Showing papers in "The IUP Journal of Applied Finance in 2013"

Causal Relationship between Stock Market Indices and Gold Price: Evidence from India

Abstract: (ProQuest: denotes formulae omitted)IntroductionStock market plays an important role in the development of an economy It facilitates mobilization of funds across the economy-from surplus units to deficit units The escalation in stock market is important from both industry as well as investors' point of view The economic position of a country can be judged by the performance of its stock market An economic downturn escorts stock market towards collapse, and therefore, the government closely monitors the movements in the stock market The stock market indices are mainly affected by the changes in the fundamentals of the economy As India is a developing country, many researchers have tried to find out the effect of macroeconomic variables on the Indian stock market in the last few decades1There are two different views on the relationship between gold demand and income The classical theory argues that there exists a positive relationship between gold price and real income, while Keynesian theory argues that more demand means more economic backwardness hence low income, which indicates an inverse relationship India and China are the major gold purchasers in the world In the last 10 years, Indian population has increased by 12%, while the demand for Indian gold has increased by 13% According to the World Gold Council (WGC), Indians own more than 18,000 tons of gold, which represents 11% of the global stock and is the largest in the world And this stock is expected to grow over the next decade Indians roughly save 30% of their income, which is one of the highest in the world, and of this 10% is invested in gold Researchers have shown that gold as a strategic investment avenue can act as a hedge against inflation and exchange rate Gold is the most liquid asset in India It is one of the means for accumulation of wealth (WGC, 2010) Against this backdrop, this study focuses on the causal relationship between stock market indices and gold priceLiterature ReviewLiterature related to this study is divided into two parts The first part focuses on the factors affecting the stock market and gold price And, the second part reviews the findings on the relationship between stock market indices and gold pricesFactors Affecting Stock Market Indices and Gold PriceAbdalla and Murinde (1997) found causality running from exchange rates to stock market indices, except for the Philippines Patel (2012) found that long-run equilibrium relationship exists among gold price, other macroeconomic variables and Indian stock market indicesNaka et al (1999) found that long-term equilibrium relationship exists among Industrial Production Index (IPI), inflation, money stock, interest rate and the Indian stock market Ray and Vani (2004) observed that interest rate, output, money supply, inflation rate and the exchange rate had considerable influence on the stock market movement Padhan (2007) found that both the stock price and IPI are cointegrated, and bidirectional causality exists between them Agrawalla and Tuteja (2007) established that stable long-run equilibrium relationship exists between stock market developments and economic growth in India Ahmed (2008) concluded that stock prices in India lead economic activity, except movement in interest rate Srivastava (2010) concluded that in the long term, stock market is more affected by domestic macroeconomic factors like industrial production, wholesale price index and interest rate than global factors Agrawal and Srivastava (2011) found a bidirectional causality between exchange rate and stock indices Contrary to the above studies, Bhattacharya and Mukherjee (2003) concluded that no causal linkage existed between stock prices and macroeconomic variablesThere are several studies that have examined the relationship between macroeconomic variables and gold price Abken (1980) established that gold price can be modeled adequately by using economic theories …

Does Personality Affect Personal Financial Risk Tolerance Behavior

Abstract: IntroductionPersonal financial risk tolerance is an important concept with many practical implications in everyday money matters. For an investor, understanding one's risk tolerance level helps to determine the appropriate risk and return parameters of an investment portfolio so that the investor's investment plan and strategy are sustainable. Understanding one's risk tolerance also helps to clarify the difference between one's willingness and one's capacity to take risk in everyday financial matters such as the amount of auto, property, life, and vacation-protection insurances to purchase. Considering the examples of implications discussed above, it is useful to find out whether one's financial risk tolerance in everyday money matters is associated with one's personality. Understanding the link between one's personality and financial risk tolerance can provide some useful insights into one's behavior in being willing to handle uncertainties in pursuing a goal.Literature ReviewMuch research has been done to determine the relationship between demographic variables and financial risk tolerance-gender (Bajtelsmit et al., 1999), age (Palsson, 1996; Hallahan et al., 2003), education level (Grable, 2000), income and wealth levels (Bernheim et al., 2001), and marital status (Roszkowski et al., 1993).Some research has also been done to determine the link between risk tolerance and different personality traits in different settings-Type A in everyday money matters (Carducci and Wong, 1998), Myers-Briggs Type Indicator and investment behavior (Filbeck et al., 2005), risk propensity in different domains, such as sex, additions, outdoor, and others (Nicholson et al., 2005; and Chauvin et al., 2007). Schaninger (1976) found apositive relationship between risk and anxiety measures, and that the risk was negatively related to self-esteem. According to Soane et al. (2010), personality had a direct effect on risky choice behavior in four domains (social, ethical, gambling and recreation), and that perceived costs and benefits mediated the relations between personality and risk-taking. Chitra and Sreedevi (2011) found that personality traits had an impact on the choice of investment method, and that the personality impact was stronger than that of demographic variables.Very little research was done to assess the relationship between financial risk tolerance and the personality dimensions of extraversion, conscientiousness, agreeableness, emotional stability, and openness with regard to personal money matters. This study, therefore, attempts to fill this gap by determining the impact of the five personality dimensions on personal financial risk tolerance.MethodologyA questionnaire (see Appendix) was used to collect data from university students of psychology and finance classes. The questionnaire comprised two sections: the first section contained 12 financial risk tolerance assessment questions from which the financial risk tolerance score was derived. The respondents were asked what they would do in different risk scenarios on a 9-point scale (Likert Scale ranging from Extremely Accurate (9) to Extremely Inaccurate (1) was used for the study). A financial risk tolerance score for each respondent was then computed by taking the average of the scores obtained from the respondent's responses to the 12 scenario-based questions. The second section of the questionnaire contained 40 Big Five personality mini-markers developed by Saucier (1994). The personality mini-markers were also structured on a 9-point scale. The questionnaire was filled online by students who were given extra credit points for participating, and the grade incentive minimized any self- reporting bias because almost all the invited students participated, giving us a sample of 331 respondents.Regression was performed to determine as to which variables contributed to the prediction of risk tolerance and the direction and extent of such contribution. …

