Impact of Foreign Exchange Reserve, Exchange Rate and Crude Oil Price on
Dhaka Stock Exchange Index: An Empirical Evidence from Vector Error Correction
Model
Uttam Golder
Lecturer
Department of Finance and Banking
Jashore University of Science and Technology
Jashore-7408, Bangladesh
E-mail: [email protected]
Md. Nazrul Islam
Assistant Professor
Department of Finance and Banking
Jashore University of Science and Technology
�Jashore-7408,
Bangladesh
E-mail: [email protected]
Md. Shahidullah Kayser
�Assistant
Professor
Department of Finance
Jagannath University
�Dhaka-1100,
Bangladesh
E-mail: [email protected]
Abstract
The supreme thrust of the present
analysis is to explore the influences of foreign exchange reserve, exchange
rate, and crude oil price on the stock index of the Dhaka stock exchange (DSE)
of Bangladesh. Moreover, this study evaluates the identity of any
unpremeditated relationship among the variables from the viewpoint of an emerging
country like Bangladesh. Through using monthly time-series data, this study
tries to discover the evidence of a long-run affiliation among the variables by
using Johansen�s Cointegration test and Vector Error Correction Model (VECM). Besides,
the Granger Causality technique is introduced to examine the casualty among
variables where the empirical results show a causal linkage between the Dhaka
stock exchange index, foreign exchange reserve, and exchange rate, moving only
in one way from Dhaka stock exchange index to foreign exchange reserve and
exchange rate. In contrast, no causal link was identified between Dhaka stock
exchange indexes and crude oil prices. Lastly, Impulse Response Function
suggests a permanent effect of all selected macroeconomic factors on the Dhaka
stock exchange index in the long run and Variance Decomposition Analysis
settles that, the reform in Dhaka stock exchange index can be caused by the innovation
in foreign exchange reserve, exchange rate, and crude oil price.
� Keywords: � �Crude Oil Price, DSE Index, Exchange
Rate, Foreign Exchange Reserve, VECM. . � �
1. Introduction
Stock market
indices are useful overall scores that show a clear historical record of market
prices and thus allow investors, advisors, and the public to measure what the
present state of stock price trend happens to be. It is also noticeable that
company stock price may not always in the identical path as per the market
index, rather it can be opposite to the trend. Indices are subject to
fluctuation, so it is of great importance to determine the factors that play an
imminent role in deciding the trend �(Khan & Yousuf, 2013). Among some significant
macroeconomic factors that affect market index, this paper cautiously picked up
foreign exchange reserve, exchange rate, and crude oil price as the explanatory
variables and explored the relationship pattern among them.
���� In general, one country
differs from another in different points of view, such as its population,
geography, level of education, development status. It is expected that
Bangladesh will be a developing country from the least developed country (LDC)
in 2024, where three indicators require proper positioning of gross national
income, index of the human asset, and economic vulnerability. For Bangladesh,
it is a difficult challenge, and the most pressing need to meet this challenge
is to achieve economic viability. In this case, the foreign exchange reserve
can play a significant character in maintaining the confidence of a country's
economic market. However, nowadays, it is a debating issue whether excess
foreign exchange reserve is good for the economy of any country or creates some
opportunity and social costs for the country (Mezui & Duru, 2013).
���� The exchange rate is another
problematic issue that often leaves policymakers in a dilemma. No country in
the world is self-sufficient; therefore, one country has to relay on another
for making both import and export, which requires the exchange of currencies. Indeed,
the increase of the exchange rate (devaluation of the currency) discourages the
importer, just as it encourages the exporter and vice versa. Therefore,
different countries decrease or increase their exchange rate according to their
different policies, which in sequence influences the capital market in different
ways through the production and sale of the products.�
���� Without energy, the whole
world is untouchable, and hence every country has to rely on crude oil for
irrigation in agriculture and production in the industrial sector. Not all the
countries in the world have oil reserves, and for this reason, many countries
have to manage their production depending on the oil imported from other
countries. The real situation of the stock market of countries in which
countries conduct agricultural operations and industrial activities with
imported oils is generally different from those countries which do not need to
import oil.�
���� Previously, numerous
macroeconomic variables were used by many researchers to unveil the connection
of these variables with the stock returns in different stock exchanges of
different countries, including the Dhaka stock exchange (DSE) of Bangladesh.
