Three approaches to value at risk (VaR) and volatility (FRM T4-1)

The three approaches are 1. Parametric; aka, analytical; 2. Historical simulation; and 3. Monte Carlo simulation (MCS). The parametric approach assumes a clean function, the other two work with messy data. Historical simulation is betrayed by a histogram, MCS is betrayed by a random number generator. In terms of the PARAMETRIC APPROACH (the 1st of three approaches), the key question is, "How do we estimate current volatility?" and we can take three basic approaches to this question.
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[@rodlu811]

Never seen someone explain this hard subject with so much clarity and simplicity.

[@samrathore9396]

Very well explained, its actually tough to explain the mathematical functions using the principles and concepts.

[@HARSHBENIWAL23]

I was stuck on this chapter for so... Thanks David for helping me out!! Kudos!!

[@bionicturtle]

You're welcome! We are glad that our video was so helpful :)

[@yvesprimeau6031]

Exellent explanation. The diagram of volatility help me to get the big picture of the concept. I suggest more diagrams too help us to visualize all the concepts of FRM at large....

[@Small1400]

Great videos! I was wondering what the best, most appropriate, approach would be to calculate volatility and eventually VaR in electricity markets, where often times prices are negative. Thanks in advance!

[@jaylev85]

Have you posted any videos that discuss Cholesky decomposition? more specifically the procedure for generating correlated variables from independent Rho's to fatten the tails. I think this is a technique that attemps to sovle some of the limitations of the Var-Covar approach (i.e. the "parameteric" or "historical method" mentioned above).

[@adventuresunlimited4483]

Amazing Videos.I referred to many sources but this is the first time I understood the concept. Is there an excel sheet for Monte Carlo VaR calculation ?

[@viciousbeats8510]

Is "r" interpreted as returns squared or (return minus mean of returns) squared?

[@ntcuong01ct1]

Hello friends, I have a few questions: 1 / Risks will be specified after we have identified the audience, objectives, and operational processes ?. 2 / Risk will be directly integrated into the business process ?. 3 / The Risk department is responsible for determining the VaR (Value at Risk) and presenting it to the Board of Directors seeing the risks and proactively preventing them? 4 / Actively preventing risks will help us improve the value of products / services to customers?

[@lmagz84]

How can we measure it using eviews

[@aslivinschi]

Dear professor, what about if I want to understand at 95% confidence what could be my best results instead of the risk of lost.?

[@bionicturtle]

Hi @Alexel maybe due to language differences, I cannot understand your question (apologies). This video reviews the three basic approaches to VaR, and VaR is the statistical way to answer "What is the worst expected loss with 9X% confidence?" Thanks,

[@aslivinschi]

@@bionicturtle many thanks! I am looking at the gains instead of losses, is kind of a reverse of VAR. I am trying to figure out at 90% confidence interval the minimum amount to gain instead of loosing. So, I done this formula for the min gains =Mean + (Std * Z-Stat) instead of doing as usual for the VAR= Mean - (STD *Z-Stat). I just changed the sign to plus, is that enough?

[@bionicturtle]

@@aslivinschi Oh, okay, yes sure you can do that! Maybe we call it "value at [to] gain"? aka, VaG. It would be similarly one-sided such that, if normal, at 95.0% Z = +1.645. And you would add the mean, just as you show, where your format is implicitly P(+)/L(-) which is natural math, gains are positive. So looks good to me

[@aslivinschi]

@@bionicturtle you are amazing. Thanks David

[@somebody5186]

Too much words. As for me.