Thursday, December 30, 2010

Intermittent fasting benefits

Is skipping breakfast now and then really so bad? The idea of intermittent/short-term fasting is to boost growth hormone (GH) levels via fasting anywhere from 12- 48 hours at a time INFREQUENTLY so the body does not adapt with slowing metabolism. GH is important for several reasons,

1) GH helps the body gain/retain lean muscle tissue
2) GH boosts fat utilization
3) GH increases bone density
4) GH increases skin thickness for youthful looks

I became first interested in 2005 having reviewed a research paper by Louise Moller MD. As expected, this concept has become relatively well known in the bodybuilding circles today. Here're some pretty informative excerpts from an interview from Leigh Peele with Martin Berkhan.

Interview source

Leigh Peele- What was it that drove you to intermittent fasting? Is this an idea you have been toying with for sometime?

Martin Berkhan- ... I started to question the need for regular feedings and the way it was constantly being pushed as the most optimal way to eat for physique conscious people. The science certainly didn’t support the approach, so how come everyone was ranting about high meal frequency patterns being ideal?


Was eating every second or third hour important in order to “stoke the metabolic fire”? No, there was no scientific support for that idea and studies on the subject were carefully controlled, showing no correlation at all between meal frequency and metabolism.


Digestion of a regular meal takes about 6-7 hours and during this time amino acids are being released into the bloodstream. 30 g’s of casein takes about 7 hours to get fully assimilated. Double that amount and you will have amino acids in the bloodstream most of your waking hours.


There are also some correlation studies showing a link between high meal frequency and lower bodyweight in the general population, but this is easily explained when you look at the behavioral aspects surrounding low meal frequencies among “regular” people. For example, your average low meal frequency eater is usually a spontaneous eater, snacks between meals and has no clue about proper nutrition (a snickers bar on the go, maybe something from the vending machine after lunch, and so forth).

Leigh Peele-Can you give us a really brief rundown into the bare basic principals of your approach to IF? The quick and easy if you will.

Martin Berkhan- Intermittent Fasting involves a longer period of no food intake followed by a relatively brief period of eating. There’s not really a clear cut definition of it, and studies looking at IF, and human subjects, have been using a wide range of fasting periods; 20 hours in a recent study and up to 48 hours in studies on ADF (Alternate Day Fasting). This is where it becomes a bit problematic with regards to weight training and diet adherence...


My take on IF shortens the fasting period down to 16 hours – in my opinion, an ideal compromise between getting the best out of the fasting, without the negatives that may follow with a longer fast. This leaves eight hours as your eating window, in which myself and most of my clients, eat three meals, leaving room for proper pre – and post workout nutrition. I should note that I cycle calorie intake depending on where the current priority lies (fat loss, recomposition or lean mass gain). However, regardless of goals, the absolute majority of the day’s calorie intake is to be ingested in the post workout window. In my experience, this may have a nutrient partitioning effect which makes it possible to gain, or maintain, muscle even on a weekly calorie deficit, or when dieting to very low bodyfat levels.

Leigh Peele-Is it safe to say then that even with IF, just as any other fat loss plan, overall energy (in an out) is still just as important? That the users of IF need to understand that this isn’t some sort of free pass to binge on any and everything, they still need to fit it within their caloric needs for daily energy? This would make “eating to your hearts content” mean more like “don’t be stupid and scarf down a box of doughnuts correct?

Martin Berkhan-Exactly...


Monday, December 27, 2010

S&P 500 VEQTOR Index

VEQTOR stands for Volatility EQuity Target Return. Noticed it while browsing through Standard & Poors strategy indices. After some digging, found a great article explaining how it works at Surly Trader.

The strategy gains its volatility overlay through the use of short-term VIX futures.

Basic idea here is to take a long position in VIX futures against equity holdings, rebalanced frequently with respect to expected future cross correlations. As a result, it theoretically offers a much smoother return and potentially make a net profit off volatility jumps like that of late 2008.

Performance of a Dynamic VEQTOR Strategy Allocation Algorithm against a naked long S&P500 position, (click on image to see the whole thing)

Wednesday, December 22, 2010

Earnings info before press release

Wow, somebody must've made a killing off this. Another example of passing market inefficiency exploited by smart money.

So THIS Is How Bloomberg Gets Earnings Reports Hours Before They're Publicly Released...

It turns out that some companies don't want to wait until the 4PM market close to post their earnings online, perhaps because they're worried they'll forget. So what they do is post them online earlier, but don't link to the page from their web sites. This renders the page invisible--unless you know what to look for.

Humans are creatures of habit, and the humans who post earnings releases on company web sites are no different than any other humans.
Which means that if the web-page URL for a company's second quarter's earnings release was, say:

It's probably a safe bet that the URL for the third quarter's earnings release will be:


Wasteful spending of tax dollars

$3Million to research video games or cow farts? I have never realized how politically connected the universities are to the government until today.

In a time where unemployment and social distress runs wild, budget management appears to have jumped out the window in America. Of course it raises the concern that this phenomenon is highly probable in other nations, e.g. New Zealand as well.


#1 A total of $3 million has been granted to researchers at the University of California at Irvine so that they can play video games such as World of Warcraft. The goal of this “video game research” is reportedly to study how “emerging forms of communication, including multiplayer computer games and online virtual worlds such as World of Warcraft and Second Life can help organizations collaborate and compete more effectively in the global marketplace.”

#2 The U.S. Department of Agriculture gave the University of New Hampshire $700,000 this year to study methane gas emissions from dairy cows.

#3 $615,000 was given to the University of California at Santa Cruz to digitize photos, T-shirts and concert tickets belonging to the Grateful Dead.

