Suppose the question is to find the average of SALES PER VISIT (sales measured across the preceding 6 months) among the males and females in a sample of 25 shoppers.  The data look like this in Excel:

TIP:  We can easily input these data to Tableau by cutting and pasting the selection into the Tableau canvas:

Now to answer the question.

First time users of Tableau may correctly put GENDER on the row shelf and SALES PER VISIT on the column shelf.  Tableau defaults to a bar chart yielding:

First time users may also put SALES PER VISIT on the Label Marks card, which displays the value next to each bar in the chart.  They may even put GENDER on the Color Marks card to give the viz some pop.

And then they call it done.  Males spend more on average than females.

But do they?

We note that the green pills show SUM(Sales per Visit).  Tableau’s default “aggregation” is to sum the values across the rows in the data set.

Going back to Excel, if we sum SALES PER VISIT by GENDER across the 25 rows, we get, using the SUMIF function:

This is exactly what Tableau shows.

But we want to find the average.  In Excel, using the AVERAGEIF function, we see that females spend on average $11.62 while males spend $9.13 per visit.

To get Tableau to match, we simply change the aggregation by right-clicking on each of the green pills and select Measure (Average) from the drop-down menu.

Now we get the correct answer to our question.

If Tableau is not yielding the correct answer, try thinking about how you would do it in Excel.  Sometimes, but not always, this will provide the proper guidance.

The post Tableau Basics: SUM vs AVG appeared first on KDD Analytics.

This dashboard tracks the San Diego COVID experience: new cases, tests, and positivity rates at the county-level as well as new cases for each of the county’s ZIP Codes.

On this first-year anniversary of these daily postings, we thought we would look back at this roller coaster year.

And, although our dashboard does not include US data, we thought that comparing the San Diego COVID experience with the national average would be insightful.

San Diego COVID experience vs the nation

The following figure shows the 7-day moving average of daily new cases per 100,000, for both San Diego County and the entire US.[1]

As shown in the above figure, as a nation we have been through 3 waves with it being too soon to tell if the 4^th wave has crested. San Diego County’s experience was generally similar except for the 4^th wave.

Wave #1

The initial rise in daily new cases crested at a 7-day average of 10 per 100,000 for the US on April 12, 2020. San Diego’s first wave crested about a week earlier on April 4^th at about 4 per 100,000.

The US new case 7-day average fell to 6 per 100,000 by mid-June. San Diego’s briefly fell a bit but then rose back up to a daily rate of 3 to 4 per 100,000 till mid-June.

So, San Diego did not really experience the same recovery from the first wave as the US.

Wave #2

For both the US and San Diego, the second, much larger wave began in mid-June 2020. The US new case rate increased from a 7-day average of about 6 per 100,000 to a peak of 21 per 100,000 on July 23^rd. San Diego’s rate increased from about 4 per 100,000 to a peak of 16 per 100,000 on July 2^nd.

Both the US and San Diego new case rates declined through the end of the summer. The US new case rate bottomed at a 7-day average of 13 per 100,000 on September 13^th. San Diego’s bottomed at the end of August at about 8 per 100,000 and stayed essentially flat till mid-October.

Wave #3

The US third wave began in mid-September – a full month before San Diego was hit. Rising from a 7-day average low of about 11 per 100,000, the US new case rate increased throughout the fall and early winter, peaking at 76 cases per 100,000 on January 11, 2021.

San Diego’s third wave began in mid-October. From a 7-day average low of about 8 new cases per 100,000 on October 20, the new case rate peaked at a high of 109 per 100,000 on the same day that this third wave peaked for the country.

As the figure shows, San Diego (as well as Los Angeles) suffered much higher new case rates than the national average.

But daily new cases started to decline just as steeply as they increased. San Diego’s 7-day average new case rate fell from this high of 109 to around 7 per 100,000 by April 20, 2021.

The US new case rate fell as well, from a 7-day average of 76 to about 16 by March 19, 2021.

Wave #4

Until this point, San Diego’s experience, though different in severity, matched the general pattern of the country. However, a 4^th US wave began in mid-March 2021, driven by new outbreaks in Michigan and New Jersey. It is too soon to tell if this 4^th wave has crested but the most recent peak is a 7-day average of 21 new cases per 100,000 on April 13^th.

San Diego has been fortunate to escape this 4^th wave (so far).

Fingers crossed…

[1] San Diego new case data are from the San Diego County Health Department. US new case data are from the CDC.  The 7-day moving average is the average of the current and preceding 6 days. 2019 population is used to normalize case counts so we can compare San Diego with the nation.

The post San Diego and COVID-19 … A Very Challenging Year appeared first on KDD Analytics.

According to Intensity’s latest US recession start date forecast, there is a 50% probability of a recession starting sometime in the January to February 2019 period.  And a 97% probability of it starting sometime within the next 6 months.

Their “point estimate” of a recession start is January 2019.

Like, as in, right now!

If true, it will take awhile for the impacts to start showing up in the official government statistics.  But the stock market sell-off last quarter may be a harbinger of things to come.

Intensity, an economics and data science firm based in San Diego, CA, developed and back-tested a machine learning prediction algorithm for its clients.  The firm started releasing a monthly forecast of the next US recession start date to the public starting in March 2018.

Over the course of the last 11 months, it has been interesting following the updates to their forecast as economic conditions changed.

Intuitively, one would expect that the forecast would “settle down”, the closer the expected start date became.

And it got me thinking about what the best way is to visualize these changing forecasts.

Visualizing Forecast Updates Over Time

The forecasted recession start date is not linear with time.  For example, in March 2018, the next recession was forecasted by Intensity to start in April 2019.  But in April 2018, the forecast was revised, and the recession was to start 6 months earlier in October 2018.

Plotting the month of the forecast on the x-axis and the forecasted month of the recession start on the y-axis yields a “traditional time series” view as shown below.

As time progresses from left to right, we can see the forecasted recession start date fluctuating up and down, settling on January 2019, the most recent forecasted start date.

However, another way to visualize this is to show the progression of time vertically, from bottom to top.  In this case the forecasted recession start date would fluctuate horizontally, left and right, as shown below.

I don’t know about you, but I find this second view more appealing.  Maybe it is the old economist in me, trained on the Phillips Curve in graduate school.  But for me, the vertical, “up-down” orientation makes the variation in the forecasted recession start date “pop” more than in the horizontal, “left-to-right” view.

So, Recession in 2019?

It will be very interesting to see if Intensity sticks to its January 2019 point estimate.  Prior to the unexpectedly positive December 2018 jobs report, the consensus seemed to be a recession starting some time in 2019 or 2020.  For example, Gary Shilling recently tossed his hat into the recession ring with a predicted 66% chance of a recession in 2019.

However, the positive jobs report apparently has many economists now softening their stance on a recession this year.  And there is talk of policy makers being able to sidestep a recession.

Only time will tell…so stay tuned!

Plotting Ordered Times Series in Tableau

By the way, these charts were made in Tableau.  And it was not as straight forward as flipping the axes to get the vertical view.  Tableau’s default inclination is to “connect the dots” from left to right when time is involved.

Fortunately, there is an easy way to get Tableau to connect the dots vertically.  This makes use of the Path property in the Marks card.  I simply added a field to my raw data that indicated the order of my data, which, of course was calendar order.

Then dropping this field on the Path property in the Marks card tells Tableau to connect the dots (or “Marks” in Tableau-speak) in this order.  With the date of the forecast on the vertical, y-axis, Tableau connects the dots from bottom to top.

Very slick!

The post How to Visualize Changing Recession Start Date Forecasts appeared first on KDD Analytics.

Turns out that in the LATAM region, Tableau is not the preferred data visualization platform. In fact, it is not even in the top five. As shown in the chart below, among the business sites in the TUDLA database for which an indicator of business intelligence software exists, Tableau ranks 7^th. The number 1 vendor is Qlik Technologies.

This preference does appear to vary by country, but not in Tableau’s favor. In Peru, Qlik is 7x more likely to be present as compared to Tableau – the largest relative penetration in the TUDLA database. Tableau is never more likely to be present relative to Qlik. The smallest Qlik differential, among countries with sufficient data, is 2.4x in Colombia.

The TUDLA data are corroborated by an analysis of web searches conducted by Kalinax. Their infographic (shown below) indicates that in terms of impressions, Qlik is more popular than Tableau in the LATAM region. The exception is in Colombia where there are more searches for Tableau than for Qlik. Kalinax posted several analyses of Tableau and Qlik which can be found here, here and here.

You never know what you are going to find when you start to dig. You can do your own exploration of the TUDLA database free of charge here.

At the core of the TUDLA database is a 70,000+ phone verified panel. Data from this panel include firmagraphics, contact information and full technology profiles. Surrounding this core are an additional 1 million+ business locations. Associated with these expanded data are basic firmagraphics (company name, address, URL) and expanded firmagraphics, where available (employee counts, industry and revenue). Indicators of what technology may be used at these business sites are also available.

