Indian Foreign Exchange Market Research Articles

General characteristics of investment law in India

The aim of the work is a comprehensive analysis of investment law in India. The methodological basis of the study are official websites of specialized institutions, laws, analytical reports, articles by other scientists, etc. According to the results of the conducted research, it was found that two main legislative acts regulate investment activities in India. The first piece of legislation is the Foreign Exchange Management Act, 1999, the main objective of which is to promote foreign trade and foreign exchange and to develop and maintain the foreign exchange market in India. According to Section 5 and 6 of the Law, operations with a current currency account are allowed only on the condition that they do not have any restrictions (criminal, state, etc.). Capital account transactions mean transactions during which changes in assets or liabilities occur (referring to liabilities of resident and non-resident persons in relation to assets). The second act – Consolidated Policy on Attracting FDI in India by the Department of Trade and Industry Promotion 2020 – includes clarification of all investment norms. The policy update is in line with the policy of need to attract FDI to India, as per the plans of the Department. In conclusion, it was found that the legal system of India is based on common law, which is based on English law. According to the Constitution of India, a quasi-federal structure has been approved, which provides for the division of legislative power between the central government and the individual states. Foreign direct investment in India is governed by two main pieces of legislation. The first is the Foreign Exchange Management Act of 1999, its main objective is to facilitate foreign trade and foreign exchange and to develop and maintain the Indian foreign exchange market. The second – Consolidated policy on attracting FDI to India. Attracting foreign direct investment in India is possible in two ways: automatic investment of FDI and obtaining permission for FDI.

Exploring the Influence Dynamism of Economic Factors on Fluctuation of Exchange Rate - An Empirical Investigation for India Using ARDL Model

The Indian Foreign Exchange Market has experienced significant changes over the past decade, due to high degree of instability of the Indian Rupee leading to its devaluation against major global currencies. Exchange rate is considered as one of crucial indicators to determine the economic growth. Volatility of exchange rate of each day is influenced by various factors such as demand and supply, Gross Domestic Product, Interest rate, employment rate, public debt, balance of payments, inflation etc. Though there are multiple causes to determine the movement of exchange rate, but still the accurate level of causation is unpredictable. Keeping this in mind, this paper tries to attempt the relationship that exists between the exchange rate and select macroeconomic factors. To analyse the extent of influence of the selected variables on the exchange rate, the research paper uses 10 years of data spanning from Jan 2013 to Nov 2022. Further, the study uses monthly data of above-mentioned variables to bring out the analysis to meet the objectives. Descriptive statistics is used to find the characteristics of the data, correlation analysis and Ordinary Least Square method is used to find the relationship and impact level select macroeconomic factors on exchange rate. Autoregressive Distributed Lag (ARDL) model is used to find if any short run and long run association exists between the variables and the exchange rate.

Fundamental Analysis of the Indian Foreign Exchange Market

Fundamental Analysis of the Indian Foreign Exchange Market

Interaction Between Spot and Future Currency Market of India: Empirical Evidence

The study empirically analyses the interdependence and price discovery mechanism between the spot and futures (S&F) prices of the Indian Foreign Exchange Market. Daily closing prices of S&F currency pairs were collected from February 2010 to March 2021. Before investigating causality, the descriptive statistical test and unit root test (augmented Dickey–Fuller) are used to test the stationarity of data. An error correction model examines the long- and short-run relationship between S&F market currency pairs. The currency returned series stationarity at I(1) identified the presence of heteroscedasticity and found the absence of the Autoregressive Conditional Heteroskedasticity effect. To avoid the possible ignorance of the long-run relationship between S&F and to confirm the trustworthiness of regression at levels, the cointegration technique was employed under Johansen’s technique. The existence of cointegration at levels provides power to use Vector Error Correction Models, considering the level and difference in the estimation process. There is a long-run equilibrium relationship between spot rates and future rates, with a bidirectional causal association among currency S&F prices of all the currency pairs. Additionally, the futures market tends to regulate any new data quicker than the spot market. It suggests that spot price is led by future price, thus contributing substantially to the price-discovery process. The Generalized Autoregressive Conditional Heteroskedasticity models establish persistence in volatility, and the bad news gives rise to more volatility as compared to good news.