#4 A professor at Stanford University received $239,100 to study how Americans use the Internet to find love. So far one of the key findings of this “research” is that the Internet is a safer and more discreet way to find same-sex partners.

#5 The National Science Foundation spent $216,000 to study whether or not politicians “gain or lose support by taking ambiguous positions.”

#6 The National Institutes of Health spent approximately $442,340 to study the behavior of male prostitutes in Vietnam.

#7 Approximately $1 million of U.S. taxpayer money was used to create poetry for the Little Rock, New Orleans, Milwaukee and Chicago zoos. The goal of the “poetry” is to help raise awareness on environmental issues.

#8 The U.S. Department of Veterans Affairs spent $175 million during 2010 to maintain hundreds of buildings that it does not even use. This includes a pink, octagonal monkey house in the city of Dayton, Ohio.

#9 $1.8 million of U.S. taxpayer dollars went for a “museum of neon signs” in Las Vegas, Nevada.

#10 $35 million was reportedly paid out by Medicare to 118 “phantom” medical clinics that never even existed. Apparently these “phantom” medical clinics were established by a network of criminal gangs as a way to defraud the U.S. government.

#11 The Conservation Commission of Monkton, Vermont got $150,000 from the federal government to construct a “critter crossing”. Thanks to U.S. government money, the lives of “thousands” of migrating salamanders are now being saved.

#12 In California, one park received $440,000 in federal funds to perform “green energy upgrades” on a building that has not been used for a decade.

#13 $440,955 was spent this past year on an office for former Speaker of the House Dennis Hastert that he rarely even visits.

#14 One Tennessee library was given $5,000 in federal funds to host a series of video game parties.

#15 The U.S. Census Bureau spent $2.5 million on a television commercial during the Super Bowl that was so poorly produced that virtually nobody understood what is was trying to say.

#16 A professor at Dartmouth University received $137,530 to create a “recession-themed” video game entitled “Layoff”.

#17 The National Science Foundation gave the Minnesota Zoo over $600,000 so that they could develop an online video game called “Wolfquest”.

#18 A pizzeria in Iowa was given $60,000 to renovate the pizzeria’s facade and give it a more “inviting feel”.

#19 The U.S. Department of Agriculture gave one enterprising group of farmers $30,000 to develop a tourist-friendly database of farms that host guests for overnight “haycations”. This one sounds like something that Dwight Schrute would have dreamed up.

#20 Almost unbelievably, the National Institutes of Health was given $800,000 in “stimulus funds” to study the impact of a “genital-washing program” on men in South Africa.


It happens because the people ALLOW it to occur without any punitive consequence to those responsible. Politicians are susceptible to greed and corruption like the rest of humanity, just they can get away with it more easily, for now.

Tuesday, December 21, 2010

Taleb's Code

I got this off Against Value at Risk excerpt (which deserves a later analysis), from Taleb's Fooled by Randomness. These concepts could apply to not just financial trading, but all little risk/reward scenarios we go through in everyday life.


Trader Risk Management Lore : Major Rules of Thumb

Rule 1 - Do not venture in markets and products you do not understand. You will be a sitting duck.

Rule 2 - The large hit you will take next will not resemble the one you took last. Do not listen to the consensus as to where the risks are (i.e. risks shown by VAR). What will hurt you is what you expect the least.

Rule 3 - Believe half of what you read, none of what you hear. Never study a theory before doing your own prior observation and thinking. Read every piece of theoretical research you can - but stay a trader. An unguarded study of lower quantitative methods will rob you of your insight.

Rule 4 - Beware of the trader who makes a steady income. Those tend to blow up. Traders with very frequent losses might hurt you, but they are not likely to blow you up. Long volatility traders lose money most days of the week.

Rule 5 - The markets will follow the path to hurt the highest number of hedgers. The best hedges are those you are the only one to put on.

Rule 6 - Never let a day go by without studying the changes in the prices of all available trading instruments. You will build an instinctive inference that is more powerful than conventional statistics.

Rule 7 - The greatest inferential mistake: this event never happens in my market. Most of what never happened before in one market has happened in another. The fact that someone never died before does not make him immortal. (Learned name: Hume's problem of induction).

Rule 8 - Never cross a river because it is on average 4 feet deep.

Rule 9 - Read every book by traders to study where they lost money. You will learn nothing relevant from their profits (the markets adjust). You will learn from their losses.


Thursday, December 16, 2010

Stem cell HIV fix


HIV-positive man ‘cured’ by stem cell transplant

The man received bone marrow from a donor who had natural resistance to HIV infection; this was due to a genetic profile which led to the CCR5 co-receptor being absent from his cells," they explained. "The most common variety of HIV uses CCR5 as its ‘docking station’, attaching to it in order to enter and infect CD4 cells, and people with this mutation are almost completely protected against infection.

...stem cells from a donor that lacked the CCR5 receptor, "a condition that is present in less than 1 percent of Caucasians in northern and western Europe...

The complete case history can be found at

And we will probably never hear about this in the mainstream media unfortunately.

Wednesday, December 15, 2010

Trading the Chinese RMB

As mentioned in the Wall St. Journal, the Chinese currency Yuan, or RMB is tradeable externally for the first time.

Daily trading in the yuan has grown from zero to $400 million in the past few months... Global trading in yuan allows businesses to buy and sell the currency to finance trade, investment and borrowing...

(Predictable) manipulation?

Now that RMB/USD and RMB/EUR FX contracts are available at CME, and that there's all this talk of Chinese government's influence over the currency, the next logical question becomes a matter of exploiting it for a profit. OK, so the US claims that the RMB is kept artificially low within a predictable range. If that is true, then this trade could result in practically risk free profits.

