Economic Indicators

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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Is expected crude oil price volatility (risk) an important economic indicator, thereby influencing stock market and individual stock returns? In their February 2014 paper entitled “Oil Risk Exposure and Expected Stock Returns”, Peter Christoffersen and Nick Pan analyze the impact of expected oil risk on the U.S. stock market and on the cross section of individual U.S. stocks. They measure expected oil risk via option-implied oil volatility based on a 30-day horizon and constructed similarly to S&P 500 Index implied volatility (VIX) . They empirically segment the available sample period into pre-financialization (1990 through 2004) and post-financialization (2005 through 2012) subperiods. Using daily and/or monthly oil options price data, U.S. stock market and individual stock returns and commonly used U.S. equity risk factors during January 1990 through December 2012, they find that: Keep Reading

Do economic indicators usefully predict government bond returns? In the January 2014 version of their paper entitled “What Drives the International Bond Risk Premia?”, Guofu Zhou and Xiaoneng Zhu examine whether OECD-issued leading economic indicators predict government bond returns at a one-month horizon. They focus on a four-country (U.S., UK, Japan and Germany) aggregate leading economic indicator (LEI4). They test whether LEI4 outperforms historical averages and individual country LEIs in predicting term premiums (relative to a one-year bond) for U.S., UK, Japanese and German government bonds with terms of two, three, four and five years. Their test methodology employs monthly inception-to-date regressions of annual change in LEI4 versus next-month bond return for an out-of-sample test period of 1990 through 2011. Using end-of-month total return data for 1-year, 2-year, 3-year, 4-year and 5-year government bonds since 1962 for the U.S., 1970 for the UK, 1980 for Japan and 1975 for GM, all through 2011, they find that: Keep Reading

Has easy access to commodity allocations via exchange-traded instruments (financialization) changed the way commodity prices interact with the economy? In his February 2014 paper entitled “Macroeconomic Determinants of Commodity Returns in Financialized Markets”, Adam Zaremba investigates relationships between commodity returns and economic conditions in pre-financialization (before 2004) and post-financialization (2004 and after) environments. He defines an increase (decrease) in the nominal U.S. Industrial Production Index as economic growth (contraction). He employs the U.S. Consumer Price Index (CPI) to measure inflation. Using monthly levels of various global and sector commodity indexes in U.S. dollars as available, the nominal U.S. Industrial Production Index and CPI during December 1970 through November 2013, he finds that: Keep Reading

What factors truly explain movements in the price of gold? In his January 2014 paper entitled “Facts and Fantasies about Gold”, Joachim Klement checks the validity of common explanations for changes in gold price. Specifically, he investigates whether gold price responds to: change in inflation expectation; change in real interest rate; financial crises; changes in currency exchange rates; change in the marginal cost of gold production; central bank gold sales and purchases; and, change in the demand for gold-linked exchange-traded funds (ETF). Using monthly data for gold price and these potentially explanatory factors as available during 1970 through 2013, he finds that: Keep Reading

Do investors reliably reallocate between equities and cash in response to changes in government monetary stance? In their July 2013 paper entitled “Asset Allocation and Monetary Policy: Evidence from the Eurozone”, Harald Hau and Sandy Lai apply regressions to examine how variations in the tightness of monetary policy (real short-term interest rates) affect investor allocations to stock and money market funds. Specifically, they examine relationships among real short-term interest rates, equity and money market fund flows, stock index returns and estimates of local institutional ownership of stocks in eight countries: Austria, Finland, France, Germany, Italy, the Netherlands, Portugal and Spain. Using quarterly data for these variables during 2003 through 2010 (32 quarters), they find that: Keep Reading

Does the U.S. stock market reliably exhibit extreme behavior on days when the Federal Open Market Committee (FOMC) of the Federal Reserve Board issues  (at mid-afternoon) its meeting minutes? Are the minutes systematically encouraging, discouraging, calming or exciting? Using release dates for these minutes and contemporaneous daily open, high, low and close levels of S&P Depository Receipts (SPY) during February 2005 through mid-July 2013 (68 release dates), plus three samples of SPY five-minute prices for 9:30-16:oo from 2005-2006 , 2007-2008 and August 2012-July 2013 (see “Intraday U.S. Stock Market Behavior” and “Recent Intraday U.S. Stock Market Behavior”), we find that: Keep Reading

A reader asked: “Is disposable income a leading indicator of the stock market?” Arguably, an increase in disposable income would lead to growth in consumption, corporate earnings and stock valuation. The Bureau of Economic Analysis releases seasonally adjusted Disposable Personal Income (DPI) monthly with a lag of about one month via Line 27 of Table 2.6, “Personal Income and Its Disposition, Monthly.” Using this series for January 1959 through May 2013 and contemporaneous monthly levels of the S&P 500 Index (through June 2013), we find that… Keep Reading

Do country economic fundamentals provide exploitable information about future changes in associated currency exchange rates? In the June 2013 version of their paper entitled “Currency Risk Premia and Macro Fundamentals”, Lukas Menkhoff, Lucio Sarno, Maik Schmeling and Andreas Schrimpf investigate the usefulness of economic fundamentals in currency trading by measuring the performance of multi-currency hedge portfolios formed by sorting on lagged economic variables across 35 countries. They take the perspective of a U.S. investor by measuring all exchange rates versus the U.S. dollar. The country economic variables they consider are: (1) interest rates; real Gross Domestic Product (GDP) growth; real money growth (from currency in circulation); and, real exchange rates. They calculate growth rates based on 20-quarter rolling averages. They form hedge portfolios from extreme fourths (quartiles) of ranked currencies, rebalanced annually at year end, and calculate returns in excess of short-term interest rates. Using quarterly currency exchange rate, short-term interest rate, real GDP, Consumer Price Index (CPI) and currency in circulation for 35 countries/currencies for out-of-sample testing from the first quarter of 1974 through the third quarter of 2010, they find that: Keep Reading

How does central bank quantitative easing (QE) affect various financial markets? In the May 2013 preliminary and incomplete version of his paper entitled “The Time Horizon of Price Responses to Quantitative Easing”, Harry Mamaysky investigates how U.S. Federal Reserve (Fed), European Central Bank (ECB) and Bank of England (BoE) QE announcements affect the prices of asset classes, including government bills and bonds, currencies, equities, equity volatilities and credit products. He focuses on how long it takes different asset classes to respond to QE announcements (events). He first decomposes the sample period into non-overlapping event windows and non-event windows ranging in duration from two trading days before to 21 trading days after QE events. He then aggregates changes in financial market proxies separately to compare event window and non-event window changes. Using dates for 20 Fed, nine ECB and 11 BoE events and contemporaneous daily values for U.S. and European bill/bond, currency, equity, equity volatility and credit indexes during March 2008 through December 2012, he finds that: Keep Reading