The post Tableau vs. Qlik in Latin America appeared first on KDD Analytics.

A 23% compounded average annual rate of return.  Not too bad.

During his career Shelby advised Thomas Dewey on economic matters when he ran for president in 1940 and 1944 and served as Governor Dewey’s First Deputy Superintendent of Insurance from 1944 to 1947 in New York. Later, he served as US ambassador to Switzerland under Presidents Nixon and Ford (1969 – 1975).

A philanthropist, he was head of the Shelby Cullom Davis foundation which disperses funds to higher education and to research on public policy and economics. Princeton, his alma mater, was one of the beneficiaries of his grants. He also served as chairman of the Heritage Foundation.

Shelby got around.

But what the heck does this have to do with Fintech?

In a previous post we found that the Tucson, AZ metro area made our top 15 list of top addressable Fintech Securities & Investments markets on a per employee basis in 2015 (ranked 14^th).

Can a contributing reason for this can be tied directly back to Shelby Cullom Davis?

Securities & investments sector in Tucson, AZ

Tucson, AZ probably does not first come to mind when thinking about hot spots of financial activity. So, what is going on in Tucson?

As we have done in previous posts, let’s start with a high-level view of Tucson’s Securities & Investments sector. As shown below, 62% of the 2015 addressable Fintech market is due to portfolio management. Another 27% is due to securities brokerage. This is generally consistent with the West regional average of 28% for securities brokerage we saw in an earlier post. But it reflects a much higher concentration of potential Fintech spend in the portfolio management sub-sector (62 vs 48%).

Again, our analysis uses ZIP Pointe Market Sizer.  Market Sizer is our Tableau-based market sizing tool based on ZIP Code-level Census data on over 7 million private sector business locations.

In terms of business location size by sub-sector, nearly 80% of the locations are small (1 – 4 payroll employees). This is a recurring theme. The sub-sector is dominated by small locations though these are not necessarily all stand-alone companies (i.e. they could be formal branch locations).

There are only 29 locations with 10 or more payroll employees. A bit over 40% of the locations are involved with securities brokerage, another 26% are portfolio management and another 18% are investment advice (see below).

With respect to “hot spots” of potential Fintech spend per employee, it is clearly the portfolio management sub-sector that stands out, with potential spend ranging from $5,337 to $7,682 per payroll employee. The top hot spot consists of 3 locations with 50 to 99 employees.

Note: The US Census source used by Market Sizer tracks only payroll employees. Independent contractors are not reflected in these numbers. Hence, the actual employment level can be higher, possibly much higher, in sectors that make extensive use of contract labor.

ZIP Code level view

As we have done in prior posts, another way to drill into the addressable Fintech market in Tucson is by ZIP code. The following map shows the ZIP codes in the metro area color coded for addressable market size per employee. At the ZIP Code level, addressable Fintech market size ranges from $1k to $6k per payroll employee.

But there is a distinct hot spot in ZIP Code 85706 (circled in red) at $6k per employee. According to Wealthminder.com, the largest Tucson financial advisory firm (in terms of assets under management) is located in this ZIP Code:  Davis Selected Advisors.

Other top firms in the Tucson metro area (indicated by red arrows) are Tci Wealth Advisors in ZIP Code 85718; Sonora Investment Management in Zip Code 85719; Strategic Equity Management in Zip Code 85715; and Sterling Investment Management in Zip Code 85718.

Which ZIP codes account for the bulk of potential Fintech spend?

We have already discussed two of the top 3: 85706 at 16% and 85718 at 20%. But these are surpassed by ZIP Code 85712 (indicated by the green arrow) which accounts for 27%. These three ZIP Codes together account for 63% of Tucson’s potential Fintech spend in the Securities & Investments sub-sector.

Another way to drill into the addressable Fintech market is on a per business location basis.  Dividing potential spend by the number of locations is another way to normalize the data. This map (shown below) looks quite a bit different and one ZIP Code stands out above all the rest: 85706. Although the ZIP code overall accounts for 16% of total potential Fintech spend, on a per location basis, it ranks at the top with $230k in potential spend per site.

ZIP Code 85706

Turns out at there are only 3 locations in ZIP Code 85706.  At least one of these (the larger one) is associated with, yep, Davis Selected Advisors. And it may be that the other sites are also associated with Davis as we could not find any other Securities & Investments firms (with at least 10 employees) in this ZIP Code (If anyone knows, please let us know!)

Davis Selected Advisors

So, the Davis name is a major player in the Tucson metro Securities & Investments sector. Any relation to Shelby Cullom Davis perhaps?

