Low Volatility
Low Vol Selection Criteria Overlay
A volatility overlay using standard deviation or rRisk allows you to combine the Relative Strength and Low-Volatility factors by selecting the lowest volatility securities from those at the top of your matrix/fund score ranking.
With the below settings, each evaluation period your model will select the 10 stocks among your buy territory with the lowest volatility. Since the "Only Apply Overlay Rules to Buys" checkbox is unchecked, a stock will be sold if its volatility ranking falls below the top 10 or if its Matrix ranking falls below the sell threshold.
With the below settings, your model will initially select the 10 stocks among your buy territory with the lowest volatility. Since the checkbox is checked, a stock’s volatility ranking will not cause it to be sold. A holding will only be sold if it falls below your matrix/fund score rank sell threshold. Once a holding is sold, it is replaced with the lowest volatility stock in your buy territory that isn’t already owned by the model.
Standard deviation and rRisk will yield identical rankings. rRisk is calculated by dividing a security’s standard deviation by the standard deviation of the S&P 500. Since the denominator is common for all securities, it will have no impact on the ranking.
This rule set will lead to higher turnover since it will make trades to remain concentrated in the 10 least volatile stocks among the buy territory. To combat the increased turnover, you may consider lengthening the evaluation frequency or checking the "Only Apply Overlay Rules to Buys" checkbox so the model will only sell securities based on their Matrix/fund score ranking.
Low Vol Filter Overlay
A low volatility filter overlay allows you to set a maximum level of volatility that the securities in your buy territory must remain under in order to be held by your model. Unlike the low volatility overlay discussed above, this overlay will not necessarily select all of the lowest volatility securities from your buy territory, but it will help you avoid the highest volatility securities among your buy territory.
If you intend to use a volatility filter, rRisk is likely a better option than standard deviation since the figures are normalized and, thus, easier to build a rule for. rRisk is calculated as the standard deviation of the security divided by the standard deviation of the S&P 500. Therefore, a filter that says rRisk needs to be less than 1.2 is meant to exclude funds with greater than 20% more volatility than the S&P.
With these settings, each evaluation period your model will only select funds if their rRisk is less than or equal to 1.2. Since the checkbox is unchecked, a fund will also be sold if its rRisk is above 1.2 on an evaluation date.
With these settings, your model will only buy funds if their rRisk is less than or equal to 1.2. Since the checkbox is checked, a fund will only be sold if its matrix/fund score rank falls below the sell threshold.
Make sure your buy territory is not too small and your filter is not too limiting that your model ends up with fewer holdings than you intended. If this happens, you can move your buy threshold lower in the matrix/fund score rankings (in the “Strategy” step of building your model) or make your filter less restrictive (an rRisk greater than 1.2 in this case).
Yield
Yield Selection Criteria Overlay
A yield overlay allows you to combine the Relative Strength and income factors by selecting the highest-yielding securities from those at the top of your matrix ranking. This allows you to ensure you are buying high Relative Strength securities while getting as much yield as possible in the process.
With the below settings, each evaluation period your model will select the 10 securities among your buy territory with the highest yield. Since the checkbox is unchecked, a security will be sold if its yield ranking falls below the top 10 or if its matrix/fund score ranking falls below the sell threshold.
This rule set will lead to higher turnover since it will make trades to remain concentrated in the 10 highest-yielding stocks among the buy territory. To combat the increased turnover, you may consider lengthening the evaluation frequency or checking the "Only Apply Overlay Rules to Buys" checkbox so the model will only sell securities based on their Matrix/fund score ranking.
With the below settings, your model will initially select the 10 stocks among your buy territory with the highest yield. Since the checkbox is checked, a stock’s yield ranking will not cause it to be sold. A holding will only be sold if it falls below your Matrix/fund score sell threshold. Once a holding is sold, it is replaced with the highest-yielding stock in your buy territory that isn’t already owned by the model.
A longer holding period will also help ensure that you receive the dividend and hence realize the benefit of owning high-yield stocks.
Yield Filter Overlay
A yield filter allows you to combine the Relative Strength and income factors by ensuring your model only selects securities that meet a minimum yield requirement. This allows you to ensure you are buying high Relative Strength securities that also generate your desired amount of yield.
With the below settings, your model will only buy stocks with a dividend yield of at least 1%. Since the checkbox is unchecked, a stock will be sold if its dividend yield falls below 1% or if its matrix/fund score ranking falls below the sell threshold.
With the below settings, your model will only buy stocks with dividend yields of at least 1%. However, since the checkbox is checked, a stock’s yield falling below 1% after it is bought will not cause it to be sold. A holding will only be sold if it falls below your matrix/fund score rank sell threshold.
