If you made any changes in Pure these will be visible here soon.

Research Outputs 1995 2020

2020

Which risk factors drive oil futures price curves?

Ames, M., Bagnarosa, G., Matsui, T., Peters, G. & Shevchenko, P. V., 17 Jan 2020, In : Energy Economics. 104676.

Research output: Contribution to journalArticleResearchpeer-review

Stochastic models
Oil
Risk factors
Futures prices
Oils
2019

Cohort effects in mortality modelling: a Bayesian state-space approach

Fung, M. C., Peters, G. W. & Shevchenko, P. V., Mar 2019, In : Annals of Actuarial Science. 13, 1, p. 109-144 36 p.

Research output: Contribution to journalArticleResearchpeer-review

Cohort
Mortality
Modeling
Cohort effect
State space

On the parameter estimation in the Schwartz-Smith's two-factor model

Binkowski, K., He, P., Kordzakhia, N. & Shevchenko, P., 2019, Statistics and data science: Research School on Statistics and Data Science, RSSDS 2019 Melbourne, VIC, Australia, July 24–26, 2019 proceedings. Nguyen, H. (ed.). Singapore: Springer, Springer Nature, p. 226-237 12 p. (Communications in Computer and Information Science; vol. 1150).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Kalman filters
Parameter estimation
Maximum likelihood
Identification (control systems)
Costs

The impact of model risk on dynamic portfolio selection under multi-period mean-standard-deviation criterion

Penev, S., Shevchenko, P. V. & Wu, W., 1 Mar 2019, In : European Journal of Operational Research. 273, 2, p. 772-784 13 p.

Research output: Contribution to journalArticleResearchpeer-review

Portfolio Selection
Standard deviation
Quantify
Uncertainty
Kullback-Leibler Divergence
2018

Ageing population risks

Shevchenko, P. (ed.), 2018, Basel: Multidisciplinary Digital Publishing Institute (MDPI). 224 p.

Research output: Book/ReportEdited Book/AnthologyResearchpeer-review

Open Access
File
open access
edition

Special issue “ageing population risks”

Shevchenko, P. V., 1 Mar 2018, In : Risks. 6, 1, 2 p., 16.

Research output: Contribution to journalEditorialResearch

Open Access
File

Statistical machine learning analysis of cyber risk data: event case studies

Peters, G. W., Shevchenko, P. V., Cohen, R. D. & Maurice, D. R., 19 Feb 2018, Fintech: Growth and Deregulation. Maurice, D., Fairman, D. & Freund, J. (eds.). United Kingdom: Risk Books, p. 75-99 25 p.

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Machine learning
Insurance risk
Event risk
Taxonomy
Statistical methods

The Impact of management fees on the pricing of variable annuity guarantees

Sun, J., Shevchenko, P. V. & Fung, M. C., Sep 2018, In : Risks. 6, 3, 20 p., 103.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File
Variable annuities
Pricing
Management fees
Guarantee
Fees

Understanding cyber-risk and cyber-insurance

Peters, G. W., Shevchenko, P. V. & Cohen, R. D., 19 Feb 2018, Fintech: Growth and Deregulation. Maurice, D., Fairman, D. & Freund, J. (eds.). United Kingdom: Risk Books, p. 303-330 28 p.

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Insurance
Management practices
Industry
Mitigation
Emerging markets

Understanding the interplay between covariance forecasting factor models and risk‐based portfolio allocations in currency carry trades

Ames, M., Bagnarosa, G., Peters, G. W. & Shevchenko, P. V., Dec 2018, In : Journal of Forecasting. 37, 8, p. 805-831 27 p.

Research output: Contribution to journalArticleResearchpeer-review

Currency
Factor Models
Forecasting
Heteroskedasticity
Risk Measures
2017

Actuarial applications and estimation of extended CreditRisk⁺

Hirz, J., Schmock, U. & Shevchenko, P. V., 2017, In : Risks. 5, 2, p. 1-29 29 p., 23.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File
Mortality
Model
Expected Shortfall
Joint Modeling
Credit Risk

Assessment of policy changes to means-tested age pension using the expected utility model: implication for decisions in retirement

Andreasson, J. & Shevchenko, P. V., 2017, In : Risks. 5, 3, p. 1-21 21 p., 47.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File
Expected utility
Retirement
Policy change
Pensions
Income

A unified approach to mortality modelling using state-space framework: characterisation, identification, estimation and forecasting

Fung, M. C., Peters, G. W. & Shevchenko, P. V., Sep 2017, In : Annals of Actuarial Science. 11, 2, p. 343-389 47 p.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File
Mortality
State-space modeling
Stochastic volatility
Heteroscedasticity
Stochastic volatility model

Crunching mortality and life insurance portfolios with extended CreditRisk+

Hirz, J., Schmock, U. & Shevchenko, P., 2017, In : Risk. 2017, January, p. 98-103 6 p.

