The pursuit of abnormal profits is the dream of every investor. Shareholders of firms are keen about business profitability enhancement reflected by enhanced stock prices (Warrad & Box, 2015). Prior research on Pakistani capital market has found it to be inefficient which means as emerging market information takes time to be processed(Haroon, 2012; Suleman, Hamid, Shah, Akkash, & Shahid, 2010). Hence an investor can exploit excess returns in Pakistani capital markets by using financial performance information.

Therefore, a variety of surrogates has been employed so far to realize this dream. Most prominent surrogates (predictors) of excess returns realization are financial performance measures bifurcated as conventional bookkeeping metrics besides value measures respectively. Researchers have two schools of thoughts; one who advocate supremacy of EVA as an economic output evaluator towards explaining stock returns (Bao & Bao, 1998; Kumar & Sharma, 2011; Stern, Stewart, & Chew, 1995) while others prefer traditional accounting-based performance measures (Chen & Dodd, 1997; Kumar & Sharma, 2011).Moreover, each firm possesses heterogeneity and idiosyncrasy, and thus firm-specific factors akin to size, liquidity, and leverage need to be inculcated for a robust financial performance analysis unfortunately ignored in prior research studies in this context. Therefore, this study incarcerates them. Further stock prices reflect all available information in efficient capital markets so testing market efficiency is helpful in investment decisions.

The following section gives an excerpt of prior research literature relevant to the variables of this study.

Previous researches reflect little efficacy of EVA with reference to income-based output metric in elucidating stock returns. The major reason for this could be the idiosyncratic factors of a particular firm. Ismail (2006) studied 2252 firm-year data of UK and used pooled analysis for investigating the comparative and differential explanatory capacity of conventional and value-based metrics in elucidating share prices. The results showed that NOPAT and earnings after taxes are superior to EVA. Altaf (2016) examined the claim of Stern Stewart & Company about the dominance of EVA^® above orthodox bookkeeping based performance metrics in predicting stock returns. This research study chose 325 Indian companies from manufacturing and services sector and after employing univariate and multivariate regression analyses empirical evidence substantiates operating profit's dominance over EVA in terms of relationship with share returns.

In a study, 59 companies out of KSE 100 Index were empirically examined for a sample period 2006-2010 to reveal that EVA is significant financial metric to explain stock returns and it is significant at a level less than 10%. (Siddique & Sarwar, 2014). Kumar & Sharma (2011) analyzed 873 non-financial Indian firms to examine preeminence of EVA as a business output gauge in comparison to conventional accounting-based performance measures by using panel OLS to examine differential and individual predictive capacity for market value-added.

Firm Size, Liquidity, and Leverage

An important but ignored factor of a business is the firm size (Li & Zhu, 2015). Since EVA doesn't take into consideration size differences (Hansen & Mowen., 1997). Starting from Banz (1981) reported 0.4% excess market-adjusted returns for smaller US stocks. Another study on 556 US firms equity returns during 1963-1977 testified excess returns of 1.77% on small size firms over their larger counterparts (Reinganum, 1981). Investor recognition hypothesis posits higher returns for small stocks because of investors ignorance and lack of information (Merton, 1987). Later on, the 3-factor model presented by Fama & French (1995) incorporated the firm size effect as a formal component of the asset pricing model cementing the claims of prior researchers.

Leverage means magnification of returns by use of constant charge. Hence the linkage of financial performance and leverage is undeniable. Modigliani & Miller (1958) flagged direction for contemporary capital structure theory punch line of these propositions were the value of the company and total cost of capital behavior under three cases ranging from the irrelevance of debt-equity mix, 100% debt to the ideal blend of debt and equity which maximizes corporate worth and curtail the required rate of return.

Trade-off Theory suggests firms should equilibrium the tax shield with the costs associated with insolvency (Kraus & Litzenberger, 1973). Agency cost Theory of free cash flow proposed by Jensen (1986) favors leverage. Once ample surplus cash is at the discretion of management it gives rise to shirking, conflict of goal congruence and tempts management to prioritize self-interest and perks rather than shareholder wealth maximization. The remedy of this agency problem is debt financing which shares the monitoring costs in the shape of debt indentures and debt covenants.

