Basic Models of Complex Systems

Crux of the Duplex Method
plus Case Study
of the Dow Stock Index

We live in a world full of complex and chaotic systems. A good example concerns the stock market that stymies all manner of investors ranging from casual amateurs to gung-ho professionals.

According to the Efficient Market Hypothesis, the current price always reflects the totality of information available to the investing public. As a byproduct, no one can detect any clues for predicting the market in a trusty fashion.

Instead, the market is deemed to move in an utterly erratic way. In particular, a popular myth known as the Random Walk shuffle contends that the price level shifts with equal likelihood and to similar extent in either direction, whether to the upside or downside.

At first glance, the image of pure randomness does ring true in practice. For instance, the average investor is unable to beat the market averages such as the Dow Jones index. While the lack of success may seem like a letdown, the truth is even worse. In actuality, the participants in the aggregate lag comfortably behind the benchmarks of the bourse.

If we look more closely, the lousy performance of the actors springs mostly from their frantic efforts to beat the competition. Amid the frenzy, the demons of greed and fear prod the antsy players into making impulsive moves that are not only groundless and futile but actually counterproductive and harmful to their cause.

On the bright side, though, the market displays a smattering of patterns that can be exploited by a sober person. An example concerns the seasonal cycle behind the monthly moves of the Dow benchmark.

To fathom the elusive waves in a stringent fashion, we turn to the duplex method of modeling shifty systems. The sturdy framework makes use of the binomial test: the simplest and strongest, as well as safest and surest, way to profile chancy events regardless of the domain.

To this end, we first transform the conceptual models of the stock market into a trio of precise templates. The formal blueprints are then converted into R code: the top choice of programming language and software platform for statistical workouts. The trenchant results serve to debunk the fable of efficiency and confirm the existence of hardy patterns in the marketplace.

In short, the benefits of the seasonal model lie in simplicity and potency in sundry forms. The drawcards include the ease of acquiring the information required, the leanness of the dataset employed, the ubiquity of the software deployed, the universality of the experimental setup, and the strength of the conclusions at high levels of statistical significance.  

NOTE:  The full report is titled, “Basic Models of Complex Systems”. The document may be downloaded in PDF form at Smashwords or ResearchGate. Moreover, a digest of the report is available as a video at YouTube or Internet Archive.

 

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Financial Forecasting in Practice

 Of Human Bondage and Mental Reach in Financial Forecasting

One way or another, financial forecasting is an integral part of investment planning. Whether an outlook happens to be an explicit forecast or a vague impression, the investor has to envision the outcome downrange in order to make an intelligent decision today.

In a global market that grows ever more complex, an entire industry has sprung up to size up the prospects for assets ranging from stocks and bonds to commodities and properties. On the downside, the purveyors of forecasts have a lousy record of foretelling the market. For instance, the gurus as a group make calls that are worse than random guesses on the direction of the stock market. Remarkably, even the top tier of renowned pundits cannot match the performance of a coin toss in predicting the bourse.

On the upside, though, the market displays a variety of patterns which can help the investor in forecasting prices and managing portfolios. Admittedly, the power to predict the market is far from perfect. Even so, a limited ability to anticipate the movement of prices is far better than none at all.

A series of incisive studies by level-headed researchers has shed some light on the chaotic domain of financial markets. The findings provide a better grasp of the forces at work as well as the modes of behavior and the limits to forecasting. To a greater or lesser degree, financial prediction lies within reach for investors with little or no money to spare for oracles, and scarcely any time to devote to the task.

More on Financial Forecasting in Practice.

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Mirage of the Stock Market: Track Records for Investment Funds Can Be Misleading

In ironing out an investment strategy for managed accounts, a standard procedure is to examine the prior performance of the investment funds. Contrary to popular belief, however, a track record in the financial markets proves nothing of substance. As a case in point, a superior portfolio that outpaces the stock market can be constructed in a systematic fashion as explained in this article. The method adopted here may be viewed as an instance of proof by demonstration.

More on  Mirage of the Stock Market: Track Records for Investment Funds Can Be Misleading.

Shifty Data For Investment Planning - Patchy Statistics Deceive Investors

Investors are exposed to two forms of risk in the financial markets. One type of threat is discussed openly by the financial community and the business press, while the other is seldom acknowledged in spite of its whopping importance.

In the financial community, the term "risk" usually refers to the volatility of the price of an asset. We may refer this type of bugbear as chronic risk.

In addition to the fluctuation in price, however, there is a menace lurking in the background which the financial community rarely talks about in spite of its importance. All too often, an asset or even an entire fund breaks down and goes kaput. In that case, the investors in the vehicle end up losing their shirts in one fell swoop.

Since the notion of total ruin is a pariah in financial circles, hardly anyone likes to talk about it. In line with this state of affairs, there is no terminology that is in general use for this type of bogey.

Given its significance to the investor, however, the subject ought to be brought into the open and given its due. In the absence of a suitable term, we will refer to the prospect of death as terminal risk.

This type of threat is almost always ignored by the statistics of the forum. The omission is especially baleful in the case of a compilation such as the average performance of the "Top 100 Firms" in a particular area.

More on   Shifty Data For Investment Planning - Patchy Statistics Deceive Investors.