Herding during Market Upturns and Downturns: International Evidence

Abstract: (ProQuest: ... denotes formulae omitted.)IntroductionHerding behavior is commonly defined as the behavioral tendency of an investor to follow the actions of others in the market. There are several reasons that induce herding. On the one hand, investors may follow each other when it is thought that other agents in the market are better informed (Avery and Zemsky, 1998; Calvo and Mendoza, 2000; and Chari and Kehoe, 2002). On the other hand, herding may occur when investors prefer to suppress their own belief in favor of the market consensus (Devenow and Welch, 1996). Furthermore, managers may exhibit herding behavior as a result of the incentives offered by the compensation scheme, conditions of employment or maybe to save their reputation (Scharfstein and Stein, 1990; Rajan, 1993; Trueman, 1994; and Maug and Naik, 1996).The suppression of the personal information in favor of the market consensus may lead to a situation in which pricing process moves the market towards inefficiency. As Wermers (1999) underlines, the question of herding is crucial to understanding the way information is incorporated into prices.There is considerable empirical evidence in social psychology that underlines the suppression of individual opinion to group opinion.1 Despite its common use in the literature, herding can be analyzed as a rational or irrational behavior. The rational view arises when investors ignore their private information and follow others so as to maintain their reputational capital in the market (Scharfstein and Stein, 1990; Bikhchandani et al., 1992; Welch, 1992; and Rajan, 1993). However, the irrational view refers to investors' psychology where they ignore their own beliefs and opinions, and blindly follow other investors (Devenow and Welch, 1996).Lakonishok et al. (1992), Christie and Huang (1995) [hereafter CH (1995)], Chang, Cheng and Khorana (2000) [hereafter CCK (2000)], Hwang and Salmon (2004), and Hachicha et al. (2008) propose pragmatic measures to detect the herding behavior.Academic research suggests that herding would be tightly linked to market stress (CH, 1995 and CCK, 2000 among others). However, Hwang and Salmon (2004) find the opposite. In fact, they conclude that herding behavior is more widespread during periods of market calm. Although herding behavior is by now well documented in the literature, there have been a few empirical studies on the implication of this behavior both in downturns and upturns. Particularly, some questions one would like to answer are: Is herding more prevalent in upturns or in downturns? Is there a symmetrical reaction? How does herding affect prices and volatility?In this paper, we extend the work of CH (1995) and CCK(2000) along three dimensions. First, we study herding both in upturns and downturns. Second, we propose a new and more powerful approach to detect herding based on equity return behavior using EGARCH. Third, in order to verify the existence of this behavior, we use a methodology as in Hwang and Salmon (2004).Literature ReviewBanerjee (1992) developed a simple model for herding behavior. He indicates that herding is a behavioral bias that must be quantified to well understand the financial markets. The author demonstrated in his model that it would be better in some cases for market participants to ignore their personal information and blindly follow the behavior of others.Following this formulation, several researchers focused on the question to quantify this phenomenon to understand its effect on assets, prices, volatility, etc. Lakonishok et al. (1992) were the first to propose an empirical methodology to detect the herding behavior. They developed a statistical measure that defines herding as the behavioral tendency when a group of fund managers buy or sell stocks at the same time, as compared to a situation where each one reacts independently. This measure is based on the transactions of some groups who are generally the portfolio managers. …

