Why is the bank Capital One’s 2015 NIM such an outlier relative to Bank Holding Companies (BHCs) of comparable and larger asset base? Capital One NIM is double the average bank NIM in 2016, Why is that? Press coverage over that past couple years attribute COF outperformance to going long risky credits and managing the write-downs. Maybe they are right and COF is just good at making and managing loans for a decade. On the other hand, maybe COF is running a very different quantitative model than its competitors. COF has 300+ BN of assets in 2016 and is making 300 more bps per year on their assets than the average competitor BHC makes on their assets. Banks’ NIMs are at 30 year lows but not at COF. Maybe the competitors can learn from COF. We discuss some of the quantitative possibilities.
- Sort out references
- cover assess QRM, Bancware, Polymaths, Oracle Financial …
- clean up flow start to finish
- Tighten up abstract and summary.
- Find some COF folks to comment
Why is the bank Capital One’s 2015 NIM such an outlier relative to Bank Holding Companies (BHCs) of comparable and larger asset base? Capital One NIM is double the average bank NIM in 2016, Why is that? Press coverage over that past couple years attribute COF outperformance to going long risky credits and managing the write-downs. Maybe they are right and COF is just good at making and managing loans for a decade. On the other hand, maybe COF is running a very different quantitative model than its competitors. COF has 300+ BN of assets in 2016 and is making 300 more bps per year on their assets than the average competitor BHC makes on their assets. Banks NIM are at 30 year lows but not at COF. Maybe the competitors can learn from COF. We discuss some of the quantitative possibilities.
Capital One’s NIM
Bank NIM is down and Interest rates are expected to stay down (see Rieder). St. Louis Federal Reserve figures show that the current average BHC NIM is at a 30 year low.
Capital One’s NIM is not at a 30 year low. In fact they buy assets on the market from ING, GE, Chevy Chase etc. and still maintain their historic NIM levels. COF assets grew 8x from 2004 to 2015 yet the NIM level stayed in a narrow range, occasionally busting out top side. How do you do that? We will review the evidence that the correct figurative question is not “What’s in their Wallet” but “How do they choose what’s in their Wallet?” We will make the case that COF is running some sort of Dynamic Stochastic Optimization for implementing their capital allocation plan. COF’s Wallet is filled with securities through an LP/NLP optimization process and possibly some Dynamic Programming feedback control process. That is how they make 300 bps more than mostly everyone else in a punishingly low interest rate environment. Moreover, other than the competition for assets this more of an internal efficiency game than a zero sum game of someone has to lose for there to be a winner. COF has a free hand in this game at moment because no one else knows how to play.
Capital One Investor Relations, here. I think if we poke around here we can get an estimate of where they are v.v. Net Interest Margin Optimization.
Capgenimi, Doing Business The Digital Way:How Capital One Fundamentally Disrupted the Financial Services Industry. here.
Here’s a quick exercise. What links these different out ts: online bank ING Direct; Bankons, a mobile startup that creates geo-located offers; Bundle, a Citibank spin-off that specializes in analysis of spend data; Sail, a mobile point-of-sale card-swiping device1? Here’s a hint – all of these companies were acquired to bolster the digital services of a leading nancial services organization. We are talking about Capital One. Since its founding as a credit card company in 1988, Capital One Financial Corp. has grown into a diversi ed bank with more than 65 million customer accounts worldwide. It is not hard to see why Capital One is investing heavily in digital technologies. It conducts over 80,000 big data experiments a year2. Currently, 75% of customer interactions with Capital One are digital, and this number is only expected to grow3. In Q4 2013, Capital One was one of the most visited websites, with 40 million unique online visitors4.
Donal Byrne, Tabb Forum, Rethinking Speed in Financial Markets, Part 4: The Need for Machine-Time Data, here. He said/wrote microseconds, … Funny. And the Corvil guys are reasonable for the most part in my experience. It is like Dr. Evil asking for 1 million dollars ransom for not destroying the world in 2000 something. I think the clock frequency is written in the computer box, no? You would think calling it a microprocessor CLOCK would be a hint, but I guess you can never be sure.
