Knowledge that Transforms

We propose a new approach to modeling bond risk and risk premia, inspired by the equity risk-return literature, which does not impose the tight restrictions found in models that generate closed-form bond prices. We estimate the joint dynamics of the volatility and Sharpe ratio of principal-component bond-factor portfolios as functions of yield curve variables and VIX. We uncover an important second factor in risk premia and document a complex time-varying relation between the price and quantity of interest rate risk inconsistent with the frameworks in existing studies. Exploiting this predictability in dynamic portfolio choice appears to enhance portfolio performance. Abstract We propose a new approach to modeling bond risk and risk premia, inspired by the equity risk-return literature, which does not impose the tight restrictions found in models that generate closed-form bond prices. We estimate the joint dynamics of the volatility and Sharpe ratio of principal-component bond-factor portfolios as functions of yield curve variables and VIX. We uncover an important second factor in risk premia and document a complex time-varying relation between the price and quantity of interest rate risk inconsistent with the frameworks in existing studies. Exploiting this predictability in dynamic portfolio choice appears to enhance portfolio performance.

We use newspapers to create Equity Market Volatility (EMV) trackers at daily and monthly frequencies. Our headline EMV tracker moves closely with the VIX and the S&P500 returns volatility in and out of sample. We exploit the volume of newspaper text to construct forty category-specific EMV trackers. News about commodity markets, interest rates, real estate markets, aggregate activity, and inflation figure prominently in EMV articles. Policy news is another major source of market volatility: 30 % of EMV articles discuss tax policy, 30 % discuss monetary policy, and 25 % refer to some form of regulation. Combining our newspaper-based trackers with textual analysis of 10-K filings, we obtain monthly firm-level risk exposure measures. These measures help explain the cross-sectional structure of realized volatilities and its evolution over time, even after conditioning on firm and time fixed effects.

We use individual-level credit data to study how recent declines in Appalachian coal mining affected household finances between 2011 and 2018. Using exogenous variation in electricity sector demand for coal, we find declines in coal demand decreased credit scores and increased financial distress within two years of coal shocks. These effects cannot be explained solely by job losses in coal mine worker households. Credit score declines and financial distress were largest among older individuals and people with lower-middle credit scores. Our results suggest the transition away from fossil fuels may impose meaningful costs on other fossil fuel extraction communities.

We study the equity, cash, and corporate bond risk premium expectations of asset managers, investment consultants, wealth advisors, public pension funds, and professional forecasters. Subjective risk premia vary one-to-one with objective risk premia that are available in real time and countercyclical. Despite their significant time-series variation, several subjective equity premia vary more in the cross-section of institutions than in the time series. This heterogeneity persists both over time and across asset classes. We tie the heterogeneity in subjective equity return expectations to heterogeneous expectations about long-term equity valuations: some institutions believe that the price–earnings ratio behaves like a random walk, whereas others believe in varying degrees of mean reversion.

To safeguard its technological leadership, the U.S. has restricted domestic suppliers from exporting cutting-edge technologies to selected Chinese firms. Domestic firms affected by these export controls halt sales to Chinese customers, as intended, but struggle to establish new relations with alternative customers domestically or in politically aligned regions. Consequently, domestic suppliers experience sizable losses in market capitalization, along with reductions in profitability, employment, and bank lending. Chinese firms are more proactive in reconfiguring supply chains, though not without costs. Overall, export controls impose larger costs on U.S. firms developing the very technologies these policies aim to protect.

Policy uncertainty can undermine the power of government subsidies to stimulate environmentally friendly research and development. We show that Chinese firms’ green R&D falls as the uncertainty of environmental subsidies rises: Exogenous, weather-driven air pollution variability induces subsidies to fluctuate, and firms in areas with high weather-driven subsidy variability undertake less green R&D and hire fewer technical employees, controlling for the average level of subsidies. Heavy emitters and environmental technology firms are more affected. The results also illustrate how policy uncertainty can arise when policymakers are influenced by conditions that are salient but with causes that are difficult to disentangle.

We study the nature and effects of cultural biases in choice under risk and uncertainty by comparing peer-to-peer loans the same individuals ( lenders ) make alone and after observing robo-advised suggestions. When unassisted, lenders are more likely to choose co-ethnic borrowers, facing 8% higher defaults and 7.3pp lower returns. Robo-advising does not affect diversification but reduces lending to high-risk co-ethnic borrowers. Lenders in locations with high inter-ethnic animus drive the results, even when borrowers reside elsewhere. Biased beliefs explain these results better than a conscious taste for discrimination: lenders rarely override robo-advised matches to ethnicities they discriminated against when unassisted.

This paper studies the transmission of monetary policy to the stock market through investors’ discount factors. To isolate this channel, we investigate the effect of US monetary policy surprises on the ratio of prices of the same stock listed simultaneously in Hong Kong and Mainland China. We identify a strong discount rate channel driven exclusively by cycle-amplifying surprises, defined as rate cuts during easing cycles and surprise hikes during tightening cycles. A 100 basis point of such cycle-amplifying surprise induces a 30 basis point change in the price ratio within five days.