Technical Attribute/Fund Score
Technical Attribute/Fund Score Selection Criteria Overlay
A technical attribute/fund score overlay allows you to combine the Matrix concept with our stock ratings or fund scores that measure overall technical strength, making sure your holdings are considered strong by both measures. This overlay will naturally only be used on Matrix models since FSM models already rank securities by their technical attribute rating (stocks) or fund score (ETFs and Mutual Funds).
With the below settings, each evaluation period your model will select the 10 stocks among your buy territory with the highest technical attribute rating. Since the checkbox is unchecked, a stock will be sold if its technical attribute ranking falls below the top 10 or if its matrix ranking falls below the sell threshold.
With the below settings, your model will initially select the 10 stocks among your buy territory with the highest technical attribute ratings or fund scores. Since the checkbox is checked, a stock’s technical attribute ranking will not cause it to be sold. A holding will only be sold if it falls below your matrix rank sell threshold. Once a holding is sold, it is replaced with the stock in your buy territory with the highest technical attribute rating that isn’t already owned by the model. Matrix ranking is used as a tiebreaker if two stocks have the same technical attribute rating.
Technical Attribute/Fund Score Filter
A technical attribute/fund score filter allows you to combine the Matrix concept with our stock or fund scores that measure overall technical strength, making sure holdings are considered strong by both measures.
With the below settings, your model will only buy stocks with technical attribute ratings of 4 or higher. Since the checkbox is unchecked, a stock will also be sold if its technical attribute rating falls below 4 or if its matrix/fund score ranking falls below the sell threshold.
This rule set will lead to higher turnover since matrix rank is not the only factor determining if a holding will be sold. To combat the increased turnover, you may consider lengthening the evaluation period or relaxing the filter requirement to make sure more securities meet the standard.
A technical attribute/fund score filter might also be used as a way to provide your model with potential downside protection in a down market. In the below scenario, since there are no stocks in this universe rated 3 or higher, the model would be allocated entirely to cash at the moment.
In this case, you would want to make sure the "Only Apply Overlay Rules to Buys" checkbox remains unchecked so the model will sell any holdings that fall under your chosen technical attribute/fund score threshold.
Overbought/Oversold
OBOS Selection Criteria Overlay
An OBOS overlay allows you to attempt to avoid securities that are trading well above their 10 week moving average and may be likely to experience mean reversion in their price in the near term.
With the below settings, each evaluation period your model will select the 10 most oversold/least overbought stocks among your buy territory. Since the checkbox is unchecked, a stock will be sold if its OBOS% ranking falls below the top 10 or if its matrix/fund score ranking falls below the sell threshold.
This rule set will lead to higher turnover since it will make trades to remain concentrated in the 10 least overbought stocks among the buy territory. To combat the increased turnover, you may consider lengthening the evaluation frequency or checking the "Only Apply Overlay Rules to Buys" checkbox so the model will only sell securities based on their Matrix/fund score ranking.
With the below settings, your model will initially select the 10 most oversold/least overbought stocks among your buy territory. Since the checkbox is checked, a stock’s OBOS ranking will not cause it to be sold. A holding will only be sold if it falls below your matrix/fund score rank sell threshold. Once a holding is sold, it is replaced with the stock in your buy territory with the lowest OBOS that isn’t already owned by the model.
OBOS Filter Overlay
An OBOS filter allows you set a maximum overbought level for your holdings in an attempt to avoid securities that are trading at the top of their trading band and may be likely to experience mean reversion in their price.
With the below settings, the model will only buy stocks that are less than 70% overbought. Since the checkbox is unchecked, a stock will be sold if its OBOS% rises above 70% or if its matrix/fund score ranking falls below the sell threshold.
Generally, our analysts prefer to buy/hold securities that are not considered too overbought, which they generally classify as securities with OBOS above 70%. However, you may need to adjust this number depending on your other model settings, the volatility of the model's underlying holdings, and your desired level of model turnover. Setting a higher OBOS threshold will help correct for this by reducing the amount of turnover while helping you avoid securities that are severely overbought.
With the below settings, your model will only buy stocks with OBOS of less than 70%. Since the checkbox is checked, a stock’s OBOS rising above 70% will not cause it to be sold. A holding will only be sold if it falls below your matrix/fund score rank sell threshold.
Score Direction
Score Direction Selection Criteria Overlay
A score direction overlay allows you to favor securities that have shown the most improvement in their scores over the last 6 months.
