Prof. Dr. Gareth W. Peters 
(FIOR, SIRM, FRSS, FIMA, YAS-RSE, CStat-RSS, CMath-FIMA)
 
Janet & Ian Duncan Endowed Chair of Actuarial Science,
Chair Prof. of Statistics for Risk and Insurance,

Department of Statistics & Applied Probability
University of California Santa Barbara (UCSB) 
 






Currently:

Edinburgh HW:

Lecturing: developed and delivering new MSc Actuarial Course
Machine Learning for Risk and Insurance
(Actuarial Masters Year Long Course)​

News Items:

Presenting 3-day workshop on Machine Learning for the IABE Institute of Actuaries Belgium (Dec)

Presenting an invited talk at ICMA mathematics conference in Mahidol University Thailand (Dec)

Recent Travels:

None in 2020

QRSLab        

​

Specializing in Statistical Solutions in Risk and Insurance:

Theory, Methodology and Practice

 

RESEARCH

AREAS​

​

  • Statistical Risk Management
  • Statistical Insurance
  • Monte Carlo Methods and Sampling
  • Agricultural Finance, Green Finance and Urban Finance
  • Algorithmic Trading and High Frequency Finance
  • Statistical Finance and Econometrics
  • Bayesian Modelling and Methodology
  • Regulations Research
  • Blockchain and Virtual Currency
  • Spatial and Temporal Modelling
Statistical Risk Management

Quantitative modelling: 

  • Operational Risk, Credit Risk, Market Risk

Statistical Insurance

Quantitative modelling for:

  • Non-Life and General Insurance; 

  • Longevity and mortality modelling; 

  • Usage based Insurance

  • Catastrophe Modelling and Catstrophe Bonds

​

Regulations Research

Expertise in financial regulation:

  • Basel I, II, 2.5, III - Operational Risk, Credit Risk, Market Risk

  • Stress Testing 

  • Solvency II and Swiss Solvency Test

  • Exchange Regulations: MiFID, MiFID II, MiFIR, Dodd-Frank, REMIT, T2S, Reg NMS..

 
Statistical Finance and Econometrics​

  • Multifactor models for Commodities

  • Dynamic Cointegration Modelling 

  • State Space Modelling 

  • Index Models

  • Portfolio Allocation Methods

Algorithmic Trading and High Frequency Finance

  • Lit and Dark Limit Order Book Stochastic Modelling

  • Commodities, Currency, Equity, Bonds, Sports Markets.

  • Carry Trades

  • Crush Trades

  • Convexity Trades

​

Agricultural Finance, Green Finance and Urban Finance

  • Green Bonds

  • Agricultural Modelling

  • Farming and Crop Insurance

  • Smart City and Urban Analytics Finance

Blockchain and Virtual Currency

  • Blockchain applications

  • Blockchain regulations

  • Virtual Currency and Economics 

Spatial and Temporal Modelling

  • Spatial-Temporal Models

  • Sensor Networks

  • Signal Processing

Bayesian Modelling and Sampling Methodology

  • Hierarchical Bayesian Models

  • Prior Ellicitation Methods

  • Monte Carlo Methods: 

Sequential Monte Carlo

Markov Chain Monte Carlo

Indirect Inference

Approximate Bayesian Computation​

OUR VISION

The agenda of this laboratory is to produce innovative and cutting edge statistical solutions to modelling in applied Financial risk and Insurance.

​

We focus on innovative and emerging areas of high impact to research, regulators, industry and practitioners that require research level academic developments both of a fundamental nature and a practical quantitative nature.

​

This laboratory is specifically interested in modelling applied numerical and methodological financial risk problems of signficance in the financial industry and regulators - as such it aims to develop strategic partnership of a research nature with industry.  

​

Big data analytics in risk and insurance is an emerging field that is covered in many reserach themes in this laboratory

​

The QRSLab is a collective of many different research skills and expertise in multidisciplinary working group.

​

IF YOU ARE INTERESTED IN COLLABORATION OPPORTUNITIES WITH THE QRSLab ON RESEARCH PROJECTS or honours, MSc., Ph.D. or Post doctoral opportunities - see contact information .

​

​

The axioms of Frederico Ardila (Todo Cuentan) nicely capture some axiomatic principles which we subscribe to in QRSLab.

 

Axiom 1. Mathematical potential is distributed equally among different groups, irrespective of geographic, demographic, and economic boundaries.

Axiom 2. Everyone can have joyful, meaningful, and empowering mathematical experiences.

