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\title{The Firm Value Effect: Evidence from Egypt}
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\author[1]{Omar Gharaibeh}
\affil[1]{ Al Albayt University}
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\date{\small \em Received: 11 December 2015 Accepted: 3 January 2016 Published: 15 January 2016}
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\begin{abstract}
This paper investigates for a value effect in Egyptian firm returns using three different ways to determine value by sorting firms based on their past long-term returns (long-term contrarian), the book-to-market ratios (BE/ME), and the percentage changes in their BE/ME ratios (change). These three strategies are approaches commonly used to measure for value effect. Using sample period from January 1997 to April 2014, this study provides a strong evidence of an inter-firm value effect with three measures. The long-term return contrarian and BE/ME, produce significant abnormal raw returns of 2.18% and 2.01%, respectively. On the other hand, the percentage changes in their BE/ME provides weakly significant profits of 1.08% per month. This paper also shows that the value profits generated by all three alternative value strategies in Egyptian stock market can be explained by three-factor model.
\end{abstract}
\keywords{value effect, contrarian, three-factor model, egyptian stock market (EGX).}
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\section[{Introduction}]{Introduction}\par
he empirical literature on the value effect has shown that BE/ME ratio can be used to predict future returns (Clifford S Asness, Moskowitz, \& Pedersen, 2013; Chen, 2011; Dempsey, 2010; \hyperref[b8]{Fama \& French, 1993)}. Studies that have examined the value effect have proved the persistence of this effect at the level of company, industry and international index level (Clifford S Asness, et al., 2013; Chen, 2011; Chou, Ho, \& Ko, 2012; \hyperref[b6]{Dempsey, 2010;}\hyperref[b8]{Fama \& French, 1993;}\hyperref[b11]{Gharaibeh, 2016;}\hyperref[b14]{Lakonishok, Shleifer, \& Vishny, 1994)}.\par
Although most previous empirical research studies on monthly value effect employ data either from developed stock markets or emerging stock markets, few from these previous studies have addressed the Arabic stock markets. Egypt is one of the most important Arabic stock markets. Egyptian stock market constitutes an increasing share of the Arabic stock portfolio Therefore, to the best of our knowledge; no such work has yet been done on the Egyptian stock market in any international literature. This paper mainly aims to investigate value effect in an Arabic stock market of developing country, namely Egypt.\par
In addition to the traditional methods used in previous studies to calculate the value effect which are long-term contrarian strategy and BE/ME ratio, this study is the first to suggest using the percentage change in the BM ratio as a third new method for identifying value. The results of this paper are easily summarized in three points. First, the current study shows the very existence of value effect in Egypt stock Author: Al Albayt University. e-mail: omar\textunderscore k\textunderscore gharaibeh@yahoo.com market. Second, among the alternative three value strategies, this paper reveals that long-term contrarian and BE/ME strategies provide the highest monthly average returns. In particular, previous two strategies produce abnormal raw returns of 2.18\% and 2.01\% respectively, while change BE/ME strategy generate only abnormal profits of 1.08\% per month. Lastly, this paper finds that all three alternative value effects used in Egypt stock market can be explained by three factor model.\par
The rest of the current study is organized as follows. Section 2 reviews that literature related to the value effect, while Section 3 describes the data and outlines the portfolio construction for three alternative value strategies. Section 5 provides the main empirical results, and finally Section 6 concludes the chapter.
