Convexity and risk premium impacts on shape of term structure (FRM T5-08)

In this video, I'm going to try to illustrate all of the important ideas that are in Tuckman's Chapter 8: The Evolution of Short Rates and the Shape of the Term Structure. This chapter discusses the shape of the term structure and the key influences on the shape of the spot rate term structure. I'll start with pure expectations, where the term structure will reflect only expectations about the evolution of future spot rates, but that's going to be a naive theory. It might be convenient because we can say the term structure or spot race might be flat at 10%, but I'm not illustrating that here. I have non-flat curves, all of which are nonlinear because they incorporate the two influences on the shape of the term structure that is mathematically justified in Tuckman's Chapter eight. These are not easy ideas.
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[@excelisfun]

Thumbs up!!!!

[@rohangholam8270]

That cleared many of my doubts !! Amazing explanation !!

[@xploit811]

Thank you very helpful. Do you have any videos on calculating gamma exposure at different option strike prices?

[@rickyricardo75]

hi, do you have a video on building a Risk Parity Portfolio? i can't find it in your channel

[@jaylev85]

Not an instructor on here, just a peer: This isnt something that can usually be shown via a simple excel file (unless your developing with some automation and some VBA code, i.e. utilizing the Goal Seek function). Its an iterative process to align all the partial Beta's to be exactly proportional to partial expected returns. Lets say you have a portfolio with N securities, there is an ideal weight for each security where you are taking on more marginal risk for securities with higher expected returns. By doing so, the delta of your marginal sharpe ratio is = 1. (i.e. all marginal increases to the portfolio of 1 unit of reward will result in more than 1 unit of risk, all marginal decreases of 1 unit of risk will results in losing more than 1 unit of reward). Lets say your starting with a portfolio of N components each with W(i) arbitrary allocation, you can first approximate marginal VaR by calculating the Incremental VaR for each component which is similar to eff duration concept..basically each security you take the average of the Portfolio VaR for +/- 1bps change to that allocation. Then you need to figure out the w(i) of each security in the portfolio where the Expected Return (i) * Weight (i) / Margina VaR (i) are equal. Like I said...its iterative and time consuming. Using matrix math is the best approach to develop a vector of Cov(i,p), covariance of ith component relative to portfolio p.

[@thenivang]

Hi David...Thanks for sharing the video.

[@bionicturtle]

You're welcome! Thank you for watching :)

[@lenovolenovo6530]

thanks for the very detailed explaination

[@bionicturtle]

It's our pleasure!

[@staristo2355]

Are you doing ok? Haven't seen any new videos in a while. Great stuff! Surprised you don't have many more subscribers!

[@jaylev85]

Hello, I stumbled upon this channel when searching internet for some RM material. I am not familiar with GARP or FRM. Can someone comment and/or provide some clarity on what the value of this "FRM" certificate is? Anyone able to provide background in GARP beyond the limited info from their website. I am a practicing Actuary doing enterprise risk mgmt analysis in the Life/Annuity sector and I am very interested to find out more about this organization and the global recognition of this certificate. All the material discussed in this channel are the tools/foundation I use on a daily basis to perform my analysis. I am wondering why and/or if there is any collaboration between GARP and other Insurance/Risk Mgmt organizations that I am more familiar, such as SOA, CIA, RIMS, etc.

[@faustocant9381]

Thumbs up!!!! Could you please share the Excel, please?

[@nithyajayabalan7510]

I need to say something BIONIC is not a turtle