So what's the deal here? If everyone believes they know how the RMB's being manipulated, where's the volume over CME? Something's gotta give.

Friday, December 10, 2010

Day trading outsourced to China

Welcome to globalization. The New York Times has noticed a trend in outsourcing of discretionary US stock day trading to China. Given that jobs are scarce, and a culture with strong economic incentives, this was just a matter of time.

Trading firms based in the United States and Canada are recruiting inexpensive workers in China and teaching them to engage in speculative trading. This means repeatedly buying and selling shares listed on the New York Stock Exchange and Nasdaq Stock Market, hoping for quick profits.

China prohibits its citizens from using Chinese currency to buy or sell shares of companies listed on foreign stock exchanges, though there appears to be no prohibition against trading stocks for an account owned by a foreign entity.

This constant change in market microstructure is probably the explanation for the changes in daily price evolution processes that market participants must adapt to. Where will this take us? Probably a Chinese Wall St. type of thing, as there simply aren't enough "real jobs" to go around.

'Day trading is like a battlefield,' says Qu Zheng, 24, who has been trading for more than two years and typically trades a million shares a day at Lazer Trade’s office in Beijing. 'It’s very challenging because you can feel the pulse of the market.'

Wednesday, December 8, 2010

Interesting Ben Bernanke quotes

Some interesting lines from Mr. Bernanke, the Federal Reserve chairman

#1 (October 20, 2005) “House prices have risen by nearly 25 percent over the past two years. Although speculative activity has increased in some areas, at a national level these price increases largely reflect strong economic fundamentals.”

#2 (On 60 Minutes in response to a question about what would have happened if the Federal Reserve had not “bailed out” the U.S. economy) “Unemployment would be much, much higher. It might be something like it was in the Depression. Twenty-five percent.”

#3 (February 15, 2006) “Housing markets are cooling a bit. Our expectation is that the decline in activity or the slowing in activity will be moderate, that house prices will probably continue to rise.”

Say whaa?

#4 (January 10, 2008) “The Federal Reserve is not currently forecasting a recession.”

#5 (When asked directly during a congressional hearing if the Federal Reserve would monetize U.S. government debt) “The Federal Reserve will not monetize the debt.”

#6 “One myth that’s out there is that what we’re doing is printing money. We’re not printing money.”

#7 “The money supply is not changing in any significant way. What we’re doing is lowering interest rates by buying Treasury securities.”

#8 (November 21, 2002) “The U.S. government has a technology, called a printing press (or today, its electronic equivalent), that allows it to produce as many U.S. dollars as it wishes at no cost.”

#9 (March 28, 2007) “At this juncture, however, the impact on the broader economy and financial markets of the problems in the subprime market seems likely to be contained. In particular, mortgages to prime borrowers and fixed-rate mortgages to all classes of borrowers continue to perform well, with low rates of delinquency.”

#10 (July, 2005) “We’ve never had a decline in house prices on a nationwide basis. So, what I think what is more likely is that house prices will slow, maybe stabilize, might slow consumption spending a bit. I don’t think it’s gonna drive the economy too far from its full employment path, though.”

#11 “Although low inflation is generally good, inflation that is too low can pose risks to the economy – especially when the economy is struggling.”

#12 (February 15, 2007) “Despite the ongoing adjustments in the housing sector, overall economic prospects for households remain good. Household finances appear generally solid, and delinquency rates on most types of consumer loans and residential mortgages remain low.”

#13 (October 31, 2007) “It is not the responsibility of the Federal Reserve – nor would it be appropriate – to protect lenders and investors from the consequences of their financial decisions.”

#14 (On the possibility that the Fed might launch QE3) “Oh, it’s certainly possible. And again, it depends on the efficacy of the program. It depends on inflation. And finally it depends on how the economy looks.”

#15 (November 15, 2005) “With respect to their safety, derivatives, for the most part, are traded among very sophisticated financial institutions and individuals who have considerable incentive to understand them and to use them properly.”

#16 (January 18, 2008) “[The U.S. economy] has a strong labor force, excellent productivity and technology, and a deep and liquid financial market that is in the process of repairing itself.”

#17 “I wish I’d been omniscient and seen the crisis coming.”

#18 (May 17, 2007) “All that said, given the fundamental factors in place that should support the demand for housing, we believe the effect of the troubles in the subprime sector on the broader housing market will likely be limited, and we do not expect significant spillovers from the subprime market to the rest of the economy or to the financial system. The vast majority of mortgages, including even subprime mortgages, continue to perform well. Past gains in house prices have left most homeowners with significant amounts of home equity, and growth in jobs and incomes should help keep the financial obligations of most households manageable.”

#19 “The GSEs are adequately capitalized. They are in no danger of failing.”

#20 (Two months before Fannie Mae and Freddie Mac collapsed and were nationalized) “They will make it through the storm.”

#21 (September 23rd, 2008) “My interest is solely for the strength and recovery of the U.S. economy.”

#22 “Economics has many substantive areas of knowledge where there is agreement but also contains areas of controversy. That’s inescapable.”

#23 “I don’t think that Chinese ownership of U.S. assets is so large as to put our country at risk economically.”

#24 “We’ve been very, very clear that we will not allow inflation to rise above 2 percent.”

#25 “…inflation is running at rates that are too low relative to the levels that the Committee judges to be most consistent with the Federal Reserve’s dual mandate in the longer run.”

#26 (June 10, 2008) “The risk that the economy has entered a substantial downturn appears to have diminished over the past month or so.”

#27 “Not all information is beneficial.”

