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The National commodity exchanges were established in India in the year 2003-2004 to perform the functions of price discovery and price risk management in the economy. The derivatives market can perform these functions properly only if they are efficient and unbiased. So, there is a need to properly evaluate these aspects of the Indian commodity derivatives market. The purpose of this paper is to test the market efficiency and unbiasedness of the Indian soybean futures markets.

The paper uses cointegration and a QARCH-M-ECM-based framework to test the market efficiency and unbiasedness in the soybean futures contract traded in the National Commodity Derivatives Exchange (NCDEX). The cointegration test is used to test the long-run unbiasedness and market efficiency of the contract, while the QARCH-M-ECM model is used to test the short-run market efficiency and unbiasedness of the contract by allowing for a time-varying risk premium. The price data is also tested for presence of structural breaks using a Zivot and Andrews unit root test.

The soybean contract is unbiased in the long run, but there are short-run market inefficiencies and also a presence of a time-varying risk premium. Though the weak form of market efficiency is rejected in the short run, the semi-strong market efficiency is not rejected based on the forecasts.

This is the first paper to consider time-varying risk premium while performing the tests of market efficiency and unbiasedness on Indian commodity markets.

I perform the backtesting of 10-day VaR's using daily returns of KOSPI 200 from January 1994 to December 1993 (2,692 days). The seven volatility measures are calculated with the last 300-day data; those are the historical standard deviations, the exponentially weighted moving average (EWMA) volatilities, the standard deviations from GARCH (1, 1) and three measures to consider autocorrelations in daily returns. The seven types of ten-day VaR’s at 1 % and 5% significance levels are estimated from these six volatility measures and 1 or 5 percentile of the last 300-day historical distributions I use the likelihood ratio (LR) test statistics to test the expected frequency and/or independence of the occurrence of extreme losses, that is, the losses which exceed the VaR values. The LR statistics for the expected frequence show that the VaR measure based on the historical standard deviations is the best one, but the LR statistics for independence reject the usefulness of ali the VaR measures.

It is well known that volatility asymmetry exists in financial markets. This paper reviews and investigates recently developed techniques for Bayesian estimation and model selection applied to a large group of modern asymmetric heteroskedastic models. These include the GJR-GARCH, threshold autoregression with GARCH errors, TGARCH, and double threshold heteroskedastic model with auxiliary threshold variables. Further, we briefly review recent methods for Bayesian model selection, such as, reversible-jump Markov chain Monte Carlo, Monte Carlo estimation via independent sampling from each model, and importance sampling methods. Seven heteroskedastic models are then compared, for three long series of daily Asian market returns, in a model selection study illustrating the preferred model selection method. Major evidence of nonlinearity in mean and volatility is found, with the preferred model having a weighted threshold variable of local and international market news.

This study aims to examine the transmission mechanism of factors on the characteristic fluctuation of Vietnamese coffee bean export price (PVN).

Applying Markov switching–vector autoregressive model.

Significantly, the empirical results showed that the transmission of independent variables on PVN is non-linear, and the fluctuation of PVN is affected by many factors, especially PVN in the previous period. In addition, the effect of Robusta coffee price was the greatest with coefficient is 0.28785, and the correlation between PVN and it was also the highest in both regimes with coefficients are 0.5317 and 0.3959, respectively.

These obtained results are in accordance with reality, as Vietnam is the largest exporter of Robusta coffee in the world.