I hope you enjoy my latest non-stationary time series (TS) question set (T2.21.1. below). As with previous TS Q&A, I provided code snippets to add to the realism. For example, you can see how easy it is to determine the (unit root) polynomial roots with a function call. In that regard, I considered including a question that requires factoring a polynomial but I decided to include factoring as part of assumptions setup (T2.21.1.2) so that the question itself teaches. (Many of my questions convey an additional concept in the setup; for me, an ideal question teaches three times: in the setup, in the solution, and in the false choices). Some candidates will be rusty (or even new) to polynomial factoring, and here the unit root factoring is just a means to end. If you aren't comfortable with R/python, I'd also recommend https://www.wolframalpha.com/ for step-by-step solutions to math problems. For my musing this week, I share notes I took while reading Jamie Dimon's latest letter. Have a good study week!
New Practice Questions
Many are praising Jamie Dimon's 2020 CEO letter (link above). I am struck by its ambition, he somewhat fearlessly itemizes public policy problems (and no shortage of his solutions) including climate change ("we must put a price on carbon"); underserved communities (their recently introduced Path Forward commits $30 billion "to address the key drivers of the racial wealth divide"); governmental sclerosis ("there are 17,000 registered lobbyist contracts for special interest groups in Washington"); structural hurdles to long-term planning for global problems; and much space to the need to reform education at several levels ("Many companies have numerous jobs for which a 'college degree is required,' but this often turns out to be unnecessary and even harmful"). Add another data point to support the secular decline of the traditional college degree.
The unexpected section was his argument that banks, including big banks, are suffering the strains of enormous competitive threats. While he admits JPM has "huge economies of scale," he does not address the recent bank concentration dynamics. After years of the too-big-to-fail (TBTF) theme, some might not be sympathetic. The top five banks have seen their share of assets balloon from under 30% to >45% in the last twenty years (at the top of that list is JPM with $3.386 trillion in assets, according to their 10k). They sure seem like they have a heathy moat?!
Other observations and opinions:
New Practice Questions
- P1.T2.21.1. Nonlinear time trends and unit roots https://forum.bionicturtle.com/threads/p1-t2-21-1-nonlinear-time-trends-and-unit-roots.23758/
- P2.T9.21.1. Factor regression and style analysis https://forum.bionicturtle.com/threads/p2-t9-21-1-factor-regression-and-style-analysis.23762/
- Longtime member and risk expert Mani (aka, @QuantMan2318) wrote about Archegos and itemizes many risks https://trtl.bz/3a3078Y. Read his helpful LinkedIn article here http://trtl.bz/archegos-mani. Last week's WIFE curated selected links on Archegos. Since then, BusinessWeek published, Bill Hwang Had $20 Billion, Then Lost It All in Two Days https://trtl.bz/3tpdesR
- Basic techniques that any FRM candidate should know (and keeping coming up): The two basic ways to calculate a daily return https://trtl.bz/2Qk7Nwj; That beta is correlation scaled by cross-volatility, β(P,M) = COV(P,M)/σ^2(M) = ρ(P,M) * σ(P)/σ(M) https://trtl.bz/3tbKZO6; and How to construct a probability matrix; eg., https://trtl.bz/3safUZF
- The calculation of sample skew (standardized third central moment) is similar to unbiased sample variance https://trtl.bz/3g1I4DZ
- Surplus at risk (SaR) is one-tailed, as any XaR metric is always one-tailed https://trtl.bz/3fWXvgC
- GARP can't ask you to create random 'dw' in the simulation of rates under term structure models, but you should know what 'dw' represents https://forum.bionicturtle.com/threads/testability-of-tsm-term-structure-models.23763/
- Observed errors: GARP errors https://trtl.bz/2PSOGtq and https://trtl.bz/3a5GZap. Stulz gets the counterparty formula a bit wrong and apparently it's never been corrected https://trtl.bz/3a2RXgQ
- Implication of liquidity preference on term structure https://trtl.bz/3tedhaD
- On the derivation of number of years needed to demonstrate alpha, T_years ≥ (1.96/IR)^2 https://trtl.bz/3t9YMEP
- GARP's FRA math is fine but example would be better if language were more precise. The FRA buyer (seller) borrows (lends) at the fixed rate and the typical FRA settles in advance (not in arrears unless explicitly specified) which implies discounting the payoff amount over the contract period back to the settlement, as in F(T_settlement, T_payoff); e.g., F(1.0, 1.25) https://trtl.bz/3s8fpPR
- JPMorgan Chase CEO letter https://reports.jpmorganchase.com/investor-relations/2020/ar-ceo-letters.htm
- National Intelligence Council Releases Global Trends Report https://trtl.bz/3sa4PIa
- WEF's Global Risks Report 2021 https://www.weforum.org/reports/the-global-risks-report-2021 (belatedly sharing)
- Marsh Political Risk Map 2021 https://www.marsh.com/us/insights/research/political-risk-map-2021.html
- China Creates its Own Digital Currency (WSJ, paywall) https://trtl.bz/3tcm7pd
- BIS: Supervising cryptoassets for anti-money laundering https://www.bis.org/fsi/publ/insights31.htm; and Redefining insurance supervision for the new normal https://www.bis.org/fsi/fsibriefs13.htm
- GARP's Risk Intelligence For Ex-Regulators, the Door Revolves Toward Tech https://trtl.bz/3dYkUvm; The Skewed Generalized T Distribution: A Swiss Army Knife for Tail Risk https://trtl.bz/2RtkSEn
- Zero Emissions Vehicles: Making Sense of the Transition with SASB Standards https://blogs.cfainstitute.org/inve...-sense-of-the-transition-with-sasb-standards/ Did you know there is a Sustainability Accounting Standards Board (SASB)? They even have a credential that recently updated its FSA Level I (see https://www.sasb.org/blog/a-closer-look-the-fsa-level-i-curriculum-update/). See the Fundamentals of Sustainability Accounting (FSA) Credential at https://fsa.sasb.org/
- ESG 2.0: Measuring & Managing Investor Risks Beyond the Enterprise-level https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3820316 from The Predistribution Initiative (https://predistributioninitiative.org/)
- The 6 dimensions of data quality https://www.collibra.com/blog/the-6-dimensions-of-data-quality
- Twenty Years Later: The Lasting Lessons of Enron https://corpgov.law.harvard.edu/2021/04/05/twenty-years-later-the-lasting-lessons-of-enron/
- What is the state of ERM today? https://normanmarks.wordpress.com/2021/04/06/what-is-the-state-of-erm-today/
- Understanding how ESG scores https://trtl.bz/3teFsq6
- Making Monte Carlo Results More Relevant By Finding The Right Level Of Abstraction https://trtl.bz/2PUv1tg
- Book Review: Machine Learning for Asset Managers https://blogs.cfainstitute.org/investor/2021/04/08/book-review-machine-learning-for-asset-managers/
Many are praising Jamie Dimon's 2020 CEO letter (link above). I am struck by its ambition, he somewhat fearlessly itemizes public policy problems (and no shortage of his solutions) including climate change ("we must put a price on carbon"); underserved communities (their recently introduced Path Forward commits $30 billion "to address the key drivers of the racial wealth divide"); governmental sclerosis ("there are 17,000 registered lobbyist contracts for special interest groups in Washington"); structural hurdles to long-term planning for global problems; and much space to the need to reform education at several levels ("Many companies have numerous jobs for which a 'college degree is required,' but this often turns out to be unnecessary and even harmful"). Add another data point to support the secular decline of the traditional college degree.
The unexpected section was his argument that banks, including big banks, are suffering the strains of enormous competitive threats. While he admits JPM has "huge economies of scale," he does not address the recent bank concentration dynamics. After years of the too-big-to-fail (TBTF) theme, some might not be sympathetic. The top five banks have seen their share of assets balloon from under 30% to >45% in the last twenty years (at the top of that list is JPM with $3.386 trillion in assets, according to their 10k). They sure seem like they have a heathy moat?!
Other observations and opinions:
- Section I updates the 20-year old argument that shareholder capitalism is not in opposition to stakeholder capitalism conditional on long-term thinking. While many will disagree, his argument can be anticipated: JPM isn't BigTech with their antitrust concerns on the horizon, but still it's the biggest bank. Before the pandemic, capitalism's big corporations were already on the rhetorical defensive (e.g., inequality). Everyone keeps saying the pandemic has accelerated ("pulled forward") so many trends. Given the pandemic's winners included the biggest companies (and their executives), the most natural reaction would seem to be the argument that a corporation has responsibilities beyond shareholders.
- Section III (Banks' enormous competitive threats, from virtually every angle) is intriguing as he quite acknowledges FinTech and BigTech competition. "Banks already compete against a large and powerful shadow banking system. And they are facing extensive competition from Silicon Valley, both in the form of fintechs and Big Tech companies (Amazon, Apple, Facebook, Google and now Walmart)." He totally commits to the AI/ML and the cloud: "We already extensively use AI, quite successfully, in fraud and risk, marketing, prospecting, idea generation, operations, trading and in other areas – to great effect, but we are still at the beginning of this journey. And we are training our people in machine learning – there simply is no speed fast enough."
- The first item on JPM's list of specific issues (Section IV) is, you guessed it, cyber risk ("we spend more than $600 million a year on cybersecurity")
- Section V (Covid-19 and the economy) is stellar macroeconomic commentary. He explains why the liquidity coverage ratio (LCR) has effectively replaced bank reserve requirements, succinctly shares the pros/cons of quantitative easing (QE) in plain English, and challenges the spaghetti-like complexity of the regulatory system ("It is obvious, however, that we are bogged down. Ten years after the financial crisis, we still have not put the finishing touches on Basel III (aka Basel IV). And it’s not clear when it’s finished if it will be an international level playing field.").
- On average, he has concluded that remote (virtual) work has far too many problems and ultimately expects only 10% of employees to work remotely full-time.
- Section VI includes fully 15 public policy recommendations, including several related to job creation. And a sober analysis of China: "There is no question that the relationship with (and intense competition between) the United States and China will be the most critical relationship for the next 100 years so it is important to deeply understand all of China’s strengths and weaknesses ... China's system [unlike Western democracies] allows for consistent leadership and consistent execution of policies and regulations over the long term."
Last edited:
