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The Immigrant Exodus: Why America Is Losing the Global Race to Capture Entrepreneurial Talent
The Immigrant Exodus: Why America Is Losing the Global Race to Capture Entrepreneurial Talent
by Vivek Wadhwa
Edition: Paperback
Price: $13.15
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13 of 15 people found the following review helpful
5.0 out of 5 stars The most important current nonfiction book, December 28, 2012
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This is because the US ability to attract and retain highly skilled and entrepreneurial individuals worldwide is at the essence of its success. As long as the US can maintain an economic and cultural climate favorable to entrepreneurship, the US can still remain the leader in the innovation of markets for new products and services.

The author documents that the US magnet for talent has broken down due to impairing immigration policies. This is at the same time as other countries have far strengthened their own talent magnet. Historically, the US has attracted the best and the brightest and made it relatively easy to stay. But, this situation has rapidly deteriorated.

The author firsthand experience is interesting. He came from Australia with a degree in computer sciences in 1980. Within days of his arrival, he had applied and gotten a job with Xerox. Within a short 18 months he had gotten a green card. This will provide him total freedom to fulfill his full potential. And, he will soon found two successful high tech companies: Seer Technologies and Relativity Technologies creating hundreds of jobs as a result.

The author indicates that he could not have replicated his own success today. This is because he would have to wait for a decade to get a green card. Stuck in near corporate servitude with a temporary H-1B visa, he would be not only tied to his sponsoring employer but also tied to the specific job associated with his green card application. He would never have started his two companies and hundreds of jobs would not have been created. If he would have to start today, given current circumstances he would have stayed in Australia. This is obviously wrong.

Michael Bloomberg, mayor of New York City, has called our immigration policy suicidal. This is the case because if the US can't attract worldwide talent, it has lost its main competitive edge. The US, having the highest living standard, precludes it from ever being the low cost manufacturer of the World. (Germany's manufacturing prowess overcomes the high living standard handicap by earmarking the majority of its youth for trade manufacturing schools instead of college. That's a solution the US will never accept). The US has to position its economy as the one that constantly renews itself by developing new high margin markets. It can't do that if it is impairing its ability to attract high skilled talent. Yet, that is exactly what it is doing right now.

Let's look at a few numbers to better understand the situation. US citizens account for only 4% of engineering degrees worldwide; Asia (mainly India and China) account for 56% of them. Two thirds of H-1B applicants are issued for related positions in engineering and high technology. And, India and China account for two thirds of those. Thus, over 44% of H-1B applications go to Indian and Chinese engineers. This makes perfect sense since those two nations provide the majority of engineer graduates. However, the US offers only 140,000 green cards per year and limits any nation to only a 7% allocation of such green cards. This means that both China and India with each a population of over 1.2 billion providing the majority of the engineering talent worldwide get only 10,000 green card each, the same allotment as Iceland (pop 320,000) or even Liechtenstein (pop. 35,000). This situation is absurd. As a result, both Indian and Chinese engineers with H-1B visas have to wait around a decade to get a green card if ever. Many will give up and return to their home countries with thriving local opportunities. The author with other researchers estimate there are currently over 1.2 million highly skilled workers waiting in limbo for their green card. This stifles their entrepreneurship and productivity.

The author has documented that the slide in immigrant fostered entrepreneurship has already started. Just a few years ago, immigrants co-founded 52.4% of Silicon Valley companies. Within his most recent 2012 survey, this percentage had abruptly dropped to 43.9%. Similarly, the US share of total patent filings has declined from 42.8% in 1995 to 27.4% in 2010. That's even though foreigners account for a growing % of US patent filed (51% in 2011 vs only 18% in 1964).

If the US is concerned about the emerging economic competition from China and India what could it do? Probably one of the best strategies would be to attract and retain its best and brightest [from China and India] to cause a positive brain drain in favor of the US. Meanwhile, what the US does is actually attract bright Chinese and Indian minds as students and then kick them back home a short while after graduating and acquiring some training in the US. That's like US foreign aid in human capital. This could only accelerate China and India's economic rise relative to the US. In 2011, 160,000 students left China for the US. But, the number of graduates returning to China amounted to 180,000 in 2011 up from only 50,000 in 2008 (pg 42-43). The reverse brain drain has started.

Economic competition is all about international human capital. And, based on immigration policy related to the skilled the US has already lost this race to many other countries such as Australia, Canada, China, Germany, and Singapore (Chapter 5). Australia with only a tenth of the US population issues nearly as many green card equivalents! All those countries have immigration policies related to the skills that are far more hospitable and inviting than the US. Their policies have much in common. First, they recognize and value human capital (their immigration policies are highly selective on that count). Second, they provide permanent residency permits a lot easier and faster than the US does for the targeted skilled workers. In many of those countries, immigrants can apply for permanent residency before moving to the country and often receive such permit while still being in school before entering the labor force. This contrast with the 10 year purgatory Indian and Chinese engineers suffer in the US.

The author does not mention India among those countries fostering immigration. This is for a simple reason: it has an abundance of homegrown talent. And, India has far improved the local opportunities for such talent. Bangalore rivals Silicon Valley. Major US high tech companies such as Google, Amazon, and Microsoft have all huge operations in India. As a result, Indians increasingly stay home. From 1964 to 2001, 30% of Indian graduates from the Institutes of Technology went to the US. Between 2002 and 2008 that number declined to only 9%. This rapid decline is due to both faster relative economic growth in India and really restricting US immigration policies for Indians.

The author's recommendations to fix our immigration policy make a lot of sense. They include boosting the number of green cards available to skilled immigrants. The 7% cap per nation should be eliminated. The spouses of H-1B holders should be allowed to work and have driving licenses. H-1B visas should not be restricted to a specific employer, and related green card applications should not be restricted to a specific job. Those recommendations seem so obvious and humane, it is sad that they are even necessary. Meanwhile, the immigration debate in Washington is solely dominated by the issue of the porous border with Mexico. The US only ignores the issue of skilled immigration raised by the author at its own economic risk.

