This repository focuses on financial derivatives, covering fundamental pricing models, trading strategies, and risk management techniques. The goal is to provide well-documented implementations in R for analysing and understanding derivative instruments.
Fig. 1. Comparison of pay-offs between buying stocks and options
- Implementation of binomial tree models for pricing options.
A collection of options trading strategies used for hedging, speculation, and arbitrage:
a strategy using call options to profit from moderate price increases.
Fig. 2. Bull Spread using Calls
Fig. 3. Bull Spread using Puts
a strategy using put options to profit from moderate price decreases.
Fig. 4. Bear Spread using Calls
Fig. 5. Bear Spread using Puts
a neutral strategy involving multiple strike prices.
Fig. 6. Butterfly Spread using Calls
Fig. 7. Butterfly Spread using Puts
a volatility-based strategy using both call and put options.
Fig. 8. Straddle Combination
a variation of the straddle with different strike prices.
Fig. 9. Strangle Combination
a strategy betting on higher volatility with more puts than calls.
Fig. 10. Strip Combination
a similar to the strip but with more calls than puts.
Fig. 11. Strap Combination
- Estimating confidence intervals for derivative pricing models.
- Delta – Measures the sensitivity of an option's price to changes in the underlying asset's price.
- Gamma – Measures the rate of change of Delta with respect to the underlying asset's price.
- Theta – Represents the time decay of an option's price.
- Vega – Measures sensitivity to volatility changes in the underlying asset.
- Rho – Measures sensitivity to interest rate changes.
- Applications of Greeks in risk management and portfolio hedging.