The impact of these variables is not same always due to the different contexts
and nature of the market (Chauque & Rayappan,
2018). Several theories are applied to explore the
intensity of the linkage among the variables. The time frame was also an
essential factor to be considered as the researchers pondered different time
range to conduct their study. However, authors of this paper are highly
persuaded to inspect the influence of foreign exchange reserve, exchange rate,
and crude oil price on the stock index and also inspect the cointegration among
the variables in the context of DSE, Bangladesh. Although many other scholars
have already explored the influence of the chosen variables in different stock
markets (Hasan, 2018; Kibria et
al., 2014; Zaidi, Ahmed, & Siok, 2017) the nature and context of Dhaka
Stock Exchange (DSE) vary from their observed markets which is the ultimate
motivation of the authors in conducting this study.
���� This study aims to know
whether the foreign exchange reserve, exchange rate, and the crude oil price
have a long-term consequence on DSE index. The status of a causal linkage
between the variables is another exploratory question that leads to determining
the aim of the paper. Another query that comes to the authors' investigative
mind is that, if the background of the stock market changes, then what will be
the difference in the result comparing to the past literature?
The researchers,
therefore, find interest in re-examining the long-run influence of foreign
exchange reserve, exchange rate and crude oil price on the stock index in a
different setting by exerting Johansen's Cointegration test and VECM. Besides,
the paper observes the presence of any causal affiliation among the dependent
and explanatory variables via the Granger Causality approach.
���� This study has some practical
implications in the real field and is equally essential for students,
academicians, and policymakers of government. The adverse effects of foreign
exchange reserve and crude oil prices are shown here with the finger-pointing.
In short, the results of the study can help one to easily perceive how an
importer and exporter can be benefited or suffered due to adverse fluctuations
in the exchange rate.
2. Literature Review
2.1 Foreign Exchange Reserve and Stock Index
Foreign
exchange reserve includes the deposits of foreign currency and bonds. However,
in the broader sense, it is a country�s holdings of gold, SDR, and reserve of IMF
for meeting its short to medium term international financial liabilities (Maheshwari, Upamannyu,
Bhakuni, & Saban, 2013). Generally, this reserve is used to settle the payment of imported goods
and services and repayment of international loans taken by individuals and
government. Moreover, multinational companies send their royalty and profit to
their parent firms in international currencies. The importer can easily open
L/C with a minimum cost because the foreign exporters consider the importing
country less risky and are assured of receiving their money in time. It
stimulates the stock index of the importing nation as it can import raw
materials and capital goods for its production, which increases the firm�s
profit by selling produced goods and thereby flourishing stock index.
���� There is
a maxim, �nothing excess is good.� Though adequate reserve is considered
blessings for any country, the excess reserve also has some adverse effects. If
an import-oriented country can repay its import payment for the next three
months, it is expected that the country has a standard reserve. The most
troublesome negative impact of the excess reserve is the opportunity cost (Mezui & Duru, 2013). The central bank has to hold reserve either in
direct currency or in extremely liquid financial assets that can be converted
into cash with a little cost.
���� Furthermore,
direct currency does not earn any interest, and the extremely liquid financial
asset earns low yield. If the excess reserve were possible to invest in another
productive sector, it would profit more, and the economy would be more flourished.
Besides, the excess reserve is shaped when import payment is decreased
continuously due to the decline in the import of raw materials and machinery
used in the local industry.
2.2 Exchange Rate and Stock Index
The interrelation between
exchange rate and stock performance has long continued a topic of debate. Several
scholars consider the exchange rate as a double-edged blade as it converts one
currency into another and displays an incongruous effect at the same time.
There are two popular theories of the exchange rate, namely the flow-oriented
and stock-oriented models (Fauziah,
Moeljadi, & Ratnawati,
2015). Flow
oriented theory (Dornbusch & Fischer,
1980) postulates that the exchange
rate influences the nature of competitiveness of a business in international
markets by affecting the rate of interest, profit, production, and mostly on
the worth of the share of the respective firm. The influence of the movement of
the exchange rate is different from the organization, which is operated in the
international market from that of the local market. If the firm is
export-oriented, an upsurge in the exchange rate (devaluation of local
currency) will appreciate the exporter, and higher growth in export will lead
to higher profit and, ultimately, the share price will increase. Khan, Khan, Ahmad, and
Bashir (2018) studied
the monthly stock price data of 15 firms of Pakistan from the period of 2008 to
2012, and they confirmed a positive influence of the exchange rate on stock yields
through using the OLS regression model.
