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Chart of the Day 2012/02/01: October Soybean Meal Futures

Jeff

Published: 2012/02/01Posted in: Chart of the Day, Commodities

Chart of the Day 2012/02/01: October Soybean Meal Futures

For today’s chart of the day, I have chosen October soybean meal futures. Soybean meal is an important industrial byproduct from producing vegetable oil. It is used for producing animal feed and also a growing number of human foodstuffs such as ice cream, performance beverages and meal replacement bars.

Since the lows in December, soybean meal futures have performed well but have also taken on a characteristic look that suggests the price has been rising too rapidly–it looks almost like a rising wedge, considered to be a bearish pattern. The price may rise a bit further but the upside potential looks uncertain and the downside risks significant. Short strategies look as though they might be more successful, but it is hard to be very sure at this point. If I planned on playing these, for now, I would try waiting for the rising wedge to extend and/or for a clear support break to develop–or for a good reason to take on a bullish position.

A COMPREHENSIVE OVERVIEW OF POPULAR TECHNICAL INDICATORS II. STOCHASTIC OSCILLATOR, PART 1

Jeff

Published: 2012/01/29Posted in: Featured, Stocks, Technical Analysis

A COMPREHENSIVE OVERVIEW OF POPULAR TECHNICAL INDICATORS II. STOCHASTIC OSCILLATOR, PART 1

Hello again. If you have been following this series, you may have noticed that I haven’t yet comprehensively covered Bollinger Bands. We’ll be revisiting them in the future. For now, let’s turn our attention to one of my favorite technical indicators, the popular (but poorly-named) stochastic oscillator.

A stochastic oscillator takes three parameters and produces two outputs, known as %K and %D. The parameters are:

A span parameter, which specifies how many bars the oscillator will cover. The most popular configuration is 14 days.
A Ksmooth parameter, which specifies how many bars should be used for smoothing the %K oscillator. The most popular value is 3, but often people will use Ksmooth=1. This is known as the fast stochastic oscillator
A Dsmooth parameter, which specifies how many bars should be used for smoothing the %D oscillator. The most popular value is 3. Occasionally people will use a shorthand specification where it is assumed that Ksmooth=Dsmooth. This is known as the slow stochastic oscillator

Calculation of the unsmoothed %K parameter is as follows: Look back of the last span bars and find the lowest and highest prices. Use the formula $A COMPREHENSIVE OVERVIEW OF POPULAR TECHNICAL INDICATORS II. STOCHASTIC OSCILLATOR, PART 1$ . To calculate the smoothed version, calculate the simple average of the unsmoothed %K parameter over Ksmooth days, i.e. $A COMPREHENSIVE OVERVIEW OF POPULAR TECHNICAL INDICATORS II. STOCHASTIC OSCILLATOR, PART 1$ . Calculation of %D is similar, but rather than smoothing the unsmoothed %K parameter over Ksmooth bars, we instead smooth the smoothed %K parameter over Dsmooth bars: $A COMPREHENSIVE OVERVIEW OF POPULAR TECHNICAL INDICATORS II. STOCHASTIC OSCILLATOR, PART 1$

The stochastic oscillator is thought to signal noteworthy events when the %K line crosses the %D line. It is thought that where the crossover occurs is also of some importance; if a crossover occurs above 0.8, it is thought to have a different meaning than a crossover that occurs below 0.2.

Calculating stochastic oscillators on all major-exchange U.S. stocks at all timepoints in the Yahoo! Finance database that I have been using for test purposes (eliminating any stocks that have ever traded below $1.00) and then calculating the geometric averages of the five-day returns of stocks meeting various criteria leads to the following table:

14, 3, 3 Full Stochastic Oscillator Test Results, 5-day Close-to-Close, Geometric Averages
	%K Crosses Above %D	%K Crosses Below %D
Above 0.8	(0.043%)	(0.071%)
Below 0.2	0.272%	0.387%

Geometric Average 5-day Return, Close-to-Close: 0.087%

From this table we can see that choosing a random non-penny U.S. stock and holding it for five days is not a very good strategy. But choosing a non-penny U.S. stock at close when its %K crosses below its %D below 0.2 and then selling it at close five days later has shown in the test data (which is, admittedly, somewhat incomplete) returns averaging about 20% per year (minus commissions). While it is impossible to say with certainty how well such a strategy would perform in the real world, clearly, there is more to the stochastic oscillator than random chance.

A COMPREHENSIVE REVIEW OF POPULAR TECHNICAL INDICATORS I. BOLLINGER BANDS, PART 3

Jeff

Published: 2012/01/16Posted in: Technical Analysis

A COMPREHENSIVE REVIEW OF POPULAR TECHNICAL INDICATORS I. BOLLINGER BANDS, PART 3

In a recent post, I suggested that Bollinger bands *might* be useful in a trading strategy by themselves but warned that it could be risky. Let’s take a look….

If you had made a trade in the past 30 years based solely on a high Bollinger band reading, more often than not, the stock price would have risen in five days. But if you had invested all of your money in several trades that way in sequence, odds are, you would have lost money! How is that possible?

It’s simple: When you lose money on the stock market, you have to make a larger percent gain in order to make back your money. If you have a 25% loss, you need a 33% gain just to break even. Three 25% gains are more than wiped out by a single 50% loss.

This chart was prepared by calculating the geometric average of all possible 5-day changes from close to close in the Yahoo! Finance stock market historical data available on January 13, 2011 across bins of 0.1 deviations (eliminating any stocks that had ever traded below $1). While it implies that stocks that are far below their lower Bollinger bands may be profitable short-term purchases, some care should be taken in interpreting this chart, as it may understate the risk for purchases. In addition, this chart should not be used as a substitute for simulation, and past performance is not always an indicator of future results.

A COMPREHENSIVE REVIEW OF POPULAR TECHNICAL INDICATORS I. BOLLINGER BANDS, PART 2

Jeff

Published: 2012/01/16Posted in: Chart of the Day, Technical Analysis

A COMPREHENSIVE REVIEW OF POPULAR TECHNICAL INDICATORS I. BOLLINGER BANDS, PART 2

To prepare this chart, I calculated the 20 day Bollinger bands of every stock currently listed on Yahoo! Finance (as of January 13, 2012) that has never been priced below $1, at every available timeframe. I then observed the increase in closing price over a 5-day period. The intensity of each slot on the heat map is normalized relative to others directly above or below it.

In the absence of other information, it would seem that the most likely place for a stock price to be 5 days from now is where it is right now, as illustrated by the bright region across the center. You can see support/resistance lines at 1 Bollinger band and 3 Bollinger bands, with weaker support/resistance lines at about 2 1/2 Bollinger bands. Stocks that closed at those levels were more likely to remain at at those levels after five days than stocks that closed at other levels.

Due to the truncation on the chart, you can see that stocks which had Bollinger band readings above 3 were more likely to move much higher over the next 5 days than other stocks. Stocks with Bollinger band readings below 3 were also more likely to move much higher, although the odds weren’t nearly as good as those of stocks with extremely high Bollinger band readings.

Summary:

We didn’t find any evidence supporting the popular 20 day, 2 deviation Bollinger band configuration. That doesn’t mean it doesn’t exist, but we haven’t found it yet. There did appear to be weak support/resistance at around 2 1/2 deviations from the 20 day average.
We found some evidence that there was support or resistance at the 1 deviation Bollinger band on a 20-day timeframe.
We found some evidence that there was support at the 3 deviation Bollinger band on a 20 day timeframe. Stocks that passed outside the 3 deviation Bollinger band were somewhat more likely than other stocks to post large gains, especially if they had passed 3 deviations above the 20 day average.

Well, that was pretty enlightening! While some risk is involved, it appears that Bollinger bands might be able to function alone in profitable strategies. They are more useful, though, in conjunction with other indicators. Check back later in this series for further analysis of Bollinger bands and other popular indicators.

UPDATE: Part 3 shows more details on the distribution of returns of Bollinger band-only strategies.

