Guide to Using Alternative Data In Equity Research to Deliver Alpha: The 13 Stock Picks for H2 2019

Alternative data has become a mainstream source of data for investment managers, with up to 50% of funds now using it as a part of their research process. The question of how to get value from alternative data is no longer about access to the data sets; there are hundreds of vendors offering alternative datasets or services. Rather, it is a question of how to make that data useful to every equity analyst driving investment strategy.

Download the Picks Whitepaper now.

Large funds have made multi-million dollar investments in data science teams and big data infrastructures in an attempt to win an alternative data arms race that is predominantly driven on the hope of finding the needle in the haystack, big bet investment. However, with our 13 Alternative Data Stock Picks, we have proven that the most successful approach to alternative data is to directly embed it into the core research workflow for analysts, effectively democratizing alternative data.

This guide outlines how we used the Sentieo platform to pick our initial 11 stocks from the first half of the year, the performance of these stocks, and our Alternative Data Picks for the second half of 2019.

How Sentieo Makes the Alternative Data Stock Picks

For both the original Sentieo 11 and the new Sentieo 13 picks, we used the same methodology:

We started with the Sentieo Mosaic screen, where we looked for:

  •     A high correlation between the alternative data composite and revenue growth and/or KPI
  •     Large acceleration in the alternative data (our proxy for end-user demand) versus the consensus expectations

These correlations and significant changes in trends are what drive analyst usage of Alternative Data.

Usage of Alternative Data in Mosaic is easy to customize and is completely transparent: users can see basket weights, as well as data set performance for different time frames.

Our next step is to marry the broad screen results with our team’s 60+ years of collective fundamental, qualitative investing experience. Sentieo augments human decision-making: the charts and the stats will not give you the “why.” We do not adhere to specific investment style boxes, but we do look for revenue growth as the single largest driver of long-term results. No business ever shrank its way to greatness.

The ideal picks have strong revenue growth because they:

  •     Operate in high-growth industries, supported by long-term secular megatrends
  •     Are the leaders in their respective industries
  •     Tend to be underpriced relative to their growth rates

As a result, this set of long ideas has relatively high near-term P/E. We also looked at earnings momentum through a combination of the classic earnings upwards revision, plus our alternative data Mosaic index. Most alternative data sets do come from consumer-generated data, and most of our picks are in these two broad groups. As more and more consumer behaviors shift to digital, we expect to see the alternative data sets become more and more predictive.

Sentieo 13 H2 2019 Alternative Data Picks

Our latest set of picks is based on exactly the same methodology as before, but we have expanded our focus a little wider. Note: These are not stock recommendations, and we are sharing them to show the power of the Sentieo platform in bringing together the power of a complete financial research platform with both traditional and alternative datasets.

1) SNAP

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2) PLNT

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3) TWTR

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4) CROX


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To see Sentieo’s 9 other picks, download the full whitepaper here.

We’ll also be discussing all the picks and how we made them during our upcoming live webinar, featuring Sentieo’s CEO, Alap Shah. Register here.

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Disclaimer

The content of this report references opinions and is presented for product demonstration purposes only. It does not constitute, nor is it intended to be, investment advice or recommendations. Readers should assume that Sentieo staff members hold direct and/or derivative positions in all securities mentioned, and may transact in any and all of these securities, at any time, without notice. Seek a duly licensed investment professional for investment advice. Sentieo is not registered in any investment advisory capacity in any jurisdiction globally.

Wall Street Consensus Trades Fell Apart in 2016: 16.2% Underperformance

Following Consensus Trades worked in 2013 and 2014, and started to lose some money in 2015. After running the numbers, we were shocked to see this developing consensus underperformance trend accelerate by 1270bps for 2016.

We analyzed Thomson Reuters’ I/B/E/S dataset and looked at instances where analysts were unanimously bullish or bearish on a stock.  It turns out that analysts recommendations correlated strongly with share price performance.  However, there was one tiny caveat: the buys dramatically underperformed the sells in 2016.  The unanimous buys were up 4.5% while the unanimous sells were up 20.7% so a market neutral consensus portfolio lost ~16.2% last year.  It turns out that 2016 was a year where betting against the analyst herd paid off!

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The chart above shows the distribution in share price performance between both cohorts. (The bullish group had outliers up +1618% and +1189% that are not shown.) While the winners in both groups performed roughly the same, the losers in the bullish group fell more than the bearish group.

One major factor behind the underperformance was the bullishness surrounding small-cap development-stage pharma stocks.  For healthcare stocks (which were mostly small-cap pharma names in our cohorts), the number of consensus buys outnumbered the sells by a factor of 13.7X versus a baseline rate of 2.24X.

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Technical Thoughts: Sentieo’s Alexa Skill and the Three Fundamental Laws of Voice User Experience $AMZN $GOOGL $AAPL

Sentieo’s Alexa Skill is live! We present some thoughts from our technical team recapping our experiences for the benefit of those who are keen on considering the future of computer interfaces.

