# Tag Info

Accepted

### CAPM model as a regression

If you really believed the CAPM's prediction that $\alpha=0$, then imposing $\alpha=0$ in your estimation would indeed lead to your 2nd formula. The problems? The CAPM doesn't work so imposing a ...
• 6,394
Accepted

### Is there a way using matrix algebra to add portfolios to a covariance matrix of assets?

If your two assets are denoted by random variables $X_1$, $X_2$, with 2x2 covariance matrix $\mathbf{Q}$ and the portfolios: $$Z_1 = w_{11} X_1 + w_{12} X_2$$ $$Z_2 = w_{21} X_1 + w_{22} X_2$$ ...
• 8,099

### What is the preferred GARCH method in practice?

I personally use the simple Garch(1,1) for volatility filtering in the risk management area. In fact in most cases I don't even estimate the parameters, I stick 0.94 for mean reversion, 0.04 for the ...
• 4,247

### Estimate covariance matrix using prices

If you assume that a financial asset price has a change that is a wiener process then you can view the future value of that asset as the initial value plus the sum of the independent daily changes (...
• 8,099
Accepted

### Covariance matrix and Cholesky decomposition

I am not sure if I understood your question correctly but I will try to answer it anyway. If you have a standard normal random vector $z \sim N(\mathbb{0},I_n)$ (where $z,0 \in \mathbb{R}^{n\times1}$ ...
• 2,894
Accepted

• 5,938

### What is the preferred GARCH method in practice?

Interesting question, as All the answers (including mine) could not be generalized unfortunately. As far as I am concerned, I use a univariate EGARCH for risk modelling purposes (Filtered Historical ...
• 315

### Ledoit-Wolf Shrinkage estimator not giving positive definite covariance matrix

In theory, the Ledoit and Wolf shrinkage estimator is supposed to guarantee a positive-definite matrix, given that it adds a positive-definite matrix (the target) to a semi-positive one (the sample ...
• 141

### Ledoit-Wolf Shrinkage estimator not giving positive definite covariance matrix

The problem with Ledoit-Wolf is that it's very sensitive to outliers. You should try these: DCC GARCH unfortunately, not available in Python Exponentially weighed moving average (EWMA) gives ...
• 319