#28 “The financial crisis appears to be mostly behind us, and the economy seems to have stabilized and is expanding again.”

#29 “Similarly, the mandate-consistent inflation rate–the inflation rate that best promotes our dual objectives in the long run–is not necessarily zero; indeed, Committee participants have generally judged that a modestly positive inflation rate over the longer run is most consistent with the dual mandate.”

#30 (October 4, 2006) “If current trends continue, the typical U.S. worker will be considerably more productive several decades from now. Thus, one might argue that letting future generations bear the burden of population aging is appropriate, as they will likely be richer than we are even taking that burden into account.”

Friday, December 3, 2010

Fed. Treasury holding vs. stock market

OK I just looked at the Zerohedge post with the below graph (between Fed's US Treasury holding, the S&P500 Stock Index) and I have a problem with it.

It implies that by simply observing Fed's holdings, we can forecast future market moves, easily as pie right? Not really. I've looked up Fed's weekly statistical release of US Treasury and Marketable Securities for International Accounts vs. the S&P500 index Exchange Traded Fund SPY since 2002, and here's what I found,

Top: SPY from 2002 to this week
Bottom: Marketable Securities for International Accounts (series 1) US Treasury and (series 2)

Nevermind the ugly graphic... we can see that the Fed's holding has ALWAYS increased over time, including 07 and 08 where the stock market experienced significant volatility jumps.

OK so does anything from the Fed's weekly report "work" with respect to stock markets?
Overnight Facility (lending),
Top: SPY from 2002 to this week
Bottom: Overnight Facility

As we can see, this has a significant negative correlation to the SPY, like the VIX and the implied correlation index KCJ. So there may be some use for the professional trader.

Tuesday, November 30, 2010

Game Theory for Soccer Penalty Kicks

A mixed Nash Equilibrium strategy for soccer penalty kicks is mentioned at some Vanderbilt lecture.

Quick recollection of Nash Equilibrium,
A Nash equilibrium, named after John Nash, is a set of strategies, one for each player, such that no player has incentive to unilaterally change her action. Players are in equilibrium if a change in strategies by any one of them would lead that player to earn less than if she remained with her current strategy.

So onto the soccer thing,

Economist Ignacio Palacios-Huerta analyzed 1,417 penalty kicks from five years of professional soccer matches among European clubs. The success rates of penalty kickers given the decision by both the goalie and the kicker to kick or dive to the left or the right are as follows:


Left Right
Kicker Left 58% 95%
Right 93% 70%

In all cases, left and right is from the kicker's perspective. If the goalie guesses the kicker's direction correctly, he will block about 3 or 4 kicks out of 10. If the goalie guesses wrong, the kicker's chance of success is very high. Next, we calculate the mixed strategy equilibrium. Let p be the probability that the goalie jumps to the left and 1-p be the probability he jumps right. To make the kicker indifferent, we must solve:

payoff from kicking left = payoff from kicking right
58p + 95(1-p) = 93p + 70(1-p)

The result is p=42%. The goalie must jump left 42 out of 100 times to make the kicker indifferent between kicking left and right.

Next, we turn to the kicker's strategy that makes the goalie indifferent. First, note that the table above has only the kicker's payoffs represented by the probability of success. The goalie's payoffs are the opposite: the probability of a miss. We can rewrite the above table to represent the chance that the kicker misses by subtracting the numbers in the table from 100.


Left Right
Kicker Left 42% 5%
Right 7% 30%

Let q be the probability that the kicker kicks to the left and 1-q be the probability he kicks right. To make the goalie indifferent, we must solve:

payoff from jumping left = payoff from jumping right
42q + 7(1-q) = 5q + 30(1-q)

The result is q=39%. The kicker must kick left 39 out of 100 times to make the goalie indifferent between jumping left and right.

Surprisingly, the game is not very symmetric between kicking left and right which, in turn, implies that the relative frequencies of left and right for the goalie and the kicker should not be 50-50. How well does game theory predict actual behavior? Here is the actual behavior of kickers and goalies in the 1,417 observed penalty kicks:

  • Kickers:
    • Predicted proportion of kicks to the left: 39%
    • Observed proportion of kicks to the left: 40%
  • Goalies:
    • Predicted proportion of jumps to the left: 42%
    • Observed proportion of jumps to the left: 42%

Yep, now let's explain this to the kids...

Friday, November 26, 2010

Is making money at poker practical?

Having spent a good 1.5~ years of learning and playing for fun, my online poker hobby's made around $5/hour according to Hold'em Manager from the latest 15,000~ hands. So the next big question is, how much sacrifice would it take to really dig into it and overcome all living expenses through poker alone?

Skills or luck

It's a whole lot like day trading, only small edges are visibly exploitable, and they require patience, discipline, and deep understanding of statistics. Luck determines short term winners/losers, but you definitely need skills to have the stats go in your favor in the long run (10,000 hands +).

2 + 2

Two Plus Two is probably the most well known poker forum today, and it's a little talked about culture of a lot of young people who make a lot of money. That's probably where I started looking into the idea.


I'm looking to take up coaching at Collin Moshman's group, they do both coaching and backing. It's a fair set up for the coaching deal, they only make $ as a cut off players' future profits so that everyone's incentive remains in line. They require potential "students" to play at least 10,000 hands/ week, this is doable via multi-tabling and well, time; it gets the law of large numbers to kick in sooner than later, and speeds up the learning curve like CRAZY.

OK, yeah I've just talked myself into giving it a shot!

Monday, November 22, 2010

The Jump & Dump!