\section[{II.}]{II.}
\section[{Literature Review}]{Literature Review}\par
Pioneering work by \hyperref[b8]{Fama and French (1993)} which is the three-factor model has attracted the attention of many academic researchers and practitioners, as it found that the CAPM does not provide an adequate explanation of realized returns. Employing \hyperref[b8]{Fama and French's (1993)} procedure to construct risk factors, \hyperref[b18]{Simlai (2009)} re-investigated whether the size and book-to-market factors affect on the performance of portfolio returns. \hyperref[b18]{Simlai (2009)} found that both size and book-to-market ratios have a key role in interpreting the variation in stock returns over the period from July 1926 to June 2007.\par
Lakonishok, Shleifer, and Vishny (1994)(LSV) investigated the relative performance of value strategies and showed that they outperform the market. Their finding supported the result of \hyperref[b7]{Fama and French (1992)} that value strategies provide high returns. However, Whilst \hyperref[b7]{Fama and French (1992)} consider the profitability of value strategies by explaining that these strategies are fundamentally riskier, \hyperref[b14]{Lakonishok et al. (1994)} regard their profitability as being the result of stock mispricing. \hyperref[b6]{Dempsey (2010)} investigate the role of the BE/ME ratio in the formation of stock returns. He investigated whether the BE/ME ratio should take into account "risk-based", not a "mispricing" explanation for share prices in the Australian markets. His work was motivated by the explanation of stock return performance suggested by the Fama and French threefactor model, and applied Peterkort and Nielsen's (2005) approach to explain the relationship between the BM variable and stock return. Dempsey (2010) confirms the previous results that stock returns are strongly related to the firm's book-to-market equity ratio. Furthermore, strong evidence suggests that this relationship stems from the BE/ME ratio's absorption of the conclusion of company leverage as a risk factor. In spite of the distinctive characteristics of the Australian stock market, these previous results are substantially consistent with the U.S. results of \hyperref[b8]{Fama and French (1993)} and \hyperref[b17]{Peterkort and Nielsen (2005)}.\par
Chen (2011) examined the reason why the book-to-market effect increased in small stocks and decreased in large stocks. His analysis found that firms with short life expectations have high idiosyncratic volatility. Chou, Ho, and Ko (2012) claim that the bookto-market effect in the U.S. equity market is mostly an intra-industry phenomenon. In more recent study, Asness, Moskowitz and Pedersen (2013) examine value strategy returns for global stocks, currencies, equity indices, government bonds and commodities. They provide evidence of value effect in each asset class.\par
Hasan, Alam, Amin, \& Rahaman (2015) examine whether the size and value effects can explain the inter-firm returns in Dhaka Stock Exchange (DSE) in Bangladesh. They show strong evidence of size and value effects. Small firms along with high BE/ME firms tend to provide higher average monthly returns than big firms along with low BE/ME firms. Hasan, Alam, Amin, \& Rahaman (2015) also show that cross-section of expected return in DSE can be explained by three-factor model.\par
Using 18 emerging stock markets during the period 1990 -2013, Cakici, Tang, \& Yan (2016) examine the presence of value effect. Egypt market is not addressed in their study; they show that the value effect is existence in 17 emerging markets except Brazil. During the global financial crisis, Cakici, Tang, \& Yan (2016) point out that value premium move increasingly and positively together across-market.\par
Next section describes the dataset and methodology used in this study, and then this study expands upon each of these results in some detail.
\section[{III.}]{III.}
\section[{Data and Methodology a) Data}]{Data and Methodology a) Data}\par
This paper considers monthly stock returns, firm size (ME), and the firm book-to-market ratio (BE/ME) for 104 Egyptian firms of all firms listed in the Egyptian Exchange (EGX) for the period of January 1997 to May 2014. At present, a total 104 firms of different sectors are listed in EGX till May 2014. Monthly stock price data are downloaded from Data Stream. The current study use Egyptian Treasury bill rate (monthly average) as the proxy for risk free rate and collected from Jordan central Bank. MSCI index is used as the proxy for market portfolio and data are collected from Data Stream. Following \hyperref[b7]{Fama and French (1992)}, Egyptian firm's BM ratio for June of year t is the book value of equity for the last fiscal year end in t-1 divided by the market value of equity as of December of t-1. A firm's annual BM ratio for June of year t is the average of the BM ratios of the firms. In the BM monthly portfolio sorts that follow, this annual firm BM ratio is used for the following 12 months. Table {\ref 1} details descriptive statistics over the period January 1997 through May 2014 for the Egyptian firms, demonstrating average monthly returns, standard deviation, Skewness and Kurtosis for each firm. Table {\ref 1} shows big difference in the mean and standard deviation of average returns. The South Valley Cement has the biggest monthly average (over 4\% per month). In contrast, the Maridive \& Oil Services has the lowest average at -104. The Egyptian firms have an average monthly return of 1.34\% and an average standard deviation of 15.63\%.
