Relevant bibliographies by topics / Finance – Mathematical models – Swaziland

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Finance – Mathematical models – Swaziland'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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Journal articles on the topic "Finance – Mathematical models – Swaziland"

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Byrne, Patrick, S. D. Howison, F. P. Kelly, and P. Wilmott. "Mathematical Models in Finance." Statistician 45, no. 3 (1996): 389. http://dx.doi.org/10.2307/2988481.

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Busika, Themba, and Muhammad Hoque. "An investigation into the best approach to the implementation of Basel II in Swaziland." Banks and Bank Systems 12, no. 4 (December 18, 2017): 131–43. http://dx.doi.org/10.21511/bbs.12(4-1).2017.02.

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After the exposition of the Basel I Capital Accord weaknesses, the advent of the Basel II Capital Framework profoundly redefined global banking regulation and risk management practices. Many African countries had been lethargic on the migration to Basel for various reasons, amongst many being lack of skills and infrastructure. The purpose of this study was to investigate the prospect of migrating from the 1988 Basel I Capital Accord to the Basel II Capital Framework and to analyze the best approach to the implementation of the new framework in Swaziland. This was a qualitative study conducted using semi-structured interview among risk managers from the four banks operated in Swaziland. The researchers also analyzed internal regulatory documents to determine their suitability and compliance to the Basel II standards. The results showed that the adoption and implementation of Basel II are a complex and resource intensive undertaking that requires strong commitment from policy decision makers. The complex models used in the later Basel capital accords have the potential to be unattainable for emerging economies, while the risk of doing business is ever increasing with exotic banking products being introduced. Background work remains the daunting outstanding undertaking that the Central Bank must get ready to do and complete timeously and efficiently. Implementation prerequisites include aligning supervision practices with the 29 Basel Core Principles for Effective Banking Supervision, revising the current legislation to address existing regulatory weaknesses and recruiting and training human resources for efficient and effective rollout.
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CARMONA, RENÉ, and SERGEY NADTOCHIY. "TANGENT MODELS AS A MATHEMATICAL FRAMEWORK FOR DYNAMIC CALIBRATION." International Journal of Theoretical and Applied Finance 14, no. 01 (February 2011): 107–35. http://dx.doi.org/10.1142/s0219024911006280.

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Motivated by the desire to integrate repeated calibration procedures into a single dynamic market model, we introduce the notion of a "tangent model" in an abstract set up, and we show that this new mathematical paradigm accommodates all the recent attempts to study consistency and absence of arbitrage in market models. For the sake of illustration, we concentrate on the case when market quotes provide the prices of European call options for a specific set of strikes and maturities. While reviewing our recent results on dynamic local volatility and tangent Lévy models, we present a theory of tangent models unifying these two approaches and construct a new class of tangent Lévy models, which allows the underlying to have both continuous and pure jump components.
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Fatone, Lorella, Francesca Mariani, Maria Cristina Recchioni, and Francesco Zirilli. "The Calibration of Some Stochastic Volatility Models Used in Mathematical Finance." Open Journal of Applied Sciences 04, no. 02 (2014): 23–33. http://dx.doi.org/10.4236/ojapps.2014.42004.

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Egozcue, Martín, Luis Fuentes García, Konstantinos Katsikopoulos, and Michael Smithson. "Simple models in finance: a mathematical analysis of the probabilistic recognition heuristic." Journal of Risk Model Validation 11, no. 2 (June 2017): 83–103. http://dx.doi.org/10.21314/jrmv.2017.175.

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Scrimnger-Christian, Charmaine, and Saratiel Wedzerai Musvoto. "Rethinking The Use Of Causal Theories In Social Sciences: A Focus On Accounting And Finance." International Business & Economics Research Journal (IBER) 10, no. 10 (September 27, 2011): 115. http://dx.doi.org/10.19030/iber.v10i10.5991.

