ArticlePDF Available

Abstract

International trade and the exchange rate are important to an economy of a country. Both emerging and emerged countries have tried to learn the patterns involved with the international trade flow and foreign exchange rates, expecting to leverage the countries’ economic development and stability. Learning and attaining the knowledge of these will sustenance the country to recognize the behavior of the imports and exports. The investigators have used many analytical and econometric models to learn the patterns. Big Data Analytics technique could be used to analyze the impact of the relationship and extend the findings to predict the exchange rate of a country and the international trade flow of the country. There exists a possibility to a country to extend the predictions to prescriptive analytics and improve the trade performance. When reviewing the empirical findings, it proves that there exist many investigations on learning the impact of exchange rate volatility on the imports and exports. The imports of countries are overlooked in the literature and knowledge of the relationship between, exchange rate volatility and import volume will support to pursuit for a beneficial trade and prevent or be prepared for a much more stable situation within Sri Lanka.
1st Author et al, International Journal of Robotics and Information Technology, Volume 1, Issue 1, January 2018, Pg: 1-3
Analysis of Foreign Exchange Rate
Volatility on International Trade
RV Sahabandu 1, PPGD Asanka 2
1Designation, Faculty of Graduate Studies, Sri Lanka Institute of Information Technology,
Malabe, Sri Lanka
Vasana@live.com
2Designation, Faculty of Graduate Studies, Sri Lanka Institute of Information Technology,
Malabe, Sri Lanka
dineshasanka@gmail.com
Abstract
International trade and the exchange rate are important to an economy of a country. Both emerging and emerged
countries have tried to learn the patterns involved with the international trade flow and foreign exchange rates,
expecting to leverage the countries’ economic development and stability. Learning and attaining the knowledge of these
will sustenance the country to recognize the behavior of the imports and exports. The investigators have used many
analytical and econometric models to learn the patterns. Big Data Analytics technique could be used to analyze the
impact of the relationship and extend the findings to predict the exchange rate of a country and the international trade
flow of the country. There exists a possibility to a country to extend the predictions to prescriptive analytics and
improve the trade performance. When reviewing the empirical findings, it proves that there exist many investigations
on learning the impact of exchange rate volatility on the imports and exports. The imports of countries are overlooked
in the literature and knowledge of the relationship between, exchange rate volatility and import volume will support to
pursuit for a beneficial trade and prevent or be prepared for a much more stable situation within Sri Lanka.
Keywords: Exchange Rate, Volatility, Trade flow, Big-Data.
1. Introduction
The imports are important to a countries economy and it plays a major role in the international trade.
The economic liberation of Sri Lanka in 1977 resulted in drastic changes in many aspects of Sri Lanka.
Considering about 1978 to 2015, the country yearly import demand represents over 30 percent share of the
gross domestic product (GDP) except 1984, 2009, 2010, 2013 – 2015 [1].
Investigations and the studies on a countries’ imports are surprisingly overlooked as there are several
studies and analysis being carried out focusing only the aggregated export volume concerning the exchange
rate volatility. It is less to find investigations on the relationship between exchange rate volatility and
import demand of a particular country. Based on the literature there are several investigations have been
carried out on the relationship between exchange rate volatility on international trade, trade balance/
balance of payments, import flow, export flow in the context of both the emerged and emerging countries.
Many approaches have been utilized to come to certain findings and results. In many studies, the authors
have used ARCH based approaches to recognize the exchange rate volatility. Co-integration technique is
being used to discover the behavior of long-term results while some have used it to prove or validate the
hypothesis.
1
©Copyrights IJRIT, www.ijrit.net
1st Author et al, International Journal of Robotics and Information Technology, Volume 1, Issue 1, January 2018, Pg: 1-3
The imports of a country have a relationship to many economical direct and indirect factors of a
country. International trade, economic growth, the balance of payment, trade balance, monetary policy, the
exchange rate is few of those factors.
Sri Lanka as an emerging country it is a must to concern and try to resolve the problems related to the
above-mentioned factors to confirm the stability of the economic factors within the country. Currently, the
unbalanced effect of BOP has become a crisis and deterioration in the Sri Lankan economy [2] [3]. It is true
that it is caused due to multi-factors and not only of imports of the country. But it is still worth analyzing
the country’s imports rather than setting the policies under the uncertain future and it is crucial to have a
long-term measure to overcome the current BOP crisis. However, the balance of trade (BOT) of a country
contributes a large share of BOP. BOT is simply the difference between the exports and imports of a
country for a defined time period. Currently, Sri Lanka has incurred a BOP and BOT deficit as the total
imports of the country exceeds the total exports. The trade deficit is widening from 2013 to 2014 about 8
US $ millions and 2014 to 2015 about 1 US $ million. This trade deficit is persisting over the years in the
Sri Lanka economy. The trade balance or the gap is encountered mostly due to the escalating of the imports
expenditures. When looking at 2006 to 2015 economical history of Sri Lanka, it is revealing that there was
a surplus in the BOP in the year 2006, 2007, 2009, 2010, 2012 - 2014. 2014 had a surplus in BOP nearly
1500 million USD. But still, the trade deficit is over 8000 million USD. In the year 2015 and 2016 where it
is showed a deficit in both BOP and BOT [2] [4] [5] [6] [7] [8]
Considering about 1978 to 2015, the country yearly import demand represents over 30 percent share
of the gross domestic product except 1984, 2009, 2010, 2013 2015. During 1992 to 2006 years of the
period there the import demand shows up over 40 percent share of GDP. 49.621 percent is shown in the
year 2000 and it is the highest import demand ratio on GDP. 26.812 percent in the year 2010 and it is the
lowest ratio from the identified period [9]
When considering the statistical data from the year 2006 to 2015 the deficit of the trade balance share
is over (-10 percent) except in the year 2009 and 2010 from the GDP. It is somewhat reduced in the year
2009. 2009 had recorded the lowest as (-7.4 percent) and (-9.7 percent) in year 2010. The highest is in year
2011 and it is 16.4 percent [4] [5] [7] [6] [8].
At the last quarter of 2016 has recorded a growth in the expenditure on the imports and that has led to
an escalation of total import expenditure of the year. This increment is mainly caused due to IG and non-
fuel intermediate goods [4].
The largest portion of the import composition for over five years is the intermediate goods have
recorded over 50 percent of the total imports in Sri Lanka. Compared to the year 2015 their it shows an
increment of 2.4 percent. Fuel is a is categorized under these intermediate goods and there is a decline of it
in the year 2016. This fuel bares a share of 13 percent in the Sri Lanka imports. There is a slight reduction
in the Fuel expenditure compared to 2015 as the accounted expenditure decrement in both crude oil and
refined petroleum imports. Investment goods are the second largest import expenditure in 2016 and
accounted a share of 27 percent. The expenditure shares on consumer goods have increased in 2015 and
there it is recorded a slight reduction in 2016. This was resulted due to the reduction in the expenditure on
the import of non-food consumer goods. But still, 2016 accounted share remains high when com [5] [6] [7]
[8] paring the shares prior to 2015. Food and beverages section of the consumer goods has not denoted any
substantial deviation compared to previous year.
There have been accounted lot of fluctuations in the composition of imports of Sri Lanka and it is
believed to be due to many reasons. There could be an unrecognized relationship exist with the USD index.
Learning of it will be beneficial to recognize the patterns of Sri Lanka imports. It is hoped that this analysis
will provide a support to the authorities to implement Coherent, reliable policies for external finances to be
stabilized.
