AI News, Five books every data scientist should read that are not about data science
Five books every data scientist should read that are not about data science
Over the past decade, I witnessed the term ‘data science’ come into widespread use and saw the rise and fall of buzzwords like big data, business intelligence, analytics, and now artificial intelligence.
My class at UW was ‘computational finance,’ which easily filled a sizable lecture hall the way deep learning classes do today.
However, the financial crisis also laid bare the inadequacy of even the most sophisticated models to cope with the lion of chaos that is the real world.
This model was used, without understanding its inherent limitations and implicit assumptions, to gauge risk for an enormous amount of investments.
To help address this problem (of which I also suffer), I am presenting a short reading list of books that will philosophically prepare a data scientist.
Personal Data And The Next Subprime Crisis
Before derivative products graduated from esoteric financial know-how to casual dinner conversation topic, before the fog lifted on Collateralised Debt Obligations and it became common knowledge that asset-backed securitization had been resting on subprime borrowing, an entire global economy suffered the long chill of frozen interbank lending.
No finance textbook had a chapter on how banking trust worked: once over-the-counter derivatives injected complexity and lack of transparency in a single entry of a bank’s portfolio, its risk contaminated whole asset classes, whole portfolios and, ultimately, the entire financial ecosystem.
Yet, considering it does not as yet offer a workable criterion to demarcate which data points amount to personal data and which ones amount to non-personal data, and considering it casts onto businesses a triad of obligations that reach deep into how
The GDPR’s joint and several liability for businesses and their contractors in verifying data lineage and correct handling of personal data by the other party are not yet widely understood to inject counterparty data risk into every organization.
Unless clearly understood by all market operators, and unless it is offered the same degree of transparent handling and traceability that all traded financial instruments have, personal data is our next subprime asset, injecting risk into all organizations.
A primary personal data market is to be understood in its broad sense as any mechanism allowing businesses with a need to deploy personal data (demand) to agree an exchange with individuals offering up their data for a perceived benefit (offer).
Yet, because of the GDPR prohibitions to re-purpose the data thus collected, because of the absolute bar to utilizing such data past an agreed time frame and because of the heavy restrictions on any onward-transfer of such data, there will never be a deep and liquid personal data secondary market.
Three reasons why misunderstanding the new nature of data harms the financial markets One reason is that where we have no secondary markets, price discovery is tricky: we do not really know how to price correctly personal data-rich listed companies.
privacy commissioner, is commanding the world’s respect in doggedly tracing how personal data harvested through an online personality test originally devised in a Cambridge University Lab, later deployed by a consultancy for commercial gain, finally ended up in elaboratevoter profiling and micro-targeting in key marginal states in the US presidential election of 2016.
Tech dare games As if pricing opacity and data liquidity risks were not enough to feed a potential systemic risk, even two months after itsenforcement date, data-intensive multinationals still seem appear to be playing GDPR compliance games of chicken with EU regulators and confidence games with their own business ecosystem.
Just like the large systemically important banks and other financial institutions in 2008, key technology players know they are serving a public infrastructure role: if they are put out of business by the EU regulators’ fines, the global digital economy, including the EU’s small and medium players, will be crippled.
Since banks lend out most of the cash they receive in deposits (see fractional-reserve banking), it is difficult for them to quickly pay back all deposits if these are suddenly demanded, so a run renders the bank insolvent, causing customers to lose their deposits, to the extent that they are not covered by deposit insurance.
(1998), for instance, define currency crises as occurring when a weighted average of monthly percentage depreciations in the exchange rate and monthly percentage declines in exchange reserves exceeds its mean by more than three standard deviations.
In general, a currency crisis can be defined as a situation when the participants in an exchange market come to recognize that a pegged exchange rate is about to fail, causing speculation against the peg that hastens the failure and forces a devaluation.
One factor that frequently contributes to a bubble is the presence of buyers who purchase an asset based solely on the expectation that they can later resell it at a higher price, rather than calculating the income it will generate in the future.
Well-known examples of bubbles (or purported bubbles) and crashes in stock prices and other asset prices include the 17th century Dutch tulip mania, the 18th century South Sea Bubble,the Wall Street Crash of 1929, the Japanese property bubble of the 1980s, the crash of the dot-com bubble in 2000–2001, and the now-deflating United States housing bubble.
When a country that maintains a fixed exchange rate is suddenly forced to devalue its currency due to accruing an unsustainable current account deficit, this is called a currency crisis or balance of payments crisis.