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This study highlights the problems associated with the use of deterministic models in social scientific disciplines such as accounting and finance. A deterministic theory connotes a self-defining set of physical relations and it yields a set of mathematical functions, parameterized by time, which describes how a set of ideal measure numbers changes with the time parameter while statistical models are used to describe the distribution of variations of concrete measured data from the ideal mathematical law. In this study, it is argued that in disciplines such as accounting and finance there are no appropriately defined ideal mathematical laws. Moreover, it is suggested that phenomena in accounting and finance do not exhibit characteristics that facilitate an appropriate description of deterministic models. If this is the case, it follows that there are no concretely measurable data in these disciplines and consequently these data have variations whose distributions from undefined ideal mathematical laws cannot be described. Hence, it is suggested in this study that linear models can only yield misleading information in accounting and finance unless they are based on concretely measurable relations.
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Ishimura, Naoyuki. "Research on Nonlinear Partial Differential Equations in Mathematical Finance." Impact 2020, no. 8 (December 16, 2020): 48–50. http://dx.doi.org/10.21820/23987073.2020.8.48.

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Mathematical finance is a field of applied mathematics which focuses on crafting special mathematical models and computational methods which are used by the finance markets. The basis of mathematical finance lies in probability theory which focuses on analysing the behaviour of the markets to help the prediction of any random events. From this work financial companies and individuals interested in the markets can make informed choices based on a calculated risk level. Professor Naoyuki Ishimura has performed research in mathematical finance for many years, and is currently based at Chuo University, where he is now focusing on assisting in the development of better methods for calculating risk factors. One of his current collaborators is Andres Mauricio Molina Barreto, a doctoral student from Colombia. Together, they have worked on a paper that looks at the Value at Risk (VaR) for the portfolio problem in the presence of copulas, which help to explain how random variables are dependent on each other.
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Blanchet-Scalliet, Christophette, Awa Diop, Rajna Gibson, Denis Talay, and Etienne Tanré. "Technical analysis compared to mathematical models based methods under parameters mis-specification." Journal of Banking & Finance 31, no. 5 (May 2007): 1351–73. http://dx.doi.org/10.1016/j.jbankfin.2006.10.017.

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Rosenberger, Jay M., and H. W. Corley. "Mathematical programming models for some smallest-world problems." Nonlinear Analysis: Real World Applications 6, no. 5 (December 2005): 955–61. http://dx.doi.org/10.1016/j.nonrwa.2005.02.001.

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Bekri, Mahmoud, Young Shin (Aaron) Kim, and Svetlozar (Zari) T. Rachev. "Tempered stable models for Islamic finance asset management." International Journal of Islamic and Middle Eastern Finance and Management 7, no. 1 (April 14, 2014): 37–60. http://dx.doi.org/10.1108/imefm-10-2012-0096.

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Purpose – In Islamic finance (IF), the safety-first rule of investing (hifdh al mal) is held to be of utmost importance. In view of the instability in the global financial markets, the IF portfolio manager (mudharib) is committed, according to Sharia, to make use of advanced models and reliable tools. This paper seeks to address these issues. Design/methodology/approach – In this paper, the limitations of the standard models used in the IF industry are reviewed. Then, a framework was set forth for a reliable modeling of the IF markets, especially in extreme events and highly volatile periods. Based on the empirical evidence, the framework offers an improved tool to ameliorate the evaluation of Islamic stock market risk exposure and to reduce the costs of Islamic risk management. Findings – Based on the empirical evidence, the framework offers an improved tool to ameliorate the evaluation of Islamic stock market risk exposure and to reduce the costs of Islamic risk management. Originality/value – In IF, the portfolio manager – mudharib – according to Sharia, should ensure the adequacy of the mathematical and statistical tools used to model and control portfolio risk. This task became more complicated because of the increase in risk, as measured via market volatility, during the financial crisis that began in the summer of 2007. Sharia condemns the portfolio manager who demonstrates negligence and may hold him accountable for losses for failing to select the proper analytical tools. As Sharia guidelines hold the safety-first principle of investing rule (hifdh al mal) to be of utmost importance, the portfolio manager should avoid speculative investments and strategies that would lead to significant losses during periods of high market volatility.
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Dissertations / Theses on the topic "Finance – Mathematical models – Swaziland"

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Pitsillis, Zachry Steven. "Estimating dynamic affine term structure models." Master's thesis, University of Cape Town, 2015. http://hdl.handle.net/11427/15731.

