Hedging With Futures

Hedge ratio stability is especially important because hedgers are likely to use the estimate of historical hedge ratios to hedge future positions of their portfolios. One main purpose of the present study is to examine hedge ratio stability during the Asian financial crisis and post‐crisis, periods characterized by high price volatility, using the Nikkei 225, Hang Seng, and KOSPI 200 index futures contracts. Empirical results from the Hang Seng and the KOSPI 200 futures markets indicate that during the two periods of high price volatility, hedge ratios appeared to be unstable. Additionally, both in‐sample and out‐of‐sample evidences indicate that, for hedging effectiveness, the time‐varying hedge ratios clearly outperform the constant hedge ratios for the Hang Seng and the KOSPI 200 index futures, consistent with the findings of hedge ratio instability. The comparison results of different time‐varying hedge ratios support the conclusion that the bivariate error correction generalized autoregressive conditional heteroskedastic (1,1) model enhances hedging effectiveness compared to other time‐varying hedge ratios. Finally, this study examines the impact of hedge duration on hedging effectiveness and hedge ratios. The empirical results indicate that hedging effectiveness improves with increasing hedge duration.

This study attempts to study and suggest an optimal hedge ratio to Indian investors and traders by examining the three main indices of National Stock Exchange of India (NSE), namely, NIFTY, Bank NIFTY, and IT NIFTY, over the sample period from January 2011 to December 2015. The present study estimated the hedge ratio through six econometric models, namely, OLS, GARCH, EGARCH, TARCH, VAR, and VECM, in the minimum variance hedge ratio framework as suggested by Ederington (1979). The findings of the present study confirm the theoretical properties of Indian cash and futures market and suggest that the optimal hedge ratio estimated through EGARCH model was lowest for the NIFTY and Bank NIFTY, and that for IT NIFTY, the OLS model shows the lowest optimal hedge ratio as compared to that estimated through other models.

A method of calculating the past states of the earth‐moon system is developed. The method is based on the existence of three distinct time scales for dynamical change. The short time scale is determined by the revolution periods of the sun and moon about the earth or, equivalently, by the year and current month. The intermediate time scale is set by the precessional motions of the lunar orbit plane and the earth's equator plane. The rate at which tidal friction alters the state of the earth‐moon system defines the long time scale. The equations of motion governing the earth‐moon system are successively averaged over the short and then the intermediate time scales. These averaged equations are then integrated back a short interval on the long time scale. The equations of motion appropriate to this new state of the earth‐moon system are then re‐averaged on the short and intermediate time scales, and once again the averaged eqations are stepped back on the tidal time scale. The first step in this procedure (i.e. averaging on the short time scale) is performed analytically, whereas the calculations on the intermediate and long time scales require the use of a large computer.At present, the inclination of the lunar orbit plane to the ecliptic remains nearly constant during the precessional motion. On the other hand, if the moon's semimajor axis were ever less than 10R⨁, the inclination of the lunar orbit plane would have maintained a fixed value with respect to the earth's equator plane. The current investigation shows that this inclination could never have been less than 10° and, therefore, that the moon could never have moved on an equatorial orbit. This result contradicts theories that postulate fission of the earth to form the moon and also those which propose that the moon formed by accretion within 10R⨁

The purpose of this study is to determine the extent to which canola (Brassica napus L. var. napus) is distinct from soybeans [Glycine max (L.) Merr.] from a marketing perspective. If the supply and demand fundamentals of canola are closely related to those affecting the soybean complex then, from a marketing standpoint, the two crops are substitutes because canola producers and merchandisers can employ marketing strategies similar to those for soybeans. The degree to which canola and soybeans are similarly affected by market fundamentals is measured here by conventional hedging effectiveness analyses. Relationships between canola prices and soybean, soybean oil, and soybean meal futures prices are estimated to determine whether soybean futures markets can be effectively used to crosshedge canola price risk [...]

