconsistent with a view that dispersion in analysts' forecasts proxies for risk.
Essays On Predicting And Explaining The Cross Section Of Stock Returns
DOWNLOAD
Author : Xun Zhong
language : en
Publisher:
Release Date : 2019
Essays On Predicting And Explaining The Cross Section Of Stock Returns written by Xun Zhong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
My dissertation consists of three chapters that study various aspects of stock return predictability. In the first chapter, I explore the interplay between the aggregation of information about stock returns and p-hacking. P-hacking refers to the practice of trying out various variables and model specifications until the result appears to be statistically significant, that is, the p-value of the test statistic is below a particular threshold. The standard information aggregation techniques exacerbate p-hacking by increasing the probability of the type I error. I propose an aggregation technique, which is a simple modification of 3PRF/PLS, that has an opposite property: the predictability tests applied to the combined predictor become more conservative in the presence of p-hacking. I quantify the advantages of my approach relative to the standard information aggregation techniques by using simulations. As an illustration, I apply the modified 3PRF/PLS to three sets of return predictors proposed in the literature and find that the forecasting ability of combined predictors in two cases cannot be explained by p-hacking. In the second chapter, I explore whether the stochastic discount factors (SDFs) of five characteristic-based asset pricing models can be explained by a large set of macroeconomic shocks. Characteristic-based factor models are linear models whose risk factors are returns on trading strategies based on firm characteristics. Such models are very popular in finance because of their superior ability to explain the cross-section of expected stock returns, but they are also criticized for their lack of interpretability. Each characteristic-based factor model is uniquely characterized by its SDF. To approximate the SDFs by a comprehensive set of 131 macroeconomic shocks without overfitting, I employ the elastic net regression, which is a machine learning technique. I find that the best combination of macroeconomic shocks can explain only a relatively small part of the variation in the SDFs, and the whole set of macroeconomic shocks approximates the SDFs not better than only few shocks. My findings suggest that behavioral factors and sentiment are important determinants of asset prices. The third chapter investigates whether investors efficiently aggregate analysts' earnings forecasts and whether combinations of the forecasts can predict announcement returns. The traditional consensus forecast of earnings used by academics and practitioners is the simple average of all analysts' earnings forecasts (Naive Consensus). However, this measure ignores that there exists a cross-sectional variation in analysts' forecast accuracy and persistence in such accuracy. I propose a consensus that is an accuracy-weighted average of all analysts' earnings forecasts (Smart Consensus). I find that Smart Consensus is a more accurate predictor of firms' earnings per share (EPS) than Naive Consensus. If investors weight forecasts efficiently according to the analysts' forecast accuracy, the market reaction to earnings announcements should be positively related to the difference between firms' reported earnings and Smart Consensus (Smart Surprise) and should be unrelated to the difference between firms' reported earnings and Naive Consensus (Naive Surprise). However, I find that market reaction to earnings announcements is positively related to both measures. Thus, investors do not aggregate forecasts efficiently. In addition, I find that the market reaction to Smart Surprise is stronger in stocks with higher institutional ownership. A trading strategy based on Expectation Gap, which is the difference between Smart and Naive Consensuses, generates positive risk-adjusted returns in the three-day window around earnings announcements.