Probability with Martingales¶
Williams, D. (1991). Probability with Martingales. Cambridge University Press.
Cited by¶
5 citations across 5 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Conditional Probability
- Statistics and probability theory. The foundational object on which inference, decision theory, and stochastic-process theory are built; the filtration of information in martingale theory is the continuous-time generalization of conditioning.
This sourceStandard text developing conditional expectation and filtrations, the continuous-time generalization of conditioning on accumulated information in martingale theory.
- Statistics and probability theory. The foundational object on which inference, decision theory, and stochastic-process theory are built; the filtration of information in martingale theory is the continuous-time generalization of conditioning.
- Stochastic Process
- The martingale concept transfers from gambling and fair games to the no-arbitrage pricing of derivatives (a discounted price is a martingale under the risk-neutral measure) to the analysis of stochastic algorithms (martingale concentration bounds), because "the conditional future expectation equals the present" is a substrate-free structural property.
This sourceCanonical treatment of martingales — conditional future expectation equal to the present — as a substrate-free structural property.
- The martingale concept transfers from gambling and fair games to the no-arbitrage pricing of derivatives (a discounted price is a martingale under the risk-neutral measure) to the analysis of stochastic algorithms (martingale concentration bounds), because "the conditional future expectation equals the present" is a substrate-free structural property.
Domain-specific¶
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