MOMENTUM AND CONTRARIAN INVESTMENT STRATEGIES

Transcription

1 CHAPTER VI MOMENTUM AND CONTRARIAN INVESTMENT STRATEGIES The Efficient Market Hypothesis (EMH) (Fama, 1970) suggests that prices are theoretically unpredictable and therefore there is no extra profit existing in the market. However in the real world situation EMH is strongly challenged by many financial anomalies. Many studies conducted by academicians and practitioners have recognised that average stock returns are related to past performance and the stock returns are predictable based on past returns. Number of researchers report that past losers (negative or lowest returnstocks) outperform past winners. De Bondt and Thaler (1985) document those stocks with extreme capital losses in the past; the so-called losers will outperform those with extreme capital gains, the so-called winners in the future 3-5 years. Jegadeesh and Titman (1993) also finds that stocks that perform the best (worst) over a 3 to 12 months period tend to continue to perform well (poorly) over the subsequent 3 to 12 months. Many studies like (Barberish, Shleifer & Vishny, 1998) also concluded with the opinion that when return autocorrelations are positive and statistically significant, investors could generate positive and significant profits by using the momentum strategy. If return autocorrelations are negative and statistically significant, investors could earn profits by using the contrarian strategy (Daniel, Hirshleifer & Subramahnyam, 1998). Thus, the variance ratio may also suggest

2 153 that there exists profit opportunities for contrarian and momentum strategies (Pan, Liano, & Huang, 2004). Momentum and contrarian strategies are two opposite investment strategies which try to make excess returns by investigating historical price or return data in order to forecast the future trend of stock performance. Momentum strategy believes that stocks which have performed well in past will be doing so, also in the future. It buys stocks with good historical performance and sells stocks which have done worse.(figure 6.1) Fig. 6.1 Momentum Strategy Under reaction Bad News Good Under reaction Price falls less than Justified Price rises less than Justified Sell Buy Price Correction Buy again Price Correction Books profits Source: Narasimhan M, Agarwal and Jain, (2004), An Analysis of Contrarian and Momentum Strategies in Indian Stock Market, NIBM, Vol: XXIII, No.1

3 154 Contrarian strategy on the other hand believes that stocks whose historical performance is bad are going to do better in the future because they would be under priced and historical winner stocks are going to come down because majority of them would be over-priced, so it suggests buying losers and selling winners based on historical data. (Conrad and Kaul 1998) (Figure 6.2) Fig. 6.2 Contrarian Strategy Overreaction Bad News Good Overreaction Price falls more than Justified Price rises more than Justified Buy Sell Price Correction Book Profits Price Correction Buy Again Source: Narasimhan M, Agarwal and Jain, (2004), An Analysis of Contrarian and Momentum Strategies in Indian Stock Market, NIBM, Vol: XXIII, No.1

4 155 The empirical evidence of success of both these strategies is strong and extensive, and these results have created a lot of interest in this area among institutional investors. For example, the contrarian strategy has become a widely used investment strategy in many funds and other investments. Number of studies has been conducted to test the effectiveness of these two strategies in earning superior returns and for determining the factors of their profitability. De Bondt and Thaler (1985) were one of the first categories of researchers arguing that contrarian strategy outperforms the market. Ever since the debate on that area has been strong.e.g. Chan (1988), Lo and McKinlay (1990),Jegadeesh (1990), Chopra, Lakonishok and Ritter (1992), Lakonishok et al. (1994),Conrad and Kaul (1993 and 1998) and Larkomaa (1999) all gave evidence for profitability by using contrarian strategy. The first main work when momentum strategy is considered is Jegadeesh and Titman (1993). Many researchers like Chan et al. (1996 and 1999), Rouwenhorst (1998 and 1999), Conrad and Kaul (1998), Moskowitz and Grinblatt (1999), Hong et al.(2000), Griffin et al. (2003), and Avramov and Chordia (2006) studied about the possibility of making profits by using momentum strategy. The evidence that both, momentum and contrarian, strategies can earn abnormal returns is very strong. However, the reasons behind the success of these strategies are still very controversial. The aim of this study is to demonstrate the contrarian and momentum investment strategies, their profitability in Indian stock market and reasons explaining their existence.

