Asset Liability Modelling • Aim is to model assets and liabilities at the same time • Three key ingredients Return: Measurable Performance target o Time: Performance horizon o Risk: Confidence level • Parameters o Assets only • Asset returns o Liabilities only • Non-investment risks o Both with dynamic links • Exchange rates • Interest rates • Inflation • Process o Simulate many times to generate a distribution o Sensitive testing and hedging strategy o Stress testing different scenarios o Play around with Asset Allocation and its impact
Thanks a lot for this! I have CA1 tomorrow. Just doing my final revision and was still struggling to talk about asset-liability modelling confidently, this has really plugged that gap and brought the topic to life.
Thanks for the video MJ. I see in the CA1 notes the idea of adding margins to a parameter or risk being mentioned quite a lot. Could you please explain how this is effected in practice, and adds to the understanding of the model. Thank you. I love your channel man!
Adding margins is an old practice that creates a hidden reserve. Today actuaries are more likely to scrap the margins and be as realistic as possible because regulation requires them to value liabilities at market value and margins distort that figure.
Yes I agree with you, since the IRFS9 is coming to effect next year. The regulators may have to emphasize modelling risks more than using prudent basis.
This is off topic but do you feel the need for Actuaries to adopt Data Science and Machine Learning Techniques? I believe the SOA is going to require some course on it, and I am quite excited for it.
Sebastian Gobat yes actuaries love adopting new technology to help manage risk and make sense of financial uncertainty. even here in South Africa we are developing a new exam based on software and systems
Sebastian Gobat ....I think the hype around data science is really just that: hype!....What statisticians (and actuaries) do and have done,,since forever, is data science!...What we need to be careful of is falling into the new hype and also realizing that data mining, which has some uses can, in fact, will lead to false conclusions from the " patterns" in the data! ....My advice, instead; Put your statistician hat on and be skeptical!
My views on the topic "ALM Modeling and Balance Sheet Optimization" are presented on my online trainning. It may be helpfull for the discussion. Best regards! financial-risk-academy.teachable.com/p/balance-sheet-optimization-under-operational-and-regulatory-constraints
Asset Liability Modelling
• Aim is to model assets and liabilities at the same time
• Three key ingredients
Return: Measurable Performance target
o Time: Performance horizon
o Risk: Confidence level
• Parameters
o Assets only
• Asset returns
o Liabilities only
• Non-investment risks
o Both with dynamic links
• Exchange rates
• Interest rates
• Inflation
• Process
o Simulate many times to generate a distribution
o Sensitive testing and hedging strategy
o Stress testing different scenarios
o Play around with Asset Allocation and its impact
Thanks a lot for this! I have CA1 tomorrow. Just doing my final revision and was still struggling to talk about asset-liability modelling confidently, this has really plugged that gap and brought the topic to life.
Hi, thanks for the video... Could you share some literature?? I need to do an ALM and I don't know how to start. Cheers!!
Thanks for the video MJ. I see in the CA1 notes the idea of adding margins to a parameter or risk being mentioned quite a lot. Could you please explain how this is effected in practice, and adds to the understanding of the model. Thank you. I love your channel man!
Adding margins is an old practice that creates a hidden reserve. Today actuaries are more likely to scrap the margins and be as realistic as possible because regulation requires them to value liabilities at market value and margins distort that figure.
Yes I agree with you, since the IRFS9 is coming to effect next year. The regulators may have to emphasize modelling risks more than using prudent basis.
Hi,MJ,
have you cleared st5? i failed in the previous attempt but not able to exactly pin point my weaknesses.( logically everything can be improved).
This is off topic but do you feel the need for Actuaries to adopt Data Science and Machine Learning Techniques? I believe the SOA is going to require some course on it, and I am quite excited for it.
Sebastian Gobat yes actuaries love adopting new technology to help manage risk and make sense of financial uncertainty. even here in South Africa we are developing a new exam based on software and systems
Sebastian Gobat ....I think the hype around data science is really just that: hype!....What statisticians (and actuaries) do and have done,,since forever, is data science!...What we need to be careful of is falling into the new hype and also realizing that data mining, which has some uses can, in fact, will lead to false conclusions from the " patterns" in the data! ....My advice, instead; Put your statistician hat on and be skeptical!
Nice intro.... But you didn't make follow up videos?
Not everything in life is free or online lol. Where’s your content?
My views on the topic "ALM Modeling and Balance Sheet Optimization" are presented on my online trainning. It may be helpfull for the discussion. Best regards!
financial-risk-academy.teachable.com/p/balance-sheet-optimization-under-operational-and-regulatory-constraints
Thanks for the vid! Looks like you had some Doge?:)