Economic Indicators

Stocks and bonds are two of the most frequently considered asset classes in asset allocation strategies. How stable is the correlation between stock returns and bond returns? In their December 2008 paper entitled “The Dynamic Correlation between Stock and Bond Returns”, Thomas Chiang and Jiandong Li apply rolling regressions to analyze variations in the correlation between stock market returns and bond market returns. Using daily returns for the Vanguard Total Bond Market Index Fund (VBMFX) and the Vanguard Total Stock Market Index Fund (VTSMX) as proxies for their respective markets over the period 6/20/96 through 6/30/08, along with contemporaneous U.S. economic data, they conclude that: Keep Reading

In the absence of solid theory, can an adaptive empirical model successfully infer which economic indicators are driving near-term equity investor/trader behavior? In other words, can a model that continually reselects the current best economic indicators predict stock returns? In her October 2008 paper entitled “Equity Premium Predictions with Adaptive Macro Indices”, Jennie Bai uses time-varying combinations of a large number of economic variables to predict excess (relative to one-month Treasury bills) stock returns. Specifically, she iteratively selects the best macro index of economic indicators according to empirical measurement of the out-of-sample (training interval) power of competing indexes to predict stock returns. Using monthly datasets for 100 economic indicators, one-month Treasury bill (T-bill) yields and returns for a broad value-weighted stock index spanning January 1960 through November 2006, she concludes that: Keep Reading

Is there an effective way to enhance allocation of investment funds across asset classes according to economic conditions, from either a risk or a return perspective? In their January 2009 paper entitled “Dynamic Strategic Asset Allocation: Risk and Return Across Economic Regimes”, Pim Van Vliet and David Blitz present constant-risk and return-maximizing asset allocation strategies driven by four economic states: expansion, peak, recession and recovery (see the first chart below). Using data for four U.S. economic indicators (credit spread, earnings yield, Institute for Supply Management manufacturing index and unemployment rate) and returns for eight mostly U.S. asset classes (equities, bonds, cash, small-capitalization stocks, value stocks, growth stocks, credits and commodities) over the period 1948 through 2007 (60 years), they conclude that: Keep Reading

A reader requested: “Would you add Tom Madell’s Mutual Fund Research Newsletter to Guru Grades?” The most consistent thread in the Mutual Fund Research Newsletter archive for 2000-2008 [no longer publicly available] is the quarterly asset class allocation (stocks, bonds, cash) recommendation. Variation in recommended allocations across nine years supports a rough assessment of general market timing value. This assessment is related to, but more quantitative than, the narrative forecast reviews for other experts at Guru Grades. Because of this difference, we are not including Tom Madell in the list of experts at Guru Grades. Using the 36 Mutual Fund Research Newsletter quarterly asset class allocation recommendations, along with contemporaneous quarterly returns for proxy assets, we conclude that: Keep Reading

Which better explains the relationship between the inflation rate and stock market returns: the inflation illusion hypothesis, or a two-regime hypothesis? The former proposes that the typical investor irrationally raises (lowers) the required rate of return from equities (discount rate) as the inflation rate rises (falls), thereby undervaluing (overvaluing) stocks. The latter proposes that aggregate demand (supply) shocks drive a positive (negative) relationship between the inflation rate and stock returns. In his January 2009 paper entitled “Stock Returns and Inflation Revisited”, Bong-Soo Lee re-examines these hypotheses using long run U.S. data. Using stock return and inflation rate data spanning 1927-2007, he concludes that: Keep Reading

Do long-term stock market timing models work? If so, which type works best? In their October 2005 paper entitled Timing is Everything: A Comparison and Evaluation of Market Timing Strategies, Chris Brooks, Apostolos Katsaris and Gita Persand investigate the profitability of several timing models over a very long sample of S&P 500 index returns. Specifically, they test the timing power of: (1) the ratio of the long-term Treasury bond yield to the stock dividend yield; (2) the spreads between the stock earnings yield and the yields on either the three-month Treasury bills (T-bills) or the 10-year Treasury notes (T-notes); (3) a model for predicting when bear markets will occur based on the spread between T-note and T-bill yields; and, (4) an approach for predicting market turning points based on speculative bubbles. Timing signals trigger binary switching between stocks and T-bills. Using monthly stock return and model parameter data from January 1871-December 1926 for initial model calibration and January 1927-August 2003 for model testing and recalibration (a total of 1,592 months), they find that: Keep Reading

Does the value premium vary systematically with the state of the economy? More specifically, do value and growth stocks respond differently to negative macroeconomic shocks? In their September 2008 paper entitled “Value versus Growth: Time-Varying Expected Stock Returns”, Huseyin Gulen, Yuhang Xing and Lu Zhang investigate the relationship between economic conditions (recession or expansion) and the value premium. Using monthly returns for a broad sample of stocks over the period 1954-2007 (648 months), along with contemporaneous firm fundamentals and macroeconomic data, they conclude that: Keep Reading

Which of those morning economic data releases really move markets? In their August 2008 paper entitled “How Economic News Moves Markets”, Leonardo Bartolini, Linda Goldberg and Adam Sacarny explore how surprises in economic data releases affect asset prices in the stock, bond and currency exchange markets. They consider the following releases: (1) nonfarm payrolls and unemployment rate; (2) consumer price index (CPI) and CPI excluding food and energy; (3) personal consumption expenditures excluding food and energy, personal income and personal spending;(4), gross domestic product (GDP) advance; (5) Institute of Supply Management (ISM) manufacturing: (6) housing starts; (7), Conference Board Consumer Confidence Index; (8) University of Michigan Survey of Consumers; and, (9) retail sales less autos. They quantify “surprise” as the difference between the announced value for an indicator and value previously expected by key market participants. Using economic data releases and contemporaneous intraday asset and futures prices for the period January 1998 to July 2007, they conclude that: Keep Reading

How does the rate of bank interventions by the Federal Deposit Insurance Corporation (FDIC) relate to U.S. stock returns? To check, we compare the percentage of banks with FDIC closing and assistance transactions with the annual change in the Dow Jones Industrial Average (DJIA). We exclude savings and loan institutions from the sample for comparability of long-run data. Using FDIC bank population and intervention data and contemporaneous DJIA data over the period 1934-2007 (74 years), we find that: Keep Reading

Do any indicators systematically predict stock returns across global equity markets? In his June 2008 paper entitled “Predicting Global Stock Returns”, Erik Hjalmarsson tests the power of four common indicators (dividend-price ratio, earnings-price ratio, short interest rate and term spread) to predict stock returns for markets in 24 developed and 16 emerging economies. Using a very large dataset encompassing 20,000 monthly observations of returns and indicators ranging as far back as 1836, he concludes that: Keep Reading