Davis Selected Advisers was started in 1969 in New York by Shelby Davis…not Shelby Cullom Davis but his son Shelby Moore Cullom Davis. Following his father’s footsteps, Shelby M.C. Davis graduated from Princeton and rose through the ranks of the New York financial industry – specifically at the Bank of New York.

In the late 1970s the non-portfolio operations of Davis Selected were moved to Sante Fe, N.M. In 1997, a service center was opened in Tucson and personnel were hired locally and moved from Santa Fe. By 2000, Tucson had became Davis Selected’s global headquarters, specifically in ZIP Code 85706 where the company operates out of its own commercial property.

Today, Davis Selected Advisers is led by Shelby’s son, Chris Shelby, grandson of Shelby Cullom Davis.  “Davis Selected controls the nine-fund Davis group, the Selected group of funds, which is a no-load, four-fund group, private accounts of no less than $5 million, and other managed money programs.” (Inside Tucson Business).  Currently, Davis Selected has about $30b in assets under management.

So, there you have it…from Switzerland to the Sonoran Desert! 

Ok, maybe New York to Arizona…

The post Top 15 Metros – From Switzerland to the Sonoran Desert – Fintech Securities & Investments appeared first on KDD Analytics.

And so will tax incentives.

The Raleigh-Durham-Chapel Hill combined statistical area (CSA), with over 2 million people, is the second largest metro area in North Carolina following Charlotte to the south. It is home to 3 major universities: Duke, University of North Carolina (UNC) and North Carolina State. Duke and UNC form two of the vertices of the “Research Triangle,” an area known for a high concentration of corporate operations and research companies and startups, especially in life sciences. The third vertex is formed by North Carolina State University in Raleigh.

The Raleigh metro area was number two on the 2015 Forbes list of the best place for businesses and careers. Durham ranked number 20 while Charlotte was 14th. Companies located in the Raleigh-Durham area include heavy hitters like IBM, GlaxoSmithKline, Cisco, SAS Institute and Lenovo.

As one of the largest research parks in the world, Research Triangle Park (RTP), sits mostly within the Durham-Chapel Hill metro area. RTP employs nearly 50,000 “high-tech” workers and is home to over 250 companies including Credit Suisse, Dell, EMC and Fidelity Investments. None of these are tobacco companies.

North Carolina has been very aggressive in wooing companies to locate in the state.  Lucrative incentives have been offered including outright grants, rebates of employee withholding taxes and sales tax refunds. Raleigh-Durham-Chapel Hill has directly benefited from these incentive programs as has the Charlotte-Concord-Gastonia metro area.

So, what does this have to do with Fintech?

Two million people and a healthy economy means there’s a lot of money that needs good advice. And a healthy program incentivizing companies to locate in the state doesn’t hurt. This combination has pushed the Durham-Chapel Hill Metro to #6 in our ranking of the Top 15 List of Fintech Securities & Investments Markets on a per employee basis in 2015.

Securities & Investments sector in Durham-Chapel Hill

What does the Securities & Investments sector look like in Durham-Chapel Hill, NC? To start, as shown below, over 50% of the 2015 addressable Fintech market is due to securities brokerage. Another 27% is due to portfolio management. This is generally consistent with the South Atlantic regional average of 45% and 28% that we saw in an earlier post.

Again, our analysis uses ZIP Pointe Market Sizer. Market Sizer is our Tableau-based market sizing tool based on ZIP Code-level Census data on over 7 million private sector business locations.

In terms of business location size by sub-sector, over 70% of the locations are small (1 to 4 payroll employees). There are only 7 locations with 100 or more employees. A bit over 40% of these locations are involved with securities brokerage, another 28% are portfolio management and 19% are investment advice (see below). With respect to “hot spots” of potential Fintech spend per employee, several business locations classified as Miscellaneous Intermediation (e.g. venture capital) have the highest Fintech spend per employee of around $12,000. In the chart below we have circled the largest locations.

Another way to drill into this market is by ZIP code. The following map shows the ZIP codes in the metro area color coded for addressable market size per employee. At the ZIP Code level, addressable Fintech market size ranges from $1k to $6k per employee.

According to Wealthminder.com, the largest financial advisory firms (in terms of assets under management) are located in ZIP Codes 22701 (Amundi Smith Breeden and Verity Asset Management), 27713 (Piedmont Investment Advisors), 27703 (Gordon Asset Management) and 27707 (NCM Capital Management Group).

