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Oil Tanker on Fire
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Fire, huge fire. The Corinthos disaster of January 30, 1975, was the biggest fire in Philadelphia history, and one hopes the biggest forevermore. Its immensity has possibly lessened attention for some associated issues which are nevertheless quite important, too. Like the issue of punitive damages in a lawsuit, or the need to balance environmental damage with a national need for energy independence. And the changing ways that law firms charge their clients. We hope the relatives of the victims will not be offended if the tragedy is used to illustrate these other important issues.
On that cold winter day, two big tanker ships were tied up alongside the opposite banks of the Delaware River at Marcus Hook. The Corinthos was a 754-foot tanker with a capacity of 400,000 barrels of crude oil, tied up on the Pennsylvania side at the British Petroleum dock with perhaps 300,000 barrels still in its tanks at the time of the disaster. At the same time, the 660-foot tanker Edgar M. Queen
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Edgar M. Queeny
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with roughly 250,000 barrels of specialty chemicals in its hold, let go its moorings to the Monsanto Chemical dock directly across the river in New Jersey, intending to turn around and head upstream to discharge the rest of its cargo at the Mantua Creek Terminal near Paulsboro. Curiously, a tanker is more likely to explode when it is half empty because there is more opportunity for mixing oxygen with the combustible liquid sloshing around. A tug stood by to assist the turn, but the master of the Queeny felt there was ample room to make the turn under her own power. With no one paying particular attention to this routine maneuver, the Queeny seemed (to only casual observers) to head directly across the river, ramming straight into the side of the Corinthos. Actually, the Queeny had engaged in a number of backing and filling maneuvers, and the sailors aboard were appalled that it seemed to lack enough backing power to stop its headlong lunge at the Corinthos. There was an almost immediate explosion on the Corinthos, and luckily the Queeny broke free with only its bow badly damaged. Otherwise, the fire might have been twice as large as it proved to be with only the Corinthos burning. The explosion and fire killed twenty-five sailors and dockworkers, burned for days, devastated the neighborhood and occupied the efforts of three dozen fire companies. A graphic account of the fire and fire fighting was written by none other than Curt Weldon who was later to become Congressman from the district, but was then a volunteer fireman active in the Corinthos tragedy.
There were surprising water shortages in this fire on the river because the falling tides would take the water's edge too far away from the suction devices for the fire hoses on the shore. The tide would also rise above a gash in the side of the burning ship, floating water in and then oil up to the point where it would flow out of the ship onto the surface of the river. Oil floated two miles upstream from the burning ship and ignited a U.S. Navy destroyer which was tied up at that point. Observers in airplanes estimated the oil spill was eventually fifty miles long. All of these factors played a role in the decision whether to try to put the fire out at the dock or let it burn out; experts continue to argue which would have been better. There were always dangers the burning ship would break loose and float in unexpected directions, that the oil slick would ignite for its full length, and that storage tanks on shore would be ignited. The initial explosion had blown huge pieces of iron half a mile away, and the ground near the ship was littered with charred, dismembered pieces of flesh from the victims.
, Of course, there was a big lawsuit. When a ship is tied up at a dock it certainly feels aggrieved when another ship crosses a river and rams it. The time-honored principle of admiralty law holds that the owner of an offending ship is not liable for damages greater than the salvage value of its own hulk, which in this case might have been about $3 million. The underlying assumption is that the owner has no way of knowing what is going on thousands of miles away, no control over it, no power to respond in a useful way. Enter Richard Palmer, counsel for the Corinthos. Palmer was aware that the National Transportation Safety Board collects information about ship maintenance inspections in order to share useful information for the benefit of everyone. His inquiry revealed that the inspections of the Queeny for four years before the crash had repeatedly demonstrated that the stern engine had a damaged turbine, and was only able to drive the ship at 50% of its rated power. Why this turbine had not been repaired was now irrelevant; the owners of the ship did have relevant information and had failed to act in a timely safe fashion. The limitation of liability to the salvage value of the hulk now no longer applied if the negligence was judged relevant. The defendants, the owners of the Queeny, decided to settle. While the size of the settlement is a secret of the court, it is fair to guess that it approached the full value of the suit, which was $11 million. Mr. Palmer, by using his experience to surmise that maintenance records might be available at the Transportation Agency, and recognizing that the awareness of the owner might switch the basis for the compensation award from hulk value (of the defendant's ship) to the extent of the damage (to the plaintiff's ship), probably tripled the damage settlement.
Reflections on the extraordinary benefit to the client from a comparatively short period of work by the lawyer leads to a discussion about the proper basis for lawyers fees. Senior lawyers feel that the computer has revolutionized lawyer billing practices, and not for the better. Because it is now possible to produce itemized billing which summarizes conversations of less than a minute in duration, services for the settlement of estates can be many pages long, mostly for rather routine business. Matrimonial lawyers are entitled to charge for hours of listening to inconsequential recriminations; lawyers can bill for hours of time spent reading documents into a recording machine, or sitting wordlessly at depositions. Since the time expended can now be flawlessly measured and recorded on computers, there is little room for a client to remonstrate about their fairness. Discomfort about this system underlies much sympathy for billing for contingent fees, where the lawyer is gambling all of his expenses and effort against a generous proportion of the award if he wins the case, nothing at all if he loses. This latter system, customary in slip and fall cases and justified as permitting the poor client to have proper representation, undoubtedly promotes questionable class action suits and often leads to accepting personal liability suits which should be rejected for lack of merit. The thinking underlying personal injury firms is widely said to be: most insurance companies will settle for modest awards in cases without merit because the defense costs would be no less than that amount, and occasionally a personal liability case gets lucky and extracts a huge award.
Listen to one old-time lawyer describe how legal billing used to be. After the case was over, the lawyer and the client sat down to a discussion of what was involved in the legal work, and what it accomplished for the client. A winning case has more evident value than a losing one, provided the lawyer can effectively describe the professional skills that helped bring it about. The whole discussion is aimed at having both parties leave the discussion satisfied. To the extent that both parties actually are satisfied with the value of the services, the esteem and reputation of the legal profession are enhanced. And the lawyer is a happy and contented member of a grateful community. If he can occasionally claim a staggering fee for a brief but brilliant performance, as in the case of the explosive fire on the Corinthos -- well, more power to him.
It does not take much familiarity with oil refineries to make you realize that cargoes of crude oil are a very dangerous business. We are accustomed to hearing jeers at those who protest, "Not in my backyard", and we deplore those who would jeopardize our national security to protect a few fish and trees in the neighborhood of potential oil spills. Since we do have to import oil and we do therefore have to jeopardize a few selected neighborhoods to accomplish this vital service, the opponents are sadly destined to lose their protests. But that doesn't mean their concerns are trivial. The shipping and refining of oil are dangerous. We just have to live with it and be ready to pay for its associated costs.
