There is no fixed number of variables that one has to incorporate in the PMF framework. As a result, procedures for selecting an appropriate set are informal at best. The lack of a defined framework is prominent given the highly correlated nature of many economic time series variables. Macroeconomic data are also vulnerable to measurement problems especially over short horizons Chen and Jordan, However, as the study by Chen and Jordan demonstrate there is insignificant difference in terms of results when both exploratory factor and pre-specified macroeconomic factors approaches are compared but PMF seems to perform better.
After personal meetings with the officials of Bangladesh Bank Statistic Dept. Besides, inflation is a controversial issue in Bangladeshi politics and its data is reported to be manipulated. The variable term structure faces similar problems. In Bangladesh, the use of Bond and T-bill is still infrequent. During periods t-bill rate and bond rate have remained unchanged month after month which is why it is not included in the regression. All these factors are found to be priced in various studies in varying contexts.
To test the APT using pre-specified macro-economic factors, following two-pass regression methodology is used for the period There are total observations instead of as the macro variables are measured in rates of change instead of absolute values. The rate of change is calculated using logarithmic differencing which renders the series stationary.
The coefficients of factor sensitivities in the 2 nd pass regression measure the size and significance of the estimated risk premium related with each macro factor. The whole process is repeated to obtain regression results for two sub-periods: i December to November ii December to November The reason for this division is to account for the implausible movements in DSE index that occurred during periods as well as periodic fluctuations of DSE index that originate from speculation of political events and unidentified reasons.
Moreover, regressions on sub-periods help to analyse stability factor. A sub-period needs to contain 60 months as a prerequisite to effect substantial interpretation of results according to CRR methodology. Stock returns data are collected in Compact Disk format from the office of Dhaka Stock Exchange and put into time series form. The IFS database contains time series data for over two hundred countries in the world on a wide range of economic topics. However, the IFS database does not contain recent figures onward for macro-variables that are used in this study.
Moreover, it has a few missing observations it its time series data. The missing observations and recent estimates of macroeconomic variables are collected from Monthly Economic Trends of Bangladesh Bank- a monthly journal available on its website. This is so because in developing countries data is not recorded and preserved well. The key institution responsible for recording data in Bangladesh is Bangladesh Bureau of Statistics, and it is found that it does not have recorded macro variables data prior to The statistic department of Bangladesh Bank publishes Monthly Economic Trends but it does not preserve macro-variables in time series format.
Moreover, after personal investigation, the researcher finds that neither Bangladesh Bank nor Bangladesh Bureau of Statistics have developed statistically reliable data recording process. One instance of this is found in various copies of Monthly Economic Trends in which figures for the same indicator is found to be different in various issues. The stock return dataset contains seventeen missing observations.
To proxy for all these observations similar industry return data is used. Furthermore, in developing countries macroeconomic data is reported to be manipulated in favor of the government. Three stocks are found to be negatively skewed and some stocks demonstrate very high Kurtosis e. The standard deviation of the overall stock return data is medium. Dhaka Stock Exchange: Some Findings During a transition of government in the DSE index has risen sharply without any reference to the market fundamentals. The instances of such fluctuation are a common characteristic of DSE.
As recent as in Dec the DSE index rose to all-time high and then plummeted and then mounted again followed by a steep fall. All these events have taken place in a week s time. Furthermore, in Bangladesh the processing of new information is weak because of the presence of a large number of non-actively traded shares and inadequate institutional background for broker houses and mutual funds. In conjunction with all these facts and results Mollik and Bepari find Dhaka Stock Market to be weak-form inefficient while a study Mollik and Bepari , by the same authors investigates beta-instability in DSE over a period of and show that beta is highly unstable and this instability increases with holding periods.
Index 0. Index After rotation of all variables three components are retained according to Kaiser s variance criterion which suggests to retain those factors with Eigenvalues total variance accounted for each factor equal or higher than one. The rotation is varimax which produces orthogonal factors.
This implies that problems of multi-collinearity are removed and dimensionality of the original variables is reduced. The pattern matrix in Table 2 and 3 offers a concise picture of the relevance of each variable in the principal components. Component factor 1 Table 2 indicates industrial production index and money supply since these have the highest factor loadings correlation with the factor scores in it while Component 2 represents import and export for similar reasons.
Component 3 refers to exchange rate, bank rate and inflation. The coefficients of all respective components show positive sign. Communality is the variance that is unique to the variable and not shared by other variables e. The total variance explained by all factors in Table 2 is Analogously in Table 3, export, money supply and import correspond to component 1 and exchange rate and industrial production represent component 2. The last component represents remaining factors by its corresponding high loadings and total variance accounted for all components is Similar process is employed to extract PCs for the period One period has 23 regressions and a complete set e.
The R2 range and F-value range exhibit medium strength compared to other studies e. Gunsel and Cukur, The range of the F-value shows similar fluctuation from 3. Most of the values in both F-test and R2 range however, lie in the middle of the highest and the lowest value. The large fluctuation implies some stocks are inactive while others are hyper-active and equities varying degree of responsiveness to macro factors.
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Similarly, the F-value and R2 range show large variation when regression is done using PCs in all the three periods. The highest value for F-statistics and R2 are 9. To check serial correlation of stock returns data Breusch-Godfrey LM test is carried out after each of regressions. Table 4 and 5 demonstrate whether autocorrelation is present in the results. Some of the tests in both tables are done using 12 degrees of freedom since observations one year ago can influence present value.
The results in other periods show no autocorrelation. Table 4 exhibits presence of autocorrelation in three cases where as Table 5, for that matter does in one instance. Thus evidence of autocorrelation is minimal. This result is comparable to that of Gunsel and Cukur and Febrian and Herwany However, high t-values of constant indicate association of additional state variables that are not included in the study.
From the preceding section it is known that component2 represents export and import and they exhibit negative relation with the stock returns. The R2 shows low value in sub-period and in other periods it is comparatively higher though not high enough to render the results stable.
This result is similar to what is found for Finnish Stock market by Martikainen et al. But since regression contains only 23 observations F-test becomes predictable. Breusch-Pagan test of heteroskedasticity shows only results obtained in sub-period are not heteroskedastic.
In a similar pattern Table are analysed below. The result in Table 7 shows the existence of one significant factor at 0. The corresponding significant factor is exchange rate which is also found to be priced in an Indonesian stock market in a study by Febrian and Herwany The R2 shows relatively higher values particularly in periods when it is The constants are significant in all cases and test of heteroskedasticity is not passed in any cases.
To correct for heteroskedasticity different functional forms are attempted for dependent variable but these renders t-values insignificant after corrected forms of variable is regressed. This is consistent with the result found in Asprem , Chen et al. Although there is no theoretical basis for the signs of state variables as noted by CRR yet their signs are indicative of the plausible relation between stock returns and macroeconomic factors.
Table shows signs of inflation beta 2 and bank rate beta 4 to be negative while that of industrial production to be positive except for one period which is consistent with CRR and Febrian and Herwany findings. Although CRR finds five priced factors their results lack robustness which is fully addressed by Shanken and Weinstein in a seminal paper in which they use same data but find no significant factors in one of the sub-periods as opposed to five factors found in CRR for the same period. They only find one priced factor in the overall period of , thus subjecting CRR results to further scrutiny.
The F-values 1. The results in this study also show instability similar to that of Iqbal and Aziz as a consequence of low R2-adj. All in all, the findings exhibit similarities to those of Turkish, Pakistani and Indonesian stock markets as discussed in this section. This is encouraging because with longer time horizon and larger sample size the robustness of the results is likely to be augmented. A Wider Context of the Results Overall, the results demonstrate the existence of one priced factor in DSE but after correcting for heteroskedasticity t-values become insignificant. The possible reasons are numerous.
DSE is shown to be weak-form inefficient market Mollik and Bepari, Moreover, evidence explored in the following suggests that artificial maneuvering by large investors frequently leads to unexpected fluctuation in stock prices with no relation to market fundamentals.
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Since DSE is a small market a syndicate of traders who own large volume of shares would be able to control share price. There are 27 broker houses for a total number of 3. Despite the increase in number of investors, the numbers of broker-houses remain proportionately lower.
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The number of broker-houses in Bangladesh is proportionately lower than that of Karachi Stock Exchange in Pakistan which has over broker-houses for a population of over million. On 20th Jan stock market has had to be suspended as DSE index fell by points in five minutes time. However, such events have occurred in last one month since 20th Jan 11 as fig. Following the incident, the stock-market regulators suspended six stockbrokers for one month on charges of manipulation in the secondary market Daily Star, Jan An ex-governor of Bangladesh Bank says the recent failure in the stock market could not have happened if responsible perpetrators were punished in stock market bubble as referred to in previous sections Financial Express, Jan c.
Various media reports bring out the following features of DSE: limited access to information, city centred trading, imperfect trading system and inadequate learning opportunities for market participants, limited choice for investors in terms of diversification, and poor regulation, all contribute to the current events of DSE which moreover, are characteristics of frontier stock markets in general. Limitation of Findings This study has limitations in different dimensions. But data are not available in Bangladesh to extend the time-period of the study. The number of stocks selected for this study is small.
With a larger sample size, the robustness of the results is expected to increase. Important factors like unanticipated inflation and term structure rates are not incorporated in the regression as in CRR since relevant data and context, as explained in the previous section, are not found. Finally, the research is conducted only on one frontier stock market. A comparison with other frontier stock markets would be insightful.
To address the problem of multi-collinearity in macro-variables, this study uses principal component analysis. Only exchange rate is found to be priced out of seven macroeconomic variables. However, the results should be treated with caution as the significance of t-values has altered after correcting for heteroskedasticity. The focus of this research is a frontier stock market, and it is a first of its kind in this respect since previous studies are administered in the context of secondary emerging, advanced emerging and developed stock markets.
The noisy market hypothesis argues that prices can be influenced by speculators and momentum traders , as well as by insiders and institutions that often buy and sell stocks for reasons unrelated to fundamental value ; see Noise economic. The adaptive market hypothesis is an attempt to reconcile the efficient market hypothesis with behavioral economics, by applying the principles of evolution to financial interactions.
An information cascade , alternatively, shows market participants engaging in the same acts as others " herd behavior " , despite contradictions with their private information. Copula-based modelling has similarly been applied. On the obverse, however, various studies have shown that despite these departures from efficiency, asset prices do typically exhibit a random walk and that one cannot therefore consistently outperform market averages "alpha".
See also John C. Note also that institutionally inherent limits to arbitrage —as opposed to factors directly contradictory to the theory—are sometimes proposed as an explanation for these departures from efficiency. From Wikipedia, the free encyclopedia. This article includes a list of references , but its sources remain unclear because it has insufficient inline citations. Please help to improve this article by introducing more precise citations. December Learn how and when to remove this template message. Index Outline Category. History Branches Classification.
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