[We examine how investor preferences and beliefs affect trading in relation to past gains and losses. The probability of selling as a function of profit is V-shaped; at short holding periods, investors are more likely to sell big losers than small ones. There is little evidence of an upward jump in selling at zero profits. These findings provide no clear indication that realization preference explains trading. Furthermore, the disposition effect is not driven by a simple direct preference for selling a stock by virtue of having a gain versus a loss. Trading based on belief revisions can potentially explain these findings.]

It is commonly believed that deposit rates are determined primarily by supply: Depositors require higher deposit rates from risky banks, thereby creating market discipline. An alternative perspective is that market discipline is limited (e.g., due to deposit insurance and/or enhanced capital regulation) and that internal demand for funding by banks determines rates. Using branch-level deposit rate data, we find little evidence for market discipline as rates are similar across bank capitalization levels. In contrast, banks’ loan growth has a causal effect on deposit rates; for example, branches’ deposit rates are correlated with loan growth in other states in which their bank has some presence, suggesting internal capital markets help reallocate the bank’s funding.

[Hedge funds significantly reduced their equity holdings during the recent financial crisis. In 2008: Q3-Q4, hedge funds sold about 29% of their aggregate portfolio. Redemptions and margin calls were the primary drivers of selloffs. Consistent with forced deleveraging, the selloffs took place in volatile and liquid stocks. In comparison, redemptions and stock sales for mutual funds were not as severe. We show that hedge fund investors withdraw capital three times as intensely as mutual fund investors do in response to poor returns. We relate this stronger sensitivity to losses to share liquidity restrictions and institutional ownership in hedge funds.]

Data-driven lending relies on the calibration of models using training periods. We find that this type of lending is not resilient in the presence of economic conditions that are materially different from those experienced during the training period. Using data from a small business fintech lending platform, we document that the small business credit supply collapsed during the COVID-19 crisis of March 2020 even though the demand for loans doubled relative to pre-pandemic levels. As the month progressed, most lenders significantly reduced or halted their lending activities, likely due to the heightened risk of model miscalibration under the new economic conditions.

We study a controlled experiment in which a bank's loan officers were incentivized based on originated loan volume to encourage prospecting for new business. While treated loan officers did attract new applications, both extensive and intensive margins of loan origination expanded (+ 31% new loans; loan size + 15%). We find that loan officers gave greater weight to hard information in approval decisions. Despite no change in the observable characteristics of approved loans, their default rate increased (+ 24%). Finally, the bank's imputed credit default model lost its predictive power. Overall, loan prospecting incentives led to unfavorable soft information being overlooked in the origination process.

The increased availability of alcohol may harm individuals who have present-focused preferences and consume more than initially planned. Using a nationwide experiment in Sweden, we study the credit behavior of low-income households around the expansion of liquor stores’ operating hours on Saturdays. Consistent with store closures serving as commitment devices, the policy led to higher credit demand, more default, increased dependence on welfare, and higher crime on Saturdays. The effects are concentrated on the young population due to higher alcohol consumption combined with tight liquidity constraints. The policy’s impact on indebtedness is estimated at 4.5 times the expenditure on alcohol.

We examine how investor preferences and beliefs affect trading in relation to past gains and losses. The probability of selling as a function of profit is V-shaped; at short holding periods, investors are more likely to sell big losers than small ones. There is little evidence of an upward jump in selling at zero profits. These findings provide no clear indication that realization preference explains trading. Furthermore, the disposition effect is not driven by a simple direct preference for selling a stock by virtue of having a gain versus a loss. Trading based on belief revisions can potentially explain these findings. The Author 2012. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: [email protected]., Oxford University Press.

We document evidence consistent with retail traders in the Forex market attributing random success to their own skill and, as a consequence, increasing risk taking. Although past performance does not predict future success for these traders, traders increase trade sizes, trade size variability, and number of trades with gains, and less with losses. There is a large discontinuity in all of these trading variables around zero past week returns: e.g., traders increase their trade size dramatically following winning weeks, relative to losing weeks. The effects are stronger for novice traders, consistent with more intense “learning” in early trading periods.

We argue that the effective price of investing in hedge funds far exceeds the headline fee rate of “2-and-20.” In a large 22-year sample of hedge funds, we find that 60% of the gains on which incentive fees are paid are eventually offset by losses. As a result, the effective incentive fee rate is 50% vis-à-vis the nominal 20% rate. The tendency of investors and managers to disinvest capital after negative returns contributes to this phenomenon by causing the crystallization of underwater fees and net losses as well as by eroding the protection intended by the high-water mark provision. (JEL D24, G11, G23, J33)Received: April 17, 2025Editor: J.

Hard-to-value stocks provide opportunities for managers to exploit their informational advantage through trading on their firms’ and their own personal accounts. In contrast to the prediction that such transactions reflect private information about future events, they are contrarian and heavily depend on past returns. Corporate transactions in hard-to-value stocks outperform those in easy-to-value stocks in the early part of our sample, but this difference disappears after 2002, coinciding with a general decline in the profitability of stock market anomalies. Our evidence is consistent with managers’ perception of mispricing, rather than private information, being a key motivator of their transactions.