Stylized Facts, Affordable Homes and Bank Liquidity. #LIBOR #TINA #MREL @MartinSewell


Libor and its effects on Credit Allocation, the NEt results can be seen as the Old Hag and yet most of us still see the Image of TINA , there is No Alternative.
And here we see Sonia , Libor with a Makeover , Essentially its the Same old Tina with the odd Nip and Tuck.

https://www.moillusions.com/just-some-few-old-hags/

Actual and indicative minimum requirements for own funds and eligible liabilities (MREL)

https://www.bankofengland.co.uk/markets/sonia-benchmark

https://www.rollingstone.com/politics/politics-news/everything-is-rigged-the-biggest-price-fixing-scandal-ever-82255/

Secured and Unsecured InterbankMarkets: Monetary Policy,Substitution and the Cost of CollateralThibaut Piquard1 and Dilyara Salakhova2

September 2019, WP #730
https://drive.google.com/file/d/1aYHcJeu-SA-Q58bRWw0G_onNOX2pSvVo/view?usp=sharing
N ON -T ECHNICAL S UMMARY
Secured and unsecured money markets are prime short-term funding markets for banks. They play a
key role in the transmission of monetary policy, and while the interbank unsecured interest rate is the
actual monetary policy target of most central banks around the world, the repo market has only
recently attracted attention of policy makers when repo rates went below the deposit facility rate.
However, there is still lack in understanding how banks decide in which market to trade, and how
the two markets co-exist and react to monetary policy.

we build a model that is able to account for such stylized facts. Like the benchmark model
from Poole (1968), banks are subject to shocks on their reserve holdings in a corridor rates system
with reserve requirements.

Stylized Facts

Stylized Facts

SEWELL, Martin, 2011. Characterization of financial time series. Research Note RN/11/01, University College London, London.

What are stylized facts?
A stylized fact is a term used in economics to refer to empirical findings that are so consistent (for example, across a wide range of instruments, markets and time periods) that they are accepted as truth. Due to their generality, they are often qualitative.
Sewell (2006)

“In social sciences, especially economics, a stylized fact is a simplified presentation of an empirical finding. While results in statistics can only be shown to be highly probable, in a stylized fact, they are presented as true. They are a means to represent complicated statistical findings in an easy way. A stylized fact is often a broad generalisation, which although essentially true may have inaccuracies in the detail.”
Wikipedia (2006)

“Definition: Stylized facts are observations that have been made in so many contexts that they are widely understood to be empirical truths, to which theories must fit. Used especially in macroeconomic theory. Considered unhelpful in economic history where context is central. ”
About.com (2006)

“Nevertheless, the result of more than half a century of empirical studies on financial time series indicates that this is the case if one examines their properties from a statistical point of view: the seemingly random variations of asset prices do share some quite nontrivial statistical properties. Such properties, common across a wide range of instruments, markets and time periods are called stylized empirical facts.
Stylized facts are thus obtained by taking a common denominator among the properties observed in studies of different markets and instruments. Obviously by doing so one gains in generality but tends to lose in precision of the statements one can make about asset returns. Indeed, stylized facts are usually formulated in terms of qualitative properties of asset returns and may not be precise enough to distinguish among different parametric models. Nevertheless, we will see that, albeit qualitative, these stylized facts are so constraining that it is not easy to exhibit even an (ad hoc) stochastic process which possesses the same set of properties and one has to go to great lengths to reproduce them with a model.”
Cont (2001)

“An important part of the research is the analysis of financial data [1-3], which has led to the characterization of some empirical statistical regularities, known as “stylized facts”.”
Challet, Marsili and Zhang (2001)

[daily returns] “General properties that are expected to be present in any set of returns are called stylized facts.”
Taylor (2005), page 51

“The one common observation across these dimensions is that “market activity” is strongly correlated with price variability. Trading volume, return volatility, and bid-ask spreads are highest around the open and close of trading; return variability per unit of time is higher over trading than nontrading periods; trading volume and spreads are particularly high on days with large return innovations; and public information releases—which theoretically may induce price jumps without any trading—are typically associated with extrememely heavy volume.”
Andersen and Bollerslev (1998)

[The predictability of asset returns: recent empirical evidence] “However, we would be remiss if we did not cite the rich empirical tradition on which the recent literature is built, which includes: Alexander (1961, 1964), Cootner (1964), Cowles (1960), Cowles and Jones (1937), Fama (1965), Fama and Blume (1966) Kendall (1953), Granger and Morgenstern (1963), Mandelbrot (1963), Osborne (1959, 1962), Roberts (1959), and Working (1960). Campbell, Lo and MacKinlay (1997)

Distributions
Security returns are non-stationary, so we speak here of the asymptotic pdf. The distribution of returns is approximately symmetric and has high kurtosis (that is, fat tails and a peaked centre compared with the normal distribution). The distributions are increasingly fat-tailed as data frequency increases (smaller interval sizes).

