Vivek Goswami

TITLE Do Investors See New Product Introductions as Value Adding Activities? An Analysis of Stock Market Reactions to New Product Announcements in India. AUTHORS Jayasankar Ramanathan D.L.Sunder ACKNOWLEDGMENTS The authors wish to thank Mr. Vivek Goswami (academic associate) for providing assistance towards this study. ABSTRACT With increasing acceptance of innovations as a path for developing competitive advantage, firms are ramping up their rate of new product introductions. These new products are expected to generate additional revenues for the company and have the potential for changing the expected cash flows in the future. As such new product announcements must be received favourably by the stock markets with positive and significant average abnormal returns on the day of announcement. However studies on the stock market reactions to new product announcements are equivocal with some studies reporting positive results and others finding no such reactions. This study is an attempt to find how the markets in emerging markets respond to new product introductions. The authors find that the new product introductions do not create significant average abnormal returns either on day zero or on the subsequent two days suggesting that these announcements may not be considered significant by the stock markets. I. INTRODUCTION The latest buzzword today in business is Innovation. We see leaders across the world pitching for innovation and urging their governments to introduce polices that promote innovation (Kim Carr 2008; UNIDO, 2003). This focus on innovation is good because our society benefits from innovation and it would be difficult to imagine a world without the innovations we take for granted (like the telephone and electric appliances). Senior executives from the industry have also joined the bandwagon supporting innovation. In an era of globalization, where trade barriers are down and competition is fierce, innovation has become a core driver for growth, performance, and valuation (Barsh et al, 2008). According to the surveyconducted by them, 70% of the senior executives opine that innovation would be one of the top three drivers for growth but also expressed concern that stimulating innovation was not easy. The article suggests that developing a culture of innovation is critical to becoming an innovative organization. The need for an innovative culture is true for the society as it is for an organization. Unless society values innovation and encourages innovators, progress would be slow. The need to build an innovative culture resonates with the call for innovative India made by Prime ministers Manmohan Singh and Narendra Modi(Bute, 2013; Live Mint, 2015). This line of thought also finds support in the investment theory of creativity (Sternberg, 2006). According to this theory creative endeavours require commitment of time & resources and would be pursued by individuals only if the environment appreciates such efforts. Take for example the development of a new drug molecule by a Pharmaceutical company. It is estimated that it takes approximately US$800 million and 10 years to bring a new product to the market (DiMasi et al, 2003). Given the risks associated with new product development, no firm would make such investments if the environment is not innovation friendly. In the absence of adequate IntellectualPropertyRights protection, firms would be averse to making such investments. In addition to these regulatory features, it is important that the financial community views innovation positively so that businesspersonsare motivated to invest in innovative activities. The stock price of the company is an important barometer for most business leaders. According to professors Itey Goldstein and Alex Adams of Wharton (Knowledge @Wharton, 2012), market analysts have long viewed the rise and fall of a company’s share price as a gauge of the market’s expectations about the firm’s future cash flows. They claim that the price can reflect approval or disapproval of management decisions, and it can therefore affect what decisions are made. In light of the above, business leaders would be motivated to invest in innovative efforts if they see stock market reacting positively to new product announcements. This study tries to measure the stock market reactions to new product launches in India. The paper is organized as follows. Section II contains a review of literature on the stock market reactions to new product announcements. Section III discusses literature gap and mentions the research questions for this study. Section IV specifies the hypotheses. Section V discusses the methodology. Section VI reports results. Section VII includes discussion of results. Section VIII mentions limitations of this study. Section IX proposes directions for future research. II. LITERATURE REVIEW Published studies on the relation between new product introductions and stock market reactions were searched for and 12 studies were found. These are reviewed