Buying an individual stock

For the first time in a long time, I bought an individual stock in a global opportunistic portfolio focused on ETF's - but it's not for lack of discipline. The portfolio we discuss in this newsletter is an opportunistic portfolio, and sometimes the opportunities are in individual names.Viewing the remainder of this article requires a Subscription

Dangers of Indexing – This is important for money managers

There has been a lot of debate recently about the death of stock pickers, usually in conjunction with some discussion on high correlation, lower factor predictive abilities, etc. and at the same time, there has been an obvious growth in the use of index investing styles. I have tried to show different reasons why notifications of our death are premature, but a recent paper from the NBER has made me more optimistic about stock-pickers chances of success than I have recently been. For starters, a simple comparison of RSP (equal-weighted index) and SPY (market-cap-weighted index) shows that the average stock in the S&P 500 tends to outperform the index, leaving room for stock pickers over the index. For a quick chart, click here.

If that doesn’t satisfy you – because it didn’t satisfy me either – here’s a more thorough and interesting report (from FT.com):

A new paper from the National Bureau of Economic Research by Jeffrey Wurgler, Nomura professor of finance at New York University, discusses the potentially overlooked perils of indexing…

In terms of the effects, he finds:

On average, stocks that have been added to the S&P between 1990 and 2005 have increased almost nine percent around the event, with the effect generally growing over time with Index fund assets. 6 Stocks deleted from the Index have tumbled by even more. Given that mechanical indexers must trade 8.7% of shares outstanding in short order, and an even higher percentage in terms of the free float, not to mention the significant buying associated with benchmarked active management—this price jump is easy to understand and, perhaps, impressively modest.

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If a one-time inclusion effect of a few percentage points were the end of the story, then the overall impact of indexing on prices would be modest. But the inclusion effect is just the beginning. The return pattern of the newly-included S&P 500 member changes magically and quickly. It begins to move more closely with its 499 new neighbors and less closely with the rest of the market. It is as if it has joined a new school of fish.

Figure 2 (right) illustrates the phenomenon. It is worth repeating that this pattern is occurring in some of the largest and most liquid stocks in the world.7

In essence, he argues that the liquidity and market capitalisation of the stock becomes increasingly irrelevant once it becomes a member of a major index…

As he explains:

The net flows into index-linked products are both large and not perfectly correlated with other investors’ trades. Indexers and index-product users are by definition pursuing different strategies from those of the more active investor. They are less interested in keeping close track of the relative valuations of index and non-index shares. Some are index arbitrageurs or basis traders who care only about price parity between index derivatives and the underlying stock portfolio. The upshot is that over time, the index members can slowly drift away from the rest of the market, a phenomenon I will call “detachment.”

Consequently, Wurgler says this detachment may lead to a significant price premium for S&P 500 Index members.

He also cites a paper by Morck and Yang from 2001 which matched stocks within indices as closely as possible to a stock outside the index, with compatability defined in terms of size and industry.

The comparative valuations showed that S&P membership drove up a price premium in the order of 40 per cent.

Which leads him to conclude:

…the evidence is that stock prices are increasingly a function not just of fundamentals but also of the happenstance of index membership. This drives many of the negative consequences noted below.

As for those negative consequences, those are:

1) Bubbles and crashes.

The S&P 500 Index’s visibility and the easy access to ETFs and Index funds facilitate a high sensitivity of flows to returns.

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Index membership also affects high-frequency risks, and may encourage trading activity that exacerbates those risks. Dramatic examples include the crash of October 19, 1987 and the intraday “flash crash” of May 6, 2010. SEC investigations have centered on S&P 500 derivatives in both cases.

2) A confused risk-return relationship.

Whereas the basic proposition of asset pricing theory is the positive relationship between risk and expected return, he says in stock markets, the proposition is incorrect:

High risk stocks have, on average, delivered lower returns than low risk stocks in both U.S. markets and those around the world.