2. Methodology
2.1 Literature Review Criteria
There are many investigations concerning the relationship among the exchange rate and trade flow of
different countries. This paper analyses the existing literature based on the following factors. Technique/s
2
©Copyrights IJRIT, www.ijrit.net
1st Author et al, International Journal of Robotics and Information Technology, Volume 1, Issue 1, January 2018, Pg: 1-3
(TE), Performance Evaluation of the Technique (PET), Country/Region (C/R), Trade (TR), Time period
(TP), Forecasted results (FR), The effect of duration (EOD), Trade relationship to the exchange rate (RER),
and Trade relationship to the dollar index (RDI) are the factors to determine the critical analysis.
Technique/s (TE) the statistical technique to measure the relationship between the variables. The
empirical work reveals many different statistical and analytical techniques used to identify the relationships
among the variables. Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN),
Autoregressive Conditional Heteroskedasticity (ARCH), Generalized ARCH (GARCH), Auto-Regressive
Integrated Moving Average (ARIMA), Co-integration analyses, robust single-equation methods,
Hypothesis Testing, Augmented Dickey-Fuller (ADF), Cross-Sectionally ADF (CADF), Phillip-Perron (PP)
procedures, Granger Causality Test, Exponential GARCH (EGARCH) process, Autoregressive Distributed
Lag (ARDL), Time Series Analysis, extended trade gravity model approach, standard deviation approach,
multivariate error-correction model, Johansen & Juselius maximum likelihood co-integration technique,
Consistent OLS estimation; Generated Regressions methods have been used to attain many conclusions.
ARCH Models The investigators have used different ARCH based techniques to estimate the
equations and models of their research work. The EGARCH is used in (Jiranyakul 2013), GARCH
(Ekanayake & Chatrna 2010) (Oyovwi & Dickson 2012), Both ARCH (Oyovwi & Dickson 2012),
(Podivinsky, Maozu & Cheong 2004).
ADF – This is used to scan the stationarity or time trend involved in the data ( Podivinsky, Maozu &
Cheong 2004), (Alam & Ahmed 2010), (Weliwita & Tsujii 2000), (Genc & Artar May 2014).
ARDL – The bound testing was done with this technique and have identified the short-run dynamics
and long-run dynamics. The ARDL models have used in forecasting the dependent variable and
determining the speed of adjustment to the equilibrium also [10] [11].
ANFIS, ANN, GARCH, ARIMA and Time Series Analysis (Nanayakkara, Chandrasekara &
Jayasundara 2014) & (S.M. Fahimifard et al. 2009) have used those techniques to forecast the exchange
rate of a selected country.
Performance Evaluation of the Technique (PET) – The evaluations of selected techniques – This is a
critical step needs to be conducted in an investigation to draw conclusions from the best performing model
or the technique. (Nanayakkara, Chandrasekara & Jayasundara 2014), (S.M. Fahimifard et al. 2009) have
conducted the performance evaluation among the techniques used in the research context. (S.M. Fahimifard
et al. 2009) has used R-Squared (R2), Mean Absolute Deviation (MAD), Root Mean Square Error (RMSE)
to define the forecasting performance criteria. Mean Absolute Error (MAE), Normalized Mean Square
Error (NMSE), Directional Symmetry (DS), Correct Up trend and Correct Down trend are used in
(Nanayakkara, Chandrasekara & Jayasundara 2014) to evaluate the performance of the findings. NMSE
and MAE techniques are used to measure the deviation between actual exchange rate and the forecasted
exchange rate of Sri Lanka. Predicted directions were measured using the DS. The individual accuracy of
the predicted non-stationary effect was measured with Correct Up trend and Correct Down trend techniques
(Nanayakkara, Chandrasekara & Jayasundara 2014).
Country/ region (C/R) the country or the region of interest to do the investigation is concerned for
this. Both emerged and emerging countries are being researched to identify the relationship between the
variables.