A COMPREHENSIVE REVIEW OF POPULAR TECHNICAL INDICATORS I. BOLLINGER BANDS, PART 1

Jeff

Published: 2012/01/14Posted in: Technical Analysis

A COMPREHENSIVE REVIEW OF POPULAR TECHNICAL INDICATORS I. BOLLINGER BANDS, PART 1

A new investor cannot spend much time reading about how to time trades without reading about Bollinger Bands. While rarely discussed in academic research, Bollinger Bands are the most popular volatility model. The notion is simple: Calculate the average closing price and its standard deviation over a series of sliding windows, each one covering a fixed number of bars. Find the upper and lower bands by adding and subracting a multiple of the standard deviation from the average stock price, and BAM! You have Bollinger Bands.

This procedure has some appeal to many people who have had a little training in statistics. It resembles the widely-taught procedure for calculating confidence intervals on a normal distribution.

There are, however, a few problems with the analogy of Bollinger Bands and normal confidence intervals:

Stock prices do not really follow a normal distribution. They more nearly follow a log-normal or even a Levy distribution. Sometimes, people use log Bollinger Bands to partially compensate for this deficiency, but that is uncommon.
Stock prices show a high degree of autocorrelation. Ordinarily, we would expect that the price today would be highly correlated with the price tomorrow–and that the price tomorrow would be highly correlated with the next day’s price. This violates a key assumption used for calculating ordinary normal confidence intervals, i.e. that all samples are independent.
It isn’t clear what would be indicated if the stock price crosses a Bollinger Band. Does it indicate that the stock price has reached an improbable level and that regression towards the mean is to be expected? Or does it indicate that there has been a shift in the mean?
Bollinger Band calculations use the population standard deviation rather than the sample standard deviation. Common wisdom from introductory statistics classes would suggest using the sample standard deviation and the t-distribution within a normality framework.

Of course, it is a bit unfair to apply these criticisms to Bollinger Bands without noting that the same criticisms can be applied in varying degrees to a wide array of volatility models. And it is worth considering that given the popularity of Bollinger Bands, they affect investor behavior, causing forseeable price shifts. In the next article in this series, we will empirically examine the historical behavior of stock prices with relation to their Bollinger Bands in popular configurations.

Site Updates This Weekend

Jeff

Published: 2012/01/14Posted in: Announcements

ixvivxi.net may be down sporadically this weekend for site updates. It will be back up on Tuesday morning, January 17, 2011 after Martin Luther King, Jr. Day.

How Money Works, the Short Version

Jeff

Published: 2012/01/02Posted in: Chart of the Day, Top Level

There are an awful lot of people who don’t understand how the modern monetary system works. If you were to ask 100 people at random what institution is responsible for printing money, I’d expect 70 of them to name the U.S. government. Actually, it’s the Federal Reserve, which is technically an independent entity. Most people don’t realize that when the federal government borrows money, it doesn’t even pay it back; that’s left to the Federal Reserve, which pays it back by borrowing more money or just printing it. And while Federal Reserve vaults do hold large quantities of gold, most of it doesn’t belong to the U.S. There is nothing backing U.S. dollars except the full faith and credit of the U.S. government–and force.

So here’s how it works: The Federal Reserve is the source of all U.S. dollars. Its major activity consists of loaning money to the federal government, which spends it. The federal government also demands payments from people who produce things. These demands give money its value. Money spent goes to the people of the U.S., who both buy and sell various goods and services–including capital–to the rest of the world. The people also carry out transactions with the Federal Reserve, buying and redeeming government bonds.

Between every major actor in the monetary system, the flow of money is two-directional–except between the federal government and the Federal Reserve. Money flows from the Federal Reserve to the federal government, but it does not flow back. But the Federal Reserve can only print money; it can’t create wealth. So the wealth represented by the money that it prints and loans to the federal government can only come from the diminution of capital–inflation, the collapse of the housing market, stock market crashes, and so on.

A little bit of inflation forces the wealthy to generate economic activity to maintain their fortunes. But if the government spends too much for too long, the economy stops functioning. It’s a tricky issue. But politicians at the federal level must address it or be replaced by their successors.

Cullen Roche: Rail Traffic Shows Continued Economic Expansion

Jeff

Published: 2012/01/01Posted in: Economic Data, Transportation

Cullen Roche: Rail Traffic Shows Continued Economic Expansion

On his excellent blog, Pragmatic Capitalism, Cullen Roche regularly features charts of data drawn from the AAR Weekly Rail Traffic Summary. At the present time, Roche does not see a recession on the immediate horizon. I didn’t see a chart in the most recent edition of Roche’s coverage of the rail data, but much of the AAR weekly summary data can be easily extracted from their PDF reports using simple text-processing tools.