5 Sample and Methodology The methodology adopted by researcher is similar to the one which is adopted in studies like Narasimhan, Agarwal and Jain (2005), Moskowitz and Grinblatt (1999) and many other studies both in Indian markets and other emerging markets. Steps involved in the formation and evaluation of portfolios for studying Momentum and Contrarian strategies are as follows: 1. Mean of daily returns of stocks for the formation period was taken and then ranked them in the descending order. For this study the formation period was one month. Based on the ranking, two equal weight portfolios were formedone comprising of top seven stocks called as winner portfolio and other comprising of bottom seven stocks called as loser portfolio. 2. The daily returns of these two portfolios over the next H-week holding period were computed. H takes the value of 2 to 8 weeks. 3. Momentum returns are calculated as the mean of the daily returns arising from the winner portfolio for the holding period i.e H value 4. Contrarian returns are calculated as the mean of the daily returns arising from the loser portfolio for the holding period i.e H value 5. The performance of momentum and contrarian portfolios is evaluated by comparing with the daily index returns during respective periods. 6. The portfolio formation and evaluation process is repeated for the years with formation period of one month and holding period of 2,3,4,5,6,7 and 8 weeks respectively.

6 To study the profitability of momentum and contrarian strategies for various formations and holding periods, t-test was used. It was used to find out whether momentum and contrarian strategies yield significant positive returns when compared with the bench mark, i.e. index return. First step of the researcher for testing the effectiveness of the two investment strategies namely momentum and contrarian was to establish the entire study period in to various formation periods of one month each, by taking daily returns. Daily returns of the shares included in the construction of Nifty index and whose data which was available for the whole 6 years were taken for the study. So the sample size was 29 companies shares, the results of which are given in the following tables. Mean of daily returns had been taken for the study. 6.2 Analysis of momentum and Contrarian Strategies This section is divided in to three parts. First part explains the construction of formation period and the selection of the winning portfolio and Loser Portfolio. Next part of this section discusses on the formation of holding periods out of the portfolio constructed on equal weight basis and the computation of average returns. returns of winner portfolios are being compared with the average returns of looser portfolio. Index returns are calculated to provide a benchmark for all these comparisons. Researcher also employed T-test to compute the level of significance of mean returns. The results of the test are given in the third section.

7 158 Table 6.1 s in Formation Period for 29 companies (Jan 2004) Company Table 6.2 s in Formation Period for 29 companies (April 2004) Company TATA POWER UNITECH MARUTI CIPLA TATA MOTORS WIPRO GRASIM GRASIM PNB SUN PHARMA SBIN PNB M & M HCL ITC ACC SUN PHARMA RANBAXY ABB MARUTI BHEL RELCAPITEL HDFC ICICI BANK RELCAPITEL SIEMENS ACC SBIN HERO HONDA SAIL RELIANCE JINDAL HCL INFOSYS ICICI BANK ONGL UNITECH GAIL HDFC BANK ABB INFOSYS ITC ONGL TATA POWER RANBAXY M & M CIPLA HDFC BANK WIPRO HERO HONDA SAIL TATA MOTORS GAIL RELIANCE SIEMENS BHEL JINDAL HDFC

8 159 Table 6.3 s in Formation Period for 29 companies (July 2004) Table 6.4 s in Formation Period for 29 companies (Oct 2004 ) Company Company SAIL INFOSYS JINDAL UNITECH ITC WIPRO CIPLA JINDAL GAIL BHEL RELIANCE MARUTI TATA POWER SUN PHARMA INFOSYS SAIL HDFC SIEMENS TATA MOTORS ICICI BANK ICICI BANK HDFC ONGL ONGL MARUTI HDFC BANK BHEL M & M SIEMENS ABB HCL GAIL UNITECH TATA MOTORS RANBAXY RANBAXY WIPRO RELIANCE ABB HCL M & M ITC HDFC BANK TATA POWER RELCAPITEL CIPLA SBIN GRASIM ACC PNB SUN PHARMA SBIN PNB HERO HONDA GRASIM ACC HERO HONDA RELCAPITEL

9 160 Table 6.5 s in Formation Period for 29 companies (Jan 2005 ) Company Table 6.6 s in Formation Period for 29 companies (Apr 2005 ) Company HDFC BANK UNITECH ACC SUN PHARMA ITC SIEMENS SIEMENS ITC RELCAPITEL CIPLA SAIL HDFC HDFC ABB ABB ACC GRASIM BHEL PNB HDFC BANK SBIN TATA MOTORS ONGL TATA POWER RELIANCE MARUTI INFOSYS GRASIM TATA POWER WIPRO M & M RELIANCE ICICI BANK GAIL TATA MOTORS HERO HONDA MARUTI ONGL JINDAL RANBAXY UNITECH JINDAL BHEL ICICI BANK HCL HCL WIPRO M & M GAIL SBIN CIPLA PNB HERO HONDA RELCAPITEL SUN PHARMA INFOSYS RANBAXY SAIL