\section[{b) Portfolio Construction}]{b) Portfolio Construction}\par
This paper applies three alternative measures to determine value for each firm: the long-term return reversal by employing contrarian strategies, the firm's BM ratio, its 60-month past return, and the percentage change in its BE/ME ratio over the last 24, 36, 48 or 60 months. Using percentage change over the last 24, 36, 48, and 60 months allows testing the sensitivity of this new method to measure value to the same formation period. As a result this paper investigates three alternative value strategies: the long-term contrarian strategy, the BE/ME strategy and the change BE/ME strategy. The construction methodology for these strategies is presented in the next sections.\par
The portfolios for the three value strategies are formed as follows. At the beginning of each month t, the 104 firms are sorted based on their past BE/ME ratios (for the value strategy), on their 60-month past returns (for the contrarian strategy), and on the percentage changes in their BE/ME ratios over the past J months for J = 24, 36, 48 or 60months (for the change strategies). The high BE/ME, long-term winner and high change equal-weighted portfolios (denoted HV, LW and HC, respectively) contain the 25\% of firms with the highest values for their respective sorting variables in the same way, the low BE/ME, long-term loser and low change portfolios (LV, LL and LC, respectively) contain the 25\% of firms with the lowest values for their respective sorting variables.\par
The zero cost BE/ME strategy (HV-LV) is based on buying the high BE/ME portfolio and selling the low BE/ME portfolio. The zero cost long-term contrarian strategy (LL-LW) is longs the long-term loser portfolio and shorts the long-term winner portfolio. The zero cost change strategy (HC-LC) is buying the high change portfolio and selling the low change portfolio. Portfolios are held for K-month holding periods, while K = 1, 3, 6, 9 and 12 months.\par
For the long-term contrarian strategy, the current study keeps a 12-month gap between the end of the 60-month formation period and the beginning of the K-month holding period compatible with previous studies such as \hyperref[b9]{Fama and French (1996)}, \hyperref[b10]{Figelman (2007)}, \hyperref[b12]{Grinblatt and Moskowitz (2004)} and \hyperref[b15]{Malin and Bornholt (2013)}. The reason for employing this process is that \hyperref[b9]{Fama and French (1996)} show that omitting the first 12-month after the end of the formation period enhances the performance of long-term contrarian strategy because it avoids any long-term reversals being compensated by the short-term continuation of returns.\par
This process is compatible with DeBondt and Thaler's {\ref (1985)} finding that the first 12-month of the holding period did not earn significant contrarian profits. For all other strategies in this paper, the current study adopts the common practice used in momentum studies of omitting 1-month between the end of the formation period and the beginning of the holding period. Whereas a gap of zero or 1-month makes no significant difference to the outcomes, a small gap makes achievement of trading strategies easier in the real world. In addition it avoids any concerns about microstructure biases.
\section[{Table 1 : Descriptive Statistics}]{Table 1 : Descriptive Statistics}\par
Table {\ref 1} reports the descriptive statistics for 104 firm returns from January 1997 until April 2014, obtained from Datastream. The first column is the name of the firm. This is followed by the average monthly returns, the standard deviation of monthly returns, book-to-market ratios and finally the "Skew" is the skewness, and the "Kurt" is the kurtosis for each firm.
\section[{Global Journal of}]{Global Journal of}
\section[{Results}]{Results}\par
This section analyses the findings of the various value strategies. The section includes a discussion of raw and risk-adjusted results. this section reports the average monthly holding period returns for the long, short and long-short portfolios of the long-term contrarian strategy in Table {\ref 2}, the BE/ME strategy in Table {\ref 3} and the pure change BE/ME strategy in Table {\ref 4} when applied to the sample of 104 Egypt firms. Columns 3 through 7 in each Table list the equalweighted average monthly returns in percentages for the K-month holding periods (K = 1, 3, 6, 9 and 12 months).