 

ZIP Code 27709

So, on a per business location basis as well as a total basis, there is a very heavy concentration of potential Fintech spend in ZIP Code 27709. Focusing on the distribution of sites in this ZIP Code we see that the largest locations in the metro area are also in this ZIP Code (see the chart above with the red circle). Since this ZIP Code partially covers Research Triangle Park (RTP), these large locations are likely Credit Suisse and Fidelity Investments (see the RTP company directory).

Note: The US Census source used by Market Sizer tracks only payroll employees. Independent contractors are not reflected in these numbers. Hence, the actual employment level can be higher, possibly much higher, in sectors that make extensive use of contract labor.

Fidelity Investments and JIDGs

Fidelity is one of the larger employers in the Durham-Chapel Hill metro area. Fidelity first began to operate in North Carolina in 2002 “when it acquired an employee benefits business. Four years later, the firm designated North Carolina as a regional technology center, added a data center and a customer contact center and based Fidelity Charitable in the Triangle.” wral.com 

Fidelity further expanded its presence starting in 2006 and in 2015 announced plans to add an additional 600 jobs. Projections are for 4,200 jobs by 2018, mostly at the Research Triangle Park campus.

Fidelity, as well as other business, was likely incentivized to locate and expand in North Carolina by Job Investment Development Grants or JIDGs. These state grants are a

“performance-based, discretionary incentive program that provides cash grants directly to new and expanding companies to help offset the cost of locating or expanding a facility in the state. The amount of the grant is based on a percentage of the personal income tax withholdings associated with the new jobs.” Economic Development Partnership of North Carolina.

Companies can use JIDG funds for any purpose.

As these grants are performance-based, companies receive the full incentive only after meeting certain benchmarks.  These requirements can be in the form of a certain number of jobs created and retained, generation of a targeted $ amount of gross state product and/or the generation of a certain positive net revenue amount over the life of the grant.

Recently, North Carolina has “sweetened the pot” of these incentives, with an eye towards “transformative projects”, those that invest at least $4 billion and create 5,000+ jobs (ahem…listening Amazon?).

All states have some type of incentive program to entice businesses to locate and expand in their states. North Carolina appears to be one of the more aggressive ones. And this definitely was a contributing factor to why the Durham-Chapel Hill, NC metro area is #6 on our list.  #2 Omaha powered its way there more organically it seems.

All regions are different.  And Fintech companies looking to successfully disrupt these segments will need to be able to take these differences into account.

The post Top 15 Metros – Fidelity Durham – Fintech Securities & Investments appeared first on KDD Analytics.

But for those of us old enough to remember, we knew it thanks to Mutual of Omaha’s Wild Kingdom. The show aired on NBC TV just before Walt Disney’s Wonderful World of Color on Sunday nights. Hosted and narrated by zoologist Marlin Perkins, Wild Kingdom featured Jim Fowler showcasing wild animals.

Or maybe you know it for the corn? Nebraska and Iowa have always been synonymous with corn.

But now, Omaha will also be famous for making the Boulder Equity Analytics’ Top 15 List of the Largest Securities & Investments Fintech Markets, ranked by per employee revenue. In fact, as we discussed in an earlier post, it ranked #2 right after the New York metro area.

So, is Omaha’s ranking due to Berkshire Hathaway? Mutual of Omaha? Or maybe it’s companies like TD Ameritrade, Wealthplan, CWM or Securities America? Let’s dig into the data.

Securities & Investments sector in Omaha

What does the Securities & Investments sector look like in the Omaha-Council Bluffs metro area? To start, as shown below, 70% of the 2015 addressable Fintech market is securities brokerage. Another 13% is portfolio management. This is much more skewed towards securities brokerage than the Midwest region overall (36%). So, Omaha is a relative hotbed of securities brokerage business.

Again, our analysis uses ZIP Pointe Market Sizer. Market Sizer is our Tableau-based market sizing tool based on ZIP Code-level Census data on over 7 million private sector business locations.

In terms of business location size by sub-sector, nearly 76% of the locations are small (1 – 4 payroll employees). There are only 10 locations with 100 or more payroll employees. A bit under 40% of the locations are involved with securities brokerage, another 22% are in portfolio management and 24% are in investment advice (see below).

With respect to “hot spots” of potential Fintech spend per employee, business sites with over 20 employees in securities brokerage are at the top. Thirty (30) sites have a potential Fintech spend of at least $6,000 per employee.

 

Another way to drill into the addressable Fintech market in Omaha is by ZIP Code. The following map shows the ZIP Codes in the metro area color coded for addressable market size per employee. At the ZIP Code level, addressable Fintech market size ranges from $1k to $8k per employee.

