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Journal articles on the topic 'Exchange rate of USD and INR'

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Published: 5 June 2025

Last updated: 1 August 2025

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1

Dua, Pami, and Ritu Suri. "Interlinkages Between USD–INR, EUR–INR, GBP–INR and JPY–INR Exchange Rate Markets and the Impact of RBI Intervention." Journal of Emerging Market Finance 18, no. 1_suppl (2019): S102—S136. http://dx.doi.org/10.1177/0972652719831562.

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This article examines interlinkages between four major exchange rates, namely, USD–INR, EUR–INR, GBP–INR and JPY–INR in terms of returns and volatility spillovers using a vector autoregressive-multivariate GARCH–BEKK framework. In addition, we analyse the impact of RBI intervention on the returns, volatility and covariance of these exchange rates. The study finds significant bidirectional causality-in-mean and causality-in-variance between all four exchange rates. The estimation results suggest that RBI intervention in the form of net purchase of dollars leads to depreciation of INR vis-à-vis

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Mohanty, Debasis, Amiya Kumar Mohapatra, Sasikanta Tripathy, and Rahul Matta. "Nexus between foreign exchange rate and stock market: evidence from India." Investment Management and Financial Innovations 20, no. 3 (2023): 79–90. http://dx.doi.org/10.21511/imfi.20(3).2023.07.

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This study examines the impact of foreign exchange rate fluctuations on various NSE capitalized indices of India. Five exchange rates were chosen based on trading contracts in the currency derivative segment of NSE. These exchange rates are US Dollar-Indian Rupee (USD/INR), Euro-Indian Rupee (EUR/INR), Great Britain Pound-Indian Rupee (GBP/INR), Chinese Yuan-Indian Rupee (CNY/INR) and Japanese Yen-Indian Rupee (JPY/INR), which are used as a regressor in this study. The data of NSE Nifty large-cap 100, Nifty mid-cap 100 and Nifty small-cap from December 1, 2012 to December 1, 2022 was considere

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3

Animesh, Bhattacharjee, and Sunil Kumar. "Is the movement of the INR/USD Exchange Rate and the Indian Stock Market Linked? Fresh Evidence." Review of Finance and Banking 16, no. 1 (2024): 21–32. http://dx.doi.org/10.24818/rfb.23.16.01.02.

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Dollar exchange rate and Indian stock market are leading economic indicators. The present study investigates the relationship between the two economic indicators during the period April 2005 to December 2019. Analysis of Johansen cointegration test reveals that positive long-run cointegrating relationship exists between the variables. The vector error correction mechanism shows that INR/USD exchange rate influences the Indian stock prices negatively in the short-run. The study also observes the presence of bidirectional causality between the variables in the short-run. The variance decompositi

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Journal, IJSREM. "The Correlation Dynamics Between Sensex 30 Returns and INR/USD Exchange Rate Movements." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 09 (2024): 1–7. http://dx.doi.org/10.55041/ijsrem37610.

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The Sensex 30 is a benchmark index for India's largest companies, indicating the health of the stock market. Its movements are influenced by domestic economic conditions, corporate performance, and global trends. The INR/USD exchange rate, which represents the Indian rupee vs. the US dollar, is crucial for India's international trade and investment. A depreciating rupee benefits export-oriented companies but increases import costs, affecting market performance. Understanding this dynamic is essential for investors and policymakers. The fluctuating link between the INR/USD currency pair and SEN

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Inani, Sarveshwar Kumar, Manas Tripathi, and Saurabh Kumar. "Does Artificial Neural Network Forecast Better for Excessively Volatile Currency Pairs?" Journal of Prediction Markets 10, no. 2 (2017): 47–61. http://dx.doi.org/10.5750/jpm.v10i2.1252.

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This study predicts the exchange rates for three currency pairs (USD-INR, GBP-INR, and EUR-INR). We have used multi-layer perceptron (MLP) neural network architecture based on feed-forward with back-propagation learning method. The sample of the study covers daily data for the period from January 2009 to January 2016. The findings of the study confirm that the neural network predicts better for more volatile currency pairs (GBP-INR and EUR-INR) as compared to a less volatile currency pair (USD-INR). The study further observes that the optimal forecast horizon for the neural network model shoul

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Nidhi, Agrawal, Srinivasan P., and Shroff Sumita. "Revisiting the Cointegration and Casual Relationship between Different Financial Markets." Empirical Economics Letters 22, no. 12 (2023): 97–108. https://doi.org/10.5281/zenodo.10460559.