The traditional architecture of health insurance is called "Pay as you go", which like many political titles, means the opposite of what it says. When Lyndon Johnson started Medicare in 1965, he was faced with two simultaneous decisions: medical bills were coming in to be paid, and payroll deductions rolled in, intended to pay out for someone else's medical bills in the future. It seemed a simple thing to use the money on hand to pay the bills. Money was money, and it didn't care what it was for. For a while, more money came in than went out, so there was a surplus Medicare fund, but that is now gone. Almost entirely, today's' bills are paid with money intended to be spent years from now. To be brief, cash flow is used to pay current expenses, disregarding future obligations. That's very close to a Ponzi scheme, with the difference that the federal government can print reserve currency and, therefore, can borrow almost unlimited amounts from foreign countries. We quickly passed the point where we could invest the surplus money and got into the habit of borrowing it.
Pay As You Go is unable to generate income from premium reserves.
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Why Not Pay/Go?
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To restate: In addition to not earning income, we make interest payments, for a double cost. If we could find a way to get out of this blunder, we could greatly reduce overall Medicare costs. Meanwhile, most people are unaware that Medicare costs are 50% subsidized by taxes and borrowing during this process, and think it must be very well run, indeed. However, the rules of accounting were conveniently changed, so that when one arm of the government loans money to another department, it isn't called a liability, it's called an asset. After all, if you are on both sides of the transaction, it is both things, and it is also neither thing. You can find it in the CMS Medicare annual report on your home computer, listed as "Transfers from the general fund", and sure enough, it's 50% of the total cost. While we are on the subject, let us digress for a moment and say that payroll deductions from working people are 25% of the cost, and the Medicare beneficiaries themselves contribute only 25%, as premiums. Since everybody likes to get a dollar for 25 cents, the public is so approving of the balance sheet that there is a major movement to extend it to everybody, flying the flag of "single payer".
Medicare is 50% subsidized, so by implication, a Single-Payer system expects 50% subsidy, too.
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Why Not Single Payer?
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However, for present purposes this little lesson in accounting is offered to explain a much more significant feature: it might be possible to increase the revenue of Medicare by re-directing the funds' flow. The insider joke is that by adding income, the accounting system would then display a loss, and the opposition party could make a big fuss about it.
If we propose to adopt the whole-life model for Health Savings Accounts, then why don't we just add it as a new product for the companies who are already in the whole-life business? It's a good question, and most of the answer is I don't happen to own an insurance company. Somebody has to invest a pile of money to own one. You almost never hear of corporate pirates attempting a take-over, and many insurance companies make their profits on subscribers who drop their policies, although that's mostly term insurance. Come to think of it, these are mostly 19th Century organizations who sort of had the good luck to encounter windfall profits when subscribers lived longer than was necessary to break even, and then even kept living on some more. It isn't exactly the background of people who start new businesses with new ideas. Nevertheless, they do sell their products to young people, invest the premiums for many years, and eventually pay their bills to old folks, on time and cheerfully. And there would seem to be plenty of incentive. Aggregate retirement income fifty years from now will probably be many times as large as the present face value of insurance, and probably include a larger proportion of the population. They already have actuaries on their payroll who could do the math, and who yearn for the day a new product would give them a shot at being CEO. Like me, they have already had a look at the C-suite offices, and like me, compare them favorably with the Temple of Karmac.
Who will run L-HSA, once it is legal?
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However, I don't know any of them personally, so the assumption must be made that L-HSA will grow out of companies that package C-HSA at present and sort of have a term insurance point of view. Elements of it have been around for almost two centuries, but even the life insurance industry might become dubious to hear whole-life coverage of health insurance presented as an investment. As the level of income taxation rises, tax-free internal transfers assume new value, but resistance to higher taxes will grow. Extending life expectancy gives compound interest much longer to grow, it thus transforms what it can do. In addition, if you desire intergenerational cost shifting for health costs, you probably must incorporate some form of insurance as a pooled transfer vehicle. This combination also enables funds to shift within the account to a later time in life. It's a more attractive individual incentive for savings, than threateningly proposing your generation must support mine.
As a final feature, Catastrophic high-deductible is here added, providing stop-loss protection. Call it re-insurance if you prefer. It's single-purpose coverage, based on the idea that the higher the deductible, the lower the premium. So it follows that the longer you are a customer, the more catastrophic insurance you can afford. Cost saving runs through all multi-year ideas, but lifetime coverage is a cost-saving whopper, because of the way Aristotle discovered compound interest turns up at the far end. (By the way, that's why I suspect we have rules against perpetuities of inheritance.) It transforms Health Savings Accounts into a transfer vehicle for funds, from one end of life to the other, and must add debit-card health insurance for current expenses. Forward from the surplus of the present. And backward from the compound interest of the future. The last-year-of life could be chosen as an example because the last year comes to 100% of us, and is usually the most expensive year in healthcare, not greatly different from the face value of life insurance. But needs differ, and a ton of money sounds pretty good at any age. A Health Savings Account can also be used as a substitute for day to day health insurance. Another synonym might be Whole-life Health Insurance, although multi-year health insurance is probably more precise. The idea behind presenting this concept piecemeal is to provide flexibility for both overfunding and underfunding, since the time periods for coverage can be so long (and the transitions so variable) that both eventualities would occur simultaneously to different individuals.
The simple idea is to generate compound investment income -- not presently being collected -- on currently unconsumed health insurance premiums. And eventually, to apply the profit to reducing the same individual's future premiums. Even I was then startled, to realize how much money it could save. It's a scaled-up version of what whole-life life insurance does for death benefits. Since lessened premiums generate greater investment income, the math is complicated even when the theory is simple, but every whole-life insurer has experience with smoothing it out. For example, if someone had deposited $20 in an HSA total market Index fund ninety years ago, it would now be worth $10,000, roughly the average present healthcare cost of the last year of life. Neither HSAs nor Index funds existed ninety years ago, and of course, we cannot predict medical costs ninety years from now. This is only an example of the power of the concept, which we can be pretty certain would save a great deal of money, but skirts the guarantees about just how much.
There's one other advantage to using HSAs within the whole-life insurance model. It has always bothered me that life insurance tends to gravitate toward bond investments, matching fixed-income revenue with fixed-outgo expenses. But insurance companies largely support the bond market, which is many times as large as the stock market. In effect, their situation encourages them to increase the amount of leverage in the economic system, thereby increasing its volatility, and its tendency to experience black swans.
Furthermore, the insurance industry has accumulated a great many special tax preferences, based on the notion its social value is a good one. Placing life insurance in competition with non-insurance providers of the same services would justify extending the tax preferences to the others as well. The resulting competition would invigorate what has become a pretty stolid plodding citizen, with somewhat unique power over state legislatures. State legislatures, in turn, would benefit from increased competitive points of view among their lobbyists.
