10-Idiosyncratic-Volatility(ppt文档).ppt

Idiosyncratic Volatilityand Stock Returns1Debates(1/5)Traditional wisdom suggests that idiosyncratic risk does not predict stock returns.Merton(1987)shows that in the presence of market frictions where investors have limited access to information,stocks with high idiosyncratic volatility have high expected returns because investors cannot fully diversify away firm-specific risk.2Debates(2/5)Ang,Hodrick,Xing and Zhang(AHXZ,2006,2009)documented a puzzling negative relationship between return and idiosyncratic volatility.Bali and Cakici(2006)have suggested that the AHXZ result is not robust and is absent when equally-weighted portfolios are considered.3Debates(3/5)Malkiel and Xu(2002);Spiegel and Wang(2006);Chua,Goh,and Zhang(2008);and Fu(2009)find positive relation at the firm or portfolio level using monthly returns to estimate conditional idiosyncratic volatility.Baker and Wurgler(2006)and Boehme et al.(forthcoming)show that conditional on investor sentiment or short-sale constraints,idiosyncratic risk can be positively or negatively correlated with expected returns.4Debates(4/5)Huang et al.(forthcoming)find that,after controlling for return reversals,the negative relation is no longer significant.Following Fu(2009),moreover,they estimate conditional idiosyncratic volatility with an exponential GARCH(EGARCH)model using monthly returns and confirm the significantly positive relation between this proxy for idiosyncratic risk and expected returns.5Debates(5/5)However,George and Huang(2009)show that once we exclude the tax-loss selling effect in January and exclude penny stocks from the sample,the AHXZ result is very significant in equally-weighted portfolios and is robust to idiosyncratic volatility measures of different data frequency and to the returns measured in different holding periods.(Sounds like the momentum effect,doesnt it?)Low returns of the high idiosyncratic volatility stocks only exist in firms with low analyst coverage.6Ang,A.,Hodrick,R.J.,Xing,Y.,Zhang,X.,2006.The cross-section of volatility and expected returns.Journal of Finance 51,259299.AHXZ(2006)7On Page 28389Table VI.Portfolios Sorted by Volatility10Table VII.Alphas of Portfolios Sorted on Idiosyncratic Volatility The row labeled“Controlling for Size”averages across the five size quintiles to produce quintile portfolios with dispersion in idiosyncratic volatility,but which contain all sizes of firms.First,control for size by first forming quintile portfolios ranked on market capitalization.Then,within each size quintile,sort stocks into quintile portfolios ranked on idiosyncratic volatility.11Table VIIIAlphas of Portfolios Sorted on Idiosyncratic Volatility Controlling for Past Returns First sort all stocks on the basis of past returns,over the appropriate formation period,into quintiles.Then,within each momentum quintile,sort stocks into five portfolios sorted by idiosyncratic volatility,relative to the FF-3 model.The five idiosyncratic volatility portfolios are then averaged over each of the five characteristic portfolios.121314AHXZ(2009)Ang,A.,Hodrick,R.J.,Xing,Y.,Zhang,X.,2009.High idiosyncratic volatility and low returns:International and further U.S.evidence.Journal of Financial Economics 91,123.15-0.31%=(-1.224)*(0.460 0.208)1617181920Portfolio formation1.For every month,within each country,sort firms into quintile portfolios according to the W-FF idiosyncratic volatility measure in Eq.(3)using daily firm returns over the previous month.2.Aggregate the country quintile portfolios into regional portfolios,reported in the table for geographic areas(Europe and Asia),the G7 countries(with and without the U.S.),and across all 23 developed markets(with and without the U.S.).Each regional W-FF idiosyncratic volatility quintile portfolio is a value-weighted sum of the country quintile portfolios,with the weights being the market capitalization of the corresponding country quintile portfolios.Portfolio 1 contains firms with the lowest volatilities and portfolio 5 contains firms with the highest volatilities,while 51 represents a strategy that goes long the highest volatility quintile and short the lowest volatility quintile.2122Portfolio formation(1/2)1.For every month,within each country,firms are sorted into quintile portfolios according to the W-FF idiosyncratic volatility measure(see Eq.(3)using daily firm returns over the previous month.2.The country quintile portfolios are aggregated into regional quintile portfolios,for geographic areas(Europe and Asia),the G7 countries(with and without the U.S.),and across all 23 developed markets(with and without the U.S.).Each regional W-FF idiosyncratic volatility quintile portfolio is a value-weighted sum of the country quintile portfolios,with the weights being the market capitalization of the corresponding quintile portfolios in each country.23Portfolio formation(2/2)3.Within each region,there is a 51 strategy that goes long the highest idiosyncratic volatility quintile and short the quintile portfolio with the highest idiosyncratic volatility stocks.4.For the U.S.,this 51 strategy is denoted as VOLUS.The following table reports the estimates of regressions from the full sample monthly returns of the 51 regional strategies onto a constant,the three W-FF factors,and the VOLUS returns.24There are large and significant co-movements between the idiosyncratic volatility portfolio returns in international markets and in the United States.25There are large and significant co-movements between the idiosyncratic volatility portfolio returns in international markets and in the United States.VOLUS absorbs the explanatory power of MKTW and SMBW.26272829Fama-MacBeth(1973)regressions(see Eq.