References and Further Reading
Table of Contents
Foundational Papers
Roughly in order of recommended reading.
Ergodic Economics
Peters, O. (2019). The ergodicity problem in economics. Nature Physics, 15(12), 1216-1221.
Key contribution: Comprehensive overview of ergodicity in economic systems
Relevance: Core theoretical foundation for this project
Peters, O., & Gell-Mann, M. (2016). Evaluating gambles using dynamics. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(2), 023103.
DOI: 10.1063/1.4940236
Key contribution: Time-average framework for decision-making
Relevance: Mathematical basis for insurance optimization
Peters, O. (2011). The time resolution of the St Petersburg paradox. Philosophical Transactions of the Royal Society A, 369(1956), 4913-4931.
Key contribution: Resolution of classical paradox using time averages
Relevance: Historical context and motivation
Peters, O., & Adamou, A. (2018). The evolutionary advantage of cooperation. arXiv preprint.
arXiv: 1506.03414
Key contribution: Cooperation emerges from ergodic considerations
Relevance: Insurance as cooperative risk-sharing
Kelly Criterion and Growth
Kelly Jr, J. L. (1956). A new interpretation of information rate. The Bell System Technical Journal, 35(4), 917-926.
Key contribution: Original Kelly criterion formulation
Relevance: Optimal betting/investment strategy foundation
Thorp, E. O. (1971). Portfolio choice and the Kelly criterion. Proceedings of the Business and Economics Section of the American Statistical Association, 215-224.
Gwern Branwen: Full Text
Key contribution: Kelly criterion applied to portfolio management
Relevance: Extension to multiple assets and insurance
Multiplicative Processes
Redner, S. (1990). Random multiplicative processes: An elementary tutorial. American Journal of Physics, 58(3), 267-273.
DOI: 10.1119/1.16497
Key contribution: Accessible introduction to multiplicative processes
Relevance: Understanding wealth dynamics
Levy, M., & Solomon, S. (1997). New evidence for the power-law distribution of wealth. Physica A, 242(1-2), 90-94.
Key contribution: Empirical evidence for multiplicative wealth dynamics
Relevance: Real-world validation of theoretical models
Books and Textbooks
Sections are roughly in recommended study order. Books in each section are listed chronologically by latest publication date.
Ergodicity
Peters, O., & Adamou, A. (2025). An Introduction to Ergodicity Economics. LML Press.
ISBN: 978-1-0686491-3-4
Topics: Ergodicity and implications to individuals and populations
Kelly Criterion
MacLean, L. C., Thorp, E. O., & Ziemba, W. T. (2011). The Kelly capital growth investment criterion: Theory and practice. World Scientific.
ISBN: 978-981-4293-53-0
Key contribution: Comprehensive treatment of Kelly criterion
Actuarial Science
Klugman, S. A., Panjer, H. H., & Willmot, G. E. (2019). Loss Models: From Data to Decisions. John Wiley & Sons.
ISBN: 978-1-119-52378-9
Topics: Frequency-severity models, aggregate loss distributions
Risk Management
Hull, J. C. (2018). Risk Management and Financial Institutions. John Wiley & Sons.
ISBN: 978-1-119-44811-2
Topics: Market risk, credit risk, operational risk
Relevance: Comprehensive risk management overview
Sweeting, P. (2017). Financial Enterprise Risk Management. Cambridge University Press.
ISBN: 978-1-107-18461-9
Topics: ERM, extreme value theory, economic capital
McNeil, A. J., Frey, R., & Embrechts, P. (2015). Quantitative Risk Management: Concepts, Techniques and Tools. Princeton University Press.
ISBN: 978-0-691-16627-8
Topics: Risk measures, dependence modeling, extreme value theory
Relevance: Advanced risk management techniques
Statistics
Efron, B., & Hastie, T. (2021). Computer Age Statistical Inference. Cambridge University Press.