People would be expected to join at different ages, so the ones who join at birth in a given year have accumulated funds which would be matched by late-comers. In our example, if a person waited until age twenty (and most people would wait at least that long), he would need to deposit $78 -- not $20 -- to reach $10,000 at age 90. It's still within the means of almost anyone, but the train is pulling out of the station. Participation is voluntary, but no one saves any money by delaying and learns a bitter lesson when he tries. Notice, however, no one pays extra for a pre-existing condition, either; it costs more to wait, but it does not cost more to get sick while you wait. If the government wants to pay a subsidy to someone, let the government do it. But nothing about the whole-life retirement system compels increased premiums for bad health or justifies lower premiums for good health.
Whole-life health insurance takes advantage of the quirk that the biggest medical costs arise as people get older, and similarly, health insurance premiums are collected early in life when there is considerably less spending on health. The essence of this system is to reform the "pay as you go" flaw present in almost all health insurance. Like most Ponzi schemes, the new joiners do not pay for themselves, they pay for the costs of still-earlier subscribers, a system that will only work if the population grows steadily and/or prices rise. When the baby boomers bulge a generation, they bankrupt the system, but only when they themselves start to collect. Everybody knows that. What is less generally known is that "pay as you go" systems fail to collect interest on idle premium money; the HSA system does that, and it turns out to be a huge saving unless the Industrial Revolution stops. Medicare and similar systems don't collect interest during the many-year time gap between earlier premiums and later rendered service; potential compound interest is therefore lost because payroll deductions are used for other purposes. "Pay as you go" is only half of a cycle; adding a Health Savings Account converts it into a full cycle like whole life insurance, and furthermore returns the savings to the individual, rather than using them for insurance company purposes. Whole-life life insurance is more than a century old, but health insurance somehow got started without half of it, the half which could lower the premiums. Nobody stole those savings, they just weren't part of the gift.
All this creates an incentive to overfund the Health Savings Account. The surplus which remains after death is a contingency fund, probably useful for estate taxes or other purposes; but on the other hand, the uncertainty of estate taxes creates an incentive not to overfund by much. Most people would watch this pretty carefully, and soon recognize the most advantageous approach of all would be to pay a lump sum at the beginning, at birth if possible. Before someone roars in outrage about the uninsured, let me say this would work for poor people with a subsidy, and it begins to look as though the Affordable Care Act won't work unless it is subsidized. In that case, a downward adjustment doesn't reduce premiums, it reduces the subsidy.
Investment It seems best to confine the investments of a nation-wide scheme to index funds of a weighted average of the stocks of all U.S. companies above a certain size, and thus offering to pool for those who are (rightly) afraid of investing. This will disappoint the brokerage industry and the financial advisors, but it certainly is diversified, fluctuates with the United States economy, and has low management costs. In a sense, the individual gets a share in nation-wide whole-life health insurance which substitutes long-run equities for conventional fixed income securities. It removes the temptation to speculate on what is certain to occur, but on dates which are uncertain. Treasury bonds might be added to the mix, but almost anything else is too politically vulnerable to political temptations. Even so, it will have downs as well as ups, and therefore participation must be voluntary to protect the index manager from political uproar when stocks go down, as from time to time they certainly will.
One danger seems almost certainly predictable. This book has chosen 6.5 percent assumed return, mostly because it happens to make examples easy to calculate. The actually required return is probably closer to 4% plus inflation. Supposing for example that 7 % is the right number, there is little doubt a steady investment return is only achieved on an average of constant volatility, sometimes returning 20% in some years, and sometimes declining as much or more in other years. Judging from past experience, there will be a temptation for some people to make withdrawals in years of bull markets, which could reduce average returns to 3 or 4 percent in bear market years, and fall short of the 7% average at the moment it is needed. In addition, the officers of Medicare are likely to be tempted to pay Medicare more than a 7% average in windfall years, leaving the running annual average to decline below 7%, just as the trust officers of pension funds once deluded themselves by temporary runs of bull markets. Ultimately this issue reduces itself to a question whether a temporary surplus is really temporary, and if not, whether the subscribers should benefit, or the insurance company. After that is decided, extending or contracting the accordion would get consideration. It seems much better to negotiate these philosophical questions of equity in advance, and establish firm rules before sharp temporary fluctuations are upon us.
Ensuring the Uninsured. Because universal coverage has great appeal, I have gone through the exercise of calculating whether the impoverished uninsured might be included by using subsidy money to provide a lump sum advance premium on their behalf. It would work, in the sense, it would be less costly, but I do not recommend beginning by including it. Reliable government sources have calculated that even after full implementation, the Affordable Care Act will leave 31 million people uninsured. That is, there are 11 million undocumented aliens, 7 million people in jail, and about 8 million people so mentally retarded or impaired, that it is unrealistic ever to expect them to be self-supporting. In my opinion, it is better to design four or five targeted special programs for these people and keep their vicissitudes out of conventional insurance. Better, that is, than to include them in any universal scheme which the mind of man can devise. But to repeat, the mathematics are adequate to justify the opinion that it would save money to include them in this plan with a front-end subsidy of about five thousand dollars, adjusted backward for fund growth since birth. I refuse to quibble about investment size since no one can be certain what either investments or medical science will do in the future. It seems much better to make annual recalculations for inflation and medical discoveries, and then make adjustments through an accordion approach for coverage. There seems to be no need to make precise predictions since any benefit at all is an improvement over relying on taxpayer subsidies, which now run 50% for Medicare itself. This plan will help somewhat, no matter what the future brings, and as far as I can see, it would make the presently unmanageable financial difficulties, more manageable.
George Ross Fisher, M.D.
Quick Analysis of Financial-Industry
Big-Data Analytic Needs
DRAFT George Fisher July 24, 2017
Abstract
Databricks intends to create a Finance Vertical position to support the Sales and SA teams when working with financial-industry organizations. This article attempts to describe the structure of the worldwide financial industry, who the major players are and what their needs might be in the context of Apache Spark and Databricks offerings.
Contents
1 Executive Summary 2
2 Introduction 2
3 Risk Mitigation 3
4 Opportunity Discovery 5
5 Finance-Industry Sponsored Kaggle Contests 6
6 Spark and Finance on YouTube 11
7 APPENDIX 15
1 Executive Summary
The opportunities in the finance sector lie on a wide spectrum: at one
end are the quant funds for whom large-scale analytics are the entire
business, at the other, are traditional depositories for many of whom a
daily batch cycle and a quarterly book closing have long sufficed.
Quite often both extremes exist in the same company.
For this entire spectrum the easy-to-use, streaming, multi-source,
big-data analytics offered by Databricks can offer advantages.
Perhaps with quick adoption by the quants and slower adoption by the others. Early adoption may involve a lot of discovery but a growing collection of proven use cases will ease later sales.
1
.
streaming will supplant batch
.
predictive analytics will replace BI
.
easy multi-sourcing can unite stove pipes
.
pooling can dramatically reduce operational complexity and cost
In addition, in the larger companies, the pressure to comply with data-
related regulations company-wide has become almost overwhelming and
nearly all are struggling with multitudes of incompatible systems that
A spark might unite.
2 Introduction
The finance industry is vast, far too large and diverse to make a
comprehensive enumeration of all the functions performed or of the firms that perform them. The Economist Intelligence Unit [14]
might be a good source, to begin with for such a survey.
