Beginners Series Webinar: Join us on Friday, December 18^th, at 2 PM (ET) for our NDW Beginners Series Webinar. This week's topic is Individual Stock Idea Generation. Register Here.

We are excited to announce phase three of the Nasdaq Dorsey Wright Model Builder with the launch of Matrix and FSM-based Relative Strength (RS) Testing Service. As part of this launch, we are granting you free access to the Service for the remainder of 2020. The tool is designed to help you more easily design, test, implement, and monitor custom models powered by the Nasdaq Dorsey Wright methodology. Through the end of December, be sure to join us each Thursday at 1 pm EST for a custom modeler demo presented by the analyst team.

11/12/2020: Matrix Model Builder Demo Replay- Click here

11/5/2020: FSM Model Builder Demo Replay – Click here

Click here to register for future Nasdaq Dorsey Wright Model Builder Demos

Bitcoin ($BTC) surged over the 20,000 mark for the first time ever today (12/17), gathering publicity and investor assets once again.

Individuals invested in the world’s largest cryptocurrency via the Bitcoin Investment Trust (GBTC) are enjoying a nice ride this year, as the ETF-like product is up over 200% through trading yesterday (12/31/2019 – 12/16/2020). The current run reminds some of Bitcoin’s previous charge in 2017, of which was shortly followed by a material drawdown, in excess of -80%, for the digital currency through December of 2018. However, crypto analysts seem to think that this year’s run is different because of an increased institutional presence, stating that prior surges were mainly driven by speculative retail flows. The accessibility of Bitcoin is also growing, as previously highlighted, evidenced by PayPal announcing that users could buy and sell the cryptocurrency, following suit of other large platforms like Square (SQ) and Robinhood.

Bitcoin’s role in a portfolio remains up for debate, as findings about its correlation to other investments appears largely dependent on timeframe and/or asset class. Additionally, keep in mind that Bitcoin was officially launched only 11 years ago, a rather short history compared to other asset classes. Now we find GBTC with a 5.58 fund score and a strongly positive score direction of 3.96, speaking to its latest improvement; however, the space is known to be extremely volatile. To get a feel for such, see the FactSet seasonality analysis below, in addition to an expanded $BTC chart.

For a deeper dive on the cryptocurrency, see our latest feature from October of this year. To view all cryptocurrencies tracked on the NDW Research Platform, navigate to Security Selection > Chart Lists > Cryptocurrencies (bottom left).

Over the last decade, the advisory business has continued to evolve rapidly with the growing trends of lower fees and increased automation. With the influx of low-cost index funds and Robo-advisors offering nearly-free financial planning, investors can now gain beta market exposure at rock-bottom prices without ever setting foot in an advisor's office. The upshot is that it is now more challenging than ever for you as a traditional financial advisor to justify your fee and grow your client base. That said, you must scale your process and sharpen your value proposition as much as possible. To help you do just that, this year's 12 Days of Christmas Series, "Enhancing Your Process With Scalable Customization in 2021," will navigate you through the benefits, use/implementation, and customization of rules-based, Relative Strength-driven guided model portfolios. Additionally, this series will highlight the NDW Model Builder Tool's new features, providing relevant use-cases to help you scale your business in the coming year.

Day 1 - Benefits of Models and a Rules-Based Process

Day 2 - The Relative Strength Process

Day 3 - Model Foundations 

Model Foundations – Technical Attributes and The Fund Score Method (FSM)

In Day 3 of our 12 Days of Christmas of Series, we reviewed the relative strength matrix. Today we’ll review two other foundational concepts – Technical Attributes and Fund Scores - which are key to this year’s theme of “enhancing your process with scalable customization”.

What are Technical Attributes?

When evaluating a stock (or any investment vehicle for that matter), the two components we are most concerned with are relative strength and trend analysis, and the Technical Attribute Rating system is nothing more than an effective means for quantifying the presence (or absence) of those attributes at any point in time.

There are a total of five technical attributes any given stock can attain, which we have outlined below:

5 Positive Technical Attributes

• Relative Strength chart versus the Market on a Buy signal
• Relative Strength chart versus the Market column in Xs
• Relative Strength chart versus its Peer group on a Buy signal
• Relative Strength chart versus its Peer group column in Xs
• Trading above the Bullish Support Line (i.e. in a positive trend)

The technical attribute rating can be found at the top of each stock's Point & Figure chart under the "Stock Data" heading. If a stock has all five of these attributes, it is considered a technically strong stock and such stocks can often serve as market leaders. On the other end of the spectrum, stocks with zero positive attributes are considered the weakest of names. As a result, they tend to carry more risk and are often market laggards compared to other alternatives. It is not to say such a stock can't rise, but our odds of outperformance are much narrower with low attribute names versus high attribute names. On a similar note, it is often impractical to want every stock you buy to have all five traits positive. Our general rule of thumb is that a rating of 3 or better is favorable and increases the odds of success. From an implementation standpoint, using technical attributes to evaluate existing portfolios, especially portfolios being transferred over to you, is one straightforward way to add value. 

While the Technical Attribute system is not the underlying methodology for any of the guided models on the NDW platform, it can be a simple, effective, and scalable tool for managing portfolios of individual equities, i.e., by owning only stocks with favorable technical attribute ratings and exiting positions if their rating deteriorates. Our research has shown that, over time, portfolios composed of stocks with all five positive technical attributes have outperformed portfolios composed of lower attribute stocks.

