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In the present study, plant-scale process integration was applied to an Indian paper mill using the water cascade analysis (WCA) technique. Three limiting constraints, chemical oxygen demand (COD), total dissolved solids (TDS), and adsorbable organic halides (AOX), were considered for the study. A nearest neighbor algorithm was used to distribute the freshwater and recycled water among the plant operations. It was found that the limiting critical constraint depends upon the types of processes and streams involved in the integration. The limiting critical constraint can differ for different sections of the same industry, and can differ in different schemes of integration. After process integration, a 55.6% reduction in effluent flow, a 36% reduction in COD, and a 73% reduction in AOX were observed. After process integration, a 35.21% reduction in pollution costs can be achieved and, assuming the average production of the mill to be 225 tons per day, a savings of Indian rupees (INR) 1.73 per kg of paper produced can be achieved by employing process integration. The water cess was calculated as INR 3024.77 per day without integration for the sections that were considered for integration, while after integration, a 41.53% savings in the form of water cess was calculated. [Copyright &y& Elsevier]

Automatic authentication of paper money is becoming an increasingly urgent problem because of new and improved uses of counterfeits. In this paper, we describe a system developed for discriminating fake notes from genuine ones and apply it to Indian banknotes. Image processing and pattern recognition techniques are used to design the overall approach. The ability of the embedded security aspects is thoroughly analysed for detecting fake currencies. Real samples are used in the experiments that show a high-precision machine can be developed for authentication of paper money. The system performance is reported for both accuracy and processing speed. The analysis of security features to prevent counterfeiting highlights some of the issues that should be considered in designing of currency notes in the future. [ABSTRACT FROM AUTHOR]

Since the outbreak of the European war, the flow of rupee coins back from circulation to reserves, which has been going on for many years, has been reversed. The stock of rupee coin in the Reserve Bank of India has decreased, while circulation has increased, between September 1939 and July 1940. This increase of coin circulation has been due partly to the proportional increase of note circulation and to some tendency to hoard coins in preference to notes. To avoid exhaustion of the Reserve Bank's supply of coin, the government of India began the issuance of 1-rupee notes. In December 1940, it announced a reduction in the fineness of the rupee from 11/12 to 0.300. It remains to be seen whether this section will be acceptable to the population.

This paper econometrically models the dynamics of Indian rupee (INR) swap yields based on key macroeconomic factors using the autoregressive distributive lag (ARDL) approach. It examines whether the short-term interest rate has a decisive influence on long-term INR swap yields after controlling for other factors, such as core inflation, the growth of industrial production, the logarithm of the equity price index, and the logarithm of the INR exchange rate. The estimated models show that the short-term interest rate has an important influence on swap yields. This implies that the Reserve Bank of India (RBI) can sway borrowing and lending rates not just on Indian government bonds but also INR-denominated private-market financial instruments, such as swaps and swaptions. [ABSTRACT FROM AUTHOR]

Purpose: The main purpose of this paper is to examine the convergence hypothesis of House Price Index (HPI) in the case of 18 major Indian cities for the period 2014–2019. Design/methodology/approach: To attain the authors main goal, this study applies a clustering algorithm advanced by Phillips and Sul. This test creates a club of convergence based on the growth of the cities in terms of HPI. Findings: The study findings show the existence of two convergence clubs and one non-convergent group. Club 1 includes the cities with high HPI growth, whereas club 2 comprises of cities with least HPI growth. Cities belonging to the non-convergent group are neither converging nor diverging. Practical implications: This study findings will benefit home buyers, sellers, investors, regulators and policymakers interested in the dynamic interlinkages of house price (HP) among Indian cities. Originality/value: The majority of the studies are conducted in the case of China at the province or city levels. Furthermore, in the case of India, none of the studies has investigated the HP club convergence across Indian cities. Therefore, the present study fills this research gap by examining the HP club convergence across Indian cities. [ABSTRACT FROM AUTHOR]

Purpose: In 2014, real estate investment trust (REIT) emerged as a new alternative investment option in India. This research aims to give an empirical authentication of the Indian REITs performance from April 2019 to July 2022 across a range of investment variables. Design/methodology/approach: Using monthly total returns in Indian Rupee, risk-adjusted Indian REIT performance and investment portfolio characteristics are examined. Indian REITs' potential in a diversified multi-asset portfolio is analysed using the mean-variance analysis, asset allocation diagram and efficient frontier. Findings: During April 2019–July 2022, Indian REITs provided a lower return than stocks but outperformed bonds despite coronavirus disease 2019 (COVID-19) lockdowns, which hurt the traditional working from office concept. The study also examined REIT allocation to an Indian mixed-asset portfolio and the benefits of a diversified portfolio. Practical implications: Indian REITs provide a liquid, transparent alternative to direct property for investors seeking exposure to Indian real estate markets. Indian REITs gave real estate companies an extra funding source and investors an alternate asset. This paper explores Indian REITs' potential opportunities, given that domestic and foreign investors' demand for transparent property investment in India. The analysis found a positive early performance despite a challenging environment. Originality/value: This paper offers the first empirical performance validation of Indian REITs as a way to obtain exposure to commercial property in India and the REITs' role in a diversified asset portfolio. The authors' study improves investors' decision-making abilities by providing empirically validated, valuable and practicable property investing insights. [ABSTRACT FROM AUTHOR]

The exchange rate market and stock market are two main financial markets and play a key role in international business all over the world. The interconnection between exchange rate and Indian stock indices is considered an important factor as to forecast the growth and development of Indian economy.This paper focuses on the impact of exchange rate fluctuations on Indian stock market volatility by assessing the Indian rupee rates in dollar terms (₹/$) on Nifty 50,S&P BSE BANKEX, IT INDEX and S&P BSE SENSEX.The data collected for period of study was yearly data of closing prices of ten years i.e., from the year 2010 to 2021. Several statistical tools were applied to measure the impact and association of exchange rate fluctuation on Indian stock market indices by using Correlation, Regression analysis and ANOVA model. From the analysis and results part, we came to the conclusion that there is a very weak and negligible impact of exchange rate (INR/USD)on Indian stock market indices and both the variables are self-regulating of each-other. The main aim of this study is to guide investors, financial managers and analysts to analyse the market trends, to invest with minimum risk and to compare the returns to specific investments. [ABSTRACT FROM AUTHOR]

