Co‐movement of foreign exchange rate returns and stock market returns in an emerging market: Evidence from the wavelet coherence approach

Author(s):  
Xingxing He ◽  
Korhan K. Gokmenoglu ◽  
Dervis Kirikkaleli ◽  
Syed Kumail Abbas Rizvi
2021 ◽  
Vol 9 ◽  
Author(s):  
Sanjeet Singh ◽  
Pooja Bansal ◽  
Nav Bhardwaj ◽  
Anirudh Agrawal

This study attempts to analyze the time-varying pattern between the exchange rates, stock market return, temperature, and number of confirmed COVID-19 cases in G7 countries caused by the COVID-19 pandemic. We have implemented our analysis using wavelet coherence and partial wavelet coherence (PWC) on independent variables from January 4, 2021 to July 31, 2021. This paper contributes to the earlier work on the same subject by employing wavelet coherence to analyze the effect of the sudden upsurge of the COVID-19 pandemic on exchange rates, stock market returns, and temperature to sustain and improve previous results regarding correlation analysis between the above-mentioned variables. We arrived at the following results: 1) temperature levels and confirmed COVID-19 cases are cyclical indicating daily temperatures have a material bearing on propagating the novel coronavirus in G7 nations; 2) noteworthy correlations at truncated frequencies show that a material long-term impact has been observed on exchange rates and stock market returns of G7 and confirmed COVID-19 cases; 3) accounting for impact of temperature and equity market returns, a more robust co-movement is observed between the exchange rate returns of the respective nations and the surge in COVID-19 cases; and 4) accounting for the influence of temperature and exchange rate returns and the increase in the confirmed number of coronavirus-infected cases and equity returns, co-movements are more pronounced. Besides academic contributions, this paper offers insight for policymakers and investment managers alike in their attempt to navigate the impediments created by the coronavirus in their already arduous task of shaping the economy and predicting stock market patterns.


2018 ◽  
Vol 9 (3) ◽  
pp. 247-253 ◽  
Author(s):  
Edward Adedoyin Adebowale ◽  
Akindele Iyiola Akosile

This research investigated the effect of interest rate and foreign exchange rate on stock market development in Nigeria. This research was centered on two research problems. First, it was whether interest rate had a significant effect on stock market development in Nigeria. Second, it was whether foreign exchange rate had a significant impact on stock market development in Nigeria. The scope of the research covered the period from 1981 to 2017. Data for this period were chosen because it covered pre and post-liberalization periods of Nigerian financial system. This research made use of ex post facto research design. Secondary data were sourced from Nigerian Stock Exchange reports, Central Bank of Nigeria statistical bulletins, and National Bureau of Statistics publications. Data were collected on Stock Market Capitalization (SMC), Prime Lending Rate (PLR) and Real Exchange Rate (RER) (Nigerian Naira in relation to American Dollars of the United States). Data analysis was carried out with Ordinary Least Squares (OLS) and Cochrane-Orcutt Iterative techniques. The findings reveal that interest rate has a significant negative effect, and foreign exchange rate has a significant positive effect on Nigerian stock market development during the period covered. It is suggested that monetary authorities should strive to formulate policies that will make interest and foreign exchange rates stable, competitive, and at a level that will stimulate the investment of funds in the stock market.


2020 ◽  
Author(s):  
Nenavath Sre ◽  
Suresh Naik

Abstract The paper investigates the effect of exchange and inflation rate on stock market returns in India. The study uses monthly, quarterly and annual inflation and exchange rate data obtained from the RBI and market returns computed from the Indian share market index from January, 2000 to June, 2020.The paper uses the autoregressive distributed lag (ARDL) co-integration technique and the error correction parametization of the ARDL model for investigating the effect on Indian Stock markets. The GARCH and its corresponding Error Correction Model (ECM) were used to explore the long- and short-run relationship between the India Stock market returns, inflation, and exchange rate. The paper shows that there exists a long term relationship but there is no short-run relationship between Indian market returns and inflation. But, there is periodicity of inflation monthly considerable long run and short-run relationship between them existed. The outcome also illustrates a significant short-run relationship between NSE market returns and exchange rate. The variables were tested for short run and it was significantly shown the positive effects on the stock market returns and making it a desirable attribute of which investors can take advantage of. This is due to the establishment of long-run effect of inflation and exchange rate on stock market returns.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bijoy Rakshit ◽  
Yadawananda Neog

