Efficiency of Bangladesh stock market: evidence from monthly index and individual firm data

Hassan, M. Kabir; Chowdhury, Shah Saeed Hassan

doi:10.1080/09603100701320178

Cited by 17 publications

(6 citation statements)

References 20 publications

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“…The results from VR tests consistently show that most of the economic sectors in DFM and ADSM are inefficient. Similar findings of serially correlated stock returns are also reported by Chakraborty (2006) and Hassan and Chowdhury (2008) for stock markets in Bangladesh and Pakistan. The recent methodological refinements to VR tests have prompted a number of studies to conduct a re‐examination of the stock market data in Asia (Hoque et al ., 2007; Kim and Shamsuddin, 2008), Europe (Smith, 2009), Middle East and Africa (Al‐Khazali et al , 2007; Ntim et al , 2007; Smith, 2007, 2008; Lagoarde‐Segot and Lucey, 2008).…”

Section: Full Sample Analysis With Fixed Parameter: Examining the supporting

confidence: 87%

The Evolution of Stock Market Efficiency Over Time: A Survey of the Empirical Literature

Lim

Brooks²

2011

Journal of Economic Surveys

313

152

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This paper provides a systematic review of the weak-form market efficiency literature that examines return predictability from past price changes, with an exclusive focus on the stock markets. Our survey shows that the bulk of the empirical studies examine whether the stock market under study is or is not weak-form efficient in the absolute sense, assuming that the level of market efficiency remains unchanged throughout the estimation period. However, the possibility of time-varying weak-form market efficiency has received increasing attention in recent years. We categorize these emerging studies based on the research framework adopted, namely non-overlapping sub-period analysis, time-varying parameter model and rolling estimation window. An encouraging development is that the documented empirical evidence of evolving stock return predictability can be rationalized within the framework of the adaptive markets hypothesis.

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Section: Full Sample Analysis With Fixed Parameter: Examining the supporting

confidence: 87%

The Evolution of Stock Market Efficiency Over Time: A Survey of the Empirical Literature

Lim

Brooks²

2011

Journal of Economic Surveys

313

152

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“…Historically the stock market was never halted from trading since its last discontinuation that occurred after the liberation war in 1971 up until the year 1976 (Hassan & Chowdhury, 2008). Since then, the stock market in the country has gone through many broad phases of change to consider for improvement.…”

Section: Overview and Transition Of Bangladesh Stock Market During The Covid-19 Pandemicmentioning

confidence: 99%

“…There was a remarkably massive technological transformation only after introducing the pandemic while referring to the previous significant technological transformation of automated trading facilities, which was introduced in the year 1998. The automated trading facilities started later in 2001, along with many other initiatives (Hassan & Chowdhury, 2008). Contemporary literature has pointed out that the cases and fatalities of the virus outbreak and proposed a relationship with the volatility in the stock market return (Ashraf, 2020b(Ashraf, , 2020a Zeren & Hizarci, 2020).…”

Section: Overview and Transition Of Bangladesh Stock Market During The Covid-19 Pandemicmentioning

confidence: 99%

What drives DS30 Index amid bourse lockdown decision? An emerging economy perspective

Faruq

2021

int.jour.sci.res.mana.

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This study measures the impact of the COVID-19 pandemic outbreak on the stock market of Bangladesh amid bourse lockdowns. The top 30 blue-chip companies listed in the DS30 Index of the Dhaka Stock Exchange are used as the sample for this study. Panel data regression analysis has been used after performing several diagnostics tests to assess the impact for January to December during the year 2020. The regression model used in the study considers three key aspects, namely COVID-19, firm-specific factors, and macroeconomic variables amid the bourse lockdown. This study finds that daily trend in affected cases, death cases and investors' attention significantly affect the stock market but does not show any negative relation to conclude. The Government imposed lockdown shows a negative relation with the stock market significantly. Firm-specific variables like daily market capitalization and book to market ratio show a significant negative relationship with the stock market. On the other hand, macroeconomic factors have a significantly positive impact on the stock market amid bourse lockdowns. This study assesses the performance of the Bangladesh stock market by use of DS30 Index listed firms during the COVID-19 pandemic in response to the Government imposed bourse lockdown. This study provides unique insights into how the Bangladesh stock market reacted during the pandemic, along with a rare bourse lockdown decision.

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“…This feedback trading makes the market more volatile in the short run, because in the long run, the stock prices tend to return to their true values. In respect of weak form efficiency of DSE, some researchers have done several works (Uddin & Khoda, 2009;Mobarek, Mollah, & Bhuyan, 2008;Hassan & Chowdhury, 2008;Uddin & Alam, 2007;Ainul & Khaled, 2005;Kader & Rahman, 2005;Sadique & Chowdhury, 2002;Koutmos, Negakis, & Theodossiou, 1993;Chowdhury, Sadique, & Rahman, 2001). But, it is rare in conducting VAR model in order to find the relationship between risk and return of DSE.…”

Section: Literature Reviewmentioning

confidence: 99%

Vector Autoregressive (VAR) Modeling and Projection of DSE

Hossain¹,

Kamruzzaman²,

Ali³

2015

CBR

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In this paper, vector autoregressive (VAR) models have been recognized for the selected indicators of Dhaka stock exchange (DSE). Bangladesh uses the micro economic variables, such as stock trade, invested stock capital, stock volume, current market value, and DSE general indexes which have the direct impact on DSE prices. The data were collected for the period from June 2004 to July 2013 as the basis on daily scale. But to get the maximum explorative information and reduction of volatility, the data have been transformed to the monthly scale. The outliers and extreme values of the study variables are detected through box and whisker plot. To detect the unit root property of the study variables, various unit root tests have been applied. The forecast performance of the different VAR models is compared to have the minimum residual. Moreover, the dynamics of this financial market is analyzed through Granger causality and impulse response analysis.

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Efficiency of Bangladesh stock market: evidence from monthly index and individual firm data

Cited by 17 publications

References 20 publications

The Evolution of Stock Market Efficiency Over Time: A Survey of the Empirical Literature

The Evolution of Stock Market Efficiency Over Time: A Survey of the Empirical Literature

What drives DS30 Index amid bourse lockdown decision? An emerging economy perspective

Vector Autoregressive (VAR) Modeling and Projection of DSE

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