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<strong>Abstract: </strong>This study aims to examine the causal link among USD/INR exchange rates, domestic gold prices, crude oil prices, and NIFTY 50 index taking a long period of 13 years from September 2010 to September 2023. We use Augmented Dickey–Fuller (ADF) unit root test, Autoregressive Distributed Lag Model (ARDL) and Granger causality test for the analysis. ARDL results indicate the existence of a long-run relationship among USD/INR, NIFTY 50 and crude prices but absence in gold prices. Granger causality test result reveals a bidirectional causality between the NIFTY index a

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Kuldeep, Niranjan Thorat. "The Impact Of Rupee Exchange Rate Fluctuations On Indian International Trade (2015–2023)." Young Researcher 14, no. 1C (2025): 309–11. https://doi.org/10.5281/zenodo.14936697.

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<em>India's economy has become deeply intertwined with global financial systems over the past few decades. The Indian Rupee (INR) has experienced significant fluctuations against major currencies, particularly the US Dollar (USD), influenced by domestic and international factors. This paper examines the key determinants of INR/USD exchange rate volatility and its effects on India’s trade, investment flows, and economic stability. The study also evaluates the impact of global events, such as the COVID-19 pandemic, and proposes policy measures to enhance resilience against currency volatil

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Rami, Khyati, Ansh Rajput, Navin Shripathi, Jay Patel, and Roshni Patel. "Comparative Analysis of ML Models for Currency Exchange Rate Prediction." International Journal of Computer Science and Mobile Computing 13, no. 3 (2024): 27–43. http://dx.doi.org/10.47760/ijcsmc.2024.v13i03.004.

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The primary aim of this research is to improve the prediction of the exchange rate between the United States Dollar (USD) and the Indian Rupee (INR), which is an area that has received little attention in the field of financial forecasting. In contrast to widespread methodologies that consolidate results over several currency pair, this study specifically concentrates on the USD to INR pair, recognising the distinctive economic and political dynamics between the United States and India. This study aims to do a comparative analysis of four various machine learning models, namely RNN, ARIMA, LST

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Dr., Hariharan Narayanan. "Exchange rate policies and refor-ms adopted by India until 2010: A literature analysis." International Journal of Financial Engineering 8, no. 2 (2021): 33. https://doi.org/10.1142/S2424786321500201.

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Exchange rate is a rate at which one currency can be exchanged into another currency. This paper will concentrate on the exchange rate policy, policy reforms and measures undertaken by India. It also will deal with the INR appreciations and depreciations from 1993–1994 to 2010–2011. It will give the clear comprehensive literature and measure of exchange rate policy and various reforms adopted by India, chronology of money, INR fluctuations and RBI interventions to curb volatility. This study is historical, descriptive and analytical which concentrates for a period of 10 years start

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Chethan, N., and R. Sangeetha. "Sentiment Analysis of Twitter Data to Examine the Movement of Exchange Rate and Sensex." Journal of Computational and Theoretical Nanoscience 17, no. 8 (2020): 3323–27. http://dx.doi.org/10.1166/jctn.2020.9179.

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In this paper tweets available on social media about USD/INR exchange rate, BSE Sensex, NSE Nifty have been collected and Sentiment Analysis using R programming has been performed. A sentiment score has been obtained for each of the sentences and also word cloud plot have been obtained. In this paper twitter feeds are collected using the keywords: USD/INR, #USD/INR, #BSE, #Sensex, #NSE. For the purpose of obtaining the tweets, R programming is used. In this study to obtain the word cloud plot, the sentiment has been classified across 8 categories viz Anticipation, anger, trust, surprise, sadne

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Nirmala, J. "Forecasting USD/INR Exchange Rates: A Time Series Approach Using ARIMA." International Journal of Management and Development Studies 13, no. 12 (2024): 9–15. https://doi.org/10.53983/ijmds.v13n12.002.

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This study aims to forecast the USD/INR foreign exchange rate employing the Autoregressive Integrated Moving Average model, analyzing its applicability over an extensive historical period from 1970 to 2024. The primary objective is to identify the most suitable model for predicting future exchange rate trends, which is crucial for investors and businesses engaged in international trade. Using 55 years of historical time series data, the ARIMA (2, 2, 0) model was identified as the most appropriate after rigorous testing and evaluation. The analysis revealed that the first and second autoregress

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Dr., Tejal Shah, Narolkar Meera, and Naik Saumya. "The Study on the Impact of Exchange Rate and Inflation on Nifty." Journal of Economics, Finance And Management Studies 08, no. 03 (2025): 1769–73. https://doi.org/10.5281/zenodo.15055084.

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This study explores the impact of exchange rates (USD/INR) and inflation (CPI/WPI) on the performance of the Nifty index. By analysing historical data over the past 10 years, the research examines the individual and combined effects of these macroeconomic factors on stock market returns. Using correlation and regression analysis, the study identifies significant relationships, offering insights for investors and policymakers to make informed financial decisions.

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13

Kumar, Dilip. "Long range dependence in the high frequency USD/INR exchange rate." Physica A: Statistical Mechanics and its Applications 396 (February 2014): 134–48. http://dx.doi.org/10.1016/j.physa.2013.11.018.

