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Dr Boda Kang

Biography

Boda joined UTS in March 2007 as a research associate working with Professor Carl Chiarella on a project of American option pricing after finishing his PhD in Financial Mathematics at the School of Mathematics and Statistics, University of South Australia. In 2004, during the second year of his PhD, he received a Chinese government award for outstanding self-financed PhD students abroad, including a certificate and US$5,000 to each winner. He is one of 14 Chinese PhD students studying in Australia to have received this award. Before coming to Australia, he finished his Bachelor of Science in Applied Mathematics and Master of Science in Probability and Mathematical Statistics both from Department of Mathematical Science, at Tsinghua University, Beijing, China. His research interests include financial derivatives pricing, dynamic value-at-risk (VaR) and conditional value-at-risk (CVaR) analysis, time consistent risk measures, risk analysis in both financial market and environmental problems, Markov decision processes and financial mathematics. He has published a couple of refereed papers in international journals and edited volumes. He has also presented his research on a number of national and international conferences.

Visiting Fellow, Finance Discipline Group
Associate Member, Quantitative Finance Research Centre
B.Sc(Tsinghua), M.Sc(Tsinghua), PhD(UniSA)
 
Can supervise: Yes

Conferences

Chiarella, C., Griebsch, S. & Kang, B. 2014, 'A comparative study on time-efficient methods to price compound options in the Heston model'.
Chiarella, C., Kang, B., Nikitopoulos, C.S. & T, T.-.D. 2013, 'Humps in the volatility structure of the crude oil futures market: New evidence', Energy Economics, pp. 989-1000.
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This paper analyses the volatility structure of commodity derivatives markets. The model encompasses hump-shaped, unspanned stochastic volatility, which entails a finite-dimensional affine model for the commodity futures curve and quasi-analytical prices for options on commodity futures. Using an extensive database of crude oil futures and futures options spanning 21. years, we find the presence of hump-shaped, partially spanned stochastic volatility in the crude oil market. The hump shaped feature is more pronounced when the market is more volatile, and delivers better pricing as well as hedging performance under various dynamic factor hedging schemes. 2013 Elsevier B.V.
Chiarella, C. & Kang, B. 2013, 'The evaluation of American compound option prices under stochastic volatility and stochastic interest rates', JOURNAL OF COMPUTATIONAL FINANCE, pp. 71-92.
Chiarella, C., Kang, B. & Meyer, G.H. 2012, 'The evaluation of barrier option prices under stochastic volatility', Computers and Mathematics with Applications, pp. 2034-2048.
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This paper considers the problem of numerically evaluating barrier option prices when the dynamics of the underlying are driven by stochastic volatility following the square root process of Heston (1993) [7]. We develop a method of lines approach to evaluate the price as well as the delta and gamma of the option. The method is able to efficiently handle both continuously monitored and discretely monitored barrier options and can also handle barrier options with early exercise features. In the latter case, we can calculate the early exercise boundary of an American barrier option in both the continuously and discretely monitored cases. 2012 Elsevier Ltd. All rights reserved.

Journal articles

Chiarella, C., Griebsch, S. & Kang, B. 2014, 'A comparative study on time-efficient methods to price compound options in the Heston model', Computers and Mathematics with Applications, vol. 67, no. 6, pp. 1254-1270.
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The primary purpose of this paper is to provide an in-depth analysis of a number of structurally different methods to numerically evaluate European compound option prices under Heston's stochastic volatility dynamics. Therefore, we first outline several approaches that can be used to price these type of options in the Heston model: a modified sparse grid method, a fractional fast Fourier transform technique, a (semi-)analytical valuation formula using Green's function of logarithmic spot and volatility and a Monte Carlo simulation. Then we compare the methods on a theoretical basis and report on their numerical properties with respect to computational times and accuracy. One key element of our analysis is that the analyzed methods are extended to incorporate piecewise time-dependent model parameters, which allows for a more realistic compound option pricing. The results in the numerical analysis section are important for practitioners in the financial industry to identify under which model prerequisites (for instance, Heston model where Feller condition is fulfilled or not, Heston model with piecewise time-dependent parameters or with stochastic interest rates) it is preferable to use and which of the available numerical methods. 2014 Elsevier Ltd. All rights reserved.