Journal articles on the topic 'Options (Finance) Australia Mathematical models'

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.

The Haldia port is situated in the Hooghly estuary, 104 km downstream of Kolkata Port. As a result of high sedimentation, the navigational channel to the Haldia Port is maintained with great amount of dredging (25 MCM per Annum). The paper presents a study carried out to find a solution to improve the channel depth together with minimum maintenance dredging. A desk study was carried out to identify the historical formation of the estuary and the remedial measures implemented in the past. A detailed field investigation was carried out to obtain the relevant data for the calibration of numerical models. 1D (MIKE 11) river hydrodynamic modelling was carried out using the available bathymetric data to supply upstream boundary conditions for the 2D (MIKE 21) and 3D (MIKE 3) numerical models. Number of possible scenarios were tested through MIKE 21 hydrodynamic modelling to select more feasible options. Selected options were further assessed through morphodynamic and 3D hydrodynamic modelling to examine the long term sustainability of the proposed solutions. Finally, the option which comprise of; approach channel through Balari Passage & closure of the Shore Attached Channel was selected as the best option. The selected option was further studied taking navigational aspects, dredging efforts and construction sequence into consideration.

We consider calibration problems for models of pricing derivatives which occur in mathematical finance. We discuss various approaches such as using stochastic differential equations or partial differential equations for the modeling process. We discuss the development in the past literature and give an outlook into modern approaches of modelling. Furthermore, we address important numerical issues in the valuation of options and likewise the calibration of these models. This leads to interesting problems in optimization, where, e.g., the use of adjoint equations or the choice of the parametrization for the model parameters play an important role.

Abstract. Required in a wide range of applications in, e.g., finance, engineering, and physics, first-passage time problems have attracted considerable interest over the past decades. Since analytical solutions often do not exist, one strand of research focuses on fast and accurate numerical techniques. In this paper, we present an efficient and unbiased Monte-Carlo simulation to obtain double-barrier first-passage time probabilities of a jump-diffusion process with arbitrary jump size distribution; extending single-barrier results by [Journal of Derivatives 10 (2002), 43–54]. In mathematical finance, the double-barrier first-passage time is required to price exotic derivatives, for example corridor bonus certificates, (step) double barrier options, or digital first-touch options, that depend on whether or not the underlying asset price exceeds certain threshold levels. Furthermore, it is relevant in structural credit risk models if one considers two exit events, e.g., default and early repayment.

We introduce the intensity-based defaultable Lévy Libor model, which generalizes the default-free Lévy Libor model introduced by Eberlein and Özkan in [The defaultable Lévy term structure: Ratings and restructuring, Mathematical Finance13(2) (2003) 277–300], and the intensity-based defaultable model presented by Bielecki and Rutkowski in [Credit Risk: Modeling, Valuation and Hedging, Springer Finance (Springer-Verlag, 2002)] by embedding it in the defaultable HJM framework introduced by Eberlein and Özkan in [The defaultable Lévy term structure: Ratings and restructuring, Mathematical Finance13(2) (2003) 277–300]. We also derive some additional results for defaultable HJM models such as the dynamics of credit spreads. We then go on and model the default-free Libor rates and credit spreads as the primal variable and derive the dynamics of the defaultable Libor rates under the defaultable forward measure. Finally, we derive an explicit formula for options on credit default swaps, using an idea introduced by Raible in [Lévy Processes in finance: Theory, numerics and empirical facts, PhD thesis, University of Freiburg i. Brsg. (2000)].

AbstractBased on the concept of self-decomposability, we extend some recent multidimensional Lévy models built using multivariate subordination. Our aim is to construct multivariate Lévy processes that can model the propagation of the systematic risk in dependent markets with some stochastic delay instead of affecting all the markets at the same time. To this end, we extend some known approaches keeping their mathematical tractability, study the properties of the new processes, derive closed-form expressions for their characteristic functions and detail how Monte Carlo schemes can be implemented. We illustrate the applicability of our approach in the context of gas, power and emission markets focusing on the calibration and on the pricing of spread options written on different underlying commodities.