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Roa, K. Mallikarjuna. "Forecasting of Exchange Rate Volatility between USD / INR Using Garch Model." Oman Chapter of Arabian Journal of Business and Management Review 9, no. 4 (2020): 152–58. http://dx.doi.org/10.12816/0059112.

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15

E, Geetha, Iqbal Thonse Hawaldar, Vidya Bai G, Suhan Mendon, and Rajesha Thekkekutt Mathukutti. "Are global Exchange Traded Fund pretentious on exchange rate fluctuation? A study using GARCH model." Investment Management and Financial Innovations 17, no. 4 (2020): 356–66. http://dx.doi.org/10.21511/imfi.17(4).2020.30.

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Investors invest in a foreign market to reap the benefits of currency differences. The change in the value of underlying assets affects these hedged funds and, at the same time, restricts investors from higher return possible in unhedged funds. This study aims to examine the performance of most actively traded shares in Exchange Traded Fund and any influence, along with tracking the information from the index. This study also analyzes the currency fluctuation and its impact on returns and volatility of ETF and index. The equity ETF, which tracks NASDAQ (NDX 100), is chosen for the study, and t

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Parengkuan, Frangky Christoffel. "Analisis Sentimen Perubahan Harga Emas Dunia, Nilai Tukar Rupiah dan Indeks Harga Saham Gabungan terhadap Keputusan Membeli Produk Reksadana Saham." Jurnal Ilmiah Magister Managemen 4, no. 2 (2018): 1–17. http://dx.doi.org/10.34010/jimm.v4i2.3768.

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The objective of this study are (1) to describe the exchange of world gold price, USD/IDR exchage rate, the movement in Indonesian Stocks Exchange Indexs (IHSG) and investor’s sentiment to buy Equity Fund (2) to verify the corelation against the world gold price, USD/IDR exchange rate and movement of Indonesian Stocks Exchange Indexs (3) to calculate how they will make effect to decision of buying Equity Fund. The Equity Funds come from all funds that sold by Bank Danamon Region 8 Jawa Barat with minimum existing for more than 10 years performance. Analytical tools that used in this study is p

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17

Mukhaiyar, Utriweni, Devina Widyanti, and Sandy Vantika. "The time series regression analysis in evaluating the economic impact of COVID-19 cases in Indonesia." Model Assisted Statistics and Applications 16, no. 3 (2021): 197–210. http://dx.doi.org/10.3233/mas-210533.

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This study aims to determine the impact of COVID-19 cases in Indonesia on the USD/IDR exchange rate using the Transfer Function Model and Vector Autoregressive Moving-Average with Exogenous Regressors (VARMAX) Model. This paper uses daily data on the COVID-19 case in Indonesia, the USD/IDR exchange rate, and the IDX Composite period from 1 March to 29 June 2020. The analysis shows: (1) the higher the increase of the number of COVID-19 cases in Indonesia will significantly weaken the USD/IDR exchange rate, (2) an increase of 1% in the number of COVID-19 cases in Indonesia six days ago will weak

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18

Selvam, Murugesan, and Amidha Vasani Sankakumar. "Long memory features and relationship stability of Asia-Pacific currencies against USD." Business and Economic Horizons 13, no. 1 (2017): 97–109. https://doi.org/10.15208/beh.2017.07.

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This research study examines the behavior of currency rate, long memory features, and long-term stability in the returns of thirteen Asia-Pacific currencies (AUD, CNY, HKD, INR, IDR, JPY, KRW, MYR, NZD, PHP, SGD, TWD, and THB) against USD over a period of fourteen years (from 2nd January 2001 to 10th December 2014). The study uses descriptive statistics, ADF and PP test, Hurst exponent co-integration model, and figures to investigate the normality, stationarity, long memory features, and long-term relationship stability of sample currencies against USD. This study determined the valu

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19

Saidi, La Ode, Abd Azis Muthalib, Pasrun Adam, Wali Aya Rumbia, and La Ode Arsad Sani. "Exchange Rate, Exchange Rate Volatility and Stock Prices: An Analysis of the Symmetric and Asymmetric Effect Using ARDL and NARDL Models." Australasian Business, Accounting and Finance Journal 15, no. 4 (2021): 179–90. http://dx.doi.org/10.14453/aabfj.v15i4.11.

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This article examined the symmetric and asymmetric effects of the IDR/USD exchange rate and its volatility on stock prices using the monthly time series data of the IDR/USD exchange rate and the Indonesian composite stock price index from January 2006 to July 2019. The data were analyzed using ARDL and NARDL models. The results showed that in the short term, the IDR/USD exchange rate has a symmetry effect on stock prices, while volatility lacks such a symmetric influence. However, these two variables asymmetrically affect stock prices, Furthermore, in the long term both the exchange rate and t

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20

Ardesfira, Gelbi, Hazulil Fitriah Zedha, Iin Fazana, Julia Rahmadhiyanti, Siti Rahima, and Samsul Anwar. "PERAMALAN NILAI TUKAR RUPIAH TERHADAP DOLLAR AMERIKA DENGAN MENGGUNAKAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA)." Jambura Journal of Probability and Statistics 3, no. 2 (2022): 71–84. http://dx.doi.org/10.34312/jjps.v3i2.15469.