Research output: Contribution to journalArticleResearchpeer-review

Forecasting covariance for optimal carry trade portfolio allocations

Ames, M., Bagnarosa, G., Peters, G. W., Shevchenko, P. & Matsui, T., 16 Jun 2017, 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers (IEEE), p. 5910-5914 5 p. 7953290

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Machine learning techniques for mortality modeling

Deprez, P., Shevchenko, P. V. & Wüthrich, M. V., 1 Dec 2017, In : European Actuarial Journal. 7, 2, p. 337-352 16 p.

Research output: Contribution to journalArticleResearchpeer-review

Mortality
Machine Learning
Mortality Rate
Modeling
Stochastic Model

Optimal consumption, investment and housing with means-tested public pension in retirement

Andréasson, J. G., Shevchenko, P. V. & Novikov, A., Jul 2017, In : Insurance: Mathematics and Economics. 75, p. 32-47 16 p.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
Asset Allocation
Life Expectancy
Expected Utility
Maximum Likelihood Method
Stochastic Control

Optimal exercise strategies for Operational Risk insurance via multiple stopping times

Targino, R. S., Peters, G. W., Sofronov, G. & Shevchenko, P. V., 2017, In : Methodology and Computing in Applied Probability. 19, 2, p. 487-518 32 p.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File
Operational Risk
Stopping Time
Insurance
Exercise
Annual

Stochastic period and cohort effect state-space mortality models incorporating demographic factors via probabilistic robust principal components

Toczydlowska, D., Peters, G., Fung, M. C. & Shevchenko, P. V., 2017, In : Risks. 5, 3, p. 1-77 77 p., 42.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File
Stochastic models
Feature extraction
Model structures
Markov processes
Sampling

Valuation of barrier options using sequential Monte Carlo

Shevchenko, P. V. & del Moral, P., 1 Apr 2017, In : Journal of Computational Finance. 20, 4, p. 107-135 29 p.

Research output: Contribution to journalArticleResearchpeer-review

Barrier Options
Sequential Monte Carlo
Sequential Monte Carlo Methods
Valuation
Monte Carlo methods

Valuation of variable annuities with Guaranteed Minimum Withdrawal Benefit under stochastic interest rate

Shevchenko, P. V. & Luo, X., 1 Sep 2017, In : Insurance: Mathematics and Economics. 76, p. 104-117 14 p.

Research output: Contribution to journalArticleResearchpeer-review

Stochastic Interest Rates
Interest Rates
Valuation
Pricing
Transition Density
2016

A Unified pricing of variable annuity guarantees under the optimal stochastic control framework

Shevchenko, P. & Luo, X., Sep 2016, In : Risks. 4, 3, p. 1-31 31 p., 22.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File
Stochastic optimal control
Variable annuities
Pricing
Guarantee
Investors

Historical backtesting of local volatility model using AUD/USD vanilla option

Ling, T. G. & Shevchenko, P. V., 1 Jan 2016, In : ANZIAM Journal. 57, 3, p. 319-338 20 p.

Research output: Contribution to journalArticleResearchpeer-review

Volatility
Hedging
Implied Volatility
Black-Scholes Model
Model

Should the advanced measurement approach be replaced with the standardized measurement approach for operational risk?

Peters, G. W., Shevchenko, P. V., Hassani, B. & Chapelle, A., 1 Sep 2016, In : Journal of Operational Risk. 11, 3, p. 1-49 49 p.

Research output: Contribution to journalArticleResearchpeer-review

Operational risk
Risk capital
Basel Committee
Standardization
Systemic risk

Standardized Measurement Approach for Operational risk: Pros and Cons

Peters, G. W., Shevchenko, P. V., Hassani, B. & Chapelle, A., 4 Jun 2016, Basel, Switzerland: Bank for International Settlements. 18 p.

