Tuesday, May 19

Intelligent Speculation, Datawatch (DWCH)

Company Description: Background
Datawatch develops and markets self service data analytic software solutions. Non technical users can leverage expertise by accessing difficult to reach multi structured and structured data for discovery and innovation with no outside support. The data analytic software modules are now sold separate or as a coherent complementary platform for the desktop or enterprise. Datawatch’s tag line, leverage any data at any speed. Any data includes multi structured sources such as PDF, HTML, XML, JSON, log files and structured sources. Structured sources included CSV, Excel, Access, SQL, and others. Countless sources of real time streaming data used in capital markets, energy, floor shop operations and internet of things (Iot) (sensor/machine data).

The Managed Analytics Platform (introduced April 2015) is an enhanced derivative of legacy software Monarch. Both products address a new important requirement of big data analysis. This overlooked prerequisite of big data or data discovery called data prep is now the new must have for enhanced data analysis. Datawatch Monarch is the original data prep software. Datawatch has been selling, developing and improving Monarch software for 20 years. Just over the last 6 months to 9 months Gartner recognized that over 80% of the time spent with big data, data analysis was in data preparation.Datawatch’s Monarch software ignored for years by information research and advisory services such as Gartner. That’s changed. It was long overdue. Gartner’s officially recognizes data prep critical functionality. This will drive more business to Datawatch. At the end of Fiscal year 2014, Gartner published a report “Data Preparation Is Not an Afterthought”.


Major data analytic vendors such as Informatica, Alteryx, and smaller venture capital backed start up firms recently introduced data prep solution to feed visualization or analytic software such as Tableau. This new category was introduced over the past 6 to 9 months. Datawatch has a head start with access to multi structured documents that’s not being offered by the other data prep vendors. IBM uses Datawatch’s data prep Monarch technology to access semi structured content from their award winning content management solution (CMOD).