Signaling Theory Information Asymmetry Theory favors leverage contrary to the Modigliani and Miller assumption of symmetric information which is unrealistic here the difference of information among the insiders and outsiders is recognized. Pecking order theory posits firms choose unappropriated income then obligation and offer ordinary shares as the last option(Myers & Majluf, 1984).

In this study, liquidity refers to operating liquidity which is the lifeblood of any organization. Liquidity is defined as nearness to cash. Operating liquidity is the core area of working capital hence also quoted as working capital management policy in finance literature. Operating liquidity major components include the amount of cash and equivalents, receivables and inventories reflected in financial statements. Influential theories like exchange Kraus & Litzenberger (1973) and pecking order theory by Myers & Majluf (1984) have interesting connotations for researchers as trade-off theory advocates inverse association of liquidity and profitability while pecking order theory purports direct relation of liquidity and returns.

On the basis of the literature discussed, the following hypotheses are synthesized.

H1: The comparative explanatory capacity of EVA is loftier to conventional accounting metrics(ROA, ROE, EBIT, EPS, CFO and NI) as well as firm-specific factors (SIZE, LEV and LIQUIDITY) in elucidating price of the share.

H2: Differentithe al explanatory capacity of EVA is advanced compared to traditional accounting measures (ROA, ROE, EBIT, EPS, CFO, and NI) as well as firm-specific factors (SIZE, LEV and LIQUIDITY) in elucidating stock prices.

H3: EVA has a significant positive association with share prices.

H4: Firm Size has a significant negative association with share prices.

H5: Liquidity has a significant positive association with share prices.

H6: Leverage has a significant negative association with share prices.

H7: Traditional accounting measures have a significant positive association with share prices.

H8: No significant mean excess returns and growing mean excess gains are realized considering earnings announcements/EVA as a financial event

The research sample is ought to be a reflection of population ie PSX listed firms. Only non-financial firms were chosen from a total of 561 listed firms. Moreover, PSX consists of firms from 35 different sectors both financial and non-financial which accommodates all industries of the Pakistani economy. For this research precise removal of listed firms was done to arrive at the research sample. As mentioned above the deletion corresponded with the exclusion of financial sector firms because of their different financial reporting and capital structure. The research population included 7 closed-end mutual funds, 20 commercial banks, 28 investment companies, 10 leasing companies, 31 modarba companies and 23 miscellaneous totaling 109 financial companies leaving 452 non-financial firms behind. Out of 452 non-financial firms, 39 had financial year ended 30^th September, 4 firms had year ended 1 firm had November 30^th, 31^st March and 48 on 31^st December. Since the research delimits selection of only those companies having financial year ended on June 30^th choosing 6 to 10 highest market capitalization firms from 13 different non- financial sectors, and thus we were left with 360 companies. However, most of these firms were either delisted or had missing data issues, therefore, the ultimate data set shrank to 70 companies. In this research target elaborate value addition effect, corporate size, debt and nearness to cash on stock returns of 10 sectors comprising 70 companies' data of PSX during 2005-2006 to 2014-2015. For this study data was acquired from published yearly reports of respective companies. Moreover, the data was analyzed using EVIEWS 9 and STATA 14 which are specialized econometric software.

SR = Annual stock return

CFO = operating cash flows

ROE = Return on equity

ROA = Return on Assets

EBIT = Earnings before interest and taxes

NI = Net profit after tax

EPS = Earnings per share

Firm Size = Log of Total Assets

LIQ = Liquidity means Current Assets / Current Liabilities

LEV = Leverage means Debt/Total Assets

EVA =(NOPAT - WACC)×Invested Capital.

