Comovement and Predictability Relationships Between Bonds and the Cross-Section of Stocks

Malcolm  Baker; Jeffrey  Wurgler

Article | Review of Asset Pricing Studies | June 2012

Comovement and Predictability Relationships Between Bonds and the Cross-Section of Stocks

by Malcolm Baker and Jeffrey Wurgler

Abstract

Government bonds comove more strongly with bond-like stocks: stocks of large, mature, low-volatility, profitable, dividend-paying firms that are neither high growth nor distressed. Variables derived from the yield curve that are already known to predict returns on bonds also predict returns on bond-like stocks; investor sentiment, a predictor of the cross section of stock returns, also predicts excess bond returns. These relationships remain in place even when bonds and stocks become "decoupled" at the index level. They are driven by a combination of effects including correlations between real cash flows on bonds and bond-like stocks, correlations between their risk-based return premia, and periodic flights to quality.

Keywords: Relationships; Bonds; Stocks; Investment Return; Cash Flow; Quality; Risk and Uncertainty; Forecasting and Prediction; Profit;

Format: Print

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Citation:

Baker, Malcolm, and Jeffrey Wurgler. "Comovement and Predictability Relationships Between Bonds and the Cross-Section of Stocks." Review of Asset Pricing Studies 2, no. 1 (June 2012): 57–87.

This case describes the Dogs of the Dow investment strategy, value investing, and using dividend yields as a means to determine intrinsic value. It also describes exchange traded notes and a particular exchange traded note, known as the Dogs of the Dow, which tracks the performance of the 10 highest yielding stocks of the 30 stocks that make up the Dow Jones Industrial Average (DJIA). The case provides share price data, dividend data, and financial statement data on the 30 DJIA companies to enable students to perform their own calculations.

We study green bonds, which are bonds whose proceeds are used for environmentally sensitive purposes. After an overview of the U.S. corporate and municipal green bonds markets, we study pricing and ownership patterns using a simple framework that incorporates assets with nonpecuniary utility. As predicted, we find that green municipal bonds are issued at a premium to otherwise similar ordinary bonds. We also confirm that green bonds, particularly small or essentially riskless ones, are more closely held than ordinary bonds. These pricing and ownership effects are strongest for bonds that are externally certified as green.

Working Paper | 2018

Detecting Anomalies: The Relevance and Power of Standard Asset Pricing Tests

Malcolm Baker, Patrick Luo and Ryan Taliaferro

The two standard approaches for identifying capital market anomalies are cross-sectional coefficient tests, in the spirit of Fama and MacBeth (1973), and time-series intercept tests, in the spirit of Jensen (1968). A new signal can pass the first test, which we label a “score anomaly,” it can pass the second test as a “factor anomaly,” or it can pass both. We demonstrate the relevance of each to a mean-variance optimizing investor facing simple transaction costs that are constant across stocks. For a risk-neutral investor facing transaction costs, only score anomalies are relevant. For a risk-averse investor facing no transaction costs, only factor anomalies are relevant. In the more general case of risk aversion and transaction costs, both tests matter. In extensions, we derive modified versions of the basic tests that net out anomaly execution costs for situations where the investor faces capital constraints, a multi-period portfolio choice problem, or transaction costs that vary across stocks. Next, we measure the econometric power of the two tests. Time-series factor tests have uniformly lower power than equivalent cross-sectional score tests, with the gap increasing in the in-sample Sharpe ratio of the incumbent factor model. New factor anomalies are successively harder to detect. There is a lower natural limit on the number of anomalies, after which new factors can no longer be verified. Meanwhile, for an investor facing transaction costs, where score anomalies are also applicable, there is a higher natural limit on the number of anomalies that can be statistically validated as relevant.

Keywords: investment management; asset pricing; anomalies; portfolio construction; transaction costs; Investment; Management; Asset Pricing; Market Transactions; Cost;

Citation:

Baker, Malcolm, Patrick Luo, and Ryan Taliaferro. "Detecting Anomalies: The Relevance and Power of Standard Asset Pricing Tests." Working Paper, July 2018. View Details

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Comovement and Predictability Relationships Between Bonds and the Cross-Section of Stocks

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