chronologically as follows. Eddy and Saunders (1980) hypothesized that new product announcements have a discernible effect on stock returns but did not find support for this. This study was based in the US context. Chaney et al (1991) studied abnormal returns of new product announcements in the US context. They found support for their hypotheses that firms that innovate will receive market premium over similar firms that do not innovate, that smaller firms should have larger market value increases from any single innovation, that the value of innovation should be higher for firms in more technologically based industries, that original new products should receive a large market value than updates of existing products, and that factors that increase the availability of information about the product being introduced or the firm in general will be negatively related to the magnitude of the impact seen at the time of a formal announcement. Chaney and Devinney (1992) studied the relation between new product innovations and stock price performance. They found that multiple product announcements have a significantly stronger impact on excess stock returns than single product announcements, that original product announcements fare better than product update announcements, and that higher interest rates should imply a smaller return to the investment than lower rates. This study was in the US context. Lane and Jacobson (1995) found that the stock market response to brand extension announcements is nonmontonically related to brand attitude and familiarity. This study was in the US context. Kelm et al (1995) studied shareholder value creation during R&D Innovation and Commercialization stages in the US context. They found support for their hypothesis that the stage of development during which an R&D project announcement is made -innovation or commercialization-moderates the relationship between the announcement's impact on shareholder wealth and technology-and market-related variables. Lee et al (2000) found that the faster a firm introduces a new product, the higher the abnormal returns and that first and second movers will, on the average, report higher abnormal returns than late movers. They reported partial support for their hypothesis that at the time of new product imitations, the abnormal returns will be negative for the first movers. They further found that shareholder wealth effects are greater when there is higher growth in industry sales. This study was based in the US context. Chen et al (2002) examined some determinants of the wealth effect of new product introductions in the US context. They found that the abnormal returns are higher when the new product introductions are strategic substitutes than when they are strategic complements. They found that the abnormal returns are significantly positively related to the announcing firm’s investment opportunities, R&D intensity, and announcement frequency and are significantly negatively related to the announcing firm’s free cash flow, size, and interest rates. Jones and Danbolt (2005) studied stock market reaction to new product announcements in the UK context. The found that the level of abnormal returns will be negatively related to company size, that companies with high price-earnings ratio will experience more positive stock market reactions to product or market diversification investment announcements than other firms, that companies with low dividend yields ratio will experience more positive stock market reactions to product or market diversification investment announcements than other firms, and that new product announcements were found to result in significantly higher abnormal returns compared to the entry into new markets. Lee and Chen (2009) studied the impact of new product introductions on stock price with especial attention to the role of firm resources and size. They found that new product announcements are related positively to shareholder value, that there is a U-shape nonlinear effect of R&D resource intensity and the relationship between new product introduction and shareholder value, that committed marketing resources are positively related to the shareholder value of new products announcements such that the higher the marketing resource intensity, the stronger its effect on shareholder value, and that firm size is negatively related to shareholder value, such that the larger the firm, the lower is its shareholder value of new product announcements. In addition, they reported a significant positive relation between firm past performance and abnormal returns and a significant negative relationship between industry concentration and abnormal returns. This study was in the US context. Srinivasan et al (2009) found that new-to-the-company innovations increase stock market returns, and stock market returns are U shaped in the level of new-to-the-company innovation, that pioneering (new-to-the-market) innovations have a greater stock return impact than no-pioneering