���� Similar findings were shown by Khalid and Khan (2017) who found a positive impact of the exchange rate
by analyzing time series data from 1991 to 2017 in Pakistan. However, it will
create a burden for import dominated industry by increasing the cost of
imported raw material and thereby increasing the cost of production. It
decreases the earnings of the firm, which also makes a decline in the stock
price. Ndlovu, Faisal, Resatoglu, and T�rsoy (2018) inspected the affiliation between stock yield and
macroeconomic indicators in the context of South Africa from 1981 to 2016 by
using a vector error correction model. They concluded that the exchange rate possesses
a negative impact on share values. A downturn in the exchange rate (encouragement
of local currency) will encourage importer, and thus the cost of production
will be lower. It will create a high demand for domestic products, and the firm
will earn more profit, which results in an upsurge in the share price. However,
this arrangement will hamper the earnings of export-oriented firm and thus
decreases the price of stocks. �
���� Stock oriented theory (Frankel, 1993) states that there is a high capital inflow if the
stock return is increased. Investor�s insight into the capital market is very
much crucial for the fluctuation of the stock price. If the price of the stock
is increased, it will make a positive perception about the domestic stock
market, and individuals will tend to invest in the local market by selling
their foreign stocks and thus there will be a high demand for the local
currency which will decrease the exchange rate by appreciating the worth of the
domestic currency.
2.3 Crude Oil Price and Stock Index
Changes
in the international oil price are measured as a vital issue for analyzing the change
of the stock market index (Giri & Joshi, 2017). The influence of
crude oil prices on the stock index is mixed that depends on the ground that
whether the state is an oil-exporting or importing one. If the nation is an
exporting one, a rise in oil price will upsurge cash inflow, and thereby the
earnings of the company will be expanded, which will be reflected in the stock
index. Consequently, income from exporting oil will increase public expenditure
and create new investment opportunities. As per the findings of many
researchers, the oil price possess a positive reaction on the stock index (Shafi, Hua, Idrees, &
Nazeer, 2015). The effect
of the crude oil price was also found positive in China (Hosseini, Ahmad, & Lai,
2011).
���� On the
contrary, some others suggested that in the oil-importing state, there is an
inverse relationship. The country whose production activities largely depend on
imported oil, an upsurge in oil price, makes a significant contraction in its
economic progress and decreases the stock index (Khan & Yousuf, 2013). Extensive shipping and production costs may lower
the demand for the produced goods and lower the company profits, which can
disincline the investor to purchase the share of the particular firm, and
consequently, the stock index decreases (Miller & Ratti, 2009). Similar findings were reported in the stock
exchange study, showing an adverse outcome of the oil price on stock return
covering the year 1979 to 2014 (Giri & Joshi, 2017).
3. Methodology
3.1 Characterization of Data
This study has been conducted
adopting monthly historical data ranged from July 2008 to October 2019. The
index of Dhaka Stock Exchange is extracted from the authorized database of the
company and the other two macroeconomic variables out of three, e.g., foreign
exchange reserve and exchange rate were collected from the monthly publications
(Monthly Economic Trends) of the central bank of Bangladesh (Bangladesh Bank, 2019). The
data of the latter variable (crude oil price) was taken from the IFM�s primary
commodity prices (International Monetary
Fund, 2019). For
handling extreme values, all the variables have been converted into their
natural log procedure and ensured the steadiness of the variables. However, the
variables are symbolized by LOGDSEI (natural log of all share price index of
Dhaka Stock Exchange), LOGFER (natural log value of foreign exchange reserve),
LOGER (natural log of the exchange rate of BDT for US dollar), and LOGCOP
(natural log of per barrel crude oil price in US dollar).
3.2 Conceptual Outline
This review
emphasizes on the estimation of any long-run affiliation between the index of
DSE and particular macroeconomic factors as well as defining the causal
relationship among them. For fulfilling the objectives, the econometric model
(1) was used:
���� Here, the variables have
already been defined.
