A Note On Persistence In Indian IT Equities

Sanjay Rajagopal
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Abstract

The objective of the present study is to test for pricing efficiency in equities of individual information technology companies in the emerging Indian market, where the sector holds an important place in the domestic economy and is a significant contributor to the country’s exports. The fifty-six companies currently comprising the BSE IT index are studied for the possible presence of persistence in returns. Employing all continuously available price data for these firms, the Hurst exponent is estimated using three fractal analysis techniques, viz., rescaled-range, roughness-length, and wavelets. Persistence or “long memory” is unambiguously detected in eleven, or roughly 20% of the return series; antipersistence is detected in the case of two series. The results suggest that not all Indian information technology securities are priced efficiently, and that there exists the potential for investors to exploit a long memory characteristic in those stocks to extract excess profits from trading rules based on historical price information.
关于印度 IT 股票持续性的说明
本研究的目的是检验新兴印度市场中单个信息技术公司股票的定价效率,该行业在印度国内经济中占有重要地位,并对印度的出口做出了重大贡献。我们对目前构成 BSE 信息技术指数的 56 家公司进行了研究,以发现回报中可能存在的持续性。利用这些公司的所有连续可用的价格数据,使用三种分形分析技术(即重定标范围、粗糙度长度和小波)估算赫斯特指数。在 11 个(约 20%)回报序列中明确检测到了持续性或 "长记忆";在两个序列中检测到了反持续性。研究结果表明,并非所有印度信息技术证券的定价都是有效的,投资者有可能利用这些股票的长记忆特征,从基于历史价格信息的交易规则中获取超额利润。
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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