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American Put Option pricing using Least squares Monte Carlo method under Bakshi, Cao and Chen Model Framework (1997) and comparison to alternative regression techniques in Monte Carlo
Anurag Sodhi
monte carlo simulation / option pricingResource overview

American Put Option pricing using Least squares Monte Carlo method under Bakshi, Cao and Chen Model Framework (1997) and comparison to alternative regression techniques in Monte Carlo

Paper2018

by Anurag Sodhi

Tags
monte carlo simulationoption pricing

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Suggested foundations for options and derivatives pricing and monte carlo and numerical simulation. Specialist prerequisites vary by paper.

Before you read

  1. The Binomial Model

    Build replication and risk-neutral probabilities in a tractable model.

  2. Market Model and Risk-Neutral Valuation

    Distinguish pricing probabilities from physical forecasts.

  3. Laws of Large Numbers and the Central Limit Theorem

    Understand convergence, sampling error and confidence intervals.

  4. Random Number Generation

    Generate reproducible samples and distinguish randomness from model assumptions.

Go further

  1. The Black-Scholes PDE, Formula and Implied Volatility

    Connect the pricing equation, closed-form value and implied volatility.

  2. Monte Carlo Option Pricing

    Turn a discounted payoff into an estimator.

  3. Correlated Randoms and Low-Discrepancy Sequences

    Study dependence and alternatives to independent sampling.

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