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Abnormal returns using accounting information within a value portfolio
Published in Emerald Publishing
2017
Volume: 30
   
Issue: 1
Pages: 73 - 88
Abstract

Purpose

This paper investigates whether a simple accounting information-based fundamental analysis strategy could identify winners from losers within a portfolio of high book-to-market (value) stocks, over the last decade in the Indian equity market, where historically, information disclosure and transparency levels have been on the lower side.

Design/methodology/approach

Using a sample of ‘value’ firms, the authors formulate an ‘F-score’ for each firm as the sum of binary signals (favourable and unfavourable), with respect to nine key variables. The authors then form ten equal size F-score portfolios within the value band for each year, and track the performance of robust high F-score firms vis-à-vis that of weaker low F-score firms.

Findings

The study highlights that the historical success of a value strategy, in general, relies on the strong performance of a few firms while ‘tolerating the poor performance of many deteriorating companies’ within the broad value group and shows that firms with strong fundamentals within the value group outperform their less robust counterparts, based on absolute as well as risk adjusted measures.

Practical implications

The results of the study show that strong performers can indeed be distinguished from underperformers within the broad category of value stocks. This can have significant implications for investors at large in the Indian equity market.

Originality/value

The study suggests an approach to identify potential winners within a broad ‘value’ portfolio using an array of accounting information, even in a relatively less transparent Indian equity market. In UMPP program, the Ministry of Power recognized the need to "move away from cost plus approach for tariff determination to further encourage private sector investment." The program had many distinctive advantages as compared to traditional Independent Power Plants using subcritical technology in terms the scale, efficiency, consultative process used for development of the plants. However the UMPP dream have soured in more then one-way ranging with the tariff determination, rising fuel cost, delays, cost escalations, environmental clearances for mining, fuel procurement and so on.

Purpose

This paper investigates whether a simple accounting information-based fundamental analysis strategy could identify winners from losers within a portfolio of high book-to-market (value) stocks, over the last decade in the Indian equity market, where historically, information disclosure and transparency levels have been on the lower side.

Design/methodology/approach

Using a sample of ‘value’ firms, the authors formulate an ‘F-score’ for each firm as the sum of binary signals (favourable and unfavourable), with respect to nine key variables. The authors then form ten equal size F-score portfolios within the value band for each year, and track the performance of robust high F-score firms vis-à-vis that of weaker low F-score firms.

Findings

The study highlights that the historical success of a value strategy, in general, relies on the strong performance of a few firms while ‘tolerating the poor performance of many deteriorating companies’ within the broad value group and shows that firms with strong fundamentals within the value group outperform their less robust counterparts, based on absolute as well as risk adjusted measures.

Practical implications

The results of the study show that strong performers can indeed be distinguished from underperformers within the broad category of value stocks. This can have significant implications for investors at large in the Indian equity market.

Originality/value

The study suggests an approach to identify potential winners within a broad ‘value’ portfolio using an array of accounting information, even in a relatively less transparent Indian equity market.

About the journal
JournalData powered by TypesetAccounting Research Journal
PublisherData powered by TypesetEmerald Publishing
ISSN1030-9616
Open AccessNo