AIFMRM’s research objective is to advance the theory and application of modern quantitative, statistical and mathematical techniques to the modelling and risk management of financial products and markets. We are primarily interested in the application of these techniques to African and South African contexts. The Institute undertakes to engender a culture of research excellence, provide research mentorship to staff and students, encourage entrepreneurial activity and develop research capacity.

  •  Kulikova, M.V., Taylor, D.R. and Kulikov, G.Y. 2024. Evolving efficiency of the BRICS markets. Economic Systems. 48(1):101166.
  • Macrina, A., Mengütürk, L.A. and Mengütürk, M.C. 2024. Captive jump processes for bounded random systems with discontinuous dynamics. Communications in Nonlinear Science and Numerical Simulation. 128:107646.
  • Moutanabbir, K. and Bouaddi, M. 2024. A new non-parametric estimation of the expected shortfall for dependent financial losses. Journal of Statistical Planning and Inference. 232:106151.
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  • Backwell, A., Macrina, A., Schlögl, E. and Skovmand, D. 2023. Term rates, multicurve term structures and overnight rate benchmarks: A roll–over risk approach. Frontiers of Mathematical Finance. 2(3):340-384.
  • Felpel, M., Kienitz, J. and McWalter, T.A. 2023. Effective stochastic local volatility models. Quantitative Finance. 23(12):1731-1750.
  • Katona, K., Nikitopoulos, C.S. and Schlögl, E. 2023. A Hyperbolic Bid Stack Approach to Electricity Price Modelling. Risks. 11(8):147.
  • Kenyon, C., Macrina, A. and Berrahoui, M. 2023. CO2eVA: pricing the transition of Scope 3 emissions. Risk, Cutting Edge: Climate Finance, Risk.net.
  • Kenyon, C., Macrina, A. and Berrahoui, M. 2023. The carbon equivalence principle: methods for project finance. Risk.net.
  • McWalter, T.A., Schlögl, E. and van Appel, J. 2023. Analysing Quantiles in Models of Forward Term Rates. Risks. 11(2):29.
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  • Backwell, A. & Hayes, J., 2022. Expected and unexpected jumps in the overnight rate: consistent management of the Libor transition. Journal of Banking & Finance. 145:106669.
  • Backwell, A., McWalter, T.A. & Ritchken, P.H. 2022. On Buybacks, Dilutions, Dividends, and the Pricing of Stock-Based Claims. Mathematical Finance. 32(1):273-308.
  • Backwell, A. & Ramnarayan, K., 2022. Volatility Level Dependence and Linear-Rational Term Structure Models. Emerging Markets Finance and Trade. 1-17.
  • Backwell, A. & Rudd, R., 2022. Throwing away a billion yuan, real or rand: the cost of sub-optimal hedging in high interest-rate environments. Applied Economics. 1-10.
  • Felpel, M., Kienitz, J. & McWalter, T.A., 2022. Effective Markovian projection: application to CMS spread options and mid-curve swaptions. Quantitative Finance. 22(6):1169-1192.
  • Kienitz, J., McWalter, T.A., Rudd, R., & Platen, E. 2022. Quantization Methods for Stochastic Differential Equations. In Novel Mathematics Inspired by Industrial Challenges. Günther, M., & Schilders, W. Eds. Mathematics in Industry. Vol 38. Springer, Cham. 299-329.
  • McWalter, T.A., Kienitz, J., Nowaczyk, N. Rudd, R. & Acar, S.K. 2022. Dynamic initial margin estimation based on quantiles of Johnson distributions. Journal of Credit Risk. 18(4):93-116
  • McWalter, T.A. & Ritchken, P.H., 2022. Black economic empowerment regulation and risk incentives. Journal of Economic Dynamics and Control. 139:104406.
  • McWalter, T.A. & Ritchken, P.H., 2022. On stock-based loans. Journal of Financial Intermediation. 52:100991.
  • Nowaczyk, N., Kienitz, J., Acar, S.K. & Liang, Q., 2022. How deep is your model? Network topology selection from a model validation perspective. Journal of Mathematics in Industry. 12(1):1-19.
  • Rudd, R., McWalter, T.A., Kienitz, J. & Platen, E., 2022. Robust Product Markovian Quantization. Journal of Computational Finance. 25(4):55-78.