Purpose The purpose of this paper is to investigate the effects of exchange rate volatility, oil price return and COVID-19 cases on the stock market returns and volatility for selected emerging market economies. Additionally, this study compares the market performance in the emerging economies during the COVID-19 pandemic with the pre-COVID and global financial crisis (GFC) period. Design/methodology/approach The authors apply the arbitrage pricing theory to model the risk-return relationship between the risk-based factors (exchange rate volatility and COVID-19 cases) and stock market returns. By applying the exponential generalized autoregressive conditional heteroskedasticity model, the study captures the asymmetric volatility spillover from the stock markets to foreign exchange markets and vice versa. Findings Findings reveal that exchange rate volatility exerts a negative and significant effect on the market returns in Brazil (BOVESPA), Chile (S&P CLX IPSA), India (SENSEX), Mexico (S&P BMV IPC) and Russia (MOEX) during the coronavirus pandemic. Regarding the effect of oil price returns, the authors find a positive relationship between oil price and stock market returns across all the economies in the study. The market returns of Russia, India, Brazil and Peru appeared more volatile during the pandemic than the GFC period. Practical implications As the exchange rate volatility is causing higher risk and uncertainty in the stock market’s performance, the central bank’s effort to maintain a stabilizing effect on the exchange rate sale can be proven crucial for the economies under consideration. Emphasized should also be given to boost investors’ confidence in the stock market, and for this, the government policy actions in reducing the transmission of the disease are the need of the hour. Originality/value While a large volume of literature on stock market performance in times of COVID-19 has emerged from developed economies, this study adds to the literature by exploring the emerging economies’ stock market performance during the COVID-19 pandemic. Unlike previous literature, this study examines the volatility spillover between stock and exchange rate markets in the worst affected emerging economies during the crisis.


2006 ◽  
Vol 05 (03) ◽  
pp. 495-501 ◽  
Author(s):  
CHAOQUN MA ◽  
HONGQUAN LI ◽  
LIN ZOU ◽  
ZHIJIAN WU

The notion of long-term memory has received considerable attention in empirical finance. This paper makes two main contributions. First one is, the paper provides evidence of long-term memory dynamics in the equity market of China. An analysis of market patterns in the Chinese market (a typical emerging market) instead of US market (a developed market) will be meaningful because little research on the behaviors of emerging markets has been carried out previously. Second one is, we present a comprehensive research on the long-term memory characteristics in the Chinese stock market returns as well as volatilities. While many empirical results have been obtained on the detection of long-term memory in returns series, very few investigations are focused on the market volatility, though the long-term dependence in volatility may lead to some types of volatility persistence as observed in financial markets and affect volatility forecasts and derivative pricing formulas. By means of using modified rescaled range analysis and Autoregressive Fractally Integrated Moving Average model testing, this study examines the long-term dependence in Chinese stock market returns and volatility. The results show that although the returns themselves contain little serial correlation, the variability of returns has significant long-term dependence. It would be beneficial to encompass long-term memory structure to assess the behavior of stock prices and to research on financial market theory.


This paper is intended to find out whether macroeconomic variables may impact on the stock market as well as whether such impact has any country specific pattern. The stock market return was taken as the dependent variable and real interest rate, inflation rate, GDP growth rate, foreign currency reserve growth rate, fiscal deficit, FDI to GDP ratio, exchange rate were taken as independent variables. Data-set was covered from 1993 to 2019 for five South Asian countries which were Bangladesh, India, Pakistan, Sri Lanka, and Nepal. The pattern of the stock market, as well as macro conditions of these countries, was observed and it was found that some relationships exist between the stock market returns and these chosen independent variables. Unit root test, Heteroscedasticty test, autocorrelation test, Hausman test is conducted to authenticate and clarified data to investigate relationship nature. Granger Casualty test indicated that there exist cause and effect relationship between GDP growth rate, exchange rate, and stock market returns. Finally, the regression test reveals that the inflation rate and foreign currency reserve growth rate have a significant impact on the stock market returns. It was expected to have the unique nature of different countries having versatile impact on dependent, so additionally fixed effects model and random effects model were run and it was found that the random effects model is statistically appropriate through conducting the Hausman test. The test reveals that GDP growth rate, foreign currency reserve growth rate, and fiscal deficit positively impact the stock market returns and these also support the literature review. Interest rates, inflation rate, FDI to GDP ratio, and exchange rate have negatively impacted the stock market return where only interest rate, inflation rate & exchange rate.


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