Questions tagged [brownian-motion]

In mathematics, Brownian motion is described by the Wiener process; a continuous-time stochastic process named in honor of Norbert Wiener.

Filter by
Sorted by
Tagged with
0
votes
0answers
31 views

Distribution of the random variable $X (t) = ∫ s*B_sds$ [duplicate]

What is the distribution of the random variable $$X (t) = ∫ s*B_sds ?$$ The integral is taken over [0,t]. $$B_s$$ is a brownian motion.
0
votes
0answers
60 views

Two- (multi) dimensional geometric Brownian Motion

I am trying to calculate the value of a Basket Option with two stocks and the following information: S1 = 100, S2 = 120, r = 0.06 L = Volatilitymatrix = ((0.3, 0.1), (0.0, 0.2)), weight of Stock 1 = 1/...
0
votes
0answers
42 views

Risk-neutral Simple Return Moment Log-return Moment

I am trying to find a way to link Risk-neutral moment of simple return to risk-neutral moment of log-returns. Specifically, by making the same standard assumptions of the Black-Scholes model with the ...
0
votes
0answers
47 views

Does it make sense to simulate from the multidimensional GBM?

Suppose I have times series data on 3 assets and I do $N$ simulations (GBM) first for each of assets individually and then from a multidimensional GBM since their log-returns are correlated (I use ...
0
votes
0answers
213 views

Interpretation of drift parameter $\mu$ in GBM

Currently studying Ito's calculus. Looking on the GBM model: $ \frac{d S_t}{S_t} = μ dt + \sigma d B_t$ we end up on the expected stock price at time t: $E[S_t]=s_0 e^{\mu t}$.What does actually $\mu$ ...
0
votes
0answers
715 views

Proof that integral of Brownian motion wrt time is not a martingale

Let $X_t=\int_0^t W_s ds$ where $W_s$ is Brownian motion, so $E[W_s]=0$. Then $E[X_t]=\int_0^t E[W_s] ds=\int_0^t 0 ds=0$. So $E[X_t|{\cal F}_s]=0\neq X_s$, almost everywhere. So by previous ...
0
votes
1answer
464 views

Probability of Brownian motion particle touching barrier given path starts at $X_0$ and ends at a known $X_t$

I have been reading Su and Rieger's paper on barriers and from there have been able to work out the unconditional probability of the process $dXt = μ dt + σ dWt$ touching a down barrier $α$ to be $\...
-1
votes
3answers
226 views

Does the Ito correction term in GBM result in 'real money', or is it illusory?

There are two ways to think about investment returns and randomness. First is sort of like 'bank interest', with randomness. Suppose we invest 100 units of currency. Suppose each year there is a ...
-1
votes
1answer
500 views

Mark Joshi, The concepts and practice of mathematical finance chapter 6 exercise 6 [duplicate]

Suppose a stock allows a geometric Brownian motion in a Black-Scholes world. Develop an expression for the price of an option that pays $S^2 - K$ if $S^2 > K$ and zero otherwise. What PDE will this ...
-1
votes
2answers
82 views

Fourth moment of a itos integral

$I(t)=\int_0^t \sqrt sdW_s$ What is $E(I(t)^4)$
-1
votes
1answer
926 views

Bond price and its process

Suppose that x is the yield to maturity with continuous compounding on a discount bond that pays off $1 at time T. Assume that the x follows the process $dx=a(x_0-x)dt + sxdz$ where $a, x_0$ and $s$ ...
-1
votes
1answer
430 views

Expectation of the product of two Brownian motions [closed]

Could you please let me know the steps to follow to get to the solution?
-1
votes
1answer
1k views

Probability distribution and Stock Price Movement [closed]

How can we use normal distribution for finding the probability of a stock price offer where current price offer depends upon the last price offer. The price offer on some day can go 10% above (at the ...
-1
votes
1answer
88 views

Differential product Correlated processes

I am trying to derive the differential of the product of two processes, but I got stuck. This is what I have until now: We have the following two stochastic processes: $dX_t= \mu_t dt +\sigma_t dW_t$...
-2
votes
1answer
2k views

On the application of Itos lemma to Geometric Brownian motion [closed]

I recently read this from a book: The canonical SDE in financial math, the geometric Brownian motion, ${{d{S_t}} \over {{S_t}}} = \mu dt + \sigma d{W_t}$ has solution $${S_t} = {S_0}{e^{(\mu -...
-2
votes
1answer
427 views

Probability of geometric brownian motion taking a certain value

So we have an asset whose price follows a GMB: $dS_t = \mu S_t dt + \sigma S_t d W_t$ and want to know the probability that it drops 5% or more at time $t = 2$, given that $\mu = 0.04$ and $\sigma = ...
-2
votes
2answers
120 views

Martiglale and Brownian Motion [closed]

Stock market has been model as a random walk with a drift. Since it has a drift(bigger than zero) it is not a "Brownian Motion" but it still a Martingale? Is Stock market a Brownian Motion? Is it a ...
-2
votes
1answer
65 views

Why changing measure is necessary? [closed]

I want to understand the logic for why this is: We have our model for the stock price behaviour: $$d{S_t} = \mu {S_t}dt + \sigma {S_t}d{\tilde W_t}$$ It describes the development of a stock price ...
-3
votes
2answers
356 views

Geometric Brownian Motion: Why is the Wiener process multiplied by volatility?

Below is the stochastic differential equation of the Geometric Brownian Motion: $$dS_t = S_t \mu dt + S_t\sigma dW_t$$ My understanding of the Wiener process is that the volatility component of an ...
-5
votes
1answer
56 views

Which expression of $S_t$ to use under the Black-Scholes model?

I am currently looking at example exam questions relating to the evolution of a stock price under the Black-Scholes model. However, I am confused by seemingly inconsistent expressions used for the ...

1
4 5 6 7
8