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Cambridge Finance

 
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Cambridge Finance coordinates the programmes of research and study in all areas of finance across the University of Cambridge. Its members are grouped into seven research centres: 3CL, CCFin, CFR, CIMF, JBSF, REF, CFH and CEAM.
Updated: 1 hour 20 min ago

Thu 07 Mar 13:00: The Origins of Random Choice

Thu, 22/02/2024 - 11:25
The Origins of Random Choice

Using lab data on both choices and eye-movements we exam the rela*tionship between randomness in choice and attention. We bring in 50 subjects and have each make 180 choices, involving repeated choices from the same choice sets, while tracking their eye movements. Our approach allows us to consider attention as a multi-dimensional object and link different aspects of attention to distinct patterns in choice. We show that although the monotonicity condition that underlies random utility models is frequently violated, the monotonicity condition on attention sets considered by Cattaneo et al., 2020 is satisfies by almost all observations. Despite this, attention explains at most around a third of the randomness in choice. Although randomness in choice is much larger at the aggregate compared to the individual level, attention explains randomness in choice to the same degree in both. In ongoing work we conduct revealed preference tests of both random utility and random attention models.

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Thu 22 Feb 12:00: Nonparametric conditional factors for unbalanced panels

Thu, 25/01/2024 - 12:16
Nonparametric conditional factors for unbalanced panels

We introduce a nonparametric estimator for conditional covariance matrices of unbalanced panels. Our approach naturally accommodates a low-dimensional nonlinear factor structure that ensures all structural relations between moments. In high-dimensional large-data applications, we investigate various conditional return expectation and covariance models that depend on asset characteristics. The empirically successful models imply substantial conditional Sharpe ratios, along with respectable ordinal and point predictions. Our approach can easily be extended to accommodate higher-order moments and comes with asymptotic theory that can be used with large unbalanced panels.

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Thu 25 Jan 12:30: How to discipline financial markets: reputation is not enough

Thu, 25/01/2024 - 12:06
How to discipline financial markets: reputation is not enough

Historically, shocks originating in the financial sector often spilled over into the real sector with dramatic consequences. We study in the lab how interventions targeting disclosure and capital requirements of financial intermediaries can reduce insolvencies or prevent their negative effects from propagating to the broader economy. In our two-sector economy, con*sumers and producers can fund financial intermediaries, who in turn provide them with liquidity to settle trades. However, intermediaries may undertake risky investments and become insolvent, which depresses real economic activity. In the experiment, insolvencies were frequent. As a consequence, consumers and producers often refused to fund intermediaries, which lowered the trade volume. Imposing the disclosure of risky investments did not reduce risk-taking and insolvencies. Instead, imposing capital requirements prevented insolvencies from disrupting real economic activity, thus boosting financial intermediation and trade.

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Thu 22 Feb 13:00: Nonparametric conditional factors for unbalanced panels

Thu, 18/01/2024 - 14:58
Nonparametric conditional factors for unbalanced panels

We introduce a nonparametric estimator for conditional covariance matrices of unbalanced panels. Our approach naturally accommodates a low-dimensional nonlinear factor structure that ensures all structural relations between moments. In high-dimensional large-data applications, we investigate various conditional return expectation and covariance models that depend on asset characteristics. The empirically successful models imply substantial conditional Sharpe ratios, along with respectable ordinal and point predictions. Our approach can easily be extended to accommodate higher-order moments and comes with asymptotic theory that can be used with large unbalanced panels.

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Thu 22 Feb 13:00: Kernel Conditional Covariance

Fri, 12/01/2024 - 09:33
Kernel Conditional Covariance

We introduce a nonparametric estimator for conditional covariance matrices of unbalanced panels. Our approach naturally accommodates a low-dimensional conditional nonlinear factor structure that ensures all structural relations between moments. In high-dimensional large-data applications, we investigate various conditional return expectation and covariance models that depend on asset characteristics. The empirically successful models imply substantial conditional Sharpe ratios, along with respectable ordinal and point predictions. Our approach can easily be extended to accommodate higher-order moments and comes with asymptotic theory that can be used with large unbalanced panels.

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Thu 07 Mar 13:00: Title to be confirmed

Wed, 06/12/2023 - 11:32
Title to be confirmed

Abstract not available

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Thu 25 Jan 13:00: How to discipline financial markets: reputation is not enough

Thu, 23/11/2023 - 14:19
How to discipline financial markets: reputation is not enough

Historically, shocks originating in the financial sector often spilled over into the real sector with dramatic consequences. We study in the lab how interventions targeting disclosure and capital requirements of financial intermediaries can reduce insolvencies or prevent their negative effects from propagating to the broader economy. In our two-sector economy, con*sumers and producers can fund financial intermediaries, who in turn provide them with liquidity to settle trades. However, intermediaries may undertake risky investments and become insolvent, which depresses real economic activity. In the experiment, insolvencies were frequent. As a consequence, consumers and producers often refused to fund intermediaries, which lowered the trade volume. Imposing the disclosure of risky investments did not reduce risk-taking and insolvencies. Instead, imposing capital requirements prevented insolvencies from disrupting real economic activity, thus boosting financial intermediation and trade.

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