I've been reading up a lot around liquidity and ran into the story of how two postgrads, Rahul Savani (Computer Science) and Ben Veal (Applied Math.), won the Penn-Lehman Automated Trading Competition in 2005. That's University of Pennsylvania and yeah, Lehman Bros (back in the good old days of selling mortgage backed assets).

Savani and Veal's algorithm, Jump and Dump, dominated the other algorithms completely in the competition, by realizing that all of the competing algorithms focused only on market data and not any "reality checks" on price sensibility. Commented by a Wall St. friend of theirs, "... Often a strategy is successful because it anticipates how the other market participants are likely behave/react and then exploits them. "

Here's how they did it, it was brilliant and deceptively simple!


The strategy of Savani and Veal is simple to describe and even elegant in its own twisted way. The basic idea is to "clear out" one side of the market --- for instance, to simply buy all shares in the sell book. This has the effect of leaving a buy book, and thus a bid, but no sell book, and thus no ask.

The next step is to immediately place a buy and sell order at a very large price --- larger than the highest price paid to clear out the sell book. Since there is no ask, and the bid is far below this large price, this pair of orders becomes the new bid and ask, effectively leaving the current buy book far below the bid/ask.

The third step is to then self-execute a small number of shares with the new bid or ask, thus causing the last execution price to also be near the new large bid/ask.

The effect of these three steps is to (a) leave the strategy with a large long position (from the initial purchase of the sell book), and (b) move the bid, ask, and last price to a price far above the prices paid to acquire the large long position.

You can see where this is heading. Any strategy that only places orders with limit prices relative to the current bid, ask, or last execution price will blindly follow the artificial inflation in the market created by these steps, and begin trading near the new price. As long as there is enough such liquidity at the new inflated prices --- and in the recent competition, there was plenty --- the Savani and Veal strategy can then quietly start dumping its long position for far more than it paid for it. Genius incarnate.


Thursday, November 18, 2010

Quantitative Easing explanation

Funny and probably informative for anyone unfamiliar with the economy.

Wednesday, November 17, 2010

Obama vs. Hu rap battle

Pretty entertaining!

Return Distributions: Power Law > Gaussian

Power Law distributions explain fat-tail distributions much more accurately than Normal. I am aware that most academics are drilled about how Gaussian curves fit EVERYTHING in real life. That is nonsense. The existence of alternative distributions in math/stat textbooks that track empirical real life tell a very different story. Basically, extreme (potentially profitable) events occur MUCH MORE frequently than what Gaussian assumes.

According to someone who models stock returns with a normal distribution (this probably includes 99% of academic finance grads), the 1 day big market drops in 1929, 1987, 1998, 2008, Enron, GM, etc. are supposed to happen at most once every 10^30, or nonillion years. So it's numerically convenient, and obviously wrong, yet they embrace it as if it's the one and only truth.

The brilliant options trader, writer of The Black Swan, and once a professor at MIT, Taleb mentioned in Haug's Derivative Models on Models that the state of academic finance is intellectually insulting. Having met some folks from local business schools, I must agree.

It would seem more out of political reasons for this persistent blind faith of normal distributions in modern finance. As an overwhelming majority of current financial practices rely on Gaussian moments such as standard deviations, which we now know is completely meaningless in financial time series, an official recognition of this error would mean job loss for university staff, so-called analysts, and embarrassment for a number of people who came up with useless concepts such as "modern portfolio theory", "CAPM", "Black-Scholes Option Pricing", "VaR", and etc.

Is it intentional deception or incompetence? I'd say a bit of both.

Saturday, November 13, 2010

Portfolio Theory, and practice

Even though "Modern" Portfolio Theory is pretty old, and holds a lot of false assumptions around market completeness and diversification, it could be applied practically for a portfolio of positively expected strategies instead of simple assets vulnerable to systemic risk.

Original thoughts
So the original assumption around increasing the number of asset holdings is to lower the standard deviation of return, i.e. "unsystemic risk" (see below).

This is pretty easy to do by simply taking positions in index ETFs.

So what's the deal with the "Undiversifiable or Market Risk"? That includes things like credit risk, counter-party risk, basically everything that shows why buy & hold does not turn out well.

Actual application

Replacing asset holdings with trading strategies that exploit fundamental inefficiencies where systemic risks become opportunities for profit, and all of sudden portfolio theory becomes practical for the real world. It's like running a casino, to minimize swings in revenue, hosting a whole bunch of games helps the Law of Large Numbers kick in just a bit sooner; and everybody's happy.

Thursday, November 11, 2010

College/University side effect (spoiled grads!)

Not just the fresh graduates, I notice this attitude among some lecturers, professors as well. So they got a piece of paper suggesting that they can read, write (but not necessarily well), and be told what to do, all of sudden the real world has become menial. Of course they hate the question "If you're so smart, why aren't you rich?"

This story is from a friend, let's call her Mandy (keeping her anonymous), whose husband Pete runs a construction company. Mandy mentioned that her husband just hired someone who is a fresh graduate from University of Auckland in electrical engineering last week. So on the first day of work started out like this...

Pete, "Alright why don't ya dig a trench along the wall and lay the (electric) cables in there."
Uni Grad, "Oh, I don't do that..."

Long story short, reality struck, Pete was on the verge of firing him, the kid ended up digging.
What happened to the days of apprenticeships where people actually spent all their time learning RELEVANT stuff around their trade? It's ridiculous how much time and energy I must spend on practically useless stuff for the sake of a university degree.

Wednesday, November 10, 2010

Time Series analysis in R

This was part of a course I took at university. R is quite user friendly, efficient on system resources, and pretty useful! Below you'll find commands for some basic statistics along with their explanations and examples.

