Rupee-dollar Exchange Rate Research Articles

A Microstructure Study of Indian Corporate Bond Market: A Review

This Review study explores various dimensions of the Indian capital market, encompassing both equity and bond markets. It delves into the influence of equity market factors, macroeconomic variables, and corporate bond market growth on the overall financial landscape. The relationship between equity market returns, equity market volatility (VIX), and the rupee-dollar exchange rate on bond yields. They highlight that increasing volatility in the equity market leads to a higher demand for fixed income securities, subsequently reducing bond returns. The underscores the significance of a robust corporate bond market for financial system stability, credit availability, and mitigating corporate sector crises. It reviews the growth of the Indian corporate bond market and its implications for monetary, fiscal, and economic variables. The results indicate that a comprehensive corporate bond market does not exhibit a significant positive or negative association with these variables. However, GDP emerges as a crucial factor for India's bond market development, particularly in terms of foreign participants. Lastly, the influence of macroeconomic variables on the Indian corporate bond market over a 23-year period. They reveal a significant correlation between corporate bond market issuance and foreign exchange reserves. Through multiple regression analysis, they found that all selected variables, except GDP and trade openness, significantly explain the volumes of corporate bonds. Collectively, their findings contribute to a comprehensive understanding of the interplay between equity market dynamics, corporate bond market growth, and macroeconomic factors in the Indian capital market. The study provides valuable insights for policymakers and investors, aiding in informed decision-making regarding investment strategies, market stability, and economic growth.

Relation Between Inflation and Capital Market in India

Capital market has significant influence on the inflationary situation in an economy both in the short run and in the long run. The general determinants which affect capital market are share indices, stock prices, prices of gold and silver, interest rate, exchange rate and even money supply can be treated as influencing variable when money is treated as capital. In this paper the author examined the impact of capital market on inflation in India during 1980-2022 taking CPI and WPI as the indicators of inflation and gold price, silver price, BSE index, BSE market capitalization, money supply and rupee dollar nominal exchange rate are considered as the indicators of capital market. Augmented Dickey-Fuller test was applied to verify unit root for all variables including break unit roots and the author calculated growth rates during 1980 – 2022 using the simple semi-log linear trend model. Author applied Johansen cointegration test and vector error correction models among the variables in both the cases of CPI and WPI and calculated short run causality through Wald test and long run causality through cointegrating equation. In VECM, the paper found one significant cointegrating equation in case of CPI and found three significant cointegrating equations in WPI. The paper found that CPI has long run causal relationships with BSE index, BSE market capitalisation, money supply and rupee dollar exchange rate and WPI has long run cointegrating relationships with BSE market capitalisation, money supply and rupee dollar exchange rate respectively. Rupee dollar exchange rate has short run causal relationships with CPI and again CPI and BSE index has bidirectional short run causality. According to impulse response functions, the responses of CPI to gold price, BSE market capitalization and money supply have been approaching towards equilibrium but finally diverged away from equilibrium. There are significant short run causalities from BSE index and money supply to WPI. The impulse response of WPI to gold price, silver price, BSE index, BSE market capitalisation and exchange rate of rupee have been converging towards equilibrium many times although diverged finally. The model can be modified by including interest rate, share prices, bond prices under monthly data analysis.

Do Financial Assets Move in Tandem During High Impact Period of a Crisis: Evidence from Global Financial Crisis and COVID-19 Pandemic Periods

