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Return Volatility Movements in Spot and Futures Markets

Return Volatility Movements in Spot and Futures Markets
Author: Jeng-Hong Chen
Publisher:
Total Pages: 14
Release: 2014
Genre:
ISBN:
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After the Debt Ceiling Bill was passed on August 2, 2011, the S&P 500 index returns volatility increased significantly until the end of 2011. This research investigates the return volatility movements in S&P 500 spot index and index futures markets, the lead/lag relationship between two markets, and the effect of volatility on the trading costs using year 2011 intraday data. The analyses of intraday data show the following results during the higher volatility period (8/3/2011-12/30/2011): First, the difference of return variances between index futures and spot index is even greater than that during the lower volatility period. Second, the index futures market leads the spot index market and the interaction between both markets becomes stronger. Third, both index futures and spot index exhibit clearer U-shape intraday pattern of return volatilities. Finally, the trading costs, measured by the bid-ask spreads, are significantly larger.

Trading Mechanisms, Speculative Behavior of Investors, and the Volatility of Prices

Trading Mechanisms, Speculative Behavior of Investors, and the Volatility of Prices
Author: Hun Y. Park
Publisher:
Total Pages: 56
Release: 1989
Genre: Prices
ISBN:
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This paper compares the volatility of spot prices (dealership market) with that of futures prices (auction market) to test the implications of different trading mechanisms for the volatility of prices. First, a natural estimator of the volatility is sued. Using the intraday data of the major Market Index and its futures prices, we show that the volatility of opening prices is higher than that of closing prices not only in the spot market but in the futures market, and that the intraday volatility patterns are U-shaped in both markets. Of particular interest is that futures prices do not appear to be as volatile as spot prices when the natural estimator of volatility is used, to the contrary of the conventional wisdom. We argue that the different volatility patterns during the day are not necessarily due to the different trading mechanisms, auction market versus dealership market. Instead, after developing a simple theoretical model of speculative prices, we show that at least part of the different volatility patterns during the day may be attributable to speculative behavior of investors based on heterogeneous information. In addition, we further investigate the volatilities of spot and futures prices using a temporal estimator of price volatility as an alternative to the natural estimator. Based on the temporal estimator, we cannot find any systematic pattern of volatilities during the day in both spot and futures markets, and that futures prices appear to be more volatile than spot prices in terms of how quickly the price moves beyond a given unit price level, but not in terms of how much the price changes during a given unit time interval. Some policy implications are also discussed.

Futures Market - Determinants of Indian Futures Market

Futures Market - Determinants of Indian Futures Market
Author: Babu Jose
Publisher: LAP Lambert Academic Publishing
Total Pages: 132
Release: 2013
Genre:
ISBN: 9783659326042
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Futures Market movement always depends on the fluctuation of the spot market. Elements of the futures market such as Open Interest, Trade volume, Volatility of futures return and Turn over are having direct link with futures return. Underlying Market return is the major influencing factor of the futures market, but the uncertain events of the futures market can be explained by observing the different relation ships of variables in the futures market.Market Depth, Market Volatility and market Trends are having causal relationship with futures return. Market responses and reflections are explained by the study with the help of econometric models like VAR Granger Causality/Block Exogeniety test, Impulse Response Function and Variance Decomposition.Indian stock and derivative markets are so speculative and volatile, the prediction of the movement is very difficult. Daily return series of S&P CNX Nifty and its underlying index from 2000 to 2010 are taken for the analysis. The whole study period is divided in to five stages as per the market movement and structural break of the data series. The empirical results of the study reveals the determinants of the futures market in India.

A Further Investigation of the Lead-Lag Relationship in Returns and Volatility Between the Spot Market and Stock Index Futures

A Further Investigation of the Lead-Lag Relationship in Returns and Volatility Between the Spot Market and Stock Index Futures
Author: Sotirios Karagiannis
Publisher:
Total Pages: 50
Release: 2014
Genre:
ISBN:
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This paper investigates the lead-lag relationship in daily returns and volatilities between price movements of FTSE/ASE-20 futures and the underlying FTSE/ASE-20 cash index of the Athens Stock Exchange. The results suggest that there is a bidirectional causality between spot and futures returns, rejecting the usual result of futures leading spot market. However, spot market seems to play a more important role in price discovery. Volatility spillovers across the two markets are examined by using a bivariate EGARCH(1,1) model. This model is found to capture all the volatility dynamics. The results indicate that the transmission of volatility is bidirectional. Any piece of information that is released by the cash market has an effect on futures market volatility, and vice versa. Nevertheless, the volatility spillover from spot to futures market is slightly stronger than in the reverse direction.