Research output: Book/ReportCommissioned reportResearch

Industry
2015

Advances in heavy tailed risk modeling: a handbook of operational risk

Peters, G. W. & Shevchenko, P. V., 2015, Hoboken, New Jersey: John Wiley & Sons. 627 p. (Wiley handbooks in financial engineering and econometrics)

Research output: Book/ReportBookResearchpeer-review

Operational Risk
Modeling
Insurance
Risk Management
Risk management

A State-space estimation of the Lee-Carter mortality model and implications for annuity pricing

Fung, M. C., Peters, G. W. & Shevchenko, P. V., 2015, MODSIM 2015: 21st International Congress on Modelling and Simulation : Proceedings. Canberra: Modelling & Simulation Society Australia & New Zealand, p. 952-958 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Annuities
State space
Mortality rate
Mortality
Pricing

Fast numerical method for pricing of variable annuities with guaranteed minimum withdrawal benefit under optimal withdrawal strategy

Luo, X. & Shevchenko, P. V., Sep 2015, In : International journal of financial engineering. 2, 3, p. 1550024-1-1550024-26 26 p.

Research output: Contribution to journalArticleResearchpeer-review

Numerical methods
Variable annuities
Pricing
Finite difference method
Partial differential equations

Forecasting leading death causes in Australia using extended CreditRisk+

Shevchenko, P. V., Hirz, J. & Schmock, U., 2015, MODSIM2015: 21st International Congress on Modelling and Simulation : Proceedings. Canberra, ACT: Modelling & Simulation Society Australia & New Zealand, p. 966-972 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Annuities
Mortality
Scenarios
Health
Stress testing

From 'funny time, funny money' to realistic labour times

Luo, X., Shevchenko, P. V. & Sayer, B., 1 Dec 2015, In : The Mathematical Scientist. 40, 2, p. 118-127 10 p.

Research output: Contribution to journalArticleResearchpeer-review

Paint
Personnel
Industry
Statistical methods
Drying

Fundamental aspects of operational risk and insurance analytics: a handbook of operational risk

Cruz, M. G., Peters, G. W. & Shevchenko, P. V., 2015, Hoboken, NJ: John Wiley & Sons. 899 p.

Research output: Book/ReportBookResearchpeer-review

Operational risk
Insurance
Modeling
Risk model
Basel II

Holder-extendible European option: corrections and extensions

Shevchenko, P. V., Apr 2015, In : ANZIAM Journal. 56, 4, p. 359-372 14 p.

Research output: Contribution to journalArticleResearchpeer-review

European Options
Dividend
Interest Rates
Geometric Brownian Motion
Volatility

Operational risk

Shevchenko, P. V., 2015, Investment risk management. Baker, H. K. & Filbeck, G. (eds.). New York, NY: Oxford University Press, p. 119-140 22 p. (Financial markets and investments series).

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Pricing TARNs using a finite difference method

Luo, X. & Shevchenko, P. V., 1 Sep 2015, In : Journal of Derivatives. 23, 1, p. 62-72 11 p.

Research output: Contribution to journalArticleResearchpeer-review

Pricing
Finite difference
Finite difference method
Monte Carlo method
Foreign exchange

Sequential Monte Carlo Samplers for capital allocation under copula-dependent risk models

Targino, R. S., Peters, G. W. & Shevchenko, P. V., 1 Mar 2015, In : Insurance: Mathematics and Economics. 61, p. 206-226 21 p.

Research output: Contribution to journalArticleResearchpeer-review

Sequential Monte Carlo
Conditional Expectation
Copula
Rare Events
Risk Measures

Valuation of variable annuities with guaranteed minimum withdrawal and death benefits via stochastic control optimization

Luo, X. & Shevchenko, P. V., 1 May 2015, In : Insurance: Mathematics and Economics. 62, p. 5-15 11 p.

Research output: Contribution to journalArticleResearchpeer-review

Stochastic Control
Valuation
Optimization
Optimal Stochastic Control
Financial Risk

Variable Annuity with GMWB: surrender or not, that is the question

Luo, X. & Shevchenko, P. V., 2015, MODSIM2015: 21st International Congress on Modelling and Simulation : Proceedings. Canberra, ACT: Modelling & Simulation Society Australia & New Zealand, p. 959-965 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Variable annuities
Surrender option
Maturity
Optimal strategy
Fees
2014

Fast and simple method for pricing exotic options using Gauss–Hermite quadrature on a cubic spline interpolation

Luo, X. & Shevchenko, P. V., 2014, In : Journal of financial engineering. 1, 4, p. 1450033-1-1450033-31 31 p.