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The Rupiah exchange rate was immensely influential in maintaining the stability of the country's economy. The weakening of the rupiah exchange rate would have an impact on the national economy. Therefore, a forecast was needed to determine the exchange rate of the Rupiah in the future, especially against the US Dollar (USD). This study aimed to predict the rupiah exchange rate against the USD in 2022 and 2023. The data employed were the rupiah exchange rate data against the USD from January 2001 to December 2021. The forecasting method utilized in this study was the Autoregressive Integrated M

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21

D, Lazar, and Maria Immanuvel S. "How does indian gold price react to the changes in real exchange rates?" Journal of Management and Science 1, no. 4 (2012): 332–42. http://dx.doi.org/10.26524/jms.2012.42.

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This study investigates the relationship between the Indian gold price and the real exchangerates of major international currency and how does Indian gold price reacts to the exchange rates of thesecurrencies. The data set consists of monthly gold prices from Indian market and the real exchange rates ofmajor currencies like USD, Euro, Yen and INR for the period from 1994:01 to 2011:12. The relationship andreaction is tested through the Johansen cointegration test, Granger causality test and VAR models like Impulseresponse function and Variance Decomposition. It is found that the Indian gold pr

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Kumar, Manish. "Exploiting the Information of Stock Market to Forecast Exchange Rate Movements." Journal of International Business and Economy 11, no. 1 (2010): 69–87. http://dx.doi.org/10.51240/jibe.2010.1.4.

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The present study examines dynamic relation between stock index and exchange rate by using the daily data for India. The empirical evidence suggests that there is no long-run relationship; however, there is bidirectional causality between stock index and exchange rates. The findings of the causality tests strongly support portfolio or macroeconomic approach on the relationship between exchange rates and stock prices. An attempt is also made to forecast daily returns of INR/USD exchange rates by exploiting the information of causal relationship between exchange rates and stock index using Vecto

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Azis, Muh Irfandy, and Erick Karunia. "Interaction Between International Exchange Rate and Indonesian Finance Stock Index." INOVASI: Jurnal Ekonomi, Keuangan, dan Manajemen 20, no. 3 (2024): 735–49. https://doi.org/10.30872/jinv.v20i3.1821.

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This suggests that while short-term fluctuations are inevitable, the exchange rates and stock market tend to realign over time. The Granger causality test uncovers bidirectional causality between the USD/IDR and EUR/IDR exchange rates and the financial index, indicating that not only do changes in exchange rates impact the stock index, but stock market performance also influences exchange rate movements. The impulse response function shows that shocks to the USD/IDR exchange rate have the most significant and lasting impact on the IDX Finance index, reflecting the dominant role of the US dolla

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Alvian, Linda Amalia, Chasan Azari, and Herman Herman. "PENGARUH INFLASI, NILAI TUKAR DAN TINGKAT SUKU BUNGA TERHADAP INDEKS HARGA SAHAM GABUNGAN (Studi pada Bursa Efek Indonesia Periode 2015-2017)." Aplikasi Administrasi: Media Analisa Masalah Administrasi 22, no. 2 (2019): 18. http://dx.doi.org/10.30649/aamama.v22i2.128.

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This study aims to determine the effect of inflation, exchange rates (IDR/USD) and interest rates (BI Rate) on the Composite Stock Price Index (CSPI) in Indonesia Stock Exchange from 2015 to 2017. This study uses quantitative method. The data is monthly time series data, from 36 data from January 2015 to December 2017. The data analysis method is multiple linear regression analysis with a significant level of 0.05. The analysis shows that inflation, the exchange rate (IDR/USD) and the interest rate (BI Rate) have a strong relationship with the Composite Stock Price Index (CSPI). Simultaneously

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Khuntia, Sashikanta, and J. K. Pattanayak. "Evolving Efficiency of Exchange Rate Movement: An Evidence from Indian Foreign Exchange Market." Global Business Review 21, no. 4 (2019): 956–69. http://dx.doi.org/10.1177/0972150919856996.

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This study empirically verifies the evolving and time-varying efficiency of Indian foreign exchange market using the framework of adaptive market hypothesis (AMH). Whether market efficiency is time varying or static, and if time varying, identification of possible events causing such time-varying efficiency are the two major agenda of this study. We employ a set of recent methods which are robust and possess stronger power properties. Moreover, we follow a fixed-length rolling window approach to explore time-varying nature of market efficiency and to avoid data-snooping bias. Our overall findi

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Vahlevi, T. Muhd Redha, and Harjum Muharam. "Quantitative Easing Program and Financial Market Volatility in Indonesia." JEJAK 10, no. 1 (2017): 80–89. http://dx.doi.org/10.15294/jejak.v10i1.9128.

