Special Issue "Selected Papers from the Fifth International Conference on Mathematics in Finance (MiF) 2014, Organized by North-West University, University of Cape Town and University of Johannesburg, South Africa"

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Mathematical Finance".

Deadline for manuscript submissions: closed (31 December 2014).

Special Issue Editors

Prof. Dr. Coenraad Labuschagne
Website
Guest Editor
Department of Finance and Investment Management, Faculty of Economic and Financial Sciences, University of Johannesburg, PO Box 524, Aucklandpark, Johannesburg, South Africa
Interests: mathematics; statistics; mathematics of finance; quantitative finance; investment management

Special Issue Information

Dear Colleagues,

Organized by North-West University, University of Cape Town and University of Johannesburg, the Fifth International Conference on Mathematics in Finance (MiF) was held from 24-29 August 2014 at Skukuza, Kruger National Park, South Africa.

The main objective of the conference is to bring together academics, practitioners and graduate students who are working in the broad field of financial mathematics and statistics. It is envisaged that participants who are at the forefront of the area will reflect on current open problems and relevant challenges and will indicate directions for future research. It is hoped that the interplay between theory and practice, as well as issues relating to the dissemination of knowledge and teaching in this field, will be discussed critically.

The conference will focus on various aspects within financial mathematics and statistics, with special attention given to the interaction between the different areas, emphasizing the role of mathematics and statistics in finance. Topics to be covered include:

  1. Contemporary methods in the field of business analytics;
  2. Investment and credit risk;
  3. New methods of quantitative risk analysis, modeling and management, including actuarial science;
  4. Quantitative and computational methods in finance;
  5. Financial mathematics, measure theory, functional analysis, and modern stochastics in finance.

This Special Issue will collect selected papers from the conference, which will cover areas such as Actuarial Science, Quantitative Risk Management, Financial Mathematics, and Business Analytics (Data Mining). For further details, see http://www.nwu.ac.za/content/mif-2014-landing-page.

Invited Authors

 

Plenary Speakers:
Jonathan Crook (University of Edinburgh, UK)
Bruno Dupire (Bloomberg and New York University, USA)
Paul Embrechts (ETH Zurich, Switzerland)
Rüdiger Frey (Vienna University of Economics and Business, Austria)
Matheus Grasselli (McMaster University, Canada)
Alan Kirman (Aix-Marseille Université, France)
Andrea Macrina (University College London, UK)
Michael McAleer (Erasmus University Rotterdam, The Netherlands; National Tsing Hua University, Taiwan)
Alex McNeil (Heriot-Watt University, UK)
Dirk Tasche (Bank of England - Prudential Regulation Authority and Imperial College, UK)

Invited Speakers:
Graeme West Lecture: Chialin Chang (National Chung Hsing University, Taiwan)
Momentum Lecture: Ronald Surz (President, PPCA inc, USA)

Prof. Dr. Chia-Lin Chang
Prof. Dr. Coenraad Labuschagne

Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Risk and Financial Management is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (8 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Jump to: Other

Open AccessArticle
Inflation and Speculation in a Dynamic Macroeconomic Model
J. Risk Financial Manag. 2015, 8(3), 285-310; https://doi.org/10.3390/jrfm8030285 - 06 Jul 2015
Cited by 8
Abstract
We study a monetary version of the Keen model by merging two alternative extensions, namely the addition of a dynamic price level and the introduction of speculation. We recall and study old and new equilibria, together with their local stability analysis. This includes [...] Read more.
We study a monetary version of the Keen model by merging two alternative extensions, namely the addition of a dynamic price level and the introduction of speculation. We recall and study old and new equilibria, together with their local stability analysis. This includes a state of recession associated with a deflationary regime and characterized by falling employment but constant wage shares, with or without an accompanying debt crisis. Full article
Show Figures