Topics included:

Basic stats, Cross Correlations, Cointegration, GARCH( Generalized Autoregressive Conditional Heteroskedasticity), ARIMA (Autoregressive Integrated Moving Averages), VAR (Vector Autoregression), and linear single/multiple regression.

(Paul is a great guy)
Lecture Notes

Sunday, November 7, 2010

About spurious correlations

I was talking to a fellow mathematician, someone not familiar with financial economics, around autocorrelation within financial data. "It could be spurious..." he said, implying and concluding that the relationship may not be practically exploitable.

OK, so the next logical thought is, even if the correlation IS spurious, can it still be applied somehow?

(Above figure gives HFRI Hedge Fund Index Autocorrelations for the indicated period)

Spuriousness explained

William C. Burns has given a great example of a spurious correlation,

  1. Get data on all the fires in San Francisco for the last ten years.
  2. Correlate the number of fire engines at each fire and the damages in dollars at each fire.
Note the significant relationship between number of fire engines and the amount of damage. Conclude that fire engines cause the damage.

So basically, it means that correlation statistics do not explain cause and effect orders.

Some relationships remain exploitable

OK, so let's go back to significant correlations of stock index values against Dividend Yield or the autocorrelation thing. Fundamentally speaking these relationships may make sense with respect to expected rational behavior of institutional traders. However, someone who does not have a background in financial economics would assume spuriousness.

Does it really matter? Referring to serial correlation, so what if a security's return at time t, S(t) depends on S(t-1), or that maybe S(t-1) depends on S(t); as long as the relationship's there and statistically significant, it is probably exploitable. The bottom line is everything.

Wednesday, November 3, 2010

About Ito's Process

Besides Black & Scholes, Kiyoshi Ito is one of the really popular guys in mathematical finance. Everybody in the scene knows his diffusion process, and I have some problems with it!

Ito's Diffusion Process (Simplest form):

Given that X(t) is a random variable, representing price of a financial security at time t, the change in X can be represented by,

dX(t)= aX(t)dt + sdW(t)


a, s: constants with respect to the model applied
W(t): Brownian motion

Stylized Facts
Empirical findings have however shown that the markets are NOT truly random as suggested by the Brownian motion. D. Whitcomb has pointed out a negative serial correlation off Index returns since 1979! Here's an article about his findings. This means the drift parameter a above does not always make sense. Yeah, there's always the drift due to inflation on indexes, but not all securities can even keep up with it, especially those with high credit risk.

The conditional variance contradicts with a lot of existing academic assumptions around Heston's stochastic volatility paper. Well it isn't so stochastic if you've actually observed volatility time series critically. I can't get into the volatility thing until a later time.

That's it for now!

Saturday, October 30, 2010

A market for political events

Future elections, political event probabilities are tradeable now as futures at Intrade. Of course like any other betting algorithms, a positive expectancy is required to make money over time. Finally, "hobbyist political analysts" like uncle Bob has the chance to back their opinions with some dough :)

Of course on the other hand, we could reference these numbers for a more precise forecast. After all, the market does not lie.
"Intrade makes more accurate predictions than I have ever come across."
John Stossel, 20/20 ABC

Looks like that semester of Political Science at junior college was worth it after all!

Friday, October 29, 2010

The "Hot Chicks" Indicator

This is according to google trends (see above). It appears that periods where Dow Jones exceeds Hot Chicks in relative search volume by a few sigmas (standard deviations), a bullish market likely follows, and vice versa.

Easy $$$!

Thursday, October 28, 2010

Implied correlation index KCJ

KCJ is the S&P500 implied correlation index, you can see it at yahoo finance, KCJ link.

It's pretty interesting as like the VIX, it has a negative correlation to the S&P500 index. What makes it cool is that as a correlation, it's implicitly bounded. It could definitely offer an edge for directional forecasts of both underlying markets and volatilities.

So much for words, look at the chart!

Wednesday, October 27, 2010

Intro to High Frequency Finance (Book Review)

Some of the folks at university probably think I'm crazy to spend time on all this non-school related material when final exams are next week... Any way, this was a pretty good, i.e. useful book for a couple of writers with backgrounds in academia. Some of the ideas were practical in real time trading for me, especially the stuff around conditional correlations, seasonal volatility, and rolling regressions.

The good

Lots of descriptive concepts around data analysis, modeling, and trading strategy development. Some of the ideas like normalizing returns via mapping operators to take care of the skew issue with correlations could definitely help improve the trading algorithm development process. The summarized stylized facts could help any new reader become familiar with general statistics of high frequency financial time series.

The less-than-good

It felt like they might have made some things a bit more complicated than necessary.

Over all assessment

It's got some good ideas.

Sunday, October 24, 2010

College degree, not really worth it

So I've been doing some work at a prop trading firm here in Auckland, dealing with mostly Asian index futures. There's some pretty cool folks at the firm, and the IT equipment is "hardcore" enough to pull off some of my strategies where optimal return comes from low-latency execution.

But what's really bothering me is the fact that 100% of what I do to make $$ these days requires skills that I could've gotten off a few books at the local bookshop and maybe a year or two of practical experience, all for $500~ tops! Yet, I've already paid over $100k in tuition for this Bachelor of Honours degree.

Sure, some people would say that "well it's a good piece of paper, it gets you a job interview (if your personal ventures fail miserably)". Still, there're plenty of people like me sitting on the employer side who KNOW that a university degree simply means one can show up on time and maybe type up a neat little report every half year or so, without any practical experience or ability to think critically.

So yeah, is it really worth it? I'd say not.