At the upper end, ZIP Code 68101 shows a per employee value of $8k. There is only 1 site in this ZIP Code and it only has 1-4 employees, in securities brokerage. This is probably a branch office associated with a much larger company. The other 2 top ZIP Codes are 68128 and 68154 with over $6k in potential Fintech spend per employee. We will focus in on them in a bit.

 

However, if we measure addressable market size on a per business location basis (another way to normalize the data), the map looks very different but yields similar conclusions. A shown below, the top ZIP Code in terms of potential Fintech spend per site is 68128 with over $700k.  In second place is ZIP Code 68154 with a total of $126k per site. 

 

But these two ZIP codes are quite different.  ZIP Code 68128 has only 3 sites while ZIP Code 68154 has 81. And in terms of total potential Fintech spend, the ranking is reversed. ZIP Code 68154 accounts for 54% of the addressable Fintech market in Omaha while ZIP Code 68128 accounts for 12%. In third place is ZIP Code 68130 with another 9% in total potential Fintech spend.

A tale of two ZIPS

ZIP Code 68128 has the largest potential Fintech spend per business site at over $700k. But this is due to one large location as shown below (values in the chart are potential Fintech spend per employee). 

Turns out this one large site is the headquarters of Securities America.

We caution that our estimates of potential Fintech spend at a company level are directional. Our Fintech estimates are derived from market aggregates and not from specific company revenue accounts. 

Securities America, founded in 1984, helps financial advisers create more profitable practices. Through a series of acquisitions, the most recent by Ladenburg Thalmann Financial Services, it also offers more traditional services such as equity research, brokerage services and investment banking. On their website, the company says they currently have 575 employees.

We should note that the Census data only track payroll employees. Contractors are not included in these totals. So, the total employee count at any given location could be higher than what is shown here, especially sub-sectors that rely heavily on contracted labor.

ZIP Code 68154 has a much more varied representation of business sites, both in terms of size and in terms of sub-sector, as well as a larger number of sites (81). Securities brokerage accounts for 38% of the business sites with all the large sites (100+ employees) being in this sector. Portfolio management accounts for another 27% of sites and investment advice another 24%.

Wealthplan Partners, who provides financial planning and asset management services, is based in ZIP Code 68154 as is Carson Wealth CWM LLC, another asset management company. Although the representation is more varied, there does appears to be a dominant company in this Zip Code: TD Ameritrade.

TD Ameritrade consolidated employees from around the Omaha metro area into this ZIP Code in 2013. About 2/3 were relocated to the company’s new headquarters building and the remainder in other buildings nearby. At the time, the company says that 2,000 employees were relocated to the ZIP Code.

Amerivest Investment Management, owned by TD Ameritrade and the largest financial advisory firm in Omaha according to Wealthminder.com, is co-located with TD Ameritrade in its ZIP Code 68154 headquarters building.

So what about Berkshire Hathaway and Mutual of Omaha?

Berkshire Hathaway’s headquarters is in ZIP Code 68131 and is not classified as being in the Securities & Investments sector; it is a holding company. Mutual of Omaha is classified as an insurance carrier so is also outside the Securities & Investments sector.

So, the Fintech Securities & Investments market in Omaha is powered by companies in the securities brokerage sub-sector, like TD Ameritrade and Securities America.

But in case you are wondering whatever became of Mutual of Omaha’s Wild Kingdom…it is back on the web with Stephanie Arne hosting.

The post Top 15 Metros – Wild in Omaha – Fintech Securities & Investments appeared first on KDD Analytics.

Previously, we estimated the potential Fintech spend in the Securities & Investments sector to be a little over 16% of the total Fintech market of $18.8b. As of 2015, this was $3.1b.

In our continuing series on the addressable Fintech market we dive deeper into the Securities & Investments sector. Again, our analysis uses ZIP Pointe Market Sizer.  Market Sizer is our Tableau-based market sizing tool. It is based on ZIP Code-level Census data on over 7 million private sector business locations.

Portfolio Management tops the sector

Within the Securities & Investments sector, portfolio management accounts for the largest share of the addressable Fintech market at 38%. Securities brokerage (27%) and investment banking (16%) round out the top 3.

This breakout, though, varies across regions. As shown below, portfolio management companies account for the largest regional share of the market in the Northeast (42%) and the West (48%). In all other regions, securities brokerage accounts for the largest share. Across all regions, portfolio management and securities management together account for 64% to 78% of total potential Fintech spend, respectively.