Monarch and now MAP (Managed Analytics Platform), acquires, enriches, prepares, cleanses, reformats, joins, and automates data from structured, multi-structured and real-time streaming data sources. Designer (Panopticon) is the next step in the data discovery process. It’s used to further visualize, explore, uncover, and solve. Important note, Designer 13 released March 2015 now has powerful data prep functionality. A distinct advantage with all Datawatch software, its self service. The non technical expert becomes productive with no outside involvement.
This self service ability to visual discovery against any data at any speed sets Datawatch apart in the data analytics, big data and visualization markets. Organizations of every size, worldwide use Datawatch products, including 93 of the Fortune 100.
Now What? The recent history of the dramatic rise and fall.
Datawatch has become a turnaround story after a busted 2014 and 2013 growth thesis. The stock had a spectacular meteoric rise. Next, February 2014 to today (05/08/15) stock price dropped as spectacular as the rise. DWCH stock price rose to the mid 30’s or around 250 million in market value. The price was stretched but reasonable. That price could be justified. Price justification based on large relative discount to other major visualization vendors.  Furthermore, their small revenue base to post mid double digit top line growth and the large user base of Monarch users coupled with a new version to feed new designer customers. The price optimism partially started after the acquisition for Swedish visualization software company Panopotion.  It was an all stock transaction calendar 2013 quarter end. Furthermore, Datawatch raised ~ +50M from a secondary, January 2014. The secondary 5 times oversubscribed selling +2 million shares for 28.50.
DWCH board member and outside investor Chris Cox was confident. He purchased 35,000 shares at $28.50 for $997,500 during the secondary. That’s in addition to prior open market buys, 6,163 shares @ 32.14 on 09/12/13, 11,000 shares at 23.11 and 1,565 shares for 22.35.Other insiders just as optimistic during 2013 aggressively purchased stock. Quarter 2 2014 a major upgrade to Modeler (Monarch) V12 released. Historically an upgrade quarter produces material market beating expectation for top and bottom line growth. Introduction of V12 never seriously marketed, a missed opportunity. The marketing focus spent time and money on the overcrowded general visualization market. None of this mattered. Q2 February 2014 Datawatch preannounced unexpected revenue miss. The stock dropped in after hours from the mid 20’s to 13 per share.
Back to the question, why did DWCH bottom at $5.32 during February 2015? The first miss Q2 2014 when Panopticon sales people left unexpectedly. Management commented the miss driven by timing issues. Close to 2 million in additional sales from Q2 expected to close next quarter due to timing misses created by the unexpected disruption from the Panopticon sales team. Then Q3 2014; sales were weak even with the expected additional sales from Q2 2014. Every subsequent quarter had excuses for less than expected 30% YOY results. This continued until Q1 2015 when there was a mea culpa. The mea culpa was to focus marketing efforts on its niche strengths and not cast a wide net within the general visualization market. The marketing focus over the prior 12 to 15 months was general visualization. This approach competed head on with the giants specializing in this over crowed market. Someone never got the memo that Panopticon is more powerful and unique in countless ways (real time, multi time series, in memory, better UI for data discovery) but the marketing focus was general visualization. Designer didn’t stack well on several general visualization strengths to out compete vendors producing prettier graphs such as Tableau, Qlik Tech, and Spotfire. Further and more importantly the heritage product Monarch ignored. During that time, internationally recognized Monarch software’s name was changed to Modeler. Gartner’s 2015 Magic Quadrant report commented on the many unhappy Monarch customers.
 . Gartner inquiries also suggest a level of dissatisfaction in the legacy Monarch installed base as Datawatch transitions it to the new integrated platform.”
Q2 2015 the name Modeler was changed back to Monarch after 1.5 years that negatively impacted the brand and lost momentum within Data Prep.  Monarch large customer base has over 40k historical customers spanning all industries. Those responsible for product positioning at Datawatch never understood or ignored Panopticon and Monarch’s niche advantages and more important DISADVANTAGE to overcrowded commoditized general visualization such as Tableau, Qlik. Last, I speculate the sales staff driven crazy (low morale) over the past 1.50 years with the rebooting of product positioning creating unnecessary sales talent turnover. Sales during this time negatively impacted.
Q1 2015 after another miss the stock broke 6 per share. During the Q1 2015 conference call CEO Morrison communicated the strategy change. There was a renewed focus on the large and loyal Monarch customer base. February Q2 2015 the turnaround became obvious. Sequential revenue up from Q1, expense reductions implemented saves the company 4 million annually. Also, announced a powerful new product derivative of Monarch for the booming big data niche, data prep. The new product called MAP, managed analytic platform. MAP offers improved ease of use data prep, data blending, enhancement, automation, enrichment and speed of thought features for structured, real time and multi structured sources. Access to multi structured reports or machine data is not a feature or strength by other self service data prep vendors.
Datawatch is cheap. A 50% to 80% price increase is not unreasonable.
Relative Valuation:
Current Price = 6.92(05/19/15), EV= 42.41M, MC = 78.55M
EV/Sales = 1.30, EV/GP = EV(42.41M)/GP(27.72M)= 1.52
These financial statistics show a material discount to other visualization vendors. Pentaho, positioned next to Datawatch in the Magic Quadrant (see image below) was purchased by Hitachi February 2015 for 13 to 14 time’s sales. Pentaho offers the same suite of software solutions as Datawatch; ETL, visualization, data prep, and automation. Additionally, not as directly comparative but Tableau (DATA) trades at 17 times sales compared to DWCH’s EV/Sales of 1.30. Tibco went private this year at 3.5 times revenue. Actuate (BIRT) acquired by open text, Jaspersoft by Tibco at price to sales ~ +3 times sales.
Gartner published its prestigious 2015 Magic Quadrant for BI and Analytics Platforms released the end of February 2015. There was only one new entrant, Datawatch. Tiny nano capitalization Datawatch was included with other multibillion dollar vendors such as IBM, Tableau, SAP, Oracle, Microsoft, SAS and others totaling 24. Datawatch ranked in the top 24 of assessed vendors because of its differentiation in supporting emerging requirements for data discovery on streaming and multistructured data. New potential sales opportunities are being generated from the recent Feb 2015 Magic Quadrant report.
Q2 FY15 Datawatch posted market beating top line expectation after a dismal 12 months of misses. Management recognized their faulty product positioning coupled with associated costs was responsible for less than expected top line results. The sales force realigned.  That change resulted in an over 30% increases in productivity for the most recent quarter. Datawatch reduced workforce by 15%.
“The major change was the decoupling of their outside sales reps and inside sales reps which historically have worked in teams. As of April 01, the 21 outside sales reps are now enterprise named account vertically focused while the inside sales organization, of which there are 11 full time FTEs is vertically focused as well, but targeted primarily on the smaller and mid-market opportunities. The good news is that this change in the coverage model has increased sales capacity by approximately 30% without any additional headcount investment and already we see a good deal of positive energy in each of the refocus groups.” Source Q2 conference call.
