A Fast Literature Search Engine based on top-quality journals, by Dr. Mingze Gao.

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Results 6,024 resources

  • When a group of investors with dispersed private information jointly invest in a risky project, how should they divide the project's profit? We show that a simple contract dividing profits in proportion to investors' risk tolerances may facilitate information aggregation by altering investors' risk‐taking incentives when they decide on how investment strategies respond to private information. Our results provide a contracting‐based approach for information aggregation, which is an alternative to learning from endogenous market variables (e.g., prices) via contingent schedules as seen in well‐known rational expectations equilibrium models.

  • We develop a tractable model of systemic bank runs. The market‐based banking system features a two‐layer structure: banks with heterogeneous fundamentals face potential runs by their creditors while they trade short‐term funding in the asset (interbank) market in response to creditor withdrawals. The possibility of a run on a particular bank depends on its assets' interim liquidation value, and this value depends endogenously in turn on the status of other banks in the asset market. The within‐bank coordination problem among creditors and the cross‐bank price externality feed into each other. A small shock can be amplified into a systemic crisis.

  • We develop a method that identifies the attention paid by earnings call participants to firms' climate change exposures. The method adapts a machine learning keyword discovery algorithm and captures exposures related to opportunity, physical, and regulatory shocks associated with climate change. The measures are available for more than 10,000 firms from 34 countries between 2002 and 2020. We show that the measures are useful in predicting important real outcomes related to the net‐zero transition, in particular, job creation in disruptive green technologies and green patenting, and that they contain information that is priced in options and equity markets.

  • We examine decentralization of digital platforms through tokenization as an innovation to resolve the conflict between platforms and users. By delegating control to users, tokenization through utility tokens acts as a commitment device that prevents a platform from exploiting users. This commitment comes at the cost of not having an owner with an equity stake who, in conventional platforms, would subsidize participation to maximize the platform's network effect. This trade‐off makes utility tokens a more appealing funding scheme than equity for platforms with weak fundamentals. The conflict reappears when nonusers, such as token investors and validators, participate on the platform.

  • We analyze how regulatory constraints on household leverage—in the form of loan‐to‐income and loan‐to‐value limits—affect residential mortgage credit and house prices as well as other asset classes not directly targeted by the limits. Loan‐level data suggest that mortgage credit is reallocated from low‐ to high‐income borrowers and from urban to rural counties. This reallocation weakens the feedback between credit and house prices and slows house price growth in “hot” housing markets. Banks whose lending to households is more affected by the regulatory constraint drive this reallocation, but also substitute their risk‐taking into holdings of securities and corporate credit.

  • We develop a stationary model of the aggregate stock market featuring both dividend‐paying and no‐dividend stocks within a familiar, parsimonious consumption‐based equilibrium framework. We find that such a simple feature leads to profound implications supporting several stock market empirical regularities that leading consumption‐based asset pricing models have difficulty reconciling. Namely, the presence of no‐dividend stocks in the stock market leads to a lower correlation between stock market returns and the aggregate consumption growth rate, a nonmonotonic and even negative relation between the stock market risk premium and its volatility, and a downward‐sloping term structure of equity risk premia.

  • We study secured lending contracts using a proprietary, loan‐level database of bilateral repurchase agreements containing groups of simultaneous loans backed by multiple tranches within a securitization. We show that lower‐quality loans (i.e., loans backed by lower‐rated collateral) have higher margins and spreads. We calibrate a model using collateral asset prices and find that lower‐quality loans are riskier despite the higher margins, yet cheaper for the borrower. This finding is consistent with a combination of lender optimism and reaching for yield. We also show that lower‐quality loans have longer maturity, consistent with models of rollover concerns with asymmetric information.

  • We study the influence of financial innovation by fintech brokerages on individual investors’ trading and stock prices. Using data from Robinhood, we find that Robinhood investors engage in more attention‐induced trading than other retail investors. For example, Robinhood outages disproportionately reduce trading in high‐attention stocks. While this evidence is consistent with Robinhood attracting relatively inexperienced investors, we show that it is also driven in part by the app's unique features. Consistent with models of attention‐induced trading, intense buying by Robinhood users forecasts negative returns. Average 20‐day abnormal returns are −4.7% for the top stocks purchased each day.

  • We develop a flexible and bias‐adjusted approach to jointly examine skill, scalability, and value‐added across individual funds. We find that skill and scalability (i) vary substantially across funds, and (ii) are strongly related, as great investment ideas are difficult to scale up. The combination of skill and scalability produces a value‐added that (i) is positive for the majority of funds, and (ii) approaches its optimal level after an adjustment period (possibly due to investor learning). These results are consistent with theoretical models in which funds are skilled and able to extract economic rents from capital markets.

  • We analyze the effect of import competition on household balance sheets using individual data on consumer finances. We exploit variation in local industry exposure to foreign competition to study households' response to the income shock triggered by China's accession to the World Trade Organization. We show that household debt increases significantly in regions where manufacturing industries are more exposed to import competition. The effects are driven by home equity extraction and are concentrated in areas with strong house price growth. Our results highlight the role played by mortgage markets in absorbing displacement shocks triggered by globalization.

Last update from database: 5/16/24, 11:00 PM (AEST)

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