How To Improve Your Mind: 20 Keys to Unlock  the Modern World
How To Improve Your Mind: 20 Keys to Unlock the Modern World
by James Robert Flynn
Edition: Paperback
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20 of 21 people found the following review helpful
3.0 out of 5 stars A good not great book on critical thinking, December 27, 2012
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This book teaches how to think critically. My rating reflects that I have come across many other books that provide more effective tools to filter the distortion of the Media. Those books include: Sherry Seethaler's Lies, Damned Lies, and Science: How to Sort Through the Noise Around Global Warming, the Latest Health Claims, and Other Scientific Controversies (FT Press Science). Her 20 tools summarized in the conclusion are far better than Flynn's 20 keys. Keith Stanovich's What Intelligence Tests Miss: The Psychology of Rational Thought offers a more coherent framework with mindware gaps (similar to Flynn's keys) regarding the knowledge you must acquire to exercise critical judgment, and contaminated mindware (Flynn's anti-keys) that represent the myths you have to get rid off to exercise rational judgment. Sherman Stein's Survival Guide for Outsiders: How to protect yourself from politicians, experts, and other insiders is also much clearer and effective than Flynn. Gerd Gigerenzer's Calculated Risks: How to Know When Numbers Deceive You is also superior. It focuses a lot on the Bayesian Theorem that Flynn completely ignores. Given that Bayesian statistics affect just about everything when it comes to hypothesis, probability, interpretation of medical tests, etc... this is a huge gap in Flynn's book.

Some of the choices of Flynn's 20 keys appear too narrow. If you were thinking of 20 most powerful tools to teach someone critical thinking would you include on this most selective list such concepts as: universalizability (1), tautology (2), and IQ (7). Actually, all the other 17 keys would not warrant a spot in the top 20 tools to teach critical thinking. This is for two reasons. First, those concepts are too narrow and sometimes even trivial on a stand-alone basis. Second, some of those concepts should be treated together to become meaningful. For example, several of Flynn's keys belong to an introduction in statistics and all his anti-keys would be covered by an explanation of the scientific method.

Flynn's book is certainly not all bad. It is often very good. Within the body of the book, despite his awkward 20 key selection for critical thinking, he does a good job of covering what it takes to think critically. His 5 part curriculum includes: 1) logic & philosophy, 2) statistics, 3) economics, 4) the scientific method, and 5) political sciences. Thus, Flynn invariably expands way beyond the narrow confine of his keys. Except for missing out on Bayesian statistics, Flynn does a good job of developing the necessary curriculum to think critically. However, any of the other books mentioned, for the most part, will get you there more effectively.

Some passages are excellent.

The first four chapters out of five on economics (The Market and its Church) are excellent. His explaining the nature of money, basic economics, money and banking, and the 2008 financial crisis are very good. His concept of assessment inflation and the failings of credit ratings are great.

Some sections within the statistics chapters are very good. He discloses within Box 6.1 (pg. 53) a great short cut to calculate the error margin of a poll I had never seen anywhere else. I tested, and it works. His explanation of the regression to the mean is also original and clear. His exploring confounding variables and the associated concept of "correlation does not entail causation" is also excellent.

Part 4 on the scientific method is excellent even if it is somewhat self-evident for anyone who has given this concept much consideration. How much time does one need to figure that Intelligent Design is not a scientific concept? Using Flynn's own semantic, is this not a bit too tautological?

Part 5 on political science is interesting. But, it over-reaches. Flynn admits foreign policy is a very complex arena that is hard to either predict or even understand using deterministic theories such as the ones he covers including: Realism, Liberalism, and Constructivism. This chapter sometimes seems like a venue for Flynn to express and justify his own political views on what nations should do. This is a very interesting but separate subject best treated in a different book. The other recommended books on critical thinking wisely did not tread on this murky domain.

Flynn is on weaker grounds when he offers economic recommendations and assessments.

His personal recommendations to resolve the 2008 crisis is wrong a full four years after the fact. He recommends that US banks should have been nationalized just as in England. Yet, four years later the US banking system is on far stronger financial footing than its counterparts in England or anywhere in Europe.

When Flynn foresees that "Europe may bring many US banks down, no matter what America does"; he overlooks that US banks have virtually no credit exposure to the European peripheral countries (Italy, Greece, Spain, Portugal). When he foresees that "we may see the most serious depression since the Great Depression" he simply extrapolates the vicious cycle of Government defaults and their associated insolvent banks worldwide. But, this situation is confined to the Euro Zone and has been confined for over four years. The relevant sovereign bond yield trends suggest the situation is getting better not worse.

In the conclusion, Flynn discloses that he developed a test to measure people's critical thinking proficiency: Flynn's Index of Social Criticism (FISC). It would have been most interesting if Flynn shared this test (or a shorter version of it) with his audience so readers could test whether they "got it" or not after reading this book. I suspect FISC is very challenging and would trip many sharp minds on various topics. I am sure when testing for his Sociologist's fallacy concept; it is most easy to trip on those questions.

A good deal of critical thinking can boil down to exploring just three questions. Is an issue resolvable by examining any data? Is the data supportive of the theory advanced? What is the quality of the data? And, the other recommended books provide more directly the tools to answer those questions.
Comment Comments (4) | Permalink | Most recent comment: Aug 21, 2014 8:37 PM PDT

Hiding the Decline
Hiding the Decline
by A. W. Montford
Edition: Paperback
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14 of 16 people found the following review helpful
3.0 out of 5 stars An important document, not a great book, December 22, 2012
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This review is from: Hiding the Decline (Paperback)
In 2010, Montford wrote one of the best books on Global Warming and the corrupted climatology community "The Hockey Stick Illusion." The Climategate incident occurred in late 2009, when he had nearly completed that book. He will delay the completion of his book to cover Climategate in one 50 page long last chapter. Within it, he discloses tens of the most outrageous emails that reflect on the most corrupted scientific community. But, Climategate will go on for another two years beyond the release of his first book. And, this sequel is essentially following up on Climategate to cover the subsequent official investigations that will whitewash and exonerate the climatology community while entirely ignoring the incriminating works of Steve McIntyre. Given the nature of those investigations we don't learn much we did not know after reading The Hockey Stick Illusion: Climategate and the Corruption of Science (Independent Minds).

This is not to say that this book does not have merit. It is an important public document capturing well Climategate in its entirety. It also informs about a few other shenanigans that climatologists did to manufacture temperature replications. Focusing on related technical data issues, this book reinforces some insights and offers a few new ones.

The first confirmed insight is that tree ring temperature proxies are unreliable. Tree rings widths differ for numerous reasons besides temperature. Invariably, many tree ring temperature proxies will completely diverge from actual temperature records. This is the main subject of the book: Keith Briffa's tree ring generated temperature proxies that show a declining temperature trend post 1960. This is just the opposite vs the two famous hockey stick patterns generated by Michael Mann and Phil Jones respectively. The related graph is on the cover of the book and Figure 4.2 on page 87. Jones did the "Hiding the Decline" bit by either truncating Riffa's series to 1960, or fusing it post 1960 with actual temperature records. Those various subterfuges are graphed on pg 88, 89, 173, 174. This allowed Mann, Jones, and Riffa to present to subsequent IPCC assessments that the Hockey Stick temperature record pattern had been independently reconstructed by all three of them. What kind of independence is that?