10 161 Table 6.7 s in Formation Period for 29 companies (Jul 2005 ) Company Table 6.8 s in Formation Period for 29 companies (Oct 2005 ) Company ICICI BANK INFOSYS M & M ABB BHEL UNITECH JINDAL WIPRO UNITECH RELIANCE SBIN MARUTI HDFC BANK HDFC TATA MOTORS HERO HONDA ACC CIPLA RELCAPITEL SIEMENS GRASIM M & M PNB SUN PHARMA ABB RELCAPITEL RELIANCE BHEL SAIL ACC SIEMENS HCL HERO HONDA HDFC BANK HDFC SBIN SUN PHARMA PNB CIPLA ITC HCL ONGL MARUTI TATA MOTORS TATA POWER GRASIM GAIL ICICI BANK ITC GAIL WIPRO TATA POWER INFOSYS JINDAL ONGL SAIL RANBAXY RANBAXY

11 162 Table 6.9 s in Formation Period for 29 companies (Jan 2006 ) Company Table 6.10 s in Formation Period for 29 companies (Apr 2006 ) Company UNITECH UNITECH ABB ACC BHEL RELIANCE SIEMENS GRASIM MARUTI RELCAPITEL HCL RANBAXY WIPRO HDFC BANK HDFC BHEL TATA MOTORS ITC ITC MARUTI GAIL ABB M & M INFOSYS RANBAXY SUN PHARMA RELCAPITEL SAIL TATA POWER ONGL ACC TATA MOTORS HDFC BANK M & M GRASIM ICICI BANK SAIL HDFC ONGL JINDAL ICICI BANK WIPRO SUN PHARMA SIEMENS HERO HONDA HERO HONDA CIPLA TATA POWER JINDAL SBIN PNB PNB SBIN GAIL INFOSYS HCL RELIANCE CIPLA

12 163 Table 6.11 s in Formation Period for 29 companies (Jul 2006 ) Company Table 6.12 s in Formation Period for 29 companies (Oct 2006 ) Company PNB ABB ICICI BANK INFOSYS CIPLA SIEMENS GRASIM M & M SBIN UNITECH ACC HCL SUN PHARMA ICICI BANK BHEL SAIL JINDAL HDFC BANK RANBAXY GRASIM HDFC SBIN ONGL RELIANCE HCL JINDAL HDFC BANK WIPRO TATA POWER CIPLA MARUTI BHEL SIEMENS RELCAPITEL WIPRO ITC ABB MARUTI M & M HDFC GAIL PNB TATA MOTORS HERO HONDA RELIANCE ACC ITC GAIL UNITECH TATA POWER HERO HONDA SUN PHARMA SAIL TATA MOTORS RELCAPITEL RANBAXY INFOSYS ONGL

13 164 Table 6.13 s in Formation Period for 29 companies (Jan 2007 ) Company Table 6.14 s in Formation Period for 29 companies (Apr2007 ) Company SAIL JINDAL BHEL HCL TATA POWER SAIL RELIANCE ABB GAIL TATA POWER ICICI BANK ACC SUN PHARMA GRASIM ONGL RELIANCE HDFC SBIN JINDAL PNB RANBAXY UNITECH HCL HDFC HDFC BANK RELCAPITEL UNITECH BHEL SIEMENS SIEMENS WIPRO HDFC BANK RELCAPITEL TATA MOTORS PNB GAIL INFOSYS ONGL ITC WIPRO GRASIM ITC CIPLA M & M ABB RANBAXY MARUTI HERO HONDA M & M ICICI BANK TATA MOTORS MARUTI ACC INFOSYS SBIN SUN PHARMA HERO HONDA CIPLA

14 165 Table 6.15 s in Formation Period for 29 companies (Jul 2007 ) Company Table 6.16 s in Formation Period for 29 companies (Oct 2007 ) Company JINDAL JINDAL SAIL SIEMENS ACC TATA POWER BHEL BHEL GRASIM SAIL RELIANCE ONGL ITC UNITECH TATA POWER RELIANCE GAIL RELCAPITEL MARUTI ABB RELCAPITEL ICICI BANK UNITECH HDFC BANK RANBAXY WIPRO SBIN SBIN HDFC BANK HDFC ABB MARUTI TATA MOTORS SUN PHARMA ONGL HCL INFOSYS GAIL M & M GRASIM HDFC M & M PNB HERO HONDA HERO HONDA TATA MOTORS ICICI BANK PNB WIPRO INFOSYS HCL RANBAXY SIEMENS ITC CIPLA CIPLA SUN PHARMA ACC

15 166 Table 6.17 s in Formation Period for 29 companies (Jan 2008 ) Company HERO HONDA Company Table 6.18 s in Formation Period for 29 companies (Apr 2008 ) Company PNB RELCAPITEL HDFC INFOSYS SUN PHARMA HERO HONDA ICICI BANK SUN PHARMA TATA MOTORS WIPRO HDFC BANK JINDAL SBIN HDFC ITC TATA POWER CIPLA HCL RELIANCE HDFC BANK SIEMENS ICICI BANK INFOSYS UNITECH MARUTI RELIANCE TATA POWER PNB RANBAXY SBIN WIPRO RANBAXY ONGL SAIL BHEL TATA MOTORS UNITECH ITC GRASIM GAIL SAIL M & M M & M ONGL GAIL BHEL HCL CIPLA ACC ABB RELCAPITEL SIEMENS ABB GRASIM JINDAL ACC