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Duffee and Stanton (2012) demonstrated some pointed problems in estimating affine term structure models when the price of risk is dynamic, that is, risk factor dependent. The risk neutral parameters are estimated with precision, while the price of risk parameters are not. For the Gaussian models they investigated, these problems are replicated and are shown to stem from a lack of curvature in the log-likelihood function. This geometric issue for identifying the maximum of an essentially horizontal log-likelihood has statistical meaning. The Fisher information for the price of risk parameters is multiple orders of magnitude smaller than that of the risk neutral parameters. Prompted by the recent results of Christoffersen et al. (2014) a remedy to the lack of curvature is attempted. An unscented Kalman filter is used to estimate models where the observations are portfolios of FRAs, Swaps and Zero Coupon Bond Options. While the unscented Kalman filter performs admirably in identifying the unobserved risk factor processes, there is little improvement in the Fisher information.
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Ziervogel, Graham. "Hedging performance of interest-rate models." Master's thesis, University of Cape Town, 2016. http://hdl.handle.net/11427/20482.

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This dissertation is a hedging back-study which assesses the effectiveness of interest- rate modelling and the hedging of interest-rate derivatives. Caps that trade in the Johannesburg swap market are hedged using two short-rate models, namely the Hull and White (1990) one-factor model and the subsequent Hull and White (1994) two-factor extension. This is achieved by using the equivalent Gaussian additive-factor models (G1++ and G2++) outlined by Brigo and Mercurio (2007). The hedges are constructed using different combinations of theoretical zero-coupon bonds. A flexible factor hedging method is proposed by the author and the bucket hedging technique detailed by Driessen, Klaasen and Melenberg (2003) is tested. The results obtained support the claims made by Gupta and Subrahmanyam (2005), Fan, Gupta and Ritchken (2007) and others in the literature that multi-factor models outperform one-factor models in hedging interest-rate derivatives. It is also shown that the choice of hedge instruments can significantly influence hedge performance. Notably, a larger set of hedge instruments and the use of hedge instruments with the same maturity as the derivative improve hedging accuracy. However, no evidence to support the finding of Driessen et al. (2003) that a larger set of hedge instruments can remove the need for a multi-factor model is found.
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Putyatin, Vladislav Evgenievich. "Mathematical models for derivative securities markets." Thesis, University of Southampton, 1998. https://eprints.soton.ac.uk/50648/.

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The classical Black-Scholes analysis determines a unique, continuous, trading strategy which allows one to hedge a financial option perfectly and leads to a unique price for the option. It assumes, however, that there are no transaction costs involved in implementing this strategy, and the stock market is absolutely liquid. In this work some new results are obtained to accommodate costs of hedging, which occur in practice, and market imperfections into the option pricing framework. In Part One transaction charges are dealt with by means of the mean-variance technique, originally developed by Markowitz. This approach is based on the minimisation of the variance of the outcome at expiry subject to spending at most a given initial endowment. Since "perfect" replication is no longer possible in this case, there will always be an unavoidable element of risk associated with writing an option. Therefore, the option price is now not unique. A mean-variance approach makes option pricing relatively easy and meaningful to an investor, who is supposed to choose a point on the mean-deviation locus. In the limit of zero transaction costs, the problem naturally reduces to the Black-Scholes valuation method, unlike alternative approaches based on the utility-maximisation. The stochastic optimisation problem obtained is dealt with by means of the stochastic version of Pontryagin's maximum principle. This technique is believed to be applied to this kind of problem for the first time. In general the resulting free-boundary problem has to be solved numerically, but for a small level of proportional transaction costs an asymptotic solution is possible. Regions of short term and long term dynamics are identified and the intermediate behaviour is obtained by matching these regions. The perturbation analysis of the utility-maximisation approach is also revised in this work, and amendments are obtained. In addition, the maximum principle is applied to the Portfolio Selection problem of Markowitz. The dynamical rebalancing technique developed in this work proves more efficient than the classical static approach, and allows investors to obtain portfolios with lower levels of risk. The model presented in Part Two is an attempt to quantify the concept of liquidity and establish relations between various measures of market performance. Informational inefficiency is argued to be the main reason for the unavailability of an asset at its equilibrium price. A mathematical model to describe the asset price behaviour together with arbitrage considerations enable us to estimate the component of the bid-ask spread arising from the outstanding information. The impact of the market liquidity on hedging an option with another option as well as the underlying asset itself is also examined. Although in the last case uncertainty cannot be completely eliminated from the hedged portfolio, a unique risk-minimising strategy is found.
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蕭德權 and Tak-kuen Siu. "Risk measures in finance and insurance." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31242297.