��� �At first, unit root methods were carried to
confirm if the data is stationary. The regression outcomes will not be valid
unless the time series data is stationary. There are several methods for testing
the stationarity of the data, and each of these has been using widely in the
modern econometric arena. However, this study used both Augmented Dickey-Fuller
(ADF) (Dickey & Fuller, 1981)and Phillips-Peron (PP) (Phillips & Perron,
1988) unit root methods
to verify the stationarity of the data and to cross-check the results. After
that, the optimum number of lags was selected for conducting Johansen�s
Cointegration test, and VECM as those determine whether there is any long-run linkage
between the index of Dhaka stock exchange and foreign exchange reserve,
exchange rate, and crude oil price.����
���� Maximum likelihood process is
applied for examining the existence of a cointegrating vector for
non-stationary time series data (Johansen & Juselius,
1990). However,
the Johansen-Juselius technique is indirectly implemented
in Vector Auto-regression to assess the integrating association (Masuduzzaman, 2013) which is based on the equation
(2):
Where,
Where,
|
|
and |
|
���� Here, ∏ matrix
discloses disequilibrium adjustment and Γ matrix indicates an adjustment of short-run dynamic. Johansen & Juselius
(1990) propose two
tests to check hypothesis viz.�
Where, T= Size of sample and
Equation (3) shows the estimation of VECM with Dhaka stock exchange
index as the target variable:
���� Where,
���� However, the Cointegration
test only estimates whether the variables are correlated or not, but it does
not specify any information about the path of their causality (Hossain, Hossain, &
Sadi, 2013). Granger
causality test identifies whether the historical values of one variable
significantly affect in determining the forthcoming value of another variable.
This study tries to inspect whether the selected macroeconomic factors help
predict the fluctuation of the DSE index. Besides, it attempts to inspect
whether the selected macroeconomic variables are affected by the fluctuations
of the DSE index. Finally, impulse response function and variance decomposition
analysis were applied to reveal some insights about the variables. For
validating the selected model and ensuring its accuracy, this study applies
heteroskedasticity and autocorrelation test.
4. Results and Arguments
The outcomes of the unit root method set out in table 1 demonstrate that
both in the ADF and PP unit root test, all the variables are non-stationary at
the level. However, the variables are stationary at first difference both in
ADF and PP unit root method, indicating the refutation of the null hypothesis that
evidenced the nonexistence of unit root issue in variables at I(1).
Table 1. Results of Unit
Root Test
|
Variables |
From |
ADF |
PP |
||
|
C |
CT |
C |
CT |
||
|
t-stat |
t-stat |
t-stat |
t-stat |
||
|
LOGDSEI |
I (0) |
-2.4214 |
-2.1311 |
-2.4297 |
-2.1436 |
|
I (1) |
-11.4345*** |
-11.4997*** |
-11.4345*** |
-11.4997*** |
|
|
LOGFER |
I (0) |
-2.0635 |
-2.2474 |
-1.7199 |
-1.4113 |
|
I (1) |
-3.4092** |
-3.8031** |
-16.9305*** |
-17.0957*** |
|
|
LOGER |
I (0) |
-1.2528 |
-1.8446 |
-1.1579 |
-1.6675 |
|
I (1) |
-7.3832*** |
-7.3678*** |
-7.3351*** |
-7.3188*** |
|
|
LOGCOP |
I (0) |
-2.3052 |
-2.4450 |
-2.3404 |
-2.3415 |
|
I (1) |
-7.7746*** |
-7.7378*** |
-7.4110*** |
-7.3694*** |
|
|
Note: *** and ** represent 1% and 5% level of
significant respectively, C and CT refer to constant and constant plus trend
respectively. |
|||||
Source: Researchers' calculation
���� Table 2 exhibits the outcomes of lag
selection norms where the FPE and AIC recommend lag 3 as optimum; however, SC
and HQ signpost lag 2 as optimum. Moreover, the sequential modified LR test
statistic indicates 10 as the optimum number of lags. This study adopted the
AIC for selecting the optimum number of lag and used lag 3 as optimum lag for
further studies.
