Methodological Consideration

3.1 Methodological Consideration and Data:

The methodology of the study consists of following steps namely: construction of theory or model; data collection; estimation and testing; and interpretation of findings to generate conclusions and relate them to the literature and theory. It is useful to explain, as part of the methodology, the testing ground chosen for the empirical chapters, i.e. mainly India. The Indian emerging market has been undergoing economic reforms since 1991, prior to which it was characterised by high controls and extensive public ownership. Prior to reforms a licensing system required firms to obtain clearances for many routine operations. Clearances were typically determined not on economic or social basis but by the relative lobbying power of firms. Indeed, this may explain the large size of the Indian market in terms of number of listed firms while at the same time majority of Indian companies are relatively small (Green, Murinde and Suppakitjarak, 2001). Similarly, the foreign trade regime prior to reforms was characterised by high protectionism from import competition and restrictions on foreign ownership of Indian companies. Likewise the government was heavily involved with the workings of the financial systems. High reserve requirements were stipulated, interest rates were imposed, and credit was directed to priority sectors giving rise to manipulation and inefficiencies. Furthermore, supervision and financial discipline were slack, and equity markets suffered from lack of transparency and poor investor protection, while the large public sector was similarly inefficient. In 1991 India suffered a financial crisis which was followed by the initiation of economic reforms. For example, capital market reforms included the establishment of the Securities and Exchange Board of India (SEBI) in 1988, which was given statutory powers in 1992. SEBI was charged with improving disclosure rules in the primary market for equity as well as the transparency of trading practices in the secondary market. Similarly the office of the Controller of Capital Issues, which controlled the issue and pricing of new equity, was abolished in 1992, encouraging firms to sell shares. Other reforms were also launched including relaxing restrictions on foreign ownership, lowering import controls and tariffs, restructuring of the domestic tax system, and phasing out of government subsidies. It is thus in this new and changing environment that Indian firms have been making their financing decisions since the middle of the 1990s.The population of Indian firms from which the samples were drawn for Chapter 3, Chapter 5 and Chapter 6, is the 4800 or so listed companies on the Bombay Stock Exchange out of a universe of over 6500 listed and unlisted Indian firms. But the size of this population is not typical of developing countries, and thus in order to achieve a more balanced view, the 40 or so listed companies on the UK Stock Exchange form the population from which the sample for Chapter 4 is drawn. The UK economy can be differentiated from the Indian economy in other ways too, although there are also some similarities. In essence, the ownership structure in UK, like in India, is predominantly family oriented with an emphasis being placed on preventing dilution of control. The UK Stock Exchange is much more recent than the Bombay Stock Exchange, being established in 1988 by the Stock Exchange Act1. In the early 1990s it was opened to foreign investors, in spite of which it is still characterised by poor liquidity, low standards of corporate disclosures, and high domination, by a few large companies.

3.2 The Structure and Scope of the Study:

Before turning to the analysis of how the dividend policy in the Mauritian or Indian firms works, the starting point for the debate on how dividend affects firm value, which is often referred to as the dividend puzzle, is typically marked by Miller and Modigliani's (1961) irrelevancy theory. Thus the chapter begins by describing the irrelevancy theory, and then outlines some of the leading theories that have evolved once the assumptions underlying the irrelevancy theory are relaxed. These include the transaction costs theory, the bird in the hand argument, and the signalling and agency theories. The transaction cost theory of dividends is based on transaction costs, control and other considerations that are associated with paying dividends and then resorting to external finance to fund investments. The tax hypothesis proposes that government distortions by way of taxes have important implications for dividend policy and firm value. The bird in the hand argument is based on the idea that dividends reduce risk, while the signalling theory is based on the information content of dividends. Finally the agency theory of dividends deals with the role of dividends in resolving agency conflicts. After reviewing some of the relevant empirical methodologies and evidence, here an empirical approach is undertaken and an extended agency theoretic rationale for the dividend decision is investigated. The extended theory considers conflicts and associated costs that broaden beyond the pure owner-manager relations

The Bombay Stock Exchange (BSE) was established in 1875 as 'The Native Share and Stockbrokers Association'.