The present study investigates and compares the co-movement between four asset classes namely Crude, Gold, Nifty 50 Stock Index, and Rupee–Dollar Exchange Rate during the two crisis periods viz. the Global Financial Crisis (GFC) and the COVID-19 Crisis. The methodology employed for ascertaining inter-relationship includes the Johansen Co-integration technique and Toda & Yamamoto Causality model. Besides this, the entire model has been set up under the VAR Framework with Variance Decomposition and Impulse Responses giving useful insight into the relationship among the stated variables. The results of the study, however, failed to identify any co-integration among the assets during any of the two crisis periods, however, there was evidence of short-run cause–effect relation among some of the variables. The causality flow was uni-directional from Nifty 50 to both crude and exchange rate in Period I (GFC Period) while in Period II (COVID-19 Crisis Period) it was bi-directional between Gold and Nifty 50. Causality was also seen from Foreign Exchange to Gold in Period II. Further ADF Breakpoint showed all the variables were I(1) stationary and the VAR Model was also proved stable as shown by AR Characteristics Root Plots. The impulses showed that Period II or COVID-19 Crisis Period retained the innovations of other variables for a longer duration than Period I (GFC Period).

Nexus between Exchange Rate Volatility and Oil Price Fluctuations: Evidence from India

The price of crude oil has fluctuated in India over the past few decades which has drawn significant attention because of it impact on all economic sectors. The present study aims to identify how oil price volatility affects the real exchange rate in India from 1st July 2009 to 2nd January 2020. For short-run and long-run analysis, various econometric methods have been applied, including Granger Causality, ARDL Bound test, FEVD, and IRF. The study divided the entire sample into sub-samples based on Breakpoint analysis and then performed the ARDL Bound testing procedure in each sub-sample. Causality results revealed that most samples exhibited strong unidirectional causality from oil prices to exchange rates. However, the long-run and short-run results from the ARDL model failed to detect any cointegration among the underlying variables for the entire sample. The calculated F-statistics is 4.35, which is less than the lower and upper critical bound values provided by Pesaran, Shin, and Smith (2001). The GIRF has been used to calculate the dynamic marginal effect of a one-standard-deviation shock in oil prices on the current and future values of the Rupee-Dollar exchange rate. The exchange rate fell in the first three samples due to one standard deviation shock in oil prices. However, the contribution of oil prices to the exchange rate is positive in the fourth sample period.

Dynamic Relationship Between Rupee-Dollar Exchange Rate and Major Economic Indicators

Dynamic Relationship Between Rupee-Dollar Exchange Rate and Major Economic Indicators

Pandemic‐induced fear and government policy response as a measure of uncertainty in the foreign exchange market: Evidence from (a)symmetric wild bootstrap likelihood ratio test

AbstractThe paper aims to examine the ability of a global fear index (GFI) based on the COVID‐19 pandemic and government policy responses as a measure of uncertainty in predicting eight Indian rupee‐based exchange rate return series: the Australian dollar, the Canadian dollar, the Swiss franc, the US dollar, the euro, the British pound sterling, the New Zealand dollar, and the Japanese yen. The predictability of the daily Indian rupee‐based exchange rate return series is tested using the recently developed wild bootstrap likelihood ratio test of Kim and Shamsuddin for the period 2 October 2020 to 8 March 2021. Both symmetric and asymmetric tests revealed GFI as an insignificant determinant of the Indian rupee‐based exchange rate return series. However, government policy responses are a significant determinant of the rupee–dollar exchange rate return series.

Return and Volatility Spillover Effects between Rupee–Dollar Exchange Rate and Asian Stock Indices

India is a major Asian economy that has attracted global investment due to its economic stability and relatively open financial markets. We investigate the return and volatility spillover effects between the Indian rupee against US dollar and stock index volatility in neighboring (Asian) nations. Consistent with the uncovered equity parity, we find that when the rupee depreciates against US dollar, the foreign institutional investors pull back their portfolio investments from other Asian markets and invest in Indian stock market, similarly if rupee appreciates they may divest their investments to gain profits. The unidirectional causality from the exchange rate to all stock indices is indicated by the causality in the mean approach. Our study shows a strong linkage between the currency value of a stable economy and the economies with which it has strong trade ties. Further, the results also show that investors adjust their position in the related markets during periods of currency appreciation and depreciation in an economy with significant growth prospects. JEL Codes: F31, D53, B23

