Predicting Market Betas

T. Saji
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引用次数: 2

Abstract

This research, using firm-level data on NSE listed stocks for the period of 2008–2015, seeks empirical evidence on the significance of company characteristics in prediction of market betas in Indian context. The empirical methodology involves two-stage statistical procedure where an exploratory factor framework determines the historical relationship between firms’ fundamentals and systematic risk at first, and a generalized least square (GLS) technique of panel regression modelling estimates their predictive power thereafter. The search process discovers debt ratios and returns on investment predict market betas in Indian stock market. The study strongly suggests that the use of 1-year lagged historical betas along with the measures of financial leverage and overall profitability produces better predictions than the benchmark predictions solely based on historical betas. However, the analysts need to consider the industry differences in systematic risk to enhance the predictive power of the model.
预测市场beta值
本研究使用2008-2015年期间NSE上市股票的公司层面数据,寻求印度背景下公司特征在预测市场贝塔系数中的意义的经验证据。实证方法涉及两阶段统计程序,其中探索性因素框架首先确定公司基本面与系统风险之间的历史关系,然后使用面板回归模型的广义最小二乘(GLS)技术估计其预测能力。搜索过程发现负债率和投资回报率预测市场贝塔在印度股市。该研究强烈表明,使用1年滞后的历史贝塔系数以及财务杠杆和整体盈利能力的措施,比仅基于历史贝塔系数的基准预测产生更好的预测。然而,分析人员需要考虑系统风险的行业差异,以提高模型的预测能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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