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Does Customer Satisfaction Translate to Excess Stock Returns?

Do companies with high marks for customer satisfaction outperform as investments? Or, instead, does making customers happy crimp profit margins and stock returns? In their January 2006 Journal of Marketing article entitled “Customer Satisfaction and Stock Prices: High Returns, Low Risk”, Claes Fornell, Sunil Mithas, Forrest Morgeson III and M.S. Krishnan investigate the relationship between customer satisfaction as measured by the American Customer Satisfaction Index (ACSI) and stock returns. ACSI measurements are updated annually for each company rated. Using ACSI ratings for publicly traded companies during 1994-2004 and associated firm accounting and stock price data, they find that: Keep Reading

Increased Reliability for Buyback Announcements?

Since the mid-1980s, stock repurchases have increasingly displaced dividends as a means for companies to return cash to the equity market. Buybacks affect stock prices by reducing the the denominator in the earnings per share calculation, thereby elevating the value of shares still outstanding. However, firms that announce buybacks may not actually execute them, or may execute them only partially. Are stock buybacks, due to increased information transparency, more reliable now than they used to be? In his recent paper entitled “The Effect of Enhanced Disclosure on Open Market Stock Repurchases”, Michael Simkovic examines whether the SEC requirement that companies disclose repurchase activity on a quarterly basis as of 2004 has increased the likelihood that firms will follow through on buyback announcements. Using repurchase activity data over the 20 months after each of 365 buybacks announced during 2004 for comparison with data from two pre-disclosure studies, he concludes that: Keep Reading

The Trading Wire at ChangeWave

As suggested by a reader, we evaluate here the Trading Wire archives at Tobin Smith’s ChangeWave, which extend back to November 2004. Tobin Smith, according to ChangeWave.com, is “among an esteemed new breed of investment advisors, with a fresh profit strategy for the post 2000-2002 bear-market investing world. He’s an energetic straight shooter with a simple goal: exceptionally large profits from sweeping, transformational changes taking place within industries or individual companies.” As complement to analysis of “sweeping, transformational changes,” the Weekly Forecast section of ChangeWave’s Trading Wire offers commentary on stock market direction. The principal author of this weekly forecast is ChangeWave’s Chief Technical Analyst Sam Collins. The table below quotes forecast highlights from the cited source and shows the performance of the S&P 500 Index over various numbers of trading days after the publication date for each item. Grading takes into account more detailed market behavior when appropriate. Red plus (minus) signs to the right of specific forecasts indicate those graded right (wrong) based on subsequent market behavior, while red zeros denote any complex forecasts graded both right and wrong. We conclude that: Keep Reading

Do Good Employers Make Good Investments?

Do companies famously known as good places to work outperform as investments? Or, contrarily, do they waste resources keeping employees happy? In his May 2007 paper entitled “Does the Stock Market Fully Value Intangibles? Employee Satisfaction and Equity Prices”, Alex Edmans analyzes the relationship between employee satisfaction and long-term stock performance. He identifies companies with exceptionally satisfied employees via Fortune magazine’s annual list of the “100 Best Companies to Work for in America.” Using these lists for 1998-2005 and monthly stock price data for the publicly traded companies in the lists (about 60 per year), he finds that: Keep Reading

Testing the Value Premium Down Under

Is the value premium so fundamental that its exists generally among stock markets? In their recent paper entitled “Value versus Growth: Australian Evidence”, Philip Gharghori, Sebastian Stryjkowski and Madhu Veeraraghavan test the abilities of indicators based on several alternative definitions of “value” to explain the cross-sectional variation in stock returns in Australia. Specifically, they test book-to-market value ratio (B/M), sales-to-price ratio (S/P), cash flow-to-price ratio (C/P) and earnings-to-price ratio (E/P). They also compare the predictive powers of these value indicators to those of size and debt-to-equity ratio (D/E). Using firm financial data for 1/92-12/04 and associated monthly stock prices for 1/93-12/04 (a total of 137,139 firm-month observations), they find that: Keep Reading

Left Versus Right Down Under

Are “hands-off” (right-leaning) governments better for stocks than “hands-on” (left-leaning) governments? In their recent paper entitled “Investment Returns Under Right- and Left-Wing Governments in Australasia”, Hamish Anderson, Christopher Malone and Ben Marshall examine the effect of ruling party orientation on inflation, and thereby on stock, property and bond returns, in Australia and New Zealand. Using monthly, annual and political-term data as available across the period 1910-2006, they find that: Keep Reading

Technical Analysis: “Anathema to the Academic World”?

Technical analysis seeks to exploit stock mispricings derived from postulated investor/trader psychological biases. Does short-term technical analysis actually produce abnormal returns? Or, do its adherents persist based on a misperception that they are to some degree in control of random rewards. In their February 2006 paper entitled “Does Intraday Technical Analysis in the U.S. Equity Market Have Value?”, Ben Marshall, Rochester Cahan and Jared Cahan investigate whether intraday technical analysis is profitable in the overall U.S. equity market. Specifically, they apply a combination of statistically rigorous bootstrapping tests to 7,846 trading rules from five rule families (Filter, Moving Average, Support and Resistance, Channel Breakouts, and On-Balance Volume). Using 5-minute data for Standard and Poor’s Depository Receipts (SPDR) over the period 1/1/02-12/31/03 (encompassing both bear and bull trends), they conclude that: Keep Reading

Liquid Beats Illiquid for Portfolio Growth?

Do stocks that are difficult to trade (have low liquidity) offer abnormal returns as compensation for the risk of getting out of them? Or, is this reward-for-risk intuition unsound? In their recent paper entitled “Cross-Sectional Stock Returns in the UK Market: the Role of Liquidity Risk”, Soosung Hwang and Chensheng Lu investigate the relationship between liquidity and return for individual stocks, with focus on the link between liquidity and the value premium. They introduce a new measure of liquidity based on the absolute change in stock price per unit of turnover, with turnover calculated as the fraction of firm market capitalization traded. Using price, trading volume, capitalization and fundamentals data for UK stocks over the period 1987-2004, they conclude that: Keep Reading

Low Risk and High Return?

Stocks with high historical volatility should produce high returns as reward for extra risk. Shouldn’t they? In the April 2007 version of their paper entitled “The Volatility Effect: Lower Risk without Lower Return”, David Blitz and Pim van Vliet examine the relationship between long-term (past three years) historical return volatility and risk-adjusted return for stocks worldwide. Ranking stocks based on historical volatility has some similarity to ranking them based on beta. Using monthly price and fundamental data for a large number of large-capitalization stocks over the period December 1985 through January 2006, they find that: Keep Reading

Testing the Head-and-Shoulders Pattern

Does the head-and-shoulders stock price pattern embody investor attitudes that traders can exploit to earn abnormal returns? Or, does it represent an opportunity for the statistics-challenged to be fooled by randomness? In their October 2006 paper entitled “The Predictive Power of ‘Head-and-Shoulders’ Price Patterns in the U.S. Stock Market”, Gene Savin, Paul Weller and Janis Zvingelis use a pattern recognition algorithm, as filtered based on the experience of a technical analyst, to determine whether head-and-shoulders price patterns formed across intervals of 63 trading days have predictive power for future stock returns over the next few months. Using daily price data during 1990-1999 for all stocks in the S&P 500 and Russell 2000 indexes as of June 1990, they conclude that: Keep Reading

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