We develop a new index of economic policy uncertainty (EPU) based on newspaper coverage frequency Several types of evidence – including human readings of 12,000 newspaper articles – indicate that our index proxies for movements in policy-related economic uncertainty Our US index spikes near tight presidential elections, Gulf Wars I and II, the 9/11 attacks, the failure of Lehman Brothers, the 2011 debt-ceiling dispute and other major battles over fiscal policy Using firm-level data, we find that policy uncertainty raises stock price volatility and reduces investment and employment in policy-sensitive sectors like defense, healthcare, and infrastructure construction At the macro level, policy uncertainty innovations foreshadow declines in investment, output, and employment in the United States and, in a panel VAR setting, for 12 major economies Extending our US index back to 1900, EPU rose dramatically in the 1930s (from late 1931) and has drifted upwards since the 1960s

/pdf/measuring-economic-policy-uncertainty-4nrg3ei76f.pdf

Measuring Economic Policy Uncertainty

https://www.nber.org/system/files/working_papers/w17464/w17464.pdf

Political Uncertainty and Risk Premia

Many commentators argue that uncertainty about tax, spending, monetary and regulatory policy slowed the recovery from the 2007-2009 recession. To investigate this we develop a new index of economic policy uncertainty (EPU), built on three components: the frequency of newspaper references to economic policy uncertainty, the number of federal tax code provisions set to expire, and the extent of forecaster disagreement over future inflation and government purchases. This EPU index spikes near consequential presidential elections and major events such as the Gulf wars and the 9/11 attack. It also rises steeply from 2008 onward. We then evaluate our EPU index, first on a sample of 3,500 human audited news articles, and second against other measures of policy uncertainty, with these suggesting our EPU index is a good proxy for actual economic policy uncertainty. Drilling down into our index we find that the post-2008 increase was driven mainly by tax, spending and healthcare policy uncertainty. Finally, VAR estimates show that an innovation in policy uncertainty equal to the increase from 2006 to 2011 foreshadows declines of up to 2.3% in GDP and 2.3 million in employment.

/pdf/measuring-economic-policy-uncertainty-2kvq2y0fgm.pdf

The Conditional CAPM Does Not Explain Asset-Pricing Anomalies

Asset returns and inflation

We study the risk dynamics of the betting-against-beta anomaly. The strategy shows strong and predictable time variation in risk and no risk-return trade-off. A risk-managed strategy exploiting this achieves an annualized Sharpe ratio of 1.28 with a very high information ratio of 0.94 with respect to the original strategy. Similar strategies for the market, size, value, profitability, and investment factors achieve a much smaller information ratio of 0.15 on average. The large economic benefits of risk-scaling are similar to those of momentum and set these two anomalies apart from other equity factors. Decomposing risk into a market and a specific component we find the specific component drives our results.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID3628096_code589595.pdf?abstractid=2876450&mirid=1

Managing the Risk of the Beta Anomaly

We document that Bitcoin returns, while unpredictable by macroeconomic variables, are predictable by 1to 20-week moving averages (MAs) of daily prices, both inand out-of-sample. Trading strategies based on MAs generate substantial alpha, utility and Sharpe ratios gains, and significantly reduce the severity of drawdowns relative to a buyand-hold position in Bitcoin, which already has a Sharpe ratio of 1.8. We explain these facts with a novel equilibrium model that demonstrates, with uncertainty about growth in fundamentals, rational learning by investors with different priors yields predictability of returns by MAs. JEL classification: G11, G12, G14

Bitcoin: Predictability and Profitability via Technical Analysis

What predicts returns on assets with "hard-to-value" fundamentals, such as Bitcoin and stocks in new industries? We propose an equilibrium model that shows how rational learning enables return predictability through technical analysis. We document that ratios of prices to their moving averages forecast daily Bitcoin returns in- and out-of sample. Trading strategies based on these ratios generate an economically significant alpha and Sharpe ratio gains relative to a buy-and-hold position. Similar results hold for small-cap, young-firm, and low-analyst-coverage stocks as well as NASDAQ stocks during the dotcom era.

Learning and Predictability via Technical Analysis: Evidence from Bitcoin and Stocks with Hard-to-Value Fundamentals

Asset pricing theory predicts a positive cross‐sectional relation between expected profitability and expected returns. However, empirical studies typically use lagged ex post profitability as a proxy for expected profitability. In this article, we use out‐of‐sample combination forecasts to estimate expected industry‐level operating profit, gross profit, operating cash flow, and net income. We then construct real‐time industry‐rotation strategies based on high and low expected profitability. For each measure except gross profit, these predicted‐profitability strategies earn significant alpha net of transaction costs and outperform strategies based on ex post profitability.

Expected versus Ex Post Profitability in the Cross‐Section of Industry Returns

I propose an asset pricing model with the market return and a mimicking portfolio for monetary policy shocks measured on days of FOMC announcements. This economically motivated two-factor model prices portfolios formed on size, value, momentum, investment, and operating profitability with an R2 of 80% and an average annual pricing error of 0.96%-performing as well as the standard four- and five-factor models designed to price these assets. These results are consistent with intertemporal asset pricing theory and recent evidence that monetary policy shocks have a large impact on asset prices via an impact on expected future aggregate returns.

/pdf/monetary-policy-surprises-investment-opportunities-and-asset-2i3kd9id0p.pdf

Andrew L. Detzel

Papers

Managing the Risk of the Beta Anomaly

Bitcoin: Predictability and Profitability via Technical Analysis

Learning and Predictability via Technical Analysis: Evidence from Bitcoin and Stocks with Hard-to-Value Fundamentals

Expected versus Ex Post Profitability in the Cross‐Section of Industry Returns

Monetary Policy Surprises, Investment Opportunities, and Asset Prices