Expected Shortfall & Conditional Value at Risk (CVaR) Explained

[@RyanOConnellCFA]

🎓 Tutor With Me: 1-On-1 Video Call Sessions Available ► Join me for personalized finance tutoring tailored to your goals: ryanoconnellfinance.com/finance-tutoring/ 💾 Download Free Excel File: ► Grab the file from this video here: ryanoconnellfinance.com/product/expected-shortfall-value-at-risk-calculator-in-excel/

[@SwiftGQ]

This was a clear and easy to follow explanation. Thanks Ryan.

[@RyanOConnellCFA]

My pleasure!

[@cherlynn99]

Fantastic content!! So glad I found you!

[@RyanOConnellCFA]

Thank you, I'm glad you found me as well!

[@ZhanningZhang]

Great job! Thanks for your explanation!!!

[@ryszardsikorski6355]

Great explanations, please keep it up. Greetings from Poland.

[@RyanOConnellCFA]

Will do and thank you! Greetings from Texas in the US

[@husseinarslan7173]

From my earliest years until I turned 18, I grappled with self-doubt and academic challenges. Despite my best efforts, subjects like math, English, and physics remained elusive to me throughout my school years. Yet, amidst these struggles, a greater trial awaited: from ages 10 to 17, I underwent the taxing ordeal of dialysis. However, within the depths of adversity, I nurtured a flicker of hope and ambition. At 17, a life-changing kidney transplant marked a turning point in my journey, infusing me with renewed determination and a sense of purpose. But the road to success was far from smooth. In the corridors of academia, I encountered the hurtful words of bullies and the isolating silence of indifference. Yet, I refused to be defined by my setbacks. Instead, I transformed them into stepping stones, each hurdle propelling me closer to my dreams. Today, as I reflect on the trials I've overcome, I am filled with gratitude for the resilience that sustained me. With unwavering support from loved ones, I navigated the darkest of nights, emerging stronger and more determined than ever. My journey, though marked by challenges, is a testament to the power of perseverance and the resilience of the human spirit. And as I set my sights on a career in finance, particularly in pursuing my dream of becoming a CFA, I do so with a heart full of hope and a steadfast belief in the boundless possibilities that lie ahead.

[@husseinarslan7173]

This is my stroy!

[@RyanOConnellCFA]

Hussein that was very poetic and it is cool to hear your story! I wish you the best of luck as you pursue the CFA. You will crush it after what you have been through

[@husseinarslan7173]

@@RyanOConnellCFA how can I talking with you? Do you have linkedlen?

[@husseinarslan7173]

@@RyanOConnellCFA I was failare in all topics at the school, From 3 years to 17 years old, in university the GPA not good.

[@RyanOConnellCFA]

@@husseinarslan7173 The CFA is a different animal than university! It is you against the world in the CFA since you do it all alone. Perhaps you will struggle in that environment as well. But try to see if you can adopt a mentality that will carry you through the CFA

[@nikhilvengaladas]

Goldmine for practical things 🫶🏻

[@RyanOConnellCFA]

Thank you for that Nikhil!

[@mgu5929]

u r a beast my man, thx for the content 🙏🏻

[@RyanOConnellCFA]

Appreciate it! Its my pleasure

[@pipekans]

I came for copper and found gold. Thank you for sharing your knowledge.

[@RyanOConnellCFA]

Really appreciate that Felipa! Thank you for your feedback

[@cristianjimenez3264]

Awesome videos like always

[@RyanOConnellCFA]

I appreciate that Cristian!

[@fazirana123]

very easy to follow . thanks for sharing your knowledge.

[@RyanOConnellCFA]

Glad it was helpful! It is my pleasure

[@danrleidiegues4800]

Really good explanation!

[@RyanOConnellCFA]

Thank you Danrlei!

[@aaronwamser3858]

great video! Very interesting and great explanation

[@RyanOConnellCFA]

Thank you!

[@nenopower]

Thanks for sharing, indeed a goldmine, keep it up, cheers.

[@RyanOConnellCFA]

Thank you for that! You can count on my consistent uploads 💪

[@pedromizutanif]

Great video man!

[@RyanOConnellCFA]

I appreciate it!

[@NIRMALKUMAR-ig6iu]

Great explanation sir!

[@RyanOConnellCFA]

Thank you!

[@balchandrapaudel8202]

you are best teacher

[@RyanOConnellCFA]

I really appreciate that, thank you

[@AvinandaMajumdar]

Wonderful explanation

[@RyanOConnellCFA]

Thank you!

[@kazijawadahmed6488]

Great video!!

[@RyanOConnellCFA]

I appreciate that Kazi!

[@wisemintapp]

This is fabulous!

[@RyanOConnellCFA]

Thank you Norman!

[@Emmanuel-wo4gs]

excellent ! thank you

[@RyanOConnellCFA]

You are welcome!

[@mohamedridaelwafi1935]

Please can you show us how to make the frequency distribution histogram.