The purpose of this study was to create quantitative models to value ether, ether futures, and ether options based upon the ability of cryptocurrencies to transform existing intermediary-verified payments to non-intermediary-based currency transfers, the ability of ether as a late mover to displace bitcoin as the first mover, and the valuation of ether in the context of investor irrationality models. The risk-averse investor’s utility function is a combination of expectations of the performance of ether, expectations of cryptocurrencies’ transformative power, and expectations of ether superseding bitcoin. The moderate risk-taker’s utility function is an alt-Weibull distribution, along with a gamma distribution. Risk-takers have a utility function in the form of a Bessel function. Ether price functions consist of a Levy jump process. Ether futures are valued as the combination of current spot prices along with term prices. The value of spot prices is the product of a spot premium and a lognormal distribution of spot prices. The value of term prices is equal to the product of a term premium, and the Levy jump process of price fluctuations during the delivery period. For ether options, a less risky ether option portfolio offsets ether’s risk by a fixed-income trading strategy.

Although the concept of symmetry is widely used in many fields, it is almost not discussed in finance. This concept appears to be relevant in relation, for example, to mathematical models that can predict stock prices to contribute to the decision-making process. This work considers the stock price of European options with a new class of the non-constant delay model. The stochastic pantograph differential equation (SPDE) with a variable delay is provided in order to overcome the weaknesses of using stochastic models with constant delay. The proposed model is constructed to improve the evaluation process and prediction accuracy for stock prices. The feasibility of the proposed model is introduced under relatively weak conditions imposed on its volatility function. Furthermore, the sensitivity of time lag is discussed. The robust stochastic theta Milstein (STM) method is combined with the Monte Carlo simulation to compute asset prices within the proposed model. In addition, we prove that the numerical solution can preserve the non-negativity of the solution of the model. Numerical experiments using real financial data indicate that there is an increasing possibility of prediction accuracy for the proposed model with a variable delay compared to non-linear models with constant delay and the classical Black and Scholes model.

The aim of this paper is to assess the potential impacts of different fertilizer subsidy reform options on the performance of the Iranian crops production sector. This is achieved using a Regional Crop Programming (RCP) model, based on Positive Mathematical Programming, which includes in total 14 crop activities and encompasses 31 administrative regions. The RCP model is a collection of micro-economic models, working with exogenous prices, each representing the optimal crop allocation at the regional level. The model is calibrated against observed data on crop acreage, yield responses to nitrogen application, and exogenous supply elasticities. Simulation results show that a total removal of nitrogen fertilizer subsidies would affect the competitiveness of crops with the highest nitrogen application rates and lead to a slight reduction of national agricultural income, at approximately 1%. This effect, which is more pronounced at the regional level, is driven by area reallocation rather than land productivity. The reallocation of nitrogen fertilizer subsidy to only strategic crops boost their production and income but increase disparity among regions and affects negatively welfare compared to the current universal fertilizer program. The transfer efficiency analysis shows that both target and universal simulated options are inefficient with an efficiency score below one.

Ensuring the security of a software product in the conditions of large companies, taking into account confidential financial and corporate data, is quite an urgent topic in 2021-2023. Over the past year, the number of leaks of confidential information reached a historic peak, together with cyber attacks, and amounts to 114 identified cases. In modern conditions, software security testing is aimed at identifying security errors and design flaws at all stages of the software development lifecycle. At the same time, at the design stage, this type of work should be provided in order to facilitate the implementation of these characteristics in the final version of the security-related system. Research has shown that there is a wide range of opportunities for developing and using security testing software. These options may differ in implementation technologies, cost and other tactical and technical indicators, characteristics of individual elements, and so on. The main task of developing a software security testing method is to develop, improve and select models, methods and tools that belong to a subset and provide maximum software security indicators. Our approach allows us to prevent any penetration into the information system, while maintaining 100% security of confidential files and the system as a whole. The threat prevention model works with the help of proactive technology, and if you calculate the economic effect of these measures, it can be different, depending on the value of the enterprise’s information itself, and can also be calculated in millions of US dollars. The reliability of the results of mathematical modelling of technologies for creating and implementing «penetration testing» tools is evaluated. The experimental results showed that for all the studied data types, the confidence probability that the value of the statistical value «does not deviate» from the mathematical expectation by more than 1 is 0.94.