Table 2. Choosing of Lags
|
Lag |
LogL |
LR |
FPE |
AIC |
SC |
HQ |
|
0 |
585.5250 |
NA |
1.15e-09 |
-9.230556 |
-9.140515 |
-9.193975 |
|
1 |
1416.823 |
1596.620 |
2.76e-15 |
-22.17179 |
-21.72159 |
-21.98889 |
|
2 |
1492.146 |
139.8859 |
1.08e-15 |
-23.11343 |
-22.30306* |
-22.78420* |
|
3 |
1515.961 |
42.71574 |
9.54e-16* |
-23.23748* |
-22.06695 |
-22.76193 |
|
4 |
1527.525 |
20.00750 |
1.03e-15 |
-23.16706 |
-21.63637 |
-22.54519 |
|
5 |
1536.454 |
14.88128 |
1.16e-15 |
-23.05482 |
-21.16397 |
-22.28663 |
|
6 |
1554.249 |
28.52830 |
1.13e-15 |
-23.08331 |
-20.83230 |
-22.16879 |
|
7 |
1563.920 |
14.89060 |
1.27e-15 |
-22.98286 |
-20.37168 |
-21.92201 |
|
8 |
1582.394 |
27.27064 |
1.24e-15 |
-23.02212 |
-20.05078 |
-21.81496 |
|
9 |
1606.342 |
33.83190 |
1.12e-15 |
-23.14829 |
-19.81678 |
-21.79480 |
|
10 |
1627.403 |
28.41507* |
1.06e-15 |
-23.22861 |
-19.53694 |
-21.72880 |
|
Note: * designates lag order selected by the criterion. |
||||||
Source: Researchers' calculation
���� The evaluations of the
Johansen Cointegrating approach are depicted in table 3 to check the long-run connection
of the variables. This test is much responsive to slight changes to the lag
length, so this study uses one lag less than the optimum lag length selected by
the information criteria.
Table 3. Results of the
Johansen Cointegrating Test
|
CE(s) |
|
Trace Statistics ( |
5% Critical Value |
Max Eigen Statistic ( |
5% Critical Value |
|
|
r |
|
62.46252 |
47.85613 |
34.52087 |
27.58434 |
|
|
r |
|
27.94165 |
29.79707 |
14.86852 |
21.13162 |
|
|
r |
|
13.07313 |
15.49471 |
9.420578 |
14.26460 |
|
|
r |
|
3.652552 |
3.841466 |
3.652552 |
3.841466 |
|
|
|
Note:
r denotes the number of cointegrating linkages, CE(s) indicates cointegrating
equations and * signifies refusal of the hypothesis at the 0.05 level. |
|||||
Source: Researchers' calculation
���� The result identifies that
the null hypothesis (no cointegration between variables) cannot be accepted up
to the level of zero both in trace statistics and max Eigen statistics at a 5%
level of significance. It infers at least one cointegrating equation that
exists between the index of the DSE and other selected macroeconomic factors.
Table 4 shows the
coefficient of the long-run model with t statistics.�
Table 4. Long-Run Model
|
Exploratory Variables |
Coef. |
Std. Err. |
t-stat |
|
Constant |
-5.925886 |
- |
- |
|
Foreign
Exchange Reserve (LOGFER) |
-0.439875 |
0.10268 |
-4.28395*** |
|
Exchange
Rate (LOGER) |
2.688054 |
0.78237 |
3.43576*** |
|
Crude
Oil Price (LOGCOP) |
-0.514410 |
0.10774 |
-4.77445*** |
|
Note:
***, ** and * represent 1%, 5% and 10% level of significant respectively. |
|||
Source: Researchers' calculation
���� Based on cointegrating outcomes,
this study derives the following long-run relationship among variables:
���� Foreign exchange reserve is
identified to have a significantly negative (p<0.01) relationship with the Dhaka stock exchange index. This
result is coherent with the theory of opportunity and social cost (Mezui
& Duru, 2013) which postulates the negative
impact of the excess reserve on the economy of a country. Bangladesh is an
agrarian country, and till 31st October 2019, it has a total reserve of 32437.7
million U.S dollar (Bangladesh Bank, 2019) and by using this, it can meet
it's up to seven months import payment which is four months extra than usual.
Nevertheless, Bangladesh Bank does not invest those excess reserves in any
productive sector; thus, the opportunity cost is swelling day by day.
Generally, most of the foreign currency of Bangladesh comes from remittance,
and most of this through whom is earned is the working class. The local
beneficiary uses that remittance in different unproductive sectors, e.g.,
building the house, purchasing land, flat and consumer goods. As a result, this
excess reserve is not using for productive purposes and thus creating
opportunity cost. Due to lower import payment, the excess reserve is
increasing, which is not good news for the economy of Bangladesh, thus reducing
the country's production and enfeebling the stock market simultaneously. However,
these findings are conflicting with (Abakah
& Abakah, 2016; Akinlo,
2015; Hasan, 2018;� Ray, 2012) where they concentrated only on
reserve and did not pay attention to excess reserve and recognized that foreign
exchange reserve has a noteworthy positive influence on stock index.
