What is the Role of Martingale Measures in Pricing Options?

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In summary, if you have a model of the underlying asset and wish to price an option then you should take the expectation under Q (a martingale measure).
  • #1
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Hey,

I was wondering if anyone knows a bit about financial probability theory. I was wondering when you are pricing options, you take the expectation under Q (a martingale measure). In the case of Black and Scholes, this seems simple as it is unique. When the martingale measure is not unique (in the case of Levy processes for example), does it matter which measure you choose to take E under? If so which one do you choose when you wish to price options?

Thanks in advance
 
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  • #2
Yes it does matter which one you take, and there is no single correct answer. If there is more than one equivalent martingale measure, and the expectation of the contingent claim is different under different measures, then it can't be hedged exactly and there is not a unique arbitrage price.

However, there are some things you can do (by no means a complete list)
1) find upper and lower bounds on the value. If you are long the claim, to be conservative you should look at the lower bound on its value.
2) look at other related tradable market intruments. Is there a freely traded option market on the underlyer? If there is, these can also be used for hedging and you can restrict yourself to equivalent martingale measures which also correctly price these options.
3) define a utility function. You should hedge so as to maximise your total utility. The price at which you should value the claim is the maximum price which you can pay and still achieve non-negative utility.

Other things such as the so-called minimal martingale measure can be used, although I don't really know if this is used much.
 
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  • #3
If there is not a unique risk neutral price, then there are limits on the possibility of arbitrage

In practice Monte Carlo methods would be most commonly used rather than BSM
 
  • #4
BWV said:
If there is not a unique risk neutral price, then there are limits on the possibility of arbitrage

In practice Monte Carlo methods would be most commonly used rather than BSM

If the martingale exists then surely there is no arbitrage in the model?!


gel said:
Yes it does matter which one you take, and there is no single correct answer. If there is more than one equivalent martingale measure, and the expectation of the contingent claim is different under different measures, then it can't be hedged exactly and there is not a unique arbitrage price.

However, there are some things you can do (by no means a complete list)
1) find upper and lower bounds on the value. If you are long the claim, to be conservative you should look at the lower bound on its value.
2) look at other related tradable market intruments. Is there a freely traded option market on the underlyer? If there is, these can also be used for hedging and you can restrict yourself to equivalent martingale measures which also correctly price these options.
3) define a utility function. You should hedge so as to maximise your total utility. The price at which you should value the claim is the maximum price which you can pay and still achieve non-negative utility.

Other things such as the so-called minimal martingale measure can be used, although I don't really know if this is used much.

Sorry I am a bit confused. I have a model on the underlying asset of the option and I wish to price the option to see how well this pricing fits the market. I've read various papers on this by Carr and Madan and such. I ideally want to produce the circles and crosses plots they have. I also have the book Financial Modeling with Jumps by Cont and Tankov that has a section on hedging strategies. The problem is I have no idea which one to use to price options. I really just want to check the model fits against option prices. Sorry I am a bit impaired when it comes to applying stuff.

Thanks for the replies
 
  • #5
yes, it's true that if you have a martingale measure then there is no arbitrage. However, under the Black-Scholes model there is also a unique price at which you can buy/sell the option without introducing any arbitrage (which is what I mean by the arbitrage price). This is also the unique price from which you can exactly replicate the payoff of the option by continuous trading.
If you have more than one equivalent martingale measure then there can be many different prices at which it could trade without introducing arbitrage, and you can't replicate the option payoff. So the maths does not help as much here. In practise, if you were buying or selling an option then the price you would be prepared to pay will also depend on your attitude to the unhedgeable risk that you would be taking on.

Hoever, if you just want to replicate some graphs and generate a consistent set of theoretical option prices, then you need to choose one equivalent martingale measure and use that. The papers you're reading should say which measure is being used to do this, and you should use the same.
 
  • #6
Thanks for the reply, I will go over the papers again, they seem to cross referencing a lot so it looks like a long road.

Sorry to be such a pain but do you have any idea where I can get some option data from (I have about £120 which is about $200 i think + a library :D)?
 
  • #7
The papers should say which measure they are using to generate the graphs -- i.e. if they specify a SDE for the process which is already in martingale form, and it is not explicitly mentioned which measure they use, then I think you should just use the measure under which the SDE takes that form.

Sorry, don't know where's the best place to get option data from. I could look around, but I'd only be searching with google, which you can do yourself just as easy.
 
  • #8
My bad, they use Esscher Transform. I will read up on it. Don't worry about searching google, I tried already. Thanks a lot for your help. Nice to see some experts in this field :D. It is certainly interesting.
 

1. What is a risk neutral martingale?

A risk neutral martingale is a mathematical concept used in finance to model the price dynamics of financial assets. It is a stochastic process that satisfies the properties of a martingale, meaning that the expected value of the process at any future time is equal to its current value. The "risk neutral" part refers to the assumption that investors are indifferent to risk when making investment decisions, allowing for simpler calculations and analysis.

2. How is risk neutrality achieved in a risk neutral martingale?

Risk neutrality is achieved by using a risk-neutral measure, also known as a martingale measure, to calculate the expected value of the stochastic process. This measure is constructed by adjusting the probabilities of different outcomes in the process so that the expected return on the asset is equal to the risk-free rate of return. This allows for the simplification of calculations and the elimination of risk from the model.

3. What are the applications of risk neutral martingales?

Risk neutral martingales are commonly used in financial modeling to price derivatives, such as options and futures contracts. They also have applications in portfolio optimization, risk management, and asset pricing. Additionally, they can be used to analyze the fair value of complex financial instruments and to assess the likelihood of extreme market events.

4. What is the relationship between risk neutral martingales and arbitrage?

Risk neutral martingales are closely related to the concept of arbitrage, which is the ability to make a profit without taking on any risk. In a risk neutral martingale, the expected return on an asset is equal to the risk-free rate of return, so there is no opportunity for arbitrage. If a deviation from this condition occurs, an arbitrage opportunity may arise, and the market will adjust to eliminate it.

5. How are risk neutral martingales different from traditional financial models?

Risk neutral martingales differ from traditional financial models in that they do not incorporate risk or investor preferences in their calculations. Instead, they assume that investors are risk neutral, allowing for simpler and more tractable models. This can be seen as a limitation, as it does not fully capture the complexities of real-world financial markets, but it also allows for easier calculations and analysis.

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