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| Longstaff-Schwartz 方法× | 无风险中性定价× | |
|---|---|---|
| 领域 | 量化金融 | 量化金融 |
| 方法族≠ | Machine learning | Regression model |
| 起源年份≠ | 2001 | 1979 |
| 提出者≠ | Francis A. Longstaff and Eduardo S. Schwartz | John Harrison and David Kreps |
| 类型≠ | Valuation Algorithm | Fundamental Principle |
| 开创性文献≠ | Longstaff, F. A., & Schwartz, E. S. (2001). Valuing American options by simulation: A simple least-squares approach. Review of Financial Studies, 14(1), 113-147. DOI ↗ | Harrison, J. M., & Kreps, D. M. (1979). Martingales and arbitrage in multiperiod securities markets. Journal of Economic Theory, 20(3), 381-408. DOI ↗ |
| 别名≠ | LSM, Least-Squares MC, Optimal Stopping | Risk-Neutral Measure, Q-Measure |
| 相关 | 4 | 4 |
| 摘要≠ | The Longstaff-Schwartz method (2001) is a Monte Carlo algorithm for pricing American options and Bermudan swaptions by approximating the optimal exercise boundary via least-squares regression. It has become the industry standard for pricing path-dependent derivatives where analytical solutions do not exist. | Risk-neutral valuation (1979) is the fundamental principle that derivative prices equal the expected payoff discounted at the risk-free rate, computed under a risk-neutral probability measure (Q-measure). This principle, formalized by Harrison and Kreps, eliminates the need to estimate risk premia and is the foundation of modern derivatives pricing. |
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