Studies have demonstrated the potential of real options analysis (ROA) in property development decision-making. However, practitioners have yet to accept, adopt and integrate ROA in property development decision-making in Australia. This paper therefore investigates how Australian residential property developers manage uncertainties and risks, examines flexibility as a risk management tool, and evaluates the receptiveness and acceptance of ROA for decision making. Data are collected through face-to-face semi-structured interviews with twelve participants, and analysed by using thematic analysis. The results indicate that a discount rate is insufficient for managing uncertainties and risks; rather, contingency is used. Receptiveness and acceptance of the RO theory are mixed due to lack of unanimity among responses. Some participants are positive about flexibility, while others are dismissive. Beyond quantitative ROA models, the findings suggest that practitioners are receptive to ROA, but concerns remain over adoption. Flexibility cases executed by some participants in practice indicate that practitioners are subconsciously using ROA. Therefore, it is possible that acceptance and adoption could be achieved in the future. Evidence of the use of contingency as a risk management tool challenges the long-held notions of risk-return relationships in property development and investment. This is initial evidence of qualitative research on ROA in practice within Australian property developments.

The study proposes an innovative application of Discrete Event Simulations (DES) and System Dynamics (SD) theory to the pricing of a certain kind of certificates very popular among private investors and, more generally, in the context of wealth management. The paper shows how numerical simulation software mainly used in traditional engineering, such as industrial and mechanical engineering, can be successfully adapted to the risk analysis of structured financial products. The article can be divided into three macro-sections: in the first part a synthetic overview of the most widespread option pricing models in the quantitative finance branch is given to the readers together with the fundamental technical-instrumental background of the implemented DES and SD simulator. After dealing with some of the most popular models adopted for Equity and Equity index options, which are the most common underlying assets for the certificates structuring, we move, in the second part, to describe how the mathematical models can be integrated into a general simulation environment able to provide both DES and SD extensively used in the engineering field. The core stochastic differential equation (SDE) will therefore be translated, together with all its input parameters, into a visual block model which allows an immediate quantitative analysis of how market parameters and the other model variables can change over time. The possibility for the structurer to observe how the variables evolve day-by-day gives a strong sensitivity to evaluate how the price and the associated risk measures can be directly affected. The third part of the study compares the results obtained from the simulator designed by the authors with the more traditional pricing approaches, which consist in programming Matlab® codes for the numerical integration of the core stochastic dynamics through a Euler-Maruyama scheme. The comparison includes a price check using the Bloomberg® DLIB pricing module and a check directly against the valuation provided by the counterparty. In this section, real market cases will therefore be examined with a complete quantitative analysis of two of the most widespread categories of certificates in wealth management: Multi-asset Barrier Reverse Convertible with Issuer Callability and Multi-asset Express Certificate with conditional memory fixed coupon.

