This update:

http://www.fooledbyrandomness.com/blackswan-technical.htm

Some people make technical comments on a literary book (TBS was presented as a literary-philosophical essay), but do not go after my technical work that present analytical discussions and empirical evidence. I find it flattering (if unchallenging) to only be attacked in the wrong places, but it is more honest and more helpful to scientific progress to comment on technical works AND NOT DISSEMINATE A WRONG PRESENTATION ABOUT MY IDEAS (Fama, Scholes, Engle, etc.), or by some other extremely idiotic or extremely jealous persons.

Actually, no: this is VERY dishonest. I will consider it bad faith to attack the statistical statements in my literary work without looking at the technical documents and WILL NOT SPARE any shady academic who does so.

David Freedman's Farewell Gift

Very sad news: David Freedman, Berkeley statistician and a critic of pseudoscience using statistics, died of cancer. He was my ONLY supporter in the statistical community, and, reading some of the critics of The Black Swan, he suggested this excerpt from his book as a moving farewell gift:

MALPRACTICE

I am about to prove the "nonneutrality of representation". It means that risk measures CAUSE a disproportionate increase in risk taking on the part of the unsuspecting user.

The consequence is that many risk quants (& authors of VAR books, consultants, & members of the International Association of Financial Engineers promoting modern finance) will be sued (by the victims) for providing faulty Value-at-Risk measures because it led to an INCREASE in risks.

Even if you tell the person"you need to supplement this method with that method such as stress testing", it is not sufficient --he will rely on the measure. All I needed to show is the illusion of safety.

Yes, many of you (providers of risk measures) will be sued by the innocent people who lost their savings --like tobacco companies who were sued by the innocent smokers.

You will be held accountable. I will make sure it happens. I said in 1996 ( & 1997 in my debate with that ... Jorion) that I will be on the witness stand -and I will be.

I will be.

PS- This is called malpractice. I got interested in iatrogenics a few years ago.

This picture is what I am seeing about bets on the US elections. It has been there for 24 hours. People talk a lot about election markets. This is plain hogwash. Too small to be worth a trade. How you can get information "from the market" when such market is under straight Dutch book violations (here prob >1).

Maybe I should reduce my web visits even more. Bye

I am at the Edinburgh literary festival and the last thing I care about is you finance people.

I've been swamped by emails telling me that I was right (forwarding stories about "25 sigmas" by the Goldman Sachs CEO --who needs to be replaced or banned from speaking to the press -- or the Rothman guy in the wsj on 1 in 10,000 year events).

I don't understand these emails. It is as if I didn't know that I was right. Tell me what I don't know.

Marcos Carreira got it right. No wonder he gave me a Brazilian address to send him a copy of TBS. People in Braziou know about high interest rates.

The idea of follows: something that is supposed to drift BUT DOES NOT DRIFT is volatile.

Consequence: when a currency has a high interest rate, spot volatility is totally irrelevant. Using HVT on Bloomberg is not an intelligent idea.

The problem with the question: 100% interest rates can be ambiguous when translating into daily rates. I meant the daily equivalent of 100% interest rates.

So where r is the daily rate, the answer is :

STD= [Sqrt[ Sum [i=1, i=22] [ (0 - r)^2]/22] Sqrt[256] (annualized)

MAD= Sum[i=1,i=22][Abs[0-r]/22] (daily there will be another post on annualization of MAD)

If you use daily r of .4, the answer is 6%. Marcos used a lower daily r but I assumed that he was right and that the interest rate I used in my question was ambiguous.

I got an intelligent answer from Leon Pollard, that monthly volatility should be about 4% (if you measure volatility monthly) --but Marcos beat him to it.

I have another 92 Quizzes --I am in Budapest and I saw a bunch of post Empire men playing chess in a Belle Epoque style spa, standing in a pool of warm spring water. I realized that I find option quizzes far more fun than chess.

We Don’t Quite Know What We Are Talking About When We Talk About Volatility

paper

http://ssrn.com/abstract=970480

When you ask someone the following question: A currency has 5% interest rates (can be generalized to any security). The base currency (costs of funds) is 5%.

The underlying moves up 1% a day for 22 days in a row. How do you compute volatility (Standard Deviation) for the PURPOSE of decision-making (option pricing)?

Almost everyone I've quizzed throughout my career answers: 0% volatility. Their spreadsheet functions using series of log returns also erroneously provide: 0% volatility.

Nonsense.

The real answer is 16% annualized.

Why? STD = Sqrt[(E[X-E[x])^2] MAD =E[|X-E[x]|]

When you are facing an uncertain outcome you do not expect the mean return to be 1% a day. You simply expect 0% drift. Therefore you should not center volatility around the ex post drift but the ex ante one.

In other words, the options would produce the P/L of 0 volatility if and only if the drift is expected to be 1%

The classical anticipating-nonanticipating strategy. AN OPTION BREAKS EVEN AT 16% VOL (+- some adjustment) NOT 0.

Corrollary

A currency has 100% annual interest rates [paid daily]. Base currency is 5%. The exchange rate does not move for a month. What is volatility (monthly, annualized)? Easy...

please send answers to gamma [at] fooledbyrandomness [dot] com

The winner gets a copy of The Black Swan . I will not offer to sign the copy (I hate to offer to sign my book ... my signature has nothing special ... )

Simply raise vol twice this time by increment DV. Compare the following Portfolio values (hence PV) PV[V] - PV [V+DV] and PV[V+DV]-PV[V+2DV] . If the second value is smaller (larger) than the first and one is long volatility, then he is short (long) the tails. Is the second value is smaller (larger) and he is short volatility, he is long (short) the tails.

Model Risk Effectively this exercise reveals more than fat tails --sensitivity to model errors, sensitivity to problems of distribution. In a way, everything starts and ends with NonGaussianism.

How can you figure out if an option book is short the tails? Move ONE single parameter, but twice. Hint: not complicated at all. Please send answer to gamma [at] fooledbyrandomness [dot] com