Impact of Exchange Rate on Gold Price in India

In this article we investigate the impact of rupee-dollar exchange rates on growth rate of gold price in India over the period 1970-2016. The investigation is done using some steps. In the first step we use Augmented Dickey-Fuller (ADF) and Phillip-Perron (PP) test to detect that the series is stationary or not. To show the long run association of the variables we apply Johansen Co-integration test. As there is no cointegration we apply unrestricted VAR method. Since the study variables are not cointegrated, there is no long run causality, there is only short run causality running from independent variables to dependent variables. Further the Granger Causality test determines whether growth rate of gold price depends on the growth rate of rupee dollar exchange rate or not. At last we also test the stability of the model using Eigen value statistic method. The main finding of this paper is that growth rate of gold price depends negatively and significantly on growth of rupee-dollar exchange rate, means that as rupee dollar exchange rate rises gold price decreases and vice versa. The study also shows that growth rate of gold price does not Granger cause to rupee-dollar exchange rate where as rupee- dollar exchange rate Granger cause to gold price in Indian economy. That is we can stabilise the Gold Price movement by controlling the exchange rate fluctuations.

Bitcoin prices and rupee-dollar exchange rates during COVID-19

Bitcoin prices and rupee-dollar exchange rates during COVID-19

Bitcoin prices and rupee-dollar exchange rates during COVID-19

Bitcoin is the primary cryptocurrency in the world that can be stored and traded through the internet. Digital contracts and cryptocurrencies created on blockchains have now been used in exchanging...

An Empirical Investigation of the Volatility Spill-over and Asymmetries between Nifty Index and Rupee-Dollar Exchange Rate

The present study is an attempt to investigate the conditional volatility of returns of the two major segments of Indian financial markets viz. Re/$ Exchange Rate and Nifty Index Stock Index using GARCH (p,q) methodology. The period of the study has been taken to be April 2007-March 2017 and the data has been collected as monthly closing prices of the two variables, namely rupee dollar exchange rate and NSE Nifty. The analysis has been carried on first differenced (log transformed) prices. For studying the spill-over of volatility from a market to another, squared residuals (after standardization) from another market have been included as variance regressors. Further to find out whether or not there was any asymmetric returns of the markets under study, Threshold GARCH (T-GARCH) Model has been employed. The results of the study revealed the presence of conditional volatility of returns. The optimal model was identified as ARCH (1) when Re/$ Exchange Rate was the dependent variable while it was GARCH (1,1) when Nifty Index was taken as dependent variable. The bi-directional volatility spill-over (contemporaneous) was clearly evident by the two models and the same was captured by the variance regressors i.e. the standardized squared residuals. Further the results showed no sign of any asymmetry in volatility as reflected by the T-GARCH coefficients.

Exchange rate policy modeling and forecasting the exchange rate: Indian rupee vis‐à‐vis the U.S. dollar

The exchange rate is a very important key financial variable that affects decisions made by the foreign exchange investors, exporters, importers, bankers, businesses, financial institutions, policymakers, and tourists in the developed as well as the developing world. Exchange rate fluctuations affect the value of international investment portfolios, competitiveness of exports and imports, value of international reserves, currency value of debt payments, and the cost of tourists. Movements in exchange rates thus have very important implications for any country's economy's business cycle, trade, and capital flows and are therefore crucial for understanding financial developments and changes in economic policy. The study will be looking at the various aspects of country's economic policy with respect to the exchange rate and modeling and forecasting the exchange rate. The study will be analyzing India's exchange rate story and will be discussing the structure of the foreign exchange market in India in terms of participants, instruments, and trading platform as also a turnover in the Indian foreign exchange market and forward premia. The study will be attempting to develop a model for the rupee–dollar exchange rate taking into account variables from monetary and microstructure models as well as other variables including intervention by the central bank. The main focus will be on the exchange rate of the Indian rupee vis‐à‐vis the U.S. dollar, that is, the Re/$ rate. The data will be covering from January 1990 through April 2013. This study will be examining the forecasting performance of the monetary model and various extensions of it in the vector autoregressive and Bayesian vector autoregressive framework.

