FUNDAMENTAL ANALYSIS AND ECONOMETRIC MODELING OF PRICE DYNAMICS OF STOCK INDEX FUTURES CONTRACTS

Abstract

The article combines the deterministic cost-of-carry framework with econometric tools for market risk assessment applied to stock index futures contracts. The theoretical part rests on the no-arbitrage principle, under which the equilibrium forward price of a financial asset is determined by the relationship between the risk-free rate and the dividend yield, while the sign and magnitude of the basis reflect the net cost of carry. Using a quarterly S&P 500 index futures contract with end-2025 reference values, the fair price is computed, showing that the excess of financing cost over dividend yield places the market in contango with a premium of about 0.64% of the spot value. The empirical block relies on the monthly index series for 2015–2025 transformed into logarithmic returns. Descriptive statistics reveal departures from normality, namely negative skewness and excess kurtosis, confirmed by the Jarque-Bera test. The time variation of risk is formalized through conditional variance models of the GARCH family, accounting for the asymmetric reaction of volatility to negative shocks. Tail risk is measured by Value-at-Risk and Expected Shortfall, while the accumulated adverse dynamics are captured by cumulative drawdown. Scenario forecasting is performed by Monte Carlo simulation over a twelve-month horizon with quantile intervals, complemented by stress scenarios of extreme losses. The findings demonstrate that futures price dynamics cannot be described by any single indicator: the mean return captures the central tendency, the standard deviation reflects the typical scale of fluctuations, VaR and Expected Shortfall express tail risk, drawdown shows the depth of position impairment, and Monte Carlo delineates the range of future uncertainty. The practical value of the proposed approach lies in applying an integrated assessment to position sizing, margin planning, and the construction of hedging strategies. The presented framework can be embedded directly into the risk management practice of exchange participants, since every computational block relies on openly available market data and reproducible econometric procedures, which makes the approach suitable for the regular monitoring of margin adequacy, position limits and the resilience of a futures portfolio to extreme price movements.