Methods

We analyzed 11 year history of a thousand stocks to find the relationship between various price patterns and short-term returns. It was found that one needs to consider many time frames to obtain the most reliable data.

Computer analysis of 4, 8, 16 and 32 day price patterns (16 patterns for each time interval) for all stocks has been performed, and the 3 day average returns for all patterns have been calculated.  The patterns are related to the trends and price position within the trading ranges.

As a result, we calculated the Growth Parameters (GP) for every pattern. GP are the most probable short-term return in %. The average GP is calculated as

GP = (GP4 + GP8 + GP16 + GP32)/4

where GP4, ..., GP32 are the growth parameters for 4, 8, 16 and 32 day patterns.

During the day of analysis we identify the price patterns for all index components (stocks) and calculate the expected index return GP. On the front page of this site we plot negative values of GP for the DJIA and the NASDAQ-100 to make our graphs similar to other well known predictors.

The large positive values of -GP indicate an overbought condition. The large negative values of -GP indicate an oversold condition.

Daily Services
- Growth Parameters of 24 market and industry indices.

- Sorted lists of stock index components with Growth Parameters for every stock. The first stocks in the list are the most bullish (large GP). Example

- Stocks to watch: all considered stocks are sorted. The beginning (most bullish stocks) and the end (most bearish stocks) of the list are published. Example

You can use this lists for short-term trading or for starting long-term investing.


 

Historical Returns
The returns of the first stocks in the sorted lists are much higher than average. Let us show short-term returns depending on the stock position in the sorted list. The return were calculated since 1999. It should be noted that the price patterns used were obtained from 1988 - 1998 market data. The red lines show the average return.