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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When Economists Disagree…

Do some stocks react more strongly to economic uncertainty than others? In the March 2014 draft of their paper entitled “Cross-Sectional Dispersion in Economic Forecasts and Expected Stock Returns”, Turan Bali, Stephen Brown and Yi Tang examine the role of economic uncertainty in the pricing of individual stocks. They measure economic uncertainty as disagreement (dispersion) in quarterly economic forecasts from the Survey of Professional Forecasters, focusing on forecasts for the level of and growth in U.S. real Gross Domestic Product (GDP). They also consider quarterly forecasts for nominal GDP level and growth, GDP price index level and growth (inflation rate) and unemployment rate. They then use 20-quarter (or 60-month) rolling historical regressions to estimate the time-varying dependence (beta) of returns on economic uncertainty for each NYSE, AMEX and NASDAQ stock. Finally, they rank these stocks each month into tenths (deciles) based on their economic uncertainty betas and compare average future returns of the equally weighted deciles. Using quarterly economic forecast data and monthly returns for a broad sample of U.S. common stocks from the fourth quarter of 1968 (supporting tests of predictive power commencing October 1973) through 2012, they find that:

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Testing the Equity Mutual Fund Liquidity Ratio

A reader requested an evaluation of the Fosback Index and its Ned Davis variant. The creators of these indicators argue that a high (low) ratio of cash equivalents to assets among equity mutual funds indicates strong (weak) potential demand for stocks. The Investment Company Institute (ICI) surveys mutual fund managers monthly to measure the aggregate mutual fund liquidity ratio. However, only the most recent survey results and past year-end values of the liquidity ratio are publicly available. Monthly values are available with a lag of about one month. Norman Fosback adjusts the raw liquidity ratio based on current interest rates, reasoning that mutual fund managers have more (less) incentive to hold cash when interest rates are high (low). We adjust the raw liquidity ratio from ICI for interest rates by debiting the contemporaneous 13-week U.S. Treasury bill (T-bill) yieldUsing January and February closes of the S&P 500 index and year-end values of the equity mutual fund liquidity ratio and T-bill yield during December 1984 through February 2014 ( about 30 years), we find that: Keep Reading

Google Trends Data vs. Past Returns

Are Google Trends data an independently useful tool in predicting stock returns? In their March 2014 paper entitled “Do Google Trend Data Contain More Predictability than Price Returns?”, Damien Challet and Ahmed Bel Hadj Ayed apply non-linear machine learning methods to measure whether Google Trends data outperform past returns in predicting future stock returns. They focus on avoiding bias derived from choice of keywords (choosing words with obvious retrospective, but dubious prospective, import) and test strategy parameter optimization. Since Google Trends data granularity is weekly, they employ a six-month calibration interval to predict weekly stock returns. They apply a 0.2% trading friction for all backtested trades. Using weekly returns and Google Trends data for stock tickers and firm names plus other simple, non-overfitted words for the S&P 100 stocks as available through late April 2013, they find that: Keep Reading

Aggregate Short Interest as a Stock Market Indicator

Does aggregate short interest serve as an intermediate-term stock market indicator based on either momentum (shorting begets shorting) or reversion (covering follows shorting)? To investigate, we relate the behavior of NYSE aggregate short interest with that of SPDR S&P 500 (SPY). Prior to September 2007, NYSE aggregate short interest is monthly (as of the middle of each month). Since September 2007, measurements are approximately biweekly (as of the middle and end of each months). There is a delay of about two weeks between short interest measurement and release, and new releases sometimes revise prior releases. Using monthly/biweekly short interest data culled from NYSE news releases and contemporaneous dividend-adjusted SPY price for the period January 2002 through February 2014 (69 monthly followed by 154 biweekly observations), we find that: Keep Reading

Index Option Strike Price Volume Dispersion as a Return Predictor

Is the level of uncertainty among equity investors, as measured by the dispersion of S&P 500 Index option volume across strike prices, a useful predictor of stock market direction? In their January 2014 paper entitled “Stock Market Ambiguity and the Equity Premium”, Panayiotis Andreou, Anastasios Kagkadis, Paulo Maio and Dennis Philip investigate the ability of this dispersion in investor speculations (designated stock market “ambiguity”) to predict stock market returns. They argue that stock market ambiguity is a direct, forward-looking and readily computed indicator. They compare ambiguity to other commonly cited stock market predictors, with focus on the variance risk premium VRP). Using trading volumes for S&P 500 Index call and put options with maturities of 10 to 360 calendar days on the last trading day of each month, monthly data needed to calculate competing indicators and monthly returns for the broad U.S. stock market during 1996 through 2012, they find that: Keep Reading

