Why are Americans Workaholics?

By BankersBall, 27 July 2006

Every summer, someone invariably brings up the fact that Europeans get so much more vacation that we do in the States. It’s usually chalked up to the fact that Europeans are so much more “chill” about life (the pro-Europe POV), or that Europeans are just lazy (the pro-US POV).

Knowledge@Wharton cite experts with more economically oriented explanations:

  • In the US, status = more possessions, more money, more, more more. In Europe, people actually view the ability for long vacations as a sign of status. Says Wharton professor Mauro Guillen “Having fun, or being able to have fun, also is a sign of success and a source of social esteem.” Any Euros care to respond to whether this is true or not?
  • European countries provide less incentive to work more hours because of higher marginal taxes. Any explanation about the masses using taxes as a motivation I’m a bit wary about since most people don’t even know how to do their taxes here.
  • 9/10 European workers are covered by unions who fought for more vacation (why that versus other benefits is another issue), vs. 2/10 in the US.

How about the fact that Americans as a people aren’t comparable to the people in other countries, because those who come here are self-selecting hard workers who moved specifically to improve their lot?

Sharpe ratio, key hedge fund risk gauge is ‘flawed’

By Nassim Taleb (Reuters, 23 July 2006)

The Sharpe ratio is a measure of risk-adjusted return. It is the difference between returns and a risk-free interest rate – often the yield on US Treasury bills – divided by the volatility or range of possible returns. It has been used in recent years to persuade investors such as pension funds that it is less risky to invest in hedge funds than equities.

The Sharpe ratio, a key measure of performance used by hedge funds to sell themselves, is flawed and tells investors nothing about the risks they are taking, Nassim Nicholas Taleb, a hedge fund investor and a professor in the sciences of uncertainty at the University of Massachusetts.

“It’s used for marketing. It looks sophisticated, but the volatility part is not a good measure of risk,”. “The Sharpe ratio is like a horoscope … A startlingly high number of people rely on this bogus theory … It’s a big scam by finance professors …” said Taleb in an interview earlier this week.

At the root of the problem is the assumption that economics and finance are solid sciences, which allows the use of statistical tools such as the law of averages and the normal distribution to model returns. Being normally distributed means that most outcomes will fall within a narrow range either side of the mean. But the idea can only be applied to things like weight or height, where an extreme reading will not distort the mean if the sample of people is large and representative. It cannot be applied to exceptional extreme events in finance such as large losses or gains that will continue to dominate the picture no matter how large the sample gets.

“If the exception doesn’t matter in the long-run, then the law of averages applies … If the exception continues to dominate the sample even if the sample becomes very large, you can’t use the normal distribution,” Taleb said.

“It can’t be applied to socio-economic variables … An example is stock market returns … In the last 50 years, 10 days represented more than half of stock market returns.”

Hedge fund returns are another example. US-based Long Term Capital Management (LTCM) collapsed in 1998 in the wake of the emerging market crisis as liquidity dried up because of large trading losses using a model based on the law of averages.

“LTCM had lots of small up months and a few large down months,” Taleb said. “This is not detected by the Sharpe ratio as it assumes a symmetry in the distribution of returns.”

Baltic Freight Index

Last 3 years:
Baltic Freight live chart

Jul 2005 – June 2010:
Baltic Freight chart 2005-2010

Long-term from 1994:
Long term Baltic Freight (BDIY) chart


  • The Baltic Freight Index gives an indication of global export volumes as it measures cargo rates on freighters
  • It has been said by some to provide a leading indication of Chinese growth
  • It is been historically highly correlated to the Australian dollar

How to trade with the trend

By Victor Sperandeo

The idea of a trend is so intuitive as to never get a formal definition in technical analysis, even not in the classic Technical Analysis of Stock Trends by Edwards and MacGee. Sperandeo makes the following definition,

An uptrend is a sequence of rallies to successively higher highs, punctuated by pullbacks, with each pullback low ending above the previous pullback low.
and conversely for a downtrend,

A downtrend is a sequence of declines to successively lower lows, punctuated by rallies, with each rally high ending below the previous rally high.
From the definition of a trend, a trend line can be given a precise definition.

An uptrend line is drawn under prices, joining the lowest low to the highest pullback low which does not pass the line through prices in between. The line is then extended past the date of the highest high.
The condition that the line must not pass through prices between the points it joins means that it’s not necessarily the most recent low which is joined, but might be only a prior one. When the line is extended to the right, it might then pass through prices, that’s a possible indication of a trend change. A downtrend line is defined similarly,

A downtrend line is drawn above prices, joining the highest high to the lowest rally high which does not pass the line through prices in between. The line is then extended past the date of the lowest low.

1-2-3 Rule
Sperandeo identifies a change of an uptrend as

1. Trend line (defined above) broken.
2. Prices no longer making new highs.
3. Prices fall below a previous minor rally low

Or conversely for a downtrend,

1. Trend line (defined above) broken.
2. Prices no longer making new lows.
3. Prices fall rise above a previous minor rally high.

Either of 1 or 2 is a probable trend change. Two of the three conditions is an increased probability of a change. All three is the definition of a trend change.