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A $1 investment in a low beta portfolio in 1968 grows to $60.46 by 2008, while the same investment in a high beta portfolio yields $3.77. The high beta portfolio actually has a negative real return; the 2008 portfolio adjusted for inflation is worth 64 cents. Restricting to larger cap stocks doesn’t significantly change the qualitative picture.

And this he says is because the basic problem is that managers benchmarked against a simple index will tend to favour high beta stocks – because the index is actually already outperforming versus the fundamentals.

In other words, for a manager benchmarked against the market portfolio, a stock with an alpha of 2% can be a candidate for underweighting. A similar argument shows that such a manager is also incentivized to overweight a low or negative alpha, high beta stock, unless the alpha is extremely negative.

For the full article, click here.

This should come as good news for stock pickers, but also might provide some interesting fodder for new tests, particularly low-latency equity long-short strategies.

Update on q-ratio

As readers already know, I use the q-ratio (aka Tobin’s q) for insight into the general market levels: The signs ain’t good. With the Flow of Funds report coming out June 10th (for the 1st quarter), the q-ratio was standing at >1. It’s historical average is 0.65. That implies a >35% decrease from here, which implies an S&P 500 level of 724. That’s just to approach fair value; however, we all know that these mean reverting series tend to overshoot, in the case to the downside.

For the full Flow of Funds data, click here. The applicable table is B.102 on page 105.

Non-financial companies, including both quoted and unquoted, were 62% overvalued according to q at 31st March 2010, when the S&P 500 index was 1169. Adjusting for the subsequent decline to 1087 (10th June, 2010), the overvaluation had fallen to 50%. Revisions to data had little impact on q, with downward revision to net worth for Q4 2009 of 2.9% being offset by a downward revision to the market value of non-financial equities of 2.1%. Net worth for Q1 2010 fell slightly as equity buy-backs exceeded profit retentions.

The listed companies in the S&P 500 index, which include financials, were 58% overvalued at 31st March 2010, according to our calculations for CAPE, based on the data from Professor Robert Shiller’s website. Adjusting for the subsequent decline to 1087 (10th June, 2010), the overvaluation had fallen 46%. (It should be noted that we use geometric rather than arithmetic means in our calculations.)

For a bit further discussion (and the source of the chart and quote) click here.

High Risk = Low Return

When I go shopping, I like a good deal. Who doesn’t?

Yet when shoppers enter the big mall of stock investing, they switch gears, often shunning good deals for the marked up items instead. Why? So many reasons we won’t even go there. Academia has proposed some theories about buyers only taking on risk if they are compensated for it, and measuring risk against a basket or market or securities. In fact, the data leads to a different conclusion altogether.

A recent paper by Baker, Bradley, and Wurgler continues brings further evidence to support our contention that risk doesn’t pay off:

Abstract
Over the past 41 years, high volatility and high beta stocks have substantially underperformed low volatility and low beta stocks in U.S. markets. We propose an explanation that combines the average investor’s preference for risk and the typical institutional investor’s mandate to maximize the ratio of excess returns and tracking error relative to a fixed benchmark (the information ratio) without resorting to leverage. Models of delegated asset management show that such mandates discourage arbitrage activity in both high alpha, low beta stocks and low alpha, high beta stocks. This explanation is consistent with several aspects of the low volatility anomaly including why it has strengthened in recent years even as institutional investors have become more dominant.

For the full article, click here.

And for those who haven’t read it yet, please read Josef Lakonishok’s work on how behavioral biases lead to value opportunities. This is an oldie but a goodie from Lakonishok, Vishny, and Shleifer. Here’s the abstract:

For many years, stock market analysts have argued that value strategies outperform the market. These value strategies call for buying stocks that have low prices relative to earnings, dividends, book assets, or other measures of fundamental value. While there is some agreement that value strategies produce higher returns, the interpretation of why they do so is more controversial. This paper provides evidence that value strategies yield higher returns because these strategies exploit the mistakes of the typical investor and not because these strategies are fundamentally riskier.

For the full article, click here.

