1. Professional Profile
  2. Research Interests
  3. Working Papers
  4. Higher Education
  5. Awards
  6. Projects
  7. Technical Skills
  8. Employment
  9. Volunteering
  10. References

Professional Profile ๐Ÿ’ผ

Recent graduate of Lancaster University (a top-ranked UK university per the Times and Sunday Times rankings), graduated in 2018 with a First Class Honours BSc in Mathematics with Statistics, graduated summa cum laude in 2021 with a Distinction MSc in Quantitative Finance. Commencing doctoral study in Statistics and Applied Probability with an emphasis on Financial Mathematics and Statistics at the University of California Santa Barbara in fall of 2022.

Research Interests ๐Ÿ”ฌ

Research interests orientated towards machine learning, computational statistics and stochastic processes with specific interest in modelling high-dimensional stochastic processes and the applications of machine learning in portfolio construction, risk modelling, and returns forecasting.

Working Papers ๐Ÿ“„

  1. Measuring and Forecasting Mutual Fund Survival Capacity using Machine Learning Algorithms, with Dr George Wang (Lancaster University Management School) and Ian Dโ€™Souza (NYU Stern).

Higher Education ๐ŸŽ“

MSc Quantitative Finance - Distinction (Class Rank: 1st)
Lancaster University (2020-2021)

Supervisors: Professor George Wang (Lancaster University), Professor Ian D’Souza (NYU Stern).

Dissertation Title: Measuring and Forecasting Mutual Fund Survival Capacity using Machine Learning Algorithms. (Dissertation Result: 86%)

Topics Studied: (1) Foundations in Financial Markets, (2) Derivatives Pricing, (3) Financial Econometrics, (4) Market Risk Forecasting and Control, (5) Stochastic Calculus for Finance, (6) Financial Stochastic Processes, (7) Statistical Methods for Financial and Economic Applications, (8) Assessing Financial Risk: Extreme Value Methods, (9) Spreadsheet Modelling for Quantitative Finance and (10) Forecasting.

Topics Audited: (1) Python Programming and (2) Data Mining.

BSc Mathematics with Statistics - First Class Honours
Lancaster University (2013-2018)

Topics Studied: (1) Metric Spaces, (2) Differential Equations, (3) Combinatorics, (4) Likelihood Inference, (5) Bayesian Inference, (6) Statistical Modelling, (7) Time Series Analysis, (8) Real Analysis, (9) Complex Analysis, (10) Linear Algebra, (11) Groups and Rings, (12) Probability and (13) Statistics.

Awards ๐Ÿ†

  1. Award for Best Academic Performance 2020/21
    Awarded in recognition of exceptional academic performance in obtaining the highest GPA on the MSc Quantitative Finance programme at Lancaster University in the 2020/21 academic year.

  2. Award for Best Dissertation Results 2020/21
    Awarded in recognition of obtaining the highest dissertation results on the MSc Quantitative Finance programme at Lancaster University in the 2020/21 academic year.

  3. Lancaster Gold Award
    Awarded in recognition of skills obtained in activities outside of academia whilst at university. These include: (1) Obtaining a digital skills certificate, (2) Charity Work, (3) Work Experience, (4) Student Academic Representative, and (5) Career Mentoring Programme.

Projects ๐Ÿ“

  1. Implementing the Black-Scholes and Vasicek models to determine the price of European call options on stock and bonds respectively.
    Author: J.R. Inston, Supervisor: Dr A. Khaleghi, Topic: Stochastic Processes in Finance, Date: November 30, 2020, Programming Language: R.

  2. Comparing the performance of the ARMA-GARCH and HAR-RV models in forecasting the volatility of high-frequency stock trade-and-quote data.
    Authors: J.R. Inston, T.H.K. Cheng, J. Weng, A. Alao, Z. Xu, Supervisors: Dr S. Nolte, Dr I. Nolte, Topic: Financial Econometrics, Date: March 16, 2021, Programming Language: MATLAB.