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Cullinan, Cian. "Implementation of Bivariate Unspanned Stochastic Volatility Models." Master's thesis, University of Cape Town, 2018. http://hdl.handle.net/11427/29266.

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Unspanned stochastic volatility term structure models have gained popularity in the literature. This dissertation focuses on the challenges of implementing the simplest case – bivariate unspanned stochastic volatility models, where there is one state variable controlling the term structure, and one scaling the volatility. Specifically, we consider the Log-Affine Double Quadratic (1,1) model of Backwell (2017). In the class of affine term structure models, state variables are virtually always spanned and can therefore be inferred from bond yields. When fitting unspanned models, it is necessary to include option data, which adds further challenges. Because there are no analytical solutions in the LADQ (1,1) model, we show how options can be priced using an Alternating Direction Implicit finite difference scheme. We then implement an Unscented Kalman filter — a non-linear extension of the Kalman filter, which is a popular method for inferring state variable values — to recover the latent state variables from market observable data
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Wort, Joshua. "Pricing with Bivariate Unspanned Stochastic Volatility Models." Master's thesis, Faculty of Commerce, 2019. http://hdl.handle.net/11427/31323.

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Unspanned stochastic volatility (USV) models have gained popularity in the literature. USV models contain at least one source of volatility-related risk that cannot be hedged with bonds, referred to as the unspanned volatility factor(s). Bivariate USV models are the simplest case, comprising of one state variable controlling the term structure and the other controlling unspanned volatility. This dissertation focuses on pricing with two particular bivariate USV models: the Log-Affine Double Quadratic (1,1) – or LADQ(1,1) – model of Backwell (2017) and the LinearRational Square Root (1,1) – or LRSQ(1,1) – model of Filipovic´ et al. (2017). For the LADQ(1,1) model, we fully outline how an Alternating Directional Implicit finite difference scheme can be used to price options and implement the scheme to price caplets. For the LRSQ(1,1) model, we illustrate a semi-analytical Fourierbased method originally designed by Filipovic´ et al. (2017) for pricing swaptions, but adjust it to price caplets. Using the above numerical methods, we calibrate each (1,1) model to both the British-pound yield curve and caps market. Although we cannot achieve a close fit to the implied volatility surface, we find that the parameters in the LADQ(1,1) model have direct control over the qualitative features of the volatility skew, unlike the parameters within the LRSQ(1,1) model.
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Endekovski, Jessica. "Pricing multi-asset options in exponential levy models." Master's thesis, Faculty of Commerce, 2019. http://hdl.handle.net/11427/31437.

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This dissertation looks at implementing exponential Levy models whereby the un- ´ derlyings are driven by Levy processes, which are able to account for stylised facts ´ that traditional models do not, in order to price basket options more efficiently. In particular, two exponential Levy models are implemented and tested: the multi- ´ variate Variance Gamma (VG) model and the multivariate normal inverse Gaussian (NIG) model. Both models are calibrated to real market data and then used to price basket options, where the underlyings are the constituents of the KBW Bank Index. Two pricing methods are also compared: a closed-form (analytical) approximation of the price, derived by Linders and Stassen (2016) and the standard Monte Carlo method. The convergence of the analytical approximation to Monte Carlo prices was found to improve as the time to maturity of the option increased. In comparison to real market data, the multivariate NIG model was able to fit the data more accurately for shorter maturities and the multivariate VG model for longer maturities. However, when looking at Monte Carlo prices, the multivariate VG model was found to outperform the results of the multivariate NIG model, as it was able to converge to Monte Carlo prices to a greater degree.
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Oagile, Joel. "Sequential Calibration of Asset Pricing Models to Option Prices." Master's thesis, University of Cape Town, 2018. http://hdl.handle.net/11427/29840.

