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.
February 23, 2015 - Economic Indicators, Fundamental Valuation, Sentiment Indicators
The Mojena Market Timing strategy (Mojena), developed and maintained by professor Richard Mojena, is a method for timing the broad U.S. stock market based on a combination of 11 monetary, fundamental, technical and sentiment indicators to predict changes in intermediate-term and long-term market trends. He adjusts the model annually to incorporate new data year by year. Professor Mojena offers a hypothetical backtest of the timing model since 1970 and a live investing test since 1990 based on the S&P 500 Index (with dividends). To test the robustness of the strategy’s performance, we consider a sample period commencing with availability of SPDR S&P 500 (SPY) as a conveniently investable proxy for the S&P 500 Index. As benchmarks, we consider both buying and holding SPY (Buy-and-Hold) and trading SPY with crash protection based on the 10-month simple moving average of the S&P 500 Index (SMA10). Using the trade dates from the Mojena Market Timing live test, daily dividend-adjusted closes for SPY and daily yields for 13-week Treasury bills (T-bills) over the period 1/29/93 through January 2015 (22 years), we find that: Keep Reading
February 19, 2015 - Sentiment Indicators
A reader suggested looking at Rydex asset ratios as stock market sentiment indicators. The reasoning for these indicators is that a high (low) ratio of assets in bullish funds to assets in bearish funds indicates an overbought (oversold) market. Are these indicators useful? The most timing-intensive traders arguably use leveraged funds, suggesting that a bull-bear asset ratio for such funds may be especially informative and timely. We therefore use the ratio of daily closing asset level for the S&P 500 2x Strategy – H Class (RYTNX) mutual fund to daily closing asset level of the Inverse S&P 500 2x Strategy – H Class (RYTPX) mutual fund (Rydex 2X/-2X). Using daily asset levels for these funds from inception on 5/19/00 through January 2015, along with contemporaneous daily opens of the S&P 500 index (since fund assets are available only after the close), we find that: Keep Reading
January 12, 2015 - Sentiment Indicators
Does interest in, or concern about, financial markets as expressed in Internet searches predict stock market behavior? In the December 2014 revision of their paper entitled “Can We Predict the Financial Markets Based on Google’s Search Queries?”, Marcelo Perlin, Joao Caldeira, Andre Santos and Martin Pontuschka investigate whether changes in Google search frequency for finance-related words predict changes in stock market index level, volatility and trading volume in four English speaking countries (U.S., UK, Australia and Canada). They select 15 relevant search words/terms by measuring the frequency of appearance in four finance textbooks of a large number of candidates from an online financial dictionary. They then use Google Trends to construct time series of relative search frequency (on a scale of 0 to 100) for the selected words/terms in each of the four countries and relate these series to respective country stock market behaviors. Finally, they test a timing strategy that is each week long or short an index depending on level of local Google Trends search activity. Using the search activity time series and daily levels and constituent trading volumes for major stock market indexes in the four countries (aggregated weekly) during January 2005 through December 2013, they find that: Keep Reading
December 11, 2014 - Sentiment Indicators
Does margin debt serve as an intermediate-term stock market sentiment indicator based on either momentum (with an increase/decrease in margin debt signaling a continuing stock market advance/decline) or reversion (with high/low margin debt signaling a pending reversal)? To investigate, we relate the behavior of NYSE end-of-month margin debt, published with a delay of about a month, with the monthly behavior of the the stock market (S&P 500 Index). Using end-of-month data for the period January 1959 through October 2014 (670 months), we find that: Keep Reading
November 14, 2014 - Sentiment Indicators
The business media and expert commentators sometimes cite the monthly University of Michigan Consumer Sentiment Index as an indicator of U.S. economic and stock market health, generally interpreting a jump (drop) in sentiment as good (bad) for future consumption and stocks. The release schedule for this indicator is mid-month for a preliminary reading on the current month and end-of-month for a final reading. Is this indicator in fact predictive of U.S. stock market behavior in subsequent months? Using monthly final Consumer Sentiment Index data from the Federal Reserve Bank of St. Louis, augmented by more recent data from Bloomberg and contemporaneous monthly levels of the S&P 500 Index during January 1978 through October 2014 (442 monthly sentiment readings), we find that: Keep Reading
November 12, 2014 - Investing Expertise, Sentiment Indicators
Do expected investment returns as predicted by experts in surveys reliably predict actual future returns? In the October 2014 version of their preliminary paper entitled “Survey Expectations of Returns and Asset Pricing Puzzles”, Ralph Koijen, Maik Schmeling and Evert Vrugt compare survey-based expected returns to actual future returns for three major asset classes encompassing: 13 country equity market indexes; 19 currencies (versus the U.S. dollar); and, 10-year government bonds in 10 countries. They measure actual asset returns in U.S. dollars based on futures prices for equities and bonds (actual or synthetic) and forward returns for currencies. Survey-based expected returns derive from the quarterly World Economic Survey of experts, which solicits six-month expectations (“higher” or “about the same” or “lower”) for local equity prices, currency value versus the U.S. dollar and long-term government bond yield. The currency survey series commences the first quarter of 1989, while the equity and bond series commence the second quarter of 1998. They test the accuracy of survey expectations in two ways:
- Cross-sectional hedge portfolios that are each month long (short) the rank-weighted assets with the highest (lowest) survey expectations.
