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Sentiment Indicators

Investors/traders track a range of sentiments (consumer, investor, analyst, forecaster, management), searching for indications of the next swing of the psychological pendulum that paces financial markets. Usually, they view sentiment as a contrarian indicator for market turns (bad means good — it’s darkest before the dawn). These blog entries relate to relationships between human sentiment and the stock market.

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Gross National Happiness as Stock Market Return Predictor

Does aggregate social network sentiment, as measured by Facebook’s Gross National Happiness (GNH), predict future stock market returns? In his August 2011 preliminary draft paper entitled “Can Facebook Predict Stock Market Activity?”, Yigitcan Karabulut investigates the relationship between GNH as a proxy for investor sentiment and stock market activity. Per Facebook, GNH derives from “…millions of people [sharing] how they feel with the people who matter the most in their lives through status updates on Facebook. …Grouped together, these updates are indicative of how we are collectively feeling. …When people in their status updates use more positive words–or fewer negative words–then that day as a whole is counted as happier than usual.” The author corrects daily stock returns for temperature, precipitation and hours of darkness in New York and for the lunar cycle. Using daily GNH measurements for U.S. Facebook members, stock market returns and weather/seasonal/lunar phase data over the period 9/8/07 to 3/1/11 (876 trading days), he finds that: Keep Reading

Short-term News Premium for Individual Stocks

“With Thomson Reuters News Analytics, computers can not only read the news – they can interpret it too. The results can enhance your investment and trading strategies, helping you to spot new opportunities and generate alpha. And for the humans among us, news sentiment analysis offers meaningful insight to drive trading and investment decisions.” Is this representation accurate? In his July 2011 paper entitled “News Sensitivity and the Cross-section of Stock Returns”, Michal Dzielinski tests whether returns on positive, neutral and negative news days as indicated by this source are significantly different from the average daily return of a large sample of U.S. stocks. Using Thomson Reuters News Analytics sentiment assessments of novel news items timestamped at least two hours before the stock market close and contemporaneous returns and firm characteristics for covered stocks over the period January 2003 through August 2010 (780-946 stocks per year), he finds that: Keep Reading

A Few Notes on The Most Important Thing

Howard Marks introduces his 2011 book, The Most Important Thing: Uncommon Sense for the Thoughtful Investor, by stating: “…I have built this book around the idea of the most important things–each is a brick in what I hope will be a solid wall, and none is dispensable. …I consider it my creed, and in the course of my investing career it has served like a religion. …You won’t find a how-to book here. There’s no surefire recipe for investment success. …Just a way to think that might help you make good decisions and, perhaps more important, avoid the pitfalls that ensnare so many. …the thing I most want to make clear is just how complex [investing] is.” Evolved from decades of investing experience, including that as co-founder and chairman of Oaktree Capital Management, some notable points from the book are: Keep Reading

Wonders of the World and Market Tops

Does construction of new tallest-in-the-world buildings indicate financial hubris and therefore pending equity market weakness? In the March 2011 version of his paper entitled “Tower Building and Stock Market Returns”, Gunter Löffler relates construction of record-breaking skyscrapers to future stock market returns. He focuses on construction start dates, since completion dates may occur after any wave of optimism that encourages construction may have passed. He focuses on the U.S. because most relevant data is American. Using U.S. building construction and stock market data for 1871 through 2009, he finds that: Keep Reading

Stock Return Correlations and Retail Trader Herding

Is there evidence of investor herding in the variation of return correlations for individual stocks? In their January 2011 paper entitled “Asymmetric Correlations”, Tarun Chordia, Amit Goyal and Qing Tong investigate when and why return correlations for individual stocks vary over time. At the end of each month, they calculate average pairwise correlations of stocks at a daily frequency over the month. Using daily returns for all NYSE common stocks, along with contemporaneous stock trading data and firm characteristics, from January 1963 through December 2008, they find that: Keep Reading

