Value Arbitrage – Beware Of Useless Data From Governments
Buy in an emerging market, sell in the established capital markets. On the surface, the formula for arbitrage success appears fairly straightforward. But all too often, the practical foundations of a value arbitrage exercise are seriously flawed: the very data upon which the buy-sell window is premised is either misleading or too broad to justify any credible conclusions.
Yes, value arbitrage is perhaps the most compelling investment profile in today’s complex and fast-changing international environment; but the underlying value drivers must be in place, and be independently verifiable in precise terms.
For instance, protagonists of emerging market investments have been touting India’s 10%-plus GDP growth and 250 million-plus middle class in order to encourage investments either in the Bombay Stock Exchange or in unlisted counters. However, a closer scrutiny of India’s GDP numbers urges extreme caution. Firstly, India’s GDP growth is composed of a highly uneven matrix of untested data and is, in fact, littered with examples of business sectors which are going nowhere in a hurry. Secondly, a fair proportion of the middle class is surviving on debt-less than 10 million households are reporting positive balance sheets today. Finally, according to latest reliable data, almost 800 million Indians live on less than a dollar a day!!
Value arbitrage strives to be a science, not an art. Therefore, there is need for a certain minimum level of exactness when creating a value arbitrage special situation.
Nobody disputes that third world investment strategies must incorporate exponential growth in shareholder value in the chosen business segment, if only to allow for impaired statistics. “But investors must go one step further when seeking above-average profits in the emerging markets, they must adopt a dual approach, identified by a thorough, independent analysis of the supposed facts presented by various government agencies on one hand and by a wide margin of error to compensate for the lack of historical integrity in statistical determinations,” a senior Geneva-based hedge fund manager explained yesterday. “Otherwise, all arbitrage is at risk, particularly when exit strategies are time-sensitive.”
Then there is the all-important demand for specificity, i.e. raw data which directly impacts the subject investment, both in the near term and over the longer term.
Not surprisingly, the current across-the-board turmoil in pricing, influenced by sub-prime debt and the volatility in oil prices, is leading an increasing number of shrewd asset managers to conclude that GDP is one big fallacy, an abstraction devoid of any link to the real world. How can a growth rate of 10% assist an investor who is only interested in profits and losses?
In the simplest of terms, GDP is computed by calculating the total market value of all goods and services generated in a given year, plus the value of exports, less the value of imports. At first glance, GDP appears to adequately mirror a national economy and, even today, the overwhelming majority of mutual fund and asset pool managers use GDP as an early-stage selecting tool while picking one developing economy over another.
However, the GDP framework fails to tell us what causes fluctuations in government spending, consumer activity, private investment or, in the case of countries like India, agricultural production which is dependent, in the final analysis, on the vagaries of the weather. Moreover, GDP which itself is subject to one or more revisions, does not enable a reasonable assessment of boom-bust cycles.
That said, industry-specific data is generally much more reliable for decision-making purposes. And interestingly, for arbitrage traders, countries with relatively low GDP growth can, at times, offer better industry-specific investment profiles than high-growth markets. It should not be forgotten that the value arbitrage prism is extremely technical in nature, and is conditioned not only by potential returns but also by the timing of those returns.