Figure 1

Open AccessArticle
Quantification of VaR: A Note on VaR Valuation in the South African Equity Market
J. Risk Financial Manag. 2015, 8(1), 103-126; https://doi.org/10.3390/jrfm8010103 - 13 Feb 2015
Cited by 1
Abstract
The statistical distribution of financial returns plays a key role in evaluating Value-at-Risk using parametric methods. Traditionally, when evaluating parametric Value-at-Risk, the statistical distribution of the financial returns is assumed to be normally distributed. However, though simple to implement, the Normal distribution underestimates [...] Read more.
The statistical distribution of financial returns plays a key role in evaluating Value-at-Risk using parametric methods. Traditionally, when evaluating parametric Value-at-Risk, the statistical distribution of the financial returns is assumed to be normally distributed. However, though simple to implement, the Normal distribution underestimates the kurtosis and skewness of the observed financial returns. This article focuses on the evaluation of the South African equity markets in a Value-at-Risk framework. Value-at-Risk is estimated on four equity stocks listed on the Johannesburg Stock Exchange, including the FTSE/JSE TOP40 index and the S & P 500 index. The statistical distribution of the financial returns is modelled using the Normal Inverse Gaussian and is compared to the financial returns modelled using the Normal, Skew t-distribution and Student t-distribution. We then estimate Value-at-Risk under the assumption that financial returns follow the Normal Inverse Gaussian, Normal, Skew t-distribution and Student t-distribution and backtesting was performed under each distribution assumption. The results of these distributions are compared and discussed. Full article
Show Figures

Figure 1

Open AccessArticle
Quadratic Hedging of Basis Risk
J. Risk Financial Manag. 2015, 8(1), 83-102; https://doi.org/10.3390/jrfm8010083 - 02 Feb 2015
Cited by 5
Abstract
This paper examines a simple basis risk model based on correlated geometric Brownian motions. We apply quadratic criteria to minimize basis risk and hedge in an optimal manner. Initially, we derive the Föllmer–Schweizer decomposition for a European claim. This allows pricing and hedging [...] Read more.
This paper examines a simple basis risk model based on correlated geometric Brownian motions. We apply quadratic criteria to minimize basis risk and hedge in an optimal manner. Initially, we derive the Föllmer–Schweizer decomposition for a European claim. This allows pricing and hedging under the minimal martingale measure, corresponding to the local risk-minimizing strategy. Furthermore, since the mean-variance tradeoff process is deterministic in our setup, the minimal martingale- and variance-optimal martingale measures coincide. Consequently, the mean-variance optimal strategy is easily constructed. Simple pricing and hedging formulae for put and call options are derived in terms of the Black–Scholes formula. Due to market incompleteness, these formulae depend on the drift parameters of the processes. By making a further equilibrium assumption, we derive an approximate hedging formula, which does not require knowledge of these parameters. The hedging strategies are tested using Monte Carlo experiments, and are compared with results achieved using a utility maximization approach. Full article
Show Figures

Figure 1

Open AccessArticle
Implied and Local Volatility Surfaces for South African Index and Foreign Exchange Options
J. Risk Financial Manag. 2015, 8(1), 43-82; https://doi.org/10.3390/jrfm8010043 - 26 Jan 2015
Cited by 4
Abstract
Certain exotic options cannot be valued using closed-form solutions or even by numerical methods assuming constant volatility. Many exotics are priced in a local volatility framework. Pricing under local volatility has become a field of extensive research in finance, and various models are [...] Read more.
Certain exotic options cannot be valued using closed-form solutions or even by numerical methods assuming constant volatility. Many exotics are priced in a local volatility framework. Pricing under local volatility has become a field of extensive research in finance, and various models are proposed in order to overcome the shortcomings of the Black-Scholes model that assumes a constant volatility. The Johannesburg Stock Exchange (JSE) lists exotic options on its Can-Do platform. Most exotic options listed on the JSE’s derivative exchanges are valued by local volatility models. These models needs a local volatility surface. Dupire derived a mapping from implied volatilities to local volatilities. The JSE uses this mapping in generating the relevant local volatility surfaces and further uses Monte Carlo and Finite Difference methods when pricing exotic options. In this document we discuss various practical issues that influence the successful construction of implied and local volatility surfaces such that pricing engines can be implemented successfully. We focus on arbitrage-free conditions and the choice of calibrating functionals. We illustrate our methodologies by studying the implied and local volatility surfaces of South African equity index and foreign exchange options. Full article
Show Figures

