Search Results
Journal Article
The equity risk premium: a review of models
The authors estimate the equity risk premium (ERP)?the expected return on stocks in excess of the risk-free rate?by combining information from twenty models for the period 1960-2013. They begin their analysis by categorizing the models into five classes: trailing historical mean, dividend discount, cross-sectional estimation, regression analysis using valuation ratios or macroeconomic variables, and surveys. They find that an optimal weighted average of all models places the one-year-ahead ERP in June 2012 at 12.2 percent, close to levels reached in the mid- and late 1970s, when the ERP was ...
Working Paper
On the Origins of the Multinational Premium
How do foreign direct investment (FDI) dynamics relate to the risk premium of a firm? To answer this question, we compare the stock returns of US firms with different FDI and mergers and acquisitions (M&A) exposure to study the evolution of stock returns as firms expand into foreign markets. We document three empirical regularities. First, there are cross-sectional risk premia associated with both multinational activity and mergers and acquisitions. Second, firm-level stock returns decline when a firm undertakes M&A activity and with merger deepening. Third, future multinational acquirers ...
Discussion Paper
Changing Risk-Return Profiles
Are stock returns predictable? This question is a perennially popular subject of debate. In this post, we highlight some results from our recent working paper, where we investigate the matter. Rather than focusing on a single object like the forecasted mean or median, we look at the entire distribution of stock returns and find that the realized volatility of stock returns, especially financial sector stock returns, has strong predictive content for the future distribution of stock returns. This is a robust feature of the data since all of our results are obtained with real-time analyses ...
Working Paper
Investing in the Batteries and Vehicles of the Future: A View Through the Stock Market
A large number of companies operating in the EV and battery supply chain have listed on a major U.S. stock exchange in recent years. This paper investigates 1) how these companies’ stock returns are related to systematic risk factors that can explain movements in the stock market and 2) how these companies’ idiosyncratic returns are related to one another. To do so, I compile a unique data set of intradaily stock returns that spans the supply chain, including companies focused on the mining of battery and EV-related critical minerals, advanced battery technology, lithium-ion battery ...
Working Paper
The US, Economic News, and the Global Financial Cycle
We provide evidence for a causal link between the US economy and the global financial cycle. Using intraday data, we show that US macroeconomic news releases have large and significant effects on global risky asset prices. Stock price indexes of 27 countries, the VIX, and commodity prices all jump instantaneously upon news releases. The responses of stock indexes co-move across countries and are large - often comparable in size to the response of the S&P 500. Further, US macroeconomic news explains on average 23 percent of the quarterly variation in foreign stock markets. The joint behavior ...
Working Paper
More than Words: Twitter Chatter and Financial Market Sentiment
We build a new measure of credit and financial market sentiment using Natural Language Processing on Twitter data. We find that the Twitter Financial Sentiment Index (TFSI) correlates highly with corporate bond spreads and other price- and survey-based measures of financial conditions. We document that overnight Twitter financial sentiment helps predict next day stock market returns. Most notably, we show that the index contains information that helps forecast changes in the U.S. monetary policy stance: a deterioration in Twitter financial sentiment the day ahead of an FOMC statement release ...
Report
Changing Risk-Return Profiles
We show that realized volatility in market returns and financial sector stock returns have strong predictive content for the future distribution of market returns. This is a robust feature of the last century of U.S. data and, most importantly, can be exploited in real time. Current realized volatility has the most information content on the uncertainty of future returns, whereas it has only limited content about the location of the future return distribution. When volatility is low, the predicted distribution of returns is less dispersed and probabilistic forecasts are sharper.