Trade (TR) - for the investigation, the international trade is important to a countries economy and it
plays a major role in the international trade. It is possible to identify several direct and indirect
requirements of the trade for a country. A country can produce some products and services domestically
while some of the products and services are supplied by a foreign country. The domestic scarcity or
unavailability of the product or service could be a major reason for imports. If the lack of the product or
service is a cause to limit the consumption or if it doesn’t meet the consumer satisfaction, expectation,
assortment a country may have to proceed to import such things. In some cases, a country needs to import
products and services concerning the cost involved in producing or providing that domestically. There
could be much cheaper, efficient solutions when thinking about importing those from a foreign country
[12].
Time period (TP) Different investigations are carried out in different time periods with the use of
time series of data.
3
©Copyrights IJRIT, www.ijrit.net
1st Author et al, International Journal of Robotics and Information Technology, Volume 1, Issue 1, January 2018, Pg: 1-3
Forecasted results (FR) – Forecasting of data will be highly beneficial to many aspects of economy of
a country. This will support to face the uncertain future or a risk situation. A country can apply the
forecasting techniques to predict the exchange rates, Imports, Exports and many other economically
valuable information with many factors.
The effect of duration (EOD) The investigations could be conducted to find out the short-run(S/T)
and long-run(L/T) relationship between the variables. (Weliwita & Tsujii 2000), (S.M. Fahimifard, M.
Homayounifar and M. Sabouhi 2009), (Nanayakkara, Chandrasekara & Jayasundara 2014) have not
considered the effect of short or long-run relationship to the variable whereas (Arize & Shwiff 1998) and
(Oyovwi & Dickson 2012) have disscussed only the long-run relationship. (Jiranyakul 2013), (Alam &
Ahmed 2010), (Genc & Artar May 2014), (Twarowska 2015), (Ekanayake & Chatrna 2010) and
(Podivinsky, Maozu & Cheong 2004) have elaborated the short-run and long-run relationship.
Trade relationship to the exchange rate (RER) - The exchange rate of a country is a key element to its
economy as it is could be identified as a measure of deciding the no of units of the foreign currency that
the domestic country could buy [13]. This is highly important for both the import and export trades.
Exchange rate volatility is an important factor for many direct and indirect parties of the international trade
as USD is mainly used as a producer currency price for the international trade. It involves a high
uncertainty in the international trade of a country [14]. Knowledge of the relationship between USD
fluctuation, exchange rate volatility and import volume will support to pursuit for a beneficial trade and
prevent or be prepared for a much more stable situation within a country.
Trade relationship to the dollar index (RDI) - The USD is an important currency for the world
economy as it is considered as the most influential currency among many of the currencies [15]. The US
Dollar could be measured by US Dollar index (USDX, DXY), which is decided based on six other major
currencies used in worldwide [15] [16]. The USD will be relatively measured against a weighted geometric
mean of Euro (EUR), Japanese Yen (JPY), Pound Sterling (GBP), Canadian Dollar (CAD), Swedish Krona
(SEK), Swiss Franc (CHF). The basket of the above-mentioned currencies or the components of US Dollar
index will allow identifying the strength of the USD against currencies of the trade partners [ 16]. EUR is
the biggest weighting in the basket of currencies as nineteen countries are partnered with the European
union, which has a share of 57.6%. JPY denotes a weighted share of 13.6%, GBP has an 11.9% of share
and correspondingly they hold the second and third biggest weights. CAD, SEK, and CHF denote 9.1%,
4.2%, 3.6% share of the currency basket [16]. The base value of this index is hundred and if the index is
greater than the base value, it is considered that the Dollar has gained over its components. If the index is
less than the base, then the dollar has fallen vs the other countries. Considering the USD index from the
year 2005 to 2017, the US dollar is being appreciated among the other basket of foreign currencies and
raised over the base value after 2016 October. Before that, the USD was marked under the baseline. Further
considering the USD index statistics from the mid of 2008 to 2017, there exists some significant
fluctuations or the volatilities. Among all these, there is a placid result for over a year from March 2013 to
August 2014.