\section[{a) Value strategies' results}]{a) Value strategies' results}\par
Except for the J = 24 case over K =1, the longterm contrarian results in Table {\ref 2} show that the strategy profits (LL-LW) are statistically significant over all Kmonth holding periods if J =24, 36, 48, or 60 months. Table {\ref 2} demonstrates significant long-term contrarian LL-LW profits. For example, for the 60-month (five-year) formation period case with a 6-month holding period (K = 6) case, the difference between the average monthly returns of the LL portfolio and the LW portfolio is large 2.18\% per month and it is statistically significant (t-stat 2.84). In summary, there are large and significant longterm contrarian profits generated for long formation periods of 24, 36, 48 and 60 months.
\section[{Table 2 : Profitability of Long-Term Contrarian at Egypt Firms}]{Table 2 : Profitability of Long-Term Contrarian at Egypt Firms}\par
Table {\ref 2} provides the average monthly holding period returns in percentages of the selling, buying, and selling minus buying portfolios of the long-term reversal strategy for 104 Egypt firms. Portfolios are constructed as follows: At the beginning of each month t, the 104 firms are sorted derived from their past J-month formation period returns for J = 24, 36, 48, and 60 months. The long-run loser equal-weighted portfolio (LL) comprises of the 25 \% of portfolios with the lowest returns, and the long-term winner equal weighted portfolio (LW) comprises of the 25 \% of portfolios with the largest returns. The strategy LL-LW buying the long-run loser portfolio and sells the long-run winner portfolio to be held for K = 1, 3, 6, 9, or 12 months. The t-statistics depends on the \hyperref[b16]{Newey and West (1987)} The BE/ME strategy results in Table {\ref 3} show clearly that the strategy profits (HV-LV) are statistically significant over all K-month holding. For example, for the 6-month holding period (K=6) case, the difference
\section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research}\par
Volume XVI Issue VII Version I Year ( ) between the average monthly returns of the HV portfolio and the LV portfolio is large 2.01\% per month (t-stat 4.35), which is statistically significant. In general, the holding period returns in Table {\ref 3} give strong evidence of BE/ME effect at the Egypt firm level.\par
Table {\ref 4} shows that the pure change strategy produces statistical significant and sometimes weakly significant profits for all K holding periods when the percentage change in the BM ratio is measured over 24, 36, 48 or 60 months. For example, when the percentage change in the BM ratio is calculated over the past 60 months, the high change portfolio (HC) provides an average return of 2.36\% per month while the low change portfolio (LC) produces an average return of only 1.29\% per month with a six-month holding period. The difference of 1.08\% per month between HC and LC is weakly significant (t-stat 1.65), and is economically large. On the other hand, measuring the percentage change in BE/ME ratios over 24, 36 or 48 months generates statistical significant profits and consistent results, with only the six-month holding period providing statistical significant profits (1.62\%, 1.16\% and 1.23\%) per month (t-stat 2.89, 2.02 and 1.97), respectively.\par
Table {\ref 3} : Profitability of BE/ME at Egypt Firms Table {\ref 3} provides the average monthly holding period returns in percentages of the buying, selling, and buyingselling portfolios for the BE/ME strategy applies to 104 Egypt firms. At the beginning of each month t from November 1994 to April 2014, the 104 firms are ranked based on their BE/ME, and are assigned to one of four portfolios. The high BE/ME equal-weighted portfolios (HV) comprises of the 25\% of firms with the highest values, while the low BE/ME comprises of the 25\% of firms with the lowest values. HV-LV refers to the buying the fourth portfolio and selling first portfolio. All reported returns are equally weighted. The strategy LL-LW longs the long-term loser portfolio and shorts the long-term winner portfolio to be held for K = 1, 3, 6, 9, or 12 months. The t-statistics are based on the \hyperref[b16]{Newey and West (1987)} In short, the results in Table {\ref 2}, 3 and 4 suggest that the three alternative measures of value provide high levels of profitability. In Table {\ref 1 and 2}, strategy profits for the long-term contrarian and BE/ME strategies are significant and very similar for all holding periods. For example, the long-term contrarian strategy earns a significant 2.18\% per month (t-stat 2.84) and the BE/ME strategy earns 2.01\% per month (t-stat 4.35) with sixmonth holding periods (K=6). For change BE/ME strategy, although Table {\ref 4} shows that the change value strategy provides weakly significant for the same period, it is still economically large. The change value generates monthly returns 1.08\% per month (t-stat 1.65).\par
The post-formation behaviors of the value strategies' profits are also illustrated in Figure \hyperref[fig_0]{1}. Figure \hyperref[fig_0]{1} depicts the post-formation cumulative returns of the long-term contrarian strategy (LL-LW) with J = 60, the BE/ME strategy (HV-LV), and the change BE/ME strategy (HC-LC) with J = 60 for the 60 months following the end of the formation period.