Another insight is that actual temperature records are not as accurate as "actual" entails. Records from China are of terrible quality. Doug Keenan uncovered that out of 84 Chinese meteorological stations series 49 have no history and another 35 had been relocated or were deemed inconsistent. Only 7 or less than 10% of them have adequate consistent temperature history data. Yet, Phil Jones will use the entire Chinese data when building his worldwide temperature records (pg 49, 50). A junior researcher, Ian Harris, in charge of compiling data confirms unreliable time series is a common problem for other regions. He mentions that data from Australia is nearly as bad as China's (pg. 165). He then states "shouldn't usually plot past 1960 because these will be artificially adjusted to look closer to the real temperatures." That statement is an email from Climategate disclosed on pg. 166.

There is another reason why temperature records are inaccurate: the well known urban island effect whereby temperature rises as urban density increases. Phil Jones is the climatologist that first uncovered this effect in the 90s. But, ultimately he will disregard it to preserve the upward trend of the hockey stick.

Climatologists data fabrications have a predictable pattern. Old temperature proxies are manipulated so that temperatures in the past centuries are deemed low and newer ones are deemed high. This is to flatten the Warm Medieval Period and create the hockey stick pattern. Montford extensively covered that in "The Hockey Stick Illusion" by showing that Michael Mann's short-centring Principal Component Analysis method was flawed and created hockey stick patterns out of random data (Steve McIntyre's work). Other fabrications related to the mentioned "actual" temperature records over the past 150 years that are tweaked to confirm the abrupt rise in temperature in recent times.

The Cost Disease: Why Computers Get Cheaper and Health Care Doesn't
The Cost Disease: Why Computers Get Cheaper and Health Care Doesn't
by William J. Baumol
Edition: Hardcover
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23 of 25 people found the following review helpful
2.0 out of 5 stars The danger of 100 year extrapolations, December 14, 2012
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The basic premise of the book seemed so intriguing. In a nutshell, US healthcare spending is virtually uncontrollable and will go through the roof; but, we will very easily be able to afford those costs.

Baumol projects healthcare spending to rise from 15% of US GDP in 2005 to 62% in 2105. But, not to worry because overall we will be over 8 times wealthier as our GDP per capita will rise from $41,800 to $343,000. Given that, it will be so easy to spend nearly 2/3 of every dollar on healthcare.

However, Baumol's extrapolations 100 years down the road are meaningless if not completely wrong. To understand how he derived his 2105 projections you have to read carefully note 13 on page 187.

For healthcare spending as a % of GDP, Baumol observed that they grew by 1.41% per year over the 1995-2005 decade. So, here is how he got the healthcare spending of 62% of GDP: 15%(1 + 1.41%)^100 = 60.8% (I got a different figure because of decimal figures). This same logic suggests that by 2140 or just 35 years later, healthcare will account for 100% of GDP. This does not make any sense. The 62% by 2105 does not make any more sense than the 100% by 2140. Taxes, housing, other consumptions of goods and services, business investments, Government spending can't so readily be squeezed into our remaining 38 cents on the dollar (1 - 62% allocated to healthcare).

When it comes to real GDP per capita, Baumol took the 2005 level of $41,800 and used the 2.13% average annual growth rate in this measure over the 1950 to 2001 period. His calculation: $41,800(1 + 2.13%)^100 = $343,000. Now do you believe that in 2105 we could possibly be over 8 times wealthier than we are currently? This entails that our prospective economy will be far greater than 2 times the current World economy (when you factor US population growth). If we grasp what that entails in terms of World's resources and industrial capacity, this extrapolation does not make sense. So, what went wrong? It is simple. Baumol used a 2.13% GDP per capita growth rate that captured the post WWII economic boom. And, this growth rate does not resemble at all the relevant current trend. When looking at this same measure over the 1990 - 2011 period, this growth rate plummets to 1.38%. If we focus on the 2000 - 2011 period it further drops to only 0.70%. Using this last growth rate and current GDP per capita level ($42,906 in 2011), you get a GDP per capita of $82,658 in 2105 only 24% of Baumol's level. Instead of predicting we will be over 8 times wealthier; this more realistic projection suggests we will be less than twice as wealthy as currently. And, even this level may be taken with a grain of salt. What will it truly mean in terms of resource constraint, living standard, and purchasing power parity with other countries?

Where Baumol's Cost Disease theory go astray? His basic rational is that labor productivity in the "progressive sectors" (industries with fast labor productivity such as high tech) drive overall wage earnings including the ones within the "stagnant sectors" (sectors with no labor productivity increase such as healthcare and education). This perfectly explains "why computers get cheaper and healthcare doesn't" (subtitle of the book). But, this certainly does not mean that one specific single stagnant sector (healthcare) will inevitably take over the economy. This proposition is absurd in itself given that there are so many other stagnant sectors to begin with. For healthcare to take over, it would need to squeeze out not only all the progressive sectors but also all the other stagnant sectors into this minuscule 38 cents on the dollar slice of the economy.

There is another reason that even all stagnant sectors combined will not take over the economy relative to the progressive ones. That reason is the famous Jevons Paradox. The latter states that increase in efficiency do not lead to increase in savings; they lead instead to increase consumption.

The Jevons Paradox contradicts the Cost Disease theory. Computers indeed got cheaper as the Cost Disease suggests. But, spending on computers and related hi tech appliances has gone way up (think not only of PCs but laptop, tablets, smartphones that did not exist just a few years ago) as Jevons Paradox suggests. So contrary to what Baumol thinks there is no reason for the stagnant sectors to gain share of the economy relative to the progressive sectors. In fact, the opposite is not unlikely.

The Cost Disease theory embeds many other contradictions besides the Jevons Paradox. Regarding healthcare spending, how could our wages be depressed by the rising cost of healthcare benefits since it is our own wage rate increases that supposedly set the cost increase of such healthcare prices?

Baumol's proposition that we can readily afford rapidly rising healthcare cost is laughable. Those costs are bankrupting the US fragile fiscal position as any CBO projections show. They are much reducing the competitiveness of US domestic manufacturers and have lead to off shoring manufacturing capacity. Municipalities, corporations, and household budgets have all felt the crippling impact of rising in healthcare costs.

The rising costs of healthcare and college education are indeed problems. But, it is not so much because of the Cost Disease (which primarily addresses the rising wages of employees within those industries). And, Baumol's own data proves that.