Factors Influencing Abnormal Returns around Bonus and Rights Issue Announcement

Abstract: IntroductionThe changes in abnormal returns of a security around event announcement may be due to event-induced, firm-specific or event-related factors. There are a host of studies that have looked into factors that influence stock returns for seasoned issue announcements (Asquith and Mullins, 1986; Mikkelson and Partch, 1986; and Kalay and Shimrat, 1987). However, Barclay et al. (1990) have found that there exists a relationship between announcement effect on abnormal returns and the issuing firms' information asymmetry, profitability, growth, and the issue characteristics. An analysis of factors affecting abnormal returns around the announcement of new equity issue is important for the following reasons: (1) unrecorded goodwill may be reflected in the stock price which is not captured by the event itself; (2) managers have superior information about investment projects compared to investors; and (3) the issuing firm's current financial structure and the impact of new equity issued on its financial situation are also important factors considered by investors in their valuation of equity offerings. Though empirical work has focused on examining the significance of the change in abnormal returns, studies exploring the extent of influence of firm-specific or event-related factors on abnormal returns are limited.The literature shows that issue size has a mixed impact on the firm's abnormal returns (Hess and Bhagat, 1986; Abhayankar and Dunning, 1999; Marsden, 2000; Bigelli, 2002; Kato and Tsay, 2002; Tan et al., 2002; and Wu et al., 2005). A positive relationship between pre- market condition and a firm's abnormal returns has been documented by Choe et al. (1993), Tsangarakis (1996) and Tan et al. (2002). Different firm characteristics have a significant effect on the firm's abnormal returns (Balachandran et al, 2005).Measurement of Variables Affecting Abnormal ReturnsIn this study, the effects of factors influencing cumulative abnormal returns have been examined for two time periods: the first one being around one day of announcement (t_j to t+1), and the second one being around 20 days of announcement (t_20 to t 20).In the case of equity issue announcement, the selection of the factors affecting abnormal returns of a firm is primarily based on the previous studies in the context of both developed and developing countries. A review of literature shows that there are several firm-specific, issue-specific, industry-specific and country-specific factors that influence stock returns of a firm apart from the announcement of an issue alone. The characteristics of firms determine the degree of fluctuation in the abnormal returns (Tan et al, 2002; Balachandran et al, 2005; and Elayan et al, 2007), and include parameters such as firm size, issue size, dividend yield, research and development, intangible assets value, market capitalization, market-to-book ratio, capital intensity, total liabilities, return on equity and leverage. The following variables have been used in the study: Issue Size (ISSUE), Pre-Market Condition (PRECAR), Industry Type (IT), Value of Collateral Assets (VCA), Return on Equity (ROE), Price-Earnings (PE) ratio, Market Capitalization (MCAP), Operating Leverage (OPLEV), Debt-Equity (DE) ratio and Volatility of Stock Returns (VSR).Issue-Related VariablesThe present study uses bonus issue ratio calculated as the number of shares allotted against the current number of shares held by investors. In the case of rights issue, the number of shares issued scaled by the number of shares outstanding has been taken as the issue-related variables. The bonus issue size or the rights issue ratio has not been considered to avoid duplication of data in the model.Market-Related FactorsInvestors start bidding up the prices prior to the announcement date, if they anticipate revelation of information about the issue of bonus and rights shares. If the information is already anticipated in the market, then the stock price reaction to the announcement will be lower. …

Efficiency of Guar Seed Futures Market in India: An Empirical Study

Abstract: (ProQuest: ... denotes formulae omitted.)IntroductionIn India, commodity futures markets have been in existence for more than a century. Their ability to meet the price risk management needs of producers and traders has created a compelling need for transforming them to highly sophisticated markets, where cutting-edge technology, wide variety of contracts, increasing awareness and participation of users together with tight regulatory framework, all work towards the ultimate aim of improving the market efficiency. Price discovery and price risk management are the twin functions which are used to measure the efficiency of futures market. The mechanism of price discovery aids in ascertaining the true price of an asset in the marketplace where a large number of buyers and sellers are interacting. Working (1948) refers to price discovery as the use of futures prices for pricing cash market transactions. In futures market, price discovery is facilitated with the participation of hedgers and speculators who provide the much-needed liquidity and information value to the market.Commodity markets are very crucial for the sustenance and growth of any economy. In India, the demand for commodities is increasing very fast, putting a constraint on the available resources. Prior to the launch of economic reforms in the 1990s, governments' intervention, particularly in food and agriculture markets, to artificially stabilize prices was promoting inefficiencies and was expensive on the state exchequer. But the wave of liberalization which began in the early 1990s necessitated greater reliance on market-based price risk management instruments. With support from government, commodity markets were liberalized and development of commodity derivatives was taken up on priority. Derivatives in the form of commodity futures were introduced in commodities like bullion, metals, energy, weather, food and non-food agricultural items. Agriculture has been one of the strongholds of Indian economy, and it supports about two-thirds of the country's population, contributing 17.28% to the GDP at current prices.1 To make the trade in farm commodities competitive in the world markets, the Indian government signed General Agreement on Trade and Tariff(GATT) with WTO, thus opening the agriculture sector to world trade. The need to strengthen the farm sector has led to the revival of interest in commodities futures markets in India with the ultimate objective of facilitating price discovery and to serve risk mitigation needs of farmers.The response to futures trading in agriculture commodities has not been without criticism. Nevertheless, it has maintained its growth trajectory, and the volume of commodity futures trading in agriculture increased from 3.87 lakh crore in 2004-05 to 14.56 lakh crore in 2010-11.2 Rigorous efforts are being made to boost the trading volume by reaching the farmers, traders and exporters through awareness programs and training, and by increasing the number of commodities eligible for futures trading to cater to a wide variety of users. As of March 31, 2012, a total of 113 commodities have been permitted for trading at commodity futures exchanges, and in terms of value of trade, the prominent among them are gold, silver, copper, zinc, soya oil, pepper, jeera, chana and guar seed. After soya oil, guar seed had the second highest trading volume of 2,46,283 cr as on March 31, 2011 on the NCDEX and it is also dominating the international trade (see Figure 1). Hitherto an obscure commodity, it is currently being tagged as Black Gold because of itsGuar seed is a leguminous crop which grows in sandy soil and needs moderate rainfall. It is sown in the end of July after the first shower of monsoon and is harvested in October-November. Not simply a vegetable, it has commercial application in food processing, pharmaceutical and personal care industry. The US Food and Drug Administration department has approved Guar as a substitute to fats in foods. …

Forecasting Daily Stock Volatility Using GARCH Model: A Comparison between BSE and SSE