innovations, that advertising support for new-to-the-company innovations increases the stock market returns of these innovations, that advertising support for pioneering innovations increases the stock market returns of these innovations, that advertising support benefits the stock market returns more for pioneering innovations than for new-to-the-company innovations, that promotional support for new-to-the-company innovations decreases the stock market returns of these innovations, and that perceived quality of new product introductions increases stock returns. In addition, they found that new product introductions have a larger stock return impact in large than small categories and that category growth rate has a significant, positive influence on stock returns from new product introductions. This study was in the US context. Chang et al (2010) studied family control and stock market reactions to innovation announcements in the Taiwan context. They found that family control is negatively associated with stock market reactions to innovation announcements, that the divergence of cash flow rights and voting rights is negatively associated with stock market reactions to innovation announcements, and that institutional ownership can positively moderate the relation between family control and stock market reactions to innovation announcements. Lin and Chang (2012) studied corporate governance and stock market reaction to new product announcements in the US context. They found that board size is negatively associated with stock market reaction to new product introductions, that board independence is positively associated with stock market reaction to new product introductions, that audit committee independence is positively associated with stock market reaction to new product introductions, that CEO equity-based pay is positively associated with stock market reaction to new product introductions, that analyst following is positively associated with stock market reaction to new product introductions, and that G-index scores are negatively associated with stock market reaction to new product introductions (where G-index is proxy for the shareholder rights of corporate governance and higher G-index score indicates lower shareholder rights and greater management power). They also reported a negative significant relation between firm size and stock market reaction. A reading of the above research studies identifies a few gaps and raises a number of questions. III. LITERATURE GAP AND RESEARCH QUESTIONS We identify two gaps from our review of literature which we pursue in this study. First, studies on stock market reactions to new product announcements from emerging economies are rare. Second, it is not clear whether new product introductions are received favorably by the stock markets, as prior research is ambiguouson this. The literature review also indicates that the stock market reactions to new product announcements may be influenced by other factors, which suggests that the reactions may differ depending on the industrial sector in which thenew products are announced. We pursue the following research questions in this study. RQ1: What is the relation between new product announcements and stock market reactions in India? RQ2: Do the stock market reactions to new product announcements in India differ depending on the sector? IV. HYPOTHESES Eddy and Saunders (1980) suggest that firms introduce new products if they perceive positive net present value. This means that the value of the firm would increase due to the introduction of the new product and therefore the stock market should react positively to the new product announcements. Hypothesis 1: New product announcements yield positive average abnormal returns (AAR) on the day of the announcement. While the stock markets react to news about the firms’ activities that have potential to change its cash flows, the reaction can be delayed due to the timing of the announcement and also because diffusionof the news might take time. Therefore we posit that the positive effects of new product introductions will persist over a few days. Hypothesis 2: The cumulative average abnormal returns (CAAR) for the window 0 to +2 is positive. Prior studies suggest that factors such as technology (Chaney et al, 1991), marketing resources (Lee and Chen, 2009), R&D resources (Lee and Chen, 2009), analyst following (Lin and Chang, 2012), advertising support (Srinivasan et al 2009) influence stock market reactions to new product announcements. As many of these are different for different sectors like FMCG and Food, we posit that there will be differences in market returns to new product announcement of these sectors. Hypothesis 3: There is difference in the average abnormal returns (AAR) to new product announcements of FMCG companies in comparison to Food companies on the day of the announcement. Hypothesis 4: There is difference in the cumulative average abnormal returns (CAAR) during the window 0 to +2 between the FMCG