Blogger Sentiment Analysis

Are prominent stock market bloggers in aggregate able to predict the market’s direction? The Ticker Sense Blogger Sentiment Poll “is a survey of the web’s most prominent investment bloggers, asking ‘What is your outlook on the U.S. stock market for the next 30 days?’” (bullish, bearish or neutral) on a weekly basis. The site currently lists 31 participating bloggers. Participation has varied over time. Because Ticker Sense collects data weekly, we look at weekly measurements and changes in weekly measurements. Because the poll question asks for a 30-day outlook, we test the forecasts against stock market behavior four weeks into the future. Because polling takes place Thursday-Sunday, we use the coincident Friday close to represent the state of the stock market for each poll (except for the poll of 10/13/08, which took place on Monday and therefore relates to the Monday close). We use [% Bullish] minus [% Bearish] as the net sentiment measure for each poll. Using poll results from inception on 7/10/06 through 12/30/13 (381 polls) and contemporaneous weekly closes of the S&P 500 Index as representative of the broad stock market, we find that: Keep Reading

You’re Not That Fast?

How fast must attentive investors be to exploit the information in new releases of major sentiment and economic indicators? In their November 2013 paper entitled “Early Peek Advantage?”, Grace Xing Hu, Jun Pan, and Jiang Wang measure the impacts of Michigan Consumer Sentiment Index releases on E-mini S&P 500 futures volume and price with and without a small group of fee-paying, high-speed traders with early access. Early means two seconds before the 9:55:00 public release during January 2008 through June 2013 (after which the provider, Thomson Reuters, discontinues early access). To assess release impacts, they sort the sentiment releases into three subsamples according to whether the initial market response is positive, negative or neutral. Using tick-by-tick E-mini S&P 500 futures volume and price data for 9:45:00 through 10:15:00 during January 2008 through October 2013, along with semi-monthly sentiment release dates, they find that: Keep Reading

Exploiting Stock Index Correlation

Both “Stock Return Correlations and Retail Trader Herding” and “Stock Return Correlations and Equity Market Stress” imply that extremely high correlations among stock returns accompany severe market declines and may signal market bottoms. Is there some simple way to exploit this implication? Keying on the former item, we investigate the correlation of returns between a large-stock index (the S&P 500 Index) and a small-stock index (the Russell 2000 Index) as a trading signal. We hypothesize that, when this correlation is very low (high), equity markets are near a top (bottom). Using weekly returns for the S&P 500 Index since September 1987, the Russell 2000 Index since inception in September 1987, SPDR S&P 500 (SPY) since inception in January 1993 and ProShares Short S&P 500 (SH) since inception in June 2006, along with the weekly yield on 13-week Treasury bills (T-bill) as the return on cash, all through November 2013, we find that: Keep Reading

Do Investors Care About “the Way Things Are Going”?

Are broad measures of public sociopolitical sentiment relevant to investor behavior? Do they have predictive power for stock returns as potential indicators of exuberance and fear? To investigate, we relate both U.S. stock market return and 12-month trailing S&P 500 price-earnings ratio (market P/E) to the percentage of respondents saying “yes” to the recurring Gallup polling question: “In general, are you satisfied or dissatisfied with the way things are going in the United States at this time?” Since individual polls span several days, we use S&P 500 Index levels for the first or second day of the polling interval. To calculate market P/E, we use current S&P 500 Index level and the most recent quarterly aggregate operating earnings value that is at least one month old. Using Gallup polling resultsS&P 500 Index levels and 12-month trailing S&P 500 operating earnings as available during February 1979 through October 2013 (294 polls, often unevenly spaced), we find that: Keep Reading

Returns for Masters of Knowledge Management?

The “Most Admired Knowledge Enterprise” (MAKE) awards, based on opinions gathered from experts using the Delphi method (three or four rounds of the experts anonymously exchanging views), recognizes exemplary organizational knowledge management. Does the market consider this award, directly or indirectly, in valuing publicly traded MAKE award winners? In their September 2013 paper entitled “Capital Markets Valuation and Accounting Performance of Most Admired Knowledge Enterprise (MAKE) Award Winners”, Mark DeFond, Yaniv Konchitchki, Jeff McMullin and Daniel O’Leary examine stock market returns and future operating performance for MAKE award recipients. They consider both short-term returns during the five-day interval around public announcements of MAKE awards and intermediate-term returns after announcements. Using stock and accounting data and analyst earnings forecasts for all U.S. publicly traded MAKE award winners as available during 2001 through 2008 (247 MAKE awards), they find that: Keep Reading

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