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This research aims to examine the impact of the USD money supply during and before quantitative easing program towards financial market volatility in Indonesia which is proxied by variance of financial market index such as IHSG, Gold Price in IDR, and Exchange Rate IDR/USD to find out the effect of the excess USD money supply on Indonesias financial market volatility. This reseacrh has used monthly time series data of M1 of USD, IHSG, IDR/USD Exchange Rate, and Gold Price from December 2008 to December 2013. TGACRH in this research is used to find out wheter the volatility or variance at previ

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Siauwijaya, Rahmat, and Dewi Sanjung. "Bitcoin, Gold, the Indonesian Stock Market, and Exchange Rate: GARCH Volatility Analysis." Business Economic, Communication, and Social Sciences Journal (BECOSS) 4, no. 3 (2022): 197–206. http://dx.doi.org/10.21512/becossjournal.v4i3.8671.

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Bitcoin has gained popularity as an investment asset because of its similarity to gold, which sparked the idea that bitcoin can be used as a hedging instrument to the fiat currency exchange rate. This paper aims to analyze bitcoin's volatility and return to gauge its feasibility as an investment asset, and hedging tool for the USD-IDR exchange rate with the GARCH and EGARCH models. With data on the daily closing price of bitcoin, gold, IDX composite index, and USD-IDR exchange rate from January 1, 2016, to December 31, 2020, the study attempts to find factors affecting bitcoin returns with the

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Ekadjaja, Margarita, and Daisy Dianasari. "HE IMPACT OF INFLATION, CERTIFICATE OF BANK INDONESIA, AND EXCHANGE RATE OF IDR/USD ON THE INDONESIA COMPOSITE STOCK PRICE INDEX." Jurnal Muara Ilmu Ekonomi dan Bisnis 1, no. 1 (2017): 42. http://dx.doi.org/10.24912/jmieb.v1i1.405.

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This research is done with the aim to know whether some macroeconomic variables, which are inflation rate, certificate of Bank Indonesia (SBI) rate, and exchange rate of IDR/USD have an impact on the movement of the composite stock price index (IHSG) at the Indonesia stock exchange (BEI) partially and simultaneously in the period of 2006–2014. The research population is inflation rate, SBI rate, and exchange rate of IDR/USD. Data analysis in this research is multiple regression by using time series monthly data of 2006–2014. Research results show that partially inflation rate gives positive si

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Handayani, Khoriro, and Budi Santosa. "Exchange Rate Analysis: Short-Term and Long-Term Balance." International Journal of Law Policy and Governance 1, no. 1 (2022): 15–24. http://dx.doi.org/10.54099/ijlpg.v1i1.263.

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This study aims to analyse how the impact of inflation, money supply, and export to influence the movement of the IDR/USD exchange rate, so it is expected to be used as a basis for determining reduction policy to mountain the IDR/USD exchange rate. The method of analyse used this research is linier regression data time series with Error Correction Model (ECM) analysis method with the help of software E-views 9. The data used in this study are secondary data obtained from IFS and BI. The results of the study show that in the short and long term, inflation and money supply have a positive effect

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Hanuransyah, Tubagus, and Daryono Soebagiyo. "The Analysis of Inflation, Exchange rate, and Benchmark Interest Rate (BI rate) Influences on the Indonesia Composite Index (ICI)." Journal of Management Science (JMAS) 6, no. 2 (2023): 249–53. http://dx.doi.org/10.35335/jmas.v6i2.216.

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This study analyzes the correlation and influence rates of inflation, Bank Indonesia, and the Dollar Exchange (USD/IDR) on the Indonesia Composite Index(ICI) in Indonesia from 2001 to 2021. The type of study used explanatory research with quantitative approach. The research data is in the form of secondary data based on the period in the form of ICI, benchmark interest rate, inflation, and rupiah exchange rate on the US dollar (KURS) obtained from Bank Indonesia (BI), the Indonesia Stock Exchange (IDX), and the Central Statistics Agency (BPS). This study's data complements the latest month's d

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Shukla, Ramakant. "Trends and determinants of raising ECBs in Indian Context." International Journal on Recent and Innovation Trends in Computing and Communication 9, no. 7 (2021): 01–08. http://dx.doi.org/10.17762/ijritcc.v9i7.5475.

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This study examines the effect of capital control measures initiated during the last two decades in terms of all-in-cost ceilings and enhanced limits on ECB in India over the sample period 2004Q1 to 2020Q2. Using global liquidity, the exchange rate between INR/USD, imports and interest rate differentials as control variables and changes in capital control measures from 2008 to 2011 in the all-in-cost ceiling, and changes in the enhanced limits on ECBs from USD 500 million to USD 750 million under the automatic route in 2012, regression analysis of three ECB series show interesting results. Usi

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Batra, Vrinda, Diva Kandpal, and Rakshit Sinha. "Relationship between exchange rate (usd/ inr) and stock market indices in India (sensex)." Asian Journal of Research in Banking and Finance 10, no. 8 (2020): 1. http://dx.doi.org/10.5958/2249-7323.2020.00007.3.