and Food sector. V. METHODOLOGY Geographic context On 3rd January 2010, the then Prime Minister of India Dr. Manmohan Singh declared- as a "Decade of Innovations" with the objective of developing an ecosystem that would support innovations (Bute, 2012) . Exactly six years later while inaugurating the 103rd session of the Science Congress Shri. Narendara Modi, the Prime Minister of India emphasized innovation was importance for the country’s future (The Hindu, 2016). This was further reiterated in his speech on January 16, 2016 while speaking onthe Start-up India event. It appears that with the change in the IPR regime in 2005 (Newyork Times, 2005)there is an overall positive perception in India on Innovation and this should reflect in thestock market behaviour. As such it was decided to study the announcements effects of new products in India. The 2015 Global Innovation Index (GII) India ranks 81 (in the list of 141 countries) which is five places below its 2014 ranking. However, India is one of the eight economies that are being signalled as innovation achievers outperforming their peers on overall score (Business Standard, sept 18, 2015) indicating an environment that may now be more supportive of innovation than earlier. In a resource constrained environment like India, the support of the investor community would be crucial to spur firms to invest in innovations and if the environment is now positively inclined towards innovation, we expect the stock markets to react positively to new product introductions. Positive average abnormal returns that are significant on the announcement day would mean that the investors see value in a firm’s innovative activities. This in turn would encourage firms to increase their engagement in innovative activities. Data description Companies listed under Food Products and FMCG in the ‘Dun and Bradstreet India’s Top 500 Companies 2015’1 are selected and new products announced in India during the period January 1, 2004 till July 31, 2015, by these companies are considered2. Information regarding announcement date is obtained by scanning leading financial dailies namely, Business Standard, The Economic Times and The Financial Express and also by searching through Google for the above stated period. Data analysis Event study methodology is used to assess the influence of new product announcements on the shareholders’ wealth. Event studies are based on the hypothesis that the financial markets are efficient. It assumes that a security’s price reflects all publicly available information at that point in time. As new firm specific relevant information arrives, the market reacts and the stock price changes to reflect this information. A new product launch announcement reflects new and firm specific information that changes the long term prospects of the firm and as such the stock prices would change to reflect this new information. The event is the announcement of the new product launch and the day of the announcement is taken as day zero. The abnormal returns on day zero is calculated for the stock using the change in stock price at the closing of day zero compared to the previous day. As the impact of the announcement can persist over a number of days, the cumulative abnormal returns for a certain number of days post the announcement day is calculated. Previous studies have computed the abnormal returns for the stock for a number of days prior to the announcement day as the run in of the stock prices have been noticed due to information leakage etc. The abnormal returns are computed for the period -15 to +15 days to better understand how the stocks react to the announcement. Details of how abnormal returns, average abnormal returns, and cumulative abnormal returns are computed are furnished under Appendix. One sample “t” tests are used to check if the AAR and CAAR are significant on different event windows and independent sample “t” tests are used to test the hypotheses. VI.RESULTS Table 1: Count of Announcements Sector New Product announcements Food 29 FMCG 20 Combined 49 Table 1 shows that a total of 49 new products launches were identified for the study from the FMCG and Food sector. It is also seen that the number of new product launches is higher in the food sector compared to the FMCG sector. Table 2: AAR for different days DAY AAR t p value DAY AAR t p value - 1 -0.0036 - - 2 -0.0029 - -13 -0.0012 - 3 -0.0023 - - - - 5 -0.0020 - -10 -0.0014 - 6 -0.0017 - - 7 -0.0091 -*** - - - - -6 -0.0026 - 10 -0.0019 - -5 -0.0100 -*** - -4 -0.0043 - - - 13 -0.0488 - -2 -0.0078 -*** - -1 -0.0007 - - -0.0005 - * p<0.10; **p<0.05; ***p<0.01 Table 2 shows the average abnormal return for the event window -15 to +15 days for all the new product announcements. It is seen that the average abnormal returns on day zero is – 0.05% and not significant. It is seen that 16 of the total 30 average abnormal returns for the event window -15 to +15 days are negative. Table 3: CAAR for different windows WINDOW CAAR t p value (-15 to +15) -0.0681 - (-14 to +14) -0.0739 - (-13 to +13) -0.0790 -* (-12 to +12) -0.0290 -** (-11 to +11) -0.0350 -*** (-10 to +10) -0.0389 -** (-9 to +9) -0.0355 -*** (-8 to +8) -0.0367 -*** (-7 to +7) -0.0397 -*** (-6 to +6) -0.0350 -*** (-5 to +5) -0.0306 -*** (-4 to +4) -0.0187 -** (-3 to +3) -0.0154 -** (-2 to +2) -0.0155 -* (-1 to +1) -0.0048 - -0.0005 - (-15 to 0) -0.0117 - (-14 to 0) -0.0138 - (-13 to 0) -0.0166 - (-12 to 0) -0.0153 - (-11 to 0) -0.0156 - (-10 to 0) -0.0190 -* (-9 to 0) -0.0176 -* (-8 to 0) -0.0185 -* (-7 to 0) -0.0191 -** (-6 to 0) -0.0235 -*** (-5 to 0) -0.0209 -** (-4 to 0) -0.0109 - (-3 to 0) -0.0066 - (-2 to 0) -0.0090 - (-1 to 0) -0.0011 - (0 to +1) -0.0041 - (0 to +2) -0.0070 - (0 to +3) -0.0092 -* (0 to +4) -0.0083 -* (0 to +5) -0.0102 -* (0 to +6) -0.0120 -* (0 to +7) -0.0211 -** (0 to +8) -0.0186 -** (0 to +9) -0.0184 -* (0 to +10) -0.0203 -* (0 to +11) -0.0200 -** (0 to +12) -0.0141 - (0 to +13) -0.0629 - (0 to +14) -0.0606 - (0 to +15) -0.0568 - * p<0.10; **p<0.05; ***p<0.01 Table 3 shows the CAAR for new product introductions for various event windows from -15 day to +15 day. The CAAR is negative for all the event windows and is significant on many of these windows Table 4: AAR for different days within FMCG sector DAY AAR t p value DAY AAR t p value - 1 -0.0021 - -14 -0.0007 - 2 -0.0019 - - 3 -0.0013 - - - -11 -0.0006 - - - - - 7 -0.0076 - -8 -0.0009 - 8 -0.0010 - -7 -0.0015 - - -6 -0.0071 - 10 -0.0032 - -5 -0.0066 - 11 -0.0025 - - - - 13 -0.0020 - -2 -0.0097 - - -1 -0.0015 - - -0.0025 - * p<0.10; **p<0.05; ***p<0.01 Table 4 shows the average abnormal returns for FMCG on different days. It is seen that the AAR for day zero is – 0.25% and not significant. Seventeen of the 31 days see negative AAR. Table 5: AAR for different days within Food sector DAY AAR t p value DAY AAR t p value - 1 -0.0060 - - 2 -0.0044 - -13 -0.0047 - 3 -0.0037 - -12 -0.0002 - - - 5 -0.0109 - -10 -0.0072 - 6 -0.0102 - - 7 -0.0115 - - - - 9 -0.0059 - - - -5 -0.0152 - - -4 -0.0159 - - -3 -0.0025 - 13 -0.1216 - -2 -0.0049 - - - - * p<0.10; **p<0.05; ***p<0.01 Table 5 shows the AARs for Food industry. It is seen that the AAR for day zero is 0.27% and not significant. It is seen that 15 of the 31 days show negative AARs. Table 6: T test for difference between AAR for Food and FMCG sector on different days AAR DAY Food FMCG t p value Mean SD N1 Mean SD N2 -15 .0007 - .0029 - -.296 .770 -14 .0081 - -.0007 - .224 -13 -.0047 - .0010 - -.817 .420 -12 -.0002 - .0005 - -.152 .880 -11 .0098 - -.0006 - .874 .393 -10 -.0072 - .0023 - -1.119 .274 -9 .0015 - .0005 - .196 .845 -8 .0028 - -.0009 - .585 .563 -7 .0136 - -.0015 - .016** -6 .0042 - -.0071 - -5 -.0152 - -.0066 - -1.334 .190 -4 -.0159 - .0032 - -2.999 .005*** -3 -.0025 - .0055 - -.838 .411 -2 -.0049 - -.0097 - .738 .468 -1 .0006 - -.0015 - .304 .763 0 .0027 - -.0025 - .718 .480 1 -.0060 - -.0021 - -.663 .511 2 -.0044 - -.0019 - -.301 .765 3 -.0037 - -.0013 - -.427 .672 4 .0009 - .0010 - -.001 .999 5 -.0109 - .0038 - -2.916 .006*** 6 -.0102 - .0037 - -2.387 .022** 7 -.0115 - -.0076 - -.613 .543 8 .0079 - -.0010 - .228 9 -.0059 - .0041 - -1.469 .149 10 .0000 - -.0032 - .656 .517 11 .0047 - -.0025 - .937 .355 12 .0047 - .0066 - -.200 .843 13 -.1216 - -.0020 - -1.354 .183 14 .0034 - .0017 - .283 .779 15 .0027 - .0045 - -.236 .815 * p<0.10; **p<0.05; ***p<0.01 Table 6 shows the results of at-test for the difference in the AARs of FMCG and Food sector. Table 7: CAAR for FMCG sector announcements for different event windows WINDOW CAAR t p value (-15 to +15) -0.0113 - (-14 to +14) -0.0187 - (-13 to +13) -0.0197 - (-12 to +12) -0.0187 - (-11 to +11) -0.0258 -* (-10 to +10) -0.0227 -* (-9 to +9) -0.0219 -* (-8 to +8) -0.0266 -** (-7 to +7) -0.0246 -** (-6 to +6) -0.0156 - (-5 to +5) -0.0122 - (-4 to +4) -0.0094 - (-3 to +3) -0.0136 -* (-2 to +2) -0.0177 -*** (-1 to +1) -0.0061 - -0.0025 - (-15 to 0) -0.0150 - (-14 to 0) -0.0180 - (-13 to 0) -0.0173 - (-12 to 0) -0.0183 - (-11 to 0) -0.0188 - (-10 to 0) -0.0182 -* (-9 to 0) -0.0206 -** (-8 to 0) -0.0211 -** (-7 to 0) -0.0202 -** (-6 to 0) -0.0187 -** (-5 to 0) -0.0117 - (-4 to 0) -0.0051 - (-3 to 0) -0.0083 - (-2 to 0) -0.0137 -** (-1 to 0) -0.0040 - (0 to +1) -0.0046 - (0 to +2) -0.0065 - (0 to +3) -0.0078 -* (0 to +4) -0.0069 - (0 to +5) -0.0031 - (0 to - (0 to +7) -0.0069 - (0 to +8) -0.0080 - (0 to +9) -0.0038 - (0 to +10) -0.0070 - (0 to +11) -0.0095 - (0 to +12) -0.0029 - (0 to +13) -0.0049 - (0 to +14) -0.0032 - (0 to - * p<0.10; **p<0.05; ***p<0.01 Table 7 shows the CAAR for FMCG sector for the event window -15 to +15 days. It is seen that for the window 0 to +2, it is –0.65% and statistically significant. Looking at the CAAR from -2to +2 days it is also seen to be negative. Table 8: CAAR for Food sector announcements for different event windows WINDOW CAAR t p value (-15 to +15) -0.1564 - (-14 to +14) -0.1598 - (-13 to +13) -0.1713 - (-12 to +12) -0.0450 -* (-11 to +11) -0.0494 -** (-10 to +10) -0.0639 - (-9 to +9) -0.0567 -* (-8 to +8) -0.0524 -* (-7 to +7) -0.0631 -** (-6 to +6) -0.0652 -*** (-5 to +5) -0.0593 -** (-4 to +4) -0.0331 -* (-3 to +3) -0.0182 - (-2 to +2) -0.0120 - (-1 to +1) -0.0026 - (-15 to 0) -0.0066 - (-14 to 0) -0.0073 - (-13 to 0) -0.0154 - (-12 to 0) -0.0107 - (-11 to 0) -0.0105 - (-10 to 0) -0.0202 - (-9 to 0) -0.0130 - (-8 to 0) -0.0145 - (-7 to 0) -0.0174 - (-6 to 0) -0.0309 - (-5 to 0) -0.0352 -** (-4 to 0) -0.0199 - (-3 to 0) -0.0040 - (-2 to 0) -0.0016 - (-1 to- (0 to +1) -0.0033 - (0 to +2) -0.0077 - (0 to +3) -0.0114 - (0 to +4) -0.0105 - (0 to +5) -0.0214 -** (0 to +6) -0.0316 -*** (0 to +7) -0.0430 -** (0 to +8) -0.0351 -** (0 to +9) -0.0410 -** (0 to +10) -0.0410 -** (0 to +11) -0.0362 -** (0 to +12) -0.0316 -** (0 to +13) -0.1532 - (0 to +14) -0.1498 - (0 to +15) -0.1471 - * p<0.10; **p<0.05; ***p<0.01 Table 8 shows that the CAAR for Food sector for the different event windows. For the event window0 to +2. It is seen that the CAAR is – 0.77% but not significant. Looking at the CAAR for windows from -2to +2 it is seen that it is negative but not significant. Table 9: T test for difference in CAAR between Food and FMCG sector Days Food FMCG t p value Mean SD N1 Mean SD N2 (-15 to +15) -.1564 - -.0113 - -1.253 .226 (-14 to +14) -.1598 - -.0187 - -1.229 .235 (-13 to +13) -.1713 - -.0197 - -1.334 .199 (-12 to +12) -.0450 - -.0187 - -.871 .391 (-11 to +11) -.0494 - -.0258 - -.853 .400 (-10 to +10) -.0639 - -.0227 - -1.234 .229 (-9 to +9) -.0567 - -.0219 - -1.297 .201 (-8 to +8) -.0524 - -.0266 - -1.025 .311 (-7 to +7) -.0631 - -.0246 - -1.622 .112 (-6 to +6) -.0652 - -.0156 - -2.304 .026** (-5 to +5) -.0593 - -.0122 - -2.279 .028** (-4 to +4) -.0331 - -.0094 - -1.362 .180 (-3 to +3) -.0182 - -.0136 - -.266 .792 (-2 to +2) -.0120 - -.0177 - .361 .720 (-1 to +1) -.0026 - -.0061 - .286 .777 0 .0027 - -.0025 - .718 .480 (-15 to 0) -.0066 - -.0150 - .359 .722 (-14 to 0) -.0073 - -.0180 - .455 .653 (-13 to 0) -.0154 - -.0173 - .091 .928 (-12 to 0) -.0107 - -.0183 - .350 .728 (-11 to 0) -.0105 - -.0188 - .408 .685 (-10 to 0) -.0202 - -.0182 - -.093 .927 (-9 to 0) -.0130 - -.0206 - .359 .722 (-8 to 0) -.0145 - -.0211 - .310 .758 (-7 to 0) -.0174 - -.0202 - .151 .880 (-6 to 0) -.0309 - -.0187 - -.684 .498 (-5 to 0) -.0352 - -.0117 - -1.372 .181 (-4 to 0) -.0199 - -.0051 - -.891 .381 (-3 to 0) -.0040 - -.0083 - .278 .783 (-2 to 0) -.0016 - -.0137 - .900 .377 (-1 to 0) .0034 - -.0040 - .739 .467 (0 to +1) -.0033 - -.0046 - .140 .889 (0 to +2) -.0077 - -.0065 - -.106 .917 (0 to +3) -.0114 - -.0078 - -.329 .744 (0 to +4) -.0105 - -.0069 - -.376 .709 (0 to +5) -.0214 - -.0031 - -1.569 .125 (0 to +6) -.0316 - .0007 - -2.595 .014** (0 to +7) -.0430 - -.0069 - -2.373 .022** (0 to +8) -.0351 - -.0080 - -1.497 .144 (0 to +9) -.0410 - -.0038 - -1.738 .092* (0 to +10) -.0410 - -.0070 - -1.540 .134 (0 to +11) -.0362 - -.0095 - -1.376 .177 (0 to +12) -.0316 - -.0029 - -1.396 .170 (0 to +13) -.1532 - -.0049 - -1.334 .199 (0 to +14) -.1498 - -.0032 - -1.306 .208 (0 to +15) -.1471 - .0012 - -1.313 .206 * p<0.10; **p<0.05; ***p<0.01 Table 9 shows the t-test results for the difference between CAARs for FMCG and Food sector. VII. DISCUSSION The average abnormal returns for new product introductions in India is negative on day zero and not statistically significant (See Table 2). As such hypothesis 1 is not supported. This is inline with the findings of Eddy and Saunders (1980)but contrary to many of the other research findings (Chaney et al,1991; Lee and Chen, 2009). It appears that markets do not consider new product announcements important enough to react. Another explanation for the stock markets not reacting to the new product introductions could be due to the fact that companies are expected to regularly introduce new products and this has already been factored into the stock prices of the companies. The CAAR for the windows 0 to +2 is negative and contrary to expectations (See Table 3). As such hypothesis 2 is not supported. The negative CAAR over the different event windowsfrom -15 to +15 indicates that new product introductions are made during times when the stock is under pressure. If this is true, then companies are probably introducing new products reactively. It is possible that market would react positively and significantly when the new product introduction is a new to the world product and not just a new to the company product. The AAR on day zero and CAARin the event window (0 to +2)for FMCG and Food sectors are different but the difference is not statistically significant (See Table 6 and Table 9 respectively). As such hypotheses 3 and 4 are not supported. This could be due to the low sample size. VIII. LIMITATIONS The sample of new product announcements used in this study is restrictive. This is a limitation. The sample was also limited by the use of the Dunn and Bradstreet listing.That this study is based in India is another limitation in terms of the generalizability of the findings across other nations. IX. FUTURE RESEARCH AVENUES In this study, stock