ISBN: 978-1-108-82341-8
Topics: Classical statistical methods, computationally-intense modern statistical methods
Taleb, N. N. (2020). Statistical Consequences of Fat Tails. STEM Academic Press.
ISBN: 978-1-5445-0805-4
Topics: Fat tails, metaprobability, options
Wasserman, L. (2005). All of Statistics. Springer.
ISBN: 0-387-40272-1
Probability, statistical inference, statistical models and methods
Aitchison, J., & Brown, J. A. C. (1976). The Lognormal Distribution. Cambridge University Press.
ISBN: 0-521-04011-6
Topics: Lognormal distribution monograph
Stochastic Processes
Øksendal, B. (2003). Stochastic Differential Equations: An Introduction with Applications.. Springer.
ISBN: 978-3-540-04758-2
Topics: Brownian motion, Itô calculus, SDEs
Ross, S. M. (2014). Introduction to Probability Models.. Academic Press.
ISBN: 978-0-12-407948-9
Topics: Markov chains, Poisson processes, queuing theory
Extreme Value Theory
Embrechts, P., Klüppelberg, C., & Mikosch, T. (2010). Modelling Extremal Events for Insurance and Finance. Springer.
ISBN: 978-3-540-60931-5
Topics: Heavy-tailed distributions, extreme value theory
de Haan, L., & Ferreira, A. (2006). Extreme Value Theory: An Introduction. Springer.
ISBN: 978-0-387-23946-0
Topics: Extreme value theory in finite- and infinite-dimensional settings
Beirlant, J., Goegebeur, Y., Segers, J., & Teugels, J. (2004). Statistics of Extremes: Theory and Applications. John Wiley & Sons.
ISBN: 978-0-471-97647-9
Topics: Statistical inference for extremes, applications
Ruin Theory
Asmussen, S., & Albrecher, H. (2010). Ruin Probabilities. World Scientific.
ISBN: 978-981-4282-52-9
Topics: Classical and modern ruin theory
Grandell, J. (1992). Aspects of Risk Theory. Springer.
ISBN: 978-0-387-97447-8
Topics: Compound Poisson processes, ruin probabilities
Optimal Control
Pham, H. (2009). Continuous-time Stochastic Control and Optimization with Financial Applications. Springer.
ISBN: 978-3-540-89499-5
Topics: Stochastic control, applications to insurance
Relevance: Insurance and investment optimization
Fleming, W. H., & Soner, H. M. (2006). Controlled Markov Processes and Viscosity Solutions. Springer.
ISBN: 978-0-387-26045-7
Topics: HJB equations, viscosity solutions
Relevance: Mathematical framework for optimal control
Portfolio Theory
Mildenhall, S. J., & Major, J. A. (2022) Pricing Insurance Risk. John Wiley & Sons.
ISBN: 978-1-119-75567-8
Risk, portfolio pricing, price allocation
Rebonato, R., & Denev, A. (2014). Portfolio Management Under Stress. Cambridge University Press
ISBN: 978-1-107-04811-9
Topics: Bayesian-net approach to coherent asset allocation
Luenberger, D. G. (2013). Investment Science. Oxford University Press.
ISBN: 978-0-19-974008-6
Topics: Portfolio optimization, asset pricing
Relevance: Investment theory foundations
Merton, R. C. (1992). Continuous-Time Finance. Blackwell.
ISBN: 978-0-631-18508-2
Topics: Optimal portfolio selection, consumption-investment
Relevance: Continuous-time optimization methods
Monte Carlo Methods
Robert, C. P., & Casella, G. (2004). Monte Carlo Statistical Methods. Springer.
ISBN: 978-0-387-21239-5
Topics: MCMC, convergence diagnostics, applications
Glasserman, P. (2003). Monte Carlo Methods in Financial Engineering. Springer.
ISBN: 978-0-387-00451-8
Topics: Variance reduction, importance sampling, quasi-Monte Carlo
Bootstrap Methods
Davison, A. C., & Hinkley, D. V. (1997). Bootstrap Methods and their Application. Cambridge University Press.
ISBN: 978-0-521-57391-7
Topics: Advanced bootstrap techniques, applications
Shao, J., & Tu, D. (1995). The Jackknife and Bootstrap. Springer.
ISBN: 978-0-387-94515-6
Jackknife, bootstrap, and other resampling methods
Efron, B., & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. Chapman and Hall/CRC.
ISBN: 978-0-412-04231-7
Topics: Bootstrap confidence intervals, hypothesis testing
Time Series Analysis
Tsay, R. S. (2010). Analysis of Financial Time Series. John Wiley & Sons.
ISBN: 978-0-470-41435-4
Topics: GARCH models, risk management, backtesting
Hamilton, J. D. (1994). Time Series Analysis. Princeton University Press.
ISBN: 978-0-691-04289-3
Topics: State space models, filtering, forecasting
Software and Tools
Python Libraries
chainladder-python
Website: chainladder-python.readthedocs.io
Documentation: chainladder-python user guide
Usage: Actuarial functions specializing in reserving
Matplotlib/Seaborn
Matplotlib: matplotlib.org
Seaborn: seaborn.pydata.org
Usage: Data visualization
NumPy
Website: numpy.org
Documentation: numpy.org/doc
Usage: Numerical computing foundation
Pandas
Website: pandas.pydata.org
Documentation: pandas.pydata.org/docs
Usage: Data manipulation and analysis
quActuary
Website: quactuary.com
Documentation: docs.quactuary.com
Usage: Presently offers a strong simulation framework and an extensive library of actuarial distributions
SciPy
Website: scipy.org
Documentation: docs.scipy.org
Usage: Scientific computing and optimization
Actuarial Software
Commercial Tools
@RISK: Monte Carlo simulation add-in for Excel
Online Resources
Educational Websites
Casualty Actuarial Society (CAS)
Website: casact.org
Resources: Property-casualty focus, research
Relevance: Non-life insurance expertise
London Mathematical Laboratory
Website: lml.org.uk
Resources: Ergodic economics research and tutorials
Society of Actuaries (SOA)
Website: soa.org
Resources: Research papers, educational materials
Relevance: Professional actuarial resources
Online Courses
Coursera
“Financial Engineering and Risk Management” (Columbia University)
“Introduction to Actuarial Science” (University of Pennsylvania)
Website: coursera.org
edX
“Introduction to Investments” (IIMB)
“Risk Management in Banking and Financial Institutions” (NYIF)
Website: edx.org
Blogs and Forums
Ergodicity Economics
Content: Blog posts on ergodic theory applications
Quantitative Finance Stack Exchange
Content: Q&A for quantitative finance professionals
Implementation Examples
Jupyter Notebooks
Ergodic Insurance Optimization
Current project notebooks in
/notebooks/
directoryTopics: Manufacturer simulation, optimization, validation
Language: Python
Citation Guidelines
How to Cite This Work
APA Format:
Filiakov, A. (2025). Ergodic Insurance Limits: Optimizing insurance using time-average growth [Software]. GitHub.
https://ergodicityadvantage.com
BibTeX:
@software{ergodicinsurancelimits,
author = {Filiakov, Alex},
title = {Ergodic Insurance Limits: Optimizing insurance using time-average growth},
year = {2025},
publisher = {GitHub},
url = {https://ergodicityadvantage.com}
}
Acknowledgments
This project builds upon the foundational work of Ole Peters and the London Mathematical Laboratory in developing ergodic economics. I also acknowledge the contributions of the actuarial and quantitative finance communities in developing the mathematical tools and frameworks used in this implementation.
Updates and Corrections
For updates to this reference list or to suggest additional resources, please:
Open an issue on GitHub
Submit a pull request with additions
Contact the maintainers
Last updated: September 2025 Version: 0.3.0
Verification Note
All references have been verified as of September 2025. Some resources may change over time. For the most current information:
Check DOI links for academic papers
Visit organization websites directly
Search GitHub for latest community implementations
Consult academic databases for recent publications