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How financial data can lie

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William Gamble | 18/11/2013 11:55 AM | 

Investors depend on financial data but there are distortions of information throughout the financial world.  Numbers, like anything else, can lie

Any investor invariably becomes a ravenous consumer of financial information. Much of that information comes in the form of numbers. Hundreds of acronyms forming a massive alphabet soup! Besides the numbers, there are also analysts, economists and even humble financial writers, who attempt to explain, or torture, the numbers into a construction that fits their thesis. But there is a major problem with this process. You have to ask yourself an extremely important question. Are the numbers really accurate? Do they provide a complete and timely description of what they are trying to measure?

 

Investors have to have information. Markets especially react, often with breathtaking speed, to this information, but one of the main reasons why markets are so volatile is that the information is subject to major revisions. We should not be surprised. There are enormous economic and political incentives for spinning the data. Bad information does not come with an expiration date. If undiscovered the fraud can easily continue for years.

 

Even presumably honest government agencies in developed countries produce data with major gaps. The monthly circus in the United States surrounding ‘jobs Friday’ is often a meaningless charade. The US government produces the jobs and unemployment report the first Friday of the month (assuming it is not shut down). But the report also revises, sometime by large amounts, its prior reports.

 

The central governments may make good faith efforts to get accurate statistics, but their work can be stymied by local interests. When a team from the EU’s statistical office, Eurostat, tried to force the Greek government’s statistical agency to produce more accurate numbers, the local personnel staged a revolt against the new management. Beijing has a constant struggle to get provincial governments to provide good information that at a very minimum do not contradict what the central government issues.

 

It is earnings season in the US. A company’s stock, and the CEO’s compensation, can go up substantially if the company ‘beats’ analyst’s estimates. Of course one reason that companies ‘beat’ estimates is that CEOs spend a great deal of time lowering analyst’s expectation. On average 63% of the companies beat estimates. Since analysts get it right only 37% of time, far less than flipping a coin, one wonders why they bother.

 

Analysts did a little better this earning season. Despite the quantitative easing (QE) distortions in the US markets, earnings were really bad. According to Zacks Investment Research, in May analysts were forecasting 5.1% growth. Many CEOs managed to massage expectations down to 2.1% and the companies could not even beat that. Compared with the second quarter of this year, earnings per share may be flat.

 

But those numbers are even inaccurate. Thanks to widespread use of debt fuelled share buybacks designed to spread meagre earnings among fewer shares, the earnings look better than they are. If you use the actual dollars amounts, the profits of S&P 500 companies are set to fall, according to Zacks, from $260.3 billion in the second quarter to $255.2 billion in the third. The final dollar amount is probably lower. Despite all of the accounting gimmickry according to Bespoke Investment Group: “Of the 2,268 companies that reported this season, which started in early October, 58.6% beat earnings estimates.  Since the bull market began in March 2009, this is the second worst earnings beat rate we've seen.  Only Q1 of this year was worse.”

 

Despite analysis of the apparent next chairperson of the US Federal Reserve, Janet Yellen, the frothiest part of the American stock market are social media stocks. Normally, companies are judged by certain simple metrics like profit. Some even pay dividends. But old fashion concepts like earnings per share are not necessary for these stocks. In the days of the dot com stocks, investors used the number of “eyeballs” a site received. Now it is price per user, which explains the astronomical valuations for Facebook and Twitter. But there is one question. Who is a “user”?

 

Facebook and Twitter use the concept of ‘monthly active user’, but even Twitter estimates that approximately 13% of its users are fake. Other social media stocks use different measures. On the other hand, LinkedIn uses “registered users”. LinkedIn has been operating for 11 years and includes every profile ever created whether they are active or not, sort of like selling advertising based on the number of profiles on MySpace.

 

It is not only wonky metrics. The tech companies have a nasty habit of releasing profit and revenue numbers without expense deductions required by standard accounting rules. The most obvious practice is to strip out options. For example, Twitter’s adjusted EBITA of $31 million would have been negative if they included $79 million of stock compensation expense. But it is not just stock compensation expenses. These accounted for only a quarter of the expenses added back to profits. Tech firms also added back things like charges related to acquisitions, restructuring costs, amortisation of intangibles, asset impairments, fines and legal judgments. For tech companies listed in the S&P 500 these added up to a whopping $40.7 billion in 2012. The practice is increasing. In 2012, 36% of accounting expenses were added back to profits above the 20% added in 2011. There are real numbers required under GAAP (US accounting standards) available, but investors have to dig for them.

 

Dr Janet Yellen’s assertion that there are no bubbles is based on the fact that earnings are 15 times forward PE. Without mentioning the distortions of QE and share buy backs, it should be pointed out that when the market topped in 2007, the forward PE was also 15 time forward earnings. There are other measures like the cyclically adjusted price earnings ratio (CAPE) which is at levels reached in 1929, 2000 and 2008. More ominous is price to sales, which is at the highest level over the past 30 years.

 

Information in the US, though distorted often by spin, is usually available. In China it might not exist at all since the government controls information. The real GDP growth has an interesting habit of always matching analyst’s estimates. Other measure of GDP put it at below 5% rather than the official 7.8%.

 

Companies are infinitely worse. For example, Zoomlion is one of the largest heavy equipment manufacturers in China. It is also partially owned by the province of Hunan. It has long had a reputation for rather interesting sales and financing practices. Last January, Zoomlion was accused, at last. At that time a letter was sent to Hong Kong market regulator from a “a concerned international investor” which accused Zoomlion of “suspected fraud” and “disclosure of false information”.  In May, newspapers in Hong Kong again received information purportedly showing inflated sales. Finally, in October a Chinese journalist, Chen Yongzhou, working for the Chinese paper New Express was arrested for a story about fraud at Zoomlion. Conveniently, he was arrested and then confessed on television. Zoomlion has never been investigated by anyone.

 

These are just some examples of distortions of information throughout the financial world. Some are far greater than other, but it is important for investors to understand that numbers, like anything else, can lie.

 

(William Gamble is president of Emerging Market Strategies. An international lawyer and economist, he developed his theories beginning with his first-hand experience and business dealings in the Russia starting in 1993. Mr Gamble holds two graduate law degrees. He was educated at Institute D'Etudes Politique, Trinity College, University of Miami School of Law, and University of Virginia Darden Graduate School of Business Administration. He was a member of the bar in three states, over four different federal courts and has spoken four languages.)


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