The normal-distribution tag has no wiki summary.
7
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1answer
401 views
Monte carlo portfolio risk simulation
My objective is to show the distribution of a portfolio's expected utilities via random sampling.
The utility function has two random components. The first component is an expected return vector ...
4
votes
5answers
425 views
In Black-Scholes, why is $\log{\frac{S_{t+\triangle t}}{S_t}} \sim \phi{((\mu - \frac{1}{2}\sigma^2)\triangle t, \sigma^2 \triangle t)}$?
Namely, I dont understand why the mean is $(\mu - \frac{1}{2}\sigma^2)\triangle t$ and not just $\mu \triangle t$. I am aware that it is supposed to represent a lognormal distribution, but I guess I'm ...
3
votes
2answers
95 views
Transformation to reduce standard deviation without changing median
Consider some negative skew and high kurtosis return time-series $X_t$. I do not know the functional form of the pdf of $X_t$ and have about 150,000 data points.
Suppose that I was to create an ...
2
votes
1answer
341 views
a simpler test for normality given skewness, kurtosis and autocorrelation and size of time series
I typically do a JB (Jarque Bera) test and DW (Durbin Watson) tests for check for normality given skewness, kurtosis and autocorrelation of the data. However this requires a CHI distribution table ...
1
vote
2answers
516 views
Whats the equation to calculate the area under the curve of a normal distribution, given an upper and lower standard deviation?
Lets say I want to find out the area under the graph of normal distribution curve, between X1=standard deviation of -0.5 and X2 = standard deviation of 0.5. Is there a formula for this?
Case study: ...
1
vote
1answer
127 views
normalized accumulation distribution
I am looking for a way to take an accumulation/distribution indicator and normalize it
so I can compare a bunch of stocks with stock prices that have no relationship with each other.
EDIT: This ...
1
vote
0answers
69 views
How to trade risk-adjusted returns?
Why does dividing daily returns by daily range eliminates fat tails and results in an (almost) gaussian distribution?
And how could that distribution be exploited to enter trades?