(4)for U.S.stocks using L-FF idiosyncratic volatility(see Eq.(1)are reported.Size is the log market capitalization of the firm at the beginning of the month,Book-to-market is the book-to-market ratio available six months prior.Lagged return is the firm return over the previous six months.Leverage is defined as the book value of debt over the sum of the book value of debt and the market value of equity.3031Idiosyncratic volatility and conditional volatility(1/3)Idiosyncratic volatility exhibits strong cross-sectional persistence and is highly correlated with conditional volatility.Disentangle the effect of lagged idiosyncratic volatility from predicted future volatility by constructing cross-sectional forecasts of future idiosyncratic volatility,Eti(t,t+1),by running a cross-sectional regression of i(t,t+1)on firm characteristics at time t.32Idiosyncratic volatility and conditional volatility(2/3)Use lagged idiosyncratic volatility,size,the book-to-market ratio,past six-month returns,stock return skewness,and turnover as characteristics.Skewnessis measured using daily returns over the previous month.Turnover is defined as the trading volume over the previous month divided by the total number of shares outstanding at the end of the month.33Idiosyncratic volatility and conditional volatility(3/3)The coefficients are estimated using data only up to time t to forecast volatility over t to t+1,and we run a new cross-sectional regression at each time period.3435Note that these portfolios are not tradable because the portfolio sorts are done using forward-looking information at the end of the month.These are the returns that would accrue to an investor with perfect knowledge of future idiosyncratic volatility over the next month.We examine these sorts because they help to disentangle the effects of lagged versus contemporaneous idiosyncratic volatility.36Things to think about(1/7)The higher idiosyncratic volatility(risk),the lower stock returns.Counter-intuitive!What we can do is to link this story to other scenarios(regarding risks or behaviors)and make it reasonable.However,according to Table VII,it is possible but not easy to find explanations based on risks.How about behaviors?Invesor sentiment?37Things to think about(2/7)Hirshleifer(2001)sketches a framework for understanding decision biases,evaluates the a priori arguments and the capital market evidence bearing on the importance of investor psychology for security prices,and reviews recent models.38Things to think about(3/7)Statman,Thorley and Vorkink(2006)find that share turnover is positively related to lagged returns for many months.The relationship holds for both market-wide and individual security turnover,which we interpret as evidence of investor overconfidence and the disposition effect,respectively.The higher turnover,the higher sentiment(overconfidence),and the lower stock return.39Things to think about(4/7)Kumar and Lee(2006)find that systematic retail trading explains return comovements for stocks with high retail concentration(i.e.,small-cap,value,lower institutional ownership,and lower-priced stocks),especially if these stocks are also costly to arbitrage.Their findings support a role for investor sentiment in the formation of returns.The higher systematic retail trading,the higher the current returns.40Things to think about(5/7)Kaniel,Saar,and Titman(2008)document positive excess returns in the month following intense buying by individuals and negative excess returns after individuals sell,which we show is distinct from the previously shown past return or volume effects.41Things to think about(6/7)Baker and Stein(2004)build a model that helps to explain why increases in liquidity such as lower bidask spreads,a lower price impact of trade,or higher turnoverpredict lower subsequent returns in both firm-level and aggregate data.The model features a class of irrational investors who underreact to the information contained in order flow,thereby boosting liquidity.42Things to think about(7/7)Any idea?43ReferencesBali,T.G.,and N.Cakici.2008.Idiosyncratic Volatility and the Cross-Section of Expected Returns.Journal of Financial and Quantitative Analysis 43:2958.Boehme,R.,B.Danielsen,P.Kumar,and S.Sorescu.Forthcoming.forthcoming.Idiosyncratic Risk and the Cross-Section ofStock Returns:Merton(1987)Meets Miller(1977).Journal of Financial Markets.Chua,C.T.,J.Goh,and Z.Zhang.2008.Expected Volatility,Unexpected Volatility,and the Cross-Section of Stock Returns.Working Paper,Singapore Management University.Fu,F.2009.Idiosyncratic Risk and the Cross-Section of Expected Stock Returns.Journal of Financial Economics 91:2437.George,T.J.and C.Hwang.2008.Why Do Firms with High Idiosyncratic Volatility and High Trading Volume Volatility Have Low Returns?Working Paper,Nanyang Technological UniversityHuang,W.,Q.Liu,S.G.Rhee,and L.Zhang.Forthcoming.Return Reversals,Idiosyncratic Risk,and Expected Returns.Review of Financial Studies.Malkiel,B.G.,and Y.Xu.2002.Idiosyncratic Risk and Security Returns.Working Paper,University of Texas at Dallas.Merton,R.C.1987.Presidential Address:A Simple Model of Capital Market Equilibrium with Incomplete Information.Journal of Finance 42:483510.Spiegel,M.,and X.Wang.2006.Cross-Sectional Variation in Stock Returns:Liquidity 44