16 167 Table 6.19 s in Formation Period for 29 companies (Jul 2008 ) Company Table 6.20 s in Formation Period for 29 companies (Oct 2008 ) Company RELCAPITEL INFOSYS SIEMENS HCL SBIN PNB PNB HERO HONDA HDFC BHEL JINDAL HDFC BHEL MARUTI ONGL WIPRO GAIL ITC HDFC BANK HDFC BANK M & M ACC HERO HONDA M & M ACC ICICI BANK RELIANCE SUN PHARMA TATA POWER CIPLA ICICI BANK SBIN UNITECH TATA POWER CIPLA RELIANCE SAIL ABB ABB SAIL WIPRO RANBAXY GRASIM SIEMENS SUN PHARMA ONGL RANBAXY JINDAL ITC RELCAPITEL MARUTI GRASIM TATA MOTORS GAIL INFOSYS UNITECH HCL TATA MOTORS

17 168 Table 6.21 s in Formation Period for 29 companies (Jan 2009 ) Company Table 6.22 s in Formation Period for 29 companies (Apr 2009 ) Company JINDAL JINDAL GRASIM TATA MOTORS RANBAXY ICICI BANK PNB RELCAPITEL RELIANCE WIPRO ICICI BANK HCL TATA MOTORS M & M SBIN UNITECH HERO HONDA SIEMENS ACC SUN PHARMA TATA POWER SBIN SAIL PNB ITC HDFC GAIL GRASIM CIPLA ABB SIEMENS RELIANCE BHEL HERO HONDA HDFC BANK TATA POWER UNITECH BHEL HDFC SAIL ABB ACC WIPRO CIPLA RELCAPITEL HDFC BANK ONGL INFOSYS INFOSYS ONGL SUN PHARMA GAIL MARUTI MARUTI M & M ITC HCL RANBAXY

18 169 The formation and evaluation process was repeated for the years with formation period of one month.(table 6.1 to 6.22) Based on the results of the formation period the 29 companies were ranked accordingly. Two equal weight portfolios were formed in terms of average reruns -one comprising of top seven stocks called as winner portfolio and other comprising of bottom seven stocks called as loser portfolio. Researcher had arranged the mean returns in descending order. Top seven companies in the formation period data given in (Table 6.1 to 6.22) was the ones which were included in winning portfolio construction.last seven companies in the table constituted the loser portfolio. The study was conducted taking different holding periods and holding periods were 2, 3, 4,5,6,7 and 8 weeks respectively. This was to test the possibility of variation in profit potential of these two investment strategies with time. Below given is a sample of the work done by the researcher for computing momentum returns. In the example given here the holding period is two weeks. returns using both the strategies were compared with the average Index return. returns in two-week holding period were calculated by taking the average returns of 89 different holding periods the details of which is given in Table:6.23

19 170 Table: 6.23 s of Momentum & Contrarian Portfolios compared with index return for 2-Week Holding Period Period Momentum Contrarian Index 03-Feb-04 To 16-Feb Feb-04 To 27-Feb Mar-04 To 16-Mar Mar-04 To 31-Mar May-04 To 14-May May-04 To 31-May Jun-04 To 15-Jun Jun-04 To 30-Jun Aug-04 To 16-Aug Aug-04 To 31-Aug Sep-04 To 15-Sep Sep-04 To 30-Sep Nov-04 To 12-Nov Nov-04 To 30-Nov Dec-04 To 15-Dec Dec-04 To 31-Dec Feb-05 To 14-Feb Feb-05 To 28-Feb Mar-05 To 15-Mar Mar-05 To 31-Mar May-05 To 16-May May-05 To 31-May Jun-05 To 14-Jun Jun-05 To 30-Jun Aug-05 To 16-Aug Aug-05 To 31-Aug Sep-05 To 15-Sep Sep-05 To 30-Sep Nov-05 To 17-Nov Nov-05 To 30-Nov Dec-05 To 15-Dec Dec-05 To 30-Dec

