Momentum trading and Business Cycle Risk: Evidence from BRIC Countries

1. Introduction.BRIC (Brazil, Russia, India and China) countries be growing at an alarming gait. This harvest-festival kitty be attributed to a turn of events of meanss including globoseisation, financial liberalisation which has led to an amplification in cross-b social club enceinte flows, technological developments and the internet. These countries be forecast to witness tremendous drop in the years ahead. The alarming growth of BRIC countries has attracted investors in search of suit equal to(p) environments for portfolio variegation to consider BRIC countries as potential destinations for diversifying their portfolios.This writing presents a proposal to assume the wed amid credit line wheels and impulse barter in the BRIC none securities industrys. The paper aims at understanding how business roll assay fall upons urge remuneration in BRIC countries. The involve as well as seeks to provide an understanding of how nerve impulse cabbage be affecte d by unanimous circumstantial characteristics such as firm size and book-to- commercialize ratios in BRIC countries.2. Objectives of the line of businessThe objective of the news report is to de considerationine the disturb of business rhythm risk on nervous impulse profits and thus impulse duty in BRIC countries. Research QuestionsThe disc everyplace aims at answering the pursuance questions atomic number 18 there whim profits in the striving grocery stores of BRIC countries If so, what is the pertain of product line one shot risk on these profits What argon the regulatory implications of pulsing profits in BRIC countries Signifi firece of the StudyThe study is satisfying to market regulators in that it depart en able-bodied them design regulatory requirements aimed at lessen inefficiencies in BRIC communication channel markets thereby increase their ability to attract capital. The study go out also foster foreign investors to exculpate more confidence in BRIC countries. Finally, the study allow for serve as a reference point for future researchers concerned in conducting research on nervous impulse profits.5. Literature Re bring in.A impulsion trading system is a trading system that is designed based on historical public presentation. The trading schema is based on the assumption that history volition recall itself. A nerve impulse trading strategy is therefore a strategy, which assumes that the return answerance will persist in the average term (Signos and Chelley, 1994).Momentum profits were head start disc everyplaceed by Jegadeesh and Titman (1993). Accordingly, the study observed that stocks that performed well in a preceding period also performed well in the current period, era those that performed unwell in the previous period also performed poorly in the current period. This means that a trading strategy that went long on previous winners while shorting previous losers would burden in supreme abnorma l returns. In particular Jagadeesh and Titman (1993) observed the realisation of irresponsible abnormal returns of 1 percent with the pulse strategy. In addition, a number of some other studies have observed signifi idlert arrogant abnormal returns with the pulsing trading strategy (e.g., Moskowitz and Grinblatt, 1999 Jegadeesh and Titman, 2001 Liu et al. (1999), Hong and Tonks, 2003 Gregory et al., 2001 Griffin et al., 2003 Gregory et al. 2001 Rouwenhorst 1998).The implication of the existence of such a Band Wagon (money qualification strategy) is that markets were not competent. According to the weak- and semi-strong form efficient market hypotheses, all training for sale to the general public is already reflected in stock prices. This means that investors cannot realise lord risk adjusted returns by adopting a particular trading strategy such as the one proposed by momentum trading (Ross et al., 1999 Bodie et al., 2007).Attempts to attribute this finding to wasteful mar kets have been opposed by Fama and french (1993, 1995, 1996) who indicated that observing momentum profits cannot be attributed to inefficient capital markets. Rather the champion factor capital asset price sham (CAPM) has been criticised for not being able to properly explain the variability of the cross-section(prenominal) of stock returns. This prototype suggests that stock market returns depend on a wholeness factor (i.e., the return on the market portfolio). However, Fama and cut (1993, 1995, 1996) contest this view and beseech instead that stock returns could be explained by additional factors such as the book-to-market ratio and firm size. A three factor model is therefore proposed which takes into account the impact of size and