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This paper implements four calibration methods on stochastic volatility models. We estimate the latent state and parameters of the models using three non-linear filtering methods, namely the extended Kalman filter (EKF), iterated extended Kalman filter (IEKF) and the unscented Kalman filter (UKF). A simulation study is performed and the non-linear filtering methods are compared to the standard least square method (LSQ). The results show that both methods are capable of tracking the hidden state and time varying parameters with varying success. The non-linear filtering methods are faster and generally perform better on validation. To test the stability of the parameters, we carry out a delta hedging study. This exercise is not only of interest to academics, but also to traders who have to hedge their positions. Our results do not show any significant benefits resulting from performing delta hedging using parameter estimates obtained from non-linear filtering methods as compared to least square parameter estimates.
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Sylvester, Matthew. "Calibrating Term Structure Models to an Initial Yield Curve." Master's thesis, Faculty of Commerce, 2021. http://hdl.handle.net/11427/33027.

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The modelling of the short rate offers many advantages, with the models explored in this dissertation all offering closed-form, analytic formulae for bond prices and for options on bonds. Often, a vital primary condition is for a model to be calibrated to the initial term structure and to recover the bond prices observed in the market – that is, to be calibrated to the initial yield curve. Under the two exogenous models explored in this dissertation, the Hull-White and the CIR++, the effect of increasing the volatility parameter of the SDE increases the mean of the short rate. Increasing volatility of an SDE is a common approach to stress testing a model, as such, the consequences of bumping volatility in a calibrated model is a vital concern. The Hull-White model and CIR++ model were calibrated to market data, with the former being able to match the observed cap prices, while the latter failed, displaying an upper bound on cap prices. Investigating this, under CIR++ model, bond option prices are shown to not be straightforward increasing functions of the volatility parameter. In fact, for high volatility, bond option prices display an upper limit before decreasing, thus providing a limit to the level of cap prices too. This dissertation points to the reason residing in the underlying CIR model from which the CIR++ is based on, and the manner in which the model is extended
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Guedes, Maria do Carmo Vaz de Miranda. "Mathematical models in capital investment appraisal." Thesis, University of Warwick, 1988. http://wrap.warwick.ac.uk/107492/.

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Books on the topic "Finance – Mathematical models – Swaziland"

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Mathematical finance. Hoboken, N.J: Wiley, 2011.

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Numerical techniques in finance. Cambridge, Mass: MIT Press, 1989.

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Experiments in quantitative finance. New Brunswick: Transaction Publishers, 2011.

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Knight, John L. Linear factor models in finance. Oxford: Elsevier/Butterworth-Heinemann, 2005.

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Mathematical finance: Theory, modeling, implementation. Hoboken, N.J: John Wiley & Sons, Inc., 2007.

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Iftekhar, Hasan, ed. Quantitative methods for finance and investments. Malden, MA: Blackwell Publishers, 2002.

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1963-, Waldron Patrick, ed. Mathematics for economics and finance. New York: Routledge, 2010.

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Handbook of computational finance. Heidelberg: Springer, 2012.

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Norman, Biggs, ed. Mathematics for economics and finance: Methods and modelling. Cambridge [England]: Cambridge University Press, 1996.

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Introduction to mathematical finance: Discrete time models. Malden, Mass: Blackwell, 1997.

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Book chapters on the topic "Finance – Mathematical models – Swaziland"

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Fleming, Wendell H. "Optimal Investment Models and Risk Sensitive Stochastic Control." In Mathematical Finance, 75–88. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4757-2435-6_6.