Regarding healthcare, Baumol discloses a graph (pg. 13) that shows that medical employees (doctors, nurses) salaries have grown at nearly exactly the same pace as inflation (3% to 4%). But hospital costs have grown far faster by 8% a year (graph pg. 7). Thus, the staggering rise in healthcare costs is related to factors outside the Cost Disease domain.

Turning to college education, Baumol shows that college tuition and fees have risen at 7% a year or far faster than inflation (graph on page 8). Meanwhile, wages of professors and other employees have risen a lot slower than inflation (graph pg. 13). Thus, college education costs have risen very fast for reasons outside the Cost Disease.

Given that his analytical framework is so off, Baumol's policy recommendations are of little interest. The chapters written by his coauthors in part 2 of the book regarding how to reduce the growth of healthcare costs and other stagnant services are reasonably good and interesting. But, they are lost in Baumol's book whose main thesis is wrong.
Comment Comments (4) | Permalink | Most recent comment: Nov 18, 2013 10:57 PM PST

Are You a Stock or a Bond?: Identify Your Own Human Capital for a Secure Financial Future, Updated and Revised
Are You a Stock or a Bond?: Identify Your Own Human Capital for a Secure Financial Future, Updated and Revised
by Moshe Arye Milevsky
Edition: Hardcover
Price: $22.49
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33 of 34 people found the following review helpful
2.0 out of 5 stars His human capital valuation is inflated and his framework falls apart, December 12, 2012
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The author valuation of human capital embedded on a personal balance sheet is way inflated. And, it gives you the illusion to be far richer than you really are. This flawed framework leads the author to recommend taking on an absurd investment risk level.

Let's work through one of his examples regarding the finances of a college professor (pg. 96 - 99). The professor makes $100,000 a year. He translates this yearly wage into a PV worth several million dollars of a very safe bond portfolio on the professor's asset side of the balance sheet. However, this is an absurd value giving the professor illusion of riches he does not have. It ignores the professor's income taxes, mortgages, property tax, living expenses for his family, etc... If the author wanted to figure out the PV of the professor's earnings stream he should have focused on the professor's yearly net savings after all expenses are paid and not his entire wage before taxes.

Given that the author has estimated that the professor has the equivalent of several million dollars in liquid assets he does not have; the author goes on recommending a dangerous investment strategy. It entails leveraging the professor's existing $250,000 investment portfolio to $700,000 by borrowing $450,000; and investing the entire $700,000 in the stock market!

That the author can make such a recommendation after the stock market just blew up twice in the past decade is mind-boggling. A 35% drop in the stock market would entirely wipe out the professor's leveraged stock portfolio. The S&P 500 dropped by 48% between March 2000 and September 2002. It also dropped by 56% between October 2007 and March 2009. Also, borrowing $450,000 at let's say 3% will cost the professor $13,500. This recommendation not only wipes out the professor's investment portfolio, but his yearly savings too. It could cause him to default on his mortgage and incur a foreclosure.

Given that the author's core framework is so dangerously flawed, any other criticism will be trivial in comparison. Nevertheless, the author is on soft ground in other areas.

On page 67, he recommends that individuals reconstruct region by region an international stock portfolio instead of investing directly in a diversified international fund. This is to seek higher returns and lower fees. The opposite is more likely because the investor will need to rebalance his international exposure often. That will result in extra transaction costs and taxes.

The author's concept of time diversification (solely holding positions for the long term) is primitive. True time diversification entails disaggregating your portfolio in several buckets with different term horizon (one for emergency/liquidity, one for college savings, another for retirement).

His recommendations on asset diversification are often meaningless 20/20 hindsight. On page 81, he indicates that someone diversified equally across stocks, gold, and US Dollar currency would have weathered the recent financial crisis. The fact that this portfolio held up well in one single set of circumstances does not mean it is a viable long term strategy as 2/3d of the portfolio would earn no economic return but simply represent speculative positions.

He acknowledges the staggering cost of nursing home (pg. 109), but only mentions in a single sentence the need for long term care insurance hundred pages later with no further explanation.

On the positive side, the author shares a few interesting calculations. On page 84, he shows a simple calculation that allows you to convert average return into geometric return (same as IRR). The IRR calculation is: Average return - 0.5(Standard deviation)^2. I tested it, and it works. Throughout the book, the author comes up with interesting calculations I have not seen elsewhere.

The author talks at length about life insurance. His section on how much life insurance you need (pg 45-47) is the best part of the book. However, even within the insurance sections there are contradictions. Regarding the nature of term insurance, he states on page 48: "your monthly premiums are guaranteed for the term of the insurance" only to contradict himself on page 50: "With term insurance, your premiums increase each year."

Regarding post-retirement disinvesting he is big on annuity products (chapter 10). His very conservative recommendation to annuitize the majority of your retirement funds contrasts with his unbearably risky investment recommendation prior to retirement (the college professor bit). His asset annuitization certainly has merit. But, it is overdone. On page 174, 175, the author salivates at the 6.8% yield the annuities provide as shown in Table 9.3. However, those annuities are a lot less attractive when you consider a 65 year old would have to live till 86 to simply recover his initial premium adjusted for inflation. Thus, transferring lifespan risk to an insurer will most probably cost you. Additionally, the level of annuitization the author recommends pretty much wipes out your estate (pg. 199). When you factor Social Security that is a superior annuity rising with inflation, the level of annuitization needed may be less than the author recommends.

Overall, this is a poor book on financial planning. As a far superior alternative I recommend: The Random Walk Guide To Investing.
Comment Comments (4) | Permalink | Most recent comment: Apr 6, 2013 6:19 PM PDT

Are We Getting Smarter?: Rising IQ in the Twenty-First Century
Are We Getting Smarter?: Rising IQ in the Twenty-First Century
by James Robert Flynn
Edition: Paperback
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16 of 17 people found the following review helpful
5.0 out of 5 stars Only Flynn understands the Flynn Effect!, December 7, 2012
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I am not just kidding. Flynn uncovered in the early 80s that individuals' IQs gained about 3 pts per decade (Box 13, pg 74). Nearly 30 years later professionals within clinical psychology, education, law, and healthcare still ignore the impact of the Flynn Effect on their respective cognitive measurements.

He documents the critical consequences of ignoring the Flynn Effect. In the US any criminal with an IQ two full standard deviations below the average (IQ of 70) is deemed incompetent to stand trial and exempt from the death penalty. But, the majority of IQ tests are obsolete. An individual can get an IQ score of 76 (6 pts above incompetence) solely because of the test being outdated. Educators' assessment of children being gifted or cognitively impaired can be highly inaccurate. Giving an old test to children inflates their IQs. As a result, the selected gifted group will be far larger than it should be and many of the children needing special assistance will be ignored. The Flynn Effect also affects memory loss tests. And, health care professionals routinely administer obsolete tests. By doing so, they diagnose elderly individuals as doing just fine when they do need assistance in living.