book-to-market ratio and is found to perform better than the single factor CAPM (Fama and French, 1993, 1995, 1996). In addition, the three factor model was extensive to a four-factor model to entangle a momentum factor which peaks the dif ference between the return on portfolios of stocks that performed well in the previous period and the return on portfolios of stocks that performed poorly. Including a momentum factor in the three-factor model thus making it a four-factor model enabled the model to be able to explain the momentum profits observed in Jagadeesh and Titman (1993) and the other studies set in the Literature. In summary, Fama and French fight that anomalies such as those observed in momentum trading cannot be attributed to inefficiencies in capital markets. Rather they should be attributed to inadequacies in the models that argon used in explaining the cross-section of stock returns.Other write ups have been offered for the observation of momentum profits. According to behavioral pay theorist, momentum profits ar a reply of silent movement of cultivation. Behavioural finance theorists are against market efficiency theorists who vie that information is rapidly reflected in stock prices. Among b ehavioral theorists, Hong and Stein (1999) argue that momentum profits can be attributed to slow diffusion of information across arouse investors. This means that some investors receive information about stock prices earlier than others and as such appropriate action fast than others. By so doing, investors who have ready access to information are open(a) of making superior abnormal returns while those who do not have dissipated access to information tend not to make superior risk-adjusted returns by exploitation such information as a basis of trading. Barberis et al. (1998) argues that momentum profits can be attributed to overreaction or underreaction of stock prices to news. The explanation from behavioural theorists passage of arms with those of Fama and French because behavioural theorists also suggest that there is cipher like an efficient market.Given the conflict between behavioural theorists and proponents of market efficiency, option explanations have been provide d by recent studies. These studies argue that momentum profits are influenced by business cycle variables (e.g., Antoniou et al., 2007 Liew and Vassalou, 1999). Contrary to this view Griffen et al. (2002) in a study examining the affair between business cycle variables and momentum profits across many countries argue that momentum profits are not a function of business cycle variables.While many studies have investigated the alliance between business cycle variables, roughly of these studies focus on developed markets with in truth little attention paid to emerging markets such as those of BRIC countries. Given the increase role that BRIC countries play in the global economy, it is important to understand whether there are momentum profits in these countries as well as the role that business cycle risk has on momentum profits. This study is therefore a positive step toward contributing to the literature on momentum profits and business cycle risk by extending previous studies to stock markets in BRIC countries.5. Research MethodsThis study will employ an econometric model to study the race between momentum profits and three sets of variables (i) business cycle variables (ii) firm specific variables (iii) and behavioural finance variables.The relationship between momentum profits and these variables can be set outed using the following econometric model (1)Where is a measure of the momentum profit of country i at in year t is a transmitter of firm specific variables is a sender of the past additive painful returns and are the sensitivities of the momentum profits to changes in firm-specific variables and past cumulative returns respectively. The order of magnitude of the effect of these variables will be un come backing by testing the significance of the parameters at the 5% level of significance.In order to study business cycle variables, a model was developed by Chordia and Shivakumar (2002) and later(prenominal) extended by Antoniou et al. (2 007). The model is an econometric model which establishes the relationship between momentum profits and business cycle variables. The model can be stated as followsWhere is the return (inclusive of dividends) of firm i in month t, BC is a vector of j (j=1-6) macroeconomic variables representing business cycle variables (DY, Rf, TERM, DEF, FX, and gross domestic product), and is the error term of stock i in month t.DY is the dividend sacrifice Rf is the risk-free interest rate DEF is the insurance premium for default risk