Interdependence Between Spot and Futures Equity Markets

Interdependence Between Spot and Futures Equity Markets
Author: Vijay Kumar
Publisher: LAP Lambert Academic Publishing
Total Pages: 92
Release: 2012-06
Genre:
ISBN: 9783659144936
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Indian capital markets have been witnessed a major transformation and structural changes over the past one decade as a result of ongoing financial sector reforms initiated by the Government. This study investigated the lead lag relationship between the spot and futures equity market in India, both in terms of return and volatility, examines the lead lag relationship between the spot and futures markets for asymmetric information and also incorporate price co-integration relationship between spot and futures markets in the lead lag relationship analysis. We employed data in the study consists of intraday price histories from JAN 2001 to November 2005 for the nearby contract of nifty index futures and Index.We find a strong contemporaneous relationship between futures and cash prices, along with some significant evidence that futures markets leads spot market during times of high volatility. Consequently, reactions in futures markets are faster, and movements in futures prices lead spot price fluctuations.

Volatility of Exchange Rates in Spot and Futures Markets

Volatility of Exchange Rates in Spot and Futures Markets
Author: Sallem Koubida
Publisher:
Total Pages: 132
Release: 2007
Genre:
ISBN:
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This dissertation investigates conditional volatility in both spot and futures markets. We examine two approaches in spot market. While A parametric approach is the subject of the second chapter, the third chapter focuses on a nonparametric approach. In futures currency markets, we develop a model to identify the origin of conditional volatility using different type of traders. First, we focus on developing currency markets to explore if the conditional volatility in these markets have characteristics particular to themselves and to what extent these foreign exchange markets (Forex) share the characteristics of the developed markets using parametric models. Therefore, this paper examines weather the statistical models best suited for forecasting volatility of currencies from the high income countries also perform best in forecast of volatility of currencies from emerging market countries. Second, this study aims to forecast the conditional variance of exchange rates in developing countries using a non-parametric kernel smoothing technique with three different kernels: Gaussian, Epanechnikov, and Quartic. The evaluation of the predictive ability based on Root Mean Square Error, Mean Absolute Error, and Mean Absolute Percent Error to forecast 1, 5, and 22 days into the future shows that Gaussian distribution performs the best in short horizon while the other distributions converge to the same outcome as normal distribution in longer horizon. Finally, we try to identify what group of traders (hedgers or speculators) contributes more to the price volatility in currency futures markets. We control for both expected and unexpected trading volume and open interest to estimate the effect of traders' positions on the price volatility of currency futures. We find that short positions have significant associations with the volatility of futures prices. Further, the expected effect of short positions by speculators tends to have a larger effect than the expected effect of short positions by hedgers on volatility while the unexpected effect of short position by hedgers is likely to have a larger effect than the unexpected effect of short positions by speculators.

The Relationship Between Futures Market Speculation and Spot Market Volatility

The Relationship Between Futures Market Speculation and Spot Market Volatility
Author: Xuemei Xiao
Publisher:
Total Pages: 74
Release: 2018
Genre:
ISBN:
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This thesis investigates the relationship between speculation in futures markets and expected and unexpected volatility in the spot markets for 21 different commodities. I use the index of adequate speculation, INDADSP, and the index of excess speculation, INDEXSP, developed and estimated by Shanker (2017), to capture the degree of speculation required to meet hedging demand, and the degree of speculation in excess of hedging demand, respectively. For comparison, I also use Working's (1960) speculative index T, as a measure of speculation. I estimate the expected volatility (EV) and unexpected volatility (UEV) of the spot market using a GARCH model. The empirical results indicate that the GJR-GARCH model with a Student's t distribution for the error term is the most appropriate model, among the GARCH-family of models, to capture the volatility of 17 of the 21 spot commodity returns. However, the results of feeder cattle indicate the exists of serial correlation of the residuals for all three GARCH model I used, so I drop it and do the further analysis for the rest of 20 commodities and financial contracts. For each commodity, I create time series of matched weekly indices of speculation, expected volatility and unexpected volatility. Next, I investigate the long-run and short-run relationships between volatilities and speculation using an autoregressive distributed lag model. The results indicate that there is a long term relationship between expected and unexpected volatility and the speculative indices, for all commodities, except the Euro, Eurodollar, and U.S. T-bond, and a short term relationship between volatilities and speculation for all commodities. Finally, I apply the Toda-Yamamoto test to investigate the causal relationship between speculation in futures markets and volatility in spot markets. I find that speculation tends to lead expected volatility more than unexpected volatility for the majority of commodities/financial assets. Expected volatility, rather than unexpected volatility, tends to lead speculation for a majority of commodities/financial assets. There is a bidirectional causality between expected volatility and INDADSP, INDEXSP, and T and between unexpected volatility and INDEXSP for several different commodities and financial assets. However, there is no bidirectional causality between unexpected volatility and the speculative indices INDADSP and T for all 20 commodities/financial assets.