While devaluation and default could both be voluntary decisions of the government, they are often perceived to be the involuntary results of a change in investor sentiment that leads to a sudden stop in capital inflows or a sudden increase in capital flight.
Some economists argue that financial crises are caused by recessions instead of the other way around, and that even where a financial crisis is the initial shock that sets off a recession, other factors may be more important in prolonging the recession.
In particular, Milton Friedman and Anna Schwartz argued that the initial economic decline associated with the crash of 1929 and the bank panics of the 1930s would not have turned into a prolonged depression if it had not been reinforced by monetary policy mistakes on the part of the Federal Reserve,
The mismatch between the banks' short-term liabilities (its deposits) and its long-term assets (its loans) is seen as one of the reasons bank runs occur (when depositors panic and decide to withdraw their funds more quickly than the bank can get back the proceeds of its loans).
This generates a mismatch between the currency denomination of their liabilities (their bonds) and their assets (their local tax revenues), so that they run a risk of sovereign default due to fluctuations in exchange rates.
Kindleberger, have pointed out that crises often follow soon after major financial or technical innovations that present investors with new types of financial opportunities, which he called 'displacements' of investors' expectations.
More recently, many financial crises followed changes in the investment environment brought about by financial deregulation, and the crash of the dot com bubble in 2001 arguably began with 'irrational exuberance' about Internet technology.
Also, if the first investors in a new class of assets (for example, stock in 'dot com' companies) profit from rising asset values as other investors learn about the innovation (in our example, as others learn about the potential of the Internet), then still more others may follow their example, driving the price even higher as they rush to buy in hopes of similar profits.
If for any reason the price briefly falls, so that investors realize that further gains are not assured, then the spiral may go into reverse, with price decreases causing a rush of sales, reinforcing the decrease in prices.
In particular, the Basel II Accord has been criticized for requiring banks to increase their capital when risks rise, which might cause them to decrease lending precisely when capital is scarce, potentially aggravating a financial crisis.
Contagion refers to the idea that financial crises may spread from one institution to another, as when a bank run spreads from a few banks to many others, or from one country to another, as when currency crises, sovereign defaults, or stock market crashes spread across countries.
However, economists often debate whether observing crises in many countries around the same time is truly caused by contagion from one market to another, or whether it is instead caused by similar underlying problems that would have affected each country individually even in the absence of international linkages.
Recurrent major depressions in the world economy at the pace of 20 and 50 years have been the subject of studies since Jean Charles Léonard de Sismondi (1773–1842) provided the first theory of crisis in a critique of classical political economy's assumption of equilibrium between supply and demand.
In the long-run, however, when one considers the combined economic activity of all successfully-operating business, it is clear that less money (in the form of wages) is being returned to the mass of the population (the workers) than is available to them to buy all of these goods being produced.
The viability of this theory depends upon two main factors: firstly, the degree to which profit is taxed by government and returned to the mass of people in the form of welfare, family benefits and health and education spending;
Given the extraordinary capital expenditure required to enter modern economic sectors like airline transport, the military industry, or chemical production, these sectors are extremely difficult for new businesses to enter and are being concentrated in fewer and fewer hands.
World systems scholars and Kondratiev cycle researchers always implied that Washington Consensus oriented economists never understood the dangers and perils, which leading industrial nations will be facing and are now facing at the end of the long economic cycle which began after the oil crisis of 1973.
For example, some models of currency crises (including that of Paul Krugman) imply that a fixed exchange rate may be stable for a long period of time, but will collapse suddenly in an avalanche of currency sales in response to a sufficient deterioration of government finances or underlying economic conditions.
Likewise, in Obstfeld's model of currency crises, when economic conditions are neither too bad nor too good, there are two possible outcomes: speculators may or may not decide to attack the currency depending on what they expect other speculators to do.
In these models, asset purchases by a few agents encourage others to buy too, not because the true value of the asset increases when many buy (which is called 'strategic complementarity'), but because investors come to believe the true asset value is high when they observe others buying.
In such models, if the price of a given asset rises for some period of time, investors may begin to believe that its price always rises, which increases their tendency to buy and thus drives the price up further.
In this survey, they trace the history of financial crisis back to sovereign defaults – default on public debt, – which were the form of crisis prior to the 18th century and continue, then and now causing private bank failures;
- On Wednesday, October 23, 2019
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