The Appendix of this report contains lists of the major financial organizations grouped by function starting on page 15.
The questions of interest to Databricks are (1) which finance firms are
most likely to benefit from the manipulation and analysis of large
datasets and (2) what are the types of manipulation and analysis of
interest?
The two main concerns for the finance industry are:
.
Risk Mitigation
.
Opportunity Discovery
1 I wonder if the entirely cloud-based solution offered by Databricks
does not leave a lot on the table given the pervasiveness of
proprietary datacenters in this world. IBM mainframes, at that.
3 Risk Mitigation
[7]
Simply put, risk mitigation means don’t lose money, don’t go out of business and don’t go to jail.
Risk Categories
1. Business Risk Risks undertaken by the business
itself to maximize share- holder value and profits. For example: the
cost to launch a new product. Risk mitigation takes the form of
competent management controls.
2. Exogenous Risk Political upheaval, natural
disaster, economic disrup- tion. Insurance is the most-common risk
mitigation tool in these cases.
3. Financial Risk Financial risk arises from
volatility in equities, deriva- tives, currencies, interest rates etc.
In the case of financial firms these risks are also Business Risks
since finance is the business.
.
Market
Risk
Changes in prices, their magnitude, direction and volatility.
.
Credit Risk
The effect of counter-party default or the repercussions of providing
services to bad actors.
.
Liquidity
Risk
The inability to make timely payment. Margin calls often precipitate
this when illiquid securities cannot be sold or col- lateralized.
.
Operational Risk
Failures of judgment, integrity, controls, proce- dures or technology.
Cyber Security
An aspect of Operational Risk that gains clar- ity at senior levels
with every report of the losses incurred and chaos engendered by
widespread sophisticated hacking.
Financial-firm financial-risk mitigation is a field of study unto
itself. For example, there is a rigorous, multi-partFinancial Risk Manager (FRM) Certification [5] created by Global Association of Risk Professionals (GARP).
4. Regulatory Compliance While perhaps not a risk per
see this is a huge concern to financial firms, particularly since the
Financial Crisis of a decade ago and the rules promulgated as a
response.
For example, one of the main tenets of BCBS 239 [15] is that all
‘material risk data’ must be automatically aggregated and analyzed across the entire banking group on a near-real-time basis while facing severe economic stresses. Multitudes of incompatible systems are a huge barrier.
[11]
4 Opportunity Discovery
If Risk Mitigation is Operations, Opportunity Discovery is Research
& Devel- opment.
An inexhaustive list:
•
F
undamental
Analysis
The study of the financial characteristics of in- dividual firms,
seeking undiscovered value. Warren Buffett is the world’s most-famous
fundamental analyst.
•
Macro
The study of economy-wide signals. George Soros’ famous short of the UK
Pound is an example [12]. The ‘Big Short’ of 2007-2008 is another [22].
•
Relative
The study of relative movements of securities. Long/Short hedge funds
are an example.
•
T
ec
hnical
Analysis
The study of trendlines.
•
Quantitative
Analysis
The intersection of big data and machine learn- ing. Jim Simons’
Renaissance Capital [16] is the most successful example I know of but
there are many others; some are listed in the appendix be- ginning on
page 17. Some Kaggle contests focused on this, see Section
5.
•
Product Development
Swaps are an example of building a product to meet very specific
customer needs. Even more sophisticated products are possible with
analytical support using all available data.
•
Customer Enhancement
Using machine learning to reduce customer churn; using predictive
analytics for product-customer targeting; consis- tent customer support
across multiple access channels; etc. . . . using Ama- zonian
techniques in a banking environment to take on the characteristics of
the fintechs.
•
Cost Control
Route optimization for filling ATMs; redundant process identification;
risk reduction not just as a regulatory requirement, but as a cost
saver and a profit enhancer
•
Risk System Integration
The regulators are forcing the larger firms to create “living willsâ€
which has resulted in a much better understanding the the numerous
piece parts. The Basel risk data requirements are now forcing a
near-real-time integration of numerous disparate systems. This seems
like fertile ground for innovation both for compliance and to build
upon the results.
5 Finance-Industry Sponsored Kaggle Contests
Over the past several years a number of financial firms have sponsored
Kaggle contests. Someone at these firms thought that these subjects were worth paying for crowd-sourced analysis and was willing to go to the considerable trouble of setting up and monitoring a contest with thousands of participants lasting three months or more.
Two Sigma is a quant fund, listed in the appendix on pages 17 and 23.
The challenge was to predict daily price changes. (In this contest I
earned a Kaggle Silver Medal for coming in 37th out of 2,070
contestants. [9])
Opportunity
Di
sco
v
ery
Improve credit risk models by predicting the probability of default on
consumer credit.
Risk Mitigation
Improve the quality of information within transaction data.
Risk Mitigation
Predict which customers will leave an insurance company in the next 12
months.
Risk Mitigation
Given a dataset of 2D dashboard camera images, State Farm is
challenging Kag-
guess to classify each driver’s behavior. Are they driving attentively,
wearing their seatbelt, or taking a selfie with their friends in the
backseat?
Risk Mitigation
Santander (Spain-based bank) is challenging Kagglers to predict which
products their existing customers will use in the next month based on
their past behavior and that of similar customers.
Opportunity
Di
sco
v
ery
Santander Bank is asking Kagglers to help them identify dissatisfied customers early in their relationship.
Risk Mitigation
, Opportunity Disco very
Using terabytes of noisy, non-stationary data Winton Capital is looking
for data scientists who excel at finding the hidden signal in the
proverbial haystack, and who are excited by creating novel statistical
modeling and data mining techniques.
Opportunity
Di
sco
v
ery
Using a customers shopping history, can you predict what insurance policy they will end up choosing?
Opportunity
Di
sco
v
ery
Claims management may require different levels of the check before a claim can be approved and payment can be made. With the new practices and behaviors generated by the digital economy, this process needs adaptation thanks to data science to meet the new needs and expectations of customers. Kagglers are challenged to predict the category of a claim based on features available early in the process.
Risk Mitigation
, Opportunity Disco very
The life insurance application process is antiquated. Customers provide
extensive information to identify risk classification and
eligibility, including scheduling medical exams, a process that takes
an average of 30 days.
The result? People are turned off. That's why only 40% of U.S.
households own individual life insurance. Prudential wants to make it quicker and less labor intensive for new and existing customers to get a quote while maintaining privacy boundaries.
Opportunity
Di
sco
v
ery
Predict a transformed count of hazards or pre-existing damages using a
dataset of property information. This will enable Liberty Mutual to more accurately identify high-risk homes that require an additional examination to confirm their insurability.
Risk Mitigation
Fire losses account for a significant portion of total property losses.
High severity and low frequency, fire losses are inherently volatile,
which makes modeling them difficult. In this challenge, your task is to
predict the transformed ratio of loss to the total insured value. This will
enable more accurate identification of each policyholders risk exposure
and the ability to tailor the insurance coverage for
their specific operation.