Impact of currency futures on spot rate volatility in Indian foreign exchange market

The work aimed going to ascertain the efficacy of the currency futures on cash-market or Spot exchange rates volatility with respect of USD/INR, EURO/INR, GBP/INR & JPY/INR. The daily closing of have been taken from RBI website. Also, the time series data is checked for stationarity using ADF test. Existence of ARCH effect examined in spot rate residual of the return series data and checked with Autoregressive conditional heteroskedasticity L.M. test by using GARCH (1,1) model. Findings of GARCH model shows that large volatility is persistent pre-introduction of currency futures and finding shows presence of time-varying conditional volatility of returns of currencies spot prices at pre-post and total period of currency futures introduction in currency exchange market. The variances in volatility of the exchange rate returns of pre and post introduction of currency futures time periods being analyzed by using statistical tools. Findings shows to be importantly varied and volatility has been came down in the post futures era also series were found more stable in terms of volatility.

Impact of Currency Futures on Spot Market Volatility in Indian Foreign Exchange Market

Impact of Currency Futures on Spot Market Volatility in Indian Foreign Exchange Market

Second Moment Spillover Across Stock and Indian Forex Market During Covid-19 Pandemic

This paper explored the second moment spillover across stock market (domestic & foreign) and Indian Foreign Exchange market (INR/USD, INR/GBP & INR/ JPY) with three data frames labelled: Full Period (April 2, 2014, to March 31, 2021), Pre-Covid Period (April 2, 2014, to January 29, 2020) & Post-Covid Period (January 20, 2020, to March 31, 2021) by deploying Diebold & Yilmaz (2012) method. The empirical results insinuate that there is low connectedness across foreign (S&P 500; FTSE 100) and Indian Forex market except in case of Nikkei 225 which disappear in pre-covid period but inflate in post-covid period with moderate connectedness. Similarly, low connectedness across domestic stock market & Indian Forex market is experienced except in case of INR/JPY rate. Furthermore, in the context of own inducement, each series has shown high spillover which gradually decrease in post-covid period but in contrast, inducement from stock to forex market has increased except in case of CNX Nifty & INR/GBP. This empirical evidence expounds the presence of contagion effect across both the markets.

Impact of Currency Futures on Spot Market Volatility in Indian Foreign Exchange Market

This work is an endeavor to explore the relationship of Lag between future & underlying market, ie. Spot in foreign exchange market of India. Only the USD/INR exchange rate is considered for the study for the presented work. This study is comprised of both analytical and empirical. The daily exchange rates of US Dollar and Indian Rupee (INR) were collected over some time from 30th January 2015 up to 23rd November 2020. The presented study has been worked out in four phases. First is to get (Augmented Dickey-Fuller), unit root and stationarity tests PP (i.e., Philips- Perron) & Kwiatkowski Phillips Schmidt-Shin) is being applied to check time series data stationarity. Second, to get cointegration between the futures and spot market tests (Johansen’s Cointegration Test) was used. Granger Causality and Vector error correction models are used to get the lag relationship between futures and spot markets. The results depict the long-run relationship between the spot market and futures market, and the futures market is seen as leading in the empirical analysis of this paper. From the perspective of Investors, hedgers, and Policy Maker, Currency Futures has more helpful information to work further.

‘Manna from heaven’: does the presence of central banks make technical analysis profitable?

Profitability of technical-analysis strategies has been explained with reference to central-bank intervention in markets (Neely 1998; LeBaron 1999; Saacke 2002). I argue that central-bank intervention is a market shock which leads to a generation of trends, making technical analysis profitable. Looking at empirical evidence from the Indian foreign-exchange market, I find returns calculated for the entire period are consistently and substantially higher than when intervention periods are removed. Thirteen out of the 15 strategies demonstrate higher returns with intervention periods included, compared to without intervention periods. The Kolmogorov–Smirnov sample tests show statistically significant differences in the returns between the entire period and the without-intervention period for four strategies, which is confirmed by bootstrap estimation. The paper contributes first by including actual trading strategies in the empirical testing of profitability of technical analysis and second by emphasizing the efficacy of technical analysis rather than the action of the central bank itself in explaining profitability, in a departure from the existing literature.