This paper brings out the effect of movie piracy on legitimate sales of the movies in the Indian context. The paper becomes much more relevant when internet and streaming services are very much common these days. Based on the survey of 500 undergraduates students of university of Delhi, the paper finds that first, one unit of unpaid movie viewing displaces about 0.35 units of paid (first) movie viewings. Second, due to presence of "sampling effect" one unit of unpaid (first) movie viewing increases second paid viewings by 0.1 units. Thus, we find support for incomplete displacement, that is, a displacement rate less than one‐for‐one. Third, these displacements rates are causing an estimated 6.2% loss in sales of movies based on back‐of‐ envelope‐calculation. The number of lost movie sales are 6,3123,667 and approximately Rs 12 billion in Indian rupees as revenue lost due to movie piracy in the year 2019. Finally, Individuals who tend to show greater interests in movies are in fact contributes towards movie sales even though their indulgence in piracy cannot be ignored. [ABSTRACT FROM AUTHOR]

Do market participants look into the past whilst framing the trading decisions today? Microstructure theory shows that participants increase bid‐ask spreads in response to macroeconomic news to account for asymmetric information and inventory costs. However, the role of perceptions or biases of the market participants in influencing the bid‐ask spread has been largely overlooked. This paper incorporates the role of 'Recurrence bias' in influencing trading decisions and therefore market volatility. Empirically, the model is tested using high‐frequency exchange rate data and time‐stamped news data on Indian rupee, which has seen sharp volatility in the period under study. Logit and GARCH analysis shows that volatility is positively linked to 'Recurrence Bias', which arises from the 'availability of mental models' to traders, created by past response of exchange rate to unexpected component of news. [ABSTRACT FROM AUTHOR]

Objective: Paper currency notes are found to contaminate with microbes and the dissemination of antibiotic resistance is a global health problem. The aim of this study was to evaluate the prevalence of multi-drug resistant bacteria in the Indian currency notes. Study design: For this study, the Indian currency notes (rupee notes 10, 20 and 50) were collected from Tamil Nadu, Karnataka, West Bengal, Assam, New Delhi and Gujarat using random sampling technique. The sampling was categorised into; category 1: local markets, beggars, street vendors, conductors, hospitals and Category 2: supermarkets, banks including ATM machines, and hotels. Method: Spread plate technique, specific media and biochemical tests were used for the bacterial isolation and identification. Identification of multiple drug resistance, PCR-based screening of resistance genes and conjugation studies were performed. Results: The total of 75 bacteria was isolated including Bacillus sp., Streptococcus sp., Staphylococcus sp., Staphylococcus aureus, Escherichia coli, Klebsiella sp., Pseudomonas sp. and Salmonella sp. Multi-drug resistance was observed in 32/75 (43%) isolates and the prevalence of 25% ertapenem-resistant and 21% cefotaxime resistant bacteria was observed. The presence of blaCTX-M-9 in three isolates such as E. coli (two) and Klebsiella sp. was screened and E. coli isolates were found to involve in conjugating its resistance to E. coli AB1157. Conclusions: Our study showed the prevalence of multiple drug resistant bacteria in the Indian currency notes and also in disseminating its resistance. [ABSTRACT FROM AUTHOR]

Every day more than 5000 trade companies enlisted in Bombay stock Exchange (BSE) offer an average of 24,00,00,000+ stocks, making an approximate of 2000Cr+ Indian rupees in investments. Thus analyzing such a huge market will prove beneficial to all stakeholders of the system. An application which focuses on the patterns generated in this stock trade over the period of time, and extracting the knowledge from those patterns to predict future behavior of the BSE stock market is essential. An application representing the information in visual form for user interpretation to buy and to sell a specific company's stock is a key requirement. Such an application based on machine learning algorithms is the right choice in current scenario. This paper surveys the machine learning algorithms suitable for such an application; as well it discusses what are the current tools and techniques appropriate for its implementation. [ABSTRACT FROM AUTHOR]

Purpose: This paper investigates the causality among gold prices, crude oil prices, bitcoin and stock prices by using daily data from January 2014 to December 2021. The study also examines the data during the COVID-19 outbreak from January 2020 to December 2021. Design/methodology/approach: To estimate the long- and short-run causality, this study considers the nonlinear autoregressive distributed lag (NARDL) cointegration test. Findings: The analysis found the existence of an asymmetric long-run cointegration among selected assets. Findings indicate that positive changes in bitcoin do not affect stock market in the long term. Changes in crude oil prices have a significant impact on stock prices. Moreover, it is observed that variations in the stock prices trigger a negative impact on gold prices. During the COVID-19 period, the study notices the presence of an asymmetric long-term cointegration between selected assets except bitcoin. Besides, findings revealed that negative price adjustments in gold lead to significant positive shocks in stock market. Originality/value: These results provide critical information for policy performers and researchers to develop new strategies. Policy regulators can also consider the potential effects of the COVID-19 outbreak while developing strategies for investment decisions. [ABSTRACT FROM AUTHOR]

India has been facing the problem of continuing depreciation of its currency against US Dollar over the past few decades. Related existing literatures have identified some factors that may have contributed to this phenomenon. The current paper determines the relative importance of each factor towards currency depreciation in India by means of quantile regression analyses. Our analyses suggest that India's increasing Current Account Deficit (CAD), oil and gold imports, and changes in domestic prices relative to world prices (considered to be an indicator of inflation) are the most significant contributors towards depreciating Indian currency. However, the effects of these factors vary across the distribution of exchange rate. [ABSTRACT FROM AUTHOR]

This paper investigates the degree of connectedness of Asia Pacific forex markets post‐global financial crisis and relates it to developments in the renminbi markets. The connectedness measure developed by Diebold and Yilmaz (2014) (Journal of Econometrics, 182, 119–134) reveal the strength of linkages across the U.S. dollar currency pairs of 12 currencies, namely offshore renminbi, onshore renminbi, euro, yen, Australian dollar, Indian rupee, Korean won, Malaysian ringgit, New Zealand dollar, Singapore dollar, Thai baht and Taiwan dollar. With the gradual liberalization of China's exchange rate system, shocks from the renminbi markets contribute more to fluctuations in almost all individual Asia Pacific currency markets vis‐à‐vis the yen. Rolling regressions show a number of Asia Pacific currencies exhibit tighter association with the renminbi when the latter underwent exchange rate regime reform. Finally, results from a two‐step analysis involving a panel regression provide evidence that time‐varying sensitivities of Asia Pacific currencies to the renminbi are directly related to the countries' trade and financial links with China. [ABSTRACT FROM AUTHOR]