Axiom 3. Mathematics is a powerful, malleable tool that can be shaped and used differently by various communities to serve their needs.

Axiom 4. Every student deserves to be treated with dignity and respect.

​

​

 

QRSLab Researchers

Dr. Gareth W. Peters (FIOR, YAS-RSE)

PhD. Statistics, MSc. (Research Cambridge),

BSc. (hons 1st), BEng (hons 1st) Uni. Melb.

​

Current Research Affiliations 

​

  1. Elected Fellow of the Young Academy of Scotland - Royal Society of Edinburgh (YAS-RSE).

  2. Elected Fellow of the Institute of Operational Risk Professionals.

  3. Visiting Fellow and Theme Leader for Insurance in Alan Turing Institute.

  4. Honorary Prof. of Statistics at University College London, 2018+

  5. Core Member of Edinburgh University Centre for Statistics.

  6. Affiliated Prof. of Statistics in University of New South Wales Australia 2015+ 

  7. Affiliate Member of Systemic Risk Center, London School of Economics 2014+

  8. Affiliate Member of Oxford Mann Institute, Oxford University (OMI) 2013+

  9. Honorary Prof. of Statistics in University of Sydney Australia 2018+

  10. Honorary Prof. of Statistics in Maquarie University, Australia 2018+ 

  11. Visiting Prof. in Institute of Statistical Mathematics, Tokyo, Japan 2009-2018+

​​

Previous Research Affiliations 

​

  1. Adjunct Scientist: Mathematics, Informatics and Statistics, Commonwealth Scientific and Industrial Research Organisation (CSIRO) - Australia. 2009 - 2016.

  2. Principle Investigator in CSML , University College London (UCL) 2011-2017

  3. Academic Member: UK PhD Center in Financial Computing (UCL); 2012-2017

  4. Affiliated Prof. School of Earth and Space Sciences, Peking University PKU, Beijing, China 2015+

​

​

Membership of Societies
 

  1. Fellow of the Institute of Operational Risk Practitioners, London, UK.

  2. International Society of Bayesian Analysis (ISBA)

  3. Royal Statistical Society RSS, UK

  4. YAS Royal Society of Edinburgh, UK

​

Postdoctoral Researchers

Working on Functional Data Analysis for Insurance.

Dr. Dorota Toczydłowska

Based at University of Technology Sydney (UTS) - joint with Prof. Matthew Wand and Prof. Louise Ryan

Advanced Machine Learning research in crypto-currencies 

Anna Zaremba (Ph.D. Submitted - to be defended after COVID-19)

Crypto-ML Research Member

◄

1 / 1

►

Please reload

Ph.D. Researchers

PhD. Topic: Machine Learning Methods for Credit Portfolio Analytics

​

Supervisors: Prof. Gareth W. Peters and Prof. Mike Chantler

Edward Antonian (2019+)

Heriot-Watt Edinburgh and Royal Bank of Scotland

PhD. Topic: Machine Learning Methods for Credit Portfolio Analytics

​

Supervisors: Prof. Gareth W. Peters and Prof. Mike Chantler

Cole Van Jaarsveldt (2019+)

Heriot-Watt Edinburgh and Royal Bank of Scotland

PhD. Topic: Data Combining Methods

Supervisors: Prof. Gareth W. Peters and Prof. Mike Chantler

Pasin Marupanthorn (2019+)

Heriot-Watt Edinburgh

PhD. Topic:  Hidden Markov Models and Finance

​

Supervisors: Dr. Guido Germano, Dr. Gareth W. Peters  and Dr. Kostas Manolarkis

Andreas Koukorinis (2013+)

Set up Hedge Fund STRATAGEM London

PhD. Topic: Non-Stationary Basis Decompositions and Stable Processes

​

Supervisors: Dr. Gareth W. Peters and Dr. Nourddine Azzaoui

Marta Campi (2016+)

PhD. Topic: Machine Learning Methods for Momentum Strategies

​

Supervisors: Dr. Gareth W. Peters and Dr. Franz Kiraly

Fabio Dias (2016+)

Barclays Bank London

◄

1 / 1

►

Please reload

CONTACT

Dr. Gareth W. Peters

QRSLab

OUR ADDRESS

Department of Actuarial Mathematics and Statistics, ​

Heriot-Watt University

Edinburgh, Scotland, UK

Email: garethpeters@ucsb.edu
Tel:  email best

Tel:  email best

​

Office Number:

CM G.03 Edinburgh Campus, Riccarton, Heriot-Watt (Gate 1)

​

For any general inquiries, please fill in the following contact form:

Success! Message transmitted.