Abstract: (ProQuest: ... denotes formulae omitted.)IntroductionGiven the rapid growth in financial markets over the past 20 years, along with the explosive development of new and more complex financial instruments, an ever-growing need has emerged for accurate and efficient volatility forecasting to use in numerous practical applications of financial data such as the analysis of market timing decisions, assistance in portfolio selection, and estimates of variance in option pricing models. Furthermore, accurate volatility estimates are also vital in areas such as risk management for the calculation of metrics in hedging and Value-at-Risk (VaR) policies.Since the 1987 stock market crash, modeling and forecasting financial market volatility has received a great deal of attention from academics, practitioners and regulators due to its central role in several financial applications, including option pricing, asset allocation and hedging (Busch et al., 2011). In addition, the financial world has witnessed bankruptcy or near bankruptcy of various institutions that incurred huge losses due to their exposure to unexpected market moves for more than a decade (Liu et al., 2009). These financial disasters have further highlighted the significance of volatility forecasting in risk management (calculating VaR). Given these facts, the quest for accurate forecasts appears to be still going on in the recent years.When volatility is interpreted as uncertainty (Samanta and Samanta, 2007; and Anbarasu and Srinivasan, 2009), it becomes a key input to many investment decisions and portfolio creations. Given that investors and portfolio managers have certain bearable levels of risk, a proper forecast of the volatility of asset prices over the investment holding period is of paramount importance in assessing investment risk. Volatility forecasting is an area within which the debate continues, and indeed there is already a wealth of literature on the subject. One type of investment instrument that is being extensively adapted in recent years is Exchange-Traded Funds (ETFs); over the course of a trading day, these instruments, which hold assets such as stocks or bonds, trade at almost the same price as the net value of the underlying assets. ETFs are more popular because of their low cost, tax efficiency and stock- like features, with most ETFs tracking an index such as the S &P 500, Dow Jones or NASDAQ- 100. One of the most widely known ETFs is Standard & Poor's Depositary Receipts (SPDRs or Spider, ticker: SPY), which began trading in January 1993, and which was designed to closely track the S&P 500 index.The publication of Engle (1982) introduced Autoregressive Conditional Heteroskedasticity (ARCH) model to the world. It is used to characterize and model observed time series in econometrics. There have been some other methods of modeling and forecasting financial volatility such as the Generalized ARCH model proposed by Bollerslev (1986). It is well known that financial returns are often characterized by a number of typical 'stylized facts' such as volatility clustering, studying long-run relationship among time series data, persistence and time variation of volatility. The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) genre of volatility models is regarded as an appealing technique to cater to the aforesaid empirical phenomena. The existing literature has long since recognized that the distribution of returns can be skewed. For instance, for some stock market indices, returns are skewed toward the left, indicating that there are more negative than positive outlying observations. The intrinsically symmetric distribution such as normal, student-t or Generalized Error Distribution (GED) cannot cope with such skewness. Consequently, one can expect that forecasts and forecast error variances from a GARCH model may be biased for skewed financial time series.The Bombay Stock Exchange (BSE), the oldest exchange in Asia, was the first stock exchange to be recognized by the Indian government under the Securities Contracts Regulation Act. …

Are Share Repurchases Substitutes for Dividend Payments in India

Abstract: IntroductionCorporations possess a variety of mechanisms to distribute cash to their shareholders (Lee and Rui, 2007). The most common forms of such distributions are cash dividends and share repurchases. For decades, corporations employed cash dividends as a means of cash distribution. The trend was reversed in the 1990s with the increasing popularity of share repurchases, especially the Open Market Repurchases (OMRs) in US. The total amount distributed under repurchase programs exceeded the cash dividends for the first time in 1998 in US (Grullon and Michaely, 2002). The adoption of Rule 10b-18 by SEC1 encouraged many firms to repurchase their stock and the amount distributed under share repurchase programs increased continuously and was $181.8 bn in 1998 as against $174.1 bn paid through cash dividends (Grullon and Michaely, 2002).The increasing use of repurchases over dividends has led to a belief that firms substitute dividends by repurchases. Empirical studies in US show evidence for dividend substitution effect (Grullon and Michaely, 2002; and Skinner, 2008), while in non-US countries no such clear evidence is seen. For US firms only, Jagannathan et al. (2000) find contrary evidence that firms use repurchases to pay out temporary or variable sources of cash flows, while dividends are paid out of permanent cash flows, i.e., there is no substitution.The Indian companies have been permitted to buy back shares since 1998 and several instances of buybacks have been noticed. Though buybacks are still at their nascent stage compared to US and other European countries, a question may arise regarding the methods of financing employed by Indian firms. Do Indian firms substitute dividends by repurchases? Is dividend substitution a method of financing repurchases? What is the Indian evidence in this respect? An analysis on these lines would throw light on the motives of buyback and related influencing factors of payout policy.Dividend Versus Share RepurchasesA firm's payout policy is a complex decision variable. Considerations like tax rates, investors' requirements, firm's internal growth opportunities, amount of cash flows generated, sources of cash flows, etc., decide the actual payout policy. The share repurchase is a larger part of this overall payout ratio wherein a firm has to decide on the mode of payment of cash flows, either in the form of repurchases or cash dividends. How do these two payment methods compare? What are the similarities and dissimilarities? In both these distributions, a firm's net assets and investors' stake are reduced. Some firms might use both; some may pay dividends and avoid repurchases; some repurchase and pay no dividends and some pay nothing at all. Excess cash flows are generally used to pay dividends and for repurchases. Payout is determined by free cash flow (Jong et al., 2003). It is contended that dividends are paid out of regular or operating cash flows, while a firm repurchases shares out of non-operating cash flows (Jagannathan et al., 2000).The dividend route is laden with many difficulties. Dividends have a clientele effect. Dividends carry information. A higher dividend in one year commits a firm to pay similar dividends in subsequent years. Non-payment could send a negative signal. Debenture trust deeds often constrain managers in using excess cash flows for dividends. Therefore, firms circumvent such difficulties through share repurchase actions. Share repurchases have no clientele effect. A repurchase in one year does not necessarily foretell repurchase in the succeeding years. There is no regularity in repurchase. Jagannathan et al. (2000) note this inherent flexibility in repurchase programs as an important reason for the popularity of repurchases over regular dividends. Some regard repurchase decisions as costless market signaling mechanisms than dividends. Dividends have a signaling cost (Schmidt, 2006). Dividend announcement is followed by its completion. …