20 01-Feb-06 To 15-Feb Feb-06 To 28-Feb Mar-06 To 16-Mar Mar-06 To 31-Mar May-06 To 16-May May-06 To 31-May Jun-06 To 15-Jun Jun-06 To 30-Jun Aug-06 To 16-Aug Aug-06 To 31-Aug Sep-06 To 14-Sep Sep-06 To 29-Sep Nov-06 To 15-Nov Nov-06 To 30-Nov Dec-06 To 14-Dec Dec-06 To 29-Dec Feb-07 To 14-Feb Feb-07 To 28-Feb Mar-07 To 14-Mar Mar-07 To 30-Mar May-07 To 16-May May-07 To 31-May Jun-07 To 14-Jun Jun-07 To 29-Jun Aug-07 To 16-Aug Aug-07 To 31-Aug Sep-07 To 14-Sep Sep-07 To 28-Sep Nov-07 To 15-Nov Nov-07 To 30-Nov Dec-07 To 14-Dec Dec-07 To 31-Dec Feb-08 To 14-Feb Feb-08 To 29-Feb Mar-08 To 14-Mar Mar-08 To 31-Mar May-08 To 15-May May-08 To 30-May Jun-08 To 13-Jun

21 Jun-08 To 30-Jun Aug-08 To 14-Aug Aug-08 To 29-Aug Sep-08 To 15-Sep Sep-08 To 30-Sep Nov-08 To 14-Nov Nov-08 To 28-Nov Dec-08 To 15-Dec Dec-08 To 31-Dec Feb-09 To 13-Feb Feb-09 To 27-Feb Mar-09 To 17-Mar Mar-09 To 31-Mar May-09 To 15-May May-09 To 29-May Jun-09 To 15-Jun Jun-09 To 30-Jun In two week holding period the researcher had repeated the process of computation of holding periods and evaluation of winning and looser portfolio returns for more than 89 times, the final results of which by taking the mean portfolio returns are put in the table given above (Table: 6.23).The detailed workings (sample) of this study can be found by referring to the Appendix 1, 2, 3 given at the back of this report. The entire data is provided in a soft copy along with this report. The whole process can be explained by taking the example of January 2004 as the formation period and the next two months i.e February and March as the holding periods. During this period the winner portfolio consisted of 7 companies, the results of which are given in the following table (Table 6.24)

22 Table 6.24 Winner Portfolio s from February 2004 to March 2004 Date TATAP MARUTI TATAM GRASIM PNB SBIN M & M Index 03-Feb Feb Feb Feb Feb Feb Feb Feb Feb Feb

23 Table 6.25 Winner Portfolio s from February 2004 to March 2004 Date TATAP MARUTI TATAM GRASIM PNB SBIN M & M Index 17-Feb Feb Feb Feb Feb Feb Feb Feb Feb

24 Table 6.26 Winner Portfolio s from February 2004 to March 2004 Date TATAP MARUTI TATAM GRASIM PNB SBIN M & M Index 01-Mar Mar Mar Mar Mar Mar Mar Mar Mar Mar Mar

25 Table 6.27 Winner Portfolio s from February 2004 to March 2004 Date TATAP MARUTI TATAM GRASIM PNB SBIN M & M Index 17-Mar Mar Mar Mar Mar Mar Mar Mar Mar Mar Mar Source: Computed from data

26 177 It can be studied from the above table that the results of the average returns of the winner portfolio i.e. one which follows momentum strategy is compared with the index returns for the similar period. The same process was also applied for studying the looser portfolio i.e. which follows contrarian strategy, the sample of test results is put in Appendix. 1. Researcher had also conducted the t-test to study the profitability of momentum and contrarian strategies for various formations and holding periods. It was to find out whether momentum and contrarian strategies yield significant positive returns when compared with the bench mark, i.e. index return. The results of the t-tests for various holding periods and formation periods are given in following tables. (Table: 6.28 to 6.34) Table: 6.28 T-test for 2-Week Holding Period Pairs t df P value Momentum & Contrarian Momentum & Index Contrarian & Index Here the p-value is greater than the significance value 0.05; so the results of two-week holding periods draw towards accepting the null hypotheses (H 0 ): 1. Momentum Strategy does not give superior returns to the investor in the Indian Capital Market

27 Contrarian Strategy does not give superior returns to the investor in the Indian Capital Market 3. No significant difference is noticed between Contrarian and Momentum Strategies in making superior returns from Indian Capital Market. The results also reject the possibility of making superior returns by adopting the momentum and contrarian investment strategies for a two-week holding period in the Indian stock market during the study period. Table: 6.29 T-test for 3-Week Holding Period Pairs t df P value Momentum & Contrarian Momentum & Index Contrarian & Index Here the p-value is greater than the significance value 0.05; so the results of three-week holding periods draw towards accepting the null hypotheses (H 0 ): 1. Momentum Strategy does not give superior returns to the investor in the Indian Capital Market 2. Contrarian Strategy does not give superior returns to the investor in the Indian Capital Market 3. No significant difference is noticed between Contrarian and Momentum Strategies in making superior returns from Indian Capital Market.

