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2
votes
1answer
54 views

Parametric VaR with Student-t distribution

Im using VaR to estimate parametric VaR. I have been able to do this using a Normal Distribution, however I want to also do this using a Student t-distribution and I'm unsure how to implement that in ...
1
vote
1answer
40 views

How to measure the volatility of illiquid bond with no historical prices

The basket of corporate bonds that I am following barely traded after the issuance. Hence, there is no historical data to estimate the volatility. Can you suggest me a different approach to come up ...
2
votes
1answer
27 views

Expected Shortfall alternative formulation

Define: $$q_\alpha(F_L)=F^{\leftarrow}(\alpha)=\inf\lbrace{x\in \mathbb{R}\mid F_L(x)\geq \alpha\rbrace}=VaR_\alpha(L)$$ I want to prove that: $$ES_\alpha = ...
2
votes
0answers
37 views

Value-at-Risk Calculation with respect to the Capital Requirements

I want to calculate the Value-at-Risk at date $t$ in such a way that I minimize the capital requirements given as \begin{align} \text{CR}_{\,t+1\,:\,t+250} = \sum_{h=0}^{249}\max\left( ...
1
vote
1answer
46 views

Value-at-Risk of the sum of three independent lognormal random variables with different confidence level

there are three Business units in a firm, each has operational VaR value which are independent from eachother. the quantile for each opVaR is different from the others. can I simply add the VaRs to ...
2
votes
0answers
88 views

Empirical distribution function of overlapping time series data

If we model asset return volatility for periods of more than one (say more than one day) there is the square-root rule which holds true under some assumptions. The situation is more tricky if we look ...
1
vote
1answer
101 views

What is the difference between these two Expected Shortfall definitions?

I have come across different ways expected shortfall is defined. e.g. $$ES_a(X)=\frac{1}{1-a}\int_a^1VaR_b(X)db$$ and $$ES_a(X)=\frac{1}{a}\int_0^aVaR_b(X)db$$ e.g. on Wikipedia's article. Are these ...
0
votes
1answer
110 views

Quantiles, Value-at-Risk and log normal random walks…

Sorry, that's probably quite a bunch of silly questions, but I just got lost a bit and need to dot all the i's and cross some t's :). Let's say we have a series of returns (like this one we may get ...
1
vote
4answers
121 views

How to extrapolate VaR?

I have a model predicting 1-day VaR. How does 1-year VaR follow from it? Shall I just multiply by 365 or another method?
0
votes
0answers
30 views

Solvency Problem for Financial Institutions

According to my finance lecture, the motivation for risk measures is grounded in the solvency problem: Risk measures are used to determine the amount of capital to avoid insolvency of the financial ...
4
votes
1answer
131 views

Portfolio VaR with Copula?

Let the portfolio be given by: $$X=X_1+X_2$$ $(X_1,X_2)$ are dependent through a Copula function $C(u_1,u_2)$, such that the joint distribution is given by: $$F(x_1,x_2)=C(F(x_1),F(x_2))$$ What is ...
3
votes
1answer
155 views

Overlapping Value-at-Risk Backtest Data an Issue?

My understanding of VaR model back testing is thus: ~~ t: Calculate daily VaR using look back data over n past days t+1: Compare daily return against VaR, record breach if one occurred, repeat ...
2
votes
2answers
52 views

CVaR reformulation correct?

Conditional Value at Risk (CVaR) is given as: $$CVaR_\alpha(X)=\frac{1}{\alpha}\int_{0}^{\alpha}VaR_\beta(X)d\beta=-E(X|X\leq-VaR_\alpha(X))=-\frac{1}{\alpha}\int_{-\infty}^{-VaR_\alpha(X)}x \cdot ...
2
votes
0answers
79 views

Beta distribution - Holding period

Let's say I have a risk factor that is defined between [0,1], such as recovery rates. Assuming I have daily data, I can estimate the "daily VaR", i.e. the tails over 1 day period, since the data is ...
1
vote
2answers
207 views

Historic Value at Risk - Ratios vs. Differences

Quick Summary on Historic VaR Let $S_0,...,S_n$ be the daily values of some stock (where $S_0$ is the current value). Then for $i=1,\ldots,n$ we let $$\hat r_i:=S_{i-1}/S_i \quad \text{and}\quad \hat ...
4
votes
1answer
147 views

questions on VAR manipulation

The book of Financial Risk forecasting by Danielsson gives the following example about VAR manipulation. I have two questions: 1) If $0> VAR_1 > VAR_0$ , why the following figure plots it as ...
1
vote
2answers
1k views

Why is Value at Risk non-negative?