\section[{Table 4 : Profitability of Change BE/ME at Egypt Firms}]{Table 4 : Profitability of Change BE/ME at Egypt Firms}\par
This table reports the average monthly holding period returns in percentages of the long, short, and long-short portfolios for change strategy applied to 104 Firms. Portfolios are constructed as follows: At the beginning of each month t, the 104 industries are ranked based on their percentage changes in their BM ratios over the past J months for J =24, 36, 48 and 132 months. The high change portfolios HC contains the 25\% of firms with the largest change values, while the low change BM portfolio LC contains the 25\% of firms with the lowest change values. Given the Figure \hyperref[fig_0]{1}, while the value strategies graph suggests a slowing in the cumulative returns towards the end of the 60 months we note that all alternative three value strategies generate positive cumulative returns. Long-term contrarian strategy provides the highest cumulative returns, then comes the BE/ME strategy. The change BE/ME strategy comes in the last strategy among alternative value strategies. This graph presents the cumulative returns of the long-term return reversal portfolio LL-LW (with J = 60 months), BE/ME strategy HV-LV and change BE/ME (with J = 60 months) using non-overlapping portfolio (K = 1) for the 60 months after the end of the formation period.
\section[{b) Risk adjustments}]{b) Risk adjustments}\par
To find whether the profits of these strategies could be considered a reward for bearing risk, the profits of the long-term contrarian, BE/ME and change value strategies are risk-adjusted employing the Fama-French three-factor model. The three-factor regression model comprises of the market factor, a small minus big factor, and a value minus growth factor: \par
Where Table {\ref 5} reports the estimated regression coefficients of the three-factor model and the corresponding White-corrected t-statistics for the long, short and long-short portfolios for the long-term contrarian (J = 60), the BE/ME and the change value (J = 60) strategies with six-month holding periods (K = 6) in Panels A, B and C, respectively. Column 2 of Table {\ref 5} reports the monthly alphas of the three-factor model, while the last column lists the adjusted R 2 .\par
The alpha of the long-term contrarian long-short LL -LW portfolio in Panel A, B and C is small (0.013\%, -0.09 and -0.04 per month) and insignificant (t-stat 0.29, -1.30 and -0.76), respectively.\par
In summary, the three alternative value results in Panels A, B and C of Table {\ref 5} reveal that there is value return in Egyptian firm returns that can be explained by the Fama-French three-factor model.. The insignificant long-term contrarian strategy's alpha is consistent with Fama and French's (1996) finding that the three-factor model can explain the reversal of long-term returns of individual U.S. stocks reported by \hyperref[b5]{DeBondt and Thaler (1985)}.
\section[{Table 5 : Risk-Adjusted inter-firm value Profits}]{Table 5 : Risk-Adjusted inter-firm value Profits}\par
This table presents the three-factor regression results for the contrarian, BE/ME and change BE/ME portfolios in Panel A, B and C respectively. These portfolios are described in Tables {\ref 2 and 3}. The three-factor regression model is as follows: R pt -R ft = ? p + ? p (R m -R ft ) + sp SMB t + hp HML t + ? pt where R pt -R ft is the portfolio's excess return, R mt -R ft is the excess return on the market, and SMB t and HML t are the size and book-to-market factors. The t-statistics presented in parentheses are corrected for heteroskedasticity using \hyperref[b19]{White's (1980)} V.
