Gamma stochastic volatility models

This paper presents gamma stochastic volatility models and investigates its distributional and time series properties. The parameter estimators obtained by the method of moments are shown analytically to be consistent and asymptotically normal. The simulation results indicate that the estimators behave well. The insample analysis shows that return models with gamma autoregressive stochastic volatility processes capture the leptokurtic nature of return distributions and the slowly decaying autocorrelation functions of squared stock index returns for the USA and UK. In comparison with GARCH and EGARCH models, the gamma autoregressive model picks up the persistence in volatility for the US and UK index returns but not the volatility persistence for the Canadian and Japanese index returns. The out-of-sample analysis indicates that the gamma autoregressive model has a superior volatility forecasting performance compared to GARCH and EGARCH models.

Analysis of Stochastic Volatility Sequences Generated by Product Autoregressive Models

The classical methods of analysing time series by Box-Jenkins approach assume that the observed series uctuates around changing levels with constant variance. That is, the time series is assumed to be of homoscedastic nature. However, the nancial time series exhibits the presence of heteroscedasticity in the sense that, it possesses non-constant conditional variance given the past observations. So, the analysis of nancial time series, requires the modelling of such variances, which may depend on some time dependent factors or its own past values. This lead to introduction of several classes of models to study the behaviour of nancial time series. See Taylor (1986), Tsay (2005), Rachev et al. (2007). The class of models, used to describe the evolution of conditional variances is referred to as stochastic volatility modelsThe stochastic models available to analyse the conditional variances, are based on either normal or log-normal distributions. One of the objectives of the present study is to explore the possibility of employing some non-Gaussian distributions to model the volatility sequences and then study the behaviour of the resulting return series. This lead us to work on the related problem of statistical inference, which is the main contribution of the thesis

Computationally Efficient Bootstrap Prediction Intervals for Returns and Volatilities in ARCH and GARCH Processes

We propose a novel, simple, efficient and distribution-free re-sampling technique for developing prediction intervals for returns and volatilities following ARCH/GARCH models. In particular, our key idea is to employ a Box–Jenkins linear representation of an ARCH/GARCH equation and then to adapt a sieve bootstrap procedure to the nonlinear GARCH framework. Our simulation studies indicate that the new re-sampling method provides sharp and well calibrated prediction intervals for both returns and volatilities while reducing computational costs by up to 100 times, compared to other available re-sampling techniques for ARCH/GARCH models. The proposed procedure is illustrated by an application to Yen/U.S. dollar daily exchange rate data.

Studies on Polymer Bound Antioxidants

The primary aim of this work has been to prepare efficient and cost effective polymer bound antioxidants by direct’ attachment of conventional antioxidants to a modified polymer. Due to the importance and easy availability of natural rubber in Kerala, it is proposed to make use of low molecular weight natural rubber as the polymer substrate for binding the antioxidant in most cases. The molecular weight of such low molecular weight natural rubber can be easily manipulated by varying the time of mastication, UV—irradiation etc. Further, the bound antioxidant may also get vulcanized during the vulcanization of the elastomer to which it is added, making the antioxidant non—volatile and non extractable. Several methods are proposed to be investigated for attaching the antioxidant to the low molecular weight natural rubber such as modified Friedel-Craft's alkylation reaction, binding during UV—irradiation, binding during aggressive mastication etc. The efficiency of such rubber bound antioxidants is proposed to be compared with that of conventional antioxidants in terms of volatility, extractability in solvents, ageing resistance etc. Naturally occuring antioxidants such as cardanol, are also proposed to be modified by binding them to low molecular weight natural rubber. The study is undertaken with the intention of generating a class of bound antioxidants which can be used in elastomers for aggressive and long term application.

Product autoregressive models for non-negative variables

When variables in time series context are non-negative, such as for volatility, survival time or wave heights, a multiplicative autoregressive model of the type Xt = Xα t−1Vt , 0 ≤ α < 1, t = 1, 2, . . . may give the preferred dependent structure. In this paper, we study the properties of such models and propose methods for parameter estimation. Explicit solutions of the model are obtained in the case of gamma marginal distribution

A Study on Futures Trading in Commodities With Special Reference to Rubber

Futures trading in Commodities has three specific economic functions viz. price discovery, hedging and reduction in volatility. Natural rubber possesses all the specifications required for futures trading. Commodity futures trading in India attained momentum after the starting of national level commodity exchanges in 2003. The success of futures trading depends upon effective price risk management, price discovery and reduced volatility which in turn depends upon the volume of trading. In the case of rubber futures market, the volume of trading depends upon the extent of participation by market players like growers, dealers, manufacturers, rubber marketing co-operative societies and Rubber Producer’s Societies (RPS). The extent of participation by market players has a direct bearing on their awareness level and their perception about futures trading. In the light of the above facts and the review of literature available on rubber futures market, it is felt that a study on rubber futures market is necessary to fill the research gap, with specific focus on (1) the awareness and perception of rubber futures market participants viz. (i) rubber growers, (ii) dealers, (iii) rubber product manufacturers, (iv) rubber marketing co-operative societies and Rubber Producer’s Societies (RPS) about futures trading and (2) whether the rubber futures market is fulfilling the economic functions of futures market viz. hedging, reduction in volatility and price discovery or not. The study is confined to growers, dealers, rubber goods manufacturers, rubber marketing co-operative societies and RPS in Kerala. In order to achieve the stated objectives, the study utilized secondary data for the period from 2003 to 2013 from different published sources like bulletins, newsletters, circulars from NMCE, Reserve Bank of India (RBI), Warehousing Corporation and traders. The primary data required for this study were collected from rubber growers, rubber dealers, RPS & Rubber Marketing Co-operative Societies and rubber goods manufacturers in Kerala. Data pertaining to the awareness and perception of futures trading, participation in the futures trading, use of spot and futures prices and source of price information by dealers, farmers, manufacturers and cooperative societies also were collected. Statistical tools used for analysis include percentage, standard deviation, Chi-square test, Mann – Whitney U test, Kruskal Wallis test, Augmented Dickey – Fuller test statistic, t- statistic, Granger causality test, F- statistic, Johansen co – integration test, Trace statistic and Max –Eigen statistic. The study found that 71.5 per cent of the total hedges are effective and 28.5 per cent are ineffective for the period under study. It implies that futures market in rubber reduced the impact of price risks by approximately 71.5 per cent. Further, it is observed that, on 54.4 per cent occasions, the futures market exercised a stabilizing effect on the spot market, and on 45.6 per cent occasions futures trading exercised a destabilizing effect on the spot market. It implies that elasticity of expectation of futures market in rubber has a predominant stabilizing effect on spot prices. The market, as a whole, exhibits a bias in favour of long hedges. Spot price volatility of rubber during futures suspension period is more than that of the pre suspension period and post suspension period. There is a bi-directional association-ship or bi-directional causality or pair- wise causality between spot price and futures price of rubber. From the results of the hedging efficiency, spot price volatility, and price discovery, it can be concluded that rubber futures market fulfils all the economic functions expected from a commodity futures market. Thus in India, the future of rubber futures is Bright…!!!