market reactions to new product announcements was examined. The results show that the AAR on day zero is not significant indicating that the markets do not see new product introductions as important. This could be due to the fact that many new product introductions are the result of incremental innovation. Classifying the products on new to the company and new to the world might result in a different finding. According to Srinivasan et al (2009)the level of advertising to promote the new products influences the stock market reactions. Similarly, it is possible that the branding strategy could influence the new product announcement reactions. A new product can be given a new brand name or an established brand name (Tauber, 1981).When an established brand name is used for a new product, it is referred to as brand extension (Loken and John, 1993). It would be interesting to look at whether the stock market reactions to new product announcements differ between new brands and brand extensions. Brand extensions can be line extensions or category extensions (Farquhar, 1989). Future research may examine if the stock market reactions to new product announcements, which are brand extensions, differ between line extensions and category extensions. Researchers have observed differences in the role of brand strategy across sectors such as FMCG and Pharmceuticals (Ladha, 2007; Moss, 2007; Schuiling and Moss, 2007). Hence, another question worth considering would be whether the stock market reactions to new product announcements, which are brand extensions, differ between FMCG sector and Pharmaceutical sector? REFERENCES Bartholdy, J., Olson, D., &Peare, P. (2007). Conducting event studies on a small stock exchange. The European Journal of Finance, 13(3), 227-252. Brown, S. J., & Warner, J. B. (1985). Using daily stock returns: The case of event studies. Journal of financial economics, 14(1), 3-31. Business Standard ( September 18, 2015) India ranks 141 among 141 countries on the Global Innovation Index. http://www.business-standard.com/article/economy-policy/india-ranks-81-among-141-countries-on-the-global-innovation-index-_1.html Bute S (March 7, 2013) , Innovation: The New Mantra for Science and Technology Policies in India, Pakistan and China. Institute for Defence Studies and Analysis. http://www.idsa.in/backgrounder/ScienceandTechnologyPoliciesinIndiaPakistanandChina Chaney, P. K., &Devinney, T. M. (1992). New product innovations and stock price performance. Journal of Business Finance & Accounting, 19(5), 677-695. Chaney, P. K., Devinney, T. M., &Winer, R. S. (1991). The impact of new product introductions on the market value of firms. Journal of Business, 573-610. Chang, S. C., Wu, W. Y., & Wong, Y. J. (2010). Family control and stock market reactions to innovation announcements. British Journal of Management, 21(1), 152-170. Chen, S. S., Ho, K. W., Ik, K. H., & Lee, C. F. (2002). How does strategic competition affect firm values? A study of new product announcements.Financial Management, 67-84. DiMasi, Hansen, Grabowski (2003) The price of innovation: new estimates of drug development costs, Journal of Health Economics; Vol 22, pp. 151-185. Eddy, A. R., & Saunders, G. B. (1980). New product announcements and stock prices. Decision sciences, 11(1), 90-97. Farquhar, P. H. (1989). Managing brand equity. Marketing research, 1(3), 24-33. Joanna Barsh, Marla M. Capozzi, and Jonathan Davidson (2008) Leadership and Innovation. McKinsey Quarterly, January. Jones, E. A., &Danbolt, J. (2005). Empirical evidence on the determinants of the stock market reaction to product and market diversification announcements. Applied Financial Economics, 15(9), 623-629. Kelm, K. M., Narayanan, V. K., & Pinches, G. E. (1995). Shareholder value creation during R&D innovation and commercialization stages. Academy of Management Journal, 38(3), 770-786. Kim Carr (2008) Government announces review of national innovation system. Australian Government, Department of Innovation, Industry, Science and Research, . Knowledge @ Wharton (Oct,. 24, 2012). The feedback effect: How the financial markets affect decisions in the ‘Real Economy’. Ladha, Z. (2007). Marketing strategy: are consumers really influenced by brands when purchasing pharmaceutical products?. Journal of Medical Marketing: Device, Diagnostic and Pharmaceutical Marketing, 7(2), 146-151. Lane, V., & Jacobson, R. (1995). Stock market reactions to brand extension announcements: The effects of brand attitude and familiarity. The Journal of Marketing, 63-77. Lee, H., Smith, K. G., Grimm, C. M., &Schomburg, A. (2000). Timing, order and durability of new product advantages with imitation. Strategic Management Journal, 21(1), 23-30. Lee, R. P., & Chen, Q. (2009). The Immediate Impact of New Product Introductions on Stock Price: The Role of Firm Resources and Size*. Journal of Product Innovation Management, 26(1), 97-107. Lin, W. C., & Chang, S. C. (2012). Corporate governance and the stock market reaction to new product