ADDING VALUE TO VALUE STOCKS JOSEPH PIOTROSKI’S F-SCORE 5.pdf · ADDING VALUE TO VALUE STOCKS JOSEPH…

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  • 155

    CHAPTER 5

    ADDING VALUE TO VALUE STOCKS

    JOSEPH PIOTROSKIS F-SCORE MODEL

    5.1 INTRODUCTION

    The value investing consists of buying securities which are trading at prices

    lesser than their intrinsic value. The intrinsic value of the securities is determined

    through their fundamentals. The company showing good performance in terms of

    earnings, dividends, book value of assets, profitability etc. is said to be an

    intrinsically strong company. Thus, value investment strategies are based on

    fundamental analysis of a company. Firms fundamental or intrinsic value is

    determined by the information reflected in the financial statements. Stock prices

    deviate at times from these values but slowly converge to these fundamental values

    thereby enhancing the market value of such firms (Elleuch and Trabelsi, 2009). The

    basic premise behind value investing strategies is that the sophisticated investors can

    use historical financial information to select profitable investment opportunities.

    Specifically, investors can earn returns in excess of the returns required for risk

    compensation by identifying undervalued or overvalued securities through an analysis

    of historical financial data (Piotroski, 2005).

    Within the varied value investing strategies, the investors look for the strategy

    that consistently identifies winners and the losers in the market with minimum risk

    and earn returns superior to those averaged by the market index. In actual effect, the

    existence of such a strategy would challenge the efficient market hypothesis, one of

    the main pillars of financial market theory (Dahl et al., 2009). The efficient market

    hypothesis states that the current stock price fully reflect available information about

    the value of the firm, and there is no way to earn excess profits (more than the market

    overall) by using any publically available or private information (Clarke et al., 2001).

    Thus, no trading rule or security selection strategy which uses only publically

    available information would provide an investor with the ability to earn, on average,

    positive abnormal returns in the market that is efficient in the semi strong sense. The

    Indian stock market, a strong emerging market, offers a unique opportunity to apply

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    and test the profitability of accounting based fundamental analysis (Aggarwal and

    Gupta, 2009). In addition, the Indian stock market has become comparable to other

    mature markets due to various financial sector reforms initiated since early 1990s by

    the Government of India. The positive fundamentals combined with fast growing

    markets have made India an attractive destination for foreign institutional investors.

    Significant amounts of capital are flowing from developed world to emerging

    economy like India (Prassana, 2008). In such a situation, the profitability of an

    accounting based fundamental analysis strategy aimed at yielding excess returns in

    Indian stock market becomes imperative to explore.

    Out of different financial variables aimed at assessing the intrinsic value of

    securities, the book to market ratio has been considered as the most important and the

    keystone of value investing studies. According to this valuation metric, the securities

    that have higher book value in comparison to the market price, are called as

    intrinsically strong or value securities. The book to market ratio of the companies is

    calculated as:

    Book to market ratio= Book value of a share for last financial year end/

    Current market price of a share.

    Book value per share is an accounting concept that measures what

    shareholders would receive if all the firms liabilities were paid off and all its assets

    could be sold at their balance sheet value (Strong, 2004). The different studies, such

    as, Stattman (1980), Rosenberg et al. (1985), Chan et al. (1991), Fama and French

    (1992, 1998), Capaul et. al. (1993), Brouwer et al. (1996), Vos and Pepper (1997),

    Vaidyanathan and Chava (1997), Mukherji et al. (1997), Bauman et al. (1998),

    Arshanapalli et al. (1998), Dhatt et al. (1999), Doukas et al. (2001), Dimson et al.

    (2003), Bird and Gerlach (2003), Ding et al. (2005) and Azzopardi (2006) have

    studied the role of this ratio in providing value premium to investors.

    The book to market ratio is one of the most extensively studied variables in the

    finance literature. The reason behind the existence of value premium in high book to

    market stocks has attracted multiple explanations. The explanation on the existence of

    value premium has been explained first of all by Fama and French (1992) stating that

    market judges the prospects of a high ratio of book to market equity firms to be poor

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    in relation to the firms with low book to market equity. Further, Lakonishok et al.

    (1994) offered the mispricing explanation behind existence of value effect and hence

    provided evidence that value strategies yield higher returns because these strategies

    exploit the suboptimal behavior of the typical investor and not because these

    strategies are fundamentally riskier. Further, Vassalou and Xing (2004) conjectured

    that the value stocks based on high book to market ratio have higher default risk than

    the stocks having low book to market ratio. Also, Campbell et al. (2008) found that

    the investors make valuation errors and overprice these stocks as they fail to

    understand their poor prospects.

    However, when examining the potential of book to market ratio in generating

    excess returns to investors, Piotroski (2000) studied that no doubt the stocks selected

    on the basis of high book to market ratio yield value premium to investors but about

    44% of the high book to market firms did not show any increment in their value in 2

    years of portfolio formation. Thus, a handsome group of stocks have not shown any

    increment in value. He further held that value stocks earn returns because of being

    abandoned in the market. As a result, they are lesser suggested by analysts and thus

    less followed by investment community. Also, being financially distressed, one

    should focus on the accounting fundamentals of such stocks, such as, leverage,

    liquidity, profitability trends, cash flow adequacy etc. before taking investment

    decision in such firms. Thus, in order to avoid the distress risk associated with the

    high book to market stocks and to extract true value maximizing securities, Joseph

    Piotroski conceptualized and empirically proved the viability of the financial

    statement information in yielding true value securities.

    5.2 JOSEPH PIOTROSKIS F-SCORE

    In order to ensure the financial soundness and profitability of financially

    distressed high book to market firms, Joseph Piotroski developed a comprehensive

    financial signal known as F-score that measures three constructs pertinent to a

    companys financial position: profitability, financial leverage along with liquidity,

    and operating effectiveness. The three constructs of Pitoroskis summary measure F -

    score, is the sum of nine binary signals related to these three constructs (Wellman,

    2011). The nine signals aim at measuring the strength and quality of historical

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    performance trends are derived from the traditional financial statement analysis

    (Piotroski, 2000; Fama and French, 2004). The F-score measure intends to spot out

    the firms with the strongest enhancement in overall financial condition during the last

    fiscal year while meeting a minimum standard of financial performance (Piotroski,

    2005). Thus, the model based on set of financial variables aims to identify companies

    that would actually increase in value out of total group of value stocks. The model is

    called as F-score, whereby the 9 financial signals corresponding to the 3 constructs

    i.e. profitability; leverage along with liquidity and the operating efficiency are used to

    measure the financial performance of high book to market firms. The set of 9 binary

    signals are used, where an indicator variable for the signal is equal to one (1) if the

    signals realization is good and zero (0) if the signals realization is bad (Piotroski,

    2000). Every year, firms are rated and classified on the basis of these recent signals.

    Strong firms exhibit diverse improvements along a range of financial dimensions,

    while weak firms have weakening (and generally poor) fundamentals along these

    same dimensions (Piotroski, 2005). The score on each of the nine items are summed

    to give the F score for the stock, ranging between zero and nine. The items together

    with their desired properties are: (i) positive profitability, (ii) increase in profitability,

    (iii) positive cash flow, (iv) negative accruals, (v) increase in profit margin, (vi)

    increase in asset turnover, (vii) decrease in leverage, (viii) increase in financial

    liquidity, and (ix) no issuance of new equity (Hyde, 2013). F-score, therefore, is the

    sum of the nine binary signals and measures the financial stability, profitability and

    the efficiency of the business.

    The logical phenomenon