Risk Mitigation
The Benchmark Bond Trade Price Challenge is a competition to predict the next price that a US corporate bond might trade at.
Opportunity
Di
sco
v
ery
Determine whether a loan will default and the loss incurred. We are
building a bridge between traditional banking, where we are looking at
reducing the consumption of economic capital, to an asset-management
perspective, where we optimize on the risk to the financial investor.
Risk Mitigation
Develop models to predict the stock market’s short-term response following large trades. Contestants are asked to derive empirically
models to predict the behavior of bid and ask prices following such
“liquidity shocksâ€.
Modeling market resiliency will improve trading strategy evaluation
methods by increasing the realism of backtesting simulations, which
currently, assume zero market resiliency.
Risk Mitigation
, Opportunity Disco very
Bodily Injury Liability Insurance covers other peoples bodily injury or death for which the insured is responsible. The goal of this
competition is to predict Bodily Injury Liability Insurance claim
payments based on the characteristics of the insureds vehicle.
Risk Mitigation
Allstate is currently developing automated methods of predicting the cost, and hence severity, of claims. Kagglers are invited to create an algorithm which accurately predicts claims severity.
Risk Mitigation
6 Spark and Finance on YouTube
•
Apache Spark on IBM z Systems Demo for Finance
https://www.youtube.com/watch?v=yw0dQFMyxFQ
References to IMS, CICS, and VSAM make me think this is Spark on an IBM
mainframe. Considering the fact that IBM mainframes are still quite widely used, this might be worth understanding.
Opportunity
Discovery
, Risk Mitigation
•
Using Spark to Analyze Activity and Performance in High Speed
T
rading En
vironmen
ts
https://www.youtube.com/watch?v=zdz9Cj1-hjA
Corvil: Irish data monitoring and analytics for financial data using
Spark. Non-intrusive low-latency electronic trading monitoring,
regulatory compliance through the use of streaming telemetry.
Risk Mitigation
•
Spark in Finance Quantitative Investing
https://www.youtube.com/watch?v=WPc-DoSeCpU&t=7s
Reading historical and live tick data, determine a trend and propose
trades.
Opportunity
Disc
o
v
ery
•
Financial Modeling Using Apache Spark
https://www.youtube.com/watch?v=jCXOa6doXEs
Blackrock mortgage analysis of mortgage data. Using Spark, Scala, and D3
to visualize a large loan-level mortgage dataset, extract distributions and cluster boundaries. Also, use K-Means to reveal similar borrower groups and corresponding discriminant attributes.
Opportunity
Disc
o
v
ery
•
Estimating Financial Risk with Spark
https://www.youtube.com/watch?v=0OM68k3np0E
VaR with Monte Carlo using market risk factors explained by Cloudera
Risk Mitigation
7 APPENDIX
Global Financial Services Companies by Revenue
[20]
|
Berkshire Hathaway
|
Conglomerate
|
210.8
|
United States
|
|
AXA
|
Insurance
|
147.5
|
France
|
|
Allianz
|
Insurance
|
140.3
|
Germany
|
|
ICBC
|
Banking
|
134.8
|
China
|
|
Fannie Mae
|
Investment Services
|
131.9
|
United States
|
|
ING
|
Banking
|
130.0
|
Netherlands
|
|
BNP Paribas
|
Banking
|
126.2
|
France
|
|
Generali Group
|
Insurance
|
116.7
|
Italy
|
|
China Construction Bank
|
Banking
|
113.1
|
China
|
|
Banco Santander
|
Banking
|
108.8
|
Spain
|
|
JP Morgan Chase
|
Banking
|
108.2
|
United States
|
|
Socit Gnrale
|
Banking
|
107.8
|
France
|
|
HSBC
|
Banking
|
104.9
|
United Kingdom
|
|
Agricultural Bank of China
|
Banking
|
103.0
|
China
|
|
Bank of America
|
Banking
|
100.1
|
United States
|
|
Bank of China
|
Banking
|
98.1
|
China
|
|
Wells Fargo
|
Banking
|
91.2
|
United States
|
|
Citigroup
|
Banking
|
90.7
|
United States
|
|
Prudential
|
Insurance
|
90.2
|
United Kingdom
|
|
Munich Re
|
Insurance
|
88.0
|
Germany
|
|
Prudential Financial
|
Insurance
|
84.8
|
United States
|
|
Freddie Mac
|
Investment Services
|
80.6
|
United States
|
|
Banco Bradesco
|
Banking
|
78.3
|
Brazil
|
|
Lloyds Banking Group
|
Banking
|
75.6
|
United Kingdom
|
|
Ita Unibanco Holding
|
Banking
|
70.5
|
Brazil
|
|
Zurich Insurance Group
|
Insurance
|
70.4
|
Switzerland
|
|
Aviva
|
Insurance
|
69.0
|
United Kingdom
|
|
Banco do Brasil
|
Banking
|
69.0
|
Brazil
|
|
MetLife
|
Insurance
|
68.2
|
United States
|
|
American International Group
|
Insurance
|
65.7
|
United States
|
|
China Life Insurance
|
Insurance
|
63.2
|
China
|
|
Mitsubishi UFJ Financial Group
|
Banking
|
59.0
|
Japan
|
|
Legal & General Group
|
Insurance
|
56.9
|
United Kingdom
|
|
Dai-ichi Life
|
Insurance
|
56.5
|
Japan
|
|
Barclays
|
Banking
|
55.7
|
United Kingdom
|
|
Aegon
|
Insurance
|
55.2
|
Netherlands
|
|
Deutsche Bank
|
Banking
|
55.0
|
Germany
|
|
UniCredit
|
Banking
|
54.2
|
Italy
|
|
CNP Assurances
|
Insurance
|
53.2
|
France
|
|
BBVA
|
Banking
|
52.1
|
Spain
|
|
Credit Agricole
|
Banking
|
51.2
|
France
|
|
Ping An Insurance Group
|
Insurance
|
51.1
|
China
|
|
National Australia
|
Banking
|
49.2
|
Australia
|
|
Commonwealth Bank
|
Banking
|
47.8
|
Australia
|
|
Intesa Sanpaolo
|
Banking
|
47.7
|
Italy
|
|
UBS
|
Investment Services
|
47.7
|
Switzerland
|
|
Sumitomo Mitsui Financial Group
|
Banking
|
47.3
|
Japan
|
|
Westpac Banking Group
|
Banking
|
43.9
|
Australia
|
|
Bank of Communications
|
Banking
|
43.5
|
China
|
|
Credit Suisse Group
|
Investment Services
|
