Category Archives: Stocks

Productivity and Deflation

What happens when productivity grows faster than production?

We produce more with less work and that means unemployment, right? Initially, the answer is yes, but looking at history we can see that the answer is more encouraging than that. Productivity growth eventually transitions into falling prices. And these days, it should happen even faster. Here’s why:

Competition and consumer choice, especially now that information flows so freely, has led to much more efficient markets in terms of pricing. Improving productivity is rarely unique to a particular company… in other words, if one company benefits from a new technology, then others follow, competition drives prices down, and consumers ultimately benefit.

Are falling prices always good?

Falling prices is called deflation, and deflation is an ugly beast; it exaggerates the disparity in the distribution of wealth and creates an artificial investment hurdle. Deflation increases the buying power of wealth. It makes money more powerful. Those who have money can buy more with it, and people in debt fall deeper in debt. This makes the “real” distribution of wealth even more concentrated. Similarly, deflation means that your cash grows in value; if your cash grows in value, then your investments will have to appear very strong before you will be willing to make them.

The solution to these problems is a low stable inflation rate. Low stable inflation helps to maintain investment by discouraging holding cash, slowly eroding stagnant concentrations of old wealth unless it is invested.

In order to achieve a low stable inflation rate, the deflationary pressure of productivity growth should be balanced by growth in the money supply and a low FED Funds rate. The faster productivity grows (and it appears to be accelerating over the decades), the more aggressive the Federal Reserve may have to be in order to avoid deflation.

XML Standard for Business Reporting / Accounting

TechWeb reports in this ARTICLE on Edgar Online‘s support of XBRL, an XML standard for companies to publish and distribute financial reports.

Such a standard would be a strong movement in the direction of efficient valuation and pricing of fundamental business characteristics. Arbitrage pricing theory could be applied using each XBRL tag as a factor, resulting in the ability to calculate values and sensitivities for stock prices based on changes to the underlying fundamentals in detail.

AI and Program Trading

NewScientist published a good article describing neural network program trading systems.

An extension allows for a large number of competing signalling systems. One such signalling system may be an improvement on traditional cointegration techniques.

Sun Microsystems should acquire Yahoo

Sun Microsystems should acquire Yahooo! and integrate its web services into StarOffice and Webtop using SOAP or XML-RPC. The resulting desktop/webtop service would eliminate the need for many local applications, would revolutionize the sharabilility of files and information, and would free us to work with our personal(ized) computer from any computer. Eventually, all Webtop services would be publicly SOAP enabled, eliminating the interface maintenance burden and enabling open “skinning” possibilities.

Cointegration improvements

Cointegration typically uses the price information for two related securities, and provides relative value signals. As with traditional technical trading strategies, changes to the fundamentals create a risk of bad relative value signals. With 2-security cointegration, this risk is doubled because changes to the fundamentals of either company can skew the relative value signal. However, this problem can be cut in half by creating baskets (portfolios) of securities and running the cointegration analysis with each security against the basket. This effectively generates signals which are skewed only by changes to the fundamentals of the individual security. Additionally, the required correlation matrix for the permuted set of security combinations can be replaced by a single vector of correlations – greatly improving calculation efficiency and extending the analysis processing potential.

To improve upon normalizing data to % changes, factors typically associated with beta may also provide better signalling data. For example, as the size of a company grows over the course of a few years, its price volitility may fall. Similarly, as market cap grows, the price change correlations may increase relative to larger cap baskets and decrease relative to smaller cap baskets.

By backtesting, optimal trigger strengths and bet sizes can be measured, however, given the correlation coefficients, volitilities, number of positions, and risk preferences, probabalistically optimal bet sizes may provide better results.