Flynn proposes two solutions to resolve the Flynn Effect. The first one is updating tests frequently. The second one is adjusting scores downward by 0.3 pts per year. So, someone with an IQ of 120 associated with a test normed 20 years ago would have an adjusted IQ of 114. Somehow, the professions have rejected either approach.

Flynn considers intelligence a relative concept that needs to factor age of individuals (cognitive capabilities have their own lifecycle) and contemporary social context (Flynn Effect). Our society has become increasingly complex especially at work. And, that is the primary cause of our increasing IQ scores over time. Are we getting smarter? On page 163, he answers his own question: "I cannot give an absolute measure of the ability to classify or use logic... but I can say we are much better at both today than our ancestors were in 1900." So, the straightforward answer is "yes, we are."

Flynn contemplates whether developing nations will catch up with developed ones on IQ tests. He debunks many arguments related to climate, nutrition, and health; as he finds they do not cause IQ increases. Instead, IQ results from GDP growth that entails a society becoming increasingly complex. He notes that the IQ of developing nations is often rising rapidly. But, so are the ones of developed countries (Box 11, pg. 57). The issue is whether the societies of the developing world will catch up to the complexity of the developed ones. Some will and make the transition from developing to developed countries such as many Southeast Asian countries have.

Flynn observes that IQ changes with age, especially IQ subcomponents. And, the aging pattern is different for individuals of various brightness levels. The very bright tend to lose more of their analytical skills with age than the not so bright ones. This is because they progressively lose some of their analytical skills upon retirement. The remedy for them is to simply remain actively engaged in research and studies throughout retirement as he has done himself. Flynn is 78. But, with more leisure time in retirement, bright people communicate and socialize more. So, their vocabulary keeps on improving (Box 24, pg. 116).

Flynn observes that girls are far better students than boys. In all reviewed countries, girls have a huge advantage in reading (Box 31, pg 148). Better prepared, many more females go on to university than males. Yet, males average IQs in university are much higher than females. So, some derive that men are more intelligent than women. This is wrong. The males that go on to university represent a smaller self-selected sample than the females. It only makes sense that their average IQs would be higher than females. Flynn notices that in developing countries, women IQs are often lower than men. But, this is solely due to their being deprived of education and working opportunities. Flynn states on pg 157: "I believe that whether or not women achieve [IQ] parity with men is a good test of whether a society has achieved full modernity [men and women civil rights equality].

Flynn explains the superiority in academic achievement of the Asian Americans. By the 1980s, they represented only 2% of the American population, but already accounted for 14% of the students at Harvard, 16% at Stanford, 20% at MIT, 21% at Cal Tech, and 25% at Berkeley (pg. 177). Today all those percentages are much higher. Many believe this group has a far higher IQ. Flynn suggests this is not the case. Just like women are better students and are over-represented vs men in universities so are Asian Americans vs other Americans. It is the exact same issue. Both groups, women and Asian Americans study a lot harder than their counterparts. As a result a far larger percentage of their respective population goes onto universities. It is just that this trend is even more pronounced for the Asian Americans. Flynn states: "... it was not higher IQ scores but sociology of the family [tiger-moms and overall work ethics] that explains the remarkable academic achievements of the Asian Americans."

Within the nature-vs-nurture debate Flynn falls strongly on the nurture side. For him, nurture is having the opportunity to live and work within a complex society. Thus, Flynn weighs much less than his counterparts on nature (intelligence being inherited). Yet, when he addresses the studies on twins (pg. 167 - 169) that demonstrated that nature was a very strong factor (twins brought up apart end up having the same IQ regardless of environmental circumstances); he appears hard pressed to effectively rebut it. He goes on a long explanation regarding an "individual multiplier" that actually confirms the very "nature" argument he attempts to rebut.

In the end, intelligence is probably much less inherited than Flynn's counterparts (Jensen, Murray) suggest; but it is much more than Flynn advances. If you find this topic interesting, I also recommend Flynn's earlier book What Is Intelligence?. If you want to study the other side of the argument check out Murray's recent book Coming Apart: The State of White America, 1960-2010.
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The Physics of Wall Street: A Brief History of Predicting the Unpredictable
The Physics of Wall Street: A Brief History of Predicting the Unpredictable
by James Owen Weatherall
Edition: Hardcover
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84 of 95 people found the following review helpful
5.0 out of 5 stars A great history of the evolution of modern finance, November 28, 2012
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Weatherall tells that contrary to what we know, Warren Buffet is not the US best investor. The best one is Jim Simons, a brilliant physicist expert in String Theory who founded the investment firm Renaissance Technologies and its Medallion Fund. Simons returns have far outpaced Buffet's. During the recent financial crisis in 2008 when Buffet incurred a 50% loss, Simons Medallion Fund returned 80%. Other outstanding investors include Ed Thorp, James Doyne Farmer and Norman Packard. What those better-than-Buffet investors have in common is that they are all scientists instead of financial types. They use complex mathematical models to implement profitable short-term trades instead of holding stocks over the long term based on fundamentals like Buffet.

Weatherall develops a philosophy of the scientific method that permeates the whole book. Contrary to Taleb who dogmatically states you can't model anything; so, throw the entire body of modern finance out and just buy insurance (Put options); Weatherall, observes that "The model-building process involves constantly updating your best models and theories in light of new evidence."

Weatherall starts the history of modern finance with the French mathematician Louis Bachelier and his revolutionary paper "Theorie de la Speculation" published in 1900. Weatherall states: "In a just world, Bachelier would be to finance what Newton is to physics." Indeed, Bachelier was the first to figure that stock prices captured all information and moved randomly. He explained the related random walk of stock prices. He was a pioneer in applying probability theory to financial markets. He specified the Efficient Market Hypothesis without naming it. The latter will be articulated by Eugene Fama in 1965. Bachelier also innovated an option pricing model based on the arbitrage free principle he also developed. The related Black Scholes option model will be developed much later in 1973. Paul Samuelson uncovered Bachelier's paper in 1955 and was stunned. Bachelier had figured out the mathematics of financial markets that Samuelson was working on at the time. Thus, Bachelier was over half a century ahead of his time.

