19
votes
Quantifying climate change risk
Here are some resources that I found useful when learning about this subject, in which I'm very interested. (Some may be more general ESG than just just climate.)
Citigroup. Environmental and Social ...
- 12k
5
votes
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Can portfolio Value-at-Risk be calculated analytically for multivariate t-distributed returns?
Let the $n-$dimensional vector of returns $\mathbf{r}$ have a multivariate t distribution with $\nu$ degrees of freedom. The marginal distribution of any component $r_i$ has a univariate t ...
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4
votes
Hierarchical Risk Parity with allocation constraints?
EDITED
You are right. We have to look town to the "leaves" in each iteration. I would do it the following way:
If $L_i^{(j)}$ is the set of indices in the $j$ branch ($j \in \{1,2\}$), then we ...
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4
votes
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Quantitative risk management for energy markets
The book "Managing Energy Risk An Integrated View on Power and Other Energy Markets" by Burger et al. (2014) may be very helpful as it not only introduces the relevant notions, but does so directly ...
- 197
4
votes
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Filtered Historical Simulation VaR for swaps
Let us suppose for concreteness that the 10y swap rate is 0.5% today and was 7% a year and and 6.5% a "year minus a day" ago...
reprice the swaps for each historical scenario and calculate ...
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4
votes
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Why does Hierarchical Risk Parity ignore the clusters generated?
This turns out to be a general drawback of the HRP algorithm, as pointed out by Pfitzinger, J., & Katzke, N. (2019) (my highlights):
As shown in Figure 2.3, the naive bisection rule can violate ...
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3
votes
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How do energy companies measure the magnitude of the risks of buying energy at a variable price and selling it at a fixed price?
@Noob2’s comment above is “spot” on. Across the natural resource and energy value chains there are significant price risks that:
A. Market prices will fall below price takers’ unit costs; and,
B. ...
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3
votes
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Why is the expected value of bias statistic one?
If $r_t\sim N(\mu, \sigma)$, where $\sigma$ is the "true" standard deviation of $r_t$ (no $t$ subscript), then $\dfrac{r_t}{\sigma}\sim N(\frac \mu \sigma, 1)$.
Assuming perfect risk ...
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3
votes
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rationale for maturity adjustment formula in basel IRB formula
The maturity adjustment is there to take into account the risk of changing default probabilities in future years. Parameters are according to Basel calibrated from "observed... capital market data". ...
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3
votes
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Dominating credit risk modeling approaches for capital calculation in banks
The EBA performs the HDP (high default portfolio) and LDP (low default portfolio) benchmarking exercises, which would be relevant. You can find it on their website. Here are a couple of examples:
...
- 6,204
3
votes
PD and LGD for ECL calculations needs to be time dependent?
I assume that you calculate ECL in the context of IFRS9 -correct?
market practice often follows the following approach:
estimate a TTC PD/LGD (TTC = through the cycle). This corresponds to your ...
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3
votes
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Open source projects to gain demonstrable experience in implementing modeling in C++
I would give GitHub a try. Searching for option pricing or machine learning or anything like that yield a ton of repositories with implementations that you can look through and learn from. Here are ...
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3
votes
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Model Validation Aggregation Documentation (Binomial, Hosmer-Lemeshow, Tolerance) - Credit Risk et cetera
Take a look at these:
Bauke Maarse. Master Thesis: Backtesting Framework for PD, EAD and LGD (2012) https://essay.utwente.nl/61905/1/master_B._Maarse.pdf
Fábio Yasuhiro Tsukahara, Herbert Kimura, ...
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3
votes
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Variables for retail lending of bank
A good book on consumer credit is: Naeem Siddiqi. Intelligent Credit Scoring: Building and Implementing Better Credit Risk Scorecards.
In the U.S., there are many federal and state laws (Equal Credit ...
- 12k
3
votes
Filtered Historical Simulation VaR for swaps
Adding to Dimitris' answer (this is a too long for a comment)
Proceed as follows:
Identify risk factors $r^{(i)}$, $i=1\ldots n$. Say the absolute returns of the pillars 1Y,2Y,...30Y of the ...
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3
votes
Can PCA be used to transform a ladder of interest rate risk?
PCA is a mathematical transformation from a certain basis representation, i.e. 1y,2y,3y,4y, into another representation PC1, PC2, PC3 and PC4. In its raw form it is not a dimension reduction procedure....
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2
votes
Quantitative Real Estate Investment Finance
In fact there is at least one application, namely in the pricing of reversions. The simplest case of a reversion is where there is no ground rent, and where exclusive possession (including the right ...
- 337
2
votes
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Minimum PD under Basel II retail asset?
From the Basel II accord:
For corporate and bank exposures, the PD is the greater of the one-year PD
associated with the internal borrower grade to which that exposure is assigned, or 0.03%.
So it ...
- 1,345
2
votes
How to calculate unsystematic risk?
Unsystematic risk of a single stock can be calculated as follows:
$$\sigma_\lambda-\rho_{\lambda,m}\sigma_\lambda=\sigma_\lambda(1-\rho_{\lambda,m})$$
where $\sigma_\lambda$ is the volatility of ...
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2
votes
How to calculate unsystematic risk?
I have studied unsystematic risk [USR] for more than two decades. In fact, I wrote a book (which is here) whose central focus is how to deal with USR in the valuation of non-public companies. It is a ...
2
votes
Portfolio risk analysis in Options & Mixed portfolios
I'm not sure were your problem exactly lies, but of course you can apply standard risk techniques:
identify your risk factors (like stock prices and Implied Vol., yieldcurves, credit spreads, ...)
...
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2
votes
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Calculating HIstorical VaR with short time series
The best approach is awfully subjective but by characterizing your data set with EVT (e.g. Generalized Pareto Distribution) you could extrapolate into the tail which will give you more risk levels ...
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2
votes
It is possible to carry out the Component VaR decomposition through non parametric methodologies?
Yes, it is possible in general to allocate portfolio VaR to single positions in a portfolio. This is based on a general result on homogeneous risk measures called the Euler allocation. This allocation ...
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2
votes
Correlation or r-squared to determine if a stock has specific movement relative to an index?
Short answer: to find the companies with the higher specific risk, look for the regressions with higher mean squared residuals.
Long Answer: If you are interested in company specific risk, what you ...
2
votes
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Physical commodity trading quantitative risk return model
Your question piqued my interest. While not specific to commodities, this looks like a good starting point for quantifying political risk:
Practically, this means taking the following steps (...
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2
votes
Measuring interest rate sensitivity for illiquid private investments?
When you invest on private real estate or infrastructure, it pays you coupons periodically. So you can treat them as a bond. You can use a credit spread plus libor curve for discounting. the credit ...
- 51
2
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How to add Risks-Not-In-VaR (RNIV) to VaR under Basel III
I assume this is UK specific as RNIV is a PRA concept. You can’t recognise diversification as per the requirements which are detailed in the ss13/13: see section 2.
https://www.bankofengland.co.uk/-/...
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2
votes
Barra model: why standardize the fundamental risk factors?
Hi: If you don't standardize, then each coefficient will have a different meaning. For example, suppose you have a company, ZZZ, that has a 1.5 standard deviation value of "growth" factor exposure ...
- 1,082
2
votes
PD and LGD for ECL calculations needs to be time dependent?
You are building a model - the question you are asking is a trade off between accuracy and complexity.
If the accuracy only improves in a minor capacity and the extension is considered complex you ...
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