2B Rule
Point 2 above is essentially a failure of prices to carry past a previous rally (or previous selloff). Sometimes prices go just past then immediately reverse. Such a case is Sperandeo’s rule 2B,

2B. If prices rise just above the previous rally high but then immediately fall back down.

Or for a downtrend change,

2B. If prices fall just below the previous low but then immediately rise back up.

Sperandeo regards 2B as a powerful pattern, and in assessing the probability of a trend change he weighs it higher than any other single criterion. The advantage of a 2B is that it lets the trader get almost the exact top (or bottom) of a move (with a stop-loss at the failed high or low). Even if it worked only 1 in 3 times the reward side is excellent due to getting in early.

Four day rule
The four day rule is Sperandeo’s favourite pattern for a change in intermediate trend. The rule is

In an intermediate trending move, a reversal in the form of 4 days against the trend is highly likely to be a trend change.

This rule is based on his examination of trend changes in the Dow Jones Industrial Average from 1926 to 1985. He defines a variant as the “four-day corollary”,

In an intermediate trending move, a sequence of 4 days with the trend followed by 1 against is highly likely to be a trend change.

This rule is looking for a climax over a series of days, instead of a single high-volume climax day.

Identifying Trends

By Ray Barros

In “Anatomy of a Trade”, I said that identifying the trend of the timeframe you are trading is important because it sets up the strategy for your trade. In other words, in an uptrend, you buy dips or upside breakouts, in a downtrend, you sell rallies and downside breakouts and in a sideways trend, sell the top end of the range and buy the bottom end.

It is almost a cliche that “trends are where traders make their money”. However, I believe that you need to go beyond merely identifying a trending market. To maximise my profits, I would rank the type of trending market I am in.

For the purposes of these notes, I am assuming a monthly uptrend. The monthly is therefore the “trader’s timeframe trend”.

Moves in the direction of the trend (ie up moves), I shall be calling “impulse moves” or “impulsive” and moves in a direction opposite to the trend (ie down moves), I shall be calling “corrective moves” or “corrections”.

This article will suggest four categories. They are ranked from “0” to “3”, with “0” being the most difficult to make money and “3” being the easiest provided you can identify it.

The key to the categories is the relationship between the impulse and corrective waves by the amount that one overlaps the other.

Ranking “0”


1 Corrections of the impulse move tend to be between > 67% to < 87.5%.

2 Breakouts are followed by a correction between > 67% to < 87.5% and a deep re-entry (ie greater than 50%) into the previous correction. eg After the breakout at “3”, the market retraces between > 67% to < 87.5% of “2” to
“3” and greater than 50% of “1” to “2”.

3 At either Point 5 or point 7, the trend or trend type will change. In other words, the market will either change from an uptrend to a downtrend or at Point 5 or point 7 change to a Ranking of 1 or 2 or 3

Profit Potential

Unless you identify it, it is difficult to make money in this type of trend.

Breakout traders have to wear the pain of the retracement. Most will place their stops below the 50% or 67% retracement areas and will continually get stopped out.

Responsive buyers

ie buyers on dips will probably not get set.

Responsive sellers at the top end of the ranges will make some money if they take partial stops or use some form of trade management. Otherwise, they also will be stopped out continually.

Ranking “1”


1 Corrections of the impulse move tend to be between > 33% to < 67%.

2 Breakouts are followed by a correction between > 33% to < 67.% and a shallow re-entry (ie 50% or less) into the previous correction. eg After the breakout at “3”, the market retraces between > 33% to < 67.% of “2” to “3” and 50% or less of “1” to “2”.

Profit Potential

Profit potential is reasonable.

The danger points are the correction following the breakout when re-entry occurs below the point of breakout. Good trade management is necessary.

Ranking “2”


1 Corrections of the impulse move tend to be between > 33% to 50%.

2 Breakouts are followed by a correction between > 33% to 50% and no re-entry into the previous correction. eg After the breakout at “3”, the market retraces between > 33% to 50% of “2” to “3”
and above “1”.

Profit Potential

Profit potential is excellent as this is the most orderly of all the trends. When the market retraces into the previous correction’s range, you will KNOW that a CIT is imminent.

Ranking “3”


1 Strong (in terms or price and time) directional move after a confirmed CIT on breakout above “1”.

2 No corrective moves.

Profit Potential

Profit potential is poor unless identified early or you have developed special rules to deal with it. This type of trend can prove very frustrating for the responsive trader as the market steams ahead without any corrections.

Breakout traders can make excellent money as the market quickly turns poor trade location into fine ones.

Novice traders learn extremely dangerous habits as they “learn” that the market will get them out of trouble as long as they trade with the trend and “isn’t easy to identify a trend that will go on forever” (??!!)