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  • Bichsel, R., Lambertini, L., Mukherjee, A. & Wunderli, D. 2021. The pass-through of bank capital requirements to corporate lending spreads. Journal of Financial Stability. 100910.
  • Feng, Y., Rudd, R., Baker, C., Mashalaba, Q., Mavuso, M. & Schlögl, E. 2021. Quantifying the Model Risk Inherent in the Calibration and Recalibration of Option Pricing Models. Risks. 9(1):13.
  • Gellert, K. & Schlögl, E., 2021. Parameter Learning and Change Detection Using a Particle Filter with Accelerated Adaptation. Risks 9: 228.
  • Felpel, M., Kienitz, J. & McWalter, T.A. 2021. Effective stochastic volatility: applications to ZABR-type models. Quantitative Finance. 21(5):837-852.
  • Lambertini, L. & Mukherjee, A. 2021. Stress tests and loan pricing—Evidence from syndicated loans. Finance Research Letters. 102349.
  • Macrina, A. & Sekine, J., 2021. Stochastic modelling with randomized Markov bridges. Stochastics, 93(1):29-55.
  • Opolot, D.C. & Azomahou, T.T. 2021. Strategic diffusion in networks through contagion. Journal of Evolutionary Economics. 1-33.
  • Opolot, D.C. 2021. On the relationship between p-dominance and stochastic stability in network games. International Journal of Game Theory. 182.
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  • Alfeus, M., Grasselli, M. & Schlögl, E. 2020. A consistent stochastic model of the term structure of interest rates for multiple tenors. Journal of Economic Dynamics and Control. 103861.
  • Backwell, A. 2020. Unspanned Stochastic Volatility from an Empirical and Practical Perspective. Journal of Banking & Finance. 105993.
  • Dam, H.T., Macrina, A., Skovmand, D. & Sloth, D. 2020. Rational Models for Inflation-Linked Derivatives. SIAM Journal on Financial Mathematics. 11(4):974-1006.
  • Hoyle, E., Macrina, A. & Mengütürk, L.A. 2020. Modulated Information Flows in Financial Markets. International Journal of Theoretical and Applied Finance (IJTAF). 23(04):1-35.
  • Jiang, Y., Macrina, A. & Peters, G.W. 2020. Multiple barrier-crossings of an Ornstein-Uhlenbeck diffusion in consecutive periods. Stochastic Analysis and Applications. 1-40.
  • Macrina, A. & Skovmand, D. 2020. Rational savings account models for backward-looking interest rate benchmarks. Risks. 8(1):23.
  • Ritchken, P. & Wu, Q. 2020. Capacity Investment, Production Flexibility, and Capital Structure. Production and Operations Management. 30(12):4593-4613.
  • van Appel, J. & McWalter, T.A. 2020. Moment Approximations of Displaced Forward-LIBOR Rates with Application to Swaptions. International Journal of Theoretical and Applied Finance. 23(7):2050046.
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  • Basu, P., Dutta, S. & Shekhar, S. 2019. Ethnic conflicts with informed agents: A cheap talk game with multiple audiences. Economics Letters. 84:108661.
  • Burnecki, K., Giuricich, M. & Palmowski, Z. 2019. Valuation of contingent convertible catastrophe bonds – the case for equity conversion. Insurance: Mathematics and Economics. 88:238.
  • Giuricich, M. & Burnecki, K. 2019. Modelling of left-truncated heavy-tailed data with application to catastrophe bond pricing. Physica A. 525:498.
  • Kulikov, G., Taylor, D. & Kulikova, M. 2019. A nonlinear Bayesian filtering approach to estimating adaptive market efficiency. Russ. J. Numer. Anal.
    Math. Modelling. 34(1):31-42.
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  • Ahnert, T. & Georg, C.-P. 2018. Information contagion and systemic risk. Journal of Financial Stability. 25:159-171.
  • Gupta, R., Hollander, H. & Steinbach, R. 2018. Forecasting output growth using a DSGE-based decomposition of the South African yield curve. Empirical Economics. 1-28.
  • Kateregga, M., Mataramvura, S. & Taylor, D. 2018. Subordinated affine structure models for commodity futures prices. Cogent Journal of Economics and Finance. 6(1).
  • MacDonald, I.L. & Bhamani, F. 2018. A time-series model for underdispersed or overdispersed counts. The American Statistician. 1-34.