Buyback Announcements and Stock Market Reaction in India: Testing the Market Condition Hypothesis

Abstract: (ProQuest: ... denotes formulae omitted.)IntroductionBuyback of equity shares by companies was allowed in the early 1990s in the US and the UK, and various countries in the European Union started following the UK by incorporating changes in their respective laws.1 This was considered as a good beginning for introducing flexibility in the capital structure. As regards to the rest of the world, abolition of restrictions on buyback of equity shares was introduced in Australia in 1989, Hong Kong in 1991, Korea in 1994 and Japan in 1995.In India, a landmark legislative adjustment was made in 1998 through Sections 77A, 77AA and 77B, which were inserted into the Companies Act 1956; and thereafter companies in India are allowed to buy back their shares. Consequently, in 1999, the Securities and Exchange Board of India (SEBI) issued guidelines that are to be followed by the listed companies.As a result of allowing buybacks, companies worldwide have started experiencing a new way of adjusting the capital structure by making downward adjustment in the paid-up capital. Buybacks can be regarded as the late 20th century adoptive strategy in the ever-changing, challenging and demanding scenario of modern corporate finance. The companies going for buyback may have their own reason(s). But the interesting factor to look at is how the stock market reacts to such share repurchase programs.Literature ReviewIn spite of the general view that the buybacks are allowed to rationalize the capital structure of companies (Bagwell and Shoven, 1987; Opler and Titman, 1996; Dittmar, 2000; and Lie, 2002), researchers in the developed world have found various other reasons to go in for buybacks. They are: excess cash distributing (Li and McNally, 1999; Jagannathan et al., 2000; Grullon and Michaely, 2002; and Brown, 2007), substitution for cash dividends (Grullon and Michaely, 2002), signaling undervaluation of shares (Dann, 1981; Vermaelen, 1981; Ikenberry et al., 1995; and Balachandran and Faff, 2004), takeover defense (Davidson and Garrison, 1989) and providing liquidity to shares and wealth expropriation to bondholders (Kahle, 2002; and Chan et al., 2004). The dominant among them has been the decision by the management when it feels that the companies' share prices are undervalued (signaling).In the Indian context, because of the restriction imposed by the law of the land up to 1999, there were very few empirical studies on buybacks. The studies by Mohanty (2002), Mishra (2005), Gupta (2006), Thirumalvalavan and Sunitha (2006), Hyderabad (2009a), Dhatt (2010) and Rajagopalan and Shankar (2012) supported the undervaluation signaling of buyback announcements in the Indian stock market by observing statistically significant Average Abnormal Returns (AAR) on the event day. But Ishwar (2010) had come out with a very weak signaling of Indian buybacks in the stock market and opined that the information content did not favor undervaluation signaling by observing a statistically insignificant AAR on the announcement day.The studies pertaining to the market reaction to different methods of buybacks were also found in good number in the international markets. The first one is Open Market Repurchases (OMR) in which companies buy back their shares through the stock exchanges for a small number of shares. The second is the Fixed Price Tender (FPT) offer in which companies fix a fixed price and offer it to a limited number of target shareholders when the number and amount of shares involved is large. The results of international studies by Vermaelen (1981), Comment and Jarrell (1991) and Li and McNally (2004) found more abnormal returns in FPTs than OMRs. However, Zang (2002) found a contrasting result in Japanese market as the abnormal returns in OMRs were more than FPTs.In the Indian context, there are very few studies relating to market reaction to methods of buybacks. Hyderabad (2009a) found more returns in FPTs than OMRs, but the same author (2009b), by making a single company elimination from each dataset, had come out with a different finding, having recorded a higher abnormal returns in OMRs than FPTs. …

Institutional Preference for Firm Attributes: Evidence from India

Abstract: This paper examines the firm characteristics typically preferred by institutional investors before investing in a stock in the Indian equity market, and also explores the implications of such preferences in terms of their subsequent performance. We find that all institutional investors show strong preferences for larger market capitalization stocks, stocks with international exposure and stocks included in indices. However, their preferences for price, leverage, turnover and other parameters differ. We also find that the preferences of these institutional investors are dynamic in nature and vary over time. It is observed that such preferences exhibited by institutions do not translate into concrete performance as manifested by lack of predictive power of stock returns in the following quarter.

