Modern Stochastics: Optional Processes and their Applications
现代随机指标:可选过程及其应用
基本信息
- 批准号:RGPIN-2019-04922
- 负责人:
- 金额:$ 1.46万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2019
- 资助国家:加拿大
- 起止时间:2019-01-01 至 2020-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The cornerstone of modern stochastic analysis is a probability space equipped with filtration as a non-decreasing family of sigma-algebras. The well-developed theory of stochastic processes assumes “usual conditions”, when filtration is complete and right-continuous. This theory generated many important results in probability theory, statistics, mathematical finance etc. In 1975 famous experts in stochastic processes Doob and Dellacherie initiated studies of stochastic processes without this technical assumption. Further developments were done by Lepingle, Horowitz, Lenglart, and mostly by Galtchouk. Their parallel version of stochastic analysis deals with optional processes admitting regular trajectories. The existence of such initial theory calls for a new initiative for its further developments and applications today with its new challenges. The goal of the proposal is to take a new look at optional processes bringing new methods, techniques and results to mathematical finance and related areas. In the proposal, we are going to investigate stochastic differential equations with respect to optional semimartingales in the sense of existence of strong solutions and their path-wise comparison properties. The results will be applied to approximate option price bounds and other financial quantities in the markets driven by optional processes. The problem of approximate pricing will be also investigated with the help of extensions of probability distributions of stock returns using orthogonal polynomials and the Pade rational approximations. We are going to use the technique of optional processes in option pricing problem in the area of mergers and acquisitions, where jump processes promise to create an adequate pricing model. We investigate a possibility to obtain a version of the uniform Doob-Meyer decomposition of optional supermartingales. Its fundamental role in mathematical finance is well-established due to its application to superhedging problem in incomplete markets, markets with transaction costs and other market restrictions. We also want to show how this decomposition can be exploited to construct an optimal filter in the filtering problem for optional semimartingales which covers many well-known models. Besides optional decomposition, we will derive a version of the Galtchouk-Kunita-Watanabe representation for optional martingales with further applications to mean-variance hedging problem. Another fundamental problem known in mathematical finance as insider trading will be treated based on the calculus of optional processes. The parameter estimation problem for optional semimartingales will be investigated. These results are reasonable to provide an adequate calibration in the markets driven by optional processes and to create a general framework for many regression models exploited in mathematical finance and statistics. The Proposal is wide enough to accommodate a number of student research projects of master's and PhD levels.*****
现代随机分析的基石是一个具有过滤的概率空间,它是一个非递减的西格玛代数族。成熟的随机过程理论假定“通常条件”,即过滤是完全的和右连续的。这一理论在概率论、统计学、数理金融学等领域产生了许多重要成果。1975年,著名的随机过程专家Doob和delacherie在没有这种技术假设的情况下开始了随机过程的研究。进一步的发展由Lepingle, Horowitz, Lenglart和Galtchouk完成。他们的平行版本的随机分析处理承认规则轨迹的可选过程。这种初始理论的存在,在其面临新的挑战的今天,要求对其进一步发展和应用提出新的倡议。该提案的目标是重新审视可选过程,为数学金融和相关领域带来新的方法、技术和结果。在本文中,我们将研究关于可选半鞅的强解存在意义下的随机微分方程及其路径比较性质。结果将被应用于近似期权价格边界和其他金融数量在市场上由可选过程驱动。本文还将利用正交多项式和Pade有理逼近来扩展股票收益的概率分布,研究近似定价问题。我们将在并购领域的期权定价问题中使用可选过程的技术,其中跳跃过程有望创建一个适当的定价模型。我们研究了获得可选上鞅的统一Doob-Meyer分解的一种可能性。由于将其应用于不完全市场、具有交易成本的市场和其他市场限制的超套期保值问题,它在数学金融中的基本作用已经确立。我们还想展示如何利用这种分解在可选半鞅的过滤问题中构造一个最优滤波器,该问题涵盖了许多众所周知的模型。除了可选分解外,我们还将推导出可选鞅的Galtchouk-Kunita-Watanabe表示的一个版本,并进一步应用于均值-方差对冲问题。另一个在数学金融学中被称为内幕交易的基本问题将基于可选过程的演算来处理。研究了可选半鞅的参数估计问题。这些结果是合理的,可以为可选过程驱动的市场提供充分的校准,并为数学金融和统计学中使用的许多回归模型创建一个一般框架。该提案的宽度足以容纳一些硕士和博士水平的学生研究项目。*****
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
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Melnikov, Alexander其他文献
COMPUTABLE POLISH GROUP ACTIONS
- DOI:
10.1017/jsl.2017.68 - 发表时间:
2018-06-01 - 期刊:
- 影响因子:0.6
- 作者:
Melnikov, Alexander;Montalban, Antonio - 通讯作者:
Montalban, Antonio
FOUNDATIONS OF ONLINE STRUCTURE THEORY
- DOI:
10.1017/bsl.2019.20 - 发表时间:
2019-06-01 - 期刊:
- 影响因子:0.6
- 作者:
Bazhenov, Nikolay;Downey, Rod;Melnikov, Alexander - 通讯作者:
Melnikov, Alexander
COMPUTABLE TOPOLOGICAL GROUPS AND PONTRYAGIN DUALITY
- DOI:
10.1090/tran/7355 - 发表时间:
2018-12-01 - 期刊:
- 影响因子:1.3
- 作者:
Melnikov, Alexander - 通讯作者:
Melnikov, Alexander
Bernstein's inequalities and their extensions for getting the Black-Scholes option pricing formula
- DOI:
10.1016/j.spl.2016.01.002 - 发表时间:
2016-04-01 - 期刊:
- 影响因子:0.8
- 作者:
Glazyrina, Anna;Melnikov, Alexander - 通讯作者:
Melnikov, Alexander
COMPUTABLE FUNCTORS AND EFFECTIVE INTERPRETABILITY
- DOI:
10.1017/jsl.2016.12 - 发表时间:
2017-03-01 - 期刊:
- 影响因子:0.6
- 作者:
Harrison-Trainor, Matthew;Melnikov, Alexander;Montalban, Antonio - 通讯作者:
Montalban, Antonio
Melnikov, Alexander的其他文献
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{{ truncateString('Melