Relationship between return and market finance essay

CHAPTER-2

REVIEW OF LITERATURE

Review No. – 1

Authors: Rolf W. BANZYear & Place: 1980, USAObjective: This study aims to examine the empirical relationship between the return and the total market value of NYSE common stocks. Methodology: The basic approach of the study involves grouping individual securities into portfolios on the basis of market value and security beta, estimating the relevant parameters (beta, residual variance) of the portfolios in a subsequent period, and finally performing either an ordinary least squares (OLS) regression [Fama and MacBeth (1973)] which assumes homoscedastic errors, or a generalized least squares (GLS) regression [Black and Scholes (1974)] which allows for heteroscedastic errors, on the portfolios in each time period. Tools Used: Single-period capital asset pricing model, time series regressionsConclusion: It is found that smaller firms have had higher risk adjusted returns, on average, than larger firms. This ‘ size effect’ has been in existence for at least forty years and is evidence that the capital asset pricing model is misspecttied. The size effect is not linear in the market value; the main effect occurs for very small terms while there is little difference m return between average sized and large firms. It IS not known whether size per se is responsible for the effect or whether size IS just a proxy for one or more true unknown factors correlated with size. Research Gap: The study does come up with a relationship between the size of the common stock and the returns but it fails to list the reasons as to why this size effect is seen and what factors give rise to size effect. Source: Journal of Fractal Economics 9 (1981) 3318.

Review No. – 2

Authors: Andrew W. LoTitle: When are contrarian profits due to stock market overreaction? Year & Place: 1989, CambridgeObjective: To prove that the profitability of contrarian investment strategies need not be the result of stock market overreaction. Methodology: The study construct a simple return-generating process in which each security’s return is temporally independent, and yet will still yield positive expected profits for a portfolio strategy that buys losers and sells winners. By exploiting contrarian strategy framework, show that these cross-autocorrelations are inconsistent with a return-generating process that is the sum of a positively auto correlated common factor [which generates positive index autocorrelation] plus an idiosyncratic bid-ask spread process [which yields weak negative serial dependence in individual returns]Tools Used: Returns MatrixConclusion: The profitability of contrarian investment strategies need not be the result of stock market overreaction. Even if returns on individual securities are temporally independent, portfolio strategies that attempt to exploit return reversals may still earn positive expected profits. This is due to the effects of cross-auto covariance’s from which contrarian strategies inadvertently benefit. Research Gap: Assumptions of a perfect market condition is not realistic and hence the claim made by the study is applicable only to a certain extent. Source: National Bureau of Economic Research

Review No. – 3

Authors: Narasimhan Jegadeesh; Sheridan TitmanTitle: Returns to Buying Winners and Selling Losers: Implications for Stock Market EfficiencyYear & Place: 1993, USAObjective:. Study aims to prove that strategies which buy stocks that have performed well in the past and sell stocks that have performed poorly in the past generate significant positive returns over 3- to 12-month holding periods. Methodology: The paper first describes the trading strategies that we examine and Section I1 documents their excess returns. It provides a decomposition of the profits from relative strength strategies and evaluates the relative importance of the different components. This return in subsamples stratified on the basis of ex ante beta and firm size and measures these profits across calendar months and over 5-year sub periods. The longer term performance of the stocks included in the relative strength portfolios is also examined and back tests the strategy over the 1927 to 1964. Tools Used: Portfolio Construction Tools, Return MatrixConclusion: Study finds that the profitability of these strategies is not due to their systematic risk or to delayed stock price reactions to common factors. However, part of the abnormal returns generated in the first year after portfolio formation dissipates in the following two years. A similar pattern of returns around the earnings announcements of past winners and losers is also documented. Research Gap: Data set considered in the study is 6 – 8 decades old, though the study does provide conclusive evidence but these findings may no more be applicable in the current market scenario. Source: The Journal of Finance, Vol. 48, No. 1. (Mar., 1993), pp. 65-91.

Review No. – 4

Author- Ernst Maug and Narayan NaikTitle – Herding and Delegated Portfolio Management: The Impact of Relative Performance Evaluation on Asset AllocationYear- 1995Objective – This paper investigates the effect of fund managers’ performance evaluation on their asset allocation decisionsResearch Methodology- The model used in the paper is a two stage model in which two scenarios are analyzed (I) Asset Allocation in a Bid-Ask Market with a Single Risky Asset-It takes the optimal contract as given and examines the asset allocation decisions when information endowment is exogenous (ii) Asset Selection in an Auction Market-It indigenizes the information acquisition decision and examines the circumstances under which the fund managers decide to acquire the same information as their peers. The paper also studies two different reasons for giving fund managers relative performance contracts and derives the optimal contracts. Conclusion- The first set up analyzed the case where one risky asset was traded in a bid-ask market and the agents had imperfect but nested information sets. The main results were Fund managers adjust their portfolio allocation to that of other funds, even if this implies that they neglect their own superior information. Neglecting their superior information may even take the form of buying where they would have sold (and vice versa) if they were trading on their own account. Sometimes the fund managers herd and trade when they would not have traded had they been managing their own money. The second set-up of market structure analyzed the choice between two different assets if the fund manager can acquire perfect information about one of these assets, and all fund managers have access to the same information. It was shown that: Fund managers decide to acquire the same information and the same asset as their peers, even if the expected returns from these decisions are smaller. Trustees who write these contracts rationally anticipate this behavior. Under some circumstances they prefer the insurance possibilities of a relative performance contract to the higher returns available if fund managers do not herdResearch Gap -The research is restricted attention to the case of one fund manager, whose compensation is set through a principal-agent set-up, treating the second fund mangers’ compensation as exogenous by assuming that he is trading on his own account. A more general model could look at the implications of relative performance contracts for all funds, effectively benchmarking funds against each other. Richer informational settings, e. g., allowing for non-nested information sets may yield further interesting insights…

Review No. – 5

Authors: Narayana R. KocherlakotaTitle: The Equity Premium: It’s Still a PuzzleYear: 1996Objective: To assess various theoretical attempts to explain these two different empirical phenomena: the large ” equity premium” and the low ” risk free rate.” & to show that while there are several plausible explanations for the low level of Treasury returns, the large equity premium is still largely a mystery to economists. Methodology: Paper focuses on exclusively on the risk free rate and equity premium puzzles. Follows. The paper describes the two puzzles and lays out the fundamentalModeling assumptions that generate them. it explores the potential for explaining the two puzzles by changing the preferences of the representative agent. Study also looks at the implications of market frictions for asset returns. Tools Used: Risk Return Matrix, Conclusion: There is a large differential in the cost of trading between the stock and bond markets. To make this explanation compelling, it is important to ascertain the size of actual trading costs in these markets, and to provide an explanation of why those costs exist discuss some early steps in this direction. The second explanation is that, contrary to original parametric restrictions, individual investors have coefficients of relative risk aversion larger than ten (either with respect to their own consumption or with respect to per capita consumption). As explained, the problem with this explanation is that only a handful of economists believe that individuals are that risk averse. One way to support the ” high risk aversion” view is to demonstrate that this apparently ” strange” assumption about human behavior is consistent with data other than the average realization of the equity premium. Until now, little has been done along these lines, but analysis of a ” prototypical” real business cycle model using generalized expected utility preferences represents a promising first step. Research Gap: Study only concentrates on a small part of the whole issue of why does equity market offer higher premium as compared to treasure bonds. Hence other parts of the equity premium ‘ puzzle’ has not been put in place by the study. Source: Journal of Economic Literature, Vol. XXXIV (March 1996), pp. 42–71

Review No. – 6

Authors: Peter Adamek John Y. Campbell Andrew W. Lo A. Craig MacKinlayLuis M. ViceiraTitle: The Econometrics of Financial MarketsYear & Place: 1997Objective: To provide a solution manual to the Econometric problems involved in the financial markets all over the world. Methodology: Application of statistical and economic models to simplify omplexities of financial markets and better identify and explain trends and projections of various data sets involved in the financial markets. Tools Used: Histograms, Regression Models, RWI Markov Model & various other statistical tools. Conclusion: Econometrics can provide significant data analysis tools that can be applied for financial data crunching and producing results that go a long way in helping managers for strategy formulation. Research Gap: All of the Econometrics tools are dependent on the data provided for analysis and hence the authenticity of data becomes a major factor for deriving accurate results. Hence without availability of extensive data application of Econometric Models is limited. Source: Princeton University Press

Review No. – 7

Authors: Geert Bekaert And Campbell R. HarveyTitle: Foreign Speculators and Emerging Equity MarketsYear & Place: 2000, USAObjective: There are many perceptions of the role of foreign speculators in emerging equity markets-many of which are negative. This research looks at the various ways foreigners can access emerging market equity (ADRs, Country Funds, or direct participation in the local market) and tries to assess the impact on expected returns, volatility, beta, and correlation. Methodology: The paper briefly surveys the literature on the impact of speculative activity on price volatility and welfare, focusing more specifically on the role of foreign speculators in emerging markets. It emphasizes the gradual nature of the capital market integration process, identifying the event ” increased foreign investment activity,” with three different indicators: the gradual introduction of American Depositary Receipts (ADRs) and country funds, the actual lifting of investment restrictions, and the extent of U. S. capital flows into the emerging equity marketTools Used: Conditional Volatility, Beta, and Correlation BuildConclusion: Capital market integration process reduces the cost of capital but perhaps by less than we expected. In fact, there are reasons to believe that the effect we measure is upwardly biased. Research Gap: The study considers liberalizations as an exogenous event, whereas policymakers would probably choose to liberalize when it is most advantageous to do so. Hence policy endogeneity would suggest that estimates of the study are biased upward. Source: The Journal of Finance * Vol. Lv, No. 2

Review No. – 8

Authors: Brad M. Barber And Terrance OdeanTitle: Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual InvestorsYear & Place: 2000, USAObjective: To shed light on the investment performance of common stocks held directly by households. Also to test two competing theories of trading activityMethodology: To do so, paper analyze a unique data set that consists of position statements and trading activity for 78, 000households at a large discount brokerage firm over a six-year period ending in January 1997. Tools Used: Return Matrix. Rational and irrational trading models. Conclusion: Empirical evidence supports the view that over confidence leads to excessive trading. On one hand, there is very little difference in the gross performance of households that trade frequently with monthly turnover in excess of 8. 8 percent and those that trade infrequently. In contrast, households that trade frequently earn a net annualized geometric mean return of 11. 4 percent, and those that trade infrequently earn 18. 5 percentResearch Gap: Results are consistent with models where trading emanates from investor overconfidence, but are inconsistent with models where trading results from rational expectations. Though liquidity, risk based rebalancing, and taxes can explain some trading activity, argue that it belies common sense that these motivations for trade, even in combination, can explain average annual turnover of more than 250 percent for those households that trade most. Source: The Journal of Finance • Vol. Lv, No. 2

Review No. – 9

Title: Do Momentum Based Strategies Still Work In Foreign Currency Markets. Author: John Okunev, D. W. (2001). Introduction: The author John Okunevt tries to find the profitability through Momentum Based Strategies Still Work In Foreign Currency Markets, The popular measures of price movements used in past studies have been filter and moving average rules. Both these rules have extrapolative buy and sell signals and indicate to buy when exchange rates are increasing and sell when exchange rates are decreasing. Under filter rules investors will buy when exchange rates increase by a certain percent above their most recent trough and sell when the exchange rates decrease by a certain percent below their most recent peak. Conclusions: Moving average rules give a buy signal when a short run moving average cuts a long run moving average from below. A sell signal occurs when a short run moving average cuts a long run moving average from above. A substantial number of studies have shown that both types of trend following rules have proven to be profitable in foreign exchange markets even after adjusting for interest expense and transaction costsFindings: Result found that long/short strategy of buying the most attractive currency and shorting the least attractive currency obtains average excess returns that are significantly positive. This would indicate that strong/weak momentum currencies relative to a base currency at a particular time are typically also strong/weak currencies relative to most other base currencies as well Finally, using a bootstrap methodology we show that the performance is not due to a time-varying risk premium but depends on the underlying autocorrelation structure of the currency returns.

Review No. – 10

Authors: Louis K. C. Chan and Josef LakonishokTitle: Value and Growth Investing: A Review and UpdateYear & Place: 2002, IllinoisObjective: Provide a selective overview of the academic research literature on value and growth investing & also to provide different explanations for the performance of value versus growth stocks. Methodology: Empirical research on the alternative explanations is reviewed, and some new results are provided with an updated sample. Tools Used: Returns Matrix, Portfolio Construction models. Conclusion: The evidence suggests that, even after taking into account the experience of the late 1990s, value investing generates superior returns. Common measures of risk do not support the argument that the return differential is due to the higher riskiness of value stocks. Instead, behavioral considerations and the agency costs of delegated investment management lie at the root of the value-growth spread. Research Gap: Study does not provide any new finding in relation to value or growth investing, it basically concentrates on the academic transition of these strategies and how researchers have developed over the years.

Review No. – 11

Authors: Geert BekaertTitle: Emerging markets financeYear & Place: 2003, USAObjective: To understand the model of market integration and segmentation in case of emerging markets of the world. Methodology: Emerging markets have long posed a challenge for finance. Standard models are often ill suited to deal with the specific circumstances arising in these markets. However, the interest in emerging markets has provided impetus for both the adaptation of current models to new circumstances in these markets and the development of new models. The model of market integration and segmentation is starting point. Next, emphasize the distinction between market liberalization and integration. Study explores the financial effects of market integration as well as the impact on the real economy. Study also considers a host of other issues such as contagion, corporate finance, market micro structure and stock selection in emerging markets. Tools Used: Financial Model AnalysisConclusion: The liberalization process has led to a very small increase in correlations with the world market and a small decrease in dividend yields. This decrease could represent a decrease in the cost of capital or an improvement in growth opportunities; fi economic growth increases post liberalization by about 1% per year on average over a 5-year period. Aggregate investment increases significantly after liberalizations, providing one channel for this increased growth. An upward shift in the income share accruing to the top quintile of the income distribution at the expense of the middle class. The lowest income share remained unchanged. Such research counsels against drawing hasty inferences between economic growth and economic welfareResearch Gap: Most of the research on emerging equity markets has tried to draw inferences from a somewhat reluctant data set. Emerging market returns are highly non-normal and highly volatile, and the samples are short. Moreover, a dominating characteristic of the data is a potentially gradual… Source: Journal of Empirical Finance 10 (2003) 3 – 55

Review No. – 12

Title: The Value Premium on the Danish Stock Market: 1950-2004*Author: Ole RisagerIntroduction: A number of influential studies have documented a considerable value premium for US stocks over long time periods (Fama and French (1992, 2008), Lakonishok et al. (1994)). Stocks with low price-earnings multiples, price-book values and other measures of value are reported to have given a higher mean return than stocks with high multiples and high asset growth (Cooper et al. (2008)). Outside the US, the evidence is more uncertain due to data shortages. Methodology: On the basis of a unique data set that extends over more than half a century, this paper not only shows that there is a value premium in the Danish market but also that growth stocks only produce high earnings growth in the run-up to portfolio formation. Growth stocks are therefore likely to have disappointed investors. We therefore also estimate the proportion of the premium that can be explained by growth stocks’ earnings disappointment. Conclusion: The results show that the value premium is positive in the majority of the 10-year periods though the premium displays considerable volatility even across decades. The mean annual premium is in the range 4. 2 % to 5. 7 % (depending on the nature of the portfolio selection methodology), but had we only worked with short sample periods like in Chan et al. (1991) and Fama and French (1998), the premium would have been much higher underscoring the point that we need long samples in order to be able to extract robust insights. The premium is statistically significant in spite of its volatility. That said, it should also be noted that the premium is under attack in the early 1990s, due to a banking crisis, and in the late 1990s, due to high investor appetite for growth stocks. In the new Millennium, the premium recovers to previous highs. Research Gap: The results outside the United States are less robust due to a maximum two decades of data observations; there is a need for more research on European and Asian markets. Source: Department of International Economics & Management, Copenhagen Business School

Review No. – 13

Title – Reputation Effects In Portfolio ManagementAuthor- Heber FarnsworthYear- 2004Objective- This paper is aimed at addressing optimal contracting between an investor and a portfolio manager when reputation building is possible. It predicts to show that larger funds, or those with higher reputations, will be more likely to give performance bonuses to managers. Research Methodology- In order to understand the reputation effects on the portfolio management, the research paper studies the contract between the investors and managers by way of two-fund theorem for log investors which says that the optimal way to hedge against the uncertainty of incompetent manager is to commit only a part of the invested wealth to the managed portfolio and put the rest in a benchmark. This proposition of Contracting with Asymmetric Beliefs is shown in a single period basis. While in Multi period Contracts the proposition proofs that an increasing reputation will lead to higher expected pay because of inflows into the fund. These inflows come from the investor who commits a larger and larger percentage of wealth to the manager as reputation improves. The above two proposition does not takes into consideration the moral hazards of reputation which shown in another model whose proofs provides two interpretation-the manager is paid a fixed fraction of assets under management and the way in which the fund is managed changes through time and the manager invests all of the fund assets according to the signal and assets under management Thus the models used in the research paper which shows the effect of reputation in single and multi-period and then connecting it moral hazards and career concerns of managers. Conclusion- The model suggests that contracts which offer a fixed percentage of assets under management may be optimal in that they provide the correct incentives to undertake costly effort. As a manager’s reputation becomes more established it is more likely that the manager will receive a bonus for performance (measured by excess return). This prediction seems consistent with current industry practice. The reputation effect itself gives the manager incentive to manipulate the updating process by misreporting.

Review No. – 14

Author: Estola, Matti, Hokkanen, Veli-MattiYear: 2005, , FinlandTitle: Asset Price Dynamics by Economic ForcesObjectives: To introduce a model describing the evolution of an asset price. To define the ‘ force’ that acts upon the asset price and show that the adjustment may be stable or unstable. To show that possible equilibrium asset price is conditional on the distribution of expectations of individual investors. Methodology: Qualitative approach. Using various models, to study the behavior of an individual investor, the behavior of the stock market, the asset pricing dynamics, etc. Tools Used: CAPM modelConclusion: The study analyzed the dynamics of one asset price and showed the existence of ‘ economic forces’ which either pushes the price toward its equilibrium value, or keep the price in motion with time. The equilibrium asset price equates the ‘ investors’ average expectation of the rate of return of holding these securities as compared with other investment possibilities. The evolution of the asset price was analyzed as a stochastic process where the randomness originates from ‘ investors’ information and beliefs concerning the future asset price. Asset prices may or may not have a deterministic trend, and the randomness of the process causes deviations from this trend.

Review No. – 15

Authors: Eugene F. Fama And Kenneth R. FrenchTitle: The Value Premium and the CAPMYear & Place: 2006Objective: We examine (i) how value premiums vary with firm size, (ii) whether the CAPM explains value premiums, and (iii) whether, in general, average returns compensate β in the way predicted by the CAPM. Methodology: Study precedes as follows first the relation between the value premium and firm size. Then the study examines CAPM explanations of the value premium. Section III explores the general problem for the CAPM created by variation in β unrelated to the size and value-growth characteristics of firms. Tools Used: CAPM Model Returns Matrix, Portfolio Construction Tools. Conclusion: There is no value premium among large stocks seems to be particular to (i) the post-1963 period, (ii) using the book-to-market ratio as the value-growth indicator, and (iii) restricting the tests to U. S. stocks. The overall value premiums in U. S. average returns are similar before and after 1963, find that market βs change dramatically. During the later period, value stocks have lower βs than growth stocks – the reverse of what the CAPM needs to explain the value premium. As a result, the CAPM fails the tests for 1963 to 2004, whether or not one allows for time-varying βs. During 1926 to 1963, however value stocks have higher βs than growth stocks, and, like Ang and Chen (2005), we find that the CAPM captures the value premiums of the earlier period near perfectly. Research Gap: The study talks about the relation between value returns and size of the firm but ignores other factors such as survivorship bias and the industry of the firm. Also the findings of the study are restricted to US markets only. Source: The Journal of Finance, vol 61, p. p. 2163-2185.

Review No. – 16

Authors: Ron BirdTitle: Value Enhancement using Momentum Indicators: The European ExperienceYear & Place: 2007, AustraliaObjective: To better comprehend the transitional process by which stock prices drift away from, and revert back to, fair value. By so doing, study also provide insights to the investment community that might permit the better exploitation of these mispricing’s and as a consequence make a contribution towards more efficient pricing.. Methodology: Examining a simply overlay of price momentum on a traditional value strategy, and then turn to more complex momentum indicators which will be better attuned to identifying turning points in the pricing cycle. The two momentum signals used as an overlay on a value strategy are (i) price momentum enhanced by acceleration indices and (ii) earnings momentum as measured by analyst forecast revisions enhanced by the dispersion in the analyst forecasts. Tools Used: Payoff Matrix, Return MatrixConclusion: Study finds that a value strategy in isolation would have performed reasonably well if implemented across the European markets over the last 15 years. However, one major factor which detracts from performance is that traditional value indicators designate many stocks as being cheap which do not recover in the immediate futureResearch Gap: Study considers data of only 15 European nations and tries to develop conclusions thus the data set being small the conclusions cannot be generalized for all of Europe. Also portfolio distribution strategy of the study is also not clear.

Review No.-17

Authors: Ron BirdTitle: The Good and the Bad of Value Investing: Applying a Bayesian Approach to Develop Enhancement ModelsYear & Place: 2007, SydneyObjective: The hypothesis in this paper is that the values stocks are most likely to mean-revert are those that are financially sound. Further, it is proposed that we should be able to gain some insights into the financial strength of the value companies using fundamental accounting data. Methodology: The study applies a Bayesian model averaging approach to a set of fundamental accounting variables to forecast, the probability of each value stock outperforming the market. These probability estimates are then used as the basis for enhancing a value portfolio that has been formed using some valuation multiple. Tools Used: Mean Reversion Analysis, Bayesian ModelConclusion: Fundamental accounting data seems to be useful in differentiating between value stocks as determined by applying a traditional multiple, such as book-to-market. Research Gap: There is lack of consistency in the importance of variables both over time and between countries. We have identified at least one instance where the technique that we use to develop the models would have seemed to have problems in updating the models. Source: SSRN-id391686

Review No. – 18

Title: Relationship between P/E Ratio, P/Bv Ratio and Market, Capitalization and Common Stock Returns. The Evidence for the Warsaw Stock Exchange. Author: Dariusz Zarzecki Katarzyna ByrkaYear: 2008Objective: First objective of the paper is to present an essence of the ’P/E Ratio Effect’, ’P/BV Effect’ and ’Size Effect’ (known also as the ’Small Capitalization Firms Effect’). Second and the main objective of the paper are to investigate whether or not the effects mentioned above have occurred at the Warsaw Stock Exchange. Methodology: In order to reveal potential regularity concerning existence of the three analyzed anomalies (effects) at the Warsaw Stock Exchange the authors adopted the following procedure. Starting point of the research was chosen when twenty companies had been quoted, so the benchmark date is 12. 10. 1993. Then a division into three groups of companies was carried out.·Group 1 – five stocks with the lowest P/E ratio (portfolio No 1); Group 2 – ten stocks with an average P/E (portfolio No 2);· Group 3 – five stocks with the highest P/E ratio P/E (portfolio No 3). Each group was considered as a separate portfolio having an equal proportion of stocks which compose it. Every six months returns on the three portfolios were compared, so that H0 hypothesis: 2 1 m = m, which means that the return on portfolio No 2 is equal to the return on portfolio No 1, was verified, against the alternative H1 hypothesis: 2 1 m < m, saying that the return on the portfolio No 2 is lower than the return on portfolio No 1. H0 hypothesis was verified every consecutive moment of the analysis. Conclusions: Existence of the ‘ P/E Ratio Effect' may be confirmed by comparison of the returns from portfolios No 1 and 2, which were created again (on the basis of the P/E ratio criterion) one 10 year after the first allocation (12. 10. 94). In each analyzed period except one results obtained from the survey confirm relationship between the P/E ratio and return; however only in one case the difference is statistically significant. Nevertheless, the observed differences between returns are quite substantial. Source: Department of Finance, University Szczecin University Szczecin UniversityReview No. – 19Title: The Free Cash Flow Anomaly Revisited: Finnish EvidenceAuthors: Annukka Jokipii and Sami V¨ah¨amaa. Year: 2008Introduction: This paper examines the performance of an investment strategy based on free cash flows using financial statement data of Finnish companies during the period 1992-2002. The analysis in this paper is motivated by the so-called free cash flow anomaly previously documented e. g. in Hackel, Livnat and Rai (2000). Methodology: Using annual financial statement information, it identify large capitalization companies with positive free cash flows, low free cash flow multiples, and low financial leverage. Since a portfolio of these companies is found to consistently outperform the market index, our results suggest that the free cash flow anomaly also exists in the Finnish stock market. Conclusions: The empirical findings reported in this paper demonstrate that the free cash flow anomaly also exists in the Finnish stock market. Results show that a portfolio of large-capitalization companies with positive free cash flows, low free cash flow multiples, and low financial leverage consistently outperforms the market portfolio. On average, the 12-month buy-and-hold return for the free cash flow portfolio exceeds the corresponding return for the market index by about 11. 8%. Moreover, the cumulative 11-year return for the free cash flow portfolio is 614%, compared with the corresponding return for the market index of 144%. Even after taking into account the systematic risk and other known risk factors, the companies in the free cash flow portfolio still provide superior returns in comparison to the market index. These results are surprisingly similar to the empirical findings reported in Hackel et al. (1994 and 2000) and Hackel and Livnat (1995). Thus, consistent with the previous studies, the results presented in this paper suggest that investors can earn abnormal returns with investment strategies based on free cash flows. Source: Journal of Business Finance & Accounting, 33(7) & (8), 961–978,

Review No. – 20

Authors: Rajesh PathakTitle: Does Contrarian Investment Strategy Work in IndiaYear & Place: 2008, IndiaObjective: To check whether the widely popular contrarian strategies can produce better returns in India. Methodology: Data on returns, price to earnings ratio and price to book ratio has been collected from CMIE database (Prowess) for the period March 1993-March 2007 for all the BSE listed stocks. Reason for selecting this period for study is that after March 2007 the stock market reacted dramatically. There was a bull run first which took the market (BSE Sensex) all the way to 22000 and thereafter a nosedive. Taking data of before 1993 was reducing the sample size significantly because of unavailability of data. After sorting for the scrip with missing data the number of firms which met the criteria found to be 723. The portfolio has been designed and returns of the portfolios have been calculated in the way Lakonishok, Shliefer and Vishney (1994) have done. In the march of each year the stocks have been divided into ten deciles called portfolios on the basis of P/E and P/B separately. Portfolio 1 containing the lowest ratio stocks and portfolio 10 with highest ratio stocks for all the ten portfolio formation periods. We find the average returns of these portfolios for up to five years after formation using return data. The post formation average returns up to five years of all the portfolios for the period 1993-2007 have been averaged to find the post formation returns up to five years for all the ten portfoliosTools Used: Multiple Regression, Comparative AnalysisConclusion: The results of this paper supports the value strategy that it earns a good returns over a time period and outperforms the glamour stocks in Indian context also. It shows that buying the out of favor stocks is in the favor of investors. The another thing this paper argues that the contradictory view about value strategy that it produces higher returns as compensation of additional risk taken which means buying value stocks are riskier because they are not fundamentally strong companies does not seem applying here. The important point is for value strategy to produce returns it’s important that the investors have long term horizon, not very short term like four months or so because investors always want to offload their position as soon as possible and earn returns but this motive may put them at back foot in the market. Research Gap: The paper does not talk about the reasons for existence of higher returns through Contrarian Strategies also there is no analysis of the post-recession stage of the economy. Source: SSRN-id1782706

Review No. – 21

Author: Gagan Deep Sharma, M. M. (2008). Title: Efficiency Hypothesis of The Stock Markets: A Case Of Indian Securities

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Objective – The paper attempts to investigate the validity of the Efficient Market Hypothesis on the Indian Securities Market. Initially, the paper discusses the definitions and types of the EMH, as also the literature available on the same. Taking a sample of eleven securities listed on the Bombay Stock Exchange (BSE), the oldest stock exchange of Asia, we apply the runs tests and the autocorrelation tests in order to judge the efficiency of the Stock Markets. The Autocorrelation test when directly applied to share prices gives conflicting results with Runs test and thus, making it difficult to reach a definite conclusion. Then, the autocorrelation test is applied to first differenced series, which gives satisfactory results. In a nutshell, that the effect of stock prices for the sample companies on future prices is very meagre and an investor cannot reap profits by using the share price data as the current share prices already reflect the effect of past share prices. Methodology The paper takes a sample of eleven securities listed on the Bombay Stock Exchange (BSE). The paper concentrates on the shares of eleven companies. These include – ACC, Bajaj Auto, BhartiAirtel, Cipla, Dr. Reddy’s Labs, Grasim, HDFC Bank, Hindalco, Maruti Suzuki, Satyam Computers, and Wipro. All of these are listed on the Bombay Stock Exchange. Out of these companies, ACC, BhartiAirtel, Grasim, HDFC Bank, Hindalco, Maruti Suzuki, Satyam Computers, and Wipro are included in the thirty companies forming part of SENSEXConclusion: The findings of this study indicate that the BSE needs to strengthen its regulatory capacity to boost investors’ confidence. This would involve them being more stringent in enforcing financial regulations, performing regular market. Thus, at the end it can be inferred that the effect of stock prices for the sample companies on future prices is very meager and an investor cannot reap profits by using the share price data as the current share prices already reflect the effect of past share prices. Source: IJMBR2313250178012

Review No. – 22

Author: Shahid EhmedYear & Place: 2008, Jamia Millia Islamia, New Delhi, IndiaTitle: Aggregate Economic Variables & Stock Market in IndiaObjectives: This study investigates the causal relationship between stock prices and the key macro-economic variables representing real and financial sector of the Indian Economy. These variables are the index of industrial production, exports, foreign direct investment, money supply, exchange rate, interest rate, NSE Nifty and BSE Sensex in India. To prove that domestic economic fundamentals play determining role in the performance of stock market but in case of globally integrated economy, domestic economic variables are also subject to change due to the policies adopted and expected to be adopted by other countries or some global events. The important external factors could be stock prices in global economy, the interest and the exchange rate. Methodology: The study mainly involves the use of Time Series Analysis to know the mean and variance of data between two time periods i. e. various data regarding interest rates, inflation, exports, FDI etc. Also three unit root tests are applied to test whether a series is stationary or not. Tools Used: Co-Integration Test, TY Granger Causality Test , Variance Decomposition Impulse Response functionConclusion: The purpose of the present study is to explore the causal relationships between stock prices and the key macro variables representing real and financial sector of the Indian economy. Johansen’s approach of co integration and T-Y Granger causality test have been applied to explore the long-run causal relationships while BVAR modeling for variance decomposition and impulse response functions has been applied to examine short run causal relationships. Co-integration regressions indicate the presence of a long run relationship between stock prices and FDI, stock prices and MS and stock prices and IIP. However, except for interest rate and exports, the pattern of co integration and long-run Granger causality in each market indicates differential pattern. The relationship between money supply and stock prices has been widely studied because of the belief that money supply changes have important direct effects through portfolio changes, and indirect effects through their effect on real economic activity, which in turn postulated to be the fundamental determinants of stock prices. Research Gap: In the study it is shown that in case of short run there is no differential impact on causal pattern (i. e. stock prices and macroeconomic variables) in the result as indicated by variance decomposition and impulse response functions. The study indicates that exchange rate does not influence BSE Sensex and NSE Nifty and vice versa but actually this might not be the case.

Review No. – 23

Authors: Elton Babameto & Richard D. F. HarrisTitle: Exploiting Predictability in the Returns to Value and Momentum InvestmentStrategies: A Portfolio ApproachYear & Place: 2008, EnglandObjective: Investment managers are likely to be reluctant to pursue pure value and momentum strategies in spite of the favourable risk-return trade-off that they ostensibly offer. This paper, addresses this problem by implementing a combined value and Momentum strategy using the portfolio optimization model. Methodology: Study implement a combined value-momentum strategy using the Black-Litterman portfolio optimization framework, applied to a single global market comprising 177 national industry indices of the US, UK and Japan. It develops forecasting models for zero-investment value and momentum strategies, and incorporates the out-of-sample forecasts from these models into the Black-Litterman approach. Tools Used: Litterman portfolio optimization, Black-Litterman Forecasts ModelConclusion: The combined value-momentum strategy yields a significant improvement in performance relative to the underlying benchmark. Using the Black-Litterman model, we can effortlessly track the benchmark at the desired tracking error level under full investment, long-only and beta-neutral constraints, while producing an average annual investment outperformance of up to 0. 7 percent, even after allowing for substantial transaction costsResearch Gap: Study focuses on combining the best of value and momentum strategies but it ignore the risks that are attached to both the strategies. If a combined strategy is to be implemented a manager may stand to lose from both the strategies also. Source: Exeter Centre of Finance and Investment.

Review No. – 24

Title: Growth and Value: Past growth, predicted growth and fundamental growthAuthors: Aswath DamodaranYear: June 2008Introduction: A key input, when valuing businesses, is the expected growth rate in earnings and cash flows. Allowing for a higher growth rate in earnings usually translates into higher value for a firm. But why do some firms grow faster than others? In other words, where does growth come from? In this paper, we argue that growth is not an exogenous input subject to the whims and fancies of individual analysts, but has to be earned by firms. In particular, we trace earnings growth back to two forces: investment in new assets, also called sustainable growth, and improving efficiency on existing assets, which we term efficiency growth. Methodology: Study uses decomposition of growth to examine both historical growth rates in earnings across firms and the link between value and growth. Paper by noting that the relationship between growth and value is far more nuanced than most analysts assume, with some firms adding value as they grow, some staying in place and some destroying value. Growth is a central input in the valuation of businesses. In discounted cash flow models, it is the driver of future cash flows and by extension the value of these cash flows. In relative valuation, it is often the justification that is offered for why we should pay higher multiples of earnings or book value for some firms than for others. Given its centrality in valuation, it is surprising how ad hoc the estimation of growth is in many valuations and how little we know about its history, origins and relationship to value. Conclusions: In particular, study finds that growth rates tend to vary widely across sectors and across different measures of earnings, are lower for larger firms and reveal little persistence. Firms that have grown at high rates in the past are just as likely to be low growth firms in the future as high growth firms. We turn to the determinants of growth and argue that growth ultimately can be traced back to either new investments (or the marginal returns on those new investments) or to improved efficiency. We use that insight to develop the relationship between growth and value, and argue that growth can be value destructive in some cases. Source: Stern School of Business

Review No. – 25

Title: Value vs. Growth – The Importance of Investment StyleAuthor: Robert G. Kahl. Year: 2008Introduction: There are four major investment styles for investors in common stocks: value, growth, momentum and indexing.  Value investors seek to purchase a portion of a business for a price below its intrinsic value.  The intrinsic value of a company may be based on either (or both) the value of its net assets or the ability of the company to generate future earnings. Growth investors attempt to purchase stocks that have high expected future growth rates.  Some growth investors are more disciplined with regard to the price they are willing to pay for future growth.  They seek growth at a reasonable price (GARP). Momentum investors seek stocks that have experienced recent acceleration in earnings or upward price movement.  The theory behind momentum investing is that stocks that have done well in the recent past will continue to do well. Indexing has become more popular in recent years as some investors choose to accept modest under-performance relative to a chosen index in return for low management fees and transaction costs. Objectives: To answer questions like: Is Style a Key Determinant of Investment Returns? Higher Returns with Less Risk? Will the Value Investing Advantage Continue? Conclusions: Four major investment styles for investors in common stocks are value, growth, momentum, and indexing.   The results of all studies were consistent. Value investing strategies outperformed growth strategies.  This held true regardless of which variable was used to identify value stocks.  Variables that were used to identify value stocks included price/earnings, price/book value, price/cash flow, and price/free cash flow and dividend yield.  None of the studies found evidence to support the view that value strategies involve more risk. Although growth stocks initially experience higher growth rates than value stocks, the growth rates of both quickly revert toward the mean.  When investing in stocks, investors demonstrate over-optimism for growth stocks and over-pessimism for value stocks.  Several researchers expect the value investing advantage to continue, based upon the persistent nature of human behavior. Source: Journal of Finance

Review No. – 26

Authors: Vanita Tripathi and Shalini AggarwalTitle: The Overreaction Effect in the Indian Stock MarketYear & Place: 2009, IndiaObjective: This paper examines if there is any overreaction effect present in the Indian stock market, using the monthly closing adjusted prices of 500 stocks comprising S&P CNX 500 Equity Index. Methodology: The overreaction hypothesis is tested using the methodology of De Bondt and Thaler (1985). The possibility of change in the risk of winners’ and losers’ portfolios from the formation period to the test period as an explanation behind the observed return reversals is investigated using the method advanced by Chan (1988). Tools Used: Calculation of cumulative market adjusted returns, Mean Equality TestConclusion: The findings reveal the presence of statistically significant but asymmetric overreaction effect in the Indian stock market. Contrarian investment strategy has been found to be economically feasible, generating abnormally positive returns on market-adjusted as well as risk-adjusted basis which are largely attributable to the extremely positive returns to loser stocks during the test period. These findings cast serious objections against the informational efficiency of the Indian stock market suggesting that investors can earn superior returns by making use of the information on past prices of securities. Research Gap: The study supports the existence of over-reaction effect in Indian stock mark Asian Journal of Business and Accounting, 2(1&2), 2009, 93-114et but fails to give any reason or explanation behind why such effect exists. Source: Asian Journal of Business and Accounting, 2(1&2), 2009, 93-114

Review No. – 27

Authors: Dr. Mayank JoshipuraTitle: Does the stock market overreact? Empirical evidence of contrarian returns from Indian markets. Year & Place: 2009, IndiaObjectives: 1. to test the validity of market overreaction hypothesis and presence of contrarian profits in Indian Markets. 2. To find out the point of reversal for existing momentum, in case if evidence of long term contrarian profit is found. Methodology: Monthly adjusted return data for all companies listed on NSE for the period of January 1995 to December 2008 is used from CMIE’s Prowess and all stocks with non-missing returns during portfolio formation period are considered for analysis. The analysis is performed using six years of data, first three years’ data for portfolio formation and next three years of portfolio testing period. As study uses fourteen years’ data, this analysis is repeated for nine times using twelve months overlapping period starting from January 1995. The similar analysis is done for the shorter testing periods using one year data – 6 months of formation period and 6 months of holding period. Twenty nine such six months overlapping periods for the analysis starting from January 1995 are used. An analysis using two year data – one year formation period and one year of holing period is also done with thirteen overlapping formation and test periods. Using overlapping data provides dual advantage. First, it works against the overreaction hypothesis and hence provides rigor to the testing process. Second, it allows using more number of sample testing periods and hence increases reliability of the study. Tools Used: CMIE Prowess Database, Volatility analysis, Comparative analysis. Conclusion: There is strong evidence found against the randomness and weak form of market efficiency from Indian markets. For the short term formation – test period of six months and one year, strong evidence of momentum profit was found. Further, it has been found that momentum profits are contributed almost equally by winner and loser portfolio, the contribution of winner portfolio is much more then loser portfolio, especially in six months portfolio. Reversal in momentum is much faster in case of loser portfolio. When it comes to a longer duration formation and test period of three years, strong evidence of contrarian profit is quite evident. It has also been found that none of these momentum and contrarian profits was due to ‘ glamour stock’ or for compensation of higher risk in that portfolio. The results are consistent with the result of seminal studies of Jegadeesh and Titman (1993, 2001) and De Bondt & Thaler (1985, 1987and 1990). Results of the study provide evidence for the behavioral theory, which explains initial under-reaction due to a delayed response by chartist/momentum traders followed by an overreaction on their delayed response and momentum. However, this over-reaction effect gets fizzled out in the long run and that leads to contrarian profits. To conclude, the study provides a strong evidence of short term momentum and long term contrarian profits. It also proves that market overreaction followed by initial under-reaction actually leads to short term momentum profits. Subsequently in the long run, market adjusts itself to the overreaction, resulting into long term contrarian profits. Research Gap: Degree of success of the strategy has not been quantified. Question still remains how much are contrarian strategies successful. Also study does not compare the pre and post crisis period returns. Source: NSE India Research Journals

Review No. – 28

Title: Dynamic portfolio management with transaction costs (Suarez, Moody, & Saffell)Author: Alberto Suarez; John Moody; Matthew Saffell. Year: 2009Place: Spain; USAObjective: The selection of optimal portfolios is a central problem of great interest of quantitative finance, one that still defies complete solution. A drawback of the standard framework formulated by Markowitz is that only one period is used in the evaluation of the portfolio performance. In fact, no dynamics are explicitly considered. Authors address the asset management problem following the proposal of Moody et al and use reinforcement learning to optimize objective functions such as the Sharpe ratio that directly measure the performance of the trading system. Methodology: They extend the Recurrent Reinforcement Learning (RRL) approach to produce more evenly diversified portfolios and smoother asset allocations over time. The methods are assessed on a global asset allocation problem consisting of the Pacific, North America and Europe MSCI International Equity Indices. The performance of the reinforcement learning system is assessed on real market data and compared to the market portfolio (optimal if the market were ideally efficient) and to the tangency portfolio computed using the Markowitz framework portfolio, which is optimal in terms of the Sharpe ratio, assuming zero transaction costs. Conclusion: For zero transaction costs, both a Markowitz portfolio, and the reinforcement learning strategy perform better than the market portfolio. Since the market portfolio is never rebalanced, there is no cost associated to holding the market portfolio even when transaction costs are different from zero (other than the initial investment, no transactions are needed to implement this passive management strategy). In the presence of non-zero transaction costs, the performance of the Markowitz portfolio quickly deteriorates. Only for small transaction costs (1%) and according to the Sharpe ratio is it better than the market portfolio. By contrast, the reinforcement learning strategy improves the results of the market portfolio even when higher transactions costs are considered (up to 3%). However, for sufficiently high transaction costs (5%), the market portfolio outperforms the dynamic investment strategies considered. Research Gap: It is important to analyze its performance in the presence of correlations, autoregressive structure in the series of asset prices. Furthermore, the reinforcement learning system is being extensively tested using different financial data, and its performance compared with alternative investment strategies. Finally, it is also necessary to consider the possibility of investing in a risk-free asset so that strong decreases in profit can be avoided during periods in which all the portfolio constituents lose value.

Review No. – 29

Title: Does High Price Earnings Ratio Predict Future Falls Of Stock Price? Author: Marián Vorek (2009)Objective: This paper examines the strategy of value investing and its further possibilities for prediction of stock performance, especially in connection with falls in stock prices. Methodology: The methodology used is based on the implications of the theory of financial markets and the methodology of fundamental analysis. The value investments analysis prepare estimates of a common stock’s intrinsic value by multiplying the respective multiplier (e. g. P/E, P/S, P/CF, P/BV) times the respective actual quantity of stock’s earnings, sales, cash flow, book value, etc. Price to earnings ratio is one of the most used and frequently discussed. The price earnings ratio and its dynamics are determined by current stock price and by earnings per share. Having tested historic yields of stocks in relation with their level of price earnings ratio, the analysts have discovered that there is a negative correlation between the stock’s yield and its level of price earnings ratio. Consequently, the above outcome has been further developed into a strategy called ” the strategy of low price to earnings ratio”. This strategy was subject to the further research of which results have doubted the efficient market theory. Conclusion: The research discovered that the investments into stocks with low price to earnings ratio achieved higher than average returns. Based on the above mentioned methodology and the outcomes of empirical studies, this paper focuses on the other side of that relation, whether the high price to earnings ratio predicts the future falls in stock prices and whether the price to earnings ratio could act as an indicator of the coming bear market. Source: University of Economics in Prague

Review No. – 30

Title: Value investing using price earnings ratio in New ZealandAuthor: Cameron Truong (2009)Objectives: To determine whether PE low stocks cheap and safe investment? And also to analyze the returns of low PE investment on the NZX. Methodology: To investigate the value investing strategy in New Zealand, gather stock price data from DataStream and actual earnings per share from IBES (Institutional Broker’s Estimate System) for New Zealand firms in the period from January 1997 to December 2007. PE ratio is calculated by dividing the share price by the actual earnings per share released by the firm for the most recent financial year. I exclude any firm with a loss for the financial year as this creates a negative PE ratio which is not meaningful. At year end, form five portfolios of firms based on their ranking of PE ratio for that year and assess the return of these portfolios in the following year5. This exercise is repeated yearly or we say the portfolios are rebalanced annually. Conclusions: The key lesson learnt from this empirical work is that low PE stocks outperform high PE stocks in New Zealand. This value premium may represent a mispricing phenomenon in the New Zealand equity market as it cannot be attributed to conventional risk measures. The mispricing of low PE stocks over high PE stocks may be explained, although not solely, by investors’ incorrect extrapolation of their past performance, and the market corrects itself when new information sheds light on erroneous expectations. Investors can, however, screen for other risk factors such as the level of debt and bond rating for the firm or avoid firms with any recent bad news so that the low PE portfolio can be truly low risk. 15 The mispricing is even more likely if investors can find low PE firms with reasonable expected growth rates. 15 This can be obtained from analysts’ forecast if available or projected from historical growth rates. Investors should also be aware that a low PE portfolio can be highly undiversified as this portfolio may contain a few stocks from the same sector with low PE. Finally, a cut-off level PE must be chosen depending on how many stocks the investor wants in the portfolio and the average PE in the market at the timeSource: University of Auckland Business Review | Vol11 Iss 1 2009

Review No. –31

Title: Do Value Investors Add Value? Author: George AthanassakosYear: 2009Objective: The purpose of this paper is first to examine whether a value premium exists following a mechanical screening process (i. e., the search process) in the Canadian markets between two distinctly different periods, 1985-1999 and 1999-2007, and second whether value investors add value in the stock selection process by being able to find truly undervalued stocks from the universe of the possibly undervalued stocks identified from the search process. Research Methodology: This paper uses data from COMPUSTAT from which earnings per share (E), book value per share (BV), shares outstanding, stock prices, and dividends paid are obtained, and from which trailing price to earnings (P/E) and price to book value (P/BV) ratios and market cap are derived. For the trailing P/E and P/BV ratios, the price (P) is as of the end of April of year (t) and E and BV are, respectively, the December (t-1) fully diluted annual earnings per share and book value per share for companies with fiscal year end December (t-1), as reported in COMPUSTAT. Market cap is derived by multiplying price per share times shares outstanding at the end of April of year t. Annual total stock returns for the second sub-period are calculated as the price change plus the dividend from April of year t to April of year t+1 over the price in April of year t, using COMPUSTAT. For the first sub-period, due to data unavailability, annual total returns were calculated as above, but data for the calculation were obtained from the Canadian Financial Markets Research Center (CFMRC) database. Conclusions: We find that a strong and pervasive value premium exists in Canada over our sample periods that persist in bull and bear markets and during recessions/recoveries. Value stocks, on average, beat growth stocks even when using the very mechanical screening of the search process. Furthermore, this paper demonstrates that value investors do add value, in the sense that their process of selecting truly undervalued stocks, via in-depth security valuation of the possibly undervalued stocks and arriving at their investment decision using the concept of ” margin of safety”, produces positive excess returns over and above the naive approach of simply selecting low P/E – P/BV ratio stocks. The paper was extended to the years of the ” great recession” (2008-2009) and despite the fact that over this extended period had a severe recession and bear market, on average, the sophisticated portfolio still beat the naïve value portfolio, consistent with earlier evidence. Research Gap: The study is conducted for the Canadian Stock Market and it compares the data for two separate time periods and tries to identify the consistency of value returns nut the fact remains that even if consistency is found it cannot be conclusive as other factors may be involved in generating returns as well such as investor sentiments in the two time periods. Source: Richard Ivey School of Business, the University of Western Ontario.

Review No. – 32

Title: Size, Value, and Momentum in International Stock Returns. Authors: Eugene F. Fama,* and Kenneth R. Frenchb. Year: 2009Introduction: In the four regions (North America, Europe, Japan, and Asia Pacific) study examine, there are value premiums in average stock returns that, except for Japan, decrease with size. Except for Japan, there is return momentum everywhere, and spreads in average momentum returns also decrease from smaller to bigger stocks. Methodology: Study tests whether empirical asset pricing models capture the value and momentum patterns in international average returns and whether asset pricing seems to be integrated across the four regions. Integrated pricing across regions does not get strong support in our tests. For three regions (North America, Europe, and Japan), local models that use local explanatory returns provide passable descriptions of local average returns for portfolios formed on size and value versus growth. Even local models are less successful in tests on portfolios formed on size and momentum. Conclusions: There are common patterns in average returns in developed markets. Echoing earlier studies, we find value premiums in average returns in all four regions we examine (North America, Europe, Japan, and Asia Pacific), and there are strong momentum returns in all regions except Japan. Our new evidence centers on how international value and momentum returns vary with firm size. Except for Japan, value premiums are larger for small stocks. The winner minus loser spreads in momentum returns also decrease from smaller to bigger stocks. In Japan there is no hint of momentum returns in any size group. Research Gao: The data set considered for the study is too small for it to be considered a study that can generate International results i. e. the result of the study may not be applicable throughout the world markets. Source: University of Chicago, Chicago, IL 60637

Review No. – 33

Authors: Kumara, A. C. (2010). Title: : Factors Influencing Indian Individual Investor Behaviour: Survey EvidenceObjective: Individual investor behavior is motivated by a variety of psychological heuristics and biases. Using survey data of more than 350 individual investors, we document four important results in the context of Indian individual investor behavior. First, investors make investment decisions based on heuristics; they assume price as decision-anchor and are overconfident in their judgments. Second, their investment behavior is highly influenced by representativeness and they do lot of mental accounting in the sense of grouping their gains and losses while making decisions. Third, though investors follow fundamentals, they tend to discount complex information at first instance; they prefer those pieces of information which are easily adjustable into their investment decision-making. Data and Methodology: The primary data for the present study consist of the responses from individual investors, collected by structured questionnaires. Since this exercise is what the success of the present study is greatly dependent on, the emphasis is on collecting data from diversified group of respondent individual investors. Survey questionnaires were distributed among 375 sample individual investors based in Delhi-NCR and 360 responses were received. Out of them, 5 filled-in questionnaires were found to be incomplete in some way or other, so, finally 355 responses were used for final analysis. Research Gap: The relationship between various cognitive and behavioral factors and individual investment behavior has been one of the most discussed and explored issues among the financial economics and applied finance researchers worldwide. Conclusion and Finding: The results of the principal components reveal five psychological axes that appear driving the sample Indian individual investor behavior. These five pertinent axes on the basis of the underlying variables are named as financial heuristics, self-regulation, prudence and precautious attitude, financial addiction, and informational asymmetry. Consistent with the prior literature, the result suggests that psychological biases, such as conservatism and under-confidence, are playing significant role in determining individual investor behavior; but multivariate analysis reports certain contrary behavioral axes such as prudence and precautious attitude and informational asymmetry which are not yet explained in prior literature in growing economies, particularly in Indian context. The findings from the survey of Indian individual investors show that behavioral biases do influence their investment decision making processes. It is evident from the findings that heuristic factors and prospect theory both are influential in the context of Indian individual investors, with heuristics such as anchoring, availability bias, and regret aversion attitude taking a dominant position against factors suggested under prospect theory such as loss aversion.

Review No. – 34

Authors: Arvydas Paškevičius*, Rūta MickevičiūtėTitle: Applicability of contrarian investment strategies in small capital nation markets, evidence from nasdaq omx vilniusYear & Place: 2011, ViliniusObjective: The aim of this study was to assess whether contrarian strategies would provide excessive returns during the economic growth and decline periods in the NASDAQ OMX Vilnius. Methodology: The objective of this study is to assess the possibility of receiving above the market returns from contrarian investment strategy in the NASDAQ OMX Vilnius, comparing them against the passive index tracking strategy. Thus, the return of hypothetically constructed contrarian portfolio will be mathematically and graphically compared against the movement of the OMXV index, representing the market portfolio, over the same time frame. The test for the profitability of contrarian trading strategies in this paper is based on the methodology used by De Bondt and Thaler (1985, 1987) and Jegadeesh and Titman (1993). The profitability of contrarian investment strategy was tested in the Lithuanian stock market during two periods: the pre-crisis (growth) period (from January 2003 till the middle of 2007) and the crisis (decline) period (from the third quarter of 2007 until the middle of 2010), as no considerable signs of stock market recovery were yet evident in the country. The current approach was opted for due to the fact that the stocks could have been possibly overrated at the end of 2005, and the consequences of such overrating were peaked stock prices and a sudden dropdown of the OMXV index. Tools Used: Portfolio Construction, Comparative Analysis, Calculation of Market Returns. Conclusion: When comparing the pure return percentages over the growth period, the contrarian strategy proves to provide smaller returns than the standard market, best-performing or worst-performing portfolio during 2003–2005. In 2006, the situation changes and the contrarian portfolio significantly outperform both best-performing, worst-performing and market portfolios with all the three previously mentioned stock holding periods. The graphical analysis and mathematical comparison of stock returns indicates greater returns from the contrarian investment strategies through the entire period 2007–2009 with all of the three holding periods – quarterly, half-yearly and yearly – relatively to the market portfolio. Research Gap: Period of Analysis is short, returns calculated and compared are for a short period and there is no out right rationale provided for selection of stocks in the study. Source: ISSN 1392-1258. ekonomika 2011 Vol. 90(1)