Empirical study on the factors affecting bond market returns-evidence from Indian markets

Capital market broadly includes fixed income securities i.e., bond market and equity market. In India, the retail investors are visible mainly in equity markets, whereas the institutional investors are involved in both the markets. Largely interest rates in the economy along with inflation rates and risk in equity markets influences the bond market yields. This paper examines the impact of equity market returns, volatility in equity markets (VIX) and rupee-dollar exchange rate on bond yields. As volatility in the equity market increases the demand for fixed income securities increases, thereby reducing the returns on bonds. In this study it is assumed that the various economic factors affecting bond yield are constant and it is the equity market returns, its volatility and the exchange rate which affects the bond yields.

An ARDL & Cointegration Approach for Analyzing Determinants of Foreign Portfolio Investors’ in India

This paper examines the relationship of FPI Net flows domestic with international financial and macroeconomic indicators. The time frame covered by the study is from January 2000 till December 2017. Auto regressive distributed lag (ARDL) method along with the Co-integration Analysis is used. Results highlighted that the major determinants of FPI in India are, Nifty returns, wholesale price index (WPI), index of industrial production (IIP), rupee dollar exchange rate, NSE market capitalisation, foreign exchange reserves and in terms of international factors are S&P 500 returns and MSCI emerging market returns. LIBOR, CMR, broad money and MSCI World Index returns are not significant in explaining the variations in FPI to India.

An Empirical Investigation on the Relationship between Onshore and Offshore Indian Rupee Market

Exchange rate movements have important ramifications for the economy’s business cycle, trade and capital flows. For India, the exchange rates fluctuations have consequences for being competitive in terms of international trade and capital flows, tourist destination and for maintaining a healthy international reserve. This paper attempts to explore the relationship between rupee-dollar exchange rate in spot market, domestic forward market and off-shore forward i.e. non-delivery forward market (Singapore) to understand the information flow in between these markets. Suitable econometric techniques including causality analysis was used for the study for the period 2002 to 2014 after considering structural breaks and sub period analysis was also done. It was found that the relationship between all three markets is quite dynamic with evidences of causality in one sub period and reverse direction or no causality in other sub periods, conditional upon intervention done by RBI to curb the volatility and on various macroeconomic shocks such global financial crisis.

An Empirical Investigation of the Volatility Spill-over and Asymmetries between Nifty Index and Rupee-Dollar Exchange Rate

The present study is an attempt to investigate the conditional volatility of returns of the two major segments of Indian financial markets viz. Re/$ Exchange Rate and Nifty Index Stock Index using GARCH (p,q) methodology. The period of the study has been taken to be April 2007-March 2017 and the data has been collected as monthly closing prices of the two variables, namely rupee dollar exchange rate and NSE Nifty. The analysis has been carried on first differenced (log transformed) prices. For studying the spill-over of volatility from a market to another, squared residuals (after standardization) from another market have been included as variance regressors. Further to find out whether or not there was any asymmetric returns of the markets under study, Threshold GARCH (T-GARCH) Model has been employed. The results of the study revealed the presence of conditional volatility of returns. The optimal model was identified as ARCH (1) when Re/$ Exchange Rate was the dependent variable while it was GARCH (1,1) when Nifty Index was taken as dependent variable. The bi-directional volatility spill-over (contemporaneous) was clearly evident by the two models and the same was captured by the variance regressors i.e. the standardized squared residuals. Further the results showed no sign of any asymmetry in volatility as reflected by the T-GARCH coefficients.

Analysis of the Interactive Linkages Between Gold Prices, Oil Prices, and Exchange Rate in India

This study investigates the co-movements and linkages among gold prices, oil prices, and Indian rupee–dollar exchange rates for the time span of 12 January 2004 to 30 April 2015 to investigate whether Indian economic policy-makers should detach financial policies from energy policies. Various econometrical methods such as Johansen’s cointegration test, vector autoregressive model, Granger causality test, and impulse response were used to explain the co-movements among the variables. We find that gold prices, oil prices, and rupee–dollar exchange rates stay substantially independent from each other, which denotes energy policies and financial policies must be detached.

