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Economic Indicators

The U.S. economy is a very complex system, with indicators therefore ambiguous and difficult to interpret. To what degree do macroeconomics and the stock market go hand-in-hand, if at all? Do investors/traders: (1) react to economic readings; (2) anticipate them; or, (3) just muddle along, mostly fooled by randomness? These blog entries address relationships between economic indicators and the stock market.

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Mojena Market Timing Model

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 many 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. 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 inception of SPDR S&P 500 (SPY) as a liquid, low-cost 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) from the end of January 1993 through August 2018 (over 25 years), we find that: Keep Reading

Cass Freight Index a Stock Market Return Predictor?

The monthly Cass Freight Index is a “measure of North American freight volumes and expenditures. …Data within the Index includes all domestic freight modes and is derived from $25 billion in freight transactions processed by Cass annually on behalf of its client base of hundreds of large shippers. These companies represent a broad sampling of industries including consumer packaged goods, food, automotive, chemical, OEM, retail and heavy equipment. …Volumes represent the month in which transactions are processed by Cass, not necessarily the month when the corresponding shipments took place. The January 1990 base point is 1.00. …Each month’s volumes are adjusted to provide an average 21-day work month. Adjustments also are made to compensate for business additions/deletions to the volume figures.” Cass typically publishes the index level for a month by the middle of the following month. Does this index usefully anticipate economic trend and thereby U.S. stock market returns? To investigate, we relate index changes to SPDR S&P 500 (SPY) returns. Using monthly Cass Freight Index levels and monthly/daily dividend-adjusted SPY returns during January 1999 (limited by the freight index) through mid-August 2018, we find that: Keep Reading

Asset Class ETF Interactions with the Yuan

How do different asset classes interact with the Chinese yuan-U.S. dollar exchange rate? To investigate, we consider relationships between WisdomTree Chinese Yuan Strategy (CYB) and the following exchange-traded fund (ETF) asset class proxies used in “Simple Asset Class ETF Momentum Strategy” (SACEMS) at a monthly measurement frequency:

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 2000 Index (IWM)
SPDR S&P 500 (SPY)
iShares Barclays 20+ Year Treasury Bond (TLT)
Vanguard REIT ETF (VNQ)

Using monthly dividend-adjusted closing prices for CYB and the asset class proxies during May 2008 (when all ETFs are first available, limited by CYB) through July 2018 (123 months), we find that: Keep Reading

Asset Class ETF Interactions with the Yen

How do different asset classes interact with the Japanese yen-U.S. dollar exchange rate? To investigate, we consider relationships between Invesco CurrencyShares Japanese Yen (FXY) and the following exchange-traded fund (ETF) asset class proxies used in “Simple Asset Class ETF Momentum Strategy” (SACEMS) at a monthly measurement frequency:

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 2000 Index (IWM)
SPDR S&P 500 (SPY)
iShares Barclays 20+ Year Treasury Bond (TLT)
Vanguard REIT ETF (VNQ)

Using monthly dividend-adjusted closing prices for FXY and the asset class proxies during February 2007 (when all ETFs are first available, limited by FXY) through July 2018 (123 months), we find that: Keep Reading

Asset Class ETF Interactions with the Euro

How do different asset classes interact with euro-U.S. dollar exchange rate ? To investigate, we consider relationships between Invesco CurrencyShares Euro Currency (FXE) and the following exchange-traded fund (ETF) asset class proxies used in “Simple Asset Class ETF Momentum Strategy” (SACEMS) at a monthly measurement frequency:

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 2000 Index (IWM)
SPDR S&P 500 (SPY)
iShares Barclays 20+ Year Treasury Bond (TLT)
Vanguard REIT ETF (VNQ)

Using monthly dividend-adjusted closing prices for FXE and the asset class proxies during February 2006 (when all ETFs are first available, limited by DBC) through July 2018 (150 months), we find that: Keep Reading