  3. Calculating the Value-at-Risk (VaR) of the S&P 100 using Generalised Autoregressive Conditional Heteroscedasticity (GARCH) models.
    Author: J.R. Inston, Supervisor: Dr S. Grรผnewalder, Topic: Statistical Methods for Financial and Economic Applications, Date: December 18, 2020, Programming Language: R.

  4. Valuing Existing Off-Market Swaps.
    Authors: J.R. Inston, A. Alao, T.H.K. Cheng, Z. Xu, M. Ge, Supervisors: Dr T. Ho, Dr J. Huan, Topic: Derivatives Pricing, Date: April 26, 2021.

  5. Calculating Value-at-Risk and Expected Shortfall (ES) using the fitted Generalised Pareto Distribu- tion and the modelling of non-normal GARCH model residuals.
    Author: J.R. Inston, Supervisors: C. Lee, Z. Varty, Topic: Assessing Financial Risk: Extreme Value Methods, Date: April 17, 2021, Programming Language: R.

  6. Modelling using exponential smoothing, ARIMA, and time series regression models.
    Author: J.R. Inston, Supervisor: Dr S.F. Crone, Topic: Forecasting, Date: April 22, 2021, Programming Language: R.

Technical Skills ๐Ÿ’ป

  • Python - Highly Proficient
  • R / RMarkdown - Highly Proficient
  • LaTeX / Technical Writing - Highly Proficient
  • MATLAB - Proficient
  • SAS - Proficient

Employment ๐Ÿข

Online Mathematics & Statistics Tutor
MyTutor (2018-Present)

Online mathematics and statistics tutor on MyTutor, the largest online tutoring platform in the UK.


  • Tutoring maths, statistics, science and geography to GCSE, A-level and undergraduate students across the UK.
  • Devising and delivering interactive teaching sessions.
  • Preparing question sheets, trial exams, lesson presentations and revision material.
  • Independently managing and scheduling weekly sessions with up to 15 students.

Trainee Tax Advisor
Forbes Dawson (2019-2020)

Company Details
Address: Fairbank House, Ashley Road, Altrincham, WA14 2DP
Phone: +44 (0)161 927 9277

Full-time work as a trainee tax advisor at Forbes Dawson, a specialist firm of tax advisors and accountants in Altrincham England.


  • Preparing detailed research reports detailing the tax treatment of complex financial transactions and company restructurings.
  • Satisfying the tax reporting requirements of hundreds of clients ranging from high net-worth individuals to limited companies.

Volunteering ๐ŸŒณ

Academic Representative
Lancaster University (2020-2021)

Unpaid work as the elected academic representative of the quantitative finance students.


  • Gathering feedback from quantitative finance students via email, online messages and zoom meetings due to the restrictions of online learning.
  • Attending faculty meetings in 4 different departments and presenting the feedback from my fellow students, reporting any problems with online learning, lectures, documents and assignments.
  • Safeguarding the mental health of my fellow students, providing anonomous feedback on potential sources of difficulty and student anxiety during a global pandemic.

Volunteer Ranger
National Trust (2019-2020)

Weekend volunteering as a ranger at the National Trust’s estate at Marsden Moor, a large expanse of moorland in the South Pennines, England.


  • Creating natural fire breaks by planting sphagnum moss, a moisture rich flame retardant plant species.
  • Repairing tourist paths, fences, styals and gates to help reduce the harmful impacts of fell runners and hikers.

Whale & Dolphin Conservation (2019-2020)

Fundraising and volunteering for the Whale & Dolphin Conservation.


  • Raising money through sponsored runs.
  • Participating in beach / urban beach cleanings.

References ๐Ÿ‘ฉโ€๐Ÿ”ฌ

  1. Dr George Wang - Associate Professor and Senior Lecturer at Lancaster University (UK).
  2. Dr Sandra Nolte - Senior Lecturer and Head of Department at Lancaster University (UK).
  3. Ian D’Souza - Adjunct Professor at NYU Stern Business School (USA).