28 179 The results also reject the possibility of making superior returns by adopting the momentum and contrarian investment strategies for a three-week holding period in the Indian stock market during the study period. Table: 6.30 T-test for 4-Week Holding Period Pairs t df P value Momentum Contrarian & Momentum & Index Contrarian & Index Here the p-value is greater than the significance value 0.05; so the results of four-week holding periods draw towards accepting the null hypotheses (H 0 ): 1. Momentum Strategy does not give superior returns to the investor in the Indian Capital Market 2. Contrarian Strategy does not give superior returns to the investor in the Indian Capital Market 3. No significant difference is noticed between Contrarian and Momentum Strategies in making superior returns from Indian Capital Market. The results also reject the possibility of making superior returns by adopting the momentum and contrarian investment strategies for a four-week holding period in the Indian stock market during the study period.

29 180 Table: 6.31 T-test for 5-Week Holding Period Pairs t df P value Momentum & Contrarian Momentum & Index Contrarian & Index Here the p-value is greater than the significance value 0.05; so the results of five-week holding periods draw towards accepting the null hypotheses (H 0 ): 1. Momentum Strategy does not give superior returns to the investor in the Indian Capital Market 2. Contrarian Strategy does not give superior returns to the investor in the Indian Capital Market 3. No significant difference is noticed between Contrarian and Momentum Strategies in making superior returns from Indian Capital Market. The results also reject the possibility of making superior returns by adopting the momentum and contrarian investment strategies for a five-week holding period in the Indian stock market during the study period. Table: 6.32 T-test for 6-Week Holding Period Pairs t df P value Momentum & Contrarian Momentum & Index Contrarian & Index

30 181 Here the p-value is greater than the significance value 0.05; so the results of six-week holding periods draw towards accepting the null hypotheses (H 0 ): 1. Momentum Strategy does not give superior returns to the investor in the Indian Capital Market 2. Contrarian Strategy does not give superior returns to the investor in the Indian Capital Market 3. No significant difference is noticed between Contrarian and Momentum Strategies in making superior returns from Indian Capital Market. The results also reject the possibility of making superior returns by adopting the momentum and contrarian investment strategies for a six-week holding period in the Indian stock market during the study period. Table: 6.33 T-test for 7-Week Holding Period Pairs t df P value Momentum & Contrarian Momentum & Index Contrarian & Index Here the p-value is greater than the significance value 0.05; so the results of seven-week holding periods draw towards accepting the null hypotheses (H 0 ): 1. Momentum Strategy does not give superior returns to the investor in the Indian Capital Market

31 Contrarian Strategy does not give superior returns to the investor in the Indian Capital Market 3. No significant difference is noticed between Contrarian and Momentum Strategies in making superior returns from Indian Capital Market. The results also reject the possibility of making superior returns by adopting the momentum and contrarian investment strategies for a seven-week holding period in the Indian stock market during the study period. Table: 6.34 T-test for 8-Week Holding Period Pairs t df P value Momentum & Contrarian Momentum & Index Contrarian & Index Here the p-value is greater than the significance value 0.05; so the results of eight-week holding periods draw towards accepting the null hypotheses (H 0 ): 1. Momentum Strategy does not give superior returns to the investor in the Indian Capital Market 2. Contrarian Strategy does not give superior returns to the investor in the Indian Capital Market 3. No significant difference is noticed between Contrarian and Momentum Strategies in making superior returns from Indian Capital Market.

32 183 The results also reject the possibility of making superior returns by adopting the momentum and contrarian investment strategies for an eight -week holding period in the Indian stock market during the study period. The study results reveals that there does not appear any merits to the momentum and contrarian strategies as technical analysis tools in Indian Stock Market. The results are different from many other emerging markets where empirical studies have revealed the possibility of making superior returns using these two strategies. Many academicians and practitioners now hold that stock prices do have some degree of predictability. By using the most rigorous and credible methods, it has been recognised that stock returns can deviate from a random walk, which highlights the potential value in technical analysis or more sophisticated statistical forecasting methods. But such studies can no way reject, efficient market hypothesis. Rather, it should be treated as the base case to which alternatives can be compared. Of course, stock prices contain some predictability. Results of this study also support the weak-form inefficiency of Indian stock-market. So Investors are left with opportunity to make excess return by studying the historical prices, However, this has to be done in a way that it compensates for the transactions costs of trading. 6.3 Momentum and Contrarian strategies during recession period Researcher analysed the efficiency of momentum and contrarian investment strategies during the time period in which Indian markets were severely affected by