���� The Exchange rate occupies a
positive and significant (p<0.01)
association with the index of the Dhaka stock exchange, which supports the
flow-oriented theory of Dornbusch and Fischer (1980). Currently, an upsurge in the exchange rate of Bangladeshi taka (devaluing
the money) in contradiction of the U.S. dollar encourages native exporters; thus,
an expansion of export upsurges company�s profit. Higher profit hints to an
increase in the value of a firm and thereby increase the stock index. This
finding is consistent with (Giri
& Joshi, 2017; Keat, Ling, Yi, & Yee, 2017; Kibria et al., 2014).
However, an opposite outcome is identified by (Ali, 2013; Chauque & Rayappan, 2018; Hsing, 2014; Khan & Khan, 2018; Khan & Yousuf, 2013) who elucidate that increase of
exchange rate (currency devaluation) forces the import dominated industry to
raise the price of the products. This action negatively influences the cash
inflow and thereby decreases the firm's profit, which negatively impacts the
stock index. Besides, the stock oriented theory of Frankel (1993)
states that if some stocks give a high return, investors tend to
purchase those stocks by selling foreign stock, which also appreciates local
currency, and thus exchange rate demonstrates a negative relationship with
stock index.�
���� The result ascertains a significant
long-run negative association (p<0.01)
between Dhaka stock exchange and crude oil price. This finding is certainly
consistent with (Dhaoui
& Kheraief, 2014; Giri & Joshi, 2017; Kamande, 2015)
where it has been concluded that oil-importing country faces high
importing cost due to raises of crude oil price. As Bangladesh is an
oil-importing country, the increased price of crude oil in the global market
puts pressure on the country�s economy. If the price of crude oil in the international
market rises, the losses in the domestic market increases. The price has to be
adjusted in the local market, which has a negative impact on all types of products.
Besides, crude oil is used not only in transportation, agriculture, and
production of goods as factory fuel but also in electricity generation. It may
lead to upsurges in the price of both agricultural and manufacturing products
of the country and negatively influences the stock market by decreasing the
stock index. However, this result is inconsistent with (Aigbovo
& Izekor, 2015; Khan & Yousuf, 2013) who investigated a long-run
positive linkage between crude oil price and stock index where the business
cycle and the global economic boom in energy, industrial and material sectors
were thought to be the primary motives.
���� Table 5 represents the
results of the error correction mechanism. As this study has a coefficient of
error correction term -0.099064, it signposts a 9.91 percent speed of
adjustment, which is significant at a 1 percent level. Finally, it postulates
that if there is an exogenous shock, it will make a 9.91 percent adjustment per
month to reach in the long-run equilibrium.
Table 5. Results of VECM
|
Exploratory Variables |
Coef. |
Std. Err. |
t-stat |
|
Speed
of Adjustment |
-0.099064 |
0.037143 |
-2.667100*** |
|
|
0.001053 |
0.088684 |
0.011875 |
|
|
0.051320 |
0.087986 |
0.583270 |
|
|
0.062330 |
0.203014 |
0.307024 |
|
|
0.090643 |
0.203210 |
0.446059 |
|
|
-0.695179 |
1.063916 |
-0.653415 |
|
|
2.175796 |
1.044064 |
2.083967** |
|
|
0.082852 |
0.078487 |
1.055608 |
|
|
-0.067637 |
0.075673 |
-0.893807 |
|
Constant |
-0.000498 |
0.003602 |
-0.138181 |
|
Note:
*** and ** represent 1% and 5% and level of significant respectively. |
|||
Source: Researchers' calculation
���� The outcomes of table 6 show
the effect of both heteroskedasticity and Breusch-Godfrey Serial Correlation LM
test, where the prob. value of Chi-Square is 0.1017 in heteroskedasticity test
that is more than 0.05; hence this study confirms the presence of homogeneity
in residuals. On the other hand, in the LM test, the prob. value of Chi-Square
is 0.2589, which is more than 0.05; hence this study also confirms the absence
of serial correlation in our model.�
Table 6. Results of
Heteroskedasticity and Serial Correlation Test
|
Heteroskedasticity Test: ARCH |
|||
|
F-statistic |
2.313901 |
Prob.
F(2,128) |
0.1030 |
|
Obs*R-squared |
4.571003 |
Prob.
Chi-Square(2) |
0.1017 |
|
Serial Correlation Test |
|||
|
F-statistic |
1.254885 |
Prob.
