# Tag Info

Accepted

### Reasons for negative autocorrelation

Looking at transaction prices, they would occur at the market bid if the active part is a seller, and at the ask if the active part is a buyer. With a random flow of sellers and buyers, the price will ...
Accepted

### How to annualise the volatility of non-iid returns?

The correct answer has some intuition though it doesn't generalize to continuous time very easily: Think about the paper below like this: $Var(X+Y) = Var(X) + Var(Y) + 2Cov(X,Y)$ The generalization ...

### How to annualise the volatility of non-iid returns?

The answer is that it depends. In addition to the Lo paper above, there are a number of excellent references that go into depth about annualizing or time scaling non-i.i.d. returns, one of which is ...
Accepted

### How is the MA (moving average model) useful?

In terms of interpretation, an $MA$ model simply means that the time series is a function of the error from previous periods. You might find it informative to consider plotting simple $AR(1)$ models ...

Accepted

### Monte Carlo simulations of correlated stocks by Geometric Brownian motion

Let $n$ be the number of stocks (here $n=3$) Let $T$ be the number of sequential returns to generate (for example $T=12$ if you want to generate a year's worth of monthly returns) Let $M$ be the ...
Accepted

### Show that $\text{Cov}[X_r,X_s]=\text{Cov}[X_{r+h},X_{s+h}]$ for $X_t=a+bZ_t+cZ_{t-2}.$

in method 1 you did not use the correct definition of the covariance. For two random variables $X$ and $Y$ we have that $$Cov(X, Y) = E[XY] - E[X]E[Y].$$ Also, we can use that the covariance is ...
**please correct me if the math is wrong!! I think upon breaking down the products $E(dX_tdX_s)$, we have the $dtds$, $dtdW_s$ terms which all turns out to be 0. It leaves $E(dW_tdW_s)$ which comes ...