Designer now has a more focused marketing spend to leverage unmatched strengths. Strengths such as the complex requirements for real time streaming, time series data in addition to multi structured for in memory data visualization. The recent changes and focus will save the company 4M annually.
April 29, 2015 Dell Software announced improvement to its Gartner awarded Statistica advanced analytics platform. Dell will OEM Datawatch’s self service complex visualization Designer with Satistica. Further, Xerox integrated Datawatch’s data prep functionality to access, blend, and filter data from multiple difficult reach sources. "Xerox's Workflow Automation Solution for Supply Chain Optimization tool, for example, targets retailers with a new way to digitize, centralize, automate and govern the manual steps involved in the product life cycle." The solution reduces labor and print costs, simplifies inventory management, and invoice reconciliation, and improves fill rates by syncing data and applying automated analytics at the store level.
An important comparison to support a significantly higher valuation for DWCH is best found in Gartner’s 2015 Magic Quadrant report on Datawatch and Pentaho. Datawatch has a current EV/Sales of 1.30 versus the price paid by Hitachi’s for Pentaho in the range of 13 to 14 times sales. Copied and pasted Gartner 2015 MQ comments from the report,
Garnter wrote on Hitachi’s interest in Pentaho .  Pentaho  had a particular emphasis on solutions for the IoT”. Versus their Datawatch IoT comments “Datawatch has a large installed base in the financial services market and is expanding into other verticals. It is particularly well positioned for the emerging requirements around streaming data for the Internet of Things (IoT).”
Pentaho’s negatives mentioned by Gartner’s magic quadrant were,
14% of reference customers report that the software quality is a limitation that prevents the expansion of use and 68% of customers (the highest percentage in the Magic Quadrant) report some type of problem with the platform. Also, 24% of the reference customers claim that the platform is unreliable and unstable, while another 24% tag it as difficult to implement.  Moreover, customers give Pentaho lower than average scores for customer experience”.
Gartner’s commentary on Datawatch ,
Datawatch scores strong for customer experience and a differentiated product and vision for data discovery on real-time and multistructured data. Customers report using the platform for more complex types of analysis than with most other vendors in this Magic Quadrant. Datawatch registered the highest percentage of customers using its platform for interactive analysis. Customers also have an above average perception of their overall customer experience particularly in the areas of support and product quality.” “Datawatch's self-service data preparation capabilities, which leverage its Monarch Technology, can access structured, semi structured and unstructured data such as JavaScript Object Notation (JSON), PDF and HTML as a data source for analysis, in addition to traditional and many big data sources. Scheduling and alerting capabilities are also more extensive than those available for Tableau”   “Datawatch also has a seasoned management team (of exCognos and TM1 executives), who have thus far positively steered its platform integration and go to market strategy toward differentiation in a growing area of the market.” Source Gartner 2015 Magic Quadrant report.
Split out the software solutions Data Prep/Access and visualization to do a sum of the parts valuation justifies a higher price for DWCH. Monarch and MAP (Managed analytic platform) is Data Prep/Access. Designer is visualization data discovery. Monarch and new data prep software (MAP) can  generate 25 million annually in revenue with around 20% recurring maintenance revenue. Monarch sold to 40,000 companies with over 500,000 copies reaching 93 of the Fortune 100. Designer’s real time data in motion analytics is embedded in Reuters, NASDAQ, KxSystmes, Blacktree, Belarus, and Euromoney. Capital market customers use Designer for complex time series real time data analysis; JPMorgan ChaseCitigroup, Citadel,BlackRock and others. Designer/Panopticon before the acquisition by Datawatch won the prestigious Cool Vendor Award from Gartner. Global alliances realized with Informatica, Perceptive and others. Datawatch paid around 35M in stock for Panopticon. DWCH current enterprise value is 44.15M. Adding a simple 3 to 3.5 multiple to sales or even gross profit for both Monarch and Designer doubles the current stock price.
Summarized investment rationale
Datawatch trades at a depressed price. EV/Revenue at 1.30, EV/GP at 1.52, enterprise value of 42M versus ratios for visualization, data prep and BI vendors trading multiple times higher. New product positioning and sales realignment has lead to a recent Q2 +30% improvement in sales productivity. Sales increased sequentially from the prior quarter. Gartner selected Datawatch for the 2015 magic quadrant, positive optimistic comments.  Datawatch was the only new entrant in the 2015 Magic Quadrant. Datawatch a tiny nano cap stock versus other Magic Quadrant entrants trading in the billions. Prior month there were technology integrations wins with Dell Software and Xerox. The sum of the parts valuation, I believe is 100% greater or more than current enterprise value, 42M. The software can uniquely support Iot (internet of things) with a highly sort after functionality recognized by Gartner’s analysis. Gartner’s multiple positives coupled with industry tailwinds and managements large investment stake are catalysts for the company’s sale at a large premium or market improving valuation. Management has a deep bench that’s experienced in BI industry with a proven successful track record from IBM, Cognos and other large BI vendors. These factors may lead to a 50 to 80% increase in the stock price and will still trade at a large discount to peers. A larger valuation realized if an offer is received at a fraction of the value received by Pentaho, Actuate, Jaspersoft, or Tibco.
Datawatch has proven technology advantages with a talented management team that had difficult year integrating Panopticon and finding its product positioning. That’s been resolved. It’s important to realize senior management created significant yet to be fully realized value over the past 3 years. Michael Morrison became the CEO ~ 3 years ago. During that time sales increased, new sales and supporting team created, recruited top proven BI talent, immediately implemented annual software maintenance, and smartly purchased Monarch's intellectual property. This intellectual property created added revenue opportunities, increased margins and created new products. Monarch’s intellectual property purchased for 8 million is now worth over 50M based on fundamentals such as gross profit and revenues. Additionally, award winning Swedish visualization software Panopticon purchased in an all stock transaction. January 2014 a secondary at 28.50 per share raised over 50M.
Multiple insider open market purchases in 2013, 2014 and 2015.  Management’s communication with shareholders is exceptionally transparent. Operational performance, financial results and strategy, both positives and negatives are shared in detail with investors. Talented board of directors includes executive chairman David Mahoney. Mahoney is the former CEO of Applix. Mahoney sold Applix to Cognos and 3 months later IBM purchased Cognos. Michael Morrison was the COO of Applix during Mahoney’s tenure at Applix. David Mahoney owns 282,983 shares around 2.5% of the shares outstanding, majority purchased in the open market, CEO Morrison owns 496,743 shares or 4.34%. Other board members own large positions; Christopher Cox 711,193 shares or 6.30%, James Wood 946,729 shares or 8.38%.  Joan McArdle has 187,500 shares or 1.66%.  Insiders own 31.29%, their personal interest aligned with public shareholders.
If you’re still interested after doing research build the position over time on days of price weakness. 