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Sumantri, Vietha Devia Sagita, and Faishal Fadli. "Analysis of Macroeconomic Variables Affecting Inflation and Exchange Rates." Integrated Journal of Business and Economics 6, no. 2 (2022): 102. http://dx.doi.org/10.33019/ijbe.v6i2.417.

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This study aims to examine the movement of macroeconomic variables, especially inflation and exchange rates. Inflation affects the exchange rate through the Law of One Price and Purchasing Power Parity, while the exchange rate affects inflation through the Exchange Rate Pass-Through Effect. This study also aims to examine the effect of other macroeconomic factors on inflation and exchange rates. The variables studied and suspected of influencing inflation are interest rates, money supply, exports, imports, government spending, unemployment, and exchange rates. While the variables studied and s

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Lida, Hawiwika, and Ir. Andam Dewi Syarif M.M. Dr. "Causality Analysis of the Brent Oil Prices, the Gold Prices and the Exchange Rates (USD/IDR) on Indonesia Composite Index (Empi rical Study January 2016 – April 2021)." Journal of Economics, Finance and Management Studies 5, no. 03 (2022): 730–37. https://doi.org/10.5281/zenodo.6378364.

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Global economic conditions are in turmoil due to the COVID-19 pandemic since 2019. Many policies are implemented to suppress the spread of the virus, which then has an impact on economic activity. It influences investors' attitudes and changes the choices in investing. This study aims to analyze the causal relationship between the Indonesia Composite Index (ICI) and gold prices, oil prices and the exchange rate (USD/IDR). This study used monthly data for the period January 2016 – April 2021 with an analysis of the Vector Error Correction Model (VECM), which is a restricted VAR model

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Rahmatullah, Dedy, and Diny Ghuzini. "Exchange rate responses to macroeconomic announcement on the COVID-19 pandemic." Jurnal Ekonomi dan Bisnis 26, no. 1 (2023): 45–66. http://dx.doi.org/10.24914/jeb.v26i1.4868.

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This study examines the effects of macroeconomic announcements on the USD/IDR exchange rate before and during the COVID-19 pandemic, and the difference between the impact of positive and negative announcements on the exchange rate. To measure the macroeconomic announcement, a surprise component is used, that is the difference between actual data and market forecasts. The data in this research are daily time series from 1 January 2014 to 30 November 2020. The actual data and market forecasts for each indicator are obtained from Bloomberg. To test the exchange rate response to the macroeconomic

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Sunardiyaningsih, Siti Purnami, and Anindya Putri Pradiptha. "Pengaruh Ekspor, Impor, Cadangan Devisa, Suku Bunga Bank Sentral dan Tingkat Inflasi Nilai Tukar IDR terhadap USD dari Januari 2019 hingga Desember 2021, dibandingkan dengan Studi dari Januari 2011 hingga Desember 2013 per Kasus Dari Indonesia." KRESNA: Jurnal Riset dan Pengabdian Masyarakat 2, no. 1 (2022): 123–36. http://dx.doi.org/10.36080/jk.v2i1.20.

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The aim of this research is to study the influence of independent variables to the fluctuation of IDR exchange rate to USD. Those independent variables are export, import, foreign reserve currencies, Central Bank rate of interest and inflation rate. The population is Indonesia’s economics and the sample is data for three years. Data was analyzed by using multiple regression, the sources of data are from Central Bank (Bank Inonesia) and Central Bureau of Statistics Indonesia. Research objectives are to determine the influence of export, import, foreign reserve currencies, Central Bank rate of i

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Eni, Yuli, and Rudy Aryanto. "Analysis of Factors that Affect the Movement of Gold’s Price as Investment Alternatives in Indonesia." Advanced Science Letters 21, no. 4 (2015): 878–81. http://dx.doi.org/10.1166/asl.2015.5912.

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This study examined the dominant factors that affecting the price of gold. The factors examined are London Gold price returns, the return rate of USD—INR, JCI return, inflation rate, and the return of the EURO—USD currency, which individually or simultaneously can affect the price of gold. The purpose of this study was to investigate how influence the factors that are considered to affect the fluctuation of gold prices and gold prices predicted for the next period which can be used by investors to seek alternative investment to be made. The results will provide information to investors about g

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Firdaus, Naupal Irfan, Andrieta Shintia Dewi, and Aldilla Iradianty. "Volatility Spillover USD-IDR Exchange Rate With Indonesia Stock Price." TRIKONOMIKA 16, no. 1 (2017): 1. http://dx.doi.org/10.23969/trikonomika.v16i1.415.