When reading the book of Financial Risk Forecasting, I saw the following example. I am not very clear about two points marked with yellow and green respectively. ...
1
vote
1answer
118 views

regarding Basel II III model

I may have to get involved in some projects using Basel II, III model for risk modeling, to which I have no background. Are there any good book/tutorials to recommend? What are the underlying ...
1
vote
4answers
333 views

How can I calculate Value at Risk?

Is it possible calculate Value at Risk on an asset without a time horizon? What kind of variables do you need? Variables that are on the table are value, standard deviation, beta, market return, risk ...
3
votes
2answers
171 views

CVaR/VaR Ratio as alpha goes to 1

I am having trouble taking the following limit of CVaR/VaR for a normal distribution as alpha approaches 1: $\lim_{\alpha \to 1} \frac{\mu + \sigma \frac{\phi^{-1}(\alpha)}{1-\alpha}}{\mu + \sigma ...
2
votes
1answer
972 views

Does one use the covariance or correlation matrix in cholesky decomposition to generate correlated samples

Can we interchangeably use Cholesky decomposition of covariance and correlation matrix to generate simulations? If not, in which situations do we use one or the other and why? Thanks in advance.
7
votes
2answers
346 views

Estimation of Empirical Expected Shortfall of a heavy tailed distribution

Assume that you have a portfolio for which you have estimated a parametric model to the underlying instruments, but the distribution of the portfolio as a whole is too complicated to compute ...
1
vote
0answers
252 views

Comparing Backtests of Value-at-Risk and Expected Shortfall

My goal is to test if ES (CVaR) empirically is a better risk measure than VaR for a set of given variables (assumed underlying distribution, confidence level, sample size) for different asset classes. ...
6
votes
0answers
359 views

Value-at-Risk formula when using skewed-t distribution

I am trying to find a formula for the skewed-t VaR. For example the VaR formula for a t-distribution is $$ \sqrt{\frac{df-2}{df}} \times \Sigma{t} \times \mbox{quantitle}(t-\mbox{dist}, 0.01) + \mu ...
2
votes
1answer
298 views

Determining the portfolio return distribution to calculate CVaR/ES

I'm trying to do a portfolio optimization with an expected shortfall constraint. For this, it is necessary to know the distribution of expected portfolio returns. When doing this empirically, my plan ...
3
votes
0answers
272 views

Market risk stress testing?

I am doing a research for a paper for market risk stress testing. In fact I found some information on the web about this important topic such as: Stress Testing from Art to Science Stress Testing ...
4
votes
2answers
861 views

Fitting distributions to financial data using volatility model to estimate VaR

I want to fit a distribution to my financial data using a volatility model to estimate the VaR. So in case of a normal distribution, this would be very easy, I assume the returns to follow a normal ...
2
votes
1answer
1k views

Value at Risk Monte-Carlo using Generalized Pareto Distribution(GPD)

I have created a VBA program to calculate VaR by using Monte Carlo, I have simulated Brownian Motion. This method might be ok for 100% equity portfolio, but let's say this portfolio may have fixed ...
1
vote
1answer
927 views

How to interpret/use VaR and Standard Deviation?

The parametric VaR is defined as follows: $$VaR=Z_a*Vol$$ Is this the best way to interpret how much risk is being taken on for a particular asset? How does one interpret volatility on its own if ...
8
votes
3answers
1k views

How does Cornish-Fisher VaR (aka modified VaR) scale with time?

I am thinking about the time-scaling of Cornish-Fisher VaR (see e.g. page 130 here for the formula). It involves the skewness and the excess-kurtosis of returns. The formula is clear and well ...