Where

NOPAT=EBIT(1-Tax rate)

WACC=W_eK_e+ W_dK_d(1-Tax rate)

Invested Capital=Total Assets-Non Interest bearing Current Liabilities

K_e= R_f+ β(R_m-R_f)+ε

β= ((σ_{KSE100 & Stock})/(σ²_KSE100))

Following two approaches are employed to the robustness of EVA dynamics in explaining stock prices drifts.

Panel data analysis is employed for estimation. The statistics acquired from audited published yearly reports of respective companies and FSA (Financial Statement Analysis) reports of SBP. The methodology of prior researches to investigate the comparative and differential predictive capability of EVA in contrast to other conventional bookkeeping performance measures towards stock returns is used as follows(Ismail, 2006; U. A. Khan, Aleemi, & Qureshi, 2016; Kumar & Sharma, 2011). First, the comparative explanatory power of EVA besides supplementary traditional bookkeeping based performance measures is examined as below

SR_it=α_it+β₁EVA_it+ ∈_it(1)

SR_it=α_it+β₁SIZE_it+∈_it (2)

SR_it=α_it+β₁LEV_it+∈_it (3)

SR_it=α_it+β₁LIQ_it+∈_it (4)

SR_it=α_it+β₁ROA_it+∈_it (5)

SR_it=α_it+β₁ROE_it+∈_it (6)

SR_it=α_it+β₁EPS_it+∈_it (7)

SR_it=α_it+β₁CFO_it+∈_it (8)

SR_it=α_it+β₁EBIT_it+∈_it (9)

SR_it=α_it+β₁NI_it+∈_it (10)

Onwards the differential explanatory capacity of EVA by traditional bookkeeping methods in terms of explaining excess stock returns for fifteen days is tested as follows:

SR_it=α_it+β₁ROA_it+β₂ROE_it+β₃EPS_it++β₄EBIT_it+ β₅NI_it+ β₆SIZE_it+ β₇LEV_it +β₈LIQ_it(11)

SR_it=α_it+β₁EVAi_it+ β₂SIZE_it+ β₃LEV_it +β₄LIQ_it+β₅ROA_it+β₆ROE_it+β₇EPS_it++β₈EBIT_it+ β₉NI_it (12)

Where SR_it means the annual stock return of financial year-end on i^th stock for during t, ROA_it means percentage earnings on asset of i^th stock for during t, ROE_it means percentage earnings on equity of i^th stock for during t, EPS_it means Earnings per share after taxes of i^th stock during t, EBIT_it means Earnings before interest and taxes of i^th stock for during t, NI_it means NOPAT of i^th stock during during t, EVA_{i t} means Economic Value added of i^th stock for during t, SIZE_it means total assets of i^th stock for during t, LEV_it means financial leverage of i^th stock for during t, LIQ_it means liquidity of i^th stock for during t, β_1, β_2, β_3,..., β₉ are the coefficients.

Relative information content analysis is a technique of univariate regression analysis to study the descriptive influence of all the exogenous variables used in study individually by running separate regressions for each independent variable and then comparing the R² respectively following previous established research literature (Biddle, Bowen, & Wallace, 1997; Khan, Aleemi, & Qureshi, 2016; Sharma & Kumar, 2010; Worthington & West, 2004).

En route for investigating the incremental information content of Economic Value Added multivariate panel data regression analysis is used in model 10 and model 11 whereby model 10 excludes only EVA from the rest of the predictor variables ie. Conventional economic performance metrics like ROA, ROE, LEV, LIQ, EBIT, NI and then the difference of R squared is analyzed as follows

Consistent with prior research study of Ferguson, Rentzler, & Yu (2005) impact of EVA (earnings announcement day) financial event day t₀ is empirically tested using Event study to detect any statistically significant excess stock returns. This study uses an estimation window of pre 90 days(t-₉₀) and post 90 days (t₊₉₀) around event day (t₀) to compute expected returns using market model then these returns are statistically compared using t-test by creating 15 days window of pre 7 days (t_-7) and post 7 days (t₊₇) around event day (t₀). Below mentioned is the mathematical demonstration of the event methodology adopted.