42.5
|
Switzerland
|
|
MS&AD Insurance Group
|
Insurance
|
42.2
|
Japan
|
|
Royal Bank of Scotland
|
Banking
|
42.1
|
United Kingdom
|
|
Goldman Sachs
|
Investment Services
|
41.7
|
United States
|
|
People’s Insurance Company
|
Insurance
|
41.3
|
China
|
|
Tokio Marine Holdings
|
Insurance
|
39.4
|
Japan
|
|
Royal Bank of Canada
|
Banking
|
38.3
|
Canada
|
|
ANZ
|
Banking
|
37.5
|
Australia
|
|
Manulife Financial
|
Insurance
|
37.3
|
Canada
|
|
Sberbank
|
Banking
|
36.1
|
Russia
|
|
State Bank of India
|
Banking
|
35.1
|
India
|
|
Talanx
|
Insurance
|
34.9
|
Germany
|
|
Power Corporation of Canada
|
Insurance
|
34.2
|
Canada
|
|
Swiss Re
|
Insurance
|
33.6
|
Switzerland
|
|
American Express
|
Financial Services
|
33.4
|
United States
|
|
Allstate
|
Insurance
|
33.3
|
United States
|
|
Mizuho Financial Group
|
Banking
|
32.8
|
Japan
|
|
Old Mutual
|
Investment Services
|
32.2
|
United Kingdom
|
|
Morgan Stanley
|
Investment Services
|
32.0
|
United States
|
|
Standard Life
|
Insurance
|
31.2
|
United Kingdom
|
|
Sompo Holdings
|
Insurance
|
30.9
|
Japan
|
|
TD Bank Group
|
Banking
|
30.6
|
Canada
|
|
China
|
Banking
|
28.4
|
China
|
|
China
|
Banking
|
27.9
|
China
|
|
Bank of Nova Scotia
|
Banking
|
27.6
|
Canada
|
|
Onex
|
Investment Services
|
27.4
|
Canada
|
|
China
|
Insurance
|
27.3
|
China
|
|
Mapfre
|
Insurance
|
27.1
|
Spain
|
|
Standard Chartered
|
Banking
|
26.9
|
United Kingdom
|
|
Dexia
|
Banking
|
26.6
|
Belgium
|
|
Hartford Financial Services
|
Insurance
|
26.4
|
United States
|
|
Travelers Cos
|
Insurance
|
25.7
|
United States
|
|
Commerzbank
|
Banking
|
25.5
|
Germany
|
|
Aflac
|
Insurance
|
25.4
|
United States
|
|
Shanghai Pudong Development
|
Banking
|
25.4
|
China
|
Major
Stock Exchanges
[21]
|
New York Stock Exchange
|
United States
|
New York
|
|
NASDAQ
|
United States
|
New York
|
|
London Stock Exchange Group
|
United Kingdom
|
London
|
|
Japan Exchange Group
|
Japan
|
Tokyo
|
|
Shanghai Stock Exchange
|
China
|
Shanghai
|
|
Hong Kong Stock Exchange
|
Hong Kong
|
Hong Kong
|
|
Euronext
|
European Union
|
Amsterdam, Brussels, Lisbon, London, Paris
|
|
Shenzhen Stock Exchange
|
China
|
Shenzhen
|
|
Toronto Stock Exchange
|
Canada
|
Toronto
|
|
Deutsche Brse
|
Germany
|
Frankfurt
|
|
Bombay Stock Exchange
|
India
|
Mumbai
|
|
National Stock Exchange of India
|
India
|
Mumbai
|
|
SIX Swiss Exchange
|
Switzerland
|
Zurich
|
|
Australian Securities Exchange
|
Australia
|
Sydney
|
|
Korea Exchange
|
South Korea
|
Seoul
|
|
OMX Nordic Exchange
|
Sweden
|
Stockholm
|
|
JSE Limited
|
South Africa
|
Johannesburg
|
|
BME Spanish Exchanges
|
Spain
|
Madrid
|
|
Taiwan Stock Exchange
|
Taiwan
|
Taipei
|
|
BM&F Bovespa
|
Brazil
|
So Paulo
|
Quant
F
unds
[13]
•
D. E. Shaw (New York, NY)
•
Renaissance Technologies (East Setauket, NY)
•
Morgan Stanley PDT (New York, NY)
•
Point72 Asset Management (SAC Capital)
•
AQR Capital
•
Two Sigma Investments (New York, NY)
•
Citadel (Chicago, IL)
•
Jane Street Capital (New York and London)
•
RG Niederhoffer
•
Jump Trading
•
KCG Holdings
•
Bridgewater Associates
•
Hudson River Trading
•
Man Group AHL
•
Highbridge
•
Millennium/WorldQuant
•
Winton
•
Bluecrest
•
Ellington Capital
•
Tower Research Capital
•
Parametrica Global Master Ltd
•
Camox Ltd
•
Voloridge Trading
•
Senvest Partners Ltd
•
BlackRock European Hedge
Credit
Card Issuers
[1]
1. Visa - 323M Cardholders
2. MasterCard - 191M Cardholders
3. Chase - 93M Cardholders
4. American Express - 58M Cardholders
5. Discover - 57M Cardholders
6. Citibank - 48M Cardholders
7. Capital One - 45M Cardholders
8. Bank of America - 32M Cardholders
9. Wells Fargo - 24M Cardholders
10. US Bank - 18.5M Cardholders
11. USAA - 10M Cardholders
12. Credit One - 6M Cardholders
13. Barclaycard US 418K Cardholders
14. First PREMIER Bank (subprime)
15. PNC
Mortgage Risk
[10]
Prior to the financial collapse of 2007-2008 mortgage, securitization was the hot thing. Many institutions and individuals got burned and a
residual fear of securitization remains.
The result is that for jumbo and subprime mortgages, the originators are now holding many more of the loans. This reduces the systematic
risk but an unanticipated consequence is that Fannie Mae and Freddie Mac [3] are
now holding 50% of $11 trillion outstanding in the middle market.
Therefore the US government has undertaken a huge amount of default and
interest-rate risk.
Insurance Companies by Premium Income
[8]
Property/Casualty Insurance
|
State Farm Mutual Automobile Insurance
|
62,189,311
|
|
Berkshire Hathaway Inc.
|
33,300,439
|
|
Liberty Mutual
|
32,217,215
|
|
Allstate Corp.
|
30,875,771
|
|
Progressive Corp.
|
23,951,690
|
|
Travelers Companies Inc.
|
23,918,048
|
|
Chubb Ltd.
|
20,786,847
|
|
Nationwide Mutual Group
|
19,756,093
|
|
Farmers Insurance Group of Companies
|
19,677,601
|
|
USAA Insurance Group
|
18,273,675
|
Life Insurance/Annuities
|
MetLife Inc.
|
95,110,802
|
|
Prudential Financial Inc.
|
45,902,327
|
|
New York Life Insurance Group
|
30,922,462
|
|
Principal Financial Group Inc.
|
28,186,098
|
|
Massachusetts Mutual Life Insurance Co.
|
23,458,883
|
|
American International Group
|
22,463,202
|
|
Jackson National Life Group
|
22,132,278
|
|
AXA
|
21,920,627
|
|
AEGON
|
21,068,180
|
|
Lincoln National Corp.
|
19,441,555
|
|
Homeowners Insurance
State Farm Mutual Automobile Insurance
|
17,516,715
|
|
Allstate Corp.
