The Sweep Down function allows you to use a benchmark to determine how your model is allocated. This feature is most frequently used as a way to add a cash component to your model. In this case, the Sweep Down function allows you to allocate a larger percentage of your portfolio to cash the higher a cash proxy rises in your Relative Strength rankings, potentially providing a degree of downside protection in periods of underperformance within your model universe. Below, we will outline this use case as well as a few of the other uses for the Sweep Down function.
Sweep Down Indicator
When you designate a ticker in your model universe as the Sweep Down Indicator, you are telling the model that if any of your current holdings fall below the Sweep Down Indicator, that holding's allocation should be redirected elsewhere. You can choose to redirect these assets either to the securities ranked above your Sweep Down Indicator or to a specific ticker of your choice.
A security must be included in your Matrix universe in order to be designated the Sweep Down Indicator.
Swept to Security
When you choose the option to have your Sweep Down assets invested in the Swept to Security, you are instructing the model to invest your assets in a specific security when the Sweep Down is triggered.
The Swept to Security does not have to be a ticker included in your model. For example, you could choose to use our cash proxy- MNYMKT- as the Sweep Down Indicator (benchmark) but have the model invest in short term treasuries- SHY- once the Sweep Down is triggered.
Choosing a Swept to Security outside of the model universe allows you to use one of our system matrices with our cash proxy MNYMKT built into it but have the model invest in the security of your choice once the Sweep Down is triggered. System matrices have richer history behind them and attempt to control for survivor bias, so it is generally beneficial to use those when the option exists.
In the below example, the model uses MNYMKT as the Sweep Down Indicator and the Swept to Security. There are 10 holdings, so each holding has a target weighting of 10%. Since MNYMKT ranks 9th, this model would have approximately 80% invested in the securities ranked 1-8 with the remaining 20% "swept" into MNYMKT.
Sweep Down Rank
Sweep Down Rank allows you to control the sensitivity of your Sweep Down by instructing the model to ignore your Sweep Down Indicator until it rises to a certain level in the Matrix rankings. If left blank, the Sweep Down will trigger when the Sweep Down Indicator passes any of the model's current holdings regardless of where the Sweep Down Indicator currently ranks.
Moving the sweep down rank up will likely reduce the speed at which cash enters the portfolio but may also help reduce the instances where your portfolio gets whipsawed by cash briefly rising in the rankings and entering the portfolio and then quickly falling back down and being sold.
For example, in the below scenario the Sweep Down would only occur if MNYMKT was ranked at 5 or higher in the Matrix.
In this example below, the model uses MNYMKT as the Sweep Down Indicator and the Swept to Security and the Sweep Down Rank is set at 5, meaning the model will ignore MNYMKT until it reaches #5 in the matrix ranking. There are 10 holdings, so each holding is approximately 10% of the portfolio. Since MNYMKT only ranks 9th, this model remains 100% invested.
Securities Ranked Above Sweep Down
The option to direct Sweep Down Assets to securities ranked above the Sweep Down Indicator allows you to concentrate your portfolio in securities that are exhibiting higher Relative Strength than a benchmark while avoiding those that are exhibiting lower Relative Strength than that benchmark.
In the example below, the model has a maximum of 10 holdings, meaning when MNYMKT ranks 11th or lower, the model will hold 10 securities with a target weighting of 10% each. However, when MNYMKT ranks 10th or higher, the model will only hold those securities ranked above MNYMKT. In this case, since MNYMKT ranks 9th, the model will hold equal-weighted positions in the securities ranked 1-8 and each will have a target weighting of 12.5%.
Using the Sweep Down as a Cash Component
In the below example, the goal of the model is to gradually invest in cash as MNYMKT rises up the Matrix rankings. In this case, the model is set to own 5 funds, which means each holding will have a target weighting of 20%. This model has the following parameters:
- Target Number of Model Holdings: 5
- Sweep Down Indicator: MNYMKT
- Sweep Down Assets Invested in: Swept to Security
- Swept to Security: MNYMKT
- Sweep Down Rank: 5
- Setting the Sweep Down Rank equal to the Target Number of Holdings essentially instructs the model to ignore MNYMKT until it would normally be a holding itself
Based on the current rankings, the model would remain fully-invested. However, the way the model rules are set up means the cash position will function as follows:
- MNYMKT ranked 5th- 20% cash
- MNYMKT ranked 4th- 40% cash
- MNYMKT ranked 3rd- 60% cash
- MNYMKT ranked 2nd- 80% cash
- MNYMKT ranked 1st- 100% cash
To give you an idea of how this cash component works for this particular universe and rule set, the below chart shows this model's changing allocation over time with the blue highlighted areas indicating the model's allocation to cash.
Using the Sweep Down for Sector Rotation
In the below example, the goal of the model is to invest in all sectors that are ranked above SPX and avoid those that are ranked below SPX. In order to set up the model in this way, enter these parameters:
- Target Number of Model Holdings: 100%
- Buy Criteria: Entire Universe
- Sweep Down Indicator: SPX
- Sweep Down Assets Invested in: Securities Ranked Above Sweep Down Ticker
In this case, the model would currently own equal-weighted positions in each of the 12 sectors ranked above SPX.
To give you an idea of how this sector rotation strategy works for this particular universe and rule set, the below chart shows this model's changing sector allocation over time.