Not so long ago, defining green energy was generally straightforward: renewables. It may not have been quite that simple, but the development of agreed-upon definitions based on science has become much more complex and contentious, even within the past year. It’s not just a highbrow debate about semantics. The standardization of criteria or a widely accepted taxonomy is critical as the focus increases on not only greenwashing, but on the actual processes and technologies enabling what were thought of as at least “greener” energy. The hammering out of definitions is needed to keep the energy transition moving forward globally. This scrutiny affects the options for companies seeking alternatives in carbon markets where the price of permits for emitting a tonne of CO2 is escalating. In early February, the price of CO2 permits in the EU reached a record high above 96 Euros ($109)/tonne CO2. Reuters reported that the carbon price has risen more than 200% since the start of 2021, partly due to high natural gas prices and the switch made to coal by some power generators. This resulted in higher emissions and increased the demand for permits. In January, the EU Platform on Sustainable Finance, comprising members from utilities, banks, nongovernmental organizations, and corporations, rejected the EU Commission’s draft sustainable finance rules which proposed labeling nuclear power and natural gas as green transition fuels. Nuclear projects permitted until 2045 were to be classified as green, but only if countries can safely dispose of the radioactive waste. Gas was to be included until 2030 with emissions thresholds specified. The EU Platform concluded that even if a gas plant stays under the emissions threshold, it “is not green at any point in its life.” Nuclear energy was acknowledged as already being part of the transitioning energy system and having near to zero greenhouse-gas emissions, but it would not meet the taxonomy’s requirement to “do not significant harm” to the environment because of the toxic waste that cannot be recycled or reused. The EU Commission’s taxonomy will be sent to the European Parliament and Council for review. Blue hydrogen was questioned as a transition fuel by a peer-reviewed study published in August 2021 in Energy Science & Engineering by coauthors from Cornell and Stanford universities. They wrote, “Far from being low-carbon, greenhouse-gas emissions from the production of blue hydrogen are quite high, particularly due to the release of fugitive methane. … Perhaps surprisingly, the greenhouse-gas footprint of blue hydrogen is more than 20% greater than burning natural gas or coal for heat and some 60% greater than burning diesel oil for heat, again with our default assumptions.” They added, “Our analysis assumes that captured carbon dioxide can be stored indefinitely, an optimistic and unproven assumption. Even if true though, the use of blue hydrogen appears difficult to justify on climate grounds.” In a study published last month in the Proceedings of the National Academy of Sciences, researchers at the University of Wisconsin-Madison combined econometric analyses, land use observations, and biophysical models to estimate the realized effects of the US Environmental Protection Agency’s Renewable Fuel Standard (RFS) mandate to partially replace petroleum-based fuels with biofuels. They found that the RFS increased corn prices by 30% and the prices of other crops by 20%, which, in turn, expanded US corn cultivation by 8.7% and total cropland by 2.4% in the years following the policy’s enactment (2008 to 2016). “These changes increased annual nationwide fertilizer use by 3 to 8%, increased water-quality degradants by 3 to 5%, and caused enough domestic land use change emissions such that the carbon intensity of corn ethanol produced under the RFS is no less than gasoline and likely at least 24% higher. These tradeoffs must be weighed alongside the benefits of biofuels as decision makers consider the future of renewable energy policies and the potential for fuels like corn ethanol to meet climate mitigation goals.” The move toward energy transition has been pivotal for our industry and many others. It could be argued that no country, business, or individual will remain unaffected by the changes in progress and yet to come. “Transition” is defined as “the process or a period of changing from one state or condition to another.” And this process will take time, effort, technology, buy-in, scientific study and verification … and consensus, which may be the most challenging piece of all. A significant announcement demonstrating the application and acceptance of a scientific taxonomy was Santos Ltd.’s recent booking of 100 million metric tons of CO2 storage capacity in the Cooper Basin in South Australia. The company believes it represents the industry’s first-ever booking to be made under SPE’s CO2 Storage Resource Management System.

<p style='text-indent:20px;'>In this paper, we develop a Multilayer (ML) method for solving one-factor parabolic equations. Our approach provides a powerful alternative to the well-known finite difference and Monte Carlo methods. We discuss various advantages of this approach, which judiciously combines semi-analytical and numerical techniques and provides a fast and accurate way of finding solutions to the corresponding equations. To introduce the core of the method, we consider multilayer heat equations, known in physics for a relatively long time but never used when solving financial problems. Thus, we expand the analytic machinery of quantitative finance by augmenting it with the ML method. We demonstrate how one can solve various problems of mathematical finance by using our approach. Specifically, we develop efficient algorithms for pricing barrier options for time-dependent one-factor short-rate models, such as Black-Karasinski and Verhulst. Besides, we show how to solve the well-known Dupire equation quickly and accurately. Numerical examples confirm that our approach is considerably more efficient for solving the corresponding partial differential equations than the conventional finite difference method by being much faster and more accurate than the known alternatives.</p>