F(2,121) |
0.2888 |
|
Obs*R-squared |
2.702616 |
Prob.
Chi-Square(2) |
0.2589 |
Source: Researchers' calculation
���� The empirical results of table
7 demonstrate that there stands a causal bond between Dhaka stock exchange
index, foreign exchange reserve and exchange rate, moving only in one way from
Dhaka stock exchange index to foreign exchange reserve and the exchange rate
which indicate that if there is an upsurge or decline in the index of DSE, it
will affect in foreign exchange reserve and exchange rate. However, no causal linkage
is identified between Dhaka stock exchange indexes and crude oil prices.
��� Table 7. Results of Pairwise
Granger Causality Tests
|
Causality Direction |
F-Statistic |
Prob. |
||
|
LOGFER |
|
LOGDSEI |
0.43723 |
0.6468 |
|
LOGDSEI |
|
LOGFER |
15.9099*** |
7.E-07 |
|
LOGER |
|
LOGDSEI |
0.75989 |
0.4698 |
|
LOGDSEI |
|
LOGER |
3.37123*** |
0.0374 |
|
LOGCOP |
|
LOGDSEI |
0.87809 |
0.4180 |
|
LOGDSEI |
|
LOGCOP |
0.66622 |
0.5154 |
|
Note: *** represents 1% level of significant. |
||||
Source: Researchers' calculation
���� Figure 1 represents the shape
of the IRF of the Dhaka stock exchange index to an innovation in foreign
exchange reserve, exchange rate, and crude oil price. Along with their impacts,
this figure forecasts 36 months or 3 years of data plotted on IRF. The figure
shows, a one standard deviation innovation to its own stock index indicates a
substantial decrease in the Dhaka stock exchange index primarily. However, this
impact decreases with time and settles at a permanent level of 0.011 units
above the baseline. The impulse response of the Dhaka stock exchange index of 1
percent increased shocks coming from foreign exchange reserve leads to a
permanent increase in the Dhaka stock exchange index of 0.024 from the 24th
month, indicating a long-term positive relationship. A one standard deviation innovation
to exchange rate initially decreases the Dhaka stock exchange index, and after
the second month onward, it increases and settles at 0.001 units above the
baseline at a permanent level from 15th month. Lastly, a one SD innovation to
crude oil price causes the Dhaka stock exchange index primarily to fluctuate
positively, and it goes to a permanent level from 15th month at 0.011 units
above the baseline. So, in the long run, all the selected macroeconomic factors
have a permanent consequence on the Dhaka stock exchange index.
�Figure 1. Impulse Response
Function (IRF) for Dhaka Stock Exchange Index
Source: Researchers' computation
���� Table 8 limns the consequences
of variance decomposition analysis up to the 20 months, where it shows how much
of the Dhaka stock exchange index�s individual innovation is explicated by
movement in its individual variance along with foreign exchange reserve,
exchange rate, and crude oil price. The results show 20 months of forecast
where it demonstrates that most of the Dhaka stock exchange index variations
are elucidated by itself. In the 5th month, the Dhaka stock exchange index
explains 92.56 percent of variation by shocks to itself, 3.44 percent by
foreign exchange reserve, 1.18 percent by the exchange rate, and 2.81 percent
by the crude oil price. In the 10th month, the Dhaka stock exchange index
explains 76.95 percent of variation by shocks to itself, 14.41 percent, 1.19
percent, and 7.44 percent by foreign exchange reserve, exchange rate, and crude
oil price respectively. So, it can be marked that in the long run, the oscillation
in the Dhaka stock exchange index can be caused by the shock in foreign
exchange reserve, exchange rate, and crude oil price.