Monday, May 4

Wide Moat, Historically/Relatively Cheap, Overlooked Opportunity, Discount to Replacement Value

Rand Logistics:

Rand Logistics (RLOG) is a bulk carrier shipping company on the Great Lakes. Construction materials , grain, iron ore, coal,salt, and other products are shipped. They operate a fleet of 16 including the new addition announced on 04/22. This addition is the first new Canadian flagged river class self unloader to be introduced into service on the Great Lakes in over 40 years.  Rand’s current fleet count is 16, 10 Canadian flagged and 6 U.S. flagged vessels. “The new vessel is fully booked with long-term contractual business. It’s expected to be the most efficient river class vessel on the Great Lakes. The introduction of this vessel into service is one of the elements of their strategic plan to improve our return on invested capital.”

The CEO spoke in depth on improving ROIC during the recent earning call.  A project was implemented to identify, modify or eliminate customer contracts that are yielding an unacceptable return on invested capital. “Formalizing return on invested capital parameters for setting contract terms and pricing; continuing to improve the reliability and operating efficiency metrics to increase the percentage of time our vessels are in revenue-loaded condition. Rationalizing costs; increasing our sales efficiency relating to ship repair, maintenance and capital expenditures; and finally, introducing their newest vessel into service in the second half of 2015.”

Wide Moat:
Rand Logistics wide moat /barriers to entry are supported by several. The 1920 U.S. Jones act dictates only ships built, crewed and owned by U.S. citizens can operate between U.S. ports. Further the Canada Marine Act requires Canadian commissioned ships to operate between Canadian ports. Jones act legislation creates additional barrier to entry. Additionally, Rand has long term contacts with clients like Cargill, ADM,Kraft food, Morton Salt  and others. Customer relationships and focus to expand existing great lake region business creates advantages. Controlling the largest shipping fleet provides economies of scale.