Review No. – 35

Authors: M. Yahyazadehfar, Sh . Shams, S. LorestaniTitle: Profitability of Momentum and Contrarian Strategies Based on Trading Volume in Tehran Stock Exchange: A Comparison of Emerging MarketYear & Place: 2011, IranObjective: To determine the relationship between profitability of Momentum and Contrarian Strategies and Trading Volume with a specific focus on Tehran Stock Exchange. Methodology: In this study, the profitability of contrarian and momentum strategies were traded in mid- term based on trading volume. The stocks were categorized into three parts (high, middle and low) at the outset. Then, the relationship between excess return with three components such as cross-sectional risk, lead-lag effect and time-series pattern were examined based on Jegadeesh and Titman approach. The sample including 108 listed companies of Tehran Stock Exchange that were traded over 2005-2010. Tools Used: Mean comparisons test, ANOVA and Ordinary Least Squares. Conclusion: The study concludes show that by increasing trading volume, the momentum or contrarian return will be increased. There would be a possibility of explaining instances of no significant momentum or contrarian return with cross-sectional risk and lead-lag effect in medium trading volume. Moreover, the momentum return can be described with independent variables on middle and high trading volume. Research Gap: The period considered in the study is too short to derive any meaningful results. Further no rationale has been provided over basis of categorization of stocks. Source: IJMBR231325017800

Review No.-36

Authors: Marek JancaTitle: A growth maximizing contrarian trading strategyYear & Place: 2011, PragueObjective: The goal of the study was to develop a contrarian speculative trading strategy with growth maximization as opposed to maximization of a subjective utility function as its guiding principle. Methodology: Study has exploited the fact that growth maximization is equivalent to sequential maximization of the end of period conditional expected logarithm of wealth. Next, approximated the log optimal portfolio by a mean-variance ancient portfolio. The speciation of the conditional expected return reacted our beliefs about the portability of contrarian strategies. In particular, specied the conditional expected return as a linear function of derivation from the average return in the previous period. The conditional variance-covariance matrix was specied by the Constant Conditional Correlation model from the Multivariate GARCH class. Tools Used: Multivariate GARCH Model, Constant Conditional Correlation modelConclusion: Equipped with the simulation results, the study evaluated the performance of the strategy on historical data. Based on economic criteria, chose weekly returns of three rmsactive in oil mining equipment and aliated services industry. Over the period from 1987 to 2010, it was able to generate an annual geometric mean return of about 24% when no cap on leverage was assumed even after accounting for mild transaction costs. When we capped the leverage by two, the return shrunk to 6. 6%. Research Gap: Use of approximation along with so called error maximization property of the mean-variance optimization leads to over betting in the sense of opening too large position in absolute terms.

Review No. – 37

Title: Fear, Greed, and Financial Crises: A Cognitive Neurosciences PerspectiveAuthor: Lo, A. W. (2011). Introduction: In March 1933, unemployment in the United States was at an all-time high. Over 4, 000 banks had failed during the previous two months. Bread lines stretched around entire blocks in the largest cities. The country was in the grip of the Great Depression. This was the context in which Franklin Delano Roosevelt delivered his first inaugural address to the American people as the 32nd president of the United States the relevance of human behavior to financial markets and economic affairs is not a new idea. John Maynard Keynes (1936) observed over seven decades ago that economic decisions were due more to ” animal spirits” than carefully weighed probabilities, and that financial markets operated more like beauty contests than efficient price-discovery platforms One of the most significant consequences of the Financial Crisis of 2007–2009 is the realization that the intellectual framework of economics and finance is incomplete in several respects. Conclusion: While the Financial Crisis has exposed some of the limitations of neoclassical economics, critiques of traditional economic theory have been accumulating from within the profession for quite some time. The conflict between the rational expectations paradigm of economics and the many behavioral biases documented by psychologists, behavioral economists, sociologists, and neuroscientists has been hotly debated for decades. Economics occupies an enviable position among the social sciences because of its axiomatic consistency and uniformity.

Review No.-38

Title: A Hybrid Value Investing Method for the Evaluation of Banking StocksAuthor: Shen Kao-Yi and Yan Min-RenYear: 2011Introduction: —Stock market is regarded as a highly dynamic and complex environment consisting of opportunities and risks. All participants want to earn profits by adopting their investment strategies. One of the most famous investment strategies is value investing, which attracts both practitioners and researchers’ attention all over the world. Empirical studies have consistently found that value stocks outperform the market in the long run, but it often encounters obstacles to implement this strategy in practices. Due to the need of in-depth analysis of financial statements, investors not only need accounting knowledge but also investment expertise. Among previous studies, the accounting-based fundamental analysis (F-score) has been a widely accepted model for value investing. The F-score model proposed nine fundamental signals to measure a firm’s financial prospect. However, it is difficult to acquire the implicit knowledge and interactive considerations of senior experts. Thus, the evaluation processes of investment experts cannot be revealed for the others’ reference. Research Methodology: To improve the limitations, this paper integrates fuzzy set theory and decision methods to propose an innovative model for distinguishing strong financial prospect stocks within high book-to-market (B/M) banking stocks. Our empirical study shows the practicability of our proposed method. It also provides the relative weights and the interdependence of each measurement variables for the value investing strategy. Conclusion: The result indicates the correlation between HRP from April_2009 to Jan_2010 and the synthesized rating is about +75. 63%. The correlation between HRP from period April_2009 to Feb_2010 and the synthesized rating is about 78. 38%. The correlation result goes up to 88. 41% after one month. The result shows that the proposed model can be applied to value investing in real practice. Research Gap: Study is conducted considering data of a short time span and thus the data might not be sufficient to give accurate results also the findings of the study are restricted to the banking sector and cannot be extended to other sectors. Source: International Journal of Trade, Economics and Finance, Vol. 1, No. 3,

Review No. – 39

Authors: Denis B Chaves, Jason HsuTitle: What Drives the Value Effect? Risk versus Mispricing: Evidence from International MarketsYear & Place: 2012, USAObjective: The study aims to define what drives the value premium: exposure to risk factors or mispricing of the securities. Existing empirical studies have not conclusively rejected one in support of the other and hence the study aims to come to a conclusion on this debate. Methodology: The study uses Fama and Macbeth (1973) regressions and extensions of the portfolio tests based on Daniel and Titman (1997); we provide evidence that the book-to-market characteristic largely subsumes the loading on the value factor (HML) as a variable that explains the cross-section of stock returns. It improve the power of existing tests by using data from 23 developed countries going back more than 30 years. Tools Used: Regressions, Portfolio TestsConclusion: The study concludes that mispricing is likely a more significant portion of the value premium. Research Gap: Data used in the study is restricted to the data from developed countries only & whether the findings of the study are applicable in developing countries still remains unanswered. Different results maybe expected as market conditions in such economies vary immensely. Source: SSRN-id1940504

Review No. – 40

Author: Dr. AurangzebYear & Place: 2012, PakistanTitle: Factors Affecting Performance of Stock Market, Evidence from South Asian CountriesObjectives: To study the impact of various variables affecting the Stock Market performance in South Asian countries. To verify that Inflation has little impact on stock market movement. Methodology: To find the long run relationship between the variables we, multiple regression analysis have been used. In this research focus has been on secondary type of data, all data is collected from the official database of World Bank, official publications of respected stock markets and official website of yahoo finance. The study has used five variables namely, stock performance, interest rate, inflation, exchange rate and foreign direct investment. The data of 3 countries is collected namely, Pakistan, India and Sri Lanka from the period of 1997 to 2010. Tools Used- regression analysis and descriptive statistics to analyses the results of the three nations. Conclusion: Regression results indicate that foreign direct investment and exchange rate have significant positive impact on performance of stock market in South Asian countries while; interest rate has negative and significant impact on performance of stock market in South Asia. Results also indicate the negative but insignificant impact of inflation on stock market performance in South Asia. Research Gap: The study results show that interest rate and inflation are two important variables that need to be observed to take full advantage of the stock market.