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Value of imports higher than exports, causing the trade deficit, the appreciation of the currency in the developed countries, and withdrawals by foreign investors on the Indonesian stock exchange market. These things cause the movement of the exchange rate USD-IDR and Indonesian Stock Price are volatile and tend to weaken in the period from January 3, 2011 - August 31, 2016. This study to determine spillover volatility of the exchange rate USD-IDR with Indonesian Stock Price. By using current time series data, analyzed by Augmented Dickey-Fuller (ADF), GARCH, and Granger Causality. The results

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Wijaya, Erric. "DYNAMIC BEHAVIOR OF RUPIAH EXCHANGE RATE PERIOD 1999Q1-2020Q2 (STICKY PRICE MODEL KEYNESIAN APPROACH)." Jurnal Ilmu Ekonomi dan Pembangunan 23, no. 2 (2023): 56. http://dx.doi.org/10.20961/jiep.v23i2.52497.

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<p>This study investigates the dynamic behavior of the Indonesian Rupiah (IDR) exchange rate against the US Dollar (USD) from the first quarter of 1999 to the second quarter of 2020. The primary objective is to assess the factors influencing exchange rate fluctuations using time-series data analyzed through multiple linear regression. The study focuses on key macroeconomic variables, including the M2 money supply ratio, inflation ratio, GDP ratio, and interest rate ratio, to determine their impact on the IDR/USD exchange rate. The findings reveal that the M2 ratio, inflation ratio, and G

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Banerjee, Sougata. "Decoding currency dynamics: A multiscale machine learning approach integrating economic indicators, ESG, and investor sentiment." Investment Management and Financial Innovations 22, no. 3 (2025): 27–48. https://doi.org/10.21511/imfi.22(3).2025.03.

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The foreign exchange market, characterized by high volatility and economic significance, requires accurate predictive models. This study investigates the application of the Temporal Fusion Transformer (TFT), enhanced with Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), for forecasting major foreign exchange (forex) currency pairs: USD/EUR, USD/JPY, USD/CNY, USD/AUD, and USD/INR. The proposed framework integrates a wide range of economic indicators, which include interest rate differentials, GDP growth, and trade balances, alongside investor sentiment derived from

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Ahluwalia, Hardeepika Singh, and Kulbir Kaur Bhatti. "Study of Relationship Between USD/INR Exchange Rate and BSE Sensex from 2008-2017." International Journal of Management Studies V, no. 3(1) (2018): 106. http://dx.doi.org/10.18843/ijms/v5i3(1)/13.

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Devi, Dr Shalini. "Monetary Approach Explaining INR/USD Exchange Rate Movements under Managed Float: A Cointegration Approach." Effulgence-A Management Journal 21, no. 2 (2023): 1–10. http://dx.doi.org/10.33601/effulgence.rdias/v21/i2/2023/1-10.

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Kurniawan S., Amri Darma, Rizki Rizki, Rusiadi Rusiadi, and Lia Nazliana Nasution. "Analysis of the Exchange Rate of the Rupiah Against the US Dollar and the Factors that Influence it." PKM-P 8, no. 2 (2024): 273–83. https://doi.org/10.32832/jurma.v8i2.2334.

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This research aims to determine the effect of the Fed Interest Rate, Foreign Exchange Reserves and Antam Gold Prices on the USD/IDR Exchange Rate. Research data using secondary data obtained from the Bank Indonesia website, Trading Economics and Gold Prices.org with a time span of 2013 to 2023. The research uses the Multiple Linear Regression method (Ordinary Least Square) using Eviews 12 software. The results of Data Analysis based on the Simultaneous Test (F-Test) showed that the Fed Interest Rate, Foreign Exchange Reserves and Antam Gold Prices simultaneously had a significant effect on the

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Teguh, Sugiarto, and Subagyo Ahmad. "E-Queue Mobile Application Johansen Cointegration-Granger Causality Model Relationship between IDR and BATH Currency." Journal of Research in Business, Economics and Management 8, no. 4 (2017): 1485–92. https://doi.org/10.5281/zenodo.3958577.

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The purpose of this study to investigate the relationship in the long term and mutual relationship between the exchange rate of currency IDR (Indonesia) with BATH (Thailand). Study method used in this study, namely the Johansen cointegration and Granger causality. The data used in this study is the currency exchange rate IDR and BATH against the USD on a daily basis from January, 1 2004 to December, 31 2014. The empirical results show that the exchange rate of currency IDR and data BATH are not stationary at the level of intercept level, but the 1 st and 2 scd diff  of data exchange stati

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Ratnaningrum, Ratnaningrum, Bella Kharisma Putri, Retno Wulandari, and Kusna Djati Purnama. "The Influence of BI Rate, Inflation, and Exchange Rate on The IDX Composite Stock Index (IHSG)." International Journal of Science, Technology & Management 4, no. 2 (2023): 428–33. http://dx.doi.org/10.46729/ijstm.v4i2.779.