Next, Weatherall introduces Maury Osborne, an American astrophysicist who will make a key improvement to Bachelier's theory in his seminal 1959 paper "Brownian Motion in the Stock Market." Osborne uncovered that stock price movements follow a log-Normal distribution instead of a Normal distribution as Bachelier advanced. It is stock returns that follow a Normal distribution. This represented a critical improvement over Bachelier's initial theory.

Weatherall, next moves on to Benoit Mandelbrot, a French mathematician, who developed fractal geometry. He uncovered that stock price returns are wilder than the Normal distribution suggests. They are better captured by distributions with fatter tails denoting a higher frequency of extreme events. But, Mandelbrot's work will be rejected because finance theory already developed a large body of useful models based on Osborne's assertion that stock returns follow a Normal distribution. And, Mandelbrot did not offer any pragmatic model alternative. If you want to study Mandelbrot's work further, check out his The Misbehavior of Markets.

Next in chapter 4, we meet three star mathematicians including Ed Thorp, Claude Shannon (inventor of Information Theory) and John Kelly (the Kelly criterion). This chapter is a summary of the excellent book Fortune's Formula: The Untold Story of the Scientific Betting System That Beat the Casinos and Wall Street. Thorp, with assistance from Shannon and Kelly, will develop innovative methods on optimizing strategies at Black Jack by combining his new card-counting method with the Kelly criterion that tells when a player has a probabilistic advantage over the house. Next, Thorp makes a fortune by applying the Kelly criterion to financial markets. He develops a computer driven option pricing model and the related "delta hedging strategy" that entails selling warrants short and buying the related stock. Thorp is another better-than-Buffet investor. Either through a hedge fund or privately, Thorp recorded 20% return per year for 45 years and is still doing it. In 2008, one of his bad years, he still made 18% at the same time that Buffet was experiencing a 50% loss.

Chapter 5 covers the story of the Black Scholes option model developed in 1973 and its main protagonists: the physicist Fischer Black, the economists Myron Scholes and Robert Merton. This chapter is a summary of another great book: Fischer Black and the Revolutionary Idea of Finance. Jack Treynor introduced Black to CAPM in 1968. In 1969, Black ties CAPM and arbitrage free considerations to develop option pricing. Scholes joins Black in resolving the advanced math equations to put together the Black Scholes model published in 1973. Robert Merton develops the same model independently at nearly the same time. Scholes and Merton will receive the Nobel prize in economics for it. Black would have too, but he passed away several years before his colleagues received it.

The same chapter 5 outlines why physicists and mathematicians have gravitated to Wall Street. In earlier times, the main career outlet was the Government such as the Department of Defense (German code cracking and Manhattan Project during WWII, Cold War, Game theory), NASA (race to put the first man on the moon). But, after 1969 when Neil Armstrong became the first man to step on the surface of the moon, the urgency for such endeavors evaporated. And, the job market for physicists collapsed. The end of the Cold War also depressed this job market. In 1984, Black leaves academia for Goldman Sachs. He is one of the first and most notorious quant on Wall Street. Crowds of them will soon follow.

The next chapter covers the intriguing "The Prediction Company" an investment company co-founded by two physicists: James Doyne Farmer and Norman Packard. At first, Farmer and Packard have fun improving upon the roulette prediction that Thorp and Shannon had developed years earlier. Farmer and Packard will translate their roulette calculations into major contributions to Chaos Theory. They co-found The Prediction Company in 1991 that will be soon acquired by O'Connor, a hedge fund. The latter will be purchased by Swiss Bank Corp. But, The Prediction Company will operate as an independent subsidiary. Farmer and Packard will throw everything they know at the financial markets including Chaos theory, statistical arbitrage with genetic algorithms, and Mandelbrot concepts such as "wild" randomness and fat tails. They will develop different models and look for consensus between their valuations before implementing trades. And, they will become very successful investors.

The successes of Jim Simmons, Ed Thorp, Farmer and Packard leads Weatherall to an interesting take on the Efficient Market Hypothesis (EMH). For the markets to be efficient, one investor has to conduct a trade at anyone time so the market price fully reflects all information. This first trader reaps the gains and renders the market efficient for the rest of us. And, all the mentioned investors had this uncanny ability to be this first trader over many years. This suggests that the market is somewhat inefficient. But, the hurdle rate to reap profits from inefficiencies is extremely high. You have to beat Simmons, Thorp and company to be the first investor to capture the inefficiency.

The next chapter is about Didier Sornette, originally a geophysicist turned polymath with a wide range of expertise including economics and finance. He is the world expert on predicting extreme events ranging from earthquakes, tectonic plate movements, and even stock market crashes. For him all those rare catastrophic events leave a forewarning signature in the data consisting in an acceleration (log-periodic pattern) of smaller events leading to the eventual catastrophically larger event. Through his diagnosing those log-periodic patterns, he perfectly predicted the stock market crash of October 1997 and made a 400% return by buying cheap way-out-of-the money Puts on stock indexes. With his log-periodic patterns, he also predicted the dot-com crash in early 2000 and the financial crisis crash of September 2008. So, contrary to Taleb Sornette suggests that Black Swans are sometimes predictable. If you are interested in his work check out his Why Stock Markets Crash: Critical Events in Complex Financial Systems. This is not an easy read. However, Taleb himself gives it a 5 star rating.

In the conclusion Weatherall defends physicists' influence on finance when it is often viewed as nefarious. He takes on behavioral economists who dismiss any quantitative models suggesting they can't capture the complexity of humans. Weatherall rebutts that a better understanding of individual response (Weber-Fechner law) contributed to Osborne's improvement in modeling of stock prices. Also, Didier Sornette incorporated herding behavior in modeling occurrence of financial calamities. Thus, the two fields of behavioral economics and physics are complementary. Next, he addresses Taleb's take that we should throw all models away because they can't anticipate rare events. Weatherall thinks this nihilist position is misguided. Sure, models will never be all prescient. But, following the evolution he documents throughout this book, models are constantly improving. Those improvements increase our understanding of our financial environment. Didier Sornette's work has improved our understanding of the occurrence of rare events. Is there any merit in burning Sornette's work? No. The third criticism is that the physicists were fully responsible for the 2008 financial crisis with their toxic products (CDOs, CDS, MBS) that no one understood including themselves. Weatherall argues the financial crisis was due to institutions using models while not exercising scientific judgment and misunderstanding risk. Renaissance Technologies with the best scientists came out of the financial crisis unscathed. "Renaissance shows that mathematical sophistication is the remedy not the disease... The people charged with running the world's economies should be as good as Renaissance."
Comment Comments (16) | Permalink | Most recent comment: May 15, 2013 3:40 PM PDT

Pay: Why People Earn What They Earn and What You Can Do Now to Make More
Pay: Why People Earn What They Earn and What You Can Do Now to Make More
by Kevin F. Hallock
Edition: Hardcover
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3 of 3 people found the following review helpful
2.0 out of 5 stars Lots of info, very few insights, November 24, 2012
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In the conclusion Hallock states "This book is about why people earn what they earn and how you can make more." Actually, the book offers very few insights about either subject. The book is more about what people earn and very little else. It may be of some interest for the HR profession. It is of much less interest to anyone else especially the ones truly interested in the underlying economics of why people are paid what they are paid. Within the book there is no discussion of demand and supply for any given jobs. There is no discussion on the various causal forces affecting job demand and job pay such as globalization (off shoring, outsourcing), labor productivity (reducing demand for labor), technology (also reducing demand for labor). Given the author's sterling background in economics, I was disappointed by the lack of any relevant analysis within the book.