33 184 the global financial crisis. The period under study was 2007 October to 2008 April. The results of the study are given below. (Table: 6.35 to 6.41). Table: Week holding period result during recession Period Momentum Contrarian Index 01-Nov-07 To 16-Nov Nov-07 To 30-Nov Dec-07 To 14-Dec Dec-07 To 31-Dec Feb-08 To 15-Feb Feb-08 To 29-Feb Mar-08 To 14-Mar Mar-08 To 31-Mar Table: Week holding period result during recession Period Momentum Contrarian Index 01-Nov-07 To 23-Nov Nov-07 To 14-Dec Feb-08 To 22-Feb Feb-08 To 14-Mar

34 185 Table: Week holding period result during recession Period Momentum Contrarian Index 01-Nov-07 To 30-Nov Dec-07 To 31-Dec Feb-08 To 29-Feb Mar-08 To 31-Mar Table: Week holding period result during recession Period Momentum Contrarian Index 01-Nov-07 To 07-Dec Feb-08 To 07-Mar Table: Week holding period result during recession Period Momentum Contrarian Index 01-Nov-07 To 14-Dec Feb-08 To 14-Mar Table: Week holding period result during recession Period Momentum Contrarian Index 01-Nov-07 To 20-Dec Feb-08 To 19-Mar

35 186 Table: Week holding period result during recession Period Momentum Contrarian Index 01-Nov-07 To 31-Dec Feb-08 To 31-Mar The results reveals that there does not appear any merits to the momentum and contrarian strategies as technical analysis tools in Indian Stock Market even during recession period. So the researcher had to accept the null hypothesis (H 0 ) that momentum and contrarian strategies do not give superior returns over the bench mark. The analysis of momentum and contrarian returns gave evidence that both these strategies cannot be recommended for deciding on making short term investment decisions in Indian Stock Market. So the researcher restrained from selecting the best out of these two technical analysis tools. The strategies under study, i.e. momentum and contrarian strategies unfortunately involved high degree of turnover because the portfolios have to be reconstituted frequently. These strategies also incur substantial transaction costs. So it remains to be seen whether they would be profitable after such costs are fully accounted for. 6.4 Interdependency of Indian Stock Market with other Emerging Markets In the recent years due to globalization, deregulation and integration between countries the interdependency among major world stock markets has

36 187 increased. Equity market of a country very often responds to the equity movements of other markets from all over the world. The Indian Stock market has witnessed a major transformation and structural change from the 10 to 15 years as a result of the ongoing economic and financial sector reforms initiated by the government of India since 1991.Among these measures, lifting of barriers and opening up the doors for foreign investors have promoted integration of Indian markets with other foreign markets, especially other emerging countries. For an international investor who is willing to make portfolio investments in other financial markets would be interested to know if he can achieve desired results by going for such diversification. The interdependency between financial markets had been at the focus of interest of academicians even from 1960s. The majority of studies in that early period reached the conclusion that the degree of interdependency between markets is quite low, since the prime factors in the development of financial markets are of domestic nature. Even in those years some studies that were published supported the existence of limited interdependency between markets. Agmon (1972), establishes some degree of interdependency between the markets of the US, UK, Germany and Japan during 1961 until Integration is the process by which segmented markets become open and unified so that participants enjoy unimpeded access to international trade and finance (Nalini Prava, 2005). Integration of financial markets will encourage flow of funds from markets having lesser returns to the one which offers higher

37 188 returns. It can be assumed that financing and investing decisions by investors across the globe are greatly influenced by the perceived degree of market integration. From an investment angle, if stock markets move together then diversification of portfolio would not generate any return.on the other hand, if two markets are independent, investors can do effective portfolio diversification by investing in these markets. Therefore, a comprehensive study on stock market interdependency will carry a lot of importance for the Indian investors engaged in such portfolio diversification. The present study which is included in this chapter had been conducted by the researcher with the objective of analyzing whether Indian equity market is integrated with that of the rest of the world, especially among different Asian markets. Researcher tested interdependency of Nifty Index movements with Shanghai Composite Index, Hangseng index and Nikkei Index from using simple correlation technique. Shanghai Composite Index is a capitalization-weighted index. The index tracks the daily price performance of all A-shares and B-shares listed on the Shanghai Stock Exchange. The index was developed on December 19, 1990 with a base value of 100.

38 189 Fig. 6.3 Shanghai Composite Index Movement (May, 2009 to March 2010) Source: Bloomberg.com Shanghai Stock Exchange (SSE) was founded on November 26th, 1990 and in operation since December 19th the same year. The exchange is a membership institution directly governed by the China Securities Regulatory Commission (CSRC). By end of December 2007, the exchange had over million investors and 860 listed companies. The total market capitalization of SSE was 3.95 trillion U.S dollars with an average daily turnover of 16.8 billion U.S dollars approximately. In 2007, total capital raised from SSE market was billion U.S dollars.it is Asia's second largest stock exchange by market capitalisation, behind the Tokyo stock exchange. There are two types of stocks being issued in the Shanghai Stock Exchange: A shares and B shares. A shares are priced in the local renminbi yuan currency, while B shares are quoted in U.S.dollars. Initially, trading in A shares were restricted to domestic investors only while B shares were available to both domestic (since 2001) and foreign investors. However, after the new reforms were implemented in December 2002, foreign investors are allowed (with

