这是“金融学前沿论文速递”第1483篇推送
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Machine Learning for Continuous-Time Finance
Horizon-Dependent Risk Aversion and the Timing and Pricing of Uncertainty
Credit Cycles, Expectations, and Corporate Investment
The Technical Default Spread
Heterogeneous Real Estate Agents and the Housing Cycle
A Comprehensive 2022 Look at the Empirical Performance of Equity Premium Prediction
Computational Reproducibility in Finance: Evidence from 1,000 Tests
Machine Learning for Continuous-Time Finance
原刊和作者:
Review of Financial Studies 2024年11月
Victor Duarte (University of Illinois at Urbana-Champaign)
Diogo Duarte (Florida International University)
Dejanir Silva (Purdue University)
We develop an algorithm for solving a large class of nonlinear high-dimensional continuous-time models in finance. We approximate value and policy functions using deep learning and show that a combination of automatic differentiation and Ito’s lemma allows for the computation of exact expectations, resulting in a negligible computational cost that is independent of the number of state variables. We illustrate the applicability of our method to problems in asset pricing, corporate finance, and portfolio choice and show that the ability to solve high-dimensional problems allows us to derive new economic insights.
Horizon-Dependent Risk Aversion and the Timing and Pricing of Uncertainty
原刊和作者:
Review of Financial Studies 2024年11月
Marianne Andries (University of Southern California)
Thomas Eisenbach (Federal Reserve Bank of New York)
Martin Schmalz (University of Oxford, CEPR, and ECGI)
Inspired by experimental evidence, we amend the recursive utility model to let risk aversion decrease with the temporal horizon. Our pseudo-recursive preferences remain tractable and retain appealing features of the long-run risk framework, notably its success at explaining asset pricing moments. In addition, our model addresses two challenges to the standard model. Calibrating the agents’ preferences to explain the equity premium no longer implies an extreme preference for early resolutions of uncertainty. Horizon-dependent risk aversion helps resolve key puzzles in finance on the valuation of assets across maturities and captures the term structure of equity risk premiums and its dynamics.
Credit Cycles, Expectations, and Corporate Investment
原刊和作者:
Review of Financial Studies 2024年11月
Huseyin Gulen (Purdue University)
Mihai Ion (University of Arizona)
Candace Jens (Syracuse University)
Stefano Rossi (Bocconi University)
We provide a systematic empirical assessment of the Minsky hypothesis that business fluctuations stem from irrational swings in expectations. Using predictable firm-level forecast errors, we build an aggregate index of irrational expectations and use it to provide three sets of results. First, we show that our index predicts aggregate credit cycles. Next, we show that these predictable credit cycles drive cycles in firm-level debt issuance and investment and similar cycles between financially constrained and unconstrained firms, as Minsky predicts. Finally, we show more pronounced cycles in firm-level financing and investment for firms with ex ante more optimistic expectations.
The Technical Default Spread
原刊和作者:
Review of Financial Studies 2024年11月
Emilio Bisetti (University of Science and Technology)
Kai Li (Peking University and the PHBS Sargent Institute)
Jun Yu (University of Melbourne)
We study the quantitative impact of lender control rights on corporate investment, asset prices, and the aggregate economy. We build a general equilibrium model in which the breaching of a loan covenant (technical default) entails a switch in investment control rights from borrowers to lenders. Lenders optimally choose low-risk projects, thus mitigating borrowers’ risk-taking incentives and lowering the cost of equity. This mechanism generates strong macroeconomic effects and mitigates the financial accelerator. Consistent with our model, proximity to technical default in the data is associated with 4.12% lower returns and lower exposure to systematic risk.
Heterogeneous Real Estate Agents and the Housing Cycle
原刊和作者:
Review of Financial Studies 2024年11月
Sonia Gilbukh (The City University of New York)
Paul Goldsmith-Pinkham (Yale University and NBER)
The real estate market is highly intermediated, with 90% of buyers and sellers hiring an agent. However, low barriers to entry and fixed commission rates result in large market share for inexperienced intermediaries. Using micro-level data on 8.5 million listings and a novel research design, we show that house listings by inexperienced agents have a lower probability of selling, and this effect is strongest during the housing bust. We estimate that 3.7% more listings would have been sold in a flexible commission equilibrium. Eighty percent of this improvement comes from competition and the remainder from commission variation across experience.
A Comprehensive 2022 Look at the Empirical Performance of Equity Premium Prediction
原刊和作者:
Review of Financial Studies 2024年11月
Amit Goyal (Swiss Finance Institute)
Ivo Welch (UCLA Anderson)
Athanasse Zafirov
Our paper reexamines whether 29 variables from 26 papers published after Goyal and Welch 2008, as well as the original 17 variables, were useful in predicting the equity premium in-sample and out-of-sample as of the end of 2021. Our samples include the original periods in which these variables were identified, but end later. More than one-third of these new variables no longer have empirical significance even in-sample. Of those that do, half have poor out-of-sample performance. A small number of variables still perform reasonably well both in-sample and out-of-sample.
Computational Reproducibility in Finance: Evidence from 1,000 Tests
原刊和作者:
Review of Financial Studies 2024年11月
Christophe Pérignon et al.
We analyze the computational reproducibility of more than 1,000 empirical answers to 6 research questions in finance provided by 168 research teams. Running the researchers’ code on the same raw data regenerates exactly the same results only 52% of the time. Reproducibility is higher for researchers with better coding skills and those exerting more effort. It is lower for more technical research questions, more complex code, and results lying in the tails of the distribution. Researchers exhibit overconfidence when assessing the reproducibility of their own research. We provide guidelines for finance researchers and discuss implementable reproducibility policies for academic journals.
原文:
https://academic.oup.com/rfs/issue/37/11
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