Table 8. Variance
Decomposition of LOGDSEI
|
Period |
S.E. |
LOGDSEI |
LOGFER |
LOGER |
LOGCOP |
|
1 |
0.031080 |
100.0000 |
0.000000 |
0.000000 |
0.000000 |
|
2 |
0.042843 |
98.42375 |
0.326756 |
0.209064 |
1.040433 |
|
3 |
0.051253 |
97.02071 |
1.247897 |
0.432370 |
1.299023 |
|
4 |
0.057761 |
94.87791 |
2.300499 |
0.906790 |
1.914802 |
|
5 |
0.062980 |
92.56092 |
3.441694 |
2.814805 |
|
|
6 |
0.067530 |
89.87707 |
5.007936 |
1.285298 |
3.829694 |
|
7 |
0.071705 |
86.93744 |
6.904513 |
1.304643 |
4.853406 |
|
8 |
0.075712 |
83.69416 |
9.218202 |
1.282202 |
5.805436 |
|
9 |
0.079590 |
80.36040 |
11.72187 |
1.243664 |
6.674061 |
|
10 |
0.083417 |
7.443114 |
|||
|
11 |
0.087172 |
73.62932 |
17.09730 |
1.143225 |
8.130148 |
|
12 |
0.090899 |
70.38924 |
19.78931 |
1.089306 |
8.732140 |
|
13 |
0.094568 |
67.32482 |
22.37082 |
1.036709 |
9.267651 |
|
14 |
0.098209 |
64.41157 |
24.86704 |
0.985325 |
9.736061 |
|
15 |
0.101792 |
61.69762 |
27.21236 |
0.936924 |
10.15309 |
|
16 |
0.105340 |
59.15295 |
29.43719 |
0.891030 |
10.51883 |
|
17 |
0.108829 |
56.79925 |
31.50659 |
0.848450 |
10.84571 |
|
18 |
0.112276 |
54.60755 |
33.44992 |
0.808625 |
11.13391 |
|
19 |
0.115663 |
52.58553 |
35.24971 |
0.771888 |
11.39288 |
|
20 |
0.119003 |
50.70796 |
36.93158 |
0.737727 |
11.62273 |
Source: Researchers' calculation
5. Conclusion
This study attempts
to visualize the empirical linkage between the Dhaka stock exchange index and
three designated macroeconomic factors, namely foreign exchange reserve,
exchange rate, and crude oil price with monthly time series data ranging from
July 2008 to October 2019. ADF and PP unit root tests were applied to ensure
the same integrating order of the variables and for cross-checking of the outcomes.
The Johansen Cointegration test was applied and found a long-run equilibrium linkage
between the Dhaka stock exchange index, foreign exchange reserve, exchange
rate, and crude oil price. It was observed that both foreign exchange reserves
and crude oil prices have a significant negative consequence on the Dhaka stock
exchange index in the long run, and the exchange rate was found to have a
positive influence on the Dhaka stock exchange index, which was also
statistically significant. This result confirms that the Dhaka stock exchange
index can be projected by past data. The coefficient of ECT exposed that a 9.91
percent of disequilibrium in the long-run model is rectified per month as the
Dhaka stock exchange index goes back to its equilibrium. The results of the
Granger Causality test divulged a causal association running in one direction
from the Dhaka stock exchange index to foreign exchange reserve and exchange
rate, indicating that if there is any change in the index of DSE, it will
affect in foreign exchange reserve and exchange rate. The impulse response
function supported the long-run model of the study, and the outcomes of
variance decomposition specified that the Dhaka stock exchange index is determined
by foreign exchange reserve, exchange rate, and crude oil price. �
���� From the above discussion, it
can be said that the Bangladesh government, policymakers, and economists should
be cautious in adopting any new economic policy as these selected macroeconomic
factors have a significant consequence on the capital market of Bangladesh. For
keeping the stock market afloat, the authorities need to be aware of economic
progress, sound fiscal policy, and, above all, proper management of different
macroeconomic factors that influence the stock market. Since the stock index
has a deep connection with the exchange rate, and both importers and exporters
are affected by it, the government should try to stabilize the exchange rate.
The authority needs to adopt a policy that will stabilize the value of
Bangladeshi taka against the US dollar, and at the same time, prevent
unforeseen fluctuations in the stock market.�
Bangladesh is an oil-importing country, so it is time to think about how
to reduce the dependence on crude oil and increase domestic energy production
and become more dependent on renewable energy. The use of locally produced and
renewable energy can improve the dynamics of the stock market by reducing the
cost of production. This paper also discusses the detrimental aspects of excess
reserve that may create social and opportunity cost. The government should keep
enough money from the foreign exchange reserve, and the rest should be used for
filling the funding gap of the infrastructure of the country.
���� However, this study has
uncovered some new avenues of future research for investigators. Only the
detrimental aspects of the excess reserve are discussed, but no guidance has
been given on how these excess reserves can be used in some productive sectors.
Regarding the exchange rate, both positive and negative aspects of currency
appreciation and devaluation are mentioned, but no guideline mentioned on what
degree of appreciation and devaluation may be useful for the economy of a
country like Bangladesh. So, there is a considerable scope to cover this area
in the future.
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