Types of Traders

Trading and Exchanges: Market Microstructure for Practitioners by Larry Harris

Central to the book is the division of market participants into the following categories:

1. Informed traders, who profit by bringing prices into line with where they should be

2. News traders, who take announcements and evaluate them and hasten prices to their proper levels

3. Dealers, who provide liquidity to other traders by buying and selling out of their often very expensive inventory, from their very extensive communications and research base

4. Order anticipators, the parasites who frontrun and imitate the actions of those higher in the chain of information

5. Bluffers, who disseminate false information not related to fundamentals to create transitory movements to the cost of all others

6. Utilitarian traders, those who provide the energy that makes the system go round, including investors and borrowers who move money through time and hedgers who use the market to reduce the risk that price moves would have on their businesses

7. Asset exchangers, who switch among instruments to create the optimum portfolio as the economic backdrop and their own conditions change

8. Gamblers, who trade for entertainment.

Is there foreign exchange trading over the weekend?

By Chris Melendez

In order to have a better understanding of these fiascos, one has to have a little bit of history. Real exchange rates are set by banks and in the end determined by capital flows. Before the electronic age in fx, rates were set by banks using voice brokers. Banks also traded directly through one another via phone, and the Reuters dealing system. dealing would start in Auckland/Wellington on Sunday afternoon/Monday morning Wellington time. Australian banks would start early Monday too. Not every bank in the world had New Zealand or Australian branches. So on Friday afternoon, they would telex their orders to a friendly bank down under and have them watched until their Tokyo branch came in. Some banks wouldn’t even consider the early Pacific region a viable center, and would send their orders directly to their Tokyo or Singapore branch.

So in New Zealand, the dealer would look at where his currency closed. Let’s say dollar yen closed at 118.00. He would look at his orders which were at 117.90 to buy and 118.10 to sell. He would then punch into the phone line to his broker and say ninety-ten I deal. There would be the New Zealand open of dollar yen. 20 points wide. Then another bank would be a better buyer, and punch into the same broker and say ninety eight bid. Another bank might be a better seller and say, 03 I sell. Thus, 98-03 would be a reasonable dealing spread. This would be the same for the other major currencies. Scandinavian and some European currencies were not traded until at least Tokyo opened.

Sometimes, before the first price was made by the dealer, there might have been a geopolitical event that had happened over the weekend. It could be a comment, terrorist event, natural disaster, or even a revaluation/devaluation. Since we are on yen, let’s say that for example, over the weekend, Tokyo had a horrific earthquake. This would obviously be bad for Japan, and the yen. The yen dealer at the bank would know this, and at the very least would not want to be selling dollars and buying yen. More accurately, he would raise his bids much higher in the market. An American dealer in Sydney was famous for this. He might have had a 120.40 stop loss for good amount, and trigger it. Other banks would have similar orders, and follow suit. That is how true ‘gaps’ happen.

In the early nineties EBS (or electronic broking system) was created by a consortium of 14 banks, and almost completely did away with voice brokers. It is the benchmark for establishing highs and lows in most currencies with the exception of cad, sterling, and sometimes aussie dollar. Banks relied more and more on the EBS, and a whole consolidation of the industry started to happen. Banks would close branches, and many, even go 24 hours.

This whole business of retail platforms filling their customers on stops before the real market opens is rubbish. These platform operators are making an absolute fortune doing it.

There used to be some trading on Saturday within the Arab world, and some bullion trading in between the houses in Hong Kong, but it was not recognized in the real world.

Prices are only as good as the people who input them. The market opens in Wellington in the morning. Anything in between New York close on Friday, and the Wellington open is not real. Anyone who wants to tell you different should go back to Macau, Vegas, or Atlantic City…

The Trading Sessions

There are actually five over-lapping trading sessions that trade 24 hours a day between Sunday evening and Friday evening. The New York exchange trades from 7:30 am to 5 pm EST. The Sydney, Auckland and Wellington exchanges trade from 3 pm to 11 pm EST. The Tokyo Exchange trades from 6pm to 11 pm, they stop to take a lunch break for an hour, then trade until 4 am EST. The Hong Kong and Singapore exchanges trade from 7 pm to 3 am EST. The last exchanges to trade are the Munich, Zurich, Paris, Frankfurt, Brussels, Amsterdam, and London exchanges, which trade from 2:30am to 11:30 am EST.

Equity returns at the turn of the month

By Wei Xu and John J McConnell, July 2006 (Full paper (240kB), )

A turn-of-the-month effect in U.S. equity returns was initially identified by Lakonishok and Smidt (1988) using the DJIA for the period 1897-1986. According to the turn-of-the-month effect, equity returns over the interval beginning the last trading day of the month and ending three days later are significantly higher than over other days.

Using CRSP daily returns, we find that the turn-of the-month effect persists over the recent interval of 1987-2005: in essence, over this 19-year period (and over the 109-year period of 1897-2005) all of the excess market return occurred during the four-day turn-of-the-month interval. Thus, during the other 16 trading days of the month, on average, investors received no reward for bearing market risk.

We further find that the turn-of-the-month effect is not confined to small or low-priced stocks; it is not confined to the December-January turn-of-the-month; it is not confined to calendar-quarter-ends; it is not confined to the U.S.; and it is not due to market risk as traditionally measured: the standard deviation of returns at the turn-of-the-month is no higher than during other days.

This persistent peculiarity in equity returns poses a challenge to both “rational” and “behavioral” models of asset pricing.