The following table and related explanation shed light on the event analysis empirical findings.

Keeping in view of the relative information content analysis EVA has no significant relation with stock returns because in Pakistan Public limited company's follow International Financial Reporting Standards and Companies Act 2017 both of which don't require mandatory disclosure of EVA in annual audited financial reports nor investors have awareness of this value-based financial performance measure these are in conformance to preceding research (Altaf, 2016; Ismail, 2006). Rather results show the superiority of traditional accounting measures especially a highly significant positive impact of ROA on share prices which supports prior outcomes of(Burton, Lauridsen, & Obel, 2002; Nakhaei, 2013). Firm size has a negative and highly significant relation at a 1 % level of significance with stock returns this empirical results are in line with Investor recognition hypothesis which posits higher returns for small stocks because of investors ignorance and lack of information (Merton, 1987) and investor overreaction hypothesis too supports the notion of small firm size premium on the premise of lower expectations from small firms leads to surprising lucrative returns (Lakonishok, Shleifer, & Vishny, 1994). Moreover, reasons for this may be too big to monitor, agency costs, conflict of interest as well as these findings are in line with previous researchers (Li & Zhu, 2015; Paulson & Townsend, 2004). Leverage reveals highly significant negative relation with stock returns which shows firms dislike borrowing which supports Pecking order Theory that sheds light on the ranking of financing options because of transaction costs where companies prefer internally generated funds in shape of retained earnings before knocking at the door of external financers for debt. Furthermore because of the high cost of debt financing these days as well as bankruptcy and financial distress costs these findings are in line with prior studies (Giroud, Mueller, Stomper, & Westerkamp, 2012; Henry Kimathi, 2015). The study sample reveals investor confidence in traditional accounting-based financial performance measures like ROE and EPS but indifference towards working capital management policy is quite interesting as liquidity has a positive relation with stock returns but insignificant contrary to prior research (Abuzayed, 2012; Padachi, 2006).

Moreover, Event study results of all studied companies showed insignificant results as the t-Value in all sectors is less than +1.96. It is, therefore; established here lies the absence of any empirically substantial association among stock prices with EVA. The market reaction to EVA is not consistent with signaling hypotheses that EVA announcements provide valuable information to market and investors revised their portfolio accordingly. We may also conclude yet share prices of study sample reflect all the available information hence the Pakistani capital market is efficient. EVA is a value-based performance evaluation contrary to conventional bookkeeping metrics; however, it has no or less impact on prices of shares in case of Pakistan Stock Market. One of the reasons of insignificant results might be investors less awareness about EVA.

As we have conducted information content along with Event study analysis of value-based and conventional bookkeeping based metrics whereby the statistical outcomes refuted the claim of EVA advocates of its dominance over conventional performance methods for non-financial Pakistan Stock Exchange (PSX) listed firms. However, an interesting empirical finding of the asymmetry in EVA information content results whereby the significance of EVA reflected by incremental information content analysis yet asymmetric behavior as per the results of relative information content invites further research. Moreover, inclusion of company pertinent characteristics such as firm size, ROE and EPS enhanced the explanatory power of model towards stock returns. Furthermore, leverage reflects an inverse insignificant relation with stock returns but in line with theory due to tight economic climate cost of borrowing has risen besides the bankruptcy and financial miseries alleviate the problem also in line with the seminal work of Hamada (1972) as leverage enhances the systematic risk and required rate of return by the common stockholder as well as these findings are in line with pecking order theory of capital structure. Nevertheless, liquidity showed an insignificant with stock prices implying Pakistani investors are indifferent towards working capital management policy. In Pakistani capital markets traditional accounting-based measures are superior performance indicators and their robustness is empirically tested so they can serve well for management and other stakeholders to watch their relevant benefit i.e. from management point of view corporate profitability and from other stakeholders like creditors, suppliers and employees its financial soundness and ability to honor obligations as they become due.