As shown below, in terms of business location size by sub-sector, 77% of the locations are small (1 – 4 payroll employees). And nearly 94% have fewer than 20 payroll employees. The Census data also indicate that there are nearly 1,200 sites with 100+ employees, representing a bit over 1% of all business sites in the Securities & Investments sector.

We should note that the Census data only track payroll employees. Contractors are not included in these totals. So, the total employee count at any given location could be higher than what is shown here, especially sub-sectors that rely heavily on contracted labor.

In terms of potential Fintech spend per employee, the chart above shows a range of $598 (commodity contracts, 500 to 999 employees) to $7,041 (securities exchanges, 50 to 99 employees). The “hot spots” of potential Fintech spend are in the investment banking sub-sector among sites with 100+ employees, and the securities exchanges sub-sector among sites with 10+ employees (though there are only 36 sites in this sub-sector).

No Surprise, NYC Metro tops area ranking

In terms of total potential Fintech spend, the usual suspects are again at the top of the addressable market list in the Securities & Investments sector. The New York metro area leads the list at $1,090m. Boston $191m, Chicago $183m, Los Angeles $172m, and San Francisco $171m round out the top 5.

But in terms of per employee, San Francisco jumps from #5 to top the list.

In 2015, the top 15 metro areas in terms of addressable Fintech market per employee in the Securities & Investments sector are shown below:

We limited our analysis to metro areas with 150 or more business locations in the Securities & Investments sector. This helps reduce the “noise” in our analysis and minimizes (but does not eliminate) the likelihood that a metro’s normalized estimate is unduly swayed by a few extreme business locations.

Omaha is #2?  There’s a surprise

The San Francisco metro area heads our list of the largest addressable Fintech markets on a per employee basis in the Securities & Investments sector at $5,313. Rounding out the top 5 are Omaha-Council Bluffs, NE-IA ($5,298), Bridgeport-Stamford-Norwalk, CT ($5,122), New York ($5,107) and Worcester, MA ($4,685). Other notables in the top 15 are Durham-Chapel Hill, NC ($4,94), Charlotte-Concord-Gastonia, NC ($3,381), Austin, TX ($3,256) and Tucson, AZ ($3,130).

If you already knew Warren Buffett’s hometown of Omaha, Nebraska was going to be the #2 market in the US for Securities & Investments, give yourself a pat on the back. We’ll break that down for you in future posts, along with two other surprises on the list, Durham-Chapel Hill and Tucson.

This post was written with Tom Marsh, CTO at Boulder Equity Analytics (BEA).

The post Breaking Down the Fintech Securities & Investments Sector appeared first on KDD Analytics.

In regions where data are less complete, like Latin America, a descriptive approach offers a very cost-effective way to reveal what the size of the prospective market might be. In fact, such an approach may be the only feasible approach depending on fill rates in the database.

Once identified, this population of prospective sites or look-alikes can then be pulled from the database, matched with a contact database or passed to a call center for verification of firmagraphics, contact details and technology usage.

TUDLA’s Latin America database

As we discussed in a previous post, TUDLA maintains a database of over 1 million business sites in Latin America and the Caribbean. The data include basic firmagraphics (company name, address, URL) and expanded firmagraphics where available (employee counts, industry and revenue). Also, indicators of what technology may be used at these business site are available.

TUDLA also offers free access to the data through interactive Tableau dashboards. This allows users to explore the data at an aggregate level and get a sense of TUDLA’s coverage. It also allows users to perform their own descriptive look-alike analysis.

Descriptive look-alike analysis

As a simple example, suppose I am SAP and I want to know how many prospective customers there might be for an SAP branded ERP offering in Brazil. (Alternatively, I could be an SAP ERP competitor and I am looking for possible SAP customer sites for a competitive kill campaign). Consider the following screenshot from TUDLA’s interactive Tableau dashboard.

TUDLA’s database shows (lower left-hand corner) that there are 2,828 sites in Brazil that are known to have SAP ERP. And the charts show the characteristics of these sites (i.e. the employee, revenue and industry distributions).

Also in the left-hand corner is shown that there are 424,693 sites in Brazil that share the same characteristics (employee count, revenue size and industry) as these 2,828 sites known to have SAP ERP (i.e. these are SAP’s look-alikes). So, this is the size of the prospective market for SAP in Brazil.

Further refinement to a specific firmagraphic, say, revenue size, will more narrowly focus the prospective market. For example, suppose SAP is only interested in sites with enterprise revenue greater than $50m. In this case, the prospective market size is reduced to 19,144 sites, nearly 50% of which are in the manufacturing industry (see below).

