Stock return forecasting some new evidence
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Stock return forecasting some new evidence
Accepted ManuscriptStock Return Forecasting: Some New EvidenceDinh Hoang Bach Phan. Susan Sunila Sharma. Paresh Kumar NarayanPII:DOI:Reference:Si 057- Stock return forecasting some new evidence -5219(15100084-8 doi: 10.1016j.irfa.2015.05.002FINANA841To appeal in:International Review of Financial AnalysisReceived date:Revised date:Accepted date:419714207342137Please cite this article as: Plum, D.II.B.. Sharma, s.s. & Narayan. P.K., Stock Return Forecasting: Some New Evidence. International Stock return forecasting some new evidence Review of Financial Analysis (2015), doi: 10.1016/j.irfa.2015.05.002This is a PDF file of an unedited manuscript that has been accepted for publicatioStock return forecasting some new evidence
n. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and reviAccepted ManuscriptStock Return Forecasting: Some New EvidenceDinh Hoang Bach Phan. Susan Sunila Sharma. Paresh Kumar NarayanPII:DOI:Reference:Si 057- Stock return forecasting some new evidence ld affect the content, and all legal disclaimers that apply to the journal pertain.Stock Return Forecasting: Some New EvidenceDinh Hoang Bach Phan. Susan Sunila Shanna. Paresh Kumar NarayanMailing AddressDinh Hoang Bach Phan Centre for Economics and Financial Econometrics ResearchDeakin University 2 Stock return forecasting some new evidence 21 Burwood Highway Burwood. Victoria 3125AustraliaEmail: dphan@deakin.edu.au1ACCEPTED MANUSCRIPTStock Return Forecasting: Some New EvidenceABSTRACTThiStock return forecasting some new evidence
s paper makes three contributions to the literature on forecasting stock rentals. First, unlike the extant literature on oil price and stock returns, Accepted ManuscriptStock Return Forecasting: Some New EvidenceDinh Hoang Bach Phan. Susan Sunila Sharma. Paresh Kumar NarayanPII:DOI:Reference:Si 057- Stock return forecasting some new evidence quency used but also on the estimator. Second, out-of-sample forecasting of returns is sector-dependent, suggesting that oil price is relatively more important for some sectors than others. Third, we examine the determinants of out-of-sample predictability for each sector using industry characterist Stock return forecasting some new evidence ics and find strong evidence that return predictability has links to certain industry characteristics, such as book-to-niarket ratio.dividend yield, sStock return forecasting some new evidence
ize, price earnings ratio, and trading volume.Keywords: Slock returns; Oil price: Predictability: Forecasting: Out-of-sample.1. IntroductionSeveral stAccepted ManuscriptStock Return Forecasting: Some New EvidenceDinh Hoang Bach Phan. Susan Sunila Sharma. Paresh Kumar NarayanPII:DOI:Reference:Si 057- Stock return forecasting some new evidence ate, interest rates, aggregate output predict stock returns (see, inter olio, Fama, 1981; Campbell, 1987; Fama and French, 1988,1989; Campbell and Shiller, 1988a,b; Kothari and Shanken, 1997; Pontiff and Schall, 1998; Lamont, 1998; Rapach et al., 2005). However, the literature finds relatively limit Stock return forecasting some new evidence ed evidence of predictability using out-of-sample tests. The general conclusion is that the evidence for stock return (US market) predictability is prStock return forecasting some new evidence
edominantly in-sample; and it is not robust to out-of-sample evaluations (see, for example, Bossaerts and Million, 1999; Goyal and Welch, 2003; BrennaAccepted ManuscriptStock Return Forecasting: Some New EvidenceDinh Hoang Bach Phan. Susan Sunila Sharma. Paresh Kumar NarayanPII:DOI:Reference:Si 057- Stock return forecasting some new evidence erformance of several predictive regression models for the equity premium using a wide range of financial ratios and macroeconomic predictors. They find that the out-of-sample stock return forecast fails to beat the simple historical average benchmark forecast. The historical average forecast assume Stock return forecasting some new evidence s that the coefficients of the predictors are equal to zero, implying that the information from economic predictors is not useful for predicting stockStock return forecasting some new evidence
returns. They also test the predictive power of the predictors by including all predictors in a single model, which they refer to as the "kitchen sinAccepted ManuscriptStock Return Forecasting: Some New EvidenceDinh Hoang Bach Phan. Susan Sunila Sharma. Paresh Kumar NarayanPII:DOI:Reference:Si 057- Stock return forecasting some new evidence parameterised models typically perform very poorly in out-of-sample evaluations (Welch and Goyal, 2008). They conclude that the predictive regression models are not stable and are unable to beat the historical average. Stock return forecasting some new evidence Accepted ManuscriptStock Return Forecasting: Some New EvidenceDinh Hoang Bach Phan. Susan Sunila Sharma. Paresh Kumar NarayanPII:DOI:Reference:Si 057-Gọi ngay
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