What is value at risk (VaR)? FRM T1-02

Value at risk is just a statistical feature of the probability distribution (the hard part is specifying the probability distribution): VaR is the quantile associated with a selected probability; i.e., what's the worst that can happen with some level of confidence? (Here is my XLS trtl.bz/1008-what-is-var)
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[@kapoiosenadip7157]

My lecturer in a very expensive business school couldn’t explain that for 3 weeks... thank u so much man

[@junal27]

Nowadays education is not a matter of money anymore but willing to learn

[@loveraswift5665]

Yeah... My teacher taught this for hours but this video clearly demonstrates what it is in only 10 minutes!

[@hwillis7570]

Nice explanation, clear, concise. Keep up your good work.

[@Edusho09]

I'm from Germany and your videos are great! Easy to understand. Keep it up !

[@bionicturtle]

Thank you for watching! We are so happy to hear that our videos are so helpful!

[@TheChaozao]

god bless you. u explained what my book and lecturer couldnt

[@bionicturtle]

Thank you for watching! We are very happy to hear that our video was so helpful.

[@nafiibrahimaj8870]

Great instructor of our modern era!, thank you so much for simplicity and practicality

[@bakhtamatri9930]

Thanks a lot, very clear explanation for VAR.

[@guapotomask]

Great video very well explained

[@bionicturtle]

Thank you for watching! We are happy to hear that our video was helpful!

[@BrigataUPG]

Hi. How it would be possible to calculate the VAR for a company which holds money in a bank account? It would make sense to assess the bank financial soundness, calculating the CAP ratio e than calculating the VAR for that company? what formula might be applied for this kind of calculation? thanks!

[@jrfabian]

very nice video!! thank you!

[@knittingangel3859]

Great explanation, thank you

[@jenevavergara4125]

Hi thanks for the great video, I am doing thesis using GARCH-MIDAS model using Generalized Hyperbolic distribution, do you have any idea how to compute VAR in R using these models and distribution?

[@stickhero23]

Hello, completed your thesis? jedwriter.com

[@fjosh457]

maximum loss that an investor can put up with; so that defines amount of collateralization after default.

[@simfinso858]

it is just similar to " p" value. isn't it?

[@roberts8783]

Whats the typical var of a market portfolio like s and p 500 ?

[@trifenatejowijaya6857]

Thank you!!!!!!

[@investwithvincent6329]

What's formula in the cell for VaR?

[@celinetjokro2515]

hi, shouldn't the test be two tailed?

[@18lan]

thank you

[@jijiBoylieber]

Hello, can i please know what the confiance level is?

[@bionicturtle]

We select the confidence level. Typical selections are 95.0%, 99.0% or 99.0% because we are typically interested in levels of loss that shouldn't be exceeded except rarely; e.g., 99.0% confident VaR means "we expect this loss to be exceeded only 1.0% of the time."

[@userpanx]

The horizontal scale: shouldn't the value at the center of the chart equal $0.0 ? Right now is $1.0.

[@bionicturtle]

I happened to define N(1,1) per the label σ = 1, µ = 1 rather than a standard normal, as mentioned at kzbin.info/www/bejne/o6fPZGWtlN5mbqs

[@riccardocaselli4048]

Shouldn't the distribution be 2.5% each side with 95% confidence level instead of 5% on the left side?

[@mdavis1992]

He says in the video that VAR is single tailed because it is only concerned with losses

[@Manch271]

At around 3:53, the Y-Axis (which represents probability) is showing data corresponding to 10% of probability, NOT 5% as claimed in the video, isn't it?

[@bionicturtle]

Hi Sriman, actually the red AREA under the curve is 5% per =NORM.S.INV(5.0%) = -1.644853627 or rounded -1.645 and at the same time =NORM.S.DIST(-1.645, FALSE) = 0.10313564 such that you are correct in one sense: the pdf curve hit the point (-1.645, 0.10313564) but this is the density function. The 0.103 is not a probability; this is a continuous function. I hope that helps.

[@FelixFrost]

Corret me if I am wrong: With the non-parametric ES we simply average the returns that are lower than our desired percentile (e.g the lower 5% of last year's returns) - ok. My question is, why do we use average? Isn't this bound to be affected by extremely rare but negative events? Why don't we use a weighted average? Or a median? Many thanks

[@bionicturtle]

Hi Frosty, short answer: yes, we can (for non-param/discrete distributions also). ES is a special case of the a spectral measure (which is a special case of a general risk measure) where the tail losses are equally weighted, however a spectral measure has "weakly increasing" (ie, not decreasing) weights so it's more natural state is increasing weights as losses are greater.

[@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?

[@fenghuawang7381]

Why P(L > VaR) VaR) = 1-c

[@MN-pr7bx]

My prof should actually be fired as I learn more with youtube than with him

[@RajKumar-ti4pi]

waste explanation.