by Philip Wu
In our last Blog article 3/16/2023, we identified WFC from the financial sector to trade based on “Logic chain” analysis. Please refer back to the article as to why WFC was chosen as the symbols to trade. In this article we will analyze how WFC performed.
To determine which symbols had the most movement, you can calculate the percentage change and the volatility of each symbol over the past period. Here are two methods:
PERCENTAGE CHANGE:
To calculate the percentage change for each symbol, you calculate the difference between the symbols's closing prices during the measurement period. Then divide that difference by the closing price at the beginning of the measurement period and multiply the result by 100 to get the percentage change. The symbol with the largest percentage change will have had the most movement throughout the measurement period.
VOLATILITY:
Another way to measure the movement of a symbol is to calculate its volatility during the measurement period. You can calculate volatility using the standard deviation of the daily percentage changes in the symbols' price during the measurement period. The symbols with the highest volatility will have had the most movement throughout the period.
spy-xlf-wfc performance
When we first identified WFC compared to 10 other major holdings in XLF , it exhibited the highest AutoFramer Reward to Risk ratio of 8.2:1, had a high Regression line Fractal Framework at 2.7:1, and was in a "Godzilla" condition. The chart below are the price comparisons of SPY, XLF, and WFC since 3/15/2023. During this period SPY rose 1.16%, XLF fell -3.1%, and WFC fell -7.8%. Also during this period WFC’s volatility was 1.3x higher than XLF and 1.8x higher than SPY. Based on these results, our “Find the Mover” was effective in identifying WFC as a symbol that was in a critical state that was about to move higher or lower.
Other godzillas
In our last blog article on 3/16/2023, we also scanned for symbols in a Godzilla state using our Owl bundle on Thinkorswim. The table below shows the symbols ranked order by their volatilities. As can be seen by the table, nearly all these symbols had higher volatilities than SPY.
SUMMARY
We used Logic Chain analysis and various filters to “Find the Movers”, those symbols that are about to move higher or lower for purposes of short term trading. The Godzilla filter was shown to be effective during this measurement period in identifying the movers for short term trading.