Interaction of Investor Sentiment and Stock Return Anomalies

Does aggregate investor sentiment affect the strength of well-known U.S. stock return anomalies? In their January 2011 paper entitled “The Short of It: Investor Sentiment and Anomalies”, Robert Stambaugh, Jianfeng Yu and Yu Yuan explore the interaction of aggregate investor sentiment with 11 cross-sectional stock return anomalies. Their approach reflects expectations that: (1) overpricing of stocks is more common than underpricing due to short-sale constraints; and, (2) a high sentiment level amplifies overpricing. Specifically, they consider the effect of investor sentiment on hedge portfolios that are long (short) the highest(lowest)-performing) value-weighted deciles of stocks sorted on: financial distress (two measures), net stock issuance, composite equity issuance, total accruals, net operating assets, momentum, gross profit-to-assets, asset growth, return-on-assets and investment-to-assets. They use a long-run sentiment index derived from principal component analysis of six sentiment measures: trading volume as measured by NYSE turnover; the dividend premium; the closed-end fund discount; the number of and first-day returns on Initial Public Offerings; and, the equity share in new issues. They measure anomaly alphas relative to the three-factor model (adjusting for market, size, book-to-market). Using monthly sentiment and stock return anomaly data as available over the period July 1965 through January 2008, they find that: Keep Reading

Stated Beliefs Versus Trading Behavior

Do individual investors actually trade on their stated beliefs? In their February 2011 paper entitled “Do Investors Put Their Money Where Their Mouth Is? Stock Market Expectations and Trading Behavior”, Christoph Merkle and Martin Weber compare quarterly risk and return expectation survey responses to actual trading data and portfolio holdings for a group of self-directed individual UK investors. Using this investor data, along with contemporaneous measures of actual FTSE All-Share Index returns and volatility during 2008 through 2010 (first survey in September 2008 and last in September 2010), they find that: Keep Reading

Factor Universality?

Studies of the U.S. stock market indicate that some factors and indicators may have predictive power for future returns. Do these findings consistently translate to other large equity markets? In the July 2010 version of their paper entitled “The Cross-Section of German Stock Returns: New Data and New Evidence”, Sabine Artmann, Philipp Finter, Alexander Kempf, Stefan Koch and Erik Theissen apply a new set of single-sorted and double-sorted factor portfolios based on market beta, size, book-to-market ratio and momentum to test for beta effect, size effect, value premium and momentum in the German equity market. In the July 2010 version of their paper entitled “The Impact of Investor Sentiment on the German Stock Market”, Philipp Finter, Alexandra Niessen-Ruenzi and Stefan Ruenzi test the predictive power of a composite sentiment measure combining consumer confidence, net equity mutual funds flow, put-call ratio, aggregate trading volume, initial public offering (IPO) returns, number of IPOs and aggregate equity-to-debt ratio of new issues. Using data for 955 non-financial German firms for which sufficient data is available during the period 1960-2006 for the factor portfolios and 1993-2006 for the sentiment measure, these studies find that: Keep Reading

Exploit Media Bias in Hedge Fund Coverage?

Does media coverage of hedge funds indicate their values as investments? In their July 2010 paper entitled “Media and Investment Management”, Gideon Ozik and Ronnie Sadka investigate the level and investment implications of media bias by applying textual analysis to titles of articles from three types of news coverage about equity hedge funds (General newspapers, Specialized investment magazines, and Corporate communications). They frame their investigation by hypothesizing three aspects of bias: reporting style, editorial selection and content. Using the Google News archive to collect approximately 67,000 news articles from about 3,600 unique media sources on a sample of 774 long/short U.S. equity hedge funds over the period 1999-–2008, they find that: Keep Reading

Sentiment from Google Insights and Return Continuation

Does investor interest in stocks as measured by Google Insights for Search predict which stocks will exhibit return continuation? In his June 2010 paper entitled “The Demand for Information”, Gordon Sims examines the effects of investor attention to stocks as defined by relative search frequency from Google Insights for Search (Stock Information Demand) to short-term stock momentum. The past return interval for momentum measurement is four weeks, augmented by a one-week delay in portfolio formation to avoid short-term reversal. Search term construction for Stock Information Demand focuses on intent to buy or sell a stock by appending “stock” or “quote” to a company’s name or ticker symbol. Using weekly returns for July 2003 through December 2009 for those S&P 500 stocks (as of July 31, 2003) with sufficient weekly Stock Information Demand data over the period 2004-2009 (214 stocks), he finds that: Keep Reading

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