3. Literature Review
An empirical study by (Ekanayake & Chatrna 2010) focuses on the consequences of exchange rate
volatility on exports of Sri Lanka. This paper concerns the export statistics of ten major trading partners
including India, Japan, United States, United Kingdom, Germany, France, United Arab Emirates, Russia,
Italy, and Belgium. The data during 1980 to 2007 years were considered for the analysis. Generalized auto
regressive conditional heteroskedasticity (GARCH) model is utilized to quantify the degree of exchange
rate volatility and it is used to measure the aggregated export volume and different export categories of Sri
Lanka in the framework of multivariate error-correction model. Johansen and Juselius maximum likelihood
co-integration technique is utilized to find the export demand in the long run. The paper reveals that there is
no strong relationship discovered within the variables. Although there is a varying degree of the effect from
the exchange rate volatility to different goods of export. The investigation also posits that five out of eight
categories show a negative or discouraging exports trend against exchange rate volatility in the long run. In
4
©Copyrights IJRIT, www.ijrit.net
1st Author et al, International Journal of Robotics and Information Technology, Volume 1, Issue 1, January 2018, Pg: 1-3
most of the cases, the short run of the export also showed a significant negative trend against the exchange
rate volatility.
(Twarowska 2015) also identified the Poland’s imports and exports over the exchange rate focusing
bilateral trade flow among Poland and Euro area. The extended trade gravity model approach is used for the
analysis. The study is done for a period of the year 2004 to 2013 it is found that the depreciation of their
local currency is a reason to increase the country exports to its major trading partners and the, on the other
hand, the imports shows a negative relationship with it. Therefore, it verifies that the exchange rate is a
considerably an important factor influencing the trade income.
(Podivinsky, Maozu & Cheong 2004) investigates the bilateral trade flows in US and United Kingdom
(UK). This investigation observed a negative and statistically significant relationship between the exchange
rate volatility on imports of US from the UK.
(Arize & Shwiff 1998) reveals that there is a significant long-run negative impact on the exchange rate
volatility and the import volume of countries of G-7. This result is true for five counties the United States,
the United Kingdom, Japan, Italy, and France of G-7. However, Germany and Canada have shown a
positive and significant relationship after examining the period of 1973 second quarter to first quarter of the
year 1995. There it is analyzed finding the result there it is used the co-integration technique and robust
single-equation methods.
(Alam & Ahmed 2010) estimates the import demand for Pakistan for the period from the first quarter
of 1982 to the second quarter of 2008. The Autoregressive Distributed Lag (ARDL) approach is used to
analyze the quarterly time series data and it concludes to a hypothesis that there exists a relationship among
the imports, real economic growth, relative import prices, real effective exchange rate and volatility of real
effective exchange rate of Pakistan in the long run of the trade. When concerning long run of the import
demand of Pakistan is growth driven and the depreciation of the local currency over foreign exchange has
not demonstrated a decrease of that. Therefore, it is said that the Pakistan imports demand is unresponsive
to the exchange rate volatility and its depreciation. The paper provides evidence for a short run
phenomenon in the change of import volume of Pakistan. (Oyovwi & Dickson 2012) also reveals that the
imports of Nigeria have no significant impact on the exchange rate volatility. Augmented Dickey-Fuller
(ADF), co-integration test was used to search for a stationary relationship between the variables. It
identifies that Nigeria’s both domestic consumptions and exports are highly dependent on imports.
Therefore, the policy of the domestic currency devaluation will not sustenance to discourage the substantial
amounts of imports. It is also prescribed to manage the situation by implementing rigid policies and
restrictions as it does not indicate any favorable consequence to reduce the balance of payments. (Weliwita
& Tsujii 2000) analyzed 1978I-97IV data and reveal that real exchange rate does not indicate any
responsive result on import or the export trade flow to create a highly favorable environment to fill out the
trade balance. It is also positing that there exists a positive co-relationship between Sri Lanka’s imports and
domestic income and the growth in its exports in the long run.
