# Tag Info

### Calculating tangency portfolio weights with the given information? (2risky +riskfree asset)

The denominator $1^T \Sigma^{-1} U_e$ is a scalar number. First you multiply the inverse by $U_e$ giving a column vector which I will call $X$, then premultiplication of this vector by $1^T$ basically ...
Accepted

### Derivation of optimal portfolio weights using Risk Budgeting approach

You are correct in your assumption, this is specified at the start of section 2.2.1 Definition of a risk budgeting portfolio. We consider a set of given risk budgets $\{B_1,\dots,B_n\}$. Here $B_i$ ...

### How do I show that there is no tangency portfolio?

Any point on the efficient frontier is the sum $$Z +\lambda X, \qquad \lambda\in\mathbb{R},$$ where $Z$ is the minimum variance fully invested portfolio and $X$ is an efficient zero-cost portfolio. ...
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### Difference between Maximum Drawdown and Largest Individual Drawdown

From your (or rather Bacon's) description, it seems to me that the "Largest Individual Drawdown" would more properly be called a losing streak, or a run of negative returns. Since you seem ...
Accepted

### Confusion about the formula for gain process in a financial market

@nbbo2 Thank you very much for providing this useful reference, I had a look into it and I think I understand now :) For simplicity, let's take $A \equiv 0$, $\delta \equiv 0$ and $r(s) \equiv r$ (it ...
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### Interpretation of optimal weights in portfolio for risk-adjusted return maximization

With regards to your question about the denominator, if we expand the denominator, it becomes: \begin{equation} w_1 = \frac{\mu_1\sigma_2^2 - \mu_2\rho\sigma_1\sigma_2} {\mu_1\sigma_2^2 - \mu_1\rho\...
1 vote
Accepted

### How can this problem be defined formally?

The event that the second stock price is less than a constant $K$ at the time $h$ is mathematically described by $\{S_2(h)< K\}$. The first stock price, at the time $t\in [T,H]$, given the event is ...
1 vote
Accepted

### Solving Equation for estimation risk averse parameter

You can think about it like this: given $\mu,\sigma,r$, a risk aversion parameter $\gamma$ will induce an optimal weight $w(\gamma)$, which in turn will induce some value at risk $VaR_{\alpha}$. Hence ...
1 vote
Accepted

The first one. Your net weight is zero. This is a self financing strategy. Think of it this way: if apple goes up by 10% and google goes down by 5% your return will be: $r_p = 1 \times 10\% - 1 \times ... 1 vote ### Calculating variance of long/short portfolio I think your are really asking how to normalize the weights. For example,$\$ \begin{align} w_\textrm{usd} &= \begin{bmatrix} 100 \\ 50\\ -200\\ 51 \end{bmatrix},\\ &~\\ w^\prime &= \frac{...

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