Figure 1

Open AccessArticle
Pricing a Collateralized Derivative Trade with a Funding Value Adjustment
J. Risk Financial Manag. 2015, 8(1), 17-42; https://doi.org/10.3390/jrfm8010017 - 26 Jan 2015
Cited by 1
Abstract
The 2008 credit crisis changed the manner in which derivative trades are conducted. One of these changes is the posting of collateral in a trade to mitigate the counterparty credit risk. Another is the realization that banks are not risk-free and, as a [...] Read more.
The 2008 credit crisis changed the manner in which derivative trades are conducted. One of these changes is the posting of collateral in a trade to mitigate the counterparty credit risk. Another is the realization that banks are not risk-free and, as a result, cannot borrow at the risk-free rate any longer. The latter led banks to introduced the controversial adjustment to derivative prices, known as a funding value adjustment (FVA), which is interlinked with the posting of collateral. In this paper, we extend the Cox, Ross and Rubinstein (CRR) discrete-time model to include collateral and FVA. We prove that this derived model is a discrete analogue of Piterbarg’s partial differential equation (PDE), which describes the price of a collateralized derivative. The fact that the two models coincide is also verified by numerical implementation of the results that we obtain. Full article
Show Figures

Figure 1

Open AccessArticle
State Prices and Implementation of the Recovery Theorem
J. Risk Financial Manag. 2015, 8(1), 2-16; https://doi.org/10.3390/jrfm8010002 - 19 Jan 2015
Cited by 9
Abstract
It is generally held that derivative prices do not contain useful predictive information, that is, information relating to the distribution of future financial variables under the real-world measure. This is because the market’s implicit forecast of the future becomes entangled with market risk [...] Read more.
It is generally held that derivative prices do not contain useful predictive information, that is, information relating to the distribution of future financial variables under the real-world measure. This is because the market’s implicit forecast of the future becomes entangled with market risk preferences during derivative price formation. A result derived by Ross [1], however, recovers the real-world distribution of an equity index, requiring only current prices and mild restrictions on risk preferences. In addition to being of great interest to the theorist, the potential practical value of the result is considerable. This paper addresses implementation of the Ross Recovery Theorem. The theorem is formalised, extended, proved and discussed. Obstacles to application are identified and a workable implementation methodology is developed. Full article
Show Figures

Figure 1

Open AccessArticle
Exact Fit of Simple Finite Mixture Models
J. Risk Financial Manag. 2014, 7(4), 150-164; https://doi.org/10.3390/jrfm7040150 - 20 Nov 2014
Cited by 4
Abstract
How to forecast next year’s portfolio-wide credit default rate based on last year’s default observations and the current score distribution? A classical approach to this problem consists of fitting a mixture of the conditional score distributions observed last year to the current score [...] Read more.
How to forecast next year’s portfolio-wide credit default rate based on last year’s default observations and the current score distribution? A classical approach to this problem consists of fitting a mixture of the conditional score distributions observed last year to the current score distribution. This is a special (simple) case of a finite mixture model where the mixture components are fixed and only the weights of the components are estimated. The optimum weights provide a forecast of next year’s portfolio-wide default rate. We point out that the maximum-likelihood (ML) approach to fitting the mixture distribution not only gives an optimum but even an exact fit if we allow the mixture components to vary but keep their density ratio fixed. From this observation we can conclude that the standard default rate forecast based on last year’s conditional default rates will always be located between last year’s portfolio-wide default rate and the ML forecast for next year. As an application example, cost quantification is then discussed. We also discuss how the mixture model based estimation methods can be used to forecast total loss. This involves the reinterpretation of an individual classification problem as a collective quantification problem. Full article

Other

Jump to: Research

Open AccessBrief Report
Report on the Fifth International Mathematics in Finance (MiF) Conference 2014, Skukuza, Kruger National Park, South Africa
J. Risk Financial Manag. 2014, 7(3), 110-112; https://doi.org/10.3390/jrfm7030110 - 19 Sep 2014
Abstract
The Journal of Risk and Financial Management was first published in 2008, and, since its inception, has published a number of theoretical and empirical papers on various topics in risk and financial management, in pursuit of its stated goal of advancing knowledge and [...] Read more.
The Journal of Risk and Financial Management was first published in 2008, and, since its inception, has published a number of theoretical and empirical papers on various topics in risk and financial management, in pursuit of its stated goal of advancing knowledge and understanding in the practice of risk and financial management through the publication of high quality papers that are relevant to practitioners in the field.[...] Full article
Back to TopTop