Thursday, September 9, 2010

VIX Seasonalities & Return Distribution Patterns

Ulises Carcamo Carcamo's PhD Thesis at University of Canterbury (Sept. 4th earthquake) points out a few interesting phenomenons about the VIX and OEX returns from 1988 to 2002. The math applied is relatively fundamental, as this is not an applied math doctorate, a basic understanding of statistics would be sufficient to read this paper.

1. The VIX (CBOE Volatility Index) likely holds some seasonality over time, verified via several statistical means. VIX tests for unit roots resulted negative, that means it is highly probable that VIX values are NOT a random walk, and as expected it holds a mean reverting nature.

2. Patterns, regularities around VIX returns.

VIX Day of the Week Effect (Keep in mind it's negatively correlated with the S&P500 stock index)

There's a statistically significant "Friday-effect".

This could be exploitable, that would take some further work. The bottom line here remains: financial time series do exhibit deterministic characteristics (ergo Random Walk theory sucks :).

Sunday, September 5, 2010

Legal Outsourcing: it is here

What was once unthinkable has today become reality. "Cash-conscious Wall Street banks, mining giants, insurance firms and industrial conglomerates are hiring lawyers in India for document review, due diligence, contract management and more. " This generation of college students must seriously consider potential skill demand before investing the years of time and money/debt into the education industry.

Outsourcing to India Draws Western Lawyers

Partners in the West are asking legal outsourcing companies in India to create dedicated teams of lawyers for their firms, for example. Those teams could expand and contract depending on how much business the Western firm has. 'That means a law firm with 500 members in Chicago can compete with a 2,000-member firm in New York,' Ms. Dalrymple said.

So what's left as "un-outsource-able"? Probably just skills requiring understanding of local culture, language, etc. and self employment. At least that's how I see people survive around here.

Friday, August 6, 2010

Wall St. whistleblower documentary

Interesting talk!

Part 1/9









Friday, July 23, 2010

Fortune's Formula book review

This has got to be one of the most practical and entertaining books I've gone through. It involves crazy smart mathematicians like Claude Shannon, John Kelly, Van Thorp working with gangsters like Longy Zwillman.

A few key concepts worth noting and still practical in today's markets,

1) Statistical arbitrage

Thorp started with Warrents (still traded over the ASX today), convertible bonds against underlying stocks. The average return of these guys in the 80s BEAT Warren Buffet's track record. There still exists plenty of other opportunities today.

2) The Kelly Criterion


  • f* is the fraction of the current bankroll to wager;
  • b is the net odds received on the wager (that is, odds are usually quoted as "b to 1")
  • p is the probability of winning;
  • q is the probability of losing, which is 1 − p.
While making returns more volatile, with a positive expectancy this formula guarantees the highest possible return over time while keeping risk of ruin minimal.

3) Shannon's Demon
Claude Shannon was a freaking genius, and this is his version of a "balanced portfolio", where as long as the traded instrument IS indeed stochastic, a positive expectancy is guaranteed. So it can fit into the category of statistical arbitrage.

Sunday, July 4, 2010

Regret Minimization

I did a mini research paper for Game Theory on the topic of Regret, it's pretty interesting when considered alongside Nash Equilibrium, and financial markets. While Equilibrium proves the existence of a single mixed strategy that guarantees a minimum payoff, this payoff could still be negative, and this would only serve as the maximum payoff if everybody else is achieving equilibrium. In real life games, players often deviate quite a bit from equilibrium.

Investments, trading

The whole buy & hold thing, if done with ETFs to avoid bankruptcy risk, is an equilibrium strategy where the player is guaranteed a return that roughly equals to the actual rate of inflation. This would be an optimal strategy, if everybody else is doing the same, including hedge funds and investment banks. Obviously, that is not so, resulting in the buy & hold folks considerable opportunity loss or "Regret". A change of strategy to minimize "Regret" then is needed to exploit the inefficiencies from other players deviating from equilibrium.

Here's a basic example of regret minimization from Wikipedia,

Minimax example

Suppose an investor has to choose between investing in stocks, bonds or the money market, and the total return depends on what happens to interest rates. The following table shows some possible returns:

Return Interest rates rise Static rates Interest rates fall Worst return
Stocks −4 4 12 −4
Bonds −2 3 8 −2
Money market 3 2 1 1
Best return 3 4 12

The crude minimax choice based on returns would be to invest in the money market, ensuring a return of at least 1. However, if interest rates fell then the regret associated with this choice would be large. This would be −11, which is the difference between the 1 received and the 12 which could have been received if the outturn had been known in advance. A mixed portfolio of about 11.1% in stocks and 88.9% in the money market would have ensured a return of at least 2.22; but, if interest rates fell, there would be a regret of about −9.78.

The regret table for this example, constructed by subtracting best returns from actual returns, is as follows:

Regret Interest rates rise Static rates Interest rates fall Worst regret
Stocks −7 0 0 −7
Bonds −5 −1 −4 −5
Money market 0 −2 −11 −11

Therefore, using a minimax choice based on regret, the best course would be to invest in bonds, ensuring a regret of no worse than −5. A mixed investment portfolio would do even better: 61.1% invested in stocks, and 38.9% in the money market would produce a regret no worse than about −4.28.

Monday, June 28, 2010

Unemployment Benefits- hot topic!

Check out the top 20 list from Alexa,


Hot Topics

When you have young, savy internet users looking up unemployment benefits, it's pretty clear that the so-called "recovery" is just an illusion.

At the same time, you gotta wonder why everybody cares so much about Pinta Island turtles all of sudden...

Wednesday, June 2, 2010

Brazil facing Greece-like difficulty?

Mentioned at Zero Hedge, Brazil's long dated government bonds (due 2021) have had a failed auction. It's interesting how little news coverage this has gotton.