With the below settings, each evaluation period your model will select the securities within your buy territory with the highest score direction. Since the checkbox is unchecked, a security will be sold if its score direction ranking falls below the top 4 or if its matrix/fund score ranking falls below the sell threshold.
With the below settings, your model will initially select the 4 funds among your buy territory with the highest score direction. Since the checkbox is checked, a fund's score direction ranking will not cause it to be sold. A holding will only be sold if it falls below your matrix/fund score rank sell threshold. Once a holding is sold, it is replaced with the fund in your buy territory with the highest score direction that isn’t already owned by the model.
Score Direction Filter
A score direction filter allows you to avoid securities that have exhibited signs of relative weakness in the last 6 months.
With the below settings, your model will only buy securities with a positive score direction. Since the checkbox is unchecked, a security will be sold if its score direction falls below 0 or if its matrix/fund score ranking falls below the sell threshold.
With the below settings, your model will only buy securities with a positive score direction. Since the checkbox is checked, a security will not be sold if its score direction falls below 0 after it is bought. It will only be sold if its matrix/fund score ranking falls below the sell threshold.
Trend
Trend Selection Criteria Overlay
A trend overlay allows you to prioritize investing in securities that are in a positive trend on their Point & Figure chart.
With the below settings, your model will favor stocks in your buy range that are in a positive trend. If the number of stocks in a positive trend is less than your target number of holdings, the model will invest in the stocks in a negative trend with the highest matrix/fund score ranking. Since the checkbox is unchecked, a holding will be sold if it falls out of the top 10 of this ranking.
With the below settings, your model will initially select the top 10 stocks in these rankings, again favoring stocks in a positive trend and then stocks in a negative trend with the highest matrix/fund score ranking if necessary. However, since the checkbox is checked, a stock will only be sold if its matrix/fund score rankings falls below the sell threshold.
Trend Filter
A trend filter allows you to ensure your model only purchases stocks that are in a positive trend on their Point & Figure chart.
With the below settings, your model will only invest in stocks in a positive trend. Since the checkbox is unchecked, a stock will be sold if it falls into a negative trend after it is purchased or if it falls below the matrix/fund score sell threshold. Once a holding is sold, it is replaced with the highest ranked stock in a positive trend that the model does not already own.
With the below settings, your model will only invest in stocks in a positive trend. However, since the checkbox is checked, a holding will not be sold as a result of falling into a negative trend. A stock will only be sold if it falls below the matrix/fund score sell threshold. Once a holding is sold, it is replaced with the highest ranked stock in a positive trend that the model does not already own.
If you are looking to create a model that only invests in securities that are in a positive trend, using a filter will be the best option as the "change selection criteria" option may invest in stocks in a negative trend if the number of stocks in a positive trend is less than the model's target number of holdings.
RS Signal
RS Signal Selection Criteria Overlay
With the below settings, your model will favor stocks in your buy range that are on an RS buy signal vs. the market. If the number of stocks on an RS buy signal vs. the market is less than your target number of holdings, the model will invest in the stocks on an RS sell signal vs. the market with the highest matrix/fund score ranking. Since the checkbox is unchecked, a holding will be sold if it falls out of the top 10 of this ranking.
With the below settings, your model will initially select the top 10 stocks in these rankings, again favoring stocks on an RS buy signal vs. the market and then stocks on an RS sell signal vs. the market with the highest matrix/fund score ranking if necessary. However, since the checkbox is checked, a stock will only be sold if its matrix/fund score rankings falls below the sell threshold.
RS Signal Filter
An RS signal filter allows you to ensure your model is only buying securities that are on a Relative Strength buy signal vs. the market.
With the below settings, your model will only invest in stocks on an RS buy signal vs. the market. Since the checkbox is unchecked, a stock will be sold if it moves to an RS sell signal vs. the market after it is purchased or if it falls below the matrix/fund score sell threshold. Once a holding is sold, it is replaced with the highest ranked stock on an RS buy signal vs. the market that the model does not already own.
With the below settings, your model will only invest in stocks on an RS buy signal vs. the market. However, since the checkbox is checked, a holding will not be sold as a result of moving to an RS sell signal vs. the market. A stock will only be sold if it falls below the matrix/fund score sell threshold. Once a holding is sold, it is replaced with the highest ranked stock on an RS buy signal vs. the market that the model does not already own.
If you are looking to create a model that only invests in securities that are on an RS buy signal vs. the market, using a filter will be the best option as the "change selection criteria" option may invest in stocks on an RS sell signal vs. the market if the number of stocks on an RS buy signal is less than the model's target number of holdings.