For Voice User Interfaces (VUIs) to have any chance of success, the future direction of Voice User Experience (VUX) will be strongly tied to physical, not software, constraints.

The three features of these will be:

1) At least 100 words per minute (wpm) input

2) close to 200wpm output

3) under 250ms response time.

We are nowhere close.

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Oil & Gas Research the Smart Way with Sentieo $NFX $FANG $CLR $APC

The O&G industry reports tons of data in both volume and detail—from drilling rig and pressure pumping data to well production info. Looking for and analyzing all of this information for your investment ideas is a very necessary but time consuming process. Designed by buysiders for buysiders, Sentieo is the best tool on the market for leveraging technology to rapidly compress your research cycle and give you more time to generate true alpha insights.

In this post, I’m going to show you a glimpse into the world of oil & gas research using Sentieo—so that you can spend more time analyzing your the findings and try to come up with answers to questions such as:

Which E&P companies might be at risk of defaulting on their loan obligations?

Has an E&P operator you are following announced those new well results yet?

What would this company specific data would look if I plotted it against other metrics?

What are some ways I can use Sentieo to research industry trends?

What are companies are saying about break-even oil prices and well-economics?

How many drilled but uncompleted wells are in a company’s backlog?

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$PLATED – Using Mosaic to ballpark unlisted company financials

This is a companion post to walk through our methodology for our post on WFM.

For full transparency, we wanted to go through in detail our math on the subscription meal-kit industry, where all players are unlisted. This is where Mosaic starts to come in handy to estimate real numbers.

Guesstimating Blue Apron as the anchor

The latest delivery number for Blue Apron is 8 million meals/month (more than double the June 2015 rate of 3 million meals/month) That Fortune article equates it to a $960m run rate on an ASP of $10, but we are skeptical as customers never pay the full list price with the myriad referral bonuses and other promotions common in the business. We reckon the real number is closer to $9, which puts Blue Apron on a still-impressive $720m revenue run rate.

Hellofresh as the other end of the vector

Hellofresh’s 2015 pre-IPO numbers were $290m globally, of which 60% is US revenues. That’s $150m for calendar 2015, over which the company quadrupled, so they exited with closer to $375m run rate in US revenues.

Using Mosaic and two known points to triangulate

We don’t know much about Plated and the other smaller players in the subscription kit space, but fortunately, they all run similar business models in the most transparent traffic market in the world. We used Mosaic to pull together three independent reads on Plated’s traffic and got extremely close results:

Using the market share data and known revenue numbers, we can put an estimate on Plated of about $135m in annual run rate:

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This sounds in the ballpark considering it was pinned at $100m from this Inc article in June 2015. The closeness of fit of a linear curve shows that the revenues are strongly tied to traffic acquisition, but also that there is no clear barrier to entry or topline benefit to scale:

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Getting a Handle on Industry Growth

So we now know that the industry is doing roughly $1.4bn/yr today but that number is meaningless in isolation because the rate of growth presents a constantly moving target, something traditional investors in retail and staples aren’t used to. We need get a handle on growth as well. Wouldn’t it be nice to have a platform where you could easily pull up that data from multiple sources?

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Plated’s March peak in traffic is a one-off bump thanks to their deal with Mark Cuban on Shark Tank, but we reckon that the industry has roughly doubled year-on-year, which means that there was at least $700m in incremental revenues over 2015, backend weighted. What is a reasonable estimate for forward projections?

Forecasting the future is more art than science. If the industry saw 100% growth in 2015, is it fair to say it will grow 100% again in 2016? On the one hand, you are starting off a higher base and are going from early adopters to followers. On the other hand, you have better funding and cash flow and scale in everything from customer base to marketing campaigns to logistics. It is hard to take the over/under. We think a fair conservative estimate is $800m in incremental revenues, which is a slight acceleration year on year in dollar terms but actually a sizable deceleration percentage-wise, to +60% forward growth. We think the risk to this number is higher rather than lower as more funding and entrants like Amazon come into the space.

Calculating the Comp Sensitivity for WFM

1% of WFM’s 2015 revenues of $15bn is $150m, and given that WFM is not closing stores in any meaningful scale, this is a directly applicable number to calculate impact on comparable store sales. Every $150m taken away from WFM is 1% less in comps.

However, WFM does not solely bear the brunt of the disruption. A number of WFM’s peers, from Kroger to Sprouts Farmers Market, have all called out or commented on the potential impact on subscription meal-kit services. While WFM is a major player, it would be unfair to attribute the full amount of the disruption to them. Since WFM is approximately 25% of grocery industry revenues, we think somewhere in that ballpark would be appropriate, though pricing and demographic characteristics make WFM more susceptible to disruption than the general industry.

Taking all of the above into consideration, we are able to stress test a simple model of WFM comp sensitivity to the subscription meal-kit services, which is how we finally arrive at our Comp Sensitivity table used in the main WFM blog post.

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