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Market Noise

November 25, 2009 // Posted in Market Noise (Tags: , , , , ) |  Comments Off

All markets have a normal level of noise. The stock index markets have the greatest amount of irregular movement due to its extensive participation, the high level of anticipation built into the prices, and because it is an index. This is contrasted to short-term interest rates, which have large participation but little anticipation and a strong tie to the underlying cash market. In comparison, long-term rates allow for greater movement away from the cash market. The normal level of noise can be seen as the consistent daily or weekly trading range on a chart of the DJIA or S&P When volatility declines below the normal level of noise, the market is experiencing short-term inactivity An increase in volatility back to normal levels of noise should not be confused with a breakout.
This same situation can be applied to a triangular formation, which has traditionally been interpreted as a pause within a trend. This pattern often follows a fast rise and represents a short period of declining volatility. If volatility declines in a consistent fashion, it appears as a triangle; however, if the point of the triangle is smaller than the normal level of market noise, then a breakout from this point is likely to restore price movement to a range typical of noise, resulting in a flag or pennant formation. Both of these latter patterns have uniform height that can include a normal level of noise.

The Ultimate Project Selection Rule

November 19, 2009 // Posted in Financial market (Tags: , , , , ) |  Comments Off

Optimal project selection is easier said than done. It is easier for two projects at a time, as it was in our aquarium example, because there are only four options to consider: take neither, take one, take the other, or take both. But the complexity quickly explodes when there are more projects. For three projects, there are eight options. For four projects, there are sixteen options. For ten projects, there are about a thousand options. For twenty projects, there are over a million options. (The formula for the number of choices is 2N , where N is the number of projects.) Even the simplest corporate projects can easily involve hundreds of decisions that have to be made. For our little aquarium, there are about 54,000 different fish species to consider—and each may interact with many others. These choices do not even consider the fact that some projects may allow other projects to be added in the future, and that many projects are not just “accept” or “reject,” but “how much project to take.”
To help us determine which projects to take, we need to find suitable heuristics, i.e., rules that simplify decisions even if they are not always correct. One common heuristic algorithm is to consider project combinations, one at a time. Start with the project combination that, if you were only allowed to take two projects (one pair from a set of many different projects), would give you the highest NPV. Then take this pair as fixed, i.e., treat it as a single project. Now see which project adds the most value to your existing pair. Continue until adding the best remaining project no longer increases value. Computer scientists call this the greedy algorithm. It is a good heuristic, because it drastically cuts down the possible project combinations to consider, and usually gives a pretty good set of projects. There are many possible enhancements to this algorithm, such as forward and backward iterations, in which one considers replacing one project at a time with every other option. Full-fledged algorithms and combinatorial enhancements that guarantee optimal choice are really the domain of computer science and operations re- search, not of finance. Yet many of these algorithms have been shown to require more time than the duration of the universe, unless you make simplifications that distort the business problem so much that the results seem no longer trustworthy. Fortunately, economics is in our finance domain, and it can also help us simplify our project selection problem.