\section[{Conclusion}]{Conclusion}\par
Arabic stock markets are clearly a significant part of the world portfolio today and therefore are important to the average investor. Finance literature has discovered important facts about value effect in US, as well as in the developed equity markets. Value effect is a lot less explored for emerging markets, especially Arabic market.\par
The result of this study provides strong evidence of value effect by using three alternative value strategies: longterm contrarian, BE/ME and change BE/ME strategies. More specific, the long-term contrarian and BE/ME value strategies provide abnormal returns more than 2\% per month, while the change BE/ME value strategy generate abnormal returns more than 1\% per month. Second, this paper constructs 4 portfolios based on each value strategy for Egypt stock market, and uses these portfolios as the returns in the three-factor model. This paper also finds that the size and value premium in addition to market risk premium have very strong power to explain cross-section of expected return in the Egyptian Exchange.\par
The participants of the stock market, e.g. investors and fund managers may be utilized using previous findings. The investors from developing countries like Egypt can achieve abnormal returns by using three alternative value measures. In addition, practitioners manage their portfolios and assess their assets more accurately through applying three-factor model. For future research, it would be attractive to examine whether volatility effect can shed some light on the Egypt value returns. None of the previous studies investigate the relationship between value returns with volatility effect in Egypt stock market.\begin{figure}[htbp]
\noindent\textbf{1}\includegraphics[]{image-2.png}
\caption{\label{fig_0}Figure 1 :}\end{figure}
\begin{figure}[htbp]
\noindent\textbf{} \par
\begin{longtable}{P{0.011119186046511628\textwidth}P{0.05559593023255814\textwidth}P{0.1519622093023256\textwidth}P{0.1507267441860465\textwidth}P{0.17914244186046513\textwidth}P{0.1519622093023256\textwidth}P{0.14949127906976745\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep Holding Period Returns\tabcellsep \tabcellsep \\
J\tabcellsep Portfolio\tabcellsep K=1\tabcellsep K=3\tabcellsep K=6\tabcellsep K=9\tabcellsep K=12\\
24\tabcellsep LW\tabcellsep 0.88\tabcellsep 0.89\tabcellsep 0.87\tabcellsep 0.82\tabcellsep 0.91\\
\tabcellsep \tabcellsep (1.58)\tabcellsep (1.62)\tabcellsep (1.55)\tabcellsep (1.45)\tabcellsep (1.59)\\
\tabcellsep LL\tabcellsep 2.06\tabcellsep 2.10\tabcellsep 2.06\tabcellsep 2.61\tabcellsep 2.57\\
\tabcellsep \tabcellsep (2.74)\tabcellsep (2.78)\tabcellsep (2.73)\tabcellsep (3.94)\tabcellsep (3.84)\\
\tabcellsep LL-LW\tabcellsep 1.18\tabcellsep 1.21\tabcellsep 1.19\tabcellsep 1.79\tabcellsep 1.66\\
\tabcellsep \tabcellsep (1.94)\tabcellsep (2.01)\tabcellsep (2.05)\tabcellsep (3.98)\tabcellsep (3.76)\\
36\tabcellsep LW\tabcellsep 1.07\tabcellsep 1.08\tabcellsep 1.03\tabcellsep 1.02\tabcellsep 1.06\\
\tabcellsep \tabcellsep (1.86)\tabcellsep (1.88)\tabcellsep (1.75)\tabcellsep (1.72)\tabcellsep (1.76)\\
\tabcellsep LL\tabcellsep 2.77\tabcellsep 2.48\tabcellsep 2.41\tabcellsep 2.43\tabcellsep 2.39\\
\tabcellsep \tabcellsep (3.93)\tabcellsep (3.6)\tabcellsep (3.52)\tabcellsep (3.52)\tabcellsep (3.43)\\