  • Macrina, A. & Mahomed, O. 2018. Consistent valuation across curves using pricing kernels. Risks. 6(18).
  • McWalter, T.A., Rudd, R., Kienitz, J. & Platen, E. 2018. Recursive marginal quantization of higher-order schemes. Quantitative Finance. 18(4):693-706.
  • Shekhar, S. 2018. Signaling, reputation and spinoffs. Journal of Economic Behavior & Organization, 149:88-105.
  • van Appel, J. & McWalter, T.A. 2018. Efficient long-dated swaption volatility approximation in the forward-LIBOR model. International Journal of Theoretical and Applied Finance. 21(4):1850020.
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  • Burnecki, K. & Giuricich, M. 2017. Stable Weak Approximation at Work in Index-Linked Catastrophe Bond Pricing. Risks. 5(64).
  • Huang, C.-S., O’Hara, J. & Mataramvura, S. 2017. Efficient pricing of discrete arithmetic Asian options under mean reversion and jumps based on
    Fourier-cosine expansions. Journal of Computational and Applied Mathematics. 311:230-238.
  • Kateregga, M., Mataramvura, S. & Taylor, D. 2017. Bismut-Elworthy-Li formula for subordinated Brownian motion applied to hedging financial derivatives. Cogent Journal of Economics and Finance. 5(1):1384125.
  • Kateregga, M., Mataramvura, S. & Taylor, D. 2017. Parameter estimation for stable distributions with application to commodity futures log-returns. Cogent Journal of Economics and Finance. 5(1):1318813.
  • Kienitz, J., McWalter, T.A., & Sheppard, R. 2017. PDE Methods for SABR. In Novel Methods in Computational Finance. Ehrhardt, M., Günther, M, ter Maten, E.J.W. Eds. Mathematics in Industry. Vol 25. Springer Cham. 265-291.
  • Rajaratnam, B. Rajaratnam, K. & Rajaratnam, M. 2017. A Theoretical Model for the Term Structure of Corporate Credit based on Competitive Advantage. European Financial Management. 23:183-210.
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  • Baker, C., Rajaratnam, K. & Flint, E.J. 2016. Beta Estimates of shares on the JSE Top 40 in the context of Reference-Day Risk. Environment Systems and Decisions. 36:126-141.
  • Barkhagen, M., Blomvall, J. & Platen, E. 2016. Recovering the real-world density and liquidity premia from option data. Quantitative Finance. 16(7):1147-1164.
  • Capriotti, L., Jiang, Y. & Macrina, A. 2016. Real-Time Risk Management: An AAD-PDE Approach. International Journal of Financial Engineering. 2(4):1550039-1550070.
  • Chan, L. & Platen, E. 2016. Pricing of long dated equity-linked life insurance contracts. Stochastic Analysis and Applications. 34(2): 339-355.
  • Crépey, S., Macrina, A., Nguyen, T.M. & Skovmand, D. 2016. Rational Multi-Curve Models with Counterparty-Risk Valuation Adjustments. Quantitative Finance. 16(6):847-866.
  • Crisafi, M.A. & Macrina, A. 2016. Simultaneous trading in ‘Lit’and dark pools. International Journal of Theoretical and Applied Finance. 19(8):1650055.
  • Du, K. & Platen, E. 2016. Benchmarked risk minimization. Mathematical Finance. 26(3):617-637.
  • Elenjical, T., Mwangi, P., Panulo, B. & Huang, C.-S. 2016. A comparative cross-regime analysis on the performance of GARCH-based value-at-risk models: Evidence from the Johannesburg Stock Exchange. Risk Management. 18(2):89-110.
  • Fiedor, P. 2016. Structural Sustainability of the Polish Trade System. Acta Physica Polonica A. 129(5):1004-1007.
  • Gao, L., Rajaratnam, K. & Beling, B. 2016. Credit Scoring Decisions using a Multinomial Scorecard. Annals of Operations Research. 243:199-210.
  • Laird-Smith, J., Meyer, K. & Rajaratnam, K. 2016. A study of Total Beta specification through Symmetric Regression: The case of the Johannesburg Stock Exchange. Environment Systems and Decisions. 36:114-125.
  • Noakes, M. & Rajaratnam, K. 2016. Testing Market Efficiency on the Johannesburg Stock Exchange using the Overlapping Serial Test. Annals of Operations Research. 243:273-300.