(Jiranyakul 2013) posits that there exists an impact of real exchange rate volatility on the real imports
in concerning the long run. It is also discovered that any deviations from the equilibrium that occur in the
short run will be corrected quickly. An appreciation of the exchange rate and increasing of real sector
production will cause to promote the imports in Thailand. Increasing of the imports will deteriorate the
balance of trade of Thailand. These findings were identified during the time of floating exchange rate
regime. The above results were revealed by analyzing the import flows of Thailand from July 1997 to
December 2011. There it is used the AR – Exponential GARCH to recognize the volatility of the exchange
rate and have utilized co-integration to analyze the short run uncertainty. The investigation reveals that
there is negative impact between the uncertainty of exchange rate for the long term while the short run has
no highly significant results as such. These results were highly significant during under the floating
exchange rate regime. (Genc & Artar May 2014) concluded that five out of twenty-two developing
countries have shown a co-integration between the real exchange and the international trade including both
imports and exports. There it is found a positive and significant impact on the import flow from the
effective exchange rate index in terms of long term trade while short term reveals a negative relationship
among the variables. The trade balance is not considered to identify the relationship as the authors have
considered imports and exports as individual components to carry out the research. It is recognized that
there is a statistically significant difference in the long-term and the short-term relationship. The annual
5
©Copyrights IJRIT, www.ijrit.net
1st Author et al, International Journal of Robotics and Information Technology, Volume 1, Issue 1, January 2018, Pg: 1-3
data from World Bank Database from the year 1985 to 2012 were used for the investigation. The co-
integration Panel Model is utilized as the approach to proving the validity of hypothesis of the co-integrated
relationship between the imports-exports of the selected developing countries in the long run.
(S.M. Fahimifard, M. Homayounifar and M. Sabouhi 2009) has done a comparison of different
possible techniques to forecast the exchange rate. The different techniques include ANFIS, Artificial Neural
Network (ANN), GARCH and ARIMA. It is used a set of time series exchange rate data - Iran Rial/US
Dollar and Rial/Euro from 20th March 2002 to 21st November 2008. The investigation is generalizing that
the data-driven GARCH and ANN models could be suitable for most of the investigations based on the
empirical studies with no particular theoretical assistance is specified to recommend a proper data
generating procedure (Nanayakkara, Chandrasekara & Jayasundara 2014). Based on this posit
(Nanayakkara, Chandrasekara & Jayasundara 2014) conducted a research to forecast the exchange rate of
US Dollar /Sri Lankan Rupee (LKR). It is used 1275 no of daily exchange rate data from 2007 January to
2011 November obtained from Central Bank of Sri Lanka.
Table 1 – Literature Review Criteria
Author Evidence of Relationship Analysis of International trade
(S.M.
Fahimifard, M.
Homayounifar
and M. Sabouhi
2009)
TE ANFIS, ANN, GARCH, ARIMA
TP 03.2002 – 11.2008 PET Yes
FR Yes C/R Iran
RDI No TR -
RER Iran Rial/US Dollar
& Rial/Euro EOD -
(Arize & Shwiff
1998)
TE Co-integration analyses, Robust single-equation methods,
TP 1973:2 - 1995:1 PET No
FR No C/R G-7 countries
RDI No TR Imports of G-7 countries
RER Yes EOD LR
(Oyovwi &
Dickson 2012)
TE ADF, (ARCH) and GARCH model, Phillip Perron (PP) procedures,
Granger Causality Test
TP 1970-2009 PET No
FR No C/R Nigeria
RDI No TR Aggregated Imports
RER Yes EOD LR
(Jiranyakul
2013)
TE AR - EGARCH process, Co-Integration
TP 07.1997 – 12 2011 PET No
FR No C/R Thailand
RDI No TR Imports
RER Yes EOD SR/LR
(Alam &
Ahmed 2010)
TE Autoregressive Distributed Lag (ARDL)
TP 1982:Q1 - 2008:Q2 PET No
FR No C/R Pakistan
RDI No TR Aggregated Imports
RER Yes EOD SR/LR
(Nanayakkara,
Chandrasekara
& Jayasundara
2014)
TE Time Series and Neural network
TP 01.2007 – 11.2011 PET Yes
FR Yes C/R Sri Lanka
RDI No TR -
RER LKR/ US Dollar EOD -
6
©Copyrights IJRIT, www.ijrit.net
1st Author et al, International Journal of Robotics and Information Technology, Volume 1, Issue 1, January 2018, Pg: 1-3
(Genc & Artar
May 2014)
TE Co-integration Panel Model, Hypothesis Testing, ADF, CADF
TP 1985-2012 PET No
FR No C/R Twenty-two emerging countries
RDI No TR Imports and Exports
RER Yes EOD SR/LR
(Twarowska
2015)
TE Extended trade gravity model approach, standard deviation approach
TP 2004 - 2013 PET No
FR No C/R Poland
RDI No TR Bilateral trade flow including aggregated
Import volume among Poland & Europe.
