We test whether forecast bias affects household stock trading by combining measures of bias elicited in laboratory experiments with administrative trade-level data. On average, subjects exhibit positive forecast bias (i.e., extrapolators), while a large minority exhibit negative forecast bias (i.e., contrarians). Forecast bias is positively associated with past excess returns of stocks that are purchased: Extrapolators (contrarians) purchase past winners (losers). Forecast bias is negatively associated with the capital gains of stocks that are sold. Furthermore, forecast bias explains investor heterogeneity in the relation between market returns and net flows to stocks. Overall, our study provides evidence of a common mechanism – forecast bias – that links past returns to trading decisions for purchases, sales, and net flows.

We provide novel evidence suggestive of insider trading through concealed relationships identified using information from over 100,000 Facebook profiles and their 35 million friends. Focusing on connections between fund managers and firm officers, we demonstrate that hidden ties are linked to substantial abnormal returns averaging 135 basis points per month (exceeding 16% alpha annually, t -stat = 3.54) across the universe of mutual funds and public firms. These hidden ties emerge as the most powerful predictor of future stock returns among documented network characteristics, with predictive power increasing over time through the present day. The premium associated with such connections arises not from endogenous selection or familiarity bias; instead, fund managers exhibit specific timing ability in deciding when to hold (or avoid) stocks of firm officers linked through hidden ties. The value of trading information rises with the degree of concealment and is concentrated around earnings and M&A events. The premium is absent in index funds, where strategic stock selection and timing are infeasible. Our findings on the value of hidden ties remain robust across industries, investment styles, time periods, and firm types.

Using mutual fund flows, we evaluate prospect theory with choice outcomes in the market. We provide strong support for prospect theory: under a standard set of parameters, funds whose past returns generate higher prospect theory value attract significantly larger future flows; we also find corroborative evidence using account-level data. Taking a revealed preference approach, we estimate the prospect theory parameters through a discrete choice model and find that our field-based estimates align well with previous experiment-based estimates. Moreover, we show that prospect theory offers a new framework for understanding flows, as it has explanatory power beyond existing drivers.

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.

We document implicit extrapolation in investment decision-making that exceeds the extrapolation inferable from stated expectations. Locally experienced returns predict individual real-estate investment decisions even conditional on an investor’s forecasted home-price growth and risk aversion. Moreover, estimates of this experience effect on investment are larger than implied by the combined effect of past returns on stated expectations and stated expectations on investment. We demonstrate that heterogeneous forecast confidence helps explain why many investors rely on past returns over their survey-elicited forecasts. As their rationale, such survey respondents frequently cite intentional extrapolation or a lack of confidence in other belief factors.

Disagreement about macroeconomic fundamentals accounts for only part of the disagreement about future interest rates, creating a “disagreement correlation” puzzle. This puzzle arises because standard equilibrium models with belief differences predict a strong link between asset return disagreement and fundamental disagreement, a link not supported by the data. We address this puzzle by introducing a model where disagreement about future demand for savings—driven by disagreement over the prevalence of patient versus impatient investors in the economy—generates asset return disagreement. Our mechanism produces stochastic yield volatility, time-varying bond risk premia, and an upward-sloping yield curve. Empirically, we construct a proxy for demand disagreement by isolating the component of yield disagreement unrelated to disagreement about macro-fundamentals. This proxy is positively related to yields and their volatilities, and predicts future bond risk premia, consistent with the predictions of our demand disagreement model.

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.

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.

To enforce insider trading laws, financial regulators require top executives to make their own-company trades public. One implication of this regulatory focus is that executives below the top fly under the radar. We use administrative register data from Norway to examine whether executives below the top in listed companies earn abnormal returns on purchases in own-company stock. We find evidence of abnormal returns on such trades, about 50 to 100 basis points at the 1-month horizon. The abnormal returns on purchases in other stocks are negative, making high investor ability an unlikely explanation.