The Performance of Initial Public Offerings Based on Their Size: An Empirical Analysis of the Indian Scenario

Abstract: (ProQuest: ... denotes formulae omitted.)IntroductionEquity issues are made on the basis of market conditions. If the market perceives that a company will continue to have good earnings in future, the market price of the company's share will remain at the same level or will go up. On the other hand, if the market doubts about the future earnings capacity of the company, it may place lesser value on its share price. Of course, any new investments made for expanding a business bear results only after a short gestation period, extending sometimes to a few years. These aspects would of course be considered by the market and the prices get normalized over a period of time, blow quick the market adjusts the price, factoring in the new information would reveal the efficiency of the market. Hence, this aspect was studied with regard to the companies which made Initial Public Offerings (IPOs) during the study period. From the market point of view, it is essential to know how the market reacts to the IPOs of the Indian companies.The price fixation of shares at the time of issue is important because it is considered to have a long-term impact on the market value determination of these shares. There are a number of instances where high prices are fixed for IPOs, with the prices going down subsequent to listing, causing heavy losses for the initial investors. Earlier studies have documented that in certain cases price recovery up to the IPO level was not attained even after two years of issue, indicating heavy overpricing of issues.Companies may issue shares to public either under fixed price method or book-building method or under a combined method. Under fixed price method, the offer price for the securities is fixed and is intimated to the investors in advance. Under book-building method, the issue price is not fixed or intimated in advance. Companies offer shares at a range of price which is referred to as a price band, and within this price band the investors are allowed to bid. The final price of the security is determined only after the closure of the bidding.The issuing company nominates a lead merchant banker as 'book runner', who fixes the price band on the basis of existing market conditions and past performance of the company. The issuing company appoints a syndicate of members to receive orders from the investors for the issue. After appointing them, they open bidding. The bidding is open for at least 5 days. The book runners determine the final price of the issue on the basis of the demand at various price levels in the bid. Finally, allocation is made to the successful bidders and others get refund order from the issuing company.The study analyzes the price efficiency of the companies issuing IPOs on the basis of the size of issue to verify whether size-wise distinction could be made in the efficiency of pricing of IPOs.Literature ReviewThere are various studies on IPO performance in the Indian context as well as in the international context. Flowever, it is observed that the studies related to IPO size in the Indian context are limited, especially during the study period of the present study.Jagadeesh et al. (1993) found a positive relationship between underpricing of IPOs and the probabilities of size of subsequent seasoned offerings. The researchers evidenced that many firms which recorded high return on the IPO date went for further issues within three years of the IPO. Page and Reyneke (1997) found long-run underperformance of South African IPOs by testing the timing of IPOs in the Johannesburg Stock Exchange. They also found that the degree of underperformance was associated with the size and nature of the companies. Companies which made small issues had greater evidence of underperformance than the large-issue companies. Jaitly (2004) examined the pricing of new issues and their after issue performance in the Indian context. The results indicated that pricing of new issues appeared to be consistent with rational decision making. …

Seasonality in Southeast Asian Stock Markets: The Ramadan Effect

Abstract: (ProQuest: ... denotes formulae omitted.)IntroductionFama (1970) suggested Efficient Market Hypothesis (EMH) to explain that all available information in financial markets is fully reflected in market prices unbiasedly, implying that abnormal profit can be earned neither by using information available in the market nor by technical analysis. However, there are some evidences against EMH. In particular, those concerned with calendar anomalies discovered a predictable and consistent trend in stock prices over some period of time in the Gregorian calendar.1 It enables investors to predict the price movements of securities and hence profit from the prediction. For instance, tax-loss selling hypothesis (Wachtel, 1942) explains the changes of individual investors' behavior where investors try to sell their stocks in December and buy back in January to avoid income tax charges, causing the returns in January to be higher than in other months, while window dressing hypothesis (Haugen and Lakonishok, 1988) explains the behavior of institutional investors where fund managers furnish portfolios with blue-chip stocks in December as they are required to publish the details of the portfolio at the end of the year. These changes in investment behaviors create anomalies in stock market. Ramadan effect, being one of festivities effect, is specifically attached to Islamic calendar. During the fasting month of Ramadan, which is the ninth month of the Islamic lunar calendar, all muslims are strictly forbidden from certain activities like eating from sunrise to sunset. The fasting period is also likely to have an impact on their investment decisions. A significant change in investment trend hence would be expected during the Ramadan period, suggesting the effect of Ramadan.According to The World Tactbook 2011, Christianity is the largest (33.35%) religion in the world, followed by Islam (22.43%) and Hinduism (13.78%). Moreover, as muslim population is growing fast, bankers around the world have started to design financial products to conform to the religious beliefs of muslim investors. Islamic finance, especially islamic banking, thus is the contemporary demand that is not limited only to the muslim investors. With the rapid growth of muslim population and the islamic banking system, the effect of Ramadan will be further strengthened. In this context, continuous investigation to examine the religious effect of Islam on the stock market performance is critically needed.The purpose of this paper is to examine the seasonality of market returns and volatility in the holy month of Ramadan in the Southeast Asian stock markets. This paper differs from the previous studies in that it attempts not only to measure the Ramadan effect on risk-return compensation, but also investigates the Ramadan effect in both muslim and non-muslim countries of Southeast Asia.Literature ReviewCalendar anomalies in financial markets are well documented and most of the findings do not lend support to random walk model of EMH.2 There are some calendar anomalies, specifically related to holiday or festival. The date of these anomalies do not fall on a specific date of a Gregorian calendar. Pre-holiday effect is one of the holiday-related anomalies which illustrates the unusually good performance by stocks on the day prior to market-closing holidays. Holiday effect has been detected in some European countries-Spanish stock market (Vicente and Angel, 2004), some stock markets of Asia Pacific countries (Noor et al., 2005), and Australian stock market (Marrett and Worthington, 2009). Other than pre-holiday effect, the moving-holiday effect or festivities effect is also a holiday-related anomaly. It describes such holidays like Ramadan which follows lunar calendar. Such anomaly has a potential impact on investors' behavior and leads to seasonality in stock market due to its effect on economics and financial variables.Ramadan has recently been noticed to have a significant effect on the trading activities of Islamic countries. …