RER Yes EOD SR/LR
(Ekanayake &
Chatrna 2010)
TE (GARCH), multivariate error-correction model, Johansen & Juselius
maximum likelihood co-integration technique
TP 1980 - 2007 PET No
FR No C/R Sri Lanka
RDI No
TR exports from Sri Lanka to India, Japan,
United States, UK, Germany, France, UAE,
Russia, Italy, & Belgium
RER Yes EOD SR/LR
(Podivinsky,
Maozu &
Cheong 2004)
TE ARCH model; Consistent OLS estimation; Generated Regressions;
TP -PET No
FR No C/R US
RDI No TR Bilateral trade flows in US and UK
RER Yes EOD SR/LR
(Weliwita &
Tsujii 2000)
TE Elasticity approach
TP 1978 I-1997 IV PET No
FR No C/R Sri Lanka
RDI No TR Both the International Trades
RER Yes EOD -
4. Conclusions
Based on the literature there are several investigations have been carried out on the relationship
between exchange rate volatility on international trade, trade balance/ balance of payments, import flow,
export flow in the context of both the emerged and emerging countries. Many approaches have been
utilized to come to certain findings and results. In many studies, the authors have used ARCH based
approaches to recognize the exchange rate volatility. Co-integration technique is being used to discover the
behavior of long run results while some have used it to prove or validate the hypothesis. ARDL, Johansen
& Juselius maximum likelihood co-integration technique are main techniques used in the context of
econometrics.
As mentioned in the Table 01 investigations have conducted further research by extending to forecast
or predictions if there exists a significant positive or negative impact. It is vital for any economy as the
results of the investigations could be the determinants of the major economic decisions, policies,
frameworks. Forecasting of the exchange rate is done in many types of research such as (S.M. Fahimifard,
M. Homayounifar and M. Sabouhi 2009) and (Nanayakkara, Chandrasekara & Jayasundara 2014). It is
identified that most of the investigation have not predicted or forecasted the import, export or trade flow,
proving that by the following investigations (Arize & Shwiff 1998), (Oyovwi & Dickson 2012), (Jiranyakul
7
©Copyrights IJRIT, www.ijrit.net
1st Author et al, International Journal of Robotics and Information Technology, Volume 1, Issue 1, January 2018, Pg: 1-3
2013), (Alam & Ahmed 2010), (Genc & Artar May 2014), (Twarowska 2015), (Ekanayake & Chatrna
2010), (Podivinsky, Maozu & Cheong 2004), (Weliwita & Tsujii 2000)Investigations and the studies on a
countries’ imports are surprisingly overlooked as there are several studies and analysis being carried out
focusing only the aggregated export volume concerning the exchange rate volatility. It is less to find
investigations on the relationship between exchange rate volatility and import demand of a particular
country. It discloses that there exists an ambiguity in the empirical literature and most of the studies have
identified a negative relationship with the high volatility and the export trade and other studies have shown
up different degrees of relationships up to positive relationships. As that the empirical literature reveals an
ambiguous or no consensus relationship between the exchange rate volatility and the import flows of both
emerging and emerged countries.
