Hot answers tagged risk-neutral-measure
10
I think you are interpreting too much into the matter. The $-\frac12\sigma^2$ is just a correction term that comes from Jensen's inequality.
You need this when switching from supposedly symmetric returns (normal distribution) to the skewed price process (log-normal distribution).
I think there are no deeper truths to be found here.
7
Note first that this key equation is only assumed to hold true under some extra assumptions. Typically those assumptions are taken to be about absence of arbitrage, though it is possible to weaken them somewhat if you are willing to consider portfolio arguments or collectively agreeable objective function.
Anyway, the argument is this: if all the risk can ...
6
The classic argument using risk-neutral pricing is to assume that discounted stock prices are $\tilde{P}$-martingales where $\tilde{P}$ is the risk-neutral probability measure.
Then, you know that
$$\frac{S_t}{(1+r)^t}=\tilde{E}[\frac{S_T}{(1+r)^T} | \mathcal{F}_t]$$
by definition of a martingale process.
As the discounts are non-stochastic, you can ...
6
You can find a simple proof in the discrete time case at http://kalx.net/ftapd.pdf. I'm not sure what you are trying to derive with your Ito calculus, but here is a rigourous derivation of the Black-Sholes/Merton PDE: http://kalx.net/dsS2011/bms.pdf. The Black-Scholes '73 derivation is not mathematically correct.
The modern approach does not use so called ...
4
No, you obtain a risk-neutral measure by any change of measure; invariance is far more restrictive. Because in your formula $\mu\circ f^{-1} (A)=\mu(A)$, it has to be for any $A$.
Risk-neutrality can be seen as a way to inject into your model a list of market prices you really want to not be exposed to: once they are taken into account (i.e. once you made ...
4
The use of risk-neutral measure is based on the ability to arbitrage away the instantaneous risk of contingent claims. Although for forward contracts the hedge quantity is 1.0, in the general contingent claims case we must assume it varies instantaneously with the market state.
The Girsanov Theorem tells us what the difference is, instantaneously, between ...
3
One thing to keep in mind here is that the world of risk-free/arbitrage-free models is not necessarily the real world. Specifically, this equation
$$
\mu = r - \frac{1}{2}\sigma^2
$$
occurs not because this is the way stocks behave in reality (they don't! For S&P 500, long-run $\mu$ is closer to 6-9%, if I recall correctly), but because using any ...
3
What a great question -- it touches on many issues at the core of quantitative finance. This answer might be a lot more than you bargained for, but it's too interesting to pass up.
References
Mostly, this subject falls somewhere at the intersection of these three highly-interrelated topics: risk-neutral valuation, rational pricing and the fundamental ...
3
Yes. The risk neutral and the real path share the same volatility, so the difference is in the drift rate, where the risk-neutral path drifts with the risk-free rate r.
You may want to check out Paul Willmots book, esp. ch. 26, for applications.
3
Just following Musiela Rutkowski (the link redirects to Amazon). The risk neutral measure is derived form imposing that the present value of a self financed portfolio (i.e.; no infusion or withdraw of money) is a martingale. A portfolio can be seen as a stochastic process where its value at time $t$ is given by
$$
V_t = \phi^0_tP_t + \phi^1_tS_t\ ,
$$
...
3
Since I did not get any comments to my latest update, and since I find it quite convincing, I hereby post my solution as an answer.
maybe I can prove that Q exists assuming a lognormal distribution of $S_t$.
Assuming $dS_t = \mu S_t dt + \sigma S_t dW_t$
By Itô, $d(e^{-rt} S_t) = -r e^{-rt} S_t dt + e^{-rt} S_t dS_t$.
Replacing with the definition of ...
3
The only requirement if you are risk neutral is the property of martingale on your discounted stock price $M_t=e^{-rt} S_t$.
But if you apply Itô $d( S_t\cdot e^{-rt} e^{rt})=d(M_t\cdot e^{rt})=r_tM_te^{rt}dt + ..dW_t=r_tS_tdt+..dW_t$
you see see that under the risk free probability, the asset price must have $r_t$ as yield and to answer to your question, ...
2
The first think you have to ask is ¿¿What price??? Monetary price or equity price?? All answers,the ones I read, related to monetary price, but are equity price really risk free????
One of the biggest problem with Black Scholes (personal opinion) is that they consider the behave of equity price as monetary price: Solve this ODE: S(t)'/dt= r*S(0), this tell ...
2
ad) "Is it normal to assume no other drift?"
Under measure P you might have drift. You could use it as a working assumption, but in general indices drift every now and then. So, no, usually you do not assume away the drift.
"The index is described as "following a geometric Brownian motion", which to me says that the there is no other drift going on" ...
2
Have you looked at using Laplace in a Monte Carlo simulation? Here is how you price American style options within a MC framework:
http://www2.math.uu.se/research/pub/Jia1.pdf
and the Longstaff, Schwartz paper: http://escholarship.org/uc/item/43n1k4jb#page-1
Regarding the discretization of a process that draws its random variables from a Laplace ...
2
Yes, you do really use market prices to calibrate models derived under the risk-neutral measure. That is the whole reason why risk-neutral measures are utilized, to a) ease the calculations but mostly b) because under no arbitrage and one price for each security assumptions (among couple other other assumptions) the price derived under the risk neutral ...
2
In my mind you are simply right: you arrive at
$$
f(t,S) = S(t) - K e^{-r(T-t)}.
$$
Assume that $t=0$, so we are at the inception of the contract, then
$$
f(0,S) = S(0) - Ke^{-r T}.
$$
If you choose $K = S(0) e^{r T}$ then the contract value at inception is zero. This simply means that the fair price for the forward is given by $K= S(0) e^{r T}$ which is ...
2
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 ...
1
This may or may not be helpful, since I don't have anything to point you to that specifically addresses the high skewness of the distribution you mention. However, this sounds like it is probably an idiosyncratic risk, and that certainly has bearing on whether or not it would be priced.
In the standard capital asset pricing model, the marginal investor ...
1
I don't think Girsanov's formula works when the volatilities are different between the P measure and P* measure. P and P* will be singular with respect to each other.
Please see Prof. Goodman's class notes on page 11 at http://www.math.nyu.edu/faculty/goodman/teaching/StochCalc2012/notes/Week10.pdf .
Also, from [ ...
1
The Girsanov theorem applies to any compatible change of measure, including a volatility change. The version you have written above is a simplified version for drift changes only, but if you look in any good stochastic calculus book, you will see that full version just requires that you be able to compute the cross-variation of the two processes.
1
I'll take a stab.
In short rate modelling we start by postulating dynamics under pricing measure $Q$ and then calibrating our model to market prices. General short rate dynamics under $Q$ can be described as
$dr(t)=b(t_0+t,r(t))dt+\sigma(t_0+t,r(t))dW(t)$
, where $W$ is $Q$ Brownian motion. Note that the short rate process itself is not a $Q$-martingale ...
1
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, ...
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