announcements. Review of Quantitative Finance and Accounting, 39(2), 273-291. Live Mint (July, 7, 2015) Innovation is India’s key growth driver, says Narendra Modi. http://www.livemint.com/Politics/BFlt7k47yZzI4bIdcMVGEM/InnovationisIndiaskeygrowthdriversaysNarendraModi.Html Loken, B., & John, D. R. (1993). Diluting brand beliefs: when do brand extensions have a negative impact?. The Journal of Marketing, 71-84. MacKinlay, A. C. (1997). Event studies in economics and finance. Journal of economic literature, 35(1), 13-39. Moss, G. D. (2007). What can the pharmaceutical world learn from consumer branding practice?. Journal of Medical Marketing: Device, Diagnostic and Pharmaceutical Marketing, 7(4), 315-320. National Knowledge Commission, Innovation in India 2007. See http://www.knowledgecommission.gov.in/downloads/documents/NKC_Innovation.pdf SchuilingI., & Moss, G. (2004). How different are branding strategies in the pharmaceutical industry and the fast-moving consumer goods sector?. The Journal of Brand Management, 11(5), 366-380. Srinivasan, S., Pauwels, K., Silva-Risso, J., &Hanssens, D. M. (2009). Product innovations, advertising, and stock returns. Journal of Marketing,73(1), 24-43. Sternberg R J (2006). The nature of creativity. Creativity Research journal, Vol. 18 (1). Tauber, E. M. (1981). Brand franchise extension: new product benefits from existing brand names. Business Horizons, 24(2), 36-41. The Hindu (Jan 3, 2016) Text of PM’s inaugural address at 103rd session of Indian Science Congresshttp://www.thehindu.com/news/resources/text-of-pms-inaugural-address-at-103rd-session-of-indian-science-congress/article-.ece UNIDO Policy Papers (2003), Strategies for Regional Innovation Systems: Learning Transfer and Applications, UNIDO. APPENDIX: Computing the Abnormal Returns, Average Abnormal Returns, and Cumulative Abnormal Returns Average Abnormal Return The abnormal return on the stock for day t is computed as follows, (Abnormal return) it = (Actual Return) it – (Expected Return) it Where “i” is the ithannouncement and t is day “t”. As the calculation of the abnormal return requires estimation of the expected return on the stock based on the market indices, it is done by using the market model (see Brown and Warner, 1985) which assumes that in the absence of any confounding event that affects the stock price of the particular stock, a linear relationship exists between the return of any security and the return of the market portfolio as given below, 𝑅𝑖𝑡 =∝𝑖+ 𝛽𝑖𝑅𝑚𝑡 + 𝜀𝑖𝑡 where Rit is the return of security i on time t, αi is the intercept, Rmtis the return on the market portfolio at time t and βi is the slope coefficient, indicating how sensitive the performance of the individual share is relative to the market portfolio. The literature suggests that a broad based stock index should be used to estimate the return of the market portfolio (MacKinlay, 1997; Bartholdy et al, 2007). In this paper the BSE index is used to estimate the return of the market portfolio (Rmt) for each security, whereas the unknown parameters, α and β, is estimated using ordinary least square (OLS). Using the above equation, the Expected Return (in the absence of any confounding event) of the stock on day “t’ would be E(Rit) = =∝𝑖+ 𝛽𝑖𝑅𝑚𝑡 And the abnormal return would be 𝐴R𝑖𝑡 = 𝑅𝑖𝑡 − 𝐸 [𝑅𝑖𝑡] (1) where𝐴𝑖𝑡, 𝑅𝑖𝑡, and [𝑅𝑖𝑡] is the abnormal, actual and expected return respectively for security i in period t. The estimation period needs to be sufficiently large to create representative estimates of αi and βi – the coefficients used in the estimation of expected return, but we need to be careful that it does not lead to outdated estimates (Armitage, 1995). Generally a period of over 100 days is considered sufficient (Corrado&Zivney and MacKinlay (1992; 1997). In this study, data for the (-) 360 to (–) 30 days was used to estimate ∝ and β. To ensure that the event period does not influence the estimation of ∝ and β, it is not included in the estimation period. The Average Abnormal Return (AAR) is calculated by dividing the sum of the abnormal returns of all the sample announcements by the number of announcements. n AARt = ∑ ARit / N (2) i=1 Average cumulative abnormal return Some researchers suggest aggregation of the abnormal returns through time and across securities (MacKinlay, 1997). The aggregation over time is simply the cumulative abnormal return (CAR) of security i from time t1 to t2. The CAR is the sum of the abnormal return included in theevent period for each security, t2 𝐶𝐴𝑅𝑖 (t1, t2) = Σ AR𝑖𝜏(3) t=t1 The CAR’s are then aggregated across announcements and divided by the number of announcements to get the Average Cumulative Abnormal Returns (ACAR) or CAAR as it is sometimes refereed to. N Σ CARit(t1 t2) i=1 CAAR(t1, t2)= ----------------------------(4) 𝑁 Where CARi (t1,t2) is the cumulated abnormal return of each security, derived in (3) and N is the number of announcements.CAAR(t1,t2) is the average of the cumulative abnormal return across time and securities.