Formal Studies in Technical Analysis

good effort trader111, keep it up.

The existence of mean reversion does not by itself preclude short-term momentum. Instead, we find short-term momentum in fact interacts with long-term mean reversion. A two-component model for stock price provides a parsimonious characterization of these two effects and their interactions. A strategy based on the rolling-regression parameter estimates from the model generates positive excess returns in all cases, most of which are statistically significant. This combined strategy in general outperforms both the pure momentum strategy and the pure contrarian strategy.

again quoting part of the paper which sounded acceptable to me:







SSRN Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=970852

Fast stochastics gives impressionable signals for NF on EOD time frame. Alternative: The mathematical construction of stochastics makes it go to extreme region if there is a one-sided move for 5 consecutive bars. In short term it is very often that a ticker makes a one sided move for seemingly extended period. This makes fast stochastics unworthy on 5 min. time frame, more so for stocks. For stocks even on EOD time frame it requires a lot of combining with other methods, if used for swing trading. However index futures show a more mature behavior, a one sided move is atleast met by healthy retracement or a top/bottom reversal for range bound market on next larger time frame.

Got the difference! One simple statement versus a seemingly difficult full pahragraph.

Good trading is'nt about finding a 'good' system. It is about understanding market behavior.

There is a widespread belief in financial markets that trends in prices are arrested at support and
resistance levels that are to some degree predictable from the past behaviour of the price series. Here we examine whether ratios of the length and duration of successive price trends in the Dow Jones Industrial Average cluster around round fractions or Fibonacci ratios. We identify turning points by heuristics similar to those used in business cycle analysis, and test for clustering using a block bootstrap procedure. A few significant ratios appear, but no more than would be expected by chance given the large number of tests we conduct.

No magic in the Dow debunking Fibonaccis code

Secret codes hold no magic for investors, Professor Batchelor says

Thursday, 14 September, 2006

Every day, in financial markets all over the world, investors try to forecast stock markets. To identify target levels where prices might peak or trough, many traders use rules based on the sequence of Fibonacci numbers, recently brought into public consciousness by the bestseller The Da Vinci Code.

Does the stock market really follow patterns governed by numerology? In Magic Numbers in the Dow, Roy Batchelor, Professor of Banking and Finance at Cass, and researcher Richard Ramyar rigorously analyse daily movements in the Dow Jones Industrial Average stock index from 1914 to 2002. They conclude that, contrary to the beliefs of many technical analysts, there is no evidence that markets reverse at levels indicated by Fibonacci ratios such as 0.618 and 1.618.

Professor Batchelor comments: Nowadays we think that most short term movements in prices in financial markets are random. However, it is a natural human characteristic to look for patterns even in random data, and traders are under added pressure to rationalise their actions and display expertise. Theories of stock market waves are manifestations of this illusion of control, the instinct that makes us throw the dice harder when we want a high number. Certainly our studies suggest that the Fibonacci rule is just an illusion.

The Fibonacci sequence of numbers appears in the work of the celebrated thirteenth century mathematician Leonardo Fibonacci da Pisa. His Liber Abacci (1202), or Book of Calculation, was the first Western business mathematics text, and helped popularise algebra and the decimal system in Europe.