Market Efficiency in Emerging Economies: An Empirical Analysis of Month-of-the-Year Effect

Abstract: (ProQuest: ... denotes formulae omitted.)IntroductionEquity markets, the world over, are experiencing depressive sentiments and high volatility. The integration of financial markets have made even the safer and fast-growing economies feel the ripple effects of economic shocks at global scale. The concept of efficient stock market, with fairly-priced stocks, perfect forecast and rational behavior of investors, has become unrealistic in today's economic scenario. Documentation of seasonality in stock returns and advances in the area of behavioral finance have shifted the emphasis of financial scholars and practitioners away from efficient market hypothesis to seasonality in stock returns. An efficient market is one in which security prices reflect the intrinsic worth of a security and adjust rapidly to the arrival of new information. Therefore, there is no opportunity for investors to make abnormal profit or outperform the market through market timing or stock selection.The presence of calendar anomalies in a stock market is an indicator of market inefficiency. These anomalies are in the form of capital market regularities that are not explained by any acceptable theory or model of finance. Seasonality in stock returns means that the average returns are not uniformly distributed across various calendar periods, giving rise to various calendar anomalies, namely, week-of-the-month effect, month-of-the-year effect, monthly effect, holiday effect, month-of-the-quarter effect and day-of-the-week effect or weekend effect. Month-of-the-year effect has been documented across markets and investment categories. It is a seasonal pattern where stock and other financial assets tend to exhibit abnormal returns in a specific month of a year. Generally, it is believed that the month with higher return is January. Empirical studies have also shown that returns for the month of January are abnormally higher as compared to returns for rest of the year. That is why this is also called January effect. The January effect was first pointed out by Wachtel (1942) in the US markets. Then Rozeff and Kinney (1976) examined the January pattern using New York Stock Exchange (NYSE) stocks and the results indicate the presence of January seasonal. Several studies such as Keim (1983), Keim and Stambaugh (1984) and Ariel (1987) have pinpointed the month-of-the-year (January) effect in the US and other markets. The reason for the January effect in stock returns in most of the countries is attributed to the tax-loss selling at the end of the year, asymmetric release of information during the year, size of the firm, insider-trading and window dressing by institutional players.Globalization of world financial markets has made emerging markets one of the most attractive investment destinations for international funds seeking global diversification. These economies have experienced huge growth and received attention of practitioners and academicians the world over. It is, therefore, of vital importance to study the stock price behavior of these emerging superpowers which might provide useful insights to institutional investors, portfolio managers and individual investors to strategize their investment decisions and diversify their portfolios internationally. The presence of month-of-the-year effect may give investors clues for timing their investments or they may take suitable position in derivatives markets to enhance returns on their portfolios. The present study examines the month-of-the-year effect in stock index returns and volatility of nine emerging economies, namely, Argentina, Brazil, China, India, Indonesia, Mexico, Malaysia, Russia and Taiwan.Literature ReviewThere exists an extensive literature documenting month-of-the-year anomaly: while investigating the US stock market taking monthly return data of NYSE for the period January 1904 through December 1974, Rozeff and Kinney (1976) explored the monthly seasonality. …

Stock Price Dynamics of Listed Growth Companies: Evidence from the Options Market

Abstract: This paper empirically investigates the stock price dynamics implied by the valuation model proposed by Schwartz and Moon (2001) for growth companies. We test the hypothesis that the inherent stochastic process for the firm equity value better describes the actual dynamics than standard geometric Brownian motion. Because the form of the stochastic process decisively influences the values of options written on a firm’s stock, we rely on price information from the options market to test the hypothesis. Therefore, we propose an adapted version of the Least-Squares Monte Carlo algorithm to price options on the stock of a growth company whose value is determined by the Schwartz-Moon model. Calibrating the model to real-world stock and option data, we analyze the stock price dynamics implied by the Schwartz-Moon model empirically by comparing them to a standard geometric Brownian motion model. The study is conducted for three high-growth Internet companies: Amazon.com, eBay and Google. Contrary to our expectations, we find no evidence that the Schwartz-Moon model is superior in explaining the options market for growth companies. The reason is due to the Schwartz-Moon model’s restriction on specifying the volatility of revenues, which allows only for exponentially decreasing functions.

Distress in Money Markets during the Global Financial Crisis: An Analysis of Co-Movement and Transmission

