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Risk-Neutral Pricing and Attainable Option Payoffs

Article Quant Q&A · Author: L1meta

Summary

The discussion explains when risk-neutral pricing remains theoretically justified. Its central criterion is attainability: if a payoff can be replicated by trading in available assets, pricing can be tied to a replicating strategy. When a payoff cannot be attained, the standard unique pricing argument no longer applies, and valuation and hedging require additional choices or frameworks. The replies caution that there is no universal set of process assumptions that covers every market. Models must be assessed against their own conditions. Jumps, stochastic volatility, autocorrelation, illiquidity, and changing interest rates can all challenge assumptions or make complete hedging impossible. The Black-Scholes model is offered as an example whose simplifying assumptions may not fit observed markets. The exchange is conceptual rather than a worked derivation, and it does not specify a general alternative valuation method for unattainable claims.

Key ideas

  • Risk-neutral pricing relies on whether the payoff is attainable through trading in available assets.
  • Unattainable payoffs may not have a unique price determined by replication.
  • Model assumptions must be evaluated for the particular asset class and pricing framework.
  • Jumps, stochastic volatility, autocorrelation, illiquidity, and changing rates can affect hedging completeness.

Tags

Full text
# What mathematical characteristics are required from the asset price process in order to stay within the RNP framework?


# What mathematical characteristics are required from the asset price process in order to stay within the RNP framework?












I'm currently doing a course in derivatives pricing and I'm having some trouble wrapping my head around the sweet spot where theory meets reality in terms of Risk Neutral Pricing.

I know that the first and second fundamental theorems of asset pricing lays the foundation for the normal risk neutral pricing argument, and that part is fine. However my lecturer said that for example if you have certain types of stochastic volatility, or the asset price follows a jump process you can no longer hedge all the risks from holding the option. But the way I understand it you need to be able to hedge all the risks from the asset price process in order to use the RNP framework.

So my question is this; when building a model for an asset price process (that you ideally want to be as realistic as possible), what specific characteristics (assumptions about sources of risk etc.) need to be in place in order to keep you within the RNP framework. Conversely, at what point does this machinery break down?

## Answer by Alexey Kalmykov (score 1, accepted)

https://quant.stackexchange.com/a/3325

I assume that by "this machinery breaks down" you mean when it breaks down as theory, but not as a practical tool.

I would say that the exact point where risk neutral pricing approach fails is when the payoff is no more attainable. There exist a precise mathematical characterization for attainable payoffs (see the book of Hans Föllmer, Alexander Schied, "Stochastic Finance: An Introduction in Discrete Time"). And as far as I know, there is no standard approach to valuation and hedging non-attainable payoffs (for example). Note also that there are many reasons for payoff to be non-attainable and it's hard to define them all precisely.

## Answer by Konsta (score 2)

https://quant.stackexchange.com/a/3318

This depends. I am not aware of a general risk neutral pricing framework applying to all asset classes and/or stochastic processes. In order to reach more general statements about risk neutral pricing you need to consider jumps and autocorrelation depending on the asset regarded, maybe stochastic interest rates and/or volatility. If I remember correctly, in case of (autocorrelated) fractional Brownian Motion arbitrage opportunities occur. Thus standard assumptions do not hold anymore. So you need to compare with the assumptions of "your" risk neutral pricing framework. In case of the Black-Scholes-Model simply deviation from its assumptions need to be accounted for: normally distributed returns do not exhibit jumps nor autocorrelation, constant volatility does not account for shifts or clusters of volatility. Your asset might not be liquid (think of options on small single stocks) or interest rate might not be constant - gets more important with interest rate derivatives, but applies to longer dated euqity (index) options as well.

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.