You can find our white paper that researches this topic on the “Media & Education” page or by clicking here.

Fund Score Method (FSM)

The Fund Score Method (FSM) is a rating system that encompasses both trending and relative strength characteristics. It is dynamic enough to identify short-, intermediate-, and long-term trends in the market.  Every mutual fund and ETF in the NDW database is assigned a Fund Score between 0.00 and 6.00. This score is similar in scope to the Technical Attribute rating system we use for stocks; however, Fund Scores include additional parameters such as chart patterns, moving averages, and momentum. Also, unlike the Technical Attribute rating system, which uses only whole numbers, Fund Scores go out to two decimal places. The Fund Score calculation can be broken down into three components: trend, market relative strength, and peer relative strength. Additionally, the Fund Score incorporates a percentile rank for the fund versus several market and peer groups over different time periods. The Fund Score reflects a two-thirds weighting toward relative strength measures and a one-third weighting toward absolute price measurements. Each fund also has a score direction, which is derived by looking back to a recent peak or trough in the fund's score and comparing it to the current score, telling us whether the fund's score has been improving or deteriorating. 

The fund score of each ETF and mutual fund is displayed at the top of its chart. In most cases, a high fund score will translate into a security that possesses positive trend and relative strength characteristics.

Fund Scores are the underpinning of the Asset Class Group Scores (ACGS), which groups mutual funds and ETFs by categories (e.g, sector, size & style, etc.) Each group is ranked by the average score of its members, providing a map of where strength (and weakness) lies within the market. Similar to the Dynamic Asset Level Investing (DALI) tool, which will be covered in Day 7 of our series, the ACGS can be used as a guide for tactical asset allocation, allowing us to focus our portfolios on areas of strength while underweighting areas of weakness. Groups in the blue "zone" (average score above 4.0) are the strongest, those in the green zone (average score above 3.0) are considered favorable, those in the yellow zone (average score of 2.0 - 2.5) are average, while those in the red zone (average score below 2.5) are areas to avoid. 

Similar to the relative strength matrix we covered on Tuesday, Fund Scores can also be used to rank individual mutual funds and ETFs, which is the basis of the FSM Models. These strategies utilize Fund Scores to select the strongest funds in any given universe. Via the Fund Scores, these models have the ability to rotate within a set lineup of mutual funds or ETFs. Much like the matrix-based models that select the strongest ETFs and hold onto those positions so long as they maintain sufficient relative strength, the FSM models do the same by selecting the funds with the highest Fund Scores. Depending on the update frequency (monthly or by seasonal quarter), the FSM models will allocate to the top two to five highest-scoring funds during each review. We will review specific FSM model offerings on Monday.

The steady improvement across many risk-on groups on the Asset Class Group Scores (ACGS) page has led to a further dampening of the US Money Market group. This caused the Money Market Percentile Rank (MMPR) to drop below 2% for the first time since 2016 at a current posting of 1.41%. This reading has only dropped below 2% a handful of times since the origin of the indicator, dating back to September 2005. In order to examine these market environments closer, we took each date when the MMPR fell below 2% and filtered for only those dates where the MMPR had not been below 2% over the previous two months. This leaves us with four instances prior to Monday of this week. We then took the forward total return of the S&P 500 Index TR.SPXX from each of those dates, looking for returns over the forward 1, 3, 6, and 12-month timeframes. It should be noted that this is a small sample size of instances to work with, and each market environment certainly had its own set of unique circumstances. What we found was that the S&P 500 demonstrated the potential for either muted returns or a slight pullback one month after extremely low MMPR levels. These returns improved substantially as the timeframe examined increased, with the exception of 2011, which saw the pullback extend to the three-month timeframe before improving. The general trend displayed by these returns seems to indicate that the lowest levels for the MMPR have tended to be immediately followed by a period of market consolidation, which ultimately led to continued growth for the major domestic equity benchmark. 

It is difficult to predict from these indications alone whether the next few months will show a further pullback as we saw in 2011, or substantial improvement like we saw in 2016. However, we have already seen some consolidation in those sectors that have led the domestic equity space higher throughout the past several months. The areas of technology and consumer cyclicals are still the top-scoring sectors on the ACGS system, as well as the top two ranked sectors from a relative strength perspective in the DALI tool. These areas have seen similar score movements since early-September, as both groups have fluctuated between average scores of 4.50 and 5. They also each sit slightly south of their score highs over the past six months, leading to muted average score direction reading for both groups.

The SPDR sector representatives for technology XLK and consumer discretionary (cyclical) XLY have been indicative of this recent movement. Interestingly enough, both funds broke out to new all-time highs on their respective point & figure charts with movement Wednesday, with XLK surpassing its September high to advance to $128 and XLY advancing past its November high to $160. They each also possess a favorable fund score north of 4.00 but have negative score directions. While it is generally ideal to look for positive fund score directions, the negative score directions, in this case, do not necessarily indicate that XLK and XLY are weak. Rather, it shows that they have not continued their advances as much as other previously laggard sectors that have shown more rapid improvement over the past few weeks. The slower ascent has also led to further normalization on the trading bands of both XLK and XLY, leaving the funds actionable at current levels from a weekly overbought/oversold (OBOS) perspective.

Daily Option Ideas for December 17, 2020