|
7,926,984
|
|
Liberty Mutual
|
5,993,803
|
|
Farmers Insurance Group of Companies
|
5,284,511
|
|
USAA Insurance Group
|
5,000,407
|
|
Travelers Companies Inc.
|
3,305,427
|
|
Nationwide Mutual Group
|
3,249,456
|
|
American Family Insurance Group
|
2,609,366
|
|
Chubb Ltd. (4)
|
2,485,193
|
|
Erie Insurance Group
|
1,471,544
|
Private
P
assenger Auto Insurance
|
State Farm Mutual Automobile Insurance
|
39,194,660
|
|
Berkshire Hathaway Inc.
|
25,531,762
|
|
Allstate Corp.
|
20,813,858
|
|
Progressive Corp.
|
19,634,834
|
|
USAA Insurance Group
|
11,691,051
|
|
Liberty Mutual
|
10,774,426
|
|
Farmers Insurance Group of Companies
|
10,304,622
|
|
Nationwide Mutual Group
|
7,640,558
|
|
American Family Insurance Group
|
4,005,549
|
|
Travelers Companies Inc.
|
3,896,786
|
|
Commercial Auto Insurance
|
|
|
Progressive Corp.
|
2,625,929
|
|
Travelers Companies Inc.
|
2,124,182
|
|
Nationwide Mutual Group
|
1,735,614
|
|
Zurich Insurance Group
|
1,624,621
|
|
Liberty Mutual
|
1,604,461
|
|
Old Republic International Corp.
|
1,123,042
|
|
Berkshire Hathaway Inc.
|
951,775
|
|
American International Group (AIG)
|
867,567
|
|
Auto-Owners Insurance Co.
|
739,495
|
|
Chubb Ltd.
|
695,210
|
|
Commercial Lines Insurance
|
|
|
|
Chubb Ltd.
|
16,528,891
|
|
Travelers Companies Inc.
|
16,463,566
|
|
Liberty Mutual
|
15,056,251
|
|
American International Group (AIG)
|
13,144,961
|
|
Zurich Insurance Group
|
12,554,597
|
|
CNA Financial Corp.
|
9,763,122
|
|
Nationwide Mutual Group
|
8,335,275
|
|
Hartford Financial Services
|
7,679,737
|
|
Berkshire Hathaway Inc.
|
7,650,236
|
|
Tokio Marine Group
|
6,256,196
|
|
W
orkers’ Compensation Insurance
|
|
Travelers Companies Inc.
|
4,467,425
|
|
Hartford Financial Services
|
3,324,361
|
|
AmTrust Financial Services
|
2,972,901
|
|
Zurich Insurance Group
|
2,851,695
|
|
Liberty Mutual
|
2,481,479
|
|
Berkshire Hathaway Inc.
|
2,479,354
|
|
State Insurance Fund Workers’ Comp (NY)
|
2,437,325
|
|
Chubb Ltd.
|
2,368,918
|
|
American International Group
|
2,345,247
|
|
State Compensation Insurance Fund (CA)
|
1,638,849
|
Global Asset Management Firms by Revenue
[18]
|
BlackRock
|
United States
|
4,890
|
|
The Vanguard Group
|
United States
|
3,149
|
|
UBS
|
Switzerland
|
2,716
|
|
State Street Global Advisors
|
United States
|
2,460
|
|
Fidelity Investments
|
United States
|
2,025
|
|
Allianz
|
Germany
|
1,949
|
|
J.P. Morgan Asset Management
|
United States
|
1,760
|
|
BNY Mellon Investment Management
|
United States
|
1,740
|
|
PIMCO
|
United States
|
1,590
|
|
Credit Agricole Group
|
France
|
1,527
|
Global Investment Banks by Revenue
[2]
|
JPMorgan
|
3,361
|
|
Goldman Sachs
|
2,858
|
|
Bank of America Merrill Lynch
|
2,684
|
|
Morgan Stanley
|
2,501
|
|
Citi
|
2,378
|
|
Barclays
|
1,884
|
|
Credit Suisse
|
1,760
|
|
Deutsche Bank
|
1,387
|
|
RBC Capital Markets
|
994
|
|
UBS
|
904
|
|
Wells Fargo Securities
|
871
|
|
HSBC
|
793
|
|
Jefferies LLC
|
750
|
|
BNP Paribas
|
619
|
|
Lazard
|
565
|
|
BMO Capital Markets
|
448
|
|
Nomura
|
445
|
|
Mizuho
|
435
|
|
Sumitomo Mitsui Financial Group
|
413
|
|
Evercore Partners Inc
|
407
|
Hedge Funds By Assets Under Management
[6]
|
OrgCRD
|
PrimaryBusinessName
|
May2017AUM
|
|
110814
|
NOMURA ASSET MANAGEMENT CO., LTD.
|
367.6
|
|
105129
|
BRIDGEWATER ASSOCIATES, LP
|
239.3
|
|
158117
|
MILLENNIUM MANAGEMENT LLC
|
207.6
|
|
158319
|
SAMSUNG ASSET MANAGEMENT COMPANY, LTD.
|
182.2
|
|
148826
|
CITADEL ADVISORS LLC
|
152.7
|
|
143161
|
APOLLO CAPITAL MANAGEMENT, L.P.
|
125
|
|
140074
|
PICTET ASSET MANANGEMENT SA.
|
122.8
|
|
110997
|
NIKKO ASSET MANAGEMENT CO LTD
|
120.6
|
|
282598
|
VANGUARD ASSET MANAGEMENT, LIMITED
|
120.2
|
|
111128
|
THE CARLYLE GROUP
|
101.9
|
|
106661
|
RENAISSANCE TECHNOLOGIES LLC
|
97
|
|
144533
|
KOHLBERG KRAVIS ROBERTS
|
90
|
|
168122
|
ANNALY MANAGEMENT COMPANY
|
87.9
|
|
152719
|
ALPHADYNE ASSET MANAGEMENT PTE. LTD.
|
84.6
|
|
133720
|
PINE RIVER CAPITAL MANAGEMENT L.P.
|
82.8
|
|
159732
|
TPG GLOBAL ADVISORS, LLC
|
79.5
|
|
138111
|
BALYASNY ASSET MANAGEMENT L.P.
|
75.1
|
|
144603
|
EASTSPRING INVESTMENTS (SINGAPORE) LIMITED
|
74.5
|
|
155587
|
FIELD STREET CAPITAL MANAGEMENT, LLC
|
63.3
|
|
107580
|
BLACKSTONE ALTERNATIVE ASSET MANAGEMENT LP
|
62.3
|
|
148823
|
BLUECREST CAPITAL MANAGEMENT LIMITED
|
62.2
|
|
142979
|
BLACKSTONE REAL ESTATE ADVISORS L.P.
|
60.1
|
|
160795
|
APG ASSET MANAGEMENT US, INC
|
59.3
|
|
130074
|
ARES MANAGEMENT LLC
|
58.4
|
|
136979
|
BLACKSTONE MANAGEMENT PARTNERS L.L.C.