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Biagini, Francesca. "A Quadratic Approach To Interest Rates Models In Incomplete Markets." In Mathematical Finance, 89–98. Basel: Birkhäuser Basel, 2001. http://dx.doi.org/10.1007/978-3-0348-8291-0_8.

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Ingersoll, J. E. "General One-Period Models." In Mathematical Finance and Probability, 111–28. Basel: Birkhäuser Basel, 2003. http://dx.doi.org/10.1007/978-3-0348-8041-1_6.

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Dikta, Gerhard. "Semi-parametric Random Censorship Models." In From Statistics to Mathematical Finance, 43–56. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50986-0_3.

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Taniguchi, Setsuo. "Stochastic Analytical Models in Mathematical Finance." In Mathematics for Industry, 263–77. Tokyo: Springer Japan, 2014. http://dx.doi.org/10.1007/978-4-431-55060-0_20.

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McLeish, D. L., and A. W. Kolkiewicz. "Fitting Diffusion Models in Finance." In Institute of Mathematical Statistics Lecture Notes - Monograph Series, 327–50. Hayward, CA: Institute of Mathematical Statistics, 1997. http://dx.doi.org/10.1214/lnms/1215455054.

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Gökay, Selim, Alexandre F. Roch, and H. Mete Soner. "Liquidity Models in Continuous and Discrete Time." In Advanced Mathematical Methods for Finance, 333–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18412-3_13.

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Bender, Christian, Tommi Sottinen, and Esko Valkeila. "Fractional Processes as Models in Stochastic Finance." In Advanced Mathematical Methods for Finance, 75–103. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18412-3_3.

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González-Manteiga, Wenceslao, Jorge Passamani Zubelli, Abelardo Monsalve-Cobis, and Manuel Febrero-Bande. "Goodness–of–Fit Test for Stochastic Volatility Models." In From Statistics to Mathematical Finance, 89–104. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50986-0_6.

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Mijatović, Aleksandar, and Martijn Pistorius. "Exotic Derivatives under Stochastic Volatility Models with Jumps." In Advanced Mathematical Methods for Finance, 455–508. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18412-3_17.

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Conference papers on the topic "Finance – Mathematical models – Swaziland"

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Chiarella, Carl, Sara Pasquali, and Wolfgang J. Runggaldier. "On Filtering in Markovian Term Structure Models." In Proceedings of the International Conference on Mathematical Finance. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812799579_0012.

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Ma, Jin, and Xiaodong Sun. "Sharp Estimates of Ruin Probabilities for Insurance Models Involving Investments." In Proceedings of the International Conference on Mathematical Finance. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812799579_0007.

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Gyulov, Tihomir B., Radoslav L. Valkov, George Venkov, Ralitza Kovacheva, and Vesela Pasheva. "Classical and Weak Solutions for Two Models in Mathematical Finance." In APPLICATIONS OF MATHEMATICS IN ENGINEERING AND ECONOMICS (AMEE '11): Proceedings of the 37th International Conference. AIP, 2011. http://dx.doi.org/10.1063/1.3664370.

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Perrotta, Adamaria. "A learner-centered approach to design a Computational Finance module in higher education." In Seventh International Conference on Higher Education Advances. Valencia: Universitat Politècnica de València, 2021. http://dx.doi.org/10.4995/head21.2021.12955.

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In this paper, we describe our design of ACM30070 “Computational Finance”, a core module in the BSc in Financial Mathematics in the School of Mathematics and Statistics. The over-arching purpose of this module is to help students to develop mathematical, statistical and coding skills, along with significant knowledge and critical thinking, that allows them to effectively construct, manipulate and visualize financial datasets and to build financial mathematical models. The use of computation and a FinTech software (FinCad Analytics) are pointed out as essential to facilitate sensemaking in computational finance. More broadly, we discuss the education-research based rationale behind the “learning by doing” and “flipped classroom” institutional models that we have chosen for ACM30070, and we show how the modern “inclusive” definition of computation has been embedded into the learning activities. An accurate description of the design principles and implementation is also presented. At the end of the paper, we briefly introduce a discipline-based education research that will follow from this module design.
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