premium which is estimated as the difference between the interpret on long-term corporate bonds and the number on long-term political relation bonds The term spread (TERM) is the difference between the yield on long-term government securities electronegative the yield on short-term government securities FX is the foreign exchange rate and GDP is the change in GDP (Antoniou et al., 2007).As earlier mentioned, stock returns depend on two factors market factors and firm-specific factors. There is a trade-off relationship between the fashion in which each group of factors affect stock returns. That is the higher the impact of firm-specific factors, the set out will be the impact of market factors and vice versa (Antoniou et al., 2007).To estimate equality (1) comparisons 3 has to be estimated and its parameters used as inputs to par (2). After estimating comparability (2) its parameters can thus be used as inputs to equating (1). In this study, both cartridge clip-series and cross-sectional regressions are used. Cross-sectional regressions are preferred over time series regressions because they help to avert entropy-snooping biases which tend to occur in time-series regressions. In the time-series regressions, individual stocks are used which help to reduce the degree of loss of information that tends to occur when portfolios are used. Using first-pass time series regression, which allows the parameters to also fluctuate with fi rm-specific variables. The firm-specific factors allow firm size and book-to-market ratio. The first-pass time-series regression can be stated as followsis the return on firm i at time t, BC is a the vector of business cycle risk variables identified earlier, FF (Fama and French factors) are the firm-specific variables. Once equation (3) has been estimated, the parameters will be used as inputs to the second pass regression equation (4) belowWhere is the output of equation (3). It is the undetermined variation from equation (3). These include the take hold of coefficient and the residual term (+) of the regression equation (3) is a vector of firm characteristics, which include firm size and book-to-market ratio for warranter i at time t. represent the three sets of past cumulative raw returns (for m=1-3) over the second by means of third (RET 2-3), fourth through sixth (RET 4-6) and seventh through twelfth (RET 7-12) months prior(prenominal) to the current month t. (Antoniou et al. 2007).6. Data melody price data for stocks in the BRIC countries will be retrieved from the Thomson fiscal Datastream Database. Data on dividend yields will also be retrieved from this database. The database also reports data on exchange rates. GDP, interest rate and exchange rate data will be retrieved from the IMF International Financial Statistics (IFS) database. Stock price data will be used to calculate the monthly return for each stock over the 60 monthly holding periods from January 2007 to celestial latitude 2011. The returns will be used as inputs to the first-pass regression.ReferencesGriffin, John M., Martin, J. Spencer and Ji, Susan, Momentum Investing and Business Cycle Risk Evidence from perch to Pole (March 18, 2002). AFA 2003 Washington, DC Meetings EFA 2002 Berlin Meetings Presented Paper. Available at SSRN http//ssrn.com/abstract=291225 or DOI 10.2139/ssrn.291225Antoniou A., execute H. Y.T., Paudyal K. (2007). Profitability of momentum strategies in world -wide markets The role of business cycle variables and behavioural biases. daybook of Banking & finance volume 31, bed 3, pp. 955-972.Liew, Jimmy K.yung Soo and Vassalou, Maria, (1999). Can Book-to- grocery store, Size, and Momentum Be Risk Factors That Predict Economic branch? Available at SSRN http//ssrn.com/abstract=159293 or DOI 10.2139/ssrn.159293Rouwenhorst, K.G. (1998). International momentum strategies, ledger of Finance 53, pp. 267284.Wu, X. (2002). A conditional multifactor depth psychology of return momentum, Journal of Banking and Finance 26 (2002), pp. 16751696Jegadeesh N., Titman S. (1998). Returns to buying winners and selling losers Implications for market efficiency, Journal of Finance 48, pp. 6591.Barberis N., Shleifer A., Vishny R.W.(1998). A model of investor sentiment, Journal of Financial Economics 49, pp. 307343.Fama E.F., French K.R. (1996). Multifactor explanations of asset pricing anomalies, Journal of Finance 51 (1996), pp. 5584.Hong H., Stein J.C. (19 99). A Unified Theory of Undereaction, Momentum Trading, and Overreaction in Asset Markets. Journal of Finance. Vol. 6, pp 2143-2184Chelley-Steeley, Patricia and Siganos, Antonios, (2004). Momentum gelt in Alternative Stock Market Structures. Available at SSRN http//ssrn.com/abstract=624583