英语论文网

Contents
Abstract
Acknowledge
Chapter 1: Introduction
Chapter 2: Literature Review
Chapter 3: Data Methodology
Chapter 4: Results
Chapter 5: Conclusion
Listed Charts and Tables
Reference

Abstract
Economists have代写留学生论文 evaluated the risk of a given stock by its beta, or the sensitivity of the stock's return to the return on the market as a whole. More recently, a beta-return model has been developed in which the required return on a stock is determined by its beta.
Fama and French (1992) show conclusively that relationship between cross-sectional stock return and beta is flat. Following Fama and French’s cross-sectional framework but allowing for up and down market conditions, Pettengill et al.’s (1995) constant-beta model and Howton and Peterson’s (1998) dual-beta model both find that beta is significantly positive (negative) in the Singapore up (down) markets.
I predict the value of ordinary and dual beta in order to get the suitable model. This paper continues to extend the study in examining the dual-beta model in the UK stock market when the market is segmented into up and down markets. Bartholdy and Riding (1994) find that both the Dimson and Scholes and Williams methods previously used on NZ data to correct for beta have no incremental efficiency over the standard OLS estimators. But they study concludes that OLS estimators are most efficient and are closer to those based on synchronous data. Therefore I also look forward to adopt the simple OLS beta estimation to predict the beta to get my conclusion.

KeyWords ：Predict the beta, Dual beta model, Relation with beta and return.

Introduction
The estimation https://www.51lunwen.org/liuxuelunwendx/of CAPM betas is important to many applications in finance. Practitioners rely on beta estimates when calculating required future returns, estimating costs of capital, and determining portfolio strategies. A rational investor should measure the risks of stock market investments. Researchers also rely on beta estimates for applications such as determining relative risk, testing asset pricing models, testing trading strategies, and conducting event studies. [google it and say more]
However, since the future beta is not known, in practice historic beta estimated over some recent period is often used as a proxy for this future beta. . Using recently-estimated betas to apply to some future period presumes that the historical betas are good predictors of the future betas. The forecasting method is time series model by the lag variables, further more, it is considered in the up and down markets to predict the beta value. The beta model is based on the regression on a time trend. The regressors in this forecasting equation are deterministic which make the model attractive for forecasting because the future values of the explanatory.

Reference
Altman, E. I.., Jacquillat, B. and Levasseur, M. 1974. “Comparative Analysis of Risk Measures: France and the United States,” Journal of Finance, 29, 1495-1511.

Alexander, G. J. and N. L. Chervany (1980), `On the Estimation and Stability of Beta', Journal of Financial and Quantitative Analysis, Vol. 15, No. 1 (March), pp. 123±37.

Altman, E, B. Jacquillat and M Levasseur (1974), `Comparative Analysis of Risk Measures: France and the Un本论文由英语论文网提供整理，提供论文代写，英语论文代写，代写论文，代写英语论文，代写留学生论文，代写英文论文，留学生论文代写相关核心关键词搜索。