Fig_SupportingData

The provided dataset contains results from Monte Carlo simulations related to variance swaps. The data is organized into multiple sheets, each focusing on different parameters and scenarios.Figure 1:Monte Carlo Simulations: This section presents the results of Monte Carlo simulations for both discretely-sampled and continuously-sampled variance swaps. The values are reported for different sample sizes (N=12 to N=322), showing how the estimated variance swap values converge as the number of samples increases.Sample 1 and Sample 2: These represent two different sets of simulation results, each showing the impact of varying sample sizes on the variance swap values.Figure 2:κθ (Kappa Theta): This section explores the impact of different values of κθ on the variance swap values. θ̃ (Theta Tilde): This part examines the effect of varying θ̃ on the variance swap values .σθ (Sigma Theta): This section analyzes the influence of σθ on the variance swap values .θ₀ (Theta Zero): This part investigates the impact of different initial volatility levels (θ₀) on the variance swap values .Sheet 3:λ (Lambda): This section studies the effect of varying λ on the variance swap values .η (Eta): This part examines the influence of η on the variance swap values .v (Nu): This section analyzes the impact of v on the variance swap values .δ (Delta): This part investigates the effect of varying δ on the variance swap values .Overall, the dataset provides a comprehensive analysis of how different parameters and sampling methods affect the valuation of variance swaps, offering insights into the sensitivity and convergence behavior of these financial instruments under various conditions.