\tabcellsep LL-LW\tabcellsep 1.70\tabcellsep 1.39\tabcellsep 1.39\tabcellsep 1.40\tabcellsep 1.33\\
\tabcellsep \tabcellsep (3.17)\tabcellsep (2.79)\tabcellsep (2.88)\tabcellsep (2.97)\tabcellsep (2.87)\\
48\tabcellsep LW\tabcellsep 1.23\tabcellsep 1.33\tabcellsep 1.28\tabcellsep 1.23\tabcellsep 1.16\\
\tabcellsep \tabcellsep (1.89)\tabcellsep (2.04)\tabcellsep (1.96)\tabcellsep (1.88)\tabcellsep (1.72)\\
\tabcellsep LL\tabcellsep 2.56\tabcellsep 2.66\tabcellsep 2.58\tabcellsep 2.72\tabcellsep 2.79\\
\tabcellsep \tabcellsep (3.42)\tabcellsep (3.49)\tabcellsep (3.37)\tabcellsep (3.49)\tabcellsep (3.46)\\
\tabcellsep LL-LW\tabcellsep 1.33\tabcellsep 1.33\tabcellsep 1.30\tabcellsep 1.49\tabcellsep 1.63\\
\tabcellsep \tabcellsep (2.44)\tabcellsep (2.47)\tabcellsep (2.49)\tabcellsep (2.85)\tabcellsep (3)\\
60\tabcellsep LW\tabcellsep 0.52\tabcellsep 0.67\tabcellsep 0.68\tabcellsep 0.66\tabcellsep 0.72\\
\tabcellsep \tabcellsep (0.56)\tabcellsep (0.72)\tabcellsep (0.72)\tabcellsep (0.69)\tabcellsep (0.73)\\
\tabcellsep LL\tabcellsep 2.82\tabcellsep 2.99\tabcellsep 2.86\tabcellsep 2.86\tabcellsep 2.86\\
\tabcellsep \tabcellsep (3.15)\tabcellsep (3.37)\tabcellsep (3.32)\tabcellsep (3.25)\tabcellsep (3.22)\\
\tabcellsep LL-LW\tabcellsep 2.31\tabcellsep 2.31\tabcellsep 2.18\tabcellsep 2.19\tabcellsep 2.14\\
\tabcellsep \tabcellsep (2.78)\tabcellsep (2.85)\tabcellsep (2.84)\tabcellsep (2.83)\tabcellsep (2.56)\end{longtable} \par
\caption{\label{tab_1}}\end{figure}
\begin{figure}[htbp]
\noindent\textbf{} \par
\begin{longtable}{P{0.12466666666666666\textwidth}P{0.14733333333333334\textwidth}P{0.07933333333333334\textwidth}P{0.32866666666666666\textwidth}P{0.07933333333333334\textwidth}P{0.09066666666666667\textwidth}}
\tabcellsep \tabcellsep \tabcellsep Holding Period Returns\tabcellsep \tabcellsep \\
Portfolio\tabcellsep K=1\tabcellsep K=3\tabcellsep K=6\tabcellsep K=9\tabcellsep K=12\\
HV\tabcellsep 2.42\tabcellsep 2.45\tabcellsep 2.25\tabcellsep 2.26\tabcellsep 2.52\\
\tabcellsep (3.48)\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
\caption{\label{tab_2}}\end{figure}
\begin{figure}[htbp]
\noindent\textbf{} \par
\begin{longtable}{P{0.6392332789559544\textwidth}P{0.07071778140293639\textwidth}P{0.059624796084828714\textwidth}P{0.0013866231647634583\textwidth}P{0.0013866231647634583\textwidth}P{0.0013866231647634583\textwidth}P{0.009706362153344208\textwidth}P{0.012479608482871126\textwidth}P{0.009706362153344208\textwidth}P{0.019412724306688417\textwidth}P{0.024959216965742253\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep R pt ?\tabcellsep ft R\\
\multicolumn{9}{l}{is the monthly excess return of the strategy portfolio p,}\\
R mt ?\tabcellsep ft R\tabcellsep \multicolumn{7}{l}{is the Egyptian MSCI index's monthly excess}\\
\multicolumn{7}{l}{market return for month t, while}\tabcellsep \multicolumn{2}{l}{t SMB and}\tabcellsep t HML are\\
\multicolumn{9}{l}{the monthly size and book-to-market factors at time t,}\\
\multicolumn{3}{l}{respectively.}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \multicolumn{8}{l}{The monthly return values for the three factors}\\
\multicolumn{9}{l}{and one-month T-Bill risk-free rate covering the full}\\
\multicolumn{9}{l}{sample period from January 1997 to May 2014 are}\\
\multicolumn{9}{l}{downloaded from Data stream. The three-factor model}\\