A random process Y is infinitely divisible if, for every natural number n, it can be represented as the sum of n independent identically distributed (i.i.d.) random variables:
Y = X1 + X2+…+Xn

Consider the sum of n i.i.d. random variables:
Y = X1 + X2+…+Xn
when the functional form of Y is the same as the functional form of Xi, the stochastic process is said to be stable.

Special cases of stable distributions:

Gaussian distribution
Cauchy distribution
Lévy distribution

William Cobbett, the celebrated English writer and economist, transmitted a letter to
16
Mr. Dallas, Secretary of the Treasury under President Madison, in which he strenuously urged him to
oppose the project.
As a warning against chartering a bank of issue, Cobbett pointed out the immense power of the Bank of
England to ruin the tradesmen of that country, and to dictate the political sentiments of that people. He
said: –
London, January 13, 1816.
http://www.mega.nu:8080/ampp/comingbattle/cbchap1.htm (5 of 20) [9/11/2000 18:19:34]The Coming Battle, Chapter 1

http://www.newswithviewsstore.com/mm5/merchant.mvc?Screen=PROD&Store_Code=NWVS&Product_Code=B1&Category_Code=BOOKS

William Cobbett, the celebrated English writer and economist, transmitted a letter to
16
Mr. Dallas, Secretary of the Treasury under President Madison, in which he strenuously urged him to
oppose the project.
As a warning against chartering a bank of issue, Cobbett pointed out the immense power of the Bank of
England to ruin the tradesmen of that country, and to dictate the political sentiments of that people. He
said: –
London, January 13, 1816.

“To Mr. Secretary Dallas:
“Sir: I have read with great care and uncommon interest your proposition to congress, under date of 6th
December, 1815, for the establishment of a national bank; and as a part of the reasons which you urge in
support of that proposition appear to bc founded on the experience of a similar institution in England, I
cannot refrain from endeavoring to show you what some of these effects really have been, and what is at
present the situation of this country, owing, in a great measure, to the existence of a great banking
establishment closely connected with the government.
“It is the evil of a national bank, as experienced by us, to which I particularly wish to draw your
attention. You profess, and I dare say very sincerely, so to frame this establishment in America that it
shall bc independent of the Government. It is next to impossible, indeed, that you, or any of the persons
in whose hands the Government is, should have a desire to make a bank what our bank has long been;
but while there is a possibility of its becoming, in any hands or at any time, anything resembling this
bank, it must be a matter of serious dread to every friend of America that such an establishment is likely
to take place. Sir, it is as a bank of discount that this establishment exercises the most pernicious
influence. The directors, who are a chosen divan, regulate these discounts, and in so doing decide in
some sort upon the rise or fall, the making or the ruin, of all men in trade, and indeed 17 of most other
men, except such as have no capital at all.
17
“The amount of these discounts at any given time is supposed to bc about L6,000,000, as they are never
for more than two months. Here is a sum of thirty-six millions lent every year to individuals. The bills for
discounts are sent in; the directors consent or not, without any reasons assigned. Now, sir, consider the
magnitude of the sum discounted. It is little short of half a million dollars a day, Sundays excepted. It is
perfectly well known to you that in state of such things almost every man in trade is under the necessity
of having a regular supply from discounting. If he be excluded from his fair share here, he cannot trade
with the same advantage as other men trade. If he be in the practice of discounting, and if his discounts
be cut off, he cannot go on; he stops payment and is frequently ruined forever, even while he possesses
property which, with the fair chances of time, would not only enable him to pay his debts but to proceed
in prosperity.
“I beseech you, then, sir, to look seriously at the extent of the dangerous power of these bank directors.
You must see that they hold in their hands the pecuniary fate of a very large part of the community, and
that they have it in their power, every day of their lives, to destroy the credit of many men, and to plunge
their families into shame and misery. If I am asked for their motives to act like these, to pursue such
partiality, to make themselves the instruments in committing such detestable injustice and cruelty, need I
point out to you that they have been and must be constantly actuated by the strongest political
prejudices? The fact is, however, that the Bank of England, by means of its power of granting or
withholding discounts, has been, and is one of the most potent instruments of political corruption, on the
one hand, and of political vengeance on the other hand.”