Shipping is a capital intensive industry. It’s expensive to build a ship coupled with related costs adding another advantage over potential future competition. Executive management has deep logistics experience. Executive chairman, Laurence Levey served as chairman of of Detroit and Canada Tunnel Corporation, CEO of High Voltage Engineering Corporation, national logistics services company Ozburn-Hessey, director; Derby Industries LLC, and many other investment banking achievements. Lawrence Levey is a Baker Scholar from Harvard University.

Mean reversion attributes:

Stock's price is near its 5 year low coupled with P/B, P/S all near 5 year low. The high F score of 7 is driven by positive scores for NI, great than PY, hence current ROA positive and versus last year, Cash flow greater than NI, current ratio greater than PY, improvement in gross margins, improved efficiency as measured by the asset turnover versus PY. All these attributes contribute to a F score of 7. The F score was dragged down by a 2 tests, YOY increase in share count, increased leverage measuring Long Term Debt / Average Total Assets increased versus PY.RLOG has a history of poor execution with buybacks at attractive prices. Current F score of 7 is a positive sign. The median F score is 5 over the past 10 years. The only other time RLOG had an F score of 7 was 2012.RLOG had a 2012 high stock or price of 8.79 and low of 5.79.  Further, EV/GP is at historically cheap valuations. Current RLOG price is $3.36. Further, 52 price change was -44.10%. Temporary but significant foreign exchange rates challenges over the prior fiscal year. Lastly, anormal Great Lake ice conditions had a negative impact in prior quarterly results.

Summary Financial Statistics:
Price = $3.36
Market Cap: 61.43M , Enterprise Value: 247.90
Price/Sales (ttm):    0.40 , Price/Book (mrq):    1.09
Revenue (ttm):  153.61M , Revenue Per Share (ttm):      8.55
Qtrly Revenue Growth (yoy):     -1.70% , Gross Profit (ttm):     45.81M
EBITDA (ttm):  32.12M

Total Cash (mrq):  7.66M , Total Cash Per Share (mrq):   0.43
Total Debt (mrq):   177.40M , Total Debt/Equity (mrq):  249.35
Current Ratio (mrq):    1.53 , Book Value Per Share (mrq):     3.12
Operating Cash Flow (ttm): 21.27M , Levered Free Cash Flow (ttm):   -23.34M
52-Week Change:   -44.10%
52-Week High (Jun 12, 2014):   6.73 , 52-Week Low (Mar 10, 2015):    2.96
Shares Outstanding:   18.02M , Float:  15.16M
% Held by Insiders:    21.85% , % Held by Institutions:        69.40%
Short % of Float: 3.20%

No  position in RLOG. But, I  believe the stock will achieve market out performing returns over the next 12 months.

Sunday, April 26

WHAT HAPPENS, Blindly Buying Micro Cap Value the Day after Reported Insider Buying?

Alpha is created as an aggregated GROUP.  But can we improve and avoid those stocks that drag down aggregated returns following this method?

Insiders must use public information. Their advantage is interpretation of this public data. However, most insider trading data is noise.

The topic of insider trading has been rigorously studied. Findings published in academia and for profit firms. However, following insider trading activity is not a magic solution, get rick quick scheme. Countless insider trading newsletters have failed to justify their existence. They folded by over relying or simply misinterpreting information and ignoring financial and capital structure red flags. But having said this, studies have shown correctly using insider trading activity does have predictive market outperforming value. 

A summary of key points for using insider trading

    Less efficiently priced small companies with insider activity provide more market outperforming information. There’s a negative correlation (inverse relationship) between companies size and its insider activity forecasting value.
      Insiders have a greater understanding of their business economics. Officers (CEO, CFO) have the most accurate record. Large shareholders provide the least predictive value but shouldn’t be ignored.
      Purchases contain more information than sales. But multiple insider sales with a high short position can reveal potential company negatives.
      Consensus activity increases the predictive information of the insider trades. So a diverse group of buyers has more predictive value than one insider.
      The size of the transaction is proportionally important. I prefer to use the ratio of shares purchased to shares in the float to measure buying conviction. Further, I give more weight if the percentage of insider ownership is high before the insider activity.
      Analyze open market transactions; give less importance to private transactions.
      It seems logical insider activity within certain industries such as biotechnology may provide more directional information. The thesis is management understands the science and future possibilities of new drug breakthroughs or ability to pass future FDA hurdles. Other specialized industries should also be given a closer look.
“Several academic studies have been done over the years exploring the outperformance of insider trades and specifically insider buying. These studies have analyzed data over several decades and have shown that insider buying tends to outperform the overall market by 6% to 10.2% per year depending on which academic study and time period you look at.

