Knowledge that Transforms

This paper models benefits of quoting output price in units of crypto token under duopolistic product market competition with switching costs. Pricing output in tokens provides a firm with a de facto second-mover advantage, raising its equilibrium profit. In addition, the firm can further increase its equilibrium profit by committing via a smart contract to the number of tokens sold. By focusing on utility tokens used at the product market competition stage, the paper highlights potential benefits of issuing crypto tokens that extend beyond the advantages of issuing security tokens at the venture financing stage.

We classify asset pricing anomalies into those exacerbating mispricing (build-up anomalies) and those resolving it (resolution anomalies). We estimate the dynamics of price wedges for well-known anomaly portfolios and map them to firm-level mispricings. We find that several prominent anomalies like momentum and profitability further dislocate prices. Multi-factor models designed to eliminate one-month alphas still produce large price wedges. Our estimates yield a novel decomposition of Tobin’s q, revealing that q’s mispricing component has substantial explanatory power for firm investment. Overall, our results suggest that financial intermediaries chasing build-up anomalies negatively affect price efficiency and associated real capital allocation.

We study the influence from social interactions on equity trading. Using unique data on stock transactions, we exploit the quasi-random assignment of students to classrooms in a financial training program to identify how peer experience affects investor behavior. We find that individuals react more to peer gains than to peer losses. Students enrolled in courses where peers have positive outcomes: (i) are more likely to start trading, (ii) purchase similar stocks as their classmates, and (iii) are disproportionally attracted to stocks with extreme returns. These stocks have low subsequent returns, and new investors reacting to peer gains underperform other investors.

We provide evidence that changes in lender optimism can lead to excessive fluctuations in credit spreads across the credit cycle. Using data on the real estate properties of loan officers originating large corporate loans, we find that credit spreads overreact to sophisticated lenders’ recent local economic experiences, captured by local housing price growth. These effects are only present when borrowers own real estate assets and during times of greater uncertainty about real estate values, i.e., boom-and-bust cycles in housing prices. Our analysis suggests that recent personal experiences shape sophisticated lenders’ beliefs about real estate values, which affect their pricing decisions.

What drives the puzzle of market reactions to old news? Motivated by theories of correlation neglect, we conduct an experiment on finance professionals and show that even sophisticated investors have difficulty identifying old information that recombines content from multiple sources. We evaluate the market implications of this mechanism using a unique dataset of 17 million news articles from the Bloomberg terminal. Recombination of old information prompts larger price moves and subsequent reversals than direct reprints. This effect persists across news sentiment, ambiguity, and investor attention. Furthermore, while overall reactions to old information decline over time, differential reactions to recombinations increase.

Some events impact volatilities of most assets, asset classes, sectors and countries, causing serious damage to investment portfolios. The magnitude of such shocks is defined as global COVOL which is an abbreviation for global common volatility, a broad measure of all types of global financial risk. This paper introduces a statistical formulation of such events as common volatility innovations in both a multivariate volatility and an asset pricing context. Simulations verify the statistical performance of a simple but novel estimator and of a test to detect global COVOL. Two empirical examples show the events that have had the biggest impact on financial markets. The results are useful for portfolio optimization and risk forecasting.

A strong dollar has been associated with lower lending to emerging markets and tighter global financial conditions. This paper documents similar patterns for credit in the U.S. economy: when the U.S. broad dollar index appreciates by 1 percent, U.S. banks’ corporate loan originations fall by 4.5 percent, with banks tightening credit standards and lending to safer borrowers. This negative correlation, which we term the U.S. dollar credit channel, is at least in part driven by institutional investors, who reduce their demand for risky loans on the secondary loan market when the dollar appreciates. As it becomes harder to sell loans to these investors, banks lend less.

Securities dealers receive mortgages as collateral for credit lines provided to mortgage companies and reuse the same collateral to borrow money. Exploiting the 2005 BAPCPA rule change, which granted mortgage collateral preferred bankruptcy treatment, I find that strengthening creditor rights increases dealers’ collateral reuse. Increasing collateral reuse creates a money multiplier that increases credit supply. Using a novel dataset linking dealers to the mortgage companies they fund reveals that post-BAPCPA, dealers supply additional credit to mortgage companies by increasing credit lines and relaxing restrictions on collateral securing them. In response, mortgage companies increase origination volume and shift into riskier products.

The percentage of U.S. equity mutual funds that outperform the SPY ETF over the last 30 years decreases substantially as the horizon over which returns are measured is increased. Further, some funds with positive monthly alpha estimates have negative long-horizon abnormal returns. These results reflect positive skewness in the distribution of fund returns that increases with horizon, and highlight the limitations of conditional arithmetic means of short-horizon returns (e.g., alpha) for long-horizon investors. We tabulate an aggregate wealth loss of $1.02 trillion to mutual fund investors over our 30-year sample, when opportunity costs are based on beta-adjusted SPY returns.

We examine subjective risk premia implied by return expectations of individual investors and professionals for portfolios of stocks, bonds, currencies, and commodity futures. While in-sample predictive regressions with realized excess returns suggest that objective risk premia vary countercyclically with business-cycle and asset-valuation measures, subjective risk premia extracted from survey data are largely acyclical. Out-of-sample forecasts of excess returns exhibit a similar lack of cyclicality, which suggests that investors’ learning of forecasting relationships in real time may help explain the cyclicality gap. There is a subjective risk-return tradeoff, with subjective risk premia increasing in subjective perceptions of risk quantity.