The author makes also a few errors. On page 12, he describes the distribution of wages as a "normal distribution." But, in Figure 2.1 on the next page you can see that the relevant histograms describe a "lognormal distribution" instead. On page 101 and 102, he states he is against the notion of curbing the risk that CEOs take on behalf of their institutions believing that as investors we can diversify away that risk by holding numerous stocks. The author does not acknowledge that CEOs within the financial sector did take egregious risks that took the worldwide financial system down. And, there was no diversifying from the ensuing financial sector driven stock market meltdown.

Some chapters are unclear. Within chapter 10 on stock options, he indicates on page 133 that traded options are very different from company stock options because they are never exercised early but can be traded. Meanwhile just the opposite is true for the company stock option. But, I wonder if trading and exercising a stock option are inherently similar. The main fact is that they render the option liquid. During this discourse, I think the author advances that company stock options are worth less than their traded counterparts; but, he indicates that employees value them more (not that employees are right). I would think that company stock options are worth less because they are restricted (long vesting period) and that you would not buy them if you had the choice as they concentrate your risk with your employer (a bad idea). But, the author does not discuss such issues. And, this section is left confusing the reader.

Often much of the text is redundant. Hallock spends an entire 35 page chapter on nonprofit compensation only to disclose in the middle of it (pg. 173 Fig 13.2) that there is essentially no difference between nonprofit and for-profit compensation once you control for age, education, industries, and job occupations. Similarly, Chapter 14 on what you can do to make more does not go beyond the self-evident. Chapter 5 on compensation strategy is based entirely on two completely hypothetical cases and feels really artificial. Many more real life examples would have been more instructive.

Other parts of the text are unexplained. The author mentions several times that in the early 1990s the use of stock options in CEO compensations skyrocketed. But, he never explains that this was due to President Clinton passing a law that restricted tax-deductible salaries to $1 million. And, this did not apply to stock options. On page 19, the author indicates that upward (and downward) mobility in wages has greatly declined across generations (intergenerational wage correlation has increased). But, he does not at all explain why. This trend is in part due to an overall change in the US labor force away from manufacturing towards information and services. Such a society puts a much higher premium on higher education and brainpower. Therefore, it sorts human capital a lot more selectively than it used to. The author does not touch on any of that.

Chapter 8 on compensation at the top (CEOs, stars, etc...) that could have been really interesting was a huge disappointment. Out of the 23 pages of this chapter, he spends only three paragraphs on the compensation of athletes, entertainers, and other stars. Otherwise, the entire chapter is disclosing what CEOs are paid and in what mix (wage vs stock options, etc...). The author always discloses a lot of info about the "what" but provides you no insight about the "why."

The author does disclose some valuable information sources. Those include O*Net online from the Bureau of Labor Statistics (BLS) to find the pay for various occupations. The BLS has also other sources within its website. You can find compensation of CEOs and other highly paid employees within the SEC schedule DEF 14A. Throughout the book, the author discloses ton of information regarding wage levels by gender, education, race and sometimes by a combination of those factors. He briefly explores related inequalities, but again without uncovering truly interesting insights on those subjects.

If you want to study the bunch of analytical gaps within this book, I would recommend The New Geography of Jobs, Coming Apart: The State of White America, 1960-2010, Who's Your City and even End of Men. Obviously, those books cover a lot more than just pay. But, they all put pay in a far more interesting context. They also explain far more why people are paid what they are paid which the author really does not touch upon.

A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation
A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation
by Richard M. Bookstaber
Edition: Paperback
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2 of 3 people found the following review helpful
5.0 out of 5 stars Great book just released before the financial crisis, November 17, 2012
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Reading this book five years after its release, one has to admire how prescient the author was. He gives you a brilliant insider account of all the ways our financial system has faltered and will falter. Less than a year after the book release the financial system crashed for reasons detailed in the book including leverage, liquidity, regulatory, and complexity issues. This book is superior to Taleb's just released Antifragile: Things That Gain from Disorder that covers the same subject.

The author explains numerous financial crises that occurred since the early eighties in technical details. However, on pg. 241, he synthesizes his analysis in just a few concise sentences. The 1987 crash was a vicious downward spiral caused by hedging actions (selling futures short associated with portfolio insurance) that reinforced the decline in stock values causing further hedging actions. The LTCM meltdown was caused by the forced asset sales at liquidation price triggered by creditors that resulted in further asset price decline. The bubble was due to the majority of traders being on the buy side of a very limited supply of hi-tech stocks that created a feedback loop of self-fulfilling prophecy. When IPOs met and exceeded investor demand, the market collapsed. In other parts of the book, he spends tens of pages on each of those crises. But, in a nutshell that is pretty much what they were about.

The key explanatory chapter is chapter 8 titled "Complexity, Tight Coupling, and Normal Accidents." Here the author explains how systems that are complex with many interconnected variables with unpredictable, nonlinear effects, that in turn are associated with tight coupling (denotes a chain-like reaction without much time to react or adapt to the consequence) are recipes for disasters. Those are called "normal accidents" meaning they are to be expected; but, you can't expect what they will be. So, you can't prevent them. "The more complex and tightly coupled the system, the greater the frequency of normal accidents." The author depicts numerous failures of complex systems with various levels of tight coupling including nuclear plants disasters (Three Mile Island, Chernobyl) and aerospace disasters (Challenger and Columbia missions that both killed seven crew members).

Financial derivatives make for perfect complex systems with tight coupling. They have numerous unpredictable nonlinear outcomes, high leverage, and lightning quick trading. Those characteristics make for what Warren Buffet called "financial weapons of mass destruction."

