What does Quantum Forecast offer to its clients?
Predictive statistical models in the S&P 500 options market.
Statistical models play a crucial role in the S&P 500, Nasdaq, Russell 2000 options market, helping traders to:
• Predict price movements: Time series models, such as ARIMA and GARCH, can be used to analyze historical S&P 500 index and options price data to identify patterns and trends that can help predict future price movements.
• Estimate volatility: Volatility is a key factor in option pricing. Statistical models, such as the Black-Scholes model and stochastic volatility models, can be used to estimate implied and historical volatility, which can help traders evaluate options and manage risk.
• Identify arbitrage opportunities: Statistical models can be used to identify price discrepancies between different options or between the option price and the price of the underlying index which can create arbitrage opportunities.
• Manage risk: Risk models, such as Value at Risk (VaR) and Conditional Value at Risk (CVaR), can be used to estimate the potential losses of an options portfolio under different market conditions.
- development of code in Python language for trading platforms with the aim of automating entries and exits
- development of advanced software to analyze real-time movements of options and 0dte options
- statistical analysis and software engineering on commodities, particularly Crude Oil, Gold, Silver, Copper, Aluminium, Steel, Iron Ore
- development of algorithms for high frequency trading on Cme and Eurex market