To this end, a variant of the cost minimisation model is utilised, relaxing the assumption of linearity and using data on Indian firms. As previously hinted, management of the Indian economy has traditionally been based on socialist ideology and a high degree of state-intervention. The hypothesis is, therefore, that an agency rationale for the dividend policy fits especially well in the Indian context. The empirical method is the general to specific approach, starting with an unrestricted model that includes non-linear terms, and carrying out a simplification process based on Wald and t-tests. Chapter presents empirical results that are consistent with the hypothesis put forward. In particular, the degree of government holdings appears to be significant in explaining the target pay-out ratios of firms in the Private Sector in India. To test whether the dividend policies of group-affiliated firms are substantially different to that of independent firms, a number of techniques are applied to data on Indian firms. The experimental procedure begins with a comparative analysis, followed by multivariate analysis that utilises qualitative and limited dependent variable methodologies. Results support the notion that the decision of whether to pay dividend is sensitive.

3.3 Dividend Theories

3.3.1 The transaction cost theory

Firms may incur costs in distributing dividends while investors may incur costs in collecting and reinvesting these payments. Moreover, both firms and investors may incur costs when, due to paying dividends, the firm has to raise external finance in order to meet investment needs. Indeed, the transaction costs incurred in having to resort to external financing is the cost of dividend in Bhattacharya's (1979) model. In contrast, however, it may be argued that dividend are beneficial as they save the transaction costs associated with selling stocks for consumption purposes1. Either way, if there are

Additional transaction costs that are associated with paying or not paying dividends, then dividend policy should impact earnings expectations and hence share price and firm value. Alternatively dividends may influence value if dividend policy has an impact on management's investment decisions. For example, managers may decide to forgo positive net present value investments because dividend payments exhausted internal finance and raising external funds involves transaction or other costs. Indeed in Miller

And Rock's (1985) model the cost of dividends arises from cutting or distorting the investment decision. However, more typically, the transaction cost theory of dividend

Retains the assumption of a given level of investment, and focuses on the costs of raising external funds when the firm increases its dividend payment. Transaction costs include flotation costs to the firm of raising additional external finance such as underwriter fees, administration costs, management time, and legal expenses. Further, when the firm pays dividend and then has to raise additional external finance, existing shareholders suffer dilution of control. Thus to maintain control or for other reasons, existing shareholders may subscribe to the new issue, incurring trading costs such as stamp duty and stockbrokers' commissions. Thus Rozeff (1982) suggests that firms that have greater dependency on external finance would maximise shareholder wealth by adopting lower pay-out policies. Leverage, growth potential and volatility are all factors that can increase dependency on costly external funds. High levels of leverage imply high fixed costs that the firm has to ensure it can meet. Growth potential means the firm is faced with good investment opportunities for which it requires funds. Similarly earnings volatility suggests that dependency on external finance is higher because there is less certainty regarding earnings to be generated. This implies that highly leveraged, risky or growth firms should be associated with conservative pay-out policies. Another important factor that has implications for control consideration and for the transaction costs of raising external finance and thus for firms' dividend policies, is size.

Having to sell stock for consumption purposes is the assumption in John and Williams (1985). Indeed, Fama and French (2001) note that one possible explanation for the decline over time in the benefits of dividends may be the increased tendency to hold stocks via mutual funds. Holding via these funds reduces the transaction costs associated with selling stock to meet liquidity needs.

Particularly, the ownership structure of small companies is likely to be less dispersed than that of larger firms. The more dispersed is ownership the less control is exercised by each shareholder and hence the problem of loosing control is more critical for smaller firms. Further, the cost of external finance is likely to be higher for smaller firms compared with larger, well-established firms with easier access to the capital markets. Add to this the observation that growth firms are usually smaller and the conclusion is that small firms are likely to find the payment of dividends more costly compared with larger firms. This conclusion may explain the positive correlation often observed between firm size and the likelihood that the firm is a dividend payer (Redding, 1997, and Fama and French, 2001).

3.3.2 The bird in the hand argument

The traditional argument for dividend is the idea that dividends reduce risk because they bring shareholders' cash inflows forward. Although shareholders can create their own dividends by selling part of their holdings, this entails trading costs, which are saved when the firm pays dividends. The risk reduction or bird in the hand argument is associated with Graham and Dodd (1951) and with Gordon (1959) and it is often defended as follows. By paying dividends the firm bings forward cash inflows to shareholders, thereby reducing the uncertainty associated with future cash flows. In terms of the discounted dividend equation of firm value, the idea is that the required rate of return demanded by investors (the discount rate) increases with the plough-back ratio. Although the increased earnings retention brings about higher expected future dividend, this additional dividend stream is more than offset by the increase in the discount rate. This argument overlooks the fact that the risk of the firm is determined by its investment decisions and not by how these are financed. The required rate of return is influenced by the risk of the investments and should not change if these are financed from retained earnings rather than from the proceeds of new equity issues. As noted by Easterbrook (1984), in spite of paying dividends the firm does not withdraw from risky investments, thus the risk is merely transferred to new investors.

3.3.3 The signalling theory

A more convincing argument for dividends is the signalling hypothesis, which is associated with propositions put forward in Bhattacharya (1979), Miller and Rock (1985), John and Williams (1985), and others. It is based on the idea of information asymmetries between the different participants in the market and in particular between managers and investors. Under such conditions, the costly payment of dividend is used by managers, to signal information about the firm's prospects to the market. For example, in John and Williams' (1985) model the firm may be temporarily under-valued when investors have to meet their liquidity needs. If investors sell their holdings when the firm is undervalued, then there is a wealth transfer from old to new shareholders. However, the firm can save losses to existing shareholders by paying dividends. Although investors pay taxes on the dividends, the benefits from holding on to the undervalued firm more than offset these extra tax costs. A poor quality firm would not mimic the dividend behaviour of an undervalued firm because holding-on to over-valued shares does not increase wealth. The signalling hypothesis can explain the preference for dividends over stock repurchases in spite of the tax advantage of the latter. Particularly, as suggested in Jagannathan, Stephens and Weisbach (2000), Guay and Harford (2000) and DeAngelo, DeAngelo and Skinner (2000) among others, the regular dividend signal an on going commitment to pay out cash. This signal is consistent with Lintner (1956) observation that managers are typically reluctant to decrease dividend levels. However, unlike regular dividends, repurchases and special dividends can be used to signal prospects without long-term commitment to higher pay-outs. Therefore announcements of increases in regular dividends signal permanent improvements in performance, and should be interpreted as confidence in the firm on behalf of managers thus triggering a price rise. Conversely, announcements of dividend decreases should be interpreted as signalling poor performance and lack of managerial confidence and should therefore trigger drops in prices. If changes in the levels of dividend release information to the market, then firms can reduce price volatility and influence share prices by paying dividends. However, it is only unexpected changes which have an informative value and which can thus impact prices. Therefore, the value of the signal depends on the level of information asymmetries in the market. For example, in developing countries where capital markets are typically less efficient and where information is not as reliable as in more sophisticated markets, the signalling function of dividend may be more important. Moreover, it can be argued that information will eventually be revealed whether or not the dividend signal is sent; hence the dividend impact on prices is only temporary.

3.3.4 The agency theory of dividend

Another argument in for dividend payments is that this shifts the reinvestment decision back to the owners which may not necessarily always act as on maximise shareholders wealth. The problem here is the separation of ownership and control which gives rise to agency conflicts as defined in Jensen and Meckling (1976). Accordingly when the levels of retained earnings are high managers are expected to channel funds into bad projects either in order to advance their own interests or due to incompetency. Hence dividend policy enhances the firm's value because it can be used to reduce the amount of free cash flows in the discretion of management and thus controls the over investment problem (Jensen, 1986). Another agency theory based explanation of how dividends increase value is described in Easterbrook (1984). While the transaction cost theory of dividend proposes that dividend payments reduce value because they lead to the raising of costly external finance, Easterbrook (1984) argues that it is this process which reduces agency problems. The idea is that the payment of dividends is one possible solution to the problem of collective action that tends to lead to under-monitoring of the firm and its management. Thus the payment of dividends and the subsequent raising of external finance induce investigation of the firm by financial intermediaries such as investment banks, regulators of the securities exchange where the firm's stock is traded and potential investors. This capital market monitoring reduces agency costs and lead to appreciation in the market value of the firm. Moreover, total agency cost, as defined by Jensen and Meckling (1976), is the sum of the agency cost of equity and the agency cost of debt. The latter is partly due to potential wealth transfer from bond to equity holders through assets substitutions. Thus Easterbrook (1984) note that by paying out dividends and then raising debt, new debt contracts can be negotiated to reduce the potential for wealth transfer. We start our analysis by testing the partial adjustment model of Lintner (1956) According to the Lintner each firms i has target dividend pay-out ratio (ri). By using the target pay-out ratio Lintner calculated the target dividend at time (Dit*) as percentage of net earning of the firms i at the time t, the relationship is given below:

D it * = ri Eit (Eit)(1)

In reality the dividend which firms finally pay at time t (Dit) is different from the target one (Dit*). Therefore, it is more reasonable to model the change between the real dividends at time t-1, instead of the real dividend at time t only. By taking the change in real dividend into account it is realistic and consistent with the long run target pay-out ratio, it is assume that the real change in dividend at time t (Dit- Dit-1) equal to the constant portion (ai) plus the speed of adjustment to the target dividend at time t (Dit*- Dit-1). Since the target dividend at time t is a proportion of the net earnings at the time t, the final model become as follow:

Dit- Dit-1= a +ci ri Eit ci Dit-1(2)

Where Dit is the actual dividend paid by the firms during period t, Eit is the net earnings of the firms during the period t; ci is the adjustment factor which shows the speed of adjustment of dividends, at the time t-1, to optimum target pay-out ratio of dividends at time t and rt is the target pay-out ratio. This theoretical model can be estimated using the following econometric model:

?Dit =a + 1 Eit + 2 Dt-1 +eit(3)

Where ?Dit is the change in dividend form time t-1 for the firm i, 1 represents the ci times rt of the theoretical model 2 is represent the variable ci of the theoretical model with negative sign (2 = -ci) and eit represent the error term. Fama and Babiak (1968) extend Lintner (1956) model by incorporating one more explanatory variable that is the difference between the current earnings and previous earnings of earnings without constant term:

Dit=a + 1 ?Eit + 2 Dt-1 +eit(4)

Where Dit is the dividend of the firm i at the time t, ?Eit the change in income to the stockholders, at the time t and the time t-1 and eit is the error term. We estimate the above model by taking the ?DPSit is the change in dividend per share of the firm i at the time t as dependent variable and ?EPSit , is change in earning per share at the time t as explanatory variable and the model becomes as follow:

?DPSit = a +1 EPSit +2 ?DPSt-1(5)

Table1 reports the parameter estimates obtained for the dividend model. The coefficient on the lagged dependent variable (dividend) a varies from 0.22 obtained from GMM estimations to 0.58 when ordinary least square level is used by pool, fixed effect random effect. Though the speed of adjustment (1-a) lies within the range of 41to 77.73%. This suggests that there are some unobserved individual firm's effects on the dividend smoothing behaviour which are not captured by this model and cause a large variation in the speed of adjustment. The coefficient of dividend declines from 0.58 to 0.27 in fixed effect method estimation which suggest the firm-specific factors effects in the dividend pay-out policy of Bombay stock exchange and the endogeneity is also an issue to deal with. Furthermore the coefficients of the dividends are significant with the fixed effect method. The other useful statistics is the implicit target pay-out ratio which is shown in the above table of partial adjustment model. The target pay-out ratio (/1-a) varies from 18 to 55 % and the significantly lower then the target pay-out ratio observed from the data. The coefficient of the determination R2 is also varies from 0.39 to 0.65.

Table 1:Evidence on Dividend Policy the table reports the results of extended dividend model of Lintner (1956) by applying GMM, pooled time series cross section data with common effect model (POOL), fixed effect model (FEM) and random effect model (REM).

?Dit =a + 1 Eit + 2 Dt-1 +eit

?Dit is the change in dividend form time t-1 for the firm i

Eit is the net earnings of the firms during the period t

Table 2: Dividend Stability Model

The table reports the results of extended dividend model of Lintner (1956) modified by using dividend per share and earning per share. The GMM, pooled time series cross section data with common effect model (POOL), fixed effect model (FEM) and random effect model (REM) are used as estimation technique

?DPSit = a +1 EPSit +2 ?DPSt-1

?DPSit is the change in dividend per share of the firm i at the time t.

?EPSit is the change in earning per share of the firm i at the time t.

After the analysis of the above models partial adjustment model and the model of Fama and Babiak (1968) we modify the model which by using the change in dividend per share as dependent variable and regress it on change in earning per share of current period and lagged term of change in dividend per share. The parameter estimates obtained from our dividend stability models are reported in above Table 2. The coefficient of the lagged term dividends a varies from 40 % by GMM estimation to 57 % by OLS when it's used in levels. The balanced panels have been used to estimate the above mentioned model. The results of the model show that the speed of adjustment (1-a) lies within the range of 42.5 %to 59.01 % by GMM method which suggest that the estimate techniques use in the model are appropriate. The random effect estimation shows that the extensive firm specific effects in the dividend policy in India. The endogeneity of the explanatory variables coefficient of dividends is taken account of when GMM is used as estimation technique against OLS but the significant level is reduced when the GMM is used to however, the variation in the significance is very small. On the other side the target pay-out ratio (/1-a) which is also shown in the above table1. The target pay-out ratio vary from 25 % to 38.49 % which is significantly equal to the observed target pay-out ratio which amounts to 30 % in full sample and 35.7 % in dividend paying firms sample. The coefficient of determination does not have the variation. The firms listed on Bombay stock exchange are continuously improving their target pay-out ratio by applying this model and we can say that the India's listed firms non financial are not smooth to pay their dividends.

The results of the adjustment of the speed and the target pay-out ratio when compared with the findings in the experimental studies, the Fama and Babiak (1968) find that for non-financial UK firms the average speed of adjustment approximately 0.37 slightly higher than Lintner (1956) findings of 0.30 and target pay-out ratio of 50% almost equal to the Lintner (1956). The Behm and Zimmerman (1993) for German listed firms find a speed of adjustment ranging from 0.13 to 0.58 and the target pay-out ratio lies between 25 to 58 %. Glen (1995) fined the speed of adjustment between 40 % in Zimbabwe and 90 % in Turkey and the target pay-out ratio between 30 % and 40 %. Belanes (2007) find the speed of adjustment in Tunisian listed firms which is 23.66 to 96.59 % and the target dividend pay-out ratio lies between 14 to 52.96 %. Our results regarding the speed of adjustment and target pay-out ratio are closer to findings of other developing markets for example Turkey and Tunisia however, less then the speed of adjustment and target pay-out ratio of Germany and United Kingdom. To sum up the test of the Lintner partial adjustment model and the modified model on the sample of Bombay Stock Exchange Listed non financial firms reject that dividend decision are not based on the long term target dividend pay-out ratio. However, there is an indication that the firms give the higher importance on stable dividend pay-out to signal their future profitability to minimize the agency cost.

Data Collected and Calculations of Stock Price Volatility

Data were collected from BSE Sensex and NSE Nifty for calculating return and volatility. Sensex is a basket of 30 constituent stocks representing a sample of large, liquid and representative companies. Due to its wide acceptance amongst the Indian investors, Sensex is regarded the pulse of the Indian stock market. Nifty is a well diversified 50 stock index accounting for 24 sectors of the economy. Hence these two indices were taken for the study. Data were taken from 1998 to 2008. Return is calculated using logarithmic method as follows.

rt = (log pt-log pt-1)*100


rt= Market return at the period t

Pt= Price index at day t

Pt-1= Price index at day t-1 and

log = Natural log

Inter-day Volatility

The variation in share price return between the two trading days is called inter-day volatility. Inter-day volatility is computed by close to close and open to open value of any index level on a daily basis. Standard deviation is used to calculate inter-day volatility. The inter-day volatility is calculated by close to close and open to open volatility method.

Close to close volatility

For computing close to close volatility, the closing values of the Nifty and Sensex are taken. Close to close volatility (standard estimation volatility) is measured with the following formula

s=v[(1/ n -1)? (rt - r`)2]


n = The number of trading days

rt = Close to close return (in natural log)

r`= Average of the close to close return

Open to open volatility

Open to open volatility is considered necessary for many market participants because opening prices of shares and the index value reflect any positive or negative information that arrives after the close of the market and before the start of the next day's trading the following formula is used to calculate open-to-open volatility:

s=v[(1/ n -1)? (rt - r`)2]


n = the number of trading days

rt = Open to open return (in natural log)

r`= Average of the open to open return

Inter-day volatility takes into account only close to close and open to open index value and it is measured by standard deviation of returns.

Intra-day Volatility

The variation in share price return within the trading day is called intra-day volatility. It indicates how the indices and shares behave in a particular day. Intra-day volatility is calculated with the help of Parkinson Model and Garman and Klass model.

Parkinson Model

High-low volatility is calculated with the following formula:

s=kv[1/ n ?log (Ht /Lt)2]


s = High-Low volatility

k = 0.601

Ht = High price on the day

Lt = Low price on the day

n = Number of trading days

Garman and Klass Model

The Garman and Klass model is used to calculate the open-close volatility. The formula for Garman and Klass model (1980) takes the following form.

s=v[1/ n ?(1/2{log (Ht /Lt)}2 -[2log(2)-1] [log (Ct /Ot) ] ]2


Ht = High price on the day

Lt = Low price on the day

Ct = Closing price on the day

Ot = Opening price on the day

n = Number of trading days

s = Intra-day volatility for the period


Year-wise Descriptive Statistics for Nifty

And Sensex (1998-2008)

The daily average return of the Nifty and the Sensex in the year 1998-99 was 0.00294 %and -0.02482 %respectively. The Nifty had positive return whereas the Sensex had negative return. The pressure of economic sanctions following detonation of nuclear service, woes of East Asian financial markets, volatility of Indian currency and the redemption pressures faced by the Unit Trust of India (UTI) in respect of its US-64 Scheme made the Nifty decline from 1212.75 in April, 1998 to 808.7 in October, 1998 and the Senses from 4280.96 to 2764.16. In the year 1999-2000, the Nifty and the Sensex return increased from 0.00294 % to 0.15606 %and -0.02482 % to 0.14112 % respectively. The union budget of 1999, strength of the Government and also its commitment towards second generation reforms improved macro economic parameters and better corporate results raised the return. In this year the growth rate of GDP and industrial sector was 6.4% and 6.6% respectively and within industrial sector, the growth rate of manufacturing sector was 7.3 %The trend got reversed during 2000-2001.The Indian economy decelerated and the Nifty and the Sensex yielded negative return of -0.09435% and -0.13788% respectively. There was a large sell off in new economy stocks in global markets. This brought down the Nifty from the height of 1636.95 in April, 2000 to the lower level of 1108.20 in October, 2000 and the Sensex from 5426.82 in April, 2000 to 3689.43 in October, 2000, the growth rate of GDP and the industrial sector declined from 6.4% to 6% and from 6.6% to 4.9% respectively. Within the industrial sector, the growth rate of manufacturing sector declined to 5% and the infrastructure sector also registered a lower growth as compared to that of the previous year. Scams have over and again proved the vulnerability of the regulatory network and system of the finance and capital markets in this year. Ketan Parek scam in the stock market resulted in a big default in Calcutta Stock Exchange, the BSE and the NSE. Several stockbrokers grossly misused the badla finance given to them by investors. FIIs investment was very low in that year. The above cited reasons were the major reasons for the negative returns. The year 2001-02 recorded positive return of 0.00317% but Sensex had negative return of - 0.01129%. The introduction of rolling settlement and derivatives encouraged FIIs and domestic investment even though markets were affected by riots in Gujarat, cyclone in Orisa, suspension of repurchase facility under UTI's US 64 scheme and the attack of World trade Centre, Indian Parliament and Jammu and Kashmir Assembly. The year 2002-03 recorded negative return of -0.05239% and -0.05568% in the Nifty and Sensex respectively. Morgan and Stanley Capital International Index value for India declined to 3.9 %. Failure of the monsoon, bomb blast in Ghatkopar area of Mumbai, the war between Indo-Pak border and tussle between US and Iraq had negative impact on the stock market. There was a subdued trend in both public and rights issue. The divestment programme of the public sector units was deferred and PSU stock price declined by 50%. In June and October 2002, the FIIs turned as net sellers, and their investments were -Rs.8660 mn and -Rs.8757 mn respectively. In this year a total of Rs.4070 crore was mobilised as against Rs.7543 crore in 2001-02. Banks and financial institutions were the main mobilisers during the year. All these factors led to the negative return in the Nifty and Sensex. The daily average return in the Nifty and the Sensex was the highest in the year 2003-04. Strong economic fundamentals exhibited in the fall in interest rates, strong GDP growth rate, increase in foreign exchange reserves and exports of Indian companies doubled the Nifty and the Sensex in the first three quarters. Further, the large expenditure by the Government on infrastructure sector and the reform process enhanced the morale and motivation levels of Corporate India which in turn boosted the stock market returns. The SEBI's ban on the Participatory Notes issued by unregulated entities made the markets more disciplined and investor friendly. Global liquidity had almost been drained off following the rate increases in the US, Europe and in Japan. The RBI had also done its bit in doing the same in India and a further movement in that direction cannot but had an adverse impact on the stock market. FII flows in 2006, at about $8.5 billion (around Rs 38,000 crore), were lower by 20% than in 2005. But this was due to the markets tanking in May and June. Pharma, ferrous metals, FMCG, oil and gas, and auto components did perform wellin that year. The year 2007 saw Indian stock markets scaling new peaks. During 2007-08 the secondary market rose on a point-to-point basis with the Sensex and Nifty rising by 47.1 and 54.8% respectively. Amongst NSE indices, both Nifty and Nifty Junior delivered record annual equity returns of 54.8% and 75.7% respectively during the calendar year. The Indian financial sector is on a roll. It has emerged as the third best performing market in the world with a dollar return of 71.23%. The popular Bombay Stock Exchange (BSE) benchmark index, sensex, also posted its highest ever absolute gain of 6500 points in over two decades. Simultaneously, the National Stock Exchange (NSE) has climbed to the top spot in stock futures contracts and number-two slot in the index futures segment in the world. Spices export from India has reached record levels and exceeded the target set for 2007-08.


Ups and downs in the share prices are quite natural in stock market. The bull and the bear markets have certain characteristics and the investors adopt different strategies in the bull and the bear markets. The rise and the fall of shares are linked to a number of conditions such as economic cycle, economic growth, international trends, budget, general business conditions, company profits, product demand etc. In the bull market, buy-hold approach is adopted and in the bear market sell-move out approach is adopted by the investors. Results of return during the bull and the bear phases are presented in the following table 2


Descriptive Statistics for Various Phases -Nifty and Sensex

Table 2 gives the descriptive statistics for various phases for the Nifty and Sensex. The durations of the bull and the bear phases are more or less similar for the stocks of the Nifty and Sensex. In the bear phase-A, they had negative return of -0.22900% and -0.25564% respectively. Nuclear tests conducted in May, 1998 and imposition of economic sanctions by the US, Japan and other industrialized countries resulted in uncertainty in the Indian stock market. In the bear phase, the FIIs net investment was negative and they were net sellers except in July and September 1998.The growth in macro economic factors like GDP, industrial sector and manufacturing sector turned out to be positive with good corporate results. FIIs average monthly investment was Rs.52.41 crore in the bull phase. This moved the Nifty and Sensex to newer peaks. There was a hike in the Nifty and the Sensex index level from December, 1998 to February, 2000.