- Time series portfolios that are each month long (short) each asset depending on whether respective survey expectations indicate a positive (negative) return.
Analyses include testing of different lags between survey month and actual future return measurement, noting that a reliably executable strategy requires a lag of at least three months. Using quarterly survey response data and monthly futures/forward returns for the specified assets as available through September 2012, they find that: Keep Reading
August 14, 2014 - Sentiment Indicators, Volatility Effects
Experts and pundits sometimes cite a high Chicago Board Options Exchange (CBOE) Volatility Index (VIX), the options-implied volatility of the S&P 500 Index, as contrarian indication of investor panic and therefore of pending U.S. stock market strength. Conversely, they cite a low VIX as indication of complacency and pending market weakness. However, a more nuanced conventional wisdom considers both very high VIX and very low VIX as favorable for future stock market returns. Does evidence support belief in either version of conventional wisdom? To check, we relate the level of VIX to S&P 500 Index returns over the next 5, 10, 21, 63 and 126 trading days. Using daily and monthly closes for VIX and for the S&P 500 Index over the period January 1990 through July 2014 (296 months), we find that: Keep Reading
July 17, 2014 - Sentiment Indicators, Technical Trading
Do hedge fund managers who use technical analysis beat those who do not? In their May 2014 paper entitled “Sentiment and the Effectiveness of Technical Analysis: Evidence from the Hedge Fund Industry”, David Smith, Na Wang, Ying Wang and Edward Zychowicz examine the relative performance of users and non-users of technical analysis among hedge fund managers in different sentiment environments. They hypothesize that short-selling constraints prevent market correction of mispricings when sentiment is high (overly optimistic), but not when sentiment is low (overly pessimistic). Discovery of mispricings via technical analysis may therefore be more effective when sentiment is high. To test their hypothesis, they compare the performance of hedge funds that report using technical analysis to that of hedge funds that do not, with focus on the state of market sentiment. They define the market sentiment state as high or low depending on whether the monthly Baker-Wurgler market sentiment measure is above or below its full-sample median. Using end-of-period status on use/non-use of technical analysis and monthly returns for 3,290 live and 1,845 dead funds from the Lipper TASS hedge fund database and monthly market sentiment data during January 1994 through December 2010, they find that: Keep Reading
June 25, 2014 - Sentiment Indicators
Is the conventional wisdom that aggregate retail investor sentiment is a contrary indicator of future stock market returns accurate? To investigate, we examine the sentiment expressed by members of the American Association of Individual Investors (AAII) via a weekly survey of members. This survey “measures the percentage of individual investors who are bullish, bearish, and neutral on the stock market for the next six months; individuals are polled from the ranks of the AAII membership on a weekly basis. Only one vote per member is accepted in each weekly voting period.” Survey results are apparently available the market day after the polling period. We define aggregate (net) investor sentiment as percent bullish minus percent bearish. Using outputs of the weekly AAII surveys and prior-day closes of the S&P 500 Index from July 1987 through May 2014 (1,400 surveys and almost 55 independent 6-month forecast intervals), we find that: Keep Reading
May 15, 2014 - Fundamental Valuation, Sentiment Indicators
Research (see “Asset Growth Rate as a Return Indicator” and “Asset Growth a Bad Sign for Stocks Everywhere?”) indicates that stocks of firms with high asset growth rates tend subsequently to underperform the market. Does this finding translate to the overall stock market? In the April 2014 version of his paper entitled “Asset Growth and Stock Market Returns: a Time-Series Analysis”, Quan Wen examines whether the asset growth anomaly observed at the firm level applies in aggregate to the U.S. stock market. He also investigates whether any aggregate effect is predominantly behavioral or risk-based. He estimates aggregate growth rate quarterly as the market capitalization-weighted sum of firm-level percentage changes in book value of total assets. To ensure all asset data is known to investors, he relates asset growth rate to returns two quarters later. Using quarterly U.S. stock market excess returns (relative to the risk-free rate), asset growth rates for listed U.S. firms that employ calendar year accounting, analyst forecasts/revisions, stock returns around earnings announcements, and data required for comparison of asset growth with other U.S. stock market indicators during 1972 through 2011, he finds that: Keep Reading