I hope you enjoy my latest non-stationary time series (TS) question set (T2.21.1. below). As with the 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. In that regard, I considered including a question that requires factoring a polynomial but I decided to include factoring as part of the 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 in 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!

1. P1.T2.21.1. Nonlinear time trends and unit roots https://www.bionicturtle.com/forum/threads/p1-t2-21-1-nonlinear-time-trends-and-unit-roots.23758/

2. P2.T9.21.1. Factor regression and style analysis https://www.bionicturtle.com/forum/threads/p2-t9-21-1-factor-regression-and-style-analysis.23762/

1. 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

2. Basic techniques that any FRM^® candidate should know (and keep 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

3. The calculation of sample skew (standardized third central moment) is similar to unbiased sample variance https://trtl.bz/3g1I4DZ

4. Surplus at risk (SaR) is one-tailed, as any XaR metric is always one-tailed https://trtl.bz/3fWXvgC

5. 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://www.bionicturtle.com/forum/threads/testability-of-tsm-term-structure-models.23763/

6. 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

1. On the derivation of the number of years needed to demonstrate alpha, T_years ≥ (1.96/IR)^2 https://trtl.bz/3t9YMEP

2. Implication of liquidity preference on term structure https://trtl.bz/3tedhaD

3. GARP’s FRA math is fine but an example would be better if the 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

4. Marsh Political Risk Map 2021 https://www.marsh.com/us/insights/research/political-risk-map-2021.html

5. 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

6. China Creates its Own Digital Currency (WSJ, paywall) https://trtl.bz/3tcm7pd

7. 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

8. 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/

9. 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/)

10. The 6 dimensions of data quality https://www.collibra.com/blog/the-6-dimensions-of-data-quality

11. Twenty Years Later: The Lasting Lessons of Enron https://corpgov.law.harvard.edu/2021/04/05/twenty-years-later-the-lasting-lessons-of-enron/

12. What is the state of ERM today? https://normanmarks.wordpress.com/2021/04/06/what-is-the-state-of-erm-today/

13. Understanding how ESG scores https://trtl.bz/3teFsq6

14. Making Monte Carlo Results More Relevant By Finding The Right Level Of Abstraction https://trtl.bz/2PUv1tg

15. 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 many solutions) including climate change (“we must put a price on carbon”); underserved communities (JPM “introduced The Path Forward in October 2020, committing $30 billion over the next five years 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”) and its inability to plan long-term; and the need to reform education (“Many companies have numerous jobs for which a ‘college degree is required,’ but this often turns out to be unnecessary and even harmful”). The unexpected section was his argument that his bank (well, banks) are suffering from enormous competitive threats. While he admits JPM has “huge economies of scale,” he doesn’t mention recent bank concentration dynamics. The top five banks have seen their share of assets balloon from under 30% to above 45% in the last twenty years (at the top of that list is JPM with $3.386 trillion in assets, according to their 10k).

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), you guessed it, is 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.”