Today I came across a blog that nicely describes how a company’s clarity of vision and strategy influence its market evaluation.
That blog analyzes Oracle, HP, Apple, Google, Microsoft and SAP to support and explain its arguments. Rather than I summarizing that blog here, I would direct you to original blog.
We discussed three metrics, Altman-Z, Beneish M and Piotroski F, in my first blog on this subject. These metrics are very helpful in pointing out something unusual in financial statements of a company. Companies will usually be able to explain flags raised by these metrics. One must carefully examine each factor contributing to red-flags. That is where an expert adds value.
For example, an analysis on Enron written by by graduate students of Cornel University is frequently quoted whenever Beneish M-Score is mentioned. However, if you read that paper, students analyzed their results on Beneish M-score and concluded that “However, further examination of these indicators showed no cause for concern.” Now, in hindsight, we all know that there was a cause for concern.
Let me showcase another analysis that I did recently on Apple (AAPL). As you will notice in picture 1, Beneish analysis raises red flags for 2006, 2007, 2009 and 2010. You will need to analyze Apple’s annual reports to find causes of these red flags.
If you dig further into data for 2006 , you will notice a sudden change in AQI (asset quality index) and LVDI (Leverage Index). You will further find that apple paid $1.2 billion for prepayment of NAND memory modules, other current assets increased from 648M to 2270M and vendor non-trade receivables increase by $1B.
Data for 2007 tells us that receivables jumped from $1252M to $4029M. Also worth reading is a note in annual report
“The Company is exposed to credit risk on its accounts receivable and prepayments related to long-term supply agreements. This risk is heightened during periods when economic conditions worsen.
A substantial majority of the Company's outstanding trade receivables are not covered by collateral or credit insurance. The Company also has unsecured non-trade receivables resulting from the sale by the Company of components to vendors who manufacture sub-assemblies or assemble final products for the Company. In addition, the Company has entered into long-term supply agreements to secure supply of NAND flash-memory and has prepaid a total of $1.25 billion under these agreements, of which $208 million had been used as of September 29, 2007. While the Company has procedures to monitor and limit exposure to credit risk on its trade and non-trade receivables as well as long-term prepayments, there can be no assurance such procedures will effectively limit its credit risk and avoid losses.”
Beneish analysis also flags an unusual jump AQI to 4.46 in 2009. Annual report for 2009 indicates $16B increase in investment in long-term and short-term securities.
To summarize, examine results of these metrics for any red flags. Further analyze financial data contributing to these flags. That should lead you foot notes and explanations in financial statements. Remember that financial statements are prepared by firm and you should critically examine firm’s explanations for such changes.
I will be delighted to hear your comments on my analysis and explanations. Any suggestions for improving this blog will be most welcome. If you will like to receive a copy of my calculator, please drop me an email.
I wrote my first blog on this subject on Sept 27. Spreadsheet shown in that blog lets me compare three metrics (Altman-Z, Beneish M and Piotroski F) across different firms for last financial year. I have created another version of this spreadsheet that lets me evaluate these metrics for a single company over last 10 years. This spreadsheet also provides a summary of financial statements for that company for last 10 years.
I will be more than happy to share this sheet with you and solicit your feedback. Please send me your request for download location via email.
Thanks
Forecasting and predictive analysis is used to model or predict future behavior of a system using previous observations or facts about the system. Such analysis is used extensively by scientists, economists and financial analysts in scientific as well as business applications.
Approach used for such analysis can be summarized as
Such analysis is frequently used by financial analysts to predict future stock prices, financial viability of a project, growth rates etc. Businesses use such models to predict supply, demand, prices and various other factors.
I have been developing my own models and using models generated by others for several years. Very often, as soon as people see a computer, spreadsheet or set of mathematical equations, they assume their results to be absolute truth. I would like to caution and share following comments.
Recently I was looking at Altman-Z financial analysis presented at a web site. It was a very impressive analysis and gave very detailed in-depth recommendation on growth rate & future price targets. However, when I tried to verify the results, I found that this analysis was using incorrect historical stock prices. Thirty pages of recommendations were generated using incorrect set of input stock prices!
To conclude, always remember that predictive analysis depends on accuracy of
1. Historical data used for initial model building
2. Assumptions about future input variables.
you will get incorrect prediction if either of these are not inaccurate.
Recently there has been a consistent stream of news reports on debt value adjustment (DVA) and possibility of FASB getting rid of this concept.
What is DVA?
In order to explain concept of DVA in layman language, assume that company A has floated long term bonds with face value of $100. Further consider a drop in credit rating of company A and a resultant fair market value of $70 for this bond. Concept of DVA allows company A to recognize difference ($100 – $70 = $30) as revenue.
Concept of DVA was introduced by FASB in 2007 after intense lobbying by financial companies, such as Merrill, Morgan Stanley, Goldman Sachs and Citigroup, which wrote letters to FASB arguing that it wasn’t fair to make them mark their assets to market value if they couldn’t also mark their liabilities. Their argument was that firm’s liability on day of reporting is lower because it can buy back its debt instruments from market at reduced price. (ref: Wall Street Says -2 + -2 = 4 as Liabilities Get New Bond Math )
Detractors of DVA find it against principle of conservatism, which states that accountant must choose reporting alternative that will result in less net income and/or less asset account. Argument against DVA is that if firm attempts to buy back its instruments,
1. It will need to borrow money at a higher rate in line with its reduced credit rating, and
2. Bond holders may decide not to sell their instruments and to wait for duration of bond and wait for full payment.
How to identify DVA in annual report of a company
Unfortunately DVA is not shown on balance sheet as a line item. You will need to read full annual report and search for word like “DVA” or “Fair market value of liabilities”. For example, following is an extract from page 55 of Bank of America Corporation’s (Ticker: BAC) annual report for 2011
[“Net income decreased $3.3 billion to $3.0 billion in 2011 primarily driven by a decline of $4.2 billion in sales and trading revenue. The decrease in sales and trading revenue was due to a challenging market environment, partially offset by DVA gains, net of hedges. In 2011, DVA gains, net of hedges, were $1.0 billion compared to $262 million in 2010 due to the widening of our credit spreads.”]
BAC’s net income, inclusive of DVA for 2011 and 2010 was $2.967B and $6.297B respectively. If you get rid of DVA fluctuations, actual income numbers for two years are really $1.967B and $6.035B!
Today most commentators agree that DVA rule must go. I fully agree.
I look forward to your feedback, comments and suggestions on this post.