Abstract: (ProQuest: ... denotes formulae omitted.)IntroductionAs Hegde and Paliwal (2011) indicate, the models of financial crisis and contagion predict that an economic emergency becomes a crisis of market liquidity in the presence of borrowing constraints, information asymmetry and risk aversion. During the global financial crisis, originating from the US subprime loan problem, it was not surprising to note that distress disseminated across global money markets, amplifying both default and systemic risks. This mechanism could operate through direct linkages among global financial markets. Uncertainty over the mortgage exposure of counterparties and inability to value their respective assets were particularly enhanced after the subsidiaries of BNP Paribas announced the suspension of liquidation of asset on August 9, 2007. Taylor and Williams (2009) point out that the traders in New York City (NYC), London, and other financial centers around the world faced a dramatic change in the conditions of the money markets from that date onward.The impact of this was felt, particularly in the major financial markets, in the form of widening of the London Interbank Offered Rate - Overnight Indexed Swap (LIBOR-OIS) spreads, which in turn led to increased funding costs in the growing default risk. The collapse of Lehman Brothers saw a peak in distress in the global money markets, leading to a further widening of these spreads.LIBOR is the reference rate at which banks indicate they lend to other banks for a specified term loan. The OIS rate is the rate on a derivative contract on the overnight rate and serves as a measure of the market's expectation of the overnight funds rate over the term of the contract. There is very little default risk in the OIS market because there is no exchange of principal amounts. Funds are exchanged only at the maturity of the contract when one party pays the net interest obligation to the other. Sengupta and Tam (2008) maintain that the LIBOR-OIS spread is a closely watched barometer of distress in money markets, most seriously impaired by the events of 2007 and 2008.This paper investigates the co-movement and transmission of distress across money markets during the global financial crisis by analyzing LIBOR-OIS spreads with a focus on the US, Eurozone, UK and Japan. It makes two main contributions. Firstly, it investigates the asymmetrical impact of global financial crisis on LIBOR-OIS spreads by dividing the sample period into two, because it is important to assess the impact of the global financial crisis across these phases. As the severity of the crisis varied from one period to another, its asymmetric impact on distress in money markets needs to be considered. In other words, we analyze whether the co-movement and transmission of distress in money markets of the US, Eurozone, UK and Japan differ, depending on the period of the study.We regard the beginning of the global financial crisis as August 9, 2007 when the subsidiaries of BNP Paribas announced the suspension of the liquidation of assets because it was difficult to obtain fair values for Asset-Backed Securities (ABS) related assets under the market pressure. The second stage commenced on September 15, 2008 when Lehman Brothers went bankrupt. Imakubo et al. (2008) and Ji and In (2010) treat the global financial crisis as occurring over a single period. However, our results show that the co-movement and transmission of LIBOR- OIS spreads depend on the sample period.The distress moved synchronously in the major financial markets such as the US, Eurozone, UK and Japan, before Lehman shock, through the process of global transmission. However, such a coordination was found only between UK and Eurozone after the bankruptcy of Lehman Brothers. The distress became more of a regional issue within each major financial market. The results of this study implied that the problem of financial system stemming from the sovereign deficit crisis would be serious in Europe, particularly in Eurozone. …

The Effect of Fundamental Factors on Indian Stock Market: A Case Study of Sensex and Nifty[dagger]

Abstract: IntroductionEconomic progress depends on how savings are effectively channeled to productive investment since savings rate is considered as one of the long-term growth drivers. The securities market, being a financial institution that intermediates between savers and investors, provides fair prices to diverse types of financial instruments and plays a significant role in channelizing savings. The ability of the corporate sector to generate funds from the capital markets depends on efficient functioning of the stock exchanges. The extent to which security prices would truly reflect real worth of companies and their growth potential reflects the market efficiency.After the implementation of capital market reforms in 1991-92, the Indian securities market has now become more efficient and comparable with securities markets of the developed and other emerging economies. In fact, India has a turnover ratio which is comparable with that of other developed markets and is also one of the highest in the emerging markets (Banerjee and Sarkar, 2006). These developments have drawn the attention of the researchers from across the globe to look at the price movement of the Indian securities market. Foreign Institutional Investors (FIIs) and private equity investors have also started participating in the Indian capital market in a big way. The increasing interests of foreign investors in the Indian stock market call for greater research on various properties of this market. The development of the market has created various hurdles like excessive free pricing premiums, preponderance of speculative trading, lack of transparency transactions and insider trading. The dominance of these weaknesses in the Indian capital market led to inefficient functioning and prices did not reflect a consensus estimate of intrinsic values many a time (Banerjee and Sarkar, 2006). A vibrant market cannot afford to these distortions, hence requires corrective strategies from policy makers and market players. The present study is an attempt in the said direction to examine the role of the fundamentals.The various capital market reforms in the Indian capital market have removed the anomalies existing in the stock market functioning in the pre-reform era and now the share prices are more affected by corporate fundamentals rather than market manipulations. This has increased the confidence of the retail investors to invest in the stock market rather than government bonds and securities. More and more Indian companies are raising capital from the equity market and corporate fundamentals are playing a dominant role in shaping the direction of the Indian capital market. The Indian stock market has now become more efficient, thereby trying to reflect all types of market information and has integrated itself with the developed international stock markets. Such a changing scenario encouraged more meaningful research on various fundamental factors that have a significant bearing on the Indian capital market in the post-reform era.Stock prices change in the stock markets on a daily basis. Moreover, during certain times of the year it is easy to notice that stock prices appreciate every morning, and for some stocks this may occur many times in one day. This means that stock prices are determined by supply and demand forces. There is no foolproof system that tracks the exact movement of the stock prices in the stock market. However, the factors behind the increase or decrease in the demand and/or supply of a particular stock could include company fundamentals, external factors,1 and market behavior. But various research studies over a period of time have revealed that corporate fundamental factors are the most important determinants of share price and stock return for a particular period (Banz, 1981; Moldovosky, 1995; and Griffin, 2002).There has been considerable evidence that the cross-section of average stock returns are related to various firm-level characteristics such as size, earnings/price, cash flow/price, dividend/price, book-to-market equity, leverage, momentum both in the US and in the developed and the emerging markets around the world (Banz, 1981; and Baskin, 1989). …