The Brazilian currency however has fared OK. Perhaps this isn't so big of a deal in the eyes of institutional traders. Given the highly negative correlation of USD/BRL to US stock indices, it does look a bit scary, given the last big volatility hike (late 2008) occured at similar exchange rate.

Thursday, May 20, 2010

More disturbing Wall St. information!

Basic run down: the High Frequency Trading algorithms don't likely rely on esoteric mathematical formulas, but rather slightly earlier, probably private information on everybody else's trading behavior. This is borderline Invasion of Privacy...

THEMIS -- Data Theft On Wall Street -- 05.11.10 -

Gretl- FREE econometric, number crunching software

gretl (I have no idea what it stands for) is really cool for time series analysis. What caught my attention was its capability for Cointegration, Unit Root tests (frequently applied for statistical arbitrage strategies).

So yeah, check it out!

Friday, May 7, 2010

Food prices- what the hell!

Year to year food price changes according to National Inflation Association,

* Fresh and dry vegetables up 56.1%
* Fresh fruits and melons up 28.8%
* Eggs for fresh use up 33.6%
* Beef and veal up 10.7%
* Dairy products up 9.7%
OK, so your little buy & hold "portfolio" has made a net gain the last year, yet it probably made a loss factoring in the actual rate of inflation. More importantly, did your financial advisor really deserve to get paid?

This has been mentioned in the article on risks of long term buy & hold schemes, mainly that the stock markets don't do much but adjust with the ACTUALl rate of inflation!

Wednesday, May 5, 2010

James Chanos on Charlie Rose

For anyone who's missed this a few weeks ago, here's the interview link.

What made this interview so great was the way Chanos bluntly (and logically) explains why the credit bubble in China is unsustainable. Then indirectly we start to understand these heavily credit founded economies are all very vulnerable at this point.

Transcript from businessweek:


It's going to be that bad for China?


I think it's going to be that bad for the property market in China. Let's be clear: What we're talking about is a world-class—if not the world-class—property bubble.

What makes it a bubble? What we define as a bubble is any kind of debt-fueled asset inflation where the cash flow generated by the asset itself—a rental property, office building, condo—does not cover the debt incurred to buy the asset. So you depend on a greater fool, if you will, to come in and buy at a higher price. We're seeing behavior [we saw] in 2005 in Miami or '06 or '07 in Dubai.

You have said it's a thousand times worse than Dubai. Well, we said that [with tongue] firmly planted in cheek. But then again, according to a news report this week, there's a developer that's going to put in a new Times Square in suburban Beijing, replete with 32 Broadway theaters. You're beginning to hear about these bizarre developments in China, indoor ski resorts similar to what we saw in Dubai.

O.K. But why don't more people say Chanos is right about the bubble? Why are you standing almost alone? Well, I'm not standing almost alone, actually. There were a number of commentators who were writing about overcapacity in '09. But anytime you make a call like this, particularly if you are viewed as having an embedded financial interest in something going down, you're going to be pretty much off by yourself. There are an awful lot of very powerful vested interests, including the Chinese government, that want to keep things going for a while.

What can Beijing do if it buys into the idea real estate prices are approaching a bubble? They've already begun to take some steps. We're seeing jawboning—attempts to talk the market down. That's not having much of an effect according to the latest prices. They've also begun to take some steps such as requiring higher down payments for second homes. But the fact is the game has to keep going. They're on this treadmill to hell because 50% to 60% of GDP is construction. And if they stop construction, you'll see GDP growth go negative quickly. That's not going to happen because in China, people are rewarded at almost every level of government for making their economic growth numbers. The easiest way to do this: put up another building. So they're really hooked on this sort of heroin of real estate development.

Tom Friedman has said never short a country with $2 trillion in foreign currency reserves. The last two economies that had similar foreign currency reserves relative to the size of their economies were Japan in 1989 and the U.S. in 1929. I'll let that be the end of that discussion.

I read today about a major private equity firm with billions invested in the belief that China will be the world's biggest economy by 2035. They wouldn't do that if they didn't think China could handle this housing bubble. The perception seems to be that China will grow out of this situation. But the problem with that argument is the real estate being built is not for the masses. This is not affordable housing for the middle class. This is high-end condos in major urban areas and high-end office buildings. Just to give you an idea, right now construction costs in China are starting to hit $100 to $150 per square foot in some cities. That doesn't sound like a lot by Western standards, but it means a condominium basically presented to you with no floors, no walls, no appliances costs the average Chinese two-income couple $100,000 to $150,000 U.S. That Chinese two-income couple in their 30s probably makes combined $7,000 or $8,000 a year. You do the math. Even if they were making $10,000 to $15,000 a year, they couldn't carry a $150,000 condo. This is very similar to someone making $40,000 in the U.S. at the height of our bubble buying a $600,000 or $800,000 house. We know how that ended.

Give me the timeline you see. Ah, that's the trouble, the timeline. If I knew that, I'd be a rich guy. My guess is this begins to run its course in late 2010, 2011.

So if there is a collapse, what are the ramifications? These things shake out in different ways. If they devalue the RMB, does it bring out a trade war? Does China fry its burgeoning middle class who are becoming real estate speculators? Does it sacrifice the Western investors? I mean, I don't know.

What are you shorting? There are ways to play Chinese companies outside of China. Either they trade in Hong Kong or New York. Probably more important from an investment point of view, this has implications for the people selling stuff to China—cement, glass, copper, steel.


Brief background:

James S. Chanos is an American hedge fund manager, and is president and founder of Kynikos Associates, a New York City investment company that is focused on short selling.