The purposes of this paper are to improve the scientific processing level of risk management in the financial field, enrich the application range of mathematical models in financial calculations, and comprehensively discuss the theories and concepts of mathematical finance and stochastic differential equations. More importantly, the common option pricing issues in financial risk management have been researched using the forward–backward stochastic differential equation. The fully discrete and uncoupled forward–backward stochastic differential equation is employed to analyze the spread option and the better-of option, the complicated multi-asset options. Results demonstrate that the fully discrete and uncoupled forward–backward stochastic differential equations can effectively price the spread option and the better-of option. Simulation by the MATLAB software suggests that the value of spread option pricing is 0.0264, and the value of the better-of option pricing is 0.0251. The above results can provide scientific and useful references for the subsequent application research on forward–backward stochastic differential equations in the financial field; simultaneously, they also have important practical significance for researching on and developing the financial risk management.

Proceedings of the Second International Conference on Robotics and Artificial Intelligence Editors of the Proceedings Dr.G. Geetha, Advanced Computing Research Society, Chennai, India geetha@advancedcomputingresearchsociety.org Dr. Vincenzo Piuri, University of Milan, Italy vincenzo.piuri@unimi.it Dr. Debao Zhou, University of Minnesota Duluth, USA dzhou@d.umn.edu Preface We are honoured and glad to welcome you at the Second International Conference on Robotics and Artificial Intelligence 2021 organized by Advanced Computing Research Society on 29th and 30th November 2021. Initially, this conference was planned to be held in Chennai. Later on, due to the covid-19 pandemic situation and travel restrictions imposed by various Governments, the options available was to either postpone, cancel or conduct in virtual mode. Postponement was too unsure, since it was not clear when normalcy will be restored, conducive for physical conference. Cancellation of the conference will upset and disappoint people who have contributed to the conference. Hence the committee decided to go for online mode on the same dates as planned earlier. The organizers hosted the conference from Chennai, India. Keynote Speakers were : Dr. Jagannathan Sarangapani Rutledge Emerson Distinguished Professor and NSF I/UCRC Site Director Director, Embedded Control Systems and Networking Laboratory Missouri University Of Science And Technology, USA Dr. Ashwin Ashok Department of Computer Science Georgia State University Atlanta, Georgia, USA Dr. Ramamohanarao Kothagiri Former Professor, Head of the Department and Research Director School of School of Computing and Information Systems, The University of Melbourne, Australia This conference and these proceedings are a unique opportunity for sharing ideas and achievements, discoveries and innovation for growing together our knowledge and contribute to expand the knowledge of humanity. The conference covers topics on robotics, artificial intelligence, computational science, mathematical physics and electronics and devices. We received 48 papers and after peer review 22 papers were accepted and presented in this conference. The papers were evaluated on the basis of completeness, relevance to the conference, originality, sufficiently novel, technical quality, structure and presentation of the paper and adequate references to previous work. Every paper was reviewed by at least 2 reviewers and the review comments were shared with the authors for incorporating the suggestions and comments. The conference had participation from various countries – India, Hongkong, Australia, Romania, United Arab Emirates, United States of America and Peru. Total number of participants were 48. On the day of the conference, all the presenters were able to present online and the sessions were held smoothly as per the schedule. 22 papers were presented in 3 sessions. Each presenter was given 15 minutes for presentation, followed by question-and-answer session. A networking session was also arranged, which enabled the participants to interact, learn and network with each other. We used “Google Meet” as conference platform. We are thankful to the IOP Journal of Physics : Conference Series and its editor for accepting our proposal, for providing valuable guidance and for publishing this conference proceedings. We also thank the Morressier Conference submission and review management for providing software services which enabled timely peer review. We thank all the Committee members for their valuable inputs and time, for making this conference very successful. We thank all the authors and presenters for disseminating their research outcomes through this conference. We appreciate each and everyone who have made this conference meaningful. List of Committees, Technical Program Committee, Budget and Finance Committee are available in this Pdf.