A machine world is different. Machines act much faster than humans. Their idea of real time is much closer to a microsecond. Roughly a million times faster. I refer to this as “machine real time” or “machine time” for short. We define machine time as the time within which a machine can act or make a decision. We therefore need a machine-time watch for a machine-time world.
Matt Levine, Bloomberg, Consumer Banking and Orange Juice, here. Find these guys. Maybe it is Strats through Adam Korn for Goldman? MS no idea at this point.
For all the talk about bringing back the Glass-Steagall Act that used to separate investment banking from consumer and commercial banking, one of the big stories in modern U.S. financial regulation is the push for big investment banks to build up their consumer-banking business. That’s what Goldman Sachs and Morgan Stanley are doing:
Both firms have turned to more basic banking businesses, betting that the cachet of their brand names can overcome relative lack of experience in dealing with the deposits and loans of middle-class Americans.
The moves have surprised many and suggest capital-markets businesses have reached a turning point. “I would never have thought years ago that they would ever be doing this,” says Richard Kovacevich, Wells Fargo & Co.’s former chairman and chief executive. But as regulation and muted client activity hammers trading revenue, “you either shrink, or you try to replace” lost profits.
These are commercial decisions, but they are also influenced by regulation. Regulators view retail deposits as a more stable source of funding than wholesale funding. New capital regulation, and the Volcker Rule, have made it less appealing for banks to buy bonds, and more appealing for them to make consumer loans. The general bank-regulatory apparatus has tilted, since the crisis, to favor traditional banking over sales and trading.
Daniel Nenni, Intel 7nm due 2022, Semiwiki, here.
Vincent Natalie, HPC Wire, Why 2016 Is the Most Important Year in HPC in Over Two Decades, here.
Intel and NVIDIA are battling each other for the massive number crunching and data moving work that is the hallmark of HPC. It’s the kind of work that includes modeling and simulation tasks of everything from airflow over automobiles and aircraft, climate and weather modeling, seismic processing, reservoir simulation and much more. This year that battle is being played out by the matchup between Knights Landing and Pascal. An enormous amount is at stake and the HPC hardware market only scratches the surface. The real cost is in the millions of person-hours that will be invested writing and porting massive, complicated technical codes to one of these two platforms. It’s a huge investment for companies and developers and it will set the HPC course for the next decade. Will Intel’s Knights Landing begin to put the pressure on NVIDIA’s Pascal or will Pascal become Intel’s Knight’s Mare. This year will tell.
Ashram Eassa, Fool, Intel Corporation May Have Pushed 7-Nanometer Tech to 2021, here.
I suspect what’s going on here is that Intel had originally planned to release products manufactured on its 7-nanometer technology in the 2020 time frame, but for whatever reason the company has delayed that until 2022.
If we consider what Intel has publicly said about its manufacturing plans, this actually makes a lot of sense. Intel is expected to go into manufacturing on its first 10-nanometer products during the second half of 2017. For simplicity, let’s assume that volume availability of 10-nanometer product doesn’t happen until January 2018.
Intel has said that it plans three waves of 10-nanometer technology: 10-nanometer, 10-nanometer+, and 10-nanometer++. If Intel keeps to an annual product launch cadence, then we should see volume availability of the first 10-nanometer+ products in January 2019, and the first 10-nanometer++ products in January 2020.
Based on this cadence, which is admittedly probably on the pessimistic side, the first products based on 7-nanometer would be expected to launch in January 2021 — a bit earlier than the 2022 time frame given in the job listing.
What Intel could be planning, then, is to introduce substantially enhanced chip designs a year after the first 7-nanometer products, which could very well be modest updates to the final 10-nanometer++ products. In fact, Intel’s product cadence is now referred to as “Process, Architecture, Optimization,” so fundamentally new architecture products on 7-nanometer could, indeed, arrive in January 2022.
John R. Birge, Northwestern, talk, Stochastic Optimization in Asser-Liability Management, here.