5. Future Work
It is possible to conduct an investigation using big-data analytics technique to analyze the impact of
the relationship. It could be further extended the findings to predict and exchange rate of a country and the
international trade flow of the country. The study context will be parameterized to aggregated imports and
import categories of Sri Lanka. Then the study will focus on the US Dollar volatility and its impacts on the
Sri Lanka imports in the long run and in the short run. It is possible to use the ARDL model with the use of
big-data analytics to determine the speed of adjustment to the equilibrium of each and every import items
of the imports of Sri Lanka. This research will look ahead to identify the possibility of forecasting of the
imports of Sri Lanka over the time and the dollar index.
6. Reference
[1] Saman Kelegama. (2010, August) www.island.lk. [Online]. http://www.island.lk/index.php?
page_cat=article-details&page=article-details&code_title=5486%20
[2] Nimal Sanderatne. (2017, March) www.sundaytimes.lk. [Online].
http://www.sundaytimes.lk/170319/columns/policies-to-overcome-persistent-balance-of-payments-
difficulties-233301.html
[3] Nimal Sanderatne. (2017, March) www.sundaytimes.lk. [Online].
http://www.sundaytimes.lk/170312/columns/why-lanka-is-in-balance-of-payments-crisis-again-
232481.html
[4] Central Bank of Sri Lanka, "ANNUAL REPORT 2016," Central Bank of Sri Lanka, Annual 2016.
[5] Central Bank of Sri Lanka, "ANNUAL REPORT 2015," Central Bank of Sri Lanka , 2015.
[6] Central Bank of Sri Lanka , "ANNUAL REPORT 2014," Central Bank of Sri Lanka , 2014.
[7] Central Bank of Sri Lanka, "ANNUAL REPORT 2013," Central Bank of Sri Lanka, 2013.
[8] Central Bank of Sri Lanka, "ANNUAL REPORT 2012," Central Bank of Sri Lanka, 2012.
[9] Saman Kelegama. (2010, August) www.island.lk. [Online]. http://www.island.lk/index.php?
page_cat=article-details&page=article-details&code_title=5486%20
[10] Shaista Alam and Qazi Masood Ahmed, "Exchange Rate Volatility and Pakistan’s Import Demand: An
Application of Autoregressive Distributed Lag Model," International Research Journal of Finance
and Economics, no. 48, 2010.
[11]Komain Jiranyakul, "Exchange Rate Uncertainty and Import Demand of Thailand," Asian Economic
and Financial Review , pp. 1269-1280, 2013.
[12] Jim Sherlock and Jonathan Reuvid, The Handbook of International Trade, 2nd ed.: The Institute of
Export, 2008.
[13] Christian Bjørnskov, Basics of International Economics - Compendium.: Ventus Publishing, 2005.
[14] E M Ekanayake and Dasha Chatrna, "The effects of exchange rate volatility on Si Lankan exports: an
empirical investigation," Journal of International Business and Economy, pp. 51-68, 2010.
[15] John J. Murphy, Trading with Intermarket Analysis: A Visual Approach to Beating the Financial
8
©Copyrights IJRIT, www.ijrit.net
1st Author et al, International Journal of Robotics and Information Technology, Volume 1, Issue 1, January 2018, Pg: 1-3
Markets Using Exchange-Traded Funds.: John Wiley & Sons, 2012.
[16] Ed Ponsi, The Ed Ponsi Forex Playbook: Strategies and Trade Set-Ups.: John Wiley & Sons, 2010,
vol. Volume 453 of Wiley Trading.
9
©Copyrights IJRIT, www.ijrit.net
ResearchGate has not been able to resolve any citations for this publication.
ResearchGate has not been able to resolve any references for this publication.