About
As a career quant I've contributed to a few areas in quantitative finance including the…
Articles by Peter
Activity
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Singapore just approved a floating data centre, China has one that is actually underwater, the Hyperscale AI build out might not look like…
Singapore just approved a floating data centre, China has one that is actually underwater, the Hyperscale AI build out might not look like…
Liked by Peter Cotton
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Counting down to SportsPro London and here's another session I'm really curious about. Reading Football Club recently became the first English club…
Counting down to SportsPro London and here's another session I'm really curious about. Reading Football Club recently became the first English club…
Liked by Peter Cotton
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Happy to share that DataBallPy is now officially published in the Journal of Open Source Software, something I didn’t imagine when I first started…
Happy to share that DataBallPy is now officially published in the Journal of Open Source Software, something I didn’t imagine when I first started…
Liked by Peter Cotton
Experience
Education
Publications
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Microprediction: Building an Open AI Network
MIT Press
See publicationHow a web-scale network of autonomous micromanagers can challenge the AI revolution and combat the high cost of quantitative business optimization.
The artificial intelligence (AI) revolution is leaving behind small businesses and organizations that cannot afford in-house teams of data scientists. In Microprediction, Peter Cotton examines the repeated quantitative tasks that drive business optimization from the perspectives of economics, statistics, decision making under uncertainty, and…How a web-scale network of autonomous micromanagers can challenge the AI revolution and combat the high cost of quantitative business optimization.
The artificial intelligence (AI) revolution is leaving behind small businesses and organizations that cannot afford in-house teams of data scientists. In Microprediction, Peter Cotton examines the repeated quantitative tasks that drive business optimization from the perspectives of economics, statistics, decision making under uncertainty, and privacy concerns. He asks what things currently described as AI are not “microprediction,” whether microprediction is an individual or collective activity, and how we can produce and distribute high-quality microprediction at low cost. The world is missing a public utility, he concludes, while companies are missing an important strategic approach that would enable them to benefit—and also give back.
In an engaging, colloquial style, Cotton argues that market-inspired “superminds” are likely to be very effective compared with other orchestration mechanisms in the domain of microprediction. He presents an ambitious yet practical alternative to the expensive “artisan” data science that currently drains money from firms. Challenging the machine learning revolution and exposing a contradiction at its heart, he offers engineers a new liberty: no longer reliant on quantitative experts, they are free to create intelligent applications using general-purpose application programming interfaces (APIs) and libraries. He describes work underway to encourage this approach, one that he says might someday prove to be as valuable to businesses—and society at large—as the internet. -
Self-Organizing Supply Chains for Microprediction: Present and Future Uses of the ROAR Protocol
Thirty-sixth International Conference on Machine Learning
See publicationA multi-agent system is trialed as a means of crowd-sourcing inexpensive but high quality streams of predictions. Each agent is a microservice embodying statistical models and endowed with economic self-interest. The ability to fork and modify simple agents is granted to a large number of employees in a firm and empirical lessons are reported. We suggest that one plausible trajectory for this project is the creation of a Prediction Web.
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Stochastic Volatility Corrections for Interest Rate Derivatives
Mathematical Finance
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Rapid Simulation of Correlated Defaults an the Valuation of Basket Default Swaps
Probability, Finance and Insurance
Basket default swaps are complex credit derivatives that are difficult to price analytically and are typically priced by using Monte Carlo simulations. The pricing and risk management of basket default swaps present challenging computational problems. We present a method for efficiently generating correlated default times whose marginal distributions are consistent with a reduced form stochastic hazard rate model.
Other authorsSee publication -
Contraction of an Adapted Functional Calculus
Journal of Lie Theory
See publicationWe aim to show, using the example of a Riemannian symmetric
pair (G;K) = (SL2(R); SO(2)), how contraction ideas may be applied
to functional calculi constructed on coadjoint orbits of Lie groups
Patents
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Method an Apparatus for Collective Microprediction
Filed US 63/031406
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System and Method for Secure Causality Discovery
Filed US 16853719
Secure granger causality using secure multiparty computation protocol
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Systems and methods for analyzing financial models with probabilistic networks
Issued US 8370241
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Method of Fusing Probabilistic Models with Overlapping Domains
Filed US 61/078600
Honors & Awards
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Data Mind of the Year 2024
Rebellion Research
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Australian Junior Chess Champion
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Winner of the national U/20 championship (Brisbane 1990).
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Australian Mathematics Olympiad
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Gold (1991). Bronze (1990).
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Eric Hoffer Book Award Finalist
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https://www.hofferaward.com/Eric-Hoffer-Award-category-finalists.html
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International Physics Olympiad
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Bronze (Cuba 1991).
More activity by Peter
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🌟 📖 I’m pleased to share that our article, 𝘼 𝙁𝙪𝙡𝙡𝙮 𝘿𝙖𝙩𝙖-𝘿𝙧𝙞𝙫𝙚𝙣 𝙑𝙖𝙡𝙪𝙚 𝙄𝙩𝙚𝙧𝙖𝙩𝙞𝙤𝙣 𝙛𝙤𝙧 𝙎𝙩𝙤𝙘𝙝𝙖𝙨𝙩𝙞𝙘 𝙇𝙌𝙍:…
🌟 📖 I’m pleased to share that our article, 𝘼 𝙁𝙪𝙡𝙡𝙮 𝘿𝙖𝙩𝙖-𝘿𝙧𝙞𝙫𝙚𝙣 𝙑𝙖𝙡𝙪𝙚 𝙄𝙩𝙚𝙧𝙖𝙩𝙞𝙤𝙣 𝙛𝙤𝙧 𝙎𝙩𝙤𝙘𝙝𝙖𝙨𝙩𝙞𝙘 𝙇𝙌𝙍:…
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RETHINKING how portfolios are constructed: from static choices to #adaptive frameworks 🚀 I am pleased to share that our paper “Bridging Risk…
RETHINKING how portfolios are constructed: from static choices to #adaptive frameworks 🚀 I am pleased to share that our paper “Bridging Risk…
Liked by Peter Cotton
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Every LLM is a statistical machine. Every statistical machine can be gamed. We gamed the ones Wall Street is quietly using to read the news. In our…
Every LLM is a statistical machine. Every statistical machine can be gamed. We gamed the ones Wall Street is quietly using to read the news. In our…
Liked by Peter Cotton
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Playing around with a new DuckDB extension called ASK mode that integrates LLMs into the DuckDB CLI shell. Full video up soon. Here's a charts that…
Playing around with a new DuckDB extension called ASK mode that integrates LLMs into the DuckDB CLI shell. Full video up soon. Here's a charts that…
Liked by Peter Cotton
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Enterprise customers we have been meeting have changed the question they're asking about AI. Twelve months ago it was "does it work?" Now it's "what…
Enterprise customers we have been meeting have changed the question they're asking about AI. Twelve months ago it was "does it work?" Now it's "what…
Liked by Peter Cotton
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