Research output: Contribution to journalArticleResearchpeer-review

Quadrature
Pricing
Interpolation
Exotic options
Cubic spline
2013

Calibration and filtering for multi factor commodity models with seasonality: incorporating panel data from futures contracts

Peters, G. W., Briers, M., Shevchenko, P. & Doucet, A., Dec 2013, In : Methodology and Computing in Applied Probability. 15, 4, p. 841-874 34 p.

Research output: Contribution to journalArticleResearchpeer-review

Seasonality
Panel Data
Calibration
Filtering
Model

Loss distribution approach for operational risk capital modelling under Basel II: combining different data sources for risk estimation

Shevchenko, P. V. & Peters, G. W., 2013, In : Journal of Governance and Regulation. 2, 3, p. 33-57 25 p.

Research output: Contribution to journalArticleResearchpeer-review

requirements
industries
products

Markov Chain Monte Carlo estimation of default and recovery: dependent via the latent systematic factor

Luo, X. & Shevchenko, P. V., 1 Sep 2013, In : Journal of Credit Risk. 9, 3, p. 41-76 36 p.

Research output: Contribution to journalArticleResearchpeer-review

Markov chain Monte Carlo
Factors
Latent factors
Parameter uncertainty
Uncertainty

Understanding operational risk capital approximations: first and second orders

Peters, G. W., Targino, R. S. & Shevchenko, P. V., 2013, In : Journal of Governance and Regulation. 2, 3, p. 58-78 21 p.

Research output: Contribution to journalArticleResearchpeer-review

Risk capital
Approximation
Operational risk
Severity
Basel

When to bite the bullet? - A Study of optimal strategies for reducing global warming

Luo, X. & Shevchenko, P. V., 2013, MODSIM 2013: Proceedings of the 20th International Congress On Modelling And Simulation. Piantadosi, J., Anderssen, R. S. & Boland, J. (eds.). Canberra, ACT: Modelling and Simulation Society of Australia and New Zealand, p. 1447-1453 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Optimal strategy
Global warming
Damage
Costs
Stopping rule
2012

Bayesian model choice of grouped t-copula

Luo, X. & Shevchenko, P. V., 2012, In : Methodology and Computing in Applied Probability. 14, 4, p. 1097-1119 23 p.

Research output: Contribution to journalArticleResearchpeer-review

Model Choice
Copula
Bayesian Model
Foreign Exchange Rates
Copula Models
2011

Analytic loss distributional approach models for operational risk from the α-stable doubly stochastic compound processes and implications for capital allocation

Peters, G. W., Shevchenko, P. V., Young, M. & Yip, W., Nov 2011, In : Insurance: Mathematics and Economics. 49, 3, p. 565-579 15 p.

Research output: Contribution to journalArticleResearchpeer-review

Operational Risk
Annual
Model
Increment
Capital allocation

A short tale of long tail integration

Luo, X. & Shevchenko, P. V., Apr 2011, In : Numerical Algorithms. 56, 4, p. 577-590 14 p.

Research output: Contribution to journalArticleResearchpeer-review

Tail
Truncation Error
End point
Numerical integration
Discretization Error

A structured model for estimation of automotive paint labour times

Luo, X., Shevchenko, P. V., Sayer, B., Blackhall, W. & Coelho, C., 2011, In : ANZIAM Journal. 53, SUPPL, p. C422-C436 15 p.

Research output: Contribution to journalArticleResearchpeer-review

Directly proportional
Masking
Spray
Flash
Perimeter

Dependent default and recovery: Markov Chain Monte Carlo study of downturn loss given default credit risk model

Shevchenko, P. V. & Luo, X., 2011, In : ANZIAM Journal. 53, SUPPL, p. C185-C202 18 p.

Research output: Contribution to journalArticleResearchpeer-review

Default Risk
Credit Risk
Monte Carlo Study
Markov Chain Monte Carlo
Recovery

Impact of insurance for operational risk: Is it worthwhile to insure or be insured for severe losses?

Peters, G. W., Byrnes, A. D. & Shevchenko, P. V., Mar 2011, In : Insurance: Mathematics and Economics. 48, 2, p. 287-303 17 p.

Research output: Contribution to journalArticleResearchpeer-review

Operational Risk
Insurance
Scenarios
Annual
Analytic Solution

Modelling operational risk using Bayesian inference

Shevchenko, P. V., 2011, Berlin; Heidelberg: Springer, Springer Nature. 302 p.

Research output: Book/ReportBookResearchpeer-review

Operational Risk
Bayesian inference
Banking
Modeling
Industry