Stress Test: Reflections on Financial Crises (and the current one) – Quick Review

After the last few weeks, it clear we are in the biggest financial crisis in our generation. I read “Stress Test” a few months ago and there are several perspectives that are good to be remembered. Especially during these crazy days where the market shows ‘no bottom’.

“The fundamental causes of this crisis were familiar and straightforward,” Geithner writes. “It began with a mania — the widespread belief that devastating financial crises were a thing of the past, that future recessions would be mild, that gravity-defying home prices would never crash to earth.”

The causes of the crisis, in other words, were the same old-fashioned madness of crowds and extraordinary popular delusions responsible for every panic dating back to the Dutch mania for tulip bulbs. The entire society — including all the big banks and some nonbank financial firms, like the insurance company A.I.G. — simply ignored risk.

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What It Takes – Book Review

What It Takes: Lessons in the Pursuit of Excellence” is a book I enjoyed in the last two flights. It’s a classic entrepreneurship story and half of the book is talking about his path in starting, building and expanding Blackstone. The other half is composed of stories in his life.

Who is Stephen Schwarzman?

Well, he manages over $500 billion as the co-founder/CEO of Blackstone.
He also wants to teach readers “how to grow organizations, and do positive things, and how to help their careers”. 

I felt through the book that there are some good lessons.

One lesson is around the same (more or less) rules that Buffet coined around:

  1. Don’t lose money.
  2. Go back to confirm you are executing rule #1

A few little details make the book fun to read. For example, when he explained how Angela Merkel raised her hands to imitate a locust and how he mimics her. Another good one is when he tells of why he earned the nickname “Farmer Blackstone” in China. It is because he promised that the company’s stock price was like a seed that would grow in time.

I also liked this suggestion:
“There is nothing more interesting to people than their problems. Think about what others are dealing with, and try to come up with ideas to help them. Almost anyone, however senior or important, is receptive to good ideas provided you are thoughtful.”

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Fooled By Randomness

Fooled By RandomnessI’ve just finish to read this good (very good) book “Fooled By Randomness”. Talab is an ‘old friend’ of mine… since the happy days of “The Black Swan“.

In this book Talab describe the idea that modern humans are often unaware of the very existence of randomness. They tend to explain random outcomes as non-random through ‘scientific’ data analysis. This over-indulgence on data is not only detrimental but also often catastrophic.

The main lessons are powerful and frightening.

* How much can you rely on the track records of companies,  advisers, fund managers, newspapers, or even the market as a whole in making decisions about your investment portfolio? Not as much as you probably think (almost not at all).

* As for the Black Swan: A large-impact, hard-to-predict, and rare event beyond the realm of normal expectations. Taleb regards many scientific discoveries as black swans—”undirected” and unpredicted. He gives the rise of the Internet, the personal computer, World War I, as well as the September 11, 2001 attacks as examples of Black Swan events.

* Survivor-ship bias: We see (just!) the winners and “learn” from them, while forgetting the huge unseen cemetery of losers.

* Skewed distributions: Many real life phenomena are not 50:50 bets like tossing a coin, but have various unusual and counter-intuitive distributions. Example: a 99:1 bet where you almost always win, but when you lose you lose all your savings.

* Taleb Distribution: Applied to situations in which there is a high probability of a small gain, and a small probability of a very large loss. If you sold options in your past – this is a good example of such a case. Another way to think about it, is on insurance company – with high probability they are making money until ‘Katerina’ hit New Orleans (small probability) and for some it’s ‘game over’.
In these situations the expected value is (very much) less than zero, but this fact is camouflaged by the appearance of low risk and steady returns.

So you ask what are the main actions? Well, I would think that Talab (like Gladwell) is not reluctant to make decisions base on instinct (=’Blink’) due to the fact that deep analysis is not helpful. As for Black Swan – be aware of them, because they might put you out of your game.

And this is another good one…

“…The best test of whether someone is extremely stupid (or extremely wise) is whether financial and political news makes sense to him.”

Business, webdev

Yahoo Finance (hidden) API

London vis a vis Finance
I was looking for long time after a way to get some finance data from sources like: google, yahoo etc’ without the need to parse long html pages. Than, a friend point me to some simple pipe that fetch this information. From there it was a short step to gain access to this nice (hidden) API was inevitable.

In a nutshell, if you want to get data on some stocks you can use this request:

where some special tags:

a Ask a2 Average Daily Volume a5 Ask Size
b Bid b2 Ask (Real-time) b3 Bid (Real-time)
b4 Book Value b6 Bid Size c Change & Percent Change
c1 Change c3 Commission c6 Change (Real-time)
c8 After Hours Change (Real-time) d Dividend/Share d1 Last Trade Date
d2 Trade Date e Earnings/Share e1 Error Indication (returned for symbol changed / invalid)
e7 EPS Estimate Current Year e8 EPS Estimate Next Year e9 EPS Estimate Next Quarter
f6 Float Shares g Day’s Low h Day’s High
j 52-week Low k 52-week High g1 Holdings Gain Percent
g3 Annualized Gain g4 Holdings Gain g5 Holdings Gain Percent (Real-time)
g6 Holdings Gain (Real-time) i More Info i5 Order Book (Real-time)
j1 Market Capitalization j3 Market Cap (Real-time) j4 EBITDA
j5 Change From 52-week Low j6 Percent Change From 52-week Low k1 Last Trade (Real-time) With Time
k2 Change Percent (Real-time) k3 Last Trade Size k4 Change From 52-week High
k5 Percebt Change From 52-week High l Last Trade (With Time) l1 Last Trade (Price Only)
l2 High Limit l3 Low Limit m Day’s Range
m2 Day’s Range (Real-time) m3 50-day Moving Average m4 200-day Moving Average
m5 Change From 200-day Moving Average m6 Percent Change From 200-day Moving Average m7 Change From 50-day Moving Average
m8 Percent Change From 50-day Moving Average n Name n4 Notes
o Open p Previous Close p1 Price Paid
p2 Change in Percent p5 Price/Sales p6 Price/Book
q Ex-Dividend Date r P/E Ratio r1 Dividend Pay Date
r2 P/E Ratio (Real-time) r5 PEG Ratio r6 Price/EPS Estimate Current Year
r7 Price/EPS Estimate Next Year s Symbol s1 Shares Owned
s7 Short Ratio t1 Last Trade Time t6 Trade Links
t7 Ticker Trend t8 1 yr Target Price v Volume
v1 Holdings Value v7 Holdings Value (Real-time) w 52-week Range
w1 Day’s Value Change w4 Day’s Value Change (Real-time) x Stock Exchange
y Dividend Yield

Simple, right? 🙂

As for historical data you can use something like:

where the FROM date is: &a=01&b=10&c=2010
and the TO date is: &d=01&e=19&f=2010
You can also get it as CSV file with link like:

Now, if you want to play with the data you are getting from yahoo! you can run some fun SQL like:

Getting the Standard divination of a specific stock:

SELECT stock, STD(Close-Price) from `historic_prices` where stock = "NFLX" AND date > "2010-01-01" group by stock

This will give you the Standard divination on Netflix (hot hot stock these days) from the beginning of 2010 (and like the meaning of the universe… it’s 42!)

Here is another way to work with finance data from NodeJS.

Happy hacking!