Interactive visualization

Interactive visualization is an excellent way to get a comprehensive view of exactly what is in your database. Lack of coverage in firmagraphics, geographies and other business attributes, such as technology presence, can quickly become apparent.

Moreover, it can be used, as in the case of TUDLA, to examine your look-alike market. You can quickly and cost-effectively (don’t need to pay to have a predictive model built) see the size of your prospective market based on the characteristics of your current customers.

Are your sales territories aligned as they should be?  With just a few clicks, an interactive visualization can provide the answer.

For more information on providing an interactive visualization for your data, give us a shout.

KDD Analytics is providing analytical services to TUDLA.

The post Finding B2B “Look-Alikes” in Latin America appeared first on KDD Analytics.

Is tone really that important? And if so, can it be measured and scaled?

Why might tone be important?

Analysts and investors are seeking an edge as to where a company is headed next. So, they focus not only on the numbers, but on the words the executives use in their introductory remarks and in the answers to analysts’ questions. Executives can unintentionally or even intentionally “tip their hand” and provide a clue as to the company’s direction.

But aside from making good CNBC commentary, is there a connection between tone and future company performance? Is it possible to detect tone without listening to the call?

Financial textual analysis has matured

Before the advent of natural language programming (NLP), text analytics and enhanced computing power, written transcripts and audio recordings were all analysts had to go on. There is only so much that the human mind can discern. Subtle shifts in tone and word usage can go unnoticed when listening and tone seems lost when reading transcripts of calls you didn’t have time to cover.

But now, new tools have emerged that can help. Going beyond simple sentiment, nuances in tone emerge when analyzed with advanced computational linguistics. A new academic field of inquiry developed, financial textual analysis, out of this ability to decompose earnings transcripts and financial documents into their most granular bits. Academic researchers were (and are) keen to determine if tone can presage future company performance.

Although academic researchers have always been interested in studying financial disclosures, it wasn’t until the early 2000’s that interest in financial textual analysis really took off. The bibliography of a survey of financial textual analysis studies shows the exponential growth in the number of studies starting in the early 2000’s. The authors attribute this growth to the application of “highly evolved” computational linguistics technologies to financial documents and enhanced computing power.

So, does tone matter? Simple answer is YES.

What do these academic studies conclude about tone? Can executives’ tone on earnings calls “tell” analysts something about future company performance?

It is beyond the scope of this post to survey the entire field of financial textual analysis. But we can say the answer is “yes,” tone matters. Here is a taste of what the academic literature has found:

We note that these studies tend to be sophisticated statistical studies that attempt to estimate the relationship between tone and company or market performance after controlling for other factors that may affect such performance (i.e. they tend to be more than simple correlation studies).

A study by Price, Doran, Peterson and Bliss finds that “conference call linguistic tone is a significant predictor of abnormal returns and trading volume.” The researchers further find that the Q&A portion of calls has an incrementally greater effect than the introductory portion, which is typically a duplication of the earnings press release. The study concludes that “conference call tone dominates earnings surprises over the sixty trading days following the call.”

Another study by Price with Blau and DeLisle finds a positive relation between companies’ stock returns and earning call tone. But the researchers go on to argue that tone can be subtle and that more sophisticated investors (e.g. short sellers) process the information differently than the average investor. Empirically they find that “short sellers target firms with simultaneous high earnings surprise and abnormally high management tone.”

Druz, Petzev, Wagner and Zeckhauser looked at changes in earnings call tone from quarter to quarter finding that higher negativity of executives’ tone “strongly predicts lower future earnings and greater uncertainty.” Interestingly, the researchers find that decreased negativity only “weakly predicts the opposite.”

Finally, Chen, Demers, and Lev’s research showed that the overall negative tone of earnings call Q&A increased as the morning progressed, dipped slightly after lunch and then rose again until the market close. They also found that the more negative the tone, the more negative the stock returns over the five trading hours after the call. Those negative stock returns associated with negative calls continued downward for up to 15 trading days.

So, it’s clear that “tone matters” and computational linguistics can detect it. Analysts, investors and the market react to the choice of words used by executives in their earnings calls. Investors need to factor this information into their trading strategies, but with care to consider external factors as well.

Boulder Earnings Call Tracker

KDD Analytics is partnering with Boulder Equity Analytics in the development of the Boulder Earnings Call Tracker. This Tableau-based set of dashboards examines earnings call tone among other attributes of earnings calls. It provides our clients with highly relevant signals for sophisticated trading strategies, especially short sellers. On the flip side it provides CEOs and investor relations with unbiased metrics to improve their conference call performance.

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