Asset Class ETF Interactions with the U.S. Dollar

How do different asset classes interact with aggregate U.S. dollar valuation? To investigate, we consider relationships between Powershares DB US Dollar Index Bullish Fund (UUP) and the following exchange-traded fund (ETF) asset class proxies used in “Simple Asset Class ETF Momentum Strategy” (SACEMS) at a monthly measurement frequency:

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 2000 Index (IWM)
SPDR S&P 500 (SPY)
iShares Barclays 20+ Year Treasury Bond (TLT)
Vanguard REIT ETF (VNQ)

Using monthly dividend-adjusted closing prices for UUP and the asset class proxies during March 2007 (when all ETFs are first available, limited by UUP) through July 2018 (137 months), we find that: Keep Reading

PPI and the Stock Market

Inflation at the producer level (derived from the Producer Price Index – PPI) is arguably an advance indicator for inflation downstream at the consumer level (derived from the Consumer Price Index – CPI). Do investors therefore reliably react to changes in PPI as an indicator of the future wealth discount rate? In other words, is a high (low) producer-level inflation rate bad (good) for the stock market? Using monthly, non-seasonally adjusted PPI from the Bureau of Labor Statistics (BLS) and contemporaneous S&P 500 Index levels during January 1950 through July 2018 (823 months), we find that: Keep Reading

Federal Reserve Treasuries Holdings and Asset Returns

Is the level, or changes in the level, of Federal Reserve (Fed) holdings of U.S. Treasuries (measured weekly as of Wednesday) an indicator of future stock market and/or Treasuries returns? To investigate, we take dividend-adjusted SPDR S&P 500 (SPY) and iShares Barclays 20+ Year Treasury Bond (TLT) as tradable proxies for the U.S. stock and Treasuries markets, respectively. Using weekly Fed holdings of Treasuries, SPY and TLT during mid-December 2002 through early August 2018, we find that: Keep Reading

Economic Policy Uncertainty and the Stock Market

Does quantified uncertainty in government economic policy reliably predict stock market returns? To investigate, we consider the U.S. Economic Policy Uncertainty (EPU) Index, created by Scott Baker, Nicholas Bloom and Steven Davis and constructed from three components: (1) coverage of policy-related economic uncertainty by prominent newspapers: (2) the number of temporary federal tax code provisions set to expire in future years; and, (3) the level of disagreement in one-year forecasts among participants in the Federal Reserve Bank of Philadelphia’s Survey of Professional Forecasters for both (a) the consumer price index (CPI) and (b) purchasing of goods and services by federal, state and local governments. They first normalize each component by its own standard deviation prior to January 2012. They then compute a weighted average of components, assigning a weight of one half to news coverage and one sixth each to tax code uncertainty, CPI forecast disagreement and government purchasing forecast disagreement. They update the EPU index monthly with a delay of about one month, including revisions to recent months. Using monthly levels of the EPU Index and the S&P 500 Index during January 1985 through June 2018, we find that: Keep Reading

Gold Return vs. Change in M2

A subscriber requested testing of the relationship between U.S. M2 Money Stock and gold, offered in one form via “Why Gold May Be Looking Cheap”: “[O]ne measure I’ve found useful is the ratio of the price of gold to the U.S. money supply, measured by M2, which includes cash as well as things like money market funds, savings deposits and the like. The logic is that over the long term the price of gold should move with the change in the supply of money… That equilibrium level is also relevant for future price action. When the ratio is low, defined as 25% below equilibrium, the medium 12-month return has been over 12%. Conversely, when the ratio is high, defined as 25% above equilibrium, the 12-month median return has been -6%. …This measure can be refined further. [G]old tends to trade at a higher ratio to M2 when inflation is elevated.” Because it defines specific valuation thresholds, this approach is susceptible to data snooping bias in threshold selection. We consider an alternative setup that relates monthly change in M2 to monthly gold return. We also consider the effect of inflation on this relationship. Using monthly seasonally adjusted M2 and end-of-month London gold price fix during January 1976 (to ensure a free U.S. gold market) through June 2018 (510 months), we find that: Keep Reading

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