Adding to the vulnerability of financial complex systems is the "Butterfly Effect" (reference to Chaos theory). As financial models make even fractionally small errors, those tiny errors over multiple iterations compound and generate huge intractable outcome errors.

Another cause of complex vulnerability is scale. The business world has focused on economies of scale to extract a cost competitive edge. But, beyond a certain point scale does not contribute to economies but instead to complexities. In chapter 7 titled "Colossus" Bookstaber describes the forming of a financial conglomerate monster: Citigroup. He headed a market risk management group at Salomon that got acquired by Citi. And, he describes how the risk management function became unmanageable. Externally, tracking risk exposures globally in so many instruments, businesses, and geographies became impossible. Internally, the change in corporate scale expanded his risk management group to a dysfunctionally large level.

Bookstaber indicates that regulations does not work in reducing the risk within financial complex systems. By forcing banks to reduce existing risk exposures, they are forced to sell assets. Those forced sales cause asset values to drop further forcing further asset sales. This relates to Fisher's The Debt-Deflation Theory of Great Depressions. "Trying to control the risk ends up creating a liquidity crisis."

Forcing hedge funds towards increasing transparency is a self-defeating proposition. Hedge funds competitive edge are proprietary strategies. If their accounts become transparent, they pretty much go out of business.

Bookstaber makes an interesting connection between Heisenberg's Uncertainty Principle and finance (pg. 223). In the quantum world, you can't improve the measurement of an electron's speed without impairing the measurement of its location. In the finance world, you can't increase transparency without decreasing liquidity. As mentioned, transparency would impair the hedge fund sector. And, the latter is the major liquidity provider for illiquid assets. Without hedge funds many such markets would not be viable.

If upcoming regulatory constraints do not impair the hedge fund sector, Bookstaber anticipates it could become a dominant force within the institutional investment world. His take is that if you take two equally brilliant investors, and the first one is limited to "long" strategies only and the other one is not and can avail himself to all sorts of other investment strategies, the latter one should prevail. And, that describes the difference between a traditional mutual fund and a hedge fund.

However, that is one instance where I may question Bookstaber's opinion. The hedge fund has to deliver gross returns that are so much higher than the mutual fund because it charges so much more (1% operating expense and 20% of profits vs only the 1% for the regular mutual fund). Bookstaber suggests the hedge fund compensates for that because of the inherent leverage in hedge fund strategies. But, by doing so a hedge fund takes on risk that renders it much more fragile than a regular fund. Earlier, Bookstaber states that many hedge funds "win a little, win a little, than lose a lot." Thus, hedge funds blow ups are more frequent than mutual fund ones. Additionally, there is already too much money in hedge funds to chase too few market inefficiencies. This ultimately makes a case for neither hedge funds or regular mutual funds but index funds instead.

Bookstaber addresses the Efficient Market Hypothesis (EMH) in a most interesting way. He understands the subject better than most as he wrote his economics PhD thesis on the transmission of information through the markets. Bookstaber states that stock prices are driven by two components: one is information, and the other is liquidity factors. The EMH covers only partly the information component. That's because it makes some liberal assumptions such as that traders are perfectly rational, and that their actions do not affect the markets. But, the EMH does not cover the liquidity factors. Those include the actual float or supply of each stocks, transaction costs, and leverage constraints. And, often liquidity factors are the predominant drivers of investment prices. Bookstaber states on pg 213 "[liquidity] is the primary driver of crashes and bubbles as well." This makes sense. The information component is disseminated instantly and should be fully reflected in stock prices at all times (the EMH take). But, liquidity factors can get markets out of whack. As Bookstaber explained, the bubble was mainly fueled by a very small float (short supply) of hi-tech stock at the onset.

Bookstaber describes interesting statistical arbitrage strategies (paired stock trading) devised to differentiate between the information component of a stock price, that typically does not mean revert in the short term, vs the liquidity component that does. He indicates that this is easier said than done. As usual, the early traders who devised those strategies made a lot of money. But, the market is a rapidly learning machine and those Alpha returns were pretty much arbitraged out a long time ago. So, that's the puzzling thing about the EMH. The theory is far from perfect. Yet the markets are brutally efficient. Alpha returns depend on traders coming out with new investment strategies until they are replicated. At such point, they are forced to uncover Alpha returns some place else. So, efficiency is a moving target.

In the conclusion, Bookstaber makes recommendations on how to reduce the fragility of our financial system. We should reduce the tight coupling within the system. He proposes to do that by reducing leverage which in turn reduces liquidity and the speed of market activity (tight coupling). He also recommends selective evaluation of financial innovations to prevent dangerous complexities. Insiders will not like Bookstaber's recommendations and will argue that financial innovation has greatly improved wealth creation worldwide. But, you have to distinguish between benign vs complex financial innovations. It is easy to argue in favor of ATMs, debit cards, new mobile payment mechanisms, and online banking innovations. But, did we benefit from MBS, CDOs, and SIVs? Certainly not lately!

The Higher Education Bubble (Encounter Broadside)
The Higher Education Bubble (Encounter Broadside)
by Glenn H. Reynolds
Edition: Paperback
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5 of 6 people found the following review helpful
3.0 out of 5 stars A reasonably interesting essay., November 8, 2012
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This essay is probably less than 3,000 words long and reads in less than half an hour. Given its shortness, this essay can state only so much. Given that, I thought that the vast majority of what the author advanced made much sense was not controversial or counterintuitive. In summary, higher education cost is increasingly much faster than inflation. Meanwhile, its value is declining. Many students graduate from schools and with degrees with little hope of making college-level expected earnings. School funding is declining for both public institutions (fiscal constraints) and private ones (shrinking endowments and private donations). Schools are compensating for this funding gap with higher tuition. Students and families capacity to borrow to pay for higher tuition is also constrained. Something has to give.

The author contemplates what this means. What does an education bubble bursting mean? He figures it will result in many schools going out of business, merging, or restructuring their offerings. He sees a renewed focus on providing degrees with more utilitarian values associated with much better prospective earnings and career potential. This means for liberal arts colleges getting away somewhat from the humanities, women studies, diversity programs and refocus on sciences, engineering, and other career related majors. He sees rising competition from more innovative, career focused, value oriented online education institutions. He foresees elite universities and community colleges faring well in a post-bubble era. This is because the elite schools will always be in short supply and will always send a very valuable and powerful signal for their graduates within the job marketplace. And, community college should thrive because of their low cost and career and trade orientation. But, the restructuring will be more pronounced for all other institutions especially private ones that charge near Ivy league prices but do not deliver Ivy league credentials.

For half an hour of your time, this is a descent read.
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