The major objective of the study is to examine the performance of optimal hedge ratio and hedging effectiveness in stock futures market in National Stock Exchange, India by estimating the following econometric models like Ordinary Least Square (OLS), Vector Error Correction Model (VECM) and time varying Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) model by evaluating in sample observation and out of sample observations for the period spanning from 1st January 2011 till 31st March 2018 by accommodating sixteen stock futures retrieved through www.nseindia.com by considering banking sector of Indian economy. The findings of the study indicate both the in sample and out of sample hedging performances suggest the various strategies obtained through the time varying optimal hedge ratio, which minimizes the conditional variance performs better than the employed alterative models for most of the underlying stock futures contracts in select banking sectors in India. Moreover, the study also envisage about the model selection criteria is most important for appropriate hedge ratio through risk averse investors. Finally, the research work is also in line with the previous attempts Myers (1991), Baillie and Myers (1991) and Park and Switzer (1995a, 1995b) made in the US markets

Hedging effectiveness is the proportion of price risk removed through hedging. Empirical hedging studies typically estimate a set of risk minimizing hedge ratios, estimate the hedging effectiveness statistic, apply the estimated hedge ratios to a second group of data, and examine the robustness of the hedging strategy by comparing the hedging effectiveness for this period to the period. This study focuses on the statistical properties of the in-sample and out-of-sample hedging effectiveness estimators. Through mathematical and simulation analysis we determine the following: (a) the R2 for the hedge ratio regression will generally overstate the amount of price risk reduction that can be achieved by hedging, (b) the properly computed hedging effectiveness in the hedge ratio regression will also generally overstate the true amount of risk reduction that can be achieved, (c) hedging effectiveness estimated in the out-of-sample period will generally understate the true amount of risk reduction that can be achieved, (d) for equal numbers of observations, the overstatement in (b) is less that the understatement in (c), (e) both errors decline as more observations are used, and (f) the most accurate approach is to use all of the available data to estimate the hedge ratio and effectiveness and to not hold any data back for hedge strategy validation. If structural change in the hedge ratio model is suspected, tests for parameter equality have a better statistical foundation that do tests of hedging effectiveness equality.

The study aims to empirically examine the transmission of volatility from global stock markets to Indian stock market. The study is based on time series data comprising of daily closing stock market indices from National Stock Exchange (NSE), India and major foreign stock exchange of the three countries one each from America, Europe and Asia making the highest portfolio investment in Indian stock market. The study period covers 11 years from 1st January, 2005 to 31st December, 2015 comprising a total of 2731 observations. The Indian stock index used is CNX Nifty 50 and the foreign indices are S & P 500 from USA, FTSE 100 from UK, and Nikkei 225 from Japan. The results reveal that the Indian stock market return is co-integrated with market returns of US, UK and Japanese stock markets. Therefore, the return and hence volatility of Indian stock market is associated with global markets which depicts that it is getting integrated with global financial markets. The results provide empirical evidence for volatility transmission or volatility spillover in the Indian stock market from global markets. There exists inbound volatility transmission from US market to Indian stock market. The Indian and UK stock market have bi-directional volatility transmission. However, there exists presence of only outbound volatility transmission from Indian stock market to Japanese stock market. The volatility transmission from global markets to India is rapid with the spillover effect existing for up to three days only.Janapriya Journal of Interdisciplinary Studies, Vol. 5 (December 2016), page: 83-101

This paper is aimed at exploring the improvement of hedging effect based on the theory of portfolio hedging, with multiple groups of CSI300 stock index futures and spot sample data as the analysis object. The minimum variance method is employed to estimate the optimal hedging ratio under the OLS and GARCH hedging models and calculate the average of the hedge ratios. By comparing the hedging effects of the constructed portfolio outside of samples based on different hedging ratios, the empirical analysis displays that the hedging effect of the average hedge ratio was superior to the hedging effect of the estimated hedge ratio of most individual historical samples. Therefore, the methodology supposed is deeply improved by considering the average value of the hedging ratio in order to optimize the optimal hedging ratio.

Nifty Bank Index has started trading in futures and options (F&O) segment from 13^th June 2005 in National Stock Exchange. The purpose of the study is to enhance the literature by examining expiration effect on the price volatility and price reversal of Underlying Index in India. Historical data used for the current study primarily comprise of daily close prices of Nifty Bank which is the only equity sectoral index in India which is traded in derivatives market and its Future contract value is derived from the underlying CNX Bank Index during the period 1^st January 2010 till 31^st March 2020. To check stationarity of the data, Augmented Dicky Fuller test was used. The study employed ARMA- EGARCH model for analysing the data. The empirical results revealed that there is no effect on the mean returns of underlying Index and EGARCH (1,1) model furthermore shows there is existence of leverage effect in the Bank Index i.e., negative shocks causes more fluctuations in the Index than positive news of similar magnitude. The outcome of the study specifies that there is no effect on volatility on the underlying sectoral index due to expiration days and also observed no price reversal effect once the expiration days are over.

Background: The purpose of this study is to explore the trends and causes of established and emerging nations' stock market integration with India. The National Stock Exchange (NSE) indices act as a counterweight to international market indices. This study investigates the sustained interest of foreign investors in the Indian stock market in the wake of capital market reforms, as well as whether it moves in tandem with other markets in Asia and the United States. Methods: Our study examined the possibility of cross-country cointegration between the largest economies and indices around the world using multiple financial econometric models, such as Augmented Dickey-Fuller, Unit Root, Correlation, and Johansen Cointegration. Results: The findings of this study significantly support the notion that Indian and international financial markets are highly integrated. Vector error correction model indicates that the Indian market (NSE) is highly cointegrated with the US market (National Association of Securities Dealers Automated Quotations) and increased volatility signifies global contagion. Conclusion: A cursory examination of the data reveals distinct investment and portfolio diversification options for global investors. This could assist regulators in formulating more effective rules regarding price discovery processes.

Background: The purpose of this study is to explore the trends and causes of established and emerging nations’ stock market integration with India. The National Stock Exchange (NSE) indices act as a counterweight to international market indices. This study investigates the sustained interest of foreign investors in the Indian stock market in the wake of capital market reforms, as well as whether it moves in tandem with other markets in Asia and the United States. Methods: Our study examined the possibility of cross-country cointegration between the largest economies and indices around the world using multiple financial econometric models, such as Augmented Dickey-Fuller, Unit Root, Correlation, and Johansen Cointegration. Results: The findings of this study significantly support the notion that Indian and international financial markets are highly integrated. Vector error correction model indicates that the Indian market (NSE) is highly cointegrated with the US market (National Association of Securities Dealers Automated Quotations) and increased volatility signifies global contagion. Conclusion: A cursory examination of the data reveals distinct investment and portfolio diversification options for global investors. This could assist regulators in formulating more effective rules regarding price discovery processes.

Background: The purpose of this study is to explore the trends and causes of established and emerging nations' stock market integration with India. The National Stock Exchange (NSE) indices act as a counterweight to international market indices. This study investigates the sustained interest of foreign investors in the Indian stock market in the wake of capital market reforms, as well as whether it moves in tandem with other markets in Asia and the United States. Methods: Our study examined the possibility of cross-country cointegration between the largest economies and indices around the world using multiple financial econometric models, such as Augmented Dickey-Fuller, Unit Root, Correlation, and Johansen Cointegration. Results: The findings of this study significantly support the notion that Indian and international financial markets are highly integrated. Vector error correction model indicates that the Indian market (NSE) is highly cointegrated with the US market (National Association of Securities Dealers Automated Quotations) and increased volatility signifies global contagion. Conclusion: A cursory examination of the data reveals distinct investment and portfolio diversification options for global investors. This could assist regulators in formulating more effective rules regarding price discovery processes.

Background: The purpose of this study is to explore the trends and causes of established and emerging nations' stock market integration with India. The National Stock Exchange (NSE) indices act as a counterweight to international market indices. This study investigates the sustained interest of foreign investors in the Indian stock market in the wake of capital market reforms, as well as whether it moves in tandem with other markets in Asia and the United States. Methods: Our study examined the possibility of cross-country cointegration between the largest economies and indices around the world using multiple financial econometric models, such as Augmented Dickey-Fuller, Unit Root, Correlation, and Johansen Cointegration. Results: The findings of this study significantly support the notion that Indian and international financial markets are highly integrated. Vector error correction model indicates that the Indian market (NSE) is highly cointegrated with the US market (National Association of Securities Dealers Automated Quotations) and increased volatility signifies global contagion. Conclusion: A cursory examination of the data reveals distinct investment and portfolio diversification options for global investors. This could assist regulators in formulating more effective rules regarding price discovery processes.

PurposeThe purpose of this paper is to examine the existence of the day-of-the-week effect in the Indian stock market.Design/methodology/approachGeneralized Autoregressive Conditional Heteroskedasticity (GARCH) (1, 1), Exponential GARCH (EGARCH) (1, 1) and Threshold GARCH (TGARCH) (1, 1) models are employed to examine the day-of-the-week effect in the Indian stock market for the period of 28 years from 3rd July, 1990 to 31st March, 2022.FindingsThe empirical results derived from the GARCH models indicate the existence of day-of-the-week effects on stock returns and volatility of the Indian stock market. The study reveals that all the days of the week are positive and significant in National Stock Exchange (NSE)-Nifty market returns. The findings confirm the persistence of ARCH and GARCH effects in the daily return series. Moreover, the asymmetric GARCH models show that the daily stock returns exhibit significant asymmetric (leverage) effects.Practical implicationsThe results of this study established that the Indian stock market is not efficient and there exists an opportunity to the traders for predicting the future prices and earning abnormal profits in the Indian stock market. The findings of the study are important for traders, investors and portfolio managers to earn abnormal returns by cross-border diversification.Originality/valueFirst, to the best of the authors' knowledge, this paper is the first to study the day-of-the-week effect in Indian stock market considering the most recent and longer time period (1990–2022). Second, unlike previous research, this study used GARCH models (GARCH, EGARCH and TGARCH) to capture the volatility clustering in the data.

Chinese Abstract: 本文应用一种新的套保方法,将套期保值由统计竞技恢复回衍生品定价的金融问题,简化了套保比率的估计,并避免了拼接期货合约等问题。针对黄金、股指、外汇和原油等四大类期货市场的实证研究,我们发现:如果将期货的定价与风险管理割裂开来,忽视期货合约的衍生品本性,各种复杂的套保估计方法,套保效率都不如简单套保;如果将定价理论融入套保实践,通过预测持有成本计算套保比率,套保效果将比简单套保更出色。此外,套保合约的选择方面,简单套保倾向于选择交割日较近的合约,而考虑定价约束的套保新方法,合约的选择不受到期日的影响。因此,套保比率的研究重心应该从期货与现货价格的统计关系转到持有成本的预测上来。 English Abstract: We employ a new method for hedge in futures market. The new method brings futures’ hedge from statistical games back to its original financial nature of derivatives pricing. Thus the estimation of hedge ratio is simplified, and the continuous futures contract is not needed. We carry on an empirical study on gold futures, index futures, British pound GBP futures, and crude oil futures. We find that: If we estimate the hedge ratio using traditional methods, where futures are not treated as financial derivatives, naive hedge outperforms complex models. If the futures pricing theory is taking account when hedging, computing hedge ratio by way of forecasting cost of carry, the hedge effectiveness is higher than naive hedge. Furthermore, naive hedge prefers contracts whose delivery dates are nearby. However, the hedge effectiveness of the new method is not affected by the delivery dates. Thus, the research focus on hedging ratios should shift from the statistical relationship between futures and spot prices to the forecast of cost of carry.