\multicolumn{9}{l}{covers the period from the period January 1997 to May}\\
\multicolumn{3}{l}{2014. The coefficients}\tabcellsep ?\tabcellsep p\tabcellsep ,\tabcellsep \multicolumn{2}{l}{p s and}\tabcellsep h\tabcellsep p\tabcellsep are the regression\\
\multicolumn{9}{l}{loadings corresponding to the factors of the models,}\\
\multicolumn{3}{l}{while the intercept p}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
{\small\itshape [Note: pt R ?]}
\caption{\label{tab_5}}\end{figure}
\begin{figure}[htbp]
\noindent\textbf{} \par
\begin{longtable}{P{0.1654867256637168\textwidth}P{0.13915929203539823\textwidth}P{0.19557522123893806\textwidth}P{0.15044247787610618\textwidth}P{0.12035398230088495\textwidth}P{0.07898230088495575\textwidth}}
\tabcellsep \tabcellsep Three-Factor Model\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep ?\tabcellsep ?\tabcellsep s\tabcellsep h\tabcellsep Adj R2\\
Panel A:\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
contrarian\tabcellsep 0.013\tabcellsep 0.041\tabcellsep -0.380\tabcellsep -0.093\tabcellsep 28\%\\
\tabcellsep (0.29)\tabcellsep (0.08)\tabcellsep (-5.39)\tabcellsep (-0.86)\tabcellsep \\
Panel B:\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
BEME\tabcellsep -0.090\tabcellsep 0.011\tabcellsep -0.017\tabcellsep 1\tabcellsep 100\%\\
\tabcellsep (-1.3)\tabcellsep (1.36)\tabcellsep (-5.99)\tabcellsep (4.12)\tabcellsep \\
Panel C:\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
CHBEME\tabcellsep -0.040\tabcellsep 0.452\tabcellsep -0.205\tabcellsep 0.632\tabcellsep 12.8\%\\
\tabcellsep (-0.76)\tabcellsep (0.77)\tabcellsep (-2.34)\tabcellsep (4.77)\tabcellsep \end{longtable} \par
\caption{\label{tab_6}}\end{figure}
\begin{figure}[htbp]
\noindent\textbf{} \par
\begin{longtable}{P{0.018478260869565215\textwidth}P{0.03695652173913043\textwidth}P{0.018478260869565215\textwidth}P{0.07391304347826086\textwidth}P{0.018478260869565215\textwidth}P{0.018478260869565215\textwidth}P{0.018478260869565215\textwidth}P{0.018478260869565215\textwidth}P{0.018478260869565215\textwidth}P{0.018478260869565215\textwidth}P{0.018478260869565215\textwidth}P{0.07391304347826086\textwidth}P{0.018478260869565215\textwidth}P{0.07391304347826086\textwidth}P{0.018478260869565215\textwidth}P{0.018478260869565215\textwidth}P{0.018478260869565215\textwidth}P{0.018478260869565215\textwidth}P{0.09239130434782608\textwidth}P{0.018478260869565215\textwidth}P{0.018478260869565215\textwidth}P{0.018478260869565215\textwidth}P{0.09239130434782608\textwidth}P{0.018478260869565215\textwidth}P{0.018478260869565215\textwidth}P{0.03695652173913043\textwidth}P{0.018478260869565215\textwidth}}
R\tabcellsep pt\tabcellsep ?\tabcellsep ft R\tabcellsep =\tabcellsep ?\tabcellsep p\tabcellsep +\tabcellsep ?\tabcellsep p\tabcellsep (\tabcellsep mt R\tabcellsep ?\tabcellsep ft R\tabcellsep )\tabcellsep +\tabcellsep s\tabcellsep p\tabcellsep t SMB\tabcellsep +\tabcellsep h\tabcellsep p\tabcellsep t HML\tabcellsep +\tabcellsep ?\tabcellsep pt\tabcellsep ,\end{longtable} \par
\caption{\label{tab_7}}\end{figure}
\footnote{©20 16 Global Journals Inc. (US)} \footnote{The Firm Value Effect: Evidence from Egypt} \footnote{© 2016 Global Journals Inc. (US) 1} \backmatter \begin{bibitemlist}{1}
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