Read more at Pragmatic Capitalism: RAIL TRAFFIC SHOWS CONTINUED ECONOMIC EXPANSION | PRAGMATIC CAPITALISM.

Some Predictions for 2012

Jeff

Published: 2011/12/30Posted in: Uncategorized

Some predictions for 2012:

The housing market will bottom out (50%). If you need some property, get the best deal you can, but buy it. If you want to speculate, buy it only at exceptional value.
There will be a mild recession in the second half (60%). Things have been slowing down; a lot of economists have been predicting recession or even saying that one has happened already. I don’t think there is a lot to be concerned about, but a mild recession should not be surprising to anyone.
Mitt Romney will be elected President of the United States (70%). Credible models have predicted that he will the the Republican nominee, and credible models have predicted that a Republican will be elected President this cycle.
Republicans will gain majority control of the Senate (90%). There are more Democrats retiring than Republicans, and there are more Democrats than Republicans in contested seats. Combine that with a weak economy under Democrat control, and you can see that Republicans will almost certainly take over the Senate.
The Euro will survive (90%). Brad DeLong has said straight out that the Euro is going to survive. Cullen Roche has said that failure of the Euro is almost “unfathomable.”
The Occupy movement will gain some credibility as a political force, not on par with the Tea Party but more on the level of the Teamsters. Some would say that this has already happened.
Natural gas consumption will rise modestly (70%). Natural gas is cheap and can be used as a gasoline substitute. Plus several coal-fired power plants are being retired by the Obama administration.
Gasoline prices will fall modestly (60%). This is due in large part to expanded use of natural gas.
The U.S. will suffer a domestic terrorist attack (70%). We haven’t had a high-profile domestic terrorist attack in a while. It is only a matter of time.
Apple’s market share will wane (60%). With Steve Jobs gone, Apple is like a headless chicken. History has shown us that Apple without Jobs is a greedy brand with strict technology controls, poor innovation, and high prices.
There will be no significant additional legislation placed on high-frequency trading or any other exchange trading (80%). Republicans and Libertarians won’t allow it. Some rules may even be relaxed.

On Prediction Accuracy

Jeff

Published: 2011/12/29Posted in: Uncategorized

In the past month and a half, I made on social networks six short term predictions. I was correct about only one of these, the survival of the Euro. Fortunately, I did not lose any money on trades or embarrass myself all that much. Since the probability of using a coin flip to making predictions with equal or lower accuracy is 0.0625, I concluded that I was probably doing something wrong. After some reflection, I concluded I have been making two mistakes:

Excessive Skepticism of Authority–Some amount of skepticism is healthy, even towards society’s most trusted sources. I don’t believe everything that comes out of Ben Bernanke’s mouth–or Paul Krugman’s. But really, I have been doubting authority more than is justified in most circumstances. Once in a while, even the most prophetic of prognosticators makes a mistake. But more often than not, individuals who are considered to be “experts” or “authorities” make correct predictions when undertaking the task.
Insufficient Skepticism in Adversarial Situations–It seems obvious, but when faced with highly adversarial situations such as those seen in currency trading, it is essential to take any opinions, even of so-called “experts,” with a grain of salt. Where people have an economic incentive to lie, to mislead, to spread disinformation, some proportion of people will do exactly that. When market movers can gain material advantage by moving the market counter to expectations, they will do so. Skepticism alone will not shield you from all conceivable adversarial actions, but it does provide some armor against them.

Of course, it is always possible to avoid being wrong by hedging your statements (or at least almost always). By “hedging” I mean that you can suggest that there is some possibility that the most likely conclusion is not the one that will occur. One common way to do this is to use the statements of others to make your points. An often stronger way is to clearly and fully state your belief, detailing circumstances under which the most likely outcome might not arise. Of course, you can always just present the evidence that leads to your belief and let observers reach their own conclusions.

So, in summary: Trust authority. Be cautious in adversarial environments. Hedge.

See you in the new year!