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This study investigates the impact of variations in the BI rate, inflation rate, and the USD/IDR (US Dollar to Indonesian Rupiah) exchange rate on the IDX Composite Index (IHSG). The Composite Stock Price Index is one of the resources that investors use to choose their investing strategy. Inflation, exchange rates, business interest rates, and the IHSG are among the variables that make up the sample used in this study, which spans 60 months from January 2015 to December 2019. The analysis of the data was done using multiple regression methods. According to the findings, the IHSG is negatively

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Kathiravan, Chinnadurai, Murugesan Selvam, Balasundram Maniam, Leo Paul Dana, and Manivannan Babu. "The Effects of Crude Oil Price Surprises on National Income: Evidence from India." Energies 16, no. 3 (2023): 1148. http://dx.doi.org/10.3390/en16031148.

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The goal of this study is to look into how changes in crude oil prices affect GDP per capita and exchange rate fluctuations.to investigate the influence of crude oil price shocks on GDP per capita and exchange rate movements. This research employed yearly time series data for the price of crude oil, exchange rate (USD/INR), and GDP per capita, from 1990 to 2020. Arithmetical tools such as Descriptive, Unit Root, Granger Causality Test, and OLS Model were applied. The present study discovered a strong bi-directional Granger causality effect of Dubai crude oil prices on exchange rates, as well a

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Rashesh Vaidya and Kulchandra Pandit. "Distribution Nature of Foreign Exchange (FOREX) Rates in Nepal." Journal of Balkumari College 12, no. 1 (2023): 75–82. http://dx.doi.org/10.3126/jbkc.v12i1.60429.

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The economy of Nepal is based on the inflow of remittances sent by the Nepalese who have gone abroad for foreign employment. The trend started after the start of the Maoist insurgency and has been going on due to a lack of employment opportunities within the nation. Other than remittance, tourism and a certain amount of foreign aid have been the sources of foreign exchange earnings for Nepal. These sources of FOREX have been able to maintain the balance of payments in Nepal. One unique feature of FOREX rates in Nepal is that the Nepalese rupee (NPR) is pegged with the Indian rupee (INR), the c

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Winarko, Hilarius Bambang, Julius Caesare Wahono, Yuniningsih Yuniningsih, and Sri Tunggul Pannindriya. "How Do Inflation Rate, BI Rate, and Balance of Trade Directly Affect IDR to USD Exchange Rate and Indirectly Affect IDX Composite Index in Initial Stage of Covid-19 Outbreak?" Research in World Economy 12, no. 1 (2021): 56. http://dx.doi.org/10.5430/rwe.v12n1p56.

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This study is trying to fill the research gap by understanding how several important financial variables interplay and affect the macroeconomic indicators, especially in developing country like Indonesia during the financial crisis period caused by the unexpected and sudden Covid-19 pandemic outbreak. The purpose of this research is to determine the direct effect of the inflation rate, Bank Indonesia (BI) rate, and Balance of Trade on the movement of Indonesia Rupiah (IDR) currency stability against US Dollar (USD) and indirect impact to the Indonesia Stock Exchange (IDX) Composite index in In

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Robiyanto, Robiyanto. "THE EFFECT OF GOLD PRICE CHANGES, USD/IDR EXCHANGE RATE CHANGES AND BANK INDONESIA (BI) RATE ON JAKARTA COMPOSITE INDEX (JCI)’S RETURN AND JAKARTA ISLAMIC INDEX (JII)’S RETURN." Jurnal Manajemen dan Kewirausahaan 20, no. 1 (2018): 45. http://dx.doi.org/10.9744/jmk.20.1.45-52.

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This study examines the effect of gold price (in Rupiah) changes, US Dollar exchange rate changes against Rupiah (USD / IDR), and BI rate on Jakarta Composite Index (JCI) return and Jakarta Islamic Index (JII) return in Stock Exchange Indonesia during the period of June 2008 to September 2017. The data used in this study was obtained from the official website of Bank Indonesia and Bloomberg. Data analysis was done by using multiple regression techniques by previously doing classical assumption test. The result of this research is that the exchange rate of USD / IDR changes and BI rate has a s

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Hsing, Yu. "Short-Run Determinants of the IDR/USD Exchange Rate: A Simultaneous-Equation Model." Global Economy Journal 15, no. 3 (2015): 311–18. http://dx.doi.org/10.1515/gej-2014-0038.

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This paper examines short-run determinants of the Indonesian rupiah/USD exchange rate based on a simultaneous-equation model. Based on a reduced form equation and the EGARCH method, the paper finds that the IDR/USD exchange rate is positively associated with the real 10-year U.S. government bond yield, real GDP in Indonesia, the stock price in the U.S. and the expected exchange rate and negatively influenced by the real deposit rate in Indonesia, real GDP in the U.S., and the stock price in Indonesia. The Asian financial crisis has shifted the mean exchange rate by 4,900.857.

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