Predicting Exchange Rate Using Fundamental and Technical Analysis: Evidence from Indian Foreign Exchange Market

Predicting Exchange Rate Using Fundamental and Technical Analysis: Evidence from Indian Foreign Exchange Market

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.

Dynamics of volatility spillovers with structural breaks in Indian foreign exchange market

This research examines volatility spillovers with structural breaks in case of United States dollar (USD), Great Britain pound (GBP), Euro (EURO) and Japanese yen (JPY) of the Indian foreign exchange market from 3 January 1999 to 27 July 2018. First, the Bai and Perron test has been applied to know the structural break dates. We have found significant evidence of structural breaks in case of the respective currencies indicating one structural break in case of USD, two structural breaks in case of EURO, JPY and no structural break in case of GBP. Later on, the volatility has been checked applying the GARCH and EGARCH models on the total sample and the various sub-samples as defined by the structural breaks. In comparison to the full sample, the results of the model parameters estimates vary substantially across the various sub-samples.

Role played by FMC in the Indian Economy and Merger of Forward Market Commission in SEBI

Foreign exchange market in India started three decades ago when in 1978 the government allowed banks to trade foreign exchange with one another. Today over 70% of the trading in foreign exchange continues to take place in the inter-bank market. The market consists of over 90 Authorized Dealers (mostly banks) who transact currency among themselves and come out “square” or without exposure at the end of the trading day. Trading is regulated by the Foreign Exchange Dealers Association of India (FEDAI), a self-regulatory association of dealers. Since 2001, clearing and settlement functions in the foreign exchange market are largely carried out by the Clearing Corporation of India Limited (CCIL) that handles transactions of approximately 3.5 billion US dollars a day, about 80% of the total transactions. This paper is divided in to four sections section one deals with the introduction of the study along with the exchange rate systems, section two tries to explain the trends in the Indian foreign exchange market whereas section three explains the features of the different components of the foreign exchange markets, section four assess and analyse the regulations and the role played by the forward market commission in Indi till its merger. The Financial Sector Legislative Reforms Commission (FSLRC) had earlier stressed on the need to move away from sector-wise regulation. It proposed a system in which RBI would regulate the banking and payments system, and a Unified Financial Agency (UFA) would subsume all other financial sector regulators such as SEBI, IRDA, PFRDA and FMC, to regulate the rest of the financial markets, which results in the merger of the FMC with SEBI. Hence section four focuses on the recent merger of this organisation with SEBI.

Evolving Efficiency of Exchange Rate Movement: An Evidence from Indian Foreign Exchange Market

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 findings suggest that market efficiency is not an all-or-nothing condition; it varies over time. We also find that episodes of efficiency coincide with emergence of major events and market microstructure issues. Particularly, changes in exchange rate regime, financial turbulence, major central bank interventions and trade volume are the prominent causes for time-varying efficiency in INR–USD exchange rate. The evidence of swing between efficiency and inefficiency can prompt currency traders to exploit arbitrage opportunities that emerge with different market conditions.

Dynamics of Volatility Spillovers with structural breaks in Indian Foreign exchange market

This research examines volatility spillovers with structural breaks in case of United States dollar (USD), Great Britain pound (GBP), Euro (EURO) and Japanese yen (JPY) of the Indian foreign exchange market from 3 January 1999 to 27 July 2018. First, the Bai and Perron test has been applied to know the structural break dates. We have found significant evidence of structural breaks in case of the respective currencies indicating one structural break in case of USD, two structural breaks in case of EURO, JPY and no structural break in case of GBP. Later on, the volatility has been checked applying the GARCH and EGARCH models on the total sample and the various sub-samples as defined by the structural breaks. In comparison to the full sample, the results of the model parameters estimates vary substantially across the various sub-samples.

Dynamics of Indian Foreign Exchange Market Efficiency : An Adaptive Market Hypothesis Approach

Adaptive market hypothesis (AMH), a recent evolution in the field of finance, advocates that market efficiency is a time-variant element. In the present study, we empirically verified the time-varying degrees of market efficiency as per the propositions of AMH in the Indian foreign exchange market, which is assumed to provide an evolutionary alternative to the efficient market hypothesis (EMH). For the purpose, we used daily bilateral exchange rate between Indian rupee/United States dollar from January 1999 to December 2015. Statistical tests with linear and nonlinear approaches and better power properties unlike previous studies were used to trace the market efficiency. All tests employed unanimously supported time-varying nature of efficiency in foreign exchange returns, which adhere to the premise of AMH. The findings of the study confirmed market efficiency as an element which evolves with different market conditions, and thereby suggested for adoption of active portfolio management strategies for currency traders.

Covered Interest Parity Arbitrage and Long-Run Relation between Spot and Forward Rates in Foreign Exchange (Rupee/Dollar) Market in India-Study of Market Efficiency with Arima (p, d, q) Forecasting

The study examines the relation that spot exchange rate maintains with contemporaneous and one – month lagged forward rates in the framework of covered interest parity arbitrage in Indian foreign exchange (rupee/dollar) market from 3 rd January, 2011 to 2 nd November, 2015. ARIMA (4, 1, 0) stochastic structure of monthly spot rate (S t ) has been used to generate one – period ahead forecast (S e t+1 ) series. These forecasts are MMSE forecasts and ‘Rational’ by nature. The study shows that one – month lagged forward rate maintains an independent long – run stable relation with spot rate while there exists no co-integrating relation between spot rate and contemporaneous forward rate. One – period lagged forward rate is an optimal forecast of the next period spot rate in the sense that it will be proved wrong only to the extent ofa white noise error term. Risk premium is absent and CIRAP holds in the market such that lagged forward exchange rate on average equals the spot rate in the long – run. There exists no scope for reaping arbitrage profit arising out of the difference between forward rate and corresponding spot rate. This testifies for the ‘efficiency’ of Indian foreign exchange (rupee/dollar) market.

Dependence structure and portfolio risk in Indian foreign exchange market: A GARCH-EVT-Copula approach

Abstract The study investigates dependence structure and estimates portfolio risk on data from foreign exchange market in India. We specify both marginal models for the foreign exchange returns and a joint model for the dependence. We employ the AR-t-GARCH-EVT models for the marginal distribution of each of five currency returns series. For the joint model, we choose seven copulas with different dependence structure such as Gaussian, Frank, Clayton, Gumbel, BB1, BB2 and BB7 copulas. Using LL, AIC, and BIC values we find BB1 as the best fitted copula. The evidence of tail dependence coefficients suggests that currency markets are more likely to boom together than to crash together. Portfolio risk is measured using VaR and CVaR and global minimum risk portfolio is selected based on efficient frontiers. The evidences have direct implications for investors and risk managers during extreme currency market movements.

A review on pricing of currency futures in Indian foreign exchange market

A review on pricing of currency futures in Indian foreign exchange market

A review on pricing of currency futures in Indian foreign exchange market

This paper attempts to study theoretically the pricing of currency futures and the scope of the available models for pricing. The purpose of this study is to investigate the available literature on pricing of currency futures and understand the empirical analysis employed by various researchers. The thorough review of literature and the study of futures data on National Stock Exchange conclude that in developing countries like India, Athens, etc. the markets are inefficient and thus the future or forward prices become equal to spot prices at the time of expiry i.e., convergence is there. Though this study has not tested the convergence empirically but seeing the pattern of trading and the study on market efficiency in India supports the dependency of two on each other i.e., there is a long run stable relationship between foreign currency spot and futures market.