  • Rajaratnam, K., Beling, P. & Overstreet, G. 2016. Models of Sequential Decision Making in Consumer Lending. Decision Analytics. 3:6.
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  • Amien, I., Rajaratnam, K., & Kruger, R. 2015. Inference of Aggregational Gaussianity in Asset Returns Exhibiting a Paretian-distribution. Procedia Economics and Finance. 25:400-407.
  • Aymanns, C. & Georg, C.-P. 2015. Contagious synchronization and endogenous network formation in financial networks. Journal of Banking & Finance. 50:273-285.
  • Backwell, A. 2015. State Prices and Implementation of the Recovery Theorem. Journal of Risk and Financial Management. 8(1):2-16.
  • Baudena, M., Sanchez, A., Georg, C.-P., Ruiz-Benito, P., Rodriguez, M. A., Zavala, M. A. & Rietkerk, M. 2015. Revealing patterns of local species richness along environmental gradients with a novel network tool. Scientific reports, 5.
  • Chinhamu, K., Huang, C.-K., Huang. C.-S. & Hammujuddy, M. J. 2015. Empirical Analysis of Extreme Value Models for the South African Mining Index. South African Journal of Economics. 83(1):41-55.
  • De Jager, P.G. 2015. For banks, fair value adjustments do influence dividend policy. Southern African Business Review. 19(2):157-190.
  • Fiedor, P., 2015. Maximum entropy production principle for stock returns. In Computational Intelligence, 2015 IEEE Symposium Series. 695-702.
  • Hoyle, E., Hughston, L. P., & Macrina, A. 2015. Stable-1/2 bridges and insurance. Advances in Mathematics of Finance, Banach Center Publications, Institute of Mathematics, Polish Academy of Science. Vol 104.
  • Hulley, H. & McWalter T.A. 2015. Quadratic Hedging of Basis Risk. Journal of Risk and Financial Management. 8(1):83-102.
  • Sanderford, A., Overstreet, G.A., Beling, P. & Rajaratnam, K. 2015. Energy Efficient Homes and Mortgage Risk: Crossing the Chasm at Last? A Role for Credit Modeling? Environment Systems and Decisions. 35(1):157-168.
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  • De Jager, P. 2014. Fair value accounting, fragile bank balance sheets and crisis: A model. Accounting, Organizations and Society. 39(2):97-116.
  • Kassanjee R., McWalter T.A. & Welte A. 2014. Defining Optimality of a Test for Recent Infection for HIV Incidence Surveillance. AIDS Research and Human Retroviruses. 30(1):45-49.
  • Kienitz, J. 2014. Interest Rate Derivatives Explained. Volume 1: Products and Markets. Palgrave McMillan.
  • Kienitz, J. 2014. Transforming Volatility – Multi Curve Cap and Swaption Volatilities. International Review of Applied Financial Issues and Economics. 5(1).
  • Kruger, R. & Toerien, F. 2014. The consistency of equity style anomalies on the JSE during a period of market crisis. African Finance Journal. 16(1):1-18.
  • Macrina, A. 2014. Heat Kernel Models for Asset Pricing. International Journal of Theoretical & Applied Finance. 17(7):1-34.
  • Macrina, A. & Parbhoo, P. A. 2014. Randomised Mixture Models for Pricing Kernels. Asia-Pacific Financial Markets. 21:281-315.
  • Taylor, D. 2014. Modelling South African Single-Stock Futures Option Volatility Smiles. Investment Analysts Journal. 79:57-66.
  • Toerien, F., Rosenberg, D. & Kruger, R. 2014. The asymmetry of gain-loss time horizons on the JSE. Studies in Economics and Econometrics. 38(1):65-74.
  • Rajaratnam, M., Rajaratnam, B. & Rajaratnam, K. 2014. A Novel Equity Valuation and Capital Allocation Model for use by Long-term Value-Investors. Journal of Banking & Finance. 49:483-494.
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  • Kulikova, M. & Taylor, D. 2013. Stochastic Volatility Models for Exchange Rates and Their Estimation Using Quasi-maximum-likelihood Methods: an Application to the South African Rand. Journal of Applied Statistics. 40(3):495-507.
  • Rubin, G., Overstreet, G., Beling, P. & Rajaratnam, K. 2013. Dynamic Theory of Credit Unions. Annals of Operations Research. 205(1):29-53.
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