Excerpted from: “Solar company spinoffs lure investors with dividends”, by Reuters

Long shunned by cautious investors, solar companies have hit on a new way, [known as Yield Companies or Yield Cos], to deliver returns to shareholders. that could attract new money to an industry notorious for its stock price volatility.

Yield cos… own and operate solar assets under long-term power-purchase agreements with utilities – a guarantee of stable cash flow.

SunEdison Inc is the first of a wave of companies preparing to bundle up existing solar power plants and then spin them off into separate entities, known as “yield cos”, to raise money to build new plants.

The promise of regular dividend payouts, hitherto unknown in the solar industry, offers an entry point to the sector for retail investors and is expected to generate huge demand when these companies go public, analysts and investors said.

Most of this cash will be paid out as dividends, with the remainder re-invested in new plants, a valuable source of funding for parent companies that will retain a sizeable stake in the new entities.

The only U.S.-listed yield co that currently holds solar assets is power company NRG Energy Inc’s NRG Yield Inc , which made its stock market debut last July [2013].  

The stock for NRG increased from about $30 at its offering to over $50 on July 7, 2014.

Dwight Steward wrote:

Cattle prices in Texas will continue to go up.  There are several factors that point to a continued increase in prices.

1. The overall number of cattle in Texas has fallen.  From 2012 to 2013, the total number of cattle on feed decreased by over 600,000 from 11.9 M to 11.3M which is a 5% reduction.  As with anything, the fewer that you have the more that they will cost.

2. The number of breeding cows has decreased even more.  From 2012-13, the number of breeding cows decreased 12%, from 4.57M to 4.02M.  The smaller number of breeding cows in Texas means that there will be fewer calves born in subsequent years which absent significant imports of cattle into the state, means that there will be smaller herds into the indefinite future for Texas.

3. The Fracking Boom.  The fracking boom has made cattle ranching relatively more expensive in certain areas of the state.  In some areas, such as South Texas, cattle ranchers have found that it is more profitable to sell or lease their land for oil and/or gas exploration.

See the cattle price data here;

https://docs.google.com/spreadsheets/d/15jia1S9wv7BVUzGngeHoX-Ac6ERhCWTrzqIj2GUR4dA/edit?usp=sharing

by Dwight Steward

When manual data entry of non-analyzable financial or wage data  is not an option, OCR software and specialized designed and written computer software data cleaning routines is a good alternative.

For example in our approach, we use a number of OCR programs including Abbey Reader to first translate the data into a format that is recognized by statistical programs such as STATA and computer software script languages such as VBA.

Once the data is converted, we write specialized computer software routines to extract the relevant data from the converted file.  The computer code, which is written in STATA, VBA, or other scripting language, puts the extracted data into a format that can be analyzed by statistical and spreadsheet programs.

These approach to converting wage, business, employment or other types of data has the advantage of being able tobe  reproduced by either party if required.

Having both the data cleaning and statistical and economic analysis performed by the same economic outfit and team is desirable.  Data cleaning is not performed in a vacuum; that is the very definition of ‘dirty data; depends on what the data is to be used for.  Some data items may not convert very well by the OCR and software code, but the items may be of little value in the economic and statistical analysis in the first place.

One advantage of using the same research outfit to do both the data cleaning and the economic and statistical analysis is that the distinction gets made early in the analysis process.

Some wage and business data is electronic but is not analyzable in the format that it is maintained by the employer or company.

For instance,some employers use computerized data systems for recording the start times, lunch periods, and end periods for certain employees.  When reviewing this data in the regular course of business some of these employers review standardized, pre-formatted reports of the time punch data instead of the actual underlying time punches that were made by each individual employee.  Many of these standardized reports are presented in a PDF or other non-analyzable electronic format.

Similarly, some businesses retain certain information, such as itemized copies of purchase orders, only in a PDF or other non-analyzable electronic format.

The task when addressing economic damage issues that rely on this type of non-analyzable electronic information, is to accurately and efficiently translate the data into a format that can analyzed using statistical programs, such as STATA.  In cases with relatively small amounts of data spreadsheet programs such as EXCEL could also be used.

How is this done? Next>>>>

Allegations of economic loss arising from damaged credit history appear in cases involving business damages as well as personal injury torts.

In these cases, the loss allegations generally revolve around a specific economic damage such as a mortgage loan denial or a higher interest rate.

The economic damage calculation and/or rebuttal analysis general involves comparing the plaintiff’s current economic and credit situation to the economic and credit situation that could have been reasonably expected to occur had the incident in question not occurred.

The credit situation that could have been reasonably expected to occur had the incident in question not occurred is typically referred to as the ‘but-for’ scenario.

Credit cards and debit cards are the way of the world now; it is how we pay for nearly everything we buy now.

One question that comes up for retail businesses is: Does the type of credit card tell us anything about the customer?

For example, do AMEX users tend to be bigger spenders?  The answer of course depends on the business.  The table below shows the average sale and percentage of monthly sales made by customers of a small restaurant broken down by the type of credit/debit card used.

For this business VISA is king. Moreover there is little difference in the size of the average bill of the different types of credit/debit card users.