[@cary8039]

Ryan: Using your spreadsheet SPY data, how would I calculate the expected shortfall for a one-week holding period rather than a one-day holding period? Is there a way to make your spreadsheet calculate the expected shortfall for SPY based on different holding periods input by the user?

[@RyanOConnellCFA]

Hey there. To calculate the expected shortfall for a one-week holding period, you can modify the spreadsheet to use weekly returns instead of daily returns. First, calculate the weekly returns by using the formula: (Price_t / Price_t-5) - 1, where Price_t is the closing price on day t, and Price_t-5 is the closing price 5 trading days prior. Then, sort the weekly returns from lowest to highest and determine the VaR levels for your desired confidence intervals based on the sorted data. Finally, calculate the expected shortfall by averaging all the weekly returns that fall below the respective VaR levels for each confidence interval. To make the spreadsheet more user-friendly and flexible, you can add an input cell where users can enter their desired holding period (e.g., 5 for one week, 21 for one month, etc.). Modify the return calculation formula to use the user-defined holding period instead of a fixed value, like this: (Price_t / Price_t-holdingPeriod) - 1. Ensure that the rest of the calculations (sorting, VaR levels, expected shortfall) reference the returns based on the user-defined holding period. This way, the spreadsheet will automatically calculate the expected shortfall for SPY based on the holding period specified by the user, making it a versatile tool for analyzing risk over various time frames.

[@chikhimtang1219]

Just to clarify, for expected shortfall, is the only way to do it via historical returns? Was just thinking about this because for VaR you were using parametric method but for expected shortfall you took the history of the returns

[@RyanOConnellCFA]

Hi @chikhimtang1219, great question! Expected Shortfall (ES) or Conditional Value at Risk (CVaR) can indeed be calculated using historical returns, as shown in the video, but that's not the only method. You can also use the parametric method or Monte Carlo simulations to estimate ES. In the video, I used historical returns to provide a clear, practical example by averaging the worst outcomes below the VaR threshold. Each method has its nuances, so choosing one depends on the specific requirements of your analysis and the data available.

[@GuillerMonteroC]

El promedio de los rendimientos menores o iguales al VaR con un nivel de confianza establecido

[@PandaPong]

Nice video!!!

[@PandaPong]

Credit risk made easy

[@RyanOConnellCFA]

Never thought I'd see you showing up in the comments Brian! Thank you

[@RyanOConnellCFA]

Also, its good to see you posting videos again. Keep it up!

[@GuillerMonteroC]

Nice job

[@cupcakedcs2617]

Thanks for the valuable video! One question for the z score, in case of the one sided Var then z score for 95% is 1.65 yes, but in case of the two sides it is 1.96. Could you advise me why we are taking 1 side z score? Even though we do have two tails in the graph. I want to get the concept which z score that I need to take with what intend and what situation

[@RyanOConnellCFA]

Your understanding is on the right track. Value at risk is a one-sided measure. The purpose of VaR is to estimate the maximum potential loss in value of a portfolio over a specified period for a given confidence level. Since we are concerned only with potential losses (left side tail) and not gains (right side tail), we focus on the left side of the distribution.

[@FenderAddict93]

@@RyanOConnellCFA So, is the assumption of "potential losses (left side tail) and not gains (right side tail)" is based on having long positions (or net long position of a portfolio) correct? Whereas on the flip side, short positions (or net short position of a portfolio) will assume potential losses (right side tail) and not gains (left side tail).

[@RyanOConnellCFA]

@@FenderAddict93 Whether you are short or long, you are only looking at the left side tail (the losses of your position). It doesnt matter if you are short or long, you are looking at losses. So first focus on calculating the returns of your position and then look at the losses on the left tail. This may require a sign change in your return calculation if you are short rather than long

[@FenderAddict93]

@@RyanOConnellCFA​​⁠ Thank you for the explanation. However, I still cannot wrap my head around it. In the video, you calculated CVaR based on the average Daily log returns beyond the VaR threshold. Using the 99% Confidence Interval example from the video, doesn’t it only mean that the S&P500 can potentially drop below the VaR with 1% probability and hence the expected drop in S&P500 price (or Daily log returns) is -4% if the 1% probability materialised? From my understanding, this means that the CVaR is calculating gains (left tail) by going short. Based on this, how do we go about calculating the loss (CVaR) for short positions on the right tail? Because changing the signs to find the ES of short positions would only produce an arbitrary number not based on the mean and stdev of the distribution.

[@hiteshsolanki282]

That normal distribution on the screen

[@hamidrezakamyabfar1829]

Thanks for sharing, It's my pleasure to find your channel. do you have or know any video to show the calculating VaR by ML models?

[@stefanomeola6666]

Can you elaborate on why the ES increases (ie. gets less negative) as the confidence level decreases (ie. goes from 99 to 90)? Is that why the "extreme" events gets diluted by the bigger amount of data points? Hope you will answer :D

[@-IndriClaireCanesa]

What is the difference between expected shortfall and marginal expected shortfall?