Indian Exchange Research Articles

PRICING OF EQUITY INVESTMENT - AN EMPIRICAL ANALYSIS OF INDIAN CAPITAL MARKET

The investment is stock market is an art as well as science. The objective of stock market investment is to achieve superior returns comparing other investment options. The investment cost is one of the variable contributing towards the performance of the stock. The justified price of the stock is always a matter of discussion but no specific formula or theory exist to recognize the correct price. This paper is an attempt to decompose the market price of the stock listed on Indian exchanges. Using the data for 10 years, explanatory variables are identified which explain market price of the stock. The model identify the significant factors explaining 62 per cent changes in the market price. The findings of the study are useful to all academicians, researchers and market participants to understand the complex dynamics of market price of the stock and its explanatory factors.

Evaluating tracking errors and its determinants among indian exchange traded funds

Evaluating tracking errors and its determinants among indian exchange traded funds

Is Bitcoin Resilient for Indian Investors? The E-GARCH Analysis

This paper explores the financial asset capabilities and hedge alternative properties of Bitcoin by investigating several aspects of its volatility in relation to Nifty50 and Indian exchange rates (USD/INR & EUR/INR). This study delves into the volatility dynamics of the returns of Bitcoin. An asymmetric GARCH model (E-GARCH) is used to examine whether Bitcoin may play crucial role in risk management and ideal for risk-averse investors in anticipation of leverage effect. This paper also examines Bitcoin as an investment and hedge alternative to Nifty50 and exchange rates. The findings suggest that Bitcoin does not attributes the properties of safe hedge and an investment alternative by Indian investors

Intraday price discovery and volatility transmission between the dual-listed stock index futures and spot markets – new evidence from India

PurposeThis study empirically explores the intraday price discovery mechanism and volatility transmission effect between the dual-listed Indian Nifty index futures traded simultaneously on the onshore Indian exchange, National Stock Exchange (NSE) and offshore Singapore Exchange (SGX) and its spot market by using high-frequency data.Design/methodology/approachThis study applies the vector error correction model to analyze the lead-lag relationship in price discovery among three markets. The contributions of individual markets in assimilating new information into prices are measured using various measures, Hasbrouck's (1995) information share, Lien and Shrestha's (2009) modified information share and Gonzalo and Granger's (1995) component share. Additionally, the Granger causality test is conducted to determine the causal relationship. Lastly, the BEKK-GARCH specification is employed to analyze the volatility transmission.FindingsThis study provides robust evidence that Nifty futures lead the spot in price discovery. The offshore SGX Nifty futures consistently ranked first in contributing to price discovery, followed by onshore NSE Nifty futures and finally by the spot. Empirical results also show unidirectional causality and volatility transmission from Nifty futures to spot, as well as bidirectional causal relationship and volatility spillovers between NSE and SGX Nifty futures. These novel findings provide fresh insights into the informational efficiency of the dual-listed Indian Nifty futures, which is distinct from previous literature.Practical implicationsThese findings can potentially help market participants, policymakers, stock exchanges and regulators.Originality/valueUnlike previous studies in this area, this is the first study that empirically examines the intraday price discovery mechanism and volatility spillover between the dual-listed futures markets and its spot market using 5-min overlapping price data and trivariate econometric models.

A Model for Calculating the Effectiveness of Writing and Hedging SBI Derivatives

Options in the stock market are a form of risk management that can help protect investors from various potential liabilities. Increased demand for derivatives is reflected in higher trading volumes every day. Over time, it has been easier for regular investors to get their hands on derivatives. The major Indian exchanges trade a wide range of financial goods, including stock derivatives. This article explains how to trade F&O on the National Stock Exchange (NSE) in India. To write options, the NSE typically employs call-and-put options. It may be able to design ways to achieve this goal by studying the State Bank of India (SBI) options chain for the first quarter of fiscal years 22 and 23. Based on the current stock price, the suggested computational approach writes call (CE) and put (PE) options for the upcoming month's settlement date. CE and PE were written at prices twenty rupees higher and lower than the stock options strike price, respectively. Furthermore, the pricing for both products has been reduced to zero rupees. According to our research, selling options to firms with minimal volatility is a good idea.

Empirical analysis of machine learning techniques for prediction of indian exchange rate

Throughout the past few decades, there has been a dramatic surge in the currency market. The changes play an important role in balancing the market’s characteristics. As a result, accurate change price forecasting is essential to improve the success rate of many businesses and fund managers. Despite the fact that the market is renowned for its erratic behavior and volatility, there are organizations like agencies, banks, and others. In order to estimate the extraneous interchange rate of the dollar against the rupee with a high degree of accuracy, we used three distinct types of methodologies in this article. This research uses three different types of neural network models: ANNs (Artificial Neural Networks), LSTMs (Long Short-Term Memory Networks), and GRUs (Gated Recurring Units). The results depict that GRU’s model is outperforming the other two models.

An Enquiry into the Persistence of Turn-of-the-Month Effect on Stock Markets in India: Insights and Perspectives on a Seasonal Anomaly

Asset pricing in capital markets is a strikingly vibrant area of academic research and is considered as an indicator to evaluate the efficiency of stock markets. Though the explanation for the seasonal behavior of capital markets was attempted by various market models, several anomalies were observed historically. Calendar anomalies that belong to the specific class of seasonal anomalies provided abnormal returns in the global stock markets at regular intervals within and across various calendar years. This article documents the study on one such anomaly—namely, the turn-of-the-month effect in the context of Indian stock indices. In this pursuit, exhaustive research has been carried out considering all the broad-market and sectoral indices of two major stock exchanges, namely, National Stock Exchange and the Bombay Stock Exchange. The study used the ARIMAX methodology with dummy exogenous variables (to represent the turn-of-the-month days) and presented comprehensive findings and learnings. Besides, this article attempts to analyze the changes in the strength and significance of the anomaly in progression with various stock market reforms in both the broad-market and sectoral indices to provide new insights into the efficiency of Indian stock market exchanges.

Exchange rates in India: current account monetarism in a nonlinear context

Abstract The Indian exchange rate system has evolved from a pegged system to the current managed float. The study examines the presence of a long-run equilibrium in the monthly Indian exchange rate (Rs/USD) using a current account monetary model (or flexible price monetary model) while accounting for different nonlinearities over the period January 1993 to January 2014 (pre-inflation targeting period). The nonlinear adjustment to disequilibria is modelled using a nonlinear error correction model (NLECM). The nonlinear current account monetarism (CAM) model includes nonlinear transformations of long-run dynamics in the ECM to account for different nonlinearities: multiple equilibria (cubic polynomial function), nonlinear mean reversion (rational polynomial function), and smooth and gradual regime switches (exponential smooth transition autoregressive (ESTAR) function). The NLECM-ESTAR model outperforms other alternatives based on model and forecast performance measures, implying the existence of nonlinear mean reversion and smooth transition across different periods of overvaluation and undervaluation of the exchange rate. This implies the presence of asymmetric adjustment to the movements from the long-run equilibrium, but the nature of such transitions is smooth and not abrupt. The paper also establishes the uniqueness of the long-run equilibrium. A comparison to the sticky price monetary model could not be made due to stationary exchange rate disequilibrium.

Foreign Exchange System in Nepal: A Theoretical Perspective

International economic relation and trade are occurred in different currency system. The currency of one country may not be tendered in another country. So, the natural person or organization requires buying the currency of target country. In fact it is the process of converting one currency into another currency, which makes globalization and international trade possible. Buying and selling of currency is made in spot market, forward market, futures market, swap market, and option market. Additionally, change in real price, structural change, speculation, inflation, interest rate, public debt, and status of terms of trade make effect in equilibrium position of exchange rate. Yet, demand and supply of the currency determine appreciation and depreciation of currency. Policy exchange rate is accepted as fixed rate, floating rate, crawling band, crawling peg, conventional fixed peg arrangement, pegged exchange rate within horizontal band peg, currency board, dollarization and no separate legal tender. Earlier mint par theory was universally accepted. However, in contemporary time, balance of payment theory and purchasing power parity theory are accepted as theories of foreign exchange. Market transaction is made through hedging, speculation, and arbitrage etc. Exchange control is made through unilateral method and bilateral method. Unilateral method includes bank rate policy, import and export policy, exchange equalization fund, exchange pegging, multiple exchange rates, rationing of foreign exchange, and blocked account whereas bilateral method includes clearing agreement, payment agreement, installment agreement, differed payment agreement, and compensation agreement etc as per necessity. Nepal has accepted fixed peg exchange rate regime with Indian currency and flexible exchange rate regime with rest of the currencies.

The Dynamics of India’s Major Exchange Rates

In this article, we analyze the dynamic properties of India’s major exchange rates, both in the short and the long runs. The particular issue of our concern is to find whether present values of the exchange rates depend (a) on their own past values and (b) on the past values of India’s other exchange rates. Since the series exhibit long memory, the autoregressive fractionally integrated moving average (ARFIMA) model is used for the first purpose and the cross-correlation, entropy transfer and vector auto regression (VAR) models are used for the later purpose. Combining the results of these models, we conclude that, in general, the Indian exchange rates are persistent and depend only on their immediate past values. In particular, past values, older than two periods (days in this case), do not appear to be consistently relevant in modelling the current value. These observations have clear implications for exchange rate trades using technical analysis (TA) and for exporters and importers.

BREXIT REFERENDUM: IMPACT ON EXCHANGE RATE (POUND/ INR)

Present study is an attempt to empirically analyse the exchange rate volatility of Pound/INR with respect to Brexit referendum and its policy implications on Indian economy. The exchange rate data of Pound/INR collected over a span of six years, split into two halves: pre-Brexit-period (1/7/2013 to 23/06/2016) and post-Brexit-period (24/06/2016 to 31/06/2019). The data series were tested empirically using GARCH (1,1) model which represented that beta coefficient value is greater in post-Brexit period indicating that volatility in that period is persistent and that takes long time to vanish and the alpha coefficient is higher in case of pre-Brexit period that means the volatility reaction to market movements are quite intense than the post-Brexit period. Vote in favour of Brexit on 23rd June 2016 started the firing from gun on pounds downward trend which was further followed by initial sharp drop and various slumps and persistent decline. This left the pound sterling to Indian rupee exchange rate 8% lower than pre-referendum levels.

Stock Market Sensitivity to Macroeconomic Factors: Evidence from China and India

The purpose of this study is to analyse the impact of Chinese macroeconomic factors on Shanghai Stock Exchange (SSE) Composite returns and Indian macroeconomic factors on Nifty returns based on monthly data from January 1998 to December 2018. This study adopts quantile regression approach. The QR allows examining the conditional dependence of specific quantile of SSE and Nifty returns with respect to the conditioning factors. The authors present results for two sample periods that are pre-recession and recession period from 1998 to 2008 and the post-recession period from 2009 to 2018. This paper also documents quite interesting and useful results for the entire period. From the results, It is concluded that Chinese consumer price index significantly affects the SSE returns only for lower quantiles. However, Indian consumer price index has a significant and positive impact on the Nifty returns for the upper quantiles. Further, Chinese interest rates and Indian interest rates have no impact on the SSE and Nifty returns respectively across the different quantiles. Moreover, the Chinese exchange rate influence the SSE returns at the extreme dataset. However, the Indian exchange rate is insignificant. It is important to note that the dependence structure of China shows a negligible change during the post-recession period. Conversely, the dependence structure has changed significantly for India post-recession. The implication of this paper would guide stock market participants.

Impact of Sectoral Indices’ Fluctuation on SENSEX.

In the last few years performances of Indian exchanges are satisfactory. Last 5-6 years witnessed a massive growth in SENSEX and NIFTY. But a growth in stock indices may not provide profit to the investors unless and until they read it much before. Nobody knows when the Black swan kind of situation comes. In this backdrop, an attempt is made to analyze the correlation among all the sectors of BSE and performances of all these sectors, which may help the investors and portfolio managers to construct the portfolio by selecting the right kind of sectors. This analysis is going to exhibit risk (standard deviation and Beta) associated with all sectors and the correlation among them. Objective of the study: The main objective of the study is to find the performance of the indices and correlation among them, so that it will be an aid to the investors for selecting appropriate sectors to be involved in a particular portfolio. Research Methodology: The data collected for the analysis is from secondary sources. Kumar D. B., Sophia S,and Jucunda E. M. Suggested that there is a significant relationship of stock market with lok sabha election and from the last five years after formation of new Govt. in India, the indices like NIFTY and SENSEX are in an upward trend. So data collected for last five years. Sharpe and and Treynor ratio are used to calculate the performance of all the sectors. To get the correlation among the indices Pearson’s correlation is used. Findings: Most of the existing researches explained the relationship among different indices by selecting some of the indices. So this study got the fuel to involve the most active 7 indices to correlate with the oldest index of Asia. Pearson’s Correlation is one of the most trusted tool used by current researchers. Limitations of the Study: The data used in this study is of five years and to get the correlation Pearson correlation is used

A Research on The Stock Market Volatility of BSE and NSE in Indian Economy

In this paper, the Indian economy is energetically seemed, by all accounts, to be global markets post movement in the mid 90s. India is having economic movement over the most recent couple of years and as essentials be there gigantic hold are spouting into Indian market from over the world. By a long shot a gigantic piece of these outside assets are enormous giganticness players and their improvement in the market results in colossal frailty in stock markets. Indian economy is normally considered by inside use, yet after movement the shar Indian exchange as an essential piece of global exchange is expanding at a rich pace. India's economy has ended up being over USD 1 trillion and sorted out as the eleventh most crucial economy on earth. Unending Indian affiliations are getting related with passing on their things to global markets, raising assets by posting on remote stock exchange ( London Stock exchange, NYSE and NASDAQ and so forward). In that limit, share regard updates of these affiliations will no vulnerability on the planet be influenced by the improvement in world economy. Starting now and into the not very hard to achieve this examination was endeavored to explore the Stock Market slightness of BSE and NSE in Indian economy as shown by the examination of Economic survey for the time of (2015 - 2018).

The Lead–Lag Relationship Between Futures and Spot Price—A Case of the Oil and Oilseed Contracts Traded on Indian Exchange

In India, government intervention in the agricultural derivatives market has not allowed the market to grow and become an important tool of risk management. It has always been argued that the farmers and consumers of crops in India primarily operate in the spot market, and their expectations about the future market conditions are likely to be reflected in the spot price movements. If the farmers and consumers of the crops do not participate in the derivatives market, it is not expected to work as an efficient tool of information dissemination on the underlying commodity. We analysed the role played by the futures market in the price discovery process in this article. To test whether the futures or spot market in India plays a dominant role in information dissemination, we have done a regression analysis considering the lagged futures and spot price volatility as explanatory variables. We consider the major oil and oilseed contracts traded on National Commodity and Derivatives Exchange. As the uses of many of the oilseeds are related, we have tried to analyse the interlinkages among the market for different commodities. Our results clearly show that information on relevant futures market volatilities help significantly to assess the volatility in the spot markets. This linkage can be leveraged to manage the spot market risks better. JEL: G10, G13, G14

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.

Predictability of Indian Exchange Rates

In this paper we determine the extent of predictability of India’s major spot exchange rates by using the Lyapunov exponent. We first determine whether the series is fractal (self-similar) in nature. If it is indeed so, then next we determine whether the underlying dynamics of the system is deterministic or stochastic. If the dynamics is found to be deterministic then we calculate the Largest Lyapunov Exponent (LLE) to determine whether the series has deterministic chaos. Finally we use the inverse of the Lyapunov exponent to estimate the time period for which out of sample predictions for the series make sense. We find that India’s major spot exchange rates are: a) fractal in nature, b) chaotic with a high embedding dimension and c) The inverse of the LLE gives us a time frame in which any meaningful predictions can be made. These results are interpreted in two ways. First, exploiting the efficient market interpretation of randomness we conclude that since available information is fairly rapidly internalized, chaotic behaviour is mainly due to the unforeseen nature of the pool of new information affecting the systems at such short intervals of time. Second, anti-cyclical central bank interventions are conjectured to be the source of determinism in otherwise almost random movements.

The Relationship between Macroeconomic Factors and Stock Market Indices Performances in Indian Stock Market

This investigation endeavors in observationally testing the connection between macroeconomic variables and the exhibitions of two noteworthy Indian security advertise lists of BSE-sensex and NSE-clever. The yearly information of a few macroeconomic elements of FIIs net venture, trade rates, oil value, financing costs, swelling rates and gold rates from 1995-96 to 2014-15 are thought about and it attempts to uncover the most impact of these elements on the 'Stock files exhibitions' of the Indian securities exchange. In compatibility of this, the connection investigation and various relapse examination was utilized to contemplate the connection between the two chose security advertise files exhibitions and the six chose macroeconomic elements from the Indian economy. The significant finding is that macroeconomic elements impact securities exchange lists exhibitions in India. It is suggested that the usage of appropriate monetary approaches will be useful to money markets files and it will result in required development in the Indian capital market.

Modeling volatility of Indian exchange rates under the impact of regime shifts: A study with economic significance analysis

In this paper, we assess the impact of regime shifts on the long memory properties of the Indian exchange rates. We make use of Sanso, Arago and Carrion (2004) Iterated Cumulative Sum of Squares (hereafter referred as AIT-ICSS) algorithm to detect the points of structural breaks in volatility series. Our findings indicate that incorporating the impact of sudden changes in volatility in the model indeed reduces the magnitude of long memory parameter. In the case of INR/JPY, we observe a shift in characteristics from long memory to mean reversion when the impact of regime shifts is included in the volatility model. Our findings also highlight that incorporating the impact of regime shifts in the model also improves the volatility forecast accuracy. Moreover, we implement a trading strategy based on risk-averse investor and find that the volatility forecasts based on the model which incorporate the impact of structural breaks provide substantial gains in return in comparison to volatility models with no structural breaks. These findings have important policy implications for financial market participants, investors and policy makers.

Domestic and International Information Linkages between Gold Spot and Futures Markets: An Empirical Study for India

This article examines information linkages between gold spot market in India and gold futures at India’s Multi Commodity Exchange (MCX) and five international platforms [i.e., Commodity Exchange (COMEX), Dubai Gold and Commodity Exchange (DGCX), Tokyo Commodity Exchange (TOCOM), Hong Kong Exchange (HKE) and Singapore Mercantile Exchange (SMX)] from August 2008 to March 2015. Cointegration procedure and vector error correction model (VECM), supported by Granger causality, are employed to study price discovery process, and bivariate EGARCH-BEKK model is used to examine volatility spillover process. At domestic level, spot market dominates the futures in information transmission process. Internationally, DGCX leads all other exchanges in price discovery process, while COMEX leads in volatility spillovers. In price discovery, MCX leads only TOCOM till August 2013, while price discovery is absent thereafter. In volatility spillovers, MCX dominates TOCOM and HKE till this period and only HKE afterwards. Thus, information linkages between MCX and international exchanges appear to have been impacted severely since August 2013. The study highlights the need to re-establish price and volatility linkages between Indian and international exchanges, and also provides significant suggestions for policymakers. The study is relevant for investors, researchers and the academia. It contributes to market efficiency and information transmission literature for commodity markets.