|
57.4
|
|
161600
|
AGNC MANAGEMENT, LLC
|
56.9
|
|
129612
|
FORTRESS INVESTMENT GROUP
|
56.9
|
|
156601
|
ELLIOTT MANAGEMENT CORPORATION
|
56
|
|
160309
|
ELEMENT CAPITAL MANAGEMENT LLC
|
55.9
|
|
139345
|
MACQUARIE FUNDS MANAGEMENT
|
54.7
|
|
160188
|
MOORE CAPITAL MANAGEMENT, LP
|
53.8
|
|
107913
|
OZ MANAGEMENT LP
|
51.7
|
|
159738
|
TPG CAPITAL ADVISORS, LLC
|
51.6
|
|
137137
|
TWO SIGMA INVESTMENTS, LP
|
49.3
|
|
152254
|
TWO SIGMA ADVISERS, LP
|
48.7
|
|
110338
|
MACKENZIE INVESTMENTS
|
48.6
|
|
156078
|
HUDSON AMERICAS L.P.
|
48.4
|
|
160000
|
LONE STAR NORTH AMERICA ACQUISITIONS, LLC
|
48.1
|
|
152175
|
CERBERUS CAPITAL MANAGEMENT, L.P.
|
48
|
|
173355
|
CANDRIAM LUXEMBOURG S.C.A.
|
47.1
|
|
156934
|
3G CAPITAL PARTNERS LP
|
46.3
|
|
143158
|
APOLLO MANAGEMENT, L.P.
|
46.2
|
|
157589
|
CAPULA INVESTMENT US LP
|
45.8
|
|
156945
|
WARBURG PINCUS LLC
|
45.7
|
|
132272
|
VIKING GLOBAL INVESTORS LP
|
43.4
|
|
160679
|
ADAGE CAPITAL MANAGEMENT, L.P.
|
42
|
|
146629
|
KKR CREDIT ADVISORS (US) LLC
|
41.5
|
|
159215
|
ALPINVEST PARTNERS B.V.
|
41.2
|
|
108679
|
D. E. SHAW
|
37
|
Largest private equity firms by PE capital raised
[17]
|
The Carlyle Group
|
Washington D.C.
|
$30,650.33
|
|
Kohlberg Kravis Roberts
|
New York City
|
$27,182.33
|
|
The Blackstone Group
|
New York City
|
$24,639.84
|
|
Apollo Global Management
|
New York City
|
$22,298.02
|
|
TPG
|
Fort Worth/San Francisco
|
$18,782.59
|
|
CVC Capital Partners
|
Luxembourg
|
$18,082.35
|
|
General Atlantic
|
New York City
|
$16,600.00
|
|
Ares Management
|
Los Angeles
|
$14,113.58
|
|
Clayton Dubilier & Rice
|
New York City
|
$13,505.00
|
|
Advent International
|
Boston
|
$13,228.09
|
|
EnCap Investments
|
Houston
|
$12,400.20
|
|
Goldman Sachs Principal Investment Area
|
New York City
|
$12,343.32
|
|
Warburg Pincus
|
New York City
|
$11,213.00
|
|
Silver Lake
|
Menlo Park
|
$10,986.40
|
|
Riverstone Holdings
|
New York City
|
$10,384.26
|
|
Oaktree Capital Management
|
Los Angeles
|
$10,147.28
|
|
Onex
|
Toronto
|
$10,097.21
|
|
Ardian (formerly AXA Private Equity)
|
Paris
|
$9,805.25
|
|
Lone Star Funds
|
Dallas
|
$9,731.81
|
In
v
estmen
t
Banking Private Equity Groups
[19]
ABN AMRO AAC Capital Partners Barclays Capital Equistone Partners
Europe BNP Paribas PAI Partners
CIBC World Markets Trimaran Capital Partners
Citigroup Court Square; CVC; Welsh, Carson, Anderson &
StoweBruckmann, Rosser, S Deutsche Bank MidOcean Partners
Globus Capital Holdings Globus Capital Banca
Goldman Sachs Goldman Sachs Capital Partners JPMorgan Chase CCMP
Capital; One Equity Partners Lazard Lazard Alternative Investments
Merrill Lynch Merrill Lynch Global Private Equity
Morgan Stanley Metalmark Capital; Morgan Stanley Capital Partners New
York
National Westminster Bank Bridgepoint Capital
Nomura Group Terra Firma Capital Partners
UBS UBS Capital; Affinity Equity Partners; Capvis; Lightyear Capital
Wells Fargo Pamlico Capital
William Blair & Company William Blair Capital Partners
F
ederal Reserve System
The St. Louis Fed is well known among economics geeks as a fantastic
source of data, analysis and commentary. [4] In fact, all the Fed banks
are avid consumers of data, analysis and risk-management metrics.
[14] The Economist of London. The Economist Intelligence Unit. https://
www.eiu.com/home.aspx
.
[15] Wikipedia. BCBS 239.
https://en.m.wikipedia.org/wiki/BCBS_239
. [16] Wikipedia. James Harris Simons.
https://en.wikipedia.org/wiki/
James_Harris_Simons
.
[17] Wikipedia. Largest private equity firms by PE capital raised.
https:
//en.wikipedia.org/wiki/List_of_private_equity_firms
.
[18] Wikipedia. List of asset management firms.
https://en.wikipedia.org/
wiki/List_of_asset_management_firms
.
[19] Wikipedia. List of investment banking private equity groups.
https://
en.wikipedia.org/wiki/List_of_private_equity_firms
.
[20] Wikipedia. List of largest financial services companies by revenue.
https://en.wikipedia.org/wiki/List_of_largest_financial_
services_companies_by_revenue
.
[21] Wikipedia. Major Stock Exchanges.
https://en.wikipedia.org/wiki/
List_of_stock_exchanges
.
[22] Wikipedia. The Big Short.
https://en.wikipedia.org/wiki/The_Big_
Short
.
Originally the "lower counties" of Pennsylvania, and thus one of three Quaker colonies founded by William Penn, Delaware has developed its own set of traditions and history.
Start in Philadelphia, take two days to tour around Delaware Bay. Down the New Jersey side to Cape May, ferry over to Lewes, tour up to Dover and New Castle, visit Winterthur, Longwood Gardens, Brandywine Battlefield and art museum, then back to Philadelphia. Try it!
Millions of eye patients have been asked to read the passage from Franklin's autobiography, "I walked up Market Street, etc." which is commonly printed on eye-test cards. Here's your chance to do it.
In 1751, the Pennsylvania Hospital at 8th and Spruce was 'way out in the country. Now it is in the center of a city, but the area still remains dominated by medical institutions.
Grievances provoking the American Revolutionary War left many Philadelphians unprovoked. Loyalists often fled to Canada, especially Kingston, Ontario. Decades later the flow of dissidents reversed, Canadian anti-royalists taking refuge south of the border.