End of Part 1.
“Investment trusts were the forerunners of the unit trusts and other mutual funds. In finance many of the greatest inventions are in terminology, A new name for and old idea.”
JK Galbraith .

http://finance.martinsewell.com/crisis.html

https://newswithviews.com/Veon/joan163.htm
https://www.nytimes.com/1999/09/30/business/fannie-mae-eases-credit-to-aid-mortgage-lending.html


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A year after Duhon took on the post, she got word that Bayerische Landesbank, a large German bank, wanted to use the credit derivatives structure to remove the risk from $14bn of US mortgage loans it had extended. She debated with her team whether to accept the assignment; working with mortgage debt wasn’t a natural move for JP Morgan. But Duhon knew that some of the bank’s rivals were starting to conduct credit derivatives deals with mortgage risk, so the team decided to take it on.

As soon as Duhon talked to the quantitative analysts, she encountered a problem. When JP Morgan had offered the first Bistro deals in late 1997, it had access to extensive data about all the loans it had pooled together. So did the investors who bought the resulting credit derivatives, since the bank had deliberately named all of the 307 companies whose loans were included. In addition, many of these companies had been in business for decades, so extensive data were available on how they had performed over many business cycles. That gave JP Morgan’s statisticians, and investors, great confidence in predicting the likelihood of defaults. But the mortgage world was very different. For one thing, when banks sold bundles of mortgage loans to outside investors, they almost never revealed the names and credit histories of the individual borrowers. Worse, when Duhon went looking for data to track mortgage defaults over several business cycles, she discovered it was in short supply.

While America’s corporate world had suffered several booms and recessions in the later 20th century, the housing market had followed a steady path of growth. Some specific regions had suffered downturns: prices in Texas, for example, fell during the Savings and Loans debacle of the late 1980s. But since the second world war, there had never been a nationwide house-price slump. The last time house prices had fallen significantly en masse, in fact, was way back in the 1930s, during the Great Depression. The lack of data made Duhon nervous. When bankers assembled models to predict defaults, they wanted data on what normally happened in both booms and busts. Without that, it was impossible to know whether defaults tended to be correlated or not, in what circumstances they were isolated to particular urban centres or regions, and when they might go national. Duhon could see no way to obtain such information for mortgages. That meant she would either have to rely on data from just one region and extrapolate it across the US, or make even more assumptions than normal about how defaults were correlated. She discussed what to do with Krishna Varikooty and the other quantitative experts. Varikooty was renowned on the team for taking a sober approach to risk. He was a stickler for detail and that scrupulousness sometimes infuriated colleagues who were itching to make deals. But Demchak always defended Varikooty. His judgment on the mortgage debt was clear: he could not see a way to track the potential correlation of defaults with any confidence. Without that, he declared, no precise estimate could be made of the risks of default in a pool of mortgages. If defaults on mortgages were uncorrelated, then the Bistro structure should be safe for mortgage risk, but if they were highly correlated, it might be catastrophically dangerous. Nobody could know.

Duhon and her colleagues were reluctant simply to turn down Bayerische Landesbank’s request. The German bank was keen to go ahead, even after the uncertainty in the modelling was explained, and so Duhon came up with the best estimates she could to structure the deal. To cope with the uncertainties the team stipulated that a bigger-than-normal funding cushion be raised, which made the deal less lucrative for JP Morgan. The bank also hedged its risk. That was the only prudent thing to do, and Duhon couldn’t see herself doing many more such deals. Mortgage risk was just too uncharted. “We just could not get comfortable,” Masters later said.

In subsequent months, Duhon heard through the grapevine that other banks were starting to do credit derivatives deals with mortgage debt, and she wondered how they had coped with the lack of data that so worried her and Varikooty. Had they found a better way to track the correlation issue? Did they have more experience of dealing with mortgages? She had no way of finding out. Because the credit derivatives market was unregulated, details of the deals weren’t available.

The team at JP Morgan did only one more Bistro deal with mortgage debt, a few months later, worth $10bn. Then, as other banks ramped up their mortgage-backed business, JP Morgan largely dropped out. Eight years later, the unquantified mortgage risk that had frightened off Duhon, Varikooty and the JP Morgan team had reached vast proportions. And it was spread throughout the western world’s financial system.

Gillian Tett is an assistant editor at the FT. In March, she was named Journalist of the Year at the British Press Awards

This is an edited extract from ‘Fool’s Gold: How Unrestrained Greed Corrupted a Dream, Shattered Global Markets and Unleashed a Catastrophe’ by Gillian Tett. It is published this week by Little, Brown, £18.99, and in mid-May by Simon & Schuster in the US. To buy the book for £13.99, call the FT ordering service on 0870 429 5884 or go to http://www.ft.com/bookshop

To read the second “Fool’s Gold” extract, “How greed turned to panic”, click here.

Author: rogerglewis

https://about.me/rogerlewis Looking for a Job either in Sweden or UK. Freelance, startups, will turń my hand to anything.