What is the value of analysts?

We have often mentioned the heuristic biases of analysts, the dangers of forward looking statements, and the lack of insight analysts add (on average). The academic literature is just starting (not just starting, but still early in the process) of looking critically at behavioral factors not only in individual investors, but also institutional and professional investors and traders.

A new study by Eli Amir, Baruch Lev, and Theodore Sougiannis attempts to quantify the value of analysts:

We evaluate the contribution of analysts’ earnings forecasts to investors’ decisions by comparing the association between annual excess returns and a broad set of information items derived from financial statements with the association between excess returns and that information set plus the present value of five-year ahead analysts’ earnings forecasts. We thus bring to a sharp focus the incremental contribution (over financial statement information) of the major product of analysts – near and medium-term earnings forecasts – to investors’ decisions as reflected by annual excess returns. Large differences in explanatory power between the regressions with and without analysts’ forecasts are evidence in favor of analysts’ contribution to investors’ decisions.

However, in assessing analysts’ contribution from associations with stock returns care should be taken to account for the inherent simultaneity – analysts not only contribute (possibly) to investors, they also observe stock price behavior and learn from investors’ decisions. We are therefore using a system of simultaneous equations to control for the endogeneity of both excess returns and analysts’ forecasts, allowing us to isolate the net contribution of analysts’ forecasts to capital markets.

Our findings, based on cross-sectional regressions covering the period 1982-1997, indicate that over the sample period, analysts add a hefty 40 percent (in Adj-R2 terms) to the explanatory power of financial information with respect to stock returns. However, when simultaneity (i.e., analysts’ learning from returns) is accounted for, their contribution is estimated as a modest 12 percent. This result suggests that analysts’ mostly react to changes in market values rather than cause them.

Additional findings are: (1) The explanatory power of the broad-based financial statement information set decreased significantly over the examined period, while the explanatory power of the model including analysts’ forecasts decreased at a lower rate. Analysts, therefore, mitigate to some extent the decrease in the informativeness of financial statements. (2) The incremental contribution of analysts in firms that report losses is substantially larger than in profitable companies. (3) The incremental contribution of financial analysts is largest in high-tech industries followed by low-tech industries, and regulated firms, suggesting that the contribution of analysts is larger in sectors where the informativeness of financial reports is low. (4) Analysts’ contribution to valuation in firms with substantial research and development (R&D) capital is relatively larger than in firms without such R&D capital. (5) The incremental contribution of analysts during economic boom periods is higher than during recessions (e.g., the early 1990s). (6) Based on a firm-specific measure of analysts’ incremental contribution, we find that this contribution decreases with firm size, systematic risk, and earnings persistence, and increases with the firm’s R&D capital. All in all, we find the direct contribution of analysts’ forecasts of earnings to investors’ decision to be quite modest. However, this contribution is substantial in firms, sectors and circumstances where the informativeness of financial statements is relatively low.

To download the full article, click here.

And directly from the article:

All in all, we find the direct contribution of analysts’ forecasts of earnings to investors’ decision to be quite modest. However, this contribution is substantial in firms, sectors and circumstances where the informativeness of financial statements is relatively low. Furthermore, analysts rely more heavily on non-financial information in high-tech industries, loss firms, and companies with high R&D intensity.

Definitely worth a read for all the compensation committees and human resource departments out there.

Montier “…how EMH has damaged our industry” (reprinted with permission)

In this excellent piece from last week, James Montier highlights some flaws in the efficient market hypothesis. More importantly, he outlines the some of the damage – that may take years to repair – caused by the ensuing mentality in the investment community. Beta and alpha debates should move over already. Risk is not volatility. This is a beginning of a trend that I’m seeing of late. The intellectual framework is actually shifting. Consulting firms to big pension funds are reviewing the idea of style boxes. Stagnant asset allocation is being reworked, with emphasis on higher allocations to undervalued assets. Benchmarking is changing. Indexing itself is changing. This piece is a good starting point.

montier-06-18-09