This paper examines the relationship and related causality patterns of oil price volatility and exchange rate volatility of a group of oil-dependent economies before and after the 2008–2009 global financial crisis. We employed weekly time-series data of oil price and exchange rates for 2000–2007 (pre-crisis) and 2010–2016 (post-crisis). United States dollar exchange rates are for Ghanaian cedi, Nigerian naira, Russian ruble, Indian rupee, South African rand, and the Euro. To investigate the volatility impacts that exist between oil price and exchange rates during both sub-sample periods, we merged Vector Autoregressive (VAR) with GARCH and EGARCH models in the form of Bivariate VAR-GARCH and VAR-EGARCH. We further adopted the Toda-Yamamoto causality test to investigate related causality patterns. Empirical findings revealed both bidirectional and unidirectional relationship between oil price volatility and the exchange rates volatility of four out of the six oil-dependent economies considered for the study. These findings were more prevalent in the post-crisis period than the pre-crisis period. We also confirmed both bidirectional and unidirectional causality pattern between oil price volatility and exchange rate volatility of the same four currencies as observed with the VAR results in both sub-sample periods. [ABSTRACT FROM AUTHOR]

The paper uses a vector error correction model–multivariate generalized autoregressive conditional heteroskedasticity approach to examine the interrelationship between onshore and offshore nondeliverable forward (NDF) markets for the Indian Rupee. The empirical results suggest a stable and bidirectional long‐run relationship between onshore and offshore markets. The subperiod analysis implies that there are unidirectional mean spillovers from NDF markets to onshore spot, forward, and futures markets during the post‐taper tantrum period. Regarding "volatility spillover," the analysis indicates a unidirectional volatility spillover from spot and forward segments to NDF market in normal circumstances, which turns bidirectional during times of depreciation pressure on the rupee. [ABSTRACT FROM AUTHOR]

In practice, sequential processes often have gradual changes in their process distributions over time. This is related to the drift detection problem in statistical process control. In the literature, there have been some existing discussions on this problem. But, most existing methods are designed based on the assumption that the related drift is linear or have another specific pattern. In reality, however, such specified patterns may not be valid. In this paper, we suggest an adaptive cumulative sum (CUSUM) chart to handle the drift detection problem with a flexible drift pattern. The new method integrates the general framework to construct a CUSUM chart based on the generalized likelihood ratio statistic and estimation of a shift size by the exponentially weighted least square regression procedure. Simulation studies show that the proposed method is effective in various cases considered. The new method is also illustrated using an example about the exchange rates between Indian Rupees and US Dollars. [ABSTRACT FROM AUTHOR]

Intermodal transportation requires multiple entities to manage diverse resources under complex regulations and contracts. In this paper, we carry out a multidisciplinary cross-functional analysis of container rail haulage pricing and operations in India. We discover that the total haulage cost of a container train unduly depends on the position of the containers within the train, which is referred to here as position arbitrage. The main objective of this paper is to introduce and analyze this new concept of arbitrage for the first time in the literature. We derive the limits to the arbitrage, present management insights and empirical results, and explain that the arbitrage is undesirable because of its adverse effects on the efficiency of the container supply chain. With a real case, we empirically show that container train operators can save an average of 450 million INR annually by exploiting the arbitrage. On completion of dedicated freight corridors, the annual total value of the arbitrage can increase by one billion Indian rupees. This research is also beneficial for the railways to understand the implications of haulage pricing on operational efficiency and also for the port operators and shippers to understand the implications of the arbitrage for their operations. [ABSTRACT FROM AUTHOR]

In present days, the cultivation of land at the tail end has reduced, reasons being - insufficient irrigation water and inefficient distribution of canal water to the tail ends. As a result, farmers of Peddapatnam village are unable to carry out cultivation satisfactorily. This study is carried out to address this problem and to provide remedies. Peddapatnam canal is selected as the study area in the present paper. This canal (16°21'35.89"N, 81°15'42.82"E - 16°19'24.92"N, 81°19'46.10"E) is a branch canal of Bantumilli main canal (16°20'37.00"N, 81°3'28.61"E - 16°23'52.02"N, 81°26'13.82"E), located in Krishna district of the Andhra Pradesh State. The water from the canal is the only source for cultivation and groundwater is unsuitable as it contains a large amount of salts. Firstly, the current flows of the Bantumilli canal are found and the total cultivable land in the purview of the canal is determined. Later, a topographic survey is conducted and the longitudinal profile of the canal is drawn. Farmers and irrigation experts (who are familiar with the study area) were interviewed to know the causes and find possible remedies for the problems encountered. The problems identified are, viz., (i) Low maintenance of the canal (ii) Canal being unlined (iii) Absence of protection of side banks (iv) Damage caused by animal movements (v) Siltation (vi) Non-cooperation of some influential farmers. Seepage and evapo-transpiration have also greatly affected the efficiency of canal distribution. Based on the above observations, two recommendations are proposed, viz., (i) Construction of a retaining wall or (ii) Construction of a canal lining. Additionally, it is recommended to install solar panels along the canal to address the power shortage problem of that area. An income of 30 million Indian rupees is realized due to the installation of a canal-top solar plant, for the cash-strapped region under study. [ABSTRACT FROM AUTHOR]

The global financial crisis and its aftermath triggered extraordinary policy responses in advanced countries. Their impacts—from asset price bubbles to currency depreciations—have often been felt in the developing world, and the same can be expected from their undoing. India's experience around the Fed's 'taper talk' announcement of 2013 offers insights which could be relevant for other countries as quantitative easing programmes wind down and monetary policy is 'normalized'. This paper estimates the contribution of external and domestic factors to long‐run trends and short‐term fluctuations in the value of the Indian rupee around the 2013 depreciation episode using a rich dynamic model that controls for a large number of exchange‐rate determinants. The paper finds that a global surprise factor, more than domestic vulnerabilities, was the main driver of the large rupee depreciation in the summer of 2013. [ABSTRACT FROM AUTHOR]

Intermodal transportation requires multiple entities to manage diverse resources under complex regulations and contracts. In this paper, we carry out a multidisciplinary cross-functional analysis of container rail haulage pricing and operations in India. We discover that the total haulage cost of a container train unduly depends on the position of the containers within the train, which is referred to here as position arbitrage. The main objective of this paper is to introduce and analyze this new concept of arbitrage for the first time in the literature. We derive the limits to the arbitrage, present management insights and empirical results, and explain that the arbitrage is undesirable because of its adverse effects on the efficiency of the container supply chain. With a real case, we empirically show that container train operators can save an average of 450 million INR annually by exploiting the arbitrage. On completion of dedicated freight corridors, the annual total value of the arbitrage can increase by one billion Indian rupees. This research is also beneficial for the railways to understand the implications of haulage pricing on operational efficiency and also for the port operators and shippers to understand the implications of the arbitrage for their operations. [ABSTRACT FROM AUTHOR]

The present paper attempts to identify the ways that the Indian IT companies manage their Forex risk with the use of financial derivatives. This risk cannot be avoided, but can be managed by derivative instruments. The need and approach for managing it depends on the size of exposure and fluctuations in exchange rate. Indian IT sector is known for development of software and it mainly depends on exports. They are required to measure and manage exchange rate risk. Hence, an attempt is made in this paper to fill this gap, by documenting the management of forex exposure by using financial derivatives of IT firms in India. [ABSTRACT FROM AUTHOR]

The current study tries to empirically investigate the hedging and safe haven characteristics of gold against stock markets, crude and foreign exchange movement for India for the period 1 April 2008–31 March 2019 by taking daily closing prices obtained from www.investing.com (converted to returns). The methodology includes using both traditional OLS and quantile regression approaches by setting up both linear and nonlinear relationships amongst the assets. A separate section in the paper has been devoted which covers the Sub-Prime Crisis of 2008. The results of the study showed that gold acted as a hedge asset with respect to Nifty Stock Index and Exchange Rate but not against Crude when the OLS linear and nonlinear models were employed. Further both linear model and nonlinear OLS regression models ruled out the safe haven characteristics of gold with respect to any of the three assets. However, for quantile regression, hedge characteristics of gold were established at only few quantiles with respect to the same two assets, i.e. Nifty and foreign exchange. With respect to safe haven characteristics of gold under OLS, for both linear as well as nonlinear models, gold did not seem to act as a safe haven, while for quantile models, gold acted as a safe haven only at lower tail(s) for Exchange Rate in the linear model and against Nifty Stock Index for nonlinear model. This shows that quantile regression was able to capture the hedging and safe haven characteristics of gold in a superior manner by doing a comprehensive analysis which was based on eleven different quantiles. Such an analysis is much superior to the traditional OLS which gives only an overall broad assessment of the gold's hedging capacity. Further, the behaviour of gold return as an asset during the sub-period crisis of 2008 was not substantially different from its behaviour during other periods; however, when the yardstick of measurement was changed to return volatility of gold, the behaviour was found to be different from other periods. The asymmetric impact of return on gold with respect to all other assets was also proved in our study. [ABSTRACT FROM AUTHOR]

Economic assets play a key role in the growth of renewable power projects and depend on financial scenarios and policy structures offered by government policies. The focus of the study is to assess the impact of the existing economic scenarios and related government policies on wind and solar power deployment in India. The financial analysis of wind and solar power projects, along with parametric and sensitivity analysis, were performed based on the techno-economic parameters of recent wind and solar energy projects. Factors incorporated into the study are capital cost, annual cash flow, project terminal cost, discount rate, cost of capital, tax rate, capacity factor and technological degradation factor. The results show that the values of levelized cost of electricity (LCOE) calculated for recent wind and solar projects are ₹4.89/kWh ($0.0698/kWh) and ₹4.05/kWh ($0.0578/kWh), respectively, which can be reduced to ₹2.36/kWh ($0.0337/kWh) and ₹2.12/kWh ($0.0303/kWh) through proper amendments to the existing policy, an improved financial framework and technological enhancements. The study will be beneficial to policymakers and project developers, helping to boost the future deployment of wind and solar power projects. (Note: USD ($) was converted to Indian rupee (₹) at an exchange rate of 1$ = 70₹ throughout the paper.) [ABSTRACT FROM AUTHOR]

This paper revisits Keynes's writings from Indian Currency and Finance (1913/1971) to The General Theory (1936b/1973) with a focus on financial instability. The analysis reveals Keynes's astute concerns about the stability/fragility of the banking system, especially under deflationary conditions. Keynes's writings during the Great Depression uncover insights into how this event may have informed his General Theory. By exploring the connection between the experience of the Great Depression and the theoretical framework, Keynes presents in The General Theory, we can see that the assumption of a constant money stock featuring in that work is central. The analysis underscores the case that The General Theory is not a special case of the (neo-) classical theory that is relevant only to "depression economics"--refuting the interpretation offered by J. R. Hicks (1937) in his seminal paper "Mr. Keynes and the classics: A suggested interpretation". As a scholar of the Great Depression and Federal Reserve chairman at the time of the modern crisis, Ben Bernanke provides an important intellectual bridge between the historical crisis of the 1930s and the modern crisis of 2007-2009. The paper concludes that, while policy practice has changed, the "classical" theory Keynes attacked in 1936 remains hegemonic today. The common (mis-)interpretation of The General Theory as depression economics continues to describe the mainstream's failure to engage in relevant monetary economics. [ABSTRACT FROM AUTHOR]

This research paper is related to the devaluation of rupee in India. After 1947, India has faced two major financial crises and two consequent devaluations of the rupee. These crises were in 1966 and 1991 and now in 2013 the situation is also parallel and very destructive, as I plan to show in this paper, they had similar causes. The price of 16 Ananas is 1 rupee in 1947. The demand for decimalization existed for over a century. Sri Lanka decimalized its rupee in 1869. The Indian Coinage Act was amended in September 1955 for the adoption of a decimal system for coinage .it, however, was now divided into 100 'Paisa' instead of 16 Ananas or 64 Pice. In 1947 the value of rupee was one against the US dollar and in 1966 was 7.5, and in 1990 was 17.01 but it is 63.54 at November 2013. The Indian rupee touched a lifetime low of 68.85 against the US dollar on August 28, 2013. The rupee plunged by 3.7 percent on the day in its biggest single-day percentage fall in more than two decades. There is no denying that India is not the only emerging market experiencing a rapid decline in its currency's value. Since January 2013, the rupee has lost more than 20 percent of its value, the biggest loser among the Asian currencies. In this research we will learn about the reasons, causes and effects, and suggestions to evaluate the impact of the falling rupee on the Indian economy. [ABSTRACT FROM AUTHOR]

The Indian exchange rate system has matured from the earlier versions of a managed float system to a floating exchange rate system. India has followed the system of market determined foreign exchange rate since 1993 by replacing the dual exchange rate system or LERMS (Liberalized Exchange Rate Management System). Therefore, the behavior of volatility in exchange rate of Indian Rupee as against U.S. Dollar (before the implementation of market-determined exchange rate regime and after the implementation of market- determined exchange rate regime) has been empirically analyzed under the study to compare the volatility of Indian foreign exchange rate (high) in pre market- determined regime with that of the post market- determined regime period. The study revealed that the volatility of Indian foreign exchange rate remained high in the post market- determined regime than that in the pre market- determined regime. [ABSTRACT FROM AUTHOR]

This paper analyzes the asymmetric volatility of foreign exchange rates with respect to the Indian rupee by identifying associated macroeconomic regimes in India. The paper aims to analyze the volatility spillovers and other relationships of the Indian rupee (INR) with respect to the US dollar (USD), Canadian dollar (CAD), British pound (GBP), Swiss franc (CHF) Japanese yen (YEN) and the euro (EUR) for the period 1973-2012. The study makes use of GARCH family models. The results show that the daily exchange rates of all the currencies considered exhibit volatility persistence and conditional autocorrelation. It is also found that the impact of exchange rate innovations on the conditional variance of the foreign exchange return series varies across the macroeconomic regimes. [ABSTRACT FROM AUTHOR]

The long run dynamics of Indian foreign exchange market with respect to Indian Rupee-US Dollar spot rate can be attributed to interplay of several domestic, foreign and global factors. This paper attempts to identifies whether there exists any long term equilibrium relationship among macroeconomic variables of India and US, Indian Rupee-Euro spot rate, Indian Rupee-Yen spot rate, Indian Rupee- UK Pound spot rate and Indian Rupee-US Dollar spot rate. Time series analysis has been undertaken for ten year period of April, 2005--March, 2015 using monthly data of these variables. The variables considered are money stock (India and US), nominal long run bond yield (India and US), commodity price levels (India and US), stock prices (India and US), forward premium in Indian rupee-US dollar forward market, foreign exchange reserves with Reserve Bank of India, Indian rupee-euro spot rate, Indian rupee-British pound spot rate and Indian rupee-Japanese yen spot rate. Johansen's co-integration analysis indicates that all Indian and US macroeconomic variables and other currency pairs of rupee are in a long run relationship with rupee-dollar spot rate. [ABSTRACT FROM AUTHOR]

In this paper we assess the equilibrium value of the Mauritian rupee in 2006-7 and over the medium run using two structural models. First, we derive a current account-based measure of the exchange rate equilibrium using the macroeconomic balance approach. Second, we estimate a reduced-form fundamental equilibrium exchange rate measure. Our results, which are robust to an alternative non-econometric approach, suggest that the Mauritian rupee was aligned with its equilibrium value in 2006-7 and little adjustment appeared necessary over the medium run. [ABSTRACT FROM AUTHOR]

Foreign exchange risk management is a new challenging area. After globalization, the perfection in exchange rate forecasting is very essential for hedging decisions. In this paper, an attempt has been made to estimate the parameters of Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and apply them to simulate and predict the rupee/US dollar exchange rates. The emphasis of these methods is not on constructing single equation or simultaneousequation models but on analyzing the probabilistic or stochastic properties of economic time series on their own under the philosophy of letting the data speak for themselves. As a matter of fact, many econometric time series exhibit periods of unusually large volatility, followed by periods of relative tranquility. In such circumstances, the assumption of homoscedasticity is inappropriate. It is a particular kind of the Heteroscedasticity in which the variance of the regression error depends on the volatility of the errors in the recent past. Engle suggested the use of Autoregressive Conditional Heteroscedasticity (ARCH) model to take care of such Heteroscedasticity in order to raise the efficiency of forecasts. Many of the lagged values of unconditional error variance can be replaced with one or two lagged values of conditional error variance. This leads to the GARCH model. The main objective of this paper is to study the GARCH-based minimum mean squared error ARIMA forecast for rupee/dollar exchange rate and draw a comparison between ARIMA, GARCH-based ARIMA and RBI forecasting. [ABSTRACT FROM AUTHOR]

Energy in different forms is required to drive a nation's growth and its sustenance. However, a significant issue that plagues the world is exploitation of fossil fuel negligently, for domestic and commercial requirements. The Government of India (GoI) has devised its renewable energy policies to encourage and promote the use of renewable energy sources in an efficient manner. In this paper, feasibility is explored for employing solar PV power generation at a wind power generation site through hybridization such that power production can be improved throughout the year. Simulation studies have been conducted for the site using RETScreen to analyze hybrid power generation at Harapanahalli in Karnataka, India. The wind farm has 18 wind turbine generator (WTG's) installed, having 2 MWe capacities each, producing 36 MWe supplied to the local grid. By using sun path and shadow analysis for the site, it is calculated that 344,531.25 m2 of shadow‐free space is available which can be suitably used for alternate methods of power generation. From the present analysis, it is predicted that annual power generation capacity of the site can be improved by about 90% on adopting hybrid power generation. The project cost is pegged at 188 crores Indian rupees (INR) and the payback period of the hybrid system was ascertained to be approximately 7 years. [ABSTRACT FROM AUTHOR]

This paper studies strategic consumer shopping behavior in response to a macroeconomic policy and quantifies its unintended consequences for retailers vis-à-vis the policy goal. Using transaction-level data from a large retail chain in India, we document consumer strategies that leverage retailers to avoid costs associated with the country's currency reform policy. We observe both an increase in returns of cash-purchased items that were bought before demonetization (strategic returns) and a spike in final (unreturned) cash purchases with soon-to-be-illegal notes (strategic purchases). Both practices serve consumer incentives either to receive legal notes from the retailer or to avoid depositing cash in formal bank accounts. Our analysis suggests that strategic consumers hindered the intended policy effect while partly benefiting the retail chain, leaving 20 million Indian rupees (INR) ($0.3 million) of demonetized notes outside the formal tax network through this retail chain only; when we scale up the estimates to the country's market size, the estimated total impact reaches 100 billion INR ($1.5 billion). Our findings offer implications for policy makers by quantifying a wide spillover effect of government interventions that goes beyond the target group and document a new role of the retail industry: of absorbing and facilitating a response to macroshocks. History: Avi Goldfarb served as the senior editor for this article and Nitin Mehta served as the associate editor for this article. Funding: Chintagunta thanks the Kilts Center of Marketing at the University of Chicago for financial support. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mksc.2022.1358. [ABSTRACT FROM AUTHOR]

The Reserve Bank of India (RBI) used exceptional monetary measures to address the taper tantrum-induced exchange market pressure on the rupee in the third quarter of 2013. This paper provides theoretical and empirical justifications for using the monetary policy to defend the exchange rate under exceptional circumstances, and also outlines certain preconditions which may determine the success of such a policy response. The empirical hypothesis on the effectiveness of an interest rate defence has been examined using four alternative approaches: first, the conventional monetary approach to exchange rate; second, uncovered interest rate parity (UIP) condition in the presence of timevarying risk premium; third, impact assessment in a vector auto regression (VAR) framework; and fourth, a comparative quantitative assessment of the costs associated with depreciation of the rupee relative to a higher interest rate for the Indian corporate sector in a panel regression framework. The scope for different policy inferences that could be derived from the results of alternative approaches highlight the need for a careful assessment of preconditions while designing and applying monetary measures to stabilise the exchange rate. [ABSTRACT FROM AUTHOR]

The fiscal policy's impact on the real exchange rates is highly controversial in theory and practice but noteworthy for macroeconomic policy. This issue is more pertinent in developing countries with an active fiscal policy or wider fiscal space but is explored less. To our knowledge, the fiscal policy impact on the real exchange rate in India is not documented. Against this backdrop, this study explores this in India involving disaggregated data of government consumption and investment spending and a few related variables like trade openness, private consumption spending, and money supply for the period 1996:1–2023:1. The results corroborate long-run associations of real exchange rate and some combinations of the selected other variables. The real exchange rate dynamics estimated through the cointegrated vector autoregressive model followed by an impulse response analysis have shown that government investment spending causes a real appreciation. In contrast, government and private consumption spending exert pressure to depreciate the real exchange rate. Trade openness is another potent predictor of the real exchange rate. On the other hand, no significant impact of the money supply on the real exchange rate is noticed. The results accentuate effective fiscal allocation may be a policy tool for stabilizing the Indian rupee. The unique findings on the Indian economy may also help understand the fiscal effect of real exchange rates in other developing countries. [ABSTRACT FROM AUTHOR]

Rajasthan Urban Sector Development Program involved investment in water supply, sewerage, sanitation, and drainage, solid waste management (SWM), and etc. in major cities in the state of Rajasthan in India. This program was an initiative of the Government of Rajasthan and the Government of India carried out with a loan arrangement from Asian Development Bank. The phase II of the program was implemented in 15 cities of Rajasthan including Bharatpur with total investment of 1868.40 million Indian Rupees. The objective of this paper is to evaluate the economic viability of the infrastructure investments in Bharatpur in water supply, sewerage, sanitation, and drainage, SWM, and measure the impact on urban poor. Water supply, sewerage, sanitation, and drainage, and SWM subprojects are economically viable with internal rate of return (IRR) of 85.72%, 22.87%, and 39.34%, respectively. The sensitivity analysis shows above 12% IRR for all the above‐mentioned subprojects. The distribution of project benefits to the urban poor in Bharatpur is significant with poverty impact ratio of 9%. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to examine whether volatility implied from dollar-rupee options is an unbiased and efficient predictor of ex post volatility, and to determine which options market is a better predictor of future realized volatility and to ascertain whether the model-free measure of implied volatility outperforms the traditional measure derived from the Black–Scholes–Merton model. Design/methodology/approach: The information content of exchange-traded implied volatility and that of quoted implied volatility for OTC options is compared with that of historical volatility and a GARCH(1, 1)-based volatility. Ordinary least squares regression is used to examine the unbiasedness and informational efficiency of implied volatility. Robustness of the results is tested by using two specifications of implied volatility and realized volatility and comparison across two markets. Findings: Implied volatility from both OTC and exchange-traded options is found to contain significant information for predicting ex post volatility, but is neither unbiased nor informationally efficient. The implied volatility of at-the-money options derived using the Black–Scholes–Merton model is found to outperform the model-free implied volatility (MFIV) across both markets. MFIV from OTC options is found to be a better predictor of realized volatility than MFIV from exchange-traded options. Practical implications: This study throws light on the predictive power of currency options in India and has strong practical implications for market practitioners. Efficient currency option markets can serve as effective vehicles both for hedging and speculation and can convey useful information to the regulators regarding the market participants' expectations of future volatility. Originality/value: This study is a comprehensive study of the informational efficiency of options on an emerging currency such as the Indian rupee. To the author's knowledge, this is one of the first studies to compare the predictive ability of the exchange-traded and OTC markets and also to compare traditional model-dependent volatility with MFIV. [ABSTRACT FROM AUTHOR]

This paper considers the prediction of currency exchange rate, volatility, and momentum prediction by exploring the capabilities of Support Vector Machine (SVM) and k-Nearest Neighbor (k-NN). In this work, the parameters such as penalty C and kernel γ of SVM have been tuned with few optimization techniques such as random search, grid search, genetic algorithm, particle swarm optimization, ant colony optimization, firefly optimization, and BAT optimization algorithm. The final prediction has been obtained using k-NN by searching the neighborhood elements for either profit or loss. The performance of the proposed system has been tested with the Indian rupees with dollar (USD), British Pound (GBP), and Euro (EUR) for daily, weekly, and monthly in advance for prediction of currency exchange rate, volatility, and momentum in the currency market. The model BAT-SVM-k-NN has been found with the best forecasting ability based on performance measures such as mean absolute percentage error, root mean square error, mean squared forecast error, root mean squared forecast error, and mean absolute forecast error in comparison with other optimization techniques mentioned above. [ABSTRACT FROM AUTHOR]

Highlights • This paper use coping cost approach to measure affordability to access safe water. • Monthly coping costs are INR 553 and INR 658 for piped and non-piped households. • For non-piped households, collection costs constitute 22% of the coping costs. • Coping costs are as high as 15% for the low income households. Abstract Sustainable Development Goal 6.1 is "to achieve universal and equitable access to safe and affordable drinking water for all". To measure affordability of accessing clean water, coping cost approach has been adopted, and this paper contributes to the burgeoning empirical literature on measuring affordability. The objective of this paper is to estimate coping costs related to the erratic, unsafe, and inadequate water supply in the metropolitan area of Chennai, India. Based on the data collected from 423 households, we find that households in Chennai city resort to five main types of coping behaviors: collecting, pumping, treating, storing, and purchasing. We employ the multiple regression with robust errors, to estimate the determinants of the coping costs. We obtain the mean coping costs as INR (Indian Rupee) 553, and INR 658 per month for piped and non-piped households in this sample. For non-piped households, collection costs (time costs in traveling and queuing for collecting water) constitute 22% of the coping costs, while collection costs for piped households are less 2% of the coping costs. One interesting finding is the variation of coping costs with household income—these costs are roughly 1% of income for the high income households to as high as 15% for the low income households. The results outline the need of policy intervention to enhance affordability. [ABSTRACT FROM AUTHOR]

Predicting currency movements is perhaps one of the hardest exercises in economics as it has many variables affecting its market movement. This study concerns with some of the usual macroeconomic variables which, in theory, are expected to affect the exchange rate between two countries. Indian Rupee is currently losing its value to the Dollar which could certainly be seen to affect the Indian economy adversely. This paper attempts to investigate the interactions between the foreign exchange and stock market in India as well as determine some of the economic factors which could have influenced the Indian rupee vis-à-vis the US Dollar over the period 1990-2011. This paper studies the effect of exchange rate on three market indices; BSE Sensex index, BSE IT sector index and BSE Oil & Gas sector index for the period January 2006 to March 2012. No significant interactions were found between foreign exchange rate [USD/INR] and stock returns. Economic variables like inflation differential, lending interest rates and current account deficit (as a percentage of GDP) are found to significantly affect the exchange rate [USD/INR]. This study also analyzes how the real GDP of India is currently behaving with respect to the exchange rate. It is found that they share a negative relationship which is highly statistically significant. [ABSTRACT FROM AUTHOR]

THE price of one currency in terms of another currency (exchange rate) is a very important variable for an open economy in the global market, because it affects the overall economic performance and growth of the economy. So, the relationship between exchange rate and the related macro-economic factors causing variability in the value of the former carries a high degree of significance for any open economy. The present paper aims to identify those macro-economic factors that affect the price of Indian currency (Rupee) and their inter-relationship with the latter. Also, the study includes the fluctuations of Indian currency against the Dollar (INR/USD) post globalization and suggests measures to control the devaluation of the Indian rupee. Purpose: To analyze the effect of select macro-economic factors influencing the IndianRupee value against US Dollar post- globalization. Design/Methodology/Approach: The nature of research is Exploratory & Analytical that generates a posteriori hypothesis by analyzing a data-set and looking for potential relations between variables. Findings: Exchange rate is highly dependent on the five select independent variables taken up for this study. Research Implications: A strong relation between the dependent & independent variables suggests that steps taken to compress imports and promote FDI in explored & unexplored sectors can help improve the current rupee value. [ABSTRACT FROM AUTHOR]

This study is an attempt to estimate the dynamics (volatility) of Indian rupee instability against four major world currencies, i.e., US dollar, pound sterling, euro and Japanese yen, using 3,340 daily observations over a period of 13 years from January 3, 2000 to September 30, 2013. This paper uses the Generalized Autoregressive Conditional Heteroskedastic (GARCH) models to estimate volatility (conditional variance) in the daily log rupee value. The models include both symmetric and asymmetric that capture the most common stylized facts about rupee exchange returns such as volatility clustering and leverage effect. It is evident from the findings that asymmetric models are superior to symmetric models in providing a better fit for the exchange rate volatility because of leverage effect. [ABSTRACT FROM AUTHOR]

Abstract This paper briefly discusses the present framework and status of Indian power market and guides through the possible adaptations to accommodate the growing renewable energy (RE) integration into the grid. The participation of RE generators in the wholesale energy market would provide them a platform to optimally manage their generation portfolio which would help them in compensating the high investment cost. The increased competition in the market would eventually bring down the electricity price. The objective of this paper is to identify an ideal framework and optimal bidding mechanism for RE generators (wind energy in particular) to maximize the overall capital gain (social welfare) in the Indian power market. The inputs from various foreign electricity markets having high wind energy penetration have been considered. Recent studies suggest that battery energy storage system (BESS) can play a significant role in handling risks associated with the uncertainties in wind power generation and thus can help in maximizing the revenue for wind farm owners. It can also be instrumental in active/reactive power balancing which will further help in the frequency regulation. The paper probes into the combined wind and battery energy trading, and various bidding strategies in the day-ahead market (DAM), intraday energy market, real-time balancing, and other ancillary markets. Highlights • Reviews the state of renewable energy in major electricity markets worldwide. • Overviews the present structure and status of RE in Indian power market. • Literature survey on optimal trading of wind energy and battery energy storage. • Brings forward the major challenges in large-scale wind energy trading. • Suggests framework for Indian power market to facilitate renewable integration. [ABSTRACT FROM AUTHOR]

This paper examines the relationship between the USD/INR implied volatility and future realized volatility by using non-overlapping monthly volatility data from April 2005 to March 2017. The empirical results suggest that the USD/INR implied volatility is biased, yet a better predictor of future realized volatility of the exchange rate than historical volatility and GARCH forecast. The out-of-sample forecast also shows that implied volatility outperforms both historical volatility and GARCH forecast in predicting future realized volatility. The implied volatility is found to be an efficient predictor vis-à-vis historical volatility as it subsumes all the information content of the historical volatility about future realized volatility. However, the GARCH forecast contains some incremental information about future realized volatility beyond the information contained in the implied volatility, though the predictive power of implied volatility remains higher than the GARCH forecast. [ABSTRACT FROM AUTHOR]

Emphasizing the need for risk mitigation arising out of excess volatility in rupee experienced by India post implementation of the market determined exchange rate regime in 1993, currency futures were introduced in India in 2008, and currency trading has become one of the most important financial operations since then. In this paper, an attempt has been made to measure and compare the market risk prediction ability of historical simulation, Monte-Carlo simulation, Exponentially Weighted Moving Average (EWMA) and linear parametric VaR approaches for Indian currency spot and futures market. Using the data from 2008 to 2013, the VaR associated with the three main currencies in the economy, namely, US dollar, euro and UK pound sterling, is calculated. Conditional and unconditional coverage tests have been applied to backtest the results of various VaR approaches. The results indicate that Monte-Carlo simulation is appropriate in predicting market risk. Further, it is also found that risk seems to be higher in the future market as compared to the underlying markets. [ABSTRACT FROM AUTHOR]

Background and Aim: Two endemic capripox infectious diseases, sheeppox (SP) and goatpox (GP) are common in Asia, Africa, and the Middle East. Sheep and goats, in general, are considered current assets of small and marginal farmers and have significant economic value in terms of meat, wool, and skin/hide production. Sheep and goat populations in India total 148.88 million and 74.26 million, respectively. Capripox caused US$ 2.3 million (Indian Rupee [INR] 105 million) in economic damages in Maharashtra (India) alone, and it took over 6 years for a flock to recover from the outbreak. The projected yearly loss at the national level is US$ 27.47 million (INR 1250 million). As a result, Capripox diseases put small and marginal farmers under much financial strain. The present study estimates the seroprevalence of SP and GP diseases in the Asian and African continents using systematic review and meta-analysis. The results of the study will help researchers and policymakers to understand the spatial and temporal distribution of the disease and its burden. In addition, the results are also helpful to design and implement location-specific prevention and eradication measures against these diseases. Materials and Methods: Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines of Cochran collaborations were used for systematic review and subsequently meta-analysis were used. The literature was collected from various databases. Initial search string resulted in more than nine thousand articles for the period 2000 to 2020 using the different combinations of keywords and Boolean operators (or not) asterisk* and quotation marks. Out of 9398 papers, 80 studies were chosen for complete test reviews and quality bias evaluation using the inclusion and exclusion criteria. Finally, 21 articles were used for the meta-analysis. The statistical study employed fixed effects and random effects models using R. Results: Seroprevalence of SP and GP was calculated using studies with a cumulative sample size of 4352, out of which sheep and goats' samples together contribute 48%, followed by sheep (32%) and goat (21%). The result of the metaregression revealed that detection techniques had a significant impact on the overall effect size at 5% level (Qm=14.12). Subgroup analysis of polymerase chain reaction (PCR) test with samples was further grouped into two categories based on the median, and it revealed that 62% of samples used PCR as a detecting test followed by group-II. Conclusion: From the study, it is concluded that SP and GP diseases are highly prevalent; hence, effective vaccines, proper education to farmers through extension activity, and transboundary disease movement restriction are necessary for the control and eradication of the disease. [ABSTRACT FROM AUTHOR]

For investors and financial analysts to make informed decisions, having precise forecasts of gold prices is crucial. This study examined the effectiveness of various time series models in predicting gold prices in Indian Rupeea variety of models, ranging from linear models like Auto Regressive Integrated Moving Average (ARIMA) and Simple Linear Regression, to more complex nonlinear models such as Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) were utilised. In the study, a statistical technique was used to analyse the data collected over a twenty-year period, from January 2001 to December 2019. RMSE and MAPE were used to evaluate the models' performance. The Simple Linear Regression model achieved an RMSE value of 834.67 and a MAPE value of 2.22%, demonstrating its superior performance compared to the other models. The LSTM and GRU models achieved RMSE values of 1160.5 and 1214.8, respectively, suggesting comparable levels of performance. The MAPE values of the LSTM model and the GRU model differed by 2.96%, with the latter being 2.83%. On the other hand, the ARIMA model had a MAPE value of 22.9% and an RMSE value of 7121.1, which was noticeably lower than the previous model. Moreover, the results showed that both LSTM and GRU have the ability to capture nonlinear correlations in the fluctuations of gold prices. [ABSTRACT FROM AUTHOR]

The paper is concerned with time series modelling of foreign exchange rate of an important emerging economy, viz., India, with due consideration to possible sources of misspecification of the conditional mean like serial correlation, parameter instability, omitted time series variables and nonlinear dependences. Since structural change is pervasive in economic time series relationships, the paper first studies this aspect of the exchange rate series in detail and finds the existence of four structural breaks. Accordingly, the entire sample period is divided into five sub-periods of stable parameters each, and then the appropriate mean specification for each of these sub-periods is determined by incorporating functions of recursive residuals. Thereafter, the GARCH and EGARCH models are considered to capture the volatility contained in the data. The estimated models thus obtained suggest that return on Indian exchange rate series is marked by instabilities and that the appropriate volatility model is EGARCH. Further, out-of-sample forecasting performance of the model has been studied by standard forecasting criteria, and then compared with that of an AR model only to find that the findings are quite favorable for the former. [ABSTRACT FROM AUTHOR]

The trading of natural rubber derivatives in the Indian commodity exchanges was banned several times in the past. Hence, in India, the derivatives on natural rubber are not traded actively and regularly. We have examined the possibility of a forecast model and a cross hedge tool for the natural rubber price by using crude oil futures in India. Results of the Johansen cointegration test proved that there is no cointegration equation in the model; hence, there is no scope to develop long-run models or error correction models. We have developed a vector autoregressive [VAR(2)] model to forecast the rubber price, and we examined the possibility of a cross hedge for natural rubber further by using the Pearson correlation coefficient and Granger causality test. We have extended our research to a structural VAR analysis to examine the effect of crude futures and exchange rate shocks on the natural rubber price. Our results showed that there is a short-term relationship between the crude oil futures price, the exchange rates of the US dollar to the Indian rupee, the Malaysian ringgit to the Indian rupee and the Thai baht to the Indian rupee; and the natural rubber price in India. The effort of policymakers to cause the Indian rupee to appreciate against the Thai baht and Malaysian ringgit may increase the natural rubber price in India. Natural rubber traders, growers and consumers can use crude futures to hedge the price risk. The Indian Rubber Board can suggest the VAR(2) model to predict the short-run price for natural rubber. [ABSTRACT FROM AUTHOR]