Exchange rate interest rate linkages in India: an empirical investigation

Purpose The purpose of the paper is to examine the linkages between exchange rate and interest rate in India using quarterly data from Q1 of 1996 to Q4 of 2014. Design/methodology/approach Stationarity properties of data are checked using the Augmented Dickey–Fuller (ADF), Dickey–Fuller test with GLS de-trending (DF-GLS) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests and Perron’s unit root test with structural breaks. Johansen Juselius and Gregory Hansen tests are applied to assess cointegration, and block exogeneity test is used to detect causality among variables. Findings The study finds long-run relationship among interest rate, rupee–dollar exchange rate, capital flows, intervention, inflation differential, money supply differentials, output differentials and trade-balance differentials. However, the interest rate does not explain movements in the exchange rate, directly and indirectly, via capital flows. Intervention by the Central Banks to stabilize exchange rate does not have implications for movements in interest rate. Research limitations/implications The study finds capital flows to be insensitive with respect to interest rates and hence thwarts International Monetary Fund ’s (IMF) claim of using interest rates as a tool to stabilize exchange rate. The much-debated conflict between exchange-rate stabilization and control over interest rates also does not hold up to the empirical reality of India. Originality/value The study augments the existing literature by taking into account the problem of structural break in the relationship between interest rate and exchange rate. Three measures of interest rate are used to assess the robustness of results adding to their credibility compared to previous studies.

Integration of Exchange Rate and Stock Market : Evidence from the Indian Stock Market

The stock market represents the financial health of an economy, while the exchange rate represents the country's currency value against the value of international currency. After economic reforms in India post 1991, the economic and overall growth got a boom because of globalization and privatization. These reforms enhanced the imports and exports and brought volatility in the exchange rate. The current research work investigated the rapport among Nifty index returns in India and the Indian exchange rate in consideration with the U.S. dollar. The exchange rate volatility generates volatility in the stock market, which creates confusion in the minds of domestic investors as well as for foreign institutional investors. The main purpose of conducting this research was to find out the impact of change in the exchange rate in India on the trading volume and returns of Nifty index. To examine the relationship between stock market returns and exchange rate, econometric tools like ADF test, correlation, Johansen's co-integration test, and Granger causality test were applied with the help of EVIEWS program. The study was conducted during the period from April 2005 till March 2014. The empirical analysis showed that negative correlation existed among the stock market returns and exchange rate; however, the degree of correlation was not very significant. Co-integration test results showed that there was an absence of co-integration among the variables. The Granger causality test indicated that Nifty stock returns Granger caused the rupee-dollar exchange rates in India. This paper provides suggestions to the investors regarding the strategies that they can opt for trading in volatile stock markets to minimize risk or fear of bearing losses.

Gold as an Investment Option in India : Myth and Reality

The trend of gold demand in India has been growing continuously. Global physical demand of gold increased by 34% for the time period from 2004-2013 ; whereas, physical demand of gold in India increased by more than 40% for the same period. Though India did not count for even 1% of gold production, more than 21% of the global gold consumption was attributed to India in 2013, which was mainly supplied through imports. During the same period, in addition to jewellery, demand for bars and coins also increased substantially, indicating probably that gold is being chosen as a secure investment alternative by Indians. But is gold a good investment option? Is it more reliable than other financial investments? India's fascination for the yellow metal - is a reality or is it a myth? Gold as an investment option for an Indian investor was analyzed in this paper. Four popular Indian beliefs about gold were examined - (a) gold as an inflation hedge, (b) gold investment as an attractive alternative to fixed income investment, (c) gold investment as a less riskier investment than stock investment, and (d) rupee-dollar exchange rates and its bearing on the returns on gold investment. With a simple statistical analysis of data spanning from a period from 1971-72 to 2012-13, we found evidence for rejection/acceptance of the four beliefs.