39 190 limitations) to trade in A shares under the Qualified Foreign Institutional Investor (QFII) program which was officially launched in Currently, there are a total of 79 foreign institutional investors who have been approved to buy and sell A shares under the QFII program. Quotas under the QFII program are currently US$30 billion. There is a plan to eventually merge the two types of shares in the future. The listing requirements of the exchange include: The shares must have been publically issued following the approval of the State Council Securities Management Department. The company s total share capital must not be less than 7.32 million U.S dollars The company must have been in business for more than 3 years and have made profits over the last three consecutive years. In the case of former state-owned enterprises re-established according to the law or founded after implementation of the law and if their issuers are large and medium state owned enterprises, it can be calculated consecutively. Publically offered shares must be more than 25 percent of the company s total share capital. The company must not have been guilty of any major illegal activities or false accounting records in the last three years. Shanghai Composite Index (SSE Index) is the most commonly used indicator to reflect SSE's market performance. The index which was launched on July 15, 1991, reached 2, at the end of 2006, peaked at in late 2007 and fell back to 2500 levels in 2009 because of global financial crisis. Other

40 191 important indexes used in the Shanghai Stock Exchanges include the SSE 50 Index and SSE 180 Index. The Hang Seng Index (HSI) is a free-float capitalization-weighted index of selected companies from the Stock Exchange of Hong Kong. The components of the index are divided into four sub indexes: Commerce and Industry, Finance, Utilities, and Properties. The index was developed with a base level of 100 as on July 31, Fig. 6.4 Hangseng Index movement (May, 2009 to March 2010) Source: Bloomberg.com This index is used to record and monitor daily changes of the largest companies of the Hong Kong stock market and is the main indicator of the overall market performance in Hong Kong. The 45 companies involved in the construction of this index represent about 67 percent of capitalisation of the Hong Kong Stock Exchange. Hang Seng Index is maintained by HSI Services Limited, which is a wholly owned subsidiary of Hang Seng bank, the largest bank registered and

41 192 listed in Hong Kong in terms of market capitalisation. It is responsible for compiling, publishing and managing the Hang Seng Index and a range of other stock indexes, such as Hang Seng China AH Index Series, Hang Seng China Enterprises Index, Hang Seng China H-Financials Index, Hang Seng Composite Index Series, Hang Seng Free float Index Series and Hang Seng Total Index Series. The Hong Kong Stock Exchange is the stock exchange of Hong Kong. The exchange has predominantly been the main exchange for Hong Kong where listed companies shares are traded. It is Asia s third largest stock exchange in terms of market capitalization, behind the Tokyo stock exchange and Shanghai Stock exchange. As of 31 st December 2007, the Hong Kong Stock Exchange had 1,241 listed companies with a combined market capitalisation of $2.7 trillion. The Nikkei-225 Stock is a price-weighted average of 225 toprated Japanese companies listed in the First Section of the Tokyo Stock Exchange. The Nikkei Stock was first published on May 16, It is a price weighted average (the unit is yen) and the components are reviewed once a year. Currently, the Nikkei is the most widely quoted average of Japanese equities, similar to the Dow Jones Industry average. In fact, it was known as the "Nikkei Dow Jones Stock " from 1975 to The Nikkei average hit its all-time high on December 29, 1989, during the peak of the Japanese asset price bubble, when it reached an intra-day high of 38, before closing at 38, Its high for the 21st century stands just above 18,300 points. In January 2010, it was 72.9 percent below its peak.

42 193 Fig. 6.5 Nikkei Index movement (May, 2009 to March 2010) Source: Bloomberg.com The Tokyo stock exchange also called as Tosho or TSE for short, is located in Tokyo, Japan and is the fourth largest stock exchange in the world (as on May, 2009) and the biggest in Asia by aggregate market capitalisation.as of 31 st December 2007, the Tokyo Stock Exchange had 2,414 listed companies with a combined market capitalization of $4.3 trillion. Markets are said to be integrated when shocks arising in one market gets easily transmitted to other interrelated markets. Researcher has made an attempt to examine the empirical relationship of Indian stock market with the top three stock markets in Asia, namely Shanghai Composite Index, Hangseng index and Nikkei Index. Researcher tested interdependency of Nifty Index movements with these three Indexes from using simple correlation technique. 6.5 Results of the test of Interdependency Due to voluminous of data researcher had put only the final result of correlation test in the report. Sample of workings is given in Appendix 4.Detailed workings are given in the soft copy attached along with this report.