According to the Wharton study “Estimating the Returns to Insider Trading” that looked at a comprehensive sample of insider transactions over 22 years from 1975-1996, about one-quarter of these abnormal returns accrue within the first five days after the trade and one-half accrues within the first month. You can read this research paper along with several other related papers below.”  Source  http://www.insidertrade.net/academic-research/

For this post, I will use the micro cap insider buying shared over the past 2 months. One goal is to uncover additional metrics that can improve the directional value of using positive insider activity.  This will require several posts.
I made the following observations.
Dig dipper into stocks listed on OTCBB, OTCPK. These companies are inefficiently priced. They hide in the shadows of Wall Street with little or no institutional coverage. I’m only saying there may be hidden opportunity in this group. It’s also an area with the most garbage, be careful.
Examples of actual shared ideas meeting this criterion over past 2 months are;
Frontier Oilfield Services, Inc. (FOSI) reported insider buying on 03/09/15. The following day’s price .90 versus current price of $2.94 (226% change in price), Further, additional buys reported 03/12/15 and 03/20/12. Buying the day after for would create potential outstanding returns. Furthermore, Spindle, Inc. (SPDL), Patent Properties, Inc. (PPRO), ICTV Brands Inc. (ICTV), Research Solutions, Inc. (RSSS), Cocrystal Pharma, Inc. (COCP), Brekford Corp. (BFDI), Bimini Capital Management, Inc. (BMNM) also created outstanding short term returns.
Certain industries insider knowledge carries more weight like biotechnology. Specific examples shared, Synta Pharmaceuticals Corp. (SNTA), Accelerate Diagnostics, Inc. (AXDX),  Sequenom Inc. (SQNM) ,Conatus Pharmaceuticals Inc. (CNAT) Biotechnology created great returns.
There are many more helpful metrics to consider.

Another "anomaly" I noticed with my small 2 month data set. Combine insider buying and the review ownership, if held by value intuitions your odd may improve. So if it's held by Heartland, Royce, Kennedy Capital, Gabeli, Tenton and others as an example you may have a better chance of outperformance. But when adding to these criteria you should consider relative prior 12 month returns. Consider avoiding stocks that have had relatively large move in its stock price.

That's it for now, more insights and discoveries in future posts.

Daily insider micro cap buying will continue to be shared in the tab labeled.

In conclusion yes buying the day after reported insider purchases for micro cap value as a group appears to generate Alpha short term. But this strategy is not practical. You would have to buy all or at least a random representative sample of the population. So having said that, I would use reported insider purchases as an excellent starting point. Then review industry, size of the purchases to shares  in float,  title of buyer (Office, Director, 5% owner),  number of individual buyers, historical price performance , value ratios, who owns the shares, company size and others.

Click to view details of reported daily activity,


Monday, April 13

C- level Recent Positive Insider Buying With Micro Cap Value

I’ve been sharing Form 4 micro cap purchases , from February 25, 2015 to April 10, 2015.  Today’s post takes a closer look.

My first approach focuses on company’s officers. CEO, CFO, COO (officers) activity carry more predictive power. Further, published studies show insider activity from smaller companies (micro cap) is more useful in determining the stock’s direction.
To measure conviction, I ranked shares purchased as a percentage of shares in float. Patience, waiting for your bid, building a position over time is advantageous with tiny companies.
These are a few convincing purchases from C-level executives (Officers) from February 25, 2015 to April 10, 2015.

Luby's, Inc. (LUB)

An interesting value attribute of Luby’s,  it’s the cheapest of the Restaurant stocks when comparing the acquisition cost (enterprise value) to owned real estate. Luby’s  was founded in 1947.

Bargain Status: Real Estate Rich Highly Fixable Opportunity

long LUB


Taitron Components Inc. (TAIT)

Gordmans Stores, Inc. (GMAN)

Old post "Cheap and Risky founded 1915: 52 Change -58.40% "

AeroCentury Corp. (ACY)

Other notable insider buying click to view details on google Docs.

Click to view quotes for all notable ideas.