Portfolio Management Using Bullish Percent Sector Cycles

Wall street sign in New York with New York Stock Exchange background

naphtalina/iStock via Getty Images

After watching and maintaining Bullish Percent Indicator data for seven major indexes and ten sectors of the U.S. Equities market for over 10 years, the cyclical behavior of sectors is quite apparent. Real estate was recently added to the original ten sectors. The Bullish Percent Indicator (BPI) model is designed to capitalize on this cyclical behavior. Hence, the development of the BPI model for portfolio management.

The basic hypothesis is to purchase shares of a sector ETF when in the over-sold condition and to sell when the sector is over-bought. It is a buy low sell high model where guidance for these two decisions comes from Bullish Percent Indicator data. Point and Figure (PnF) graphs are used to generate the BPI data table.

  • Over-sold is when the Bullish Percent Indicator (BPI) percentage drops to 30% bullish or lower. In the table below, those are the percentages with the dark green background.
  • Over-bought is when the BPI percentage rises to 70% bullish or higher. In the data table those are the percentages with the red background.
  • When the bullish percentage for a sector ETF lies between these extremes, the portfolio manager does nothing. Either the sector ETF is part of the portfolio and the manager is waiting for the ETF to move up into the over-bought zone or the manage is holding cash and patiently waiting for the sector to drop into the over-sold zone.

Below is a sample screenshot of six months of Bullish Percent Indicator data for the eleven (11) sectors that make up the U.S. Equities market. Real Estate was recently added to this table so all data for that sector is not unique.

Pay most attention to the left side of the table as it is these percentages one uses when managing the BPI model. This data table is updated weekly.

Sector data table

itawealth.com

Buying and Selling: When the BPI for a particular sector ETF moves to 30% bullish or below, we purchase shares of that ETF. Example ETF tickers are listed at the bottom of the table. For example, in September of 2022 a number of sectors dipped into the over-sold zone so it was time to purchase these securities. When multiple sectors are over-sold we need to make decisions as to how many shares to purchase for the different ETFs. I plan to cover that decision making process in a later article as it requires some special handling.

Once the shares are purchased, the ETF goes into a “quiet mode” until the BPI data for that particular ETF moves into the over-bought zone. If an ETF is purchased and moves into the neutral zone and then back down into the over-sold zone, more shares are purchased if cash is available. Based on the most current data, eight of the eleven sectors are over-bought.

Selling Using TSLOs: To give a specific example of how to handle an ETF in the over-bought zone (70% or higher and red background), one portfolio using the BPI model is currently holding VDC and VNQ, both hitting the sell zone this week. Since the BPI percentage is in the 70% zone for both, Trailing Stop Loss Orders (TSLOs) of 3% were set for each ETF. The idea for using a TSLO is that this permits the ETF to continue to rise in price without being sold out of the portfolio. It is not unusual for a security to reach the 70% zone and then moving higher from that point. We want to take advantage of that continuing price rise and this is where the TSLO comes into play.

Should the BPI hit 80%, place a 2% TSLO on the ETF so as to protect capital. Were the BPI to reach 90%, and this does happen, a 1% TSLO is placed on the ETF.

Handling Cash: When a TSLO is struck and the ETF is sold, what does one do with the cash? The current move is to purchase shares of Schwab’s TIPs (SCHP) as this ETF is generating a yield of 7.0% according you Yahoo data sources.

The BPI model is in the embryonic stage and I have little performance results to report. Currently, two portfolios are managed using the BPI model and if readers wish to pursue and follow the BPI model, I can provide more details.

Be the first to comment

Leave a Reply

Your email address will not be published.


*