A commodity market is a place for investors to trade in commodities like precious metals, crude oil, natural gas, energy, and spices, among others. Currently, the Forward Markets Commission allows futures trading in India for around 120 commodities. Trading in commodities is great for investors seeking to diversify their portfolio, as these investments often help with inflation. The Indian commodity derivatives market has shown solid flexibility to the Covid-19 pandemic, recovering rapidly from the underlying stock following the nation-wide complete lockdown. This study examines the market fundamentals, contract specification and market and price behaviour is the supreme problem of commodity investors and trader. The present study spotlights the price behaviour/movement and market behaviour/volatile in Indian agricultural commodity market (MCX) using econometric model. The study aims at market fundamentals of the commodity which includes demand, supply, import and export and changes in contract specification. The study also aims to study the volatility and caused effect between futures price and spot price of commodity cotton from the period 2019 to 2020 daily data were collected from Multi Commodity Exchange (MCX). This study also analysed the correlation and co-integration between the spot price and futures price of commodity cotton in Multi Commodity Exchange (MCX). The study employed statistics tools such as descriptive statistics, unit root test (ADF test), correlation test, OLS regression test, co-integration test, granger causality test, GRACH Test and ARIMA. The study found that the existence of normality and absence of unit root in time series data, also risk was higher than the mean return of futures and spot price of commodity cotton. There was low positive correlation between futures price and spot price of commodity cotton. In co-integration between spot and future price of commodity cotton explains that there is a long run relationship and both the prices are interconnected. The GARCH test evidenced that low volatility secured both futures price and spot price of commodity cotton and absence of cause and effect during the study period. The investors have to consider the high volatility commodity futures price which make effective in trading and investments in the aspect of price discovery. The result replicates that each commodity traded or invested in exchange has different price effectiveness concept and the investors and trader should recognise the commodity to hedge price risk. The last step that is ARIMA examines that the best criteria to forecast the cotton future price is ARIMA(0,1)(0,0).