The main calculations of the stock market volatility are shown in table 3, 4, 5 and 6. Stock market volatility indicates the degree of price variation between the share prices during a particular period. A certain degree of market volatility is unavoidable, even desirable, as the stock price fluctuation indicates changing values across economic activities and it facilitates better resource allocation. But frequent and wide stock market variations cause uncertainty about the value of an asset and affect the confidence of the investor. The risk averse and the risk neutral investors may withdraw from a market at sharp price movements. Extreme volatility disrupts the smooth functioning of the stock market. The literature on stock market volatility is voluminous, but, some general conclusions on common stock risk have emerged from this research. The overall stock market volatility has fluctuated over the time with no discernible trend and some authors have argued that volatility is higher during the bear markets. In this study, inter-day and intra-day volatility are calculated for each year and for different phases. Inter-day volatility of the Nifty and Sensex are given in table 3


Year-wise Inter-day Volatility for Nifty and

Sensex (1998-2008)

The close to close volatility and the open to open volatility in the Nifty and the Sensex moved in cycle. In the Nifty and in the Sensex, the close to close volatility ranged from 0.991% to 2.025% and 1.010% to 2.151% respectively. The open to open volatility in the Nifty and the Sensex ranged from 0.992% to 2.041% and 1.047% to 2.846 %respectively. The close to close and the open to open volatility in the Sensex was very high in the year 2000-2001.The loss was very high in Sensex compared to Nifty The entire financial year (2000-2001) of the stock market was in the grip of bears. From 1998 - 2003 the Sensex values were consistently higher than the values of the Nifty, in both the volatility. From 2004-2008 the close to close volatility was very high in Nifty. In the Nifty the open to open volatility was high in the year 1999 - 2000. In the Sensex the open to open volatility was high in the year 2000- 2001. The Nifty recorded negative return and a low volatility in the year 2002-2003. The close to close volatility in the Nifty was at their peak in 2007-2008. On 3rd September 2007 the value of Sensex was 15422.05 but on 28th September it was 17291.10. In the first half of October 2007 Sensex climbed from 18K to 19K in just four days. As a result circuit breakers were applied on October 16. Year-wise intra-day volatility for the Nifty and the Sensex are given in the table 4.


Year-wise Intra-day Volatility for Nifty and Sensex (1998-2008)

In the Nifty, both open-close and high-low volatility were very high in the year 2007-2008. In 2002-2003 open -close and high -low volatility was very low in Nifty and Sensex. But in the Sensex open-close volatility was high in the year 2000-2001 and high-low volatility was very high in the year 2007-2008. Except 2007-2008 the close to close volatility was low in Sensex compared to Nifty. Open- close volatility was low compared to other volatility and it ensures minimum fluctuation in the share prices within a trading day. High-low and open -close volatility moved alongside in the Nifty and in the Sensex. Open to open volatility was the highest of the four types of volatility; that indicates high flow of information.

Inter-Day and Intra-Day Volatility in Different Phases

The bear market had a negative return and the bull market had a positive return. To know the volatility during bull and bear phases the inter-day and the intra-day volatility is calculated. Tables 5 give the result of the inter-day volatility for various phases in the Nifty and the Sensex.


Inter - Day Volatility for Various Phases -Nifty- Sensex

Open to open volatility in the Sensex was higher than that of in the Nifty. Close to close volatility in the Nifty and in the Sensex touched its peak in the bear phase-C. It lasted for a very short period. The rise in gold and silver prices and the election result affected the market sentiments negatively. In the Sensex and in Nifty open to open volatility was high in the Bull phase-I. In general the close to close volatility in the bull phase was low compared to the close to close volatility in the bear phase. Close to close volatility in the bull phase and the bear phase in the Nifty and the Sensex moved in tandem with little difference. The intra-day volatility details are given in Table 6


Intra -Day Volatility for Various Phases -Nifty- Sensex

Open-close volatility is lower than the high-low volatility. In the Nifty and in the Sensex open- close volatility was high in the bear phase and low in the bull phase. The intra-day volatility in the bull phase moved down in all the indices. For Nifty the open-close and high low volatility was very high in the bear phase-B and in the Sensex it was very high in the bear phase-C.


The outlook for India is remarkably good. Corporations are experiencing high profits. The stock market is at a record high. Commodity markets are at their strongest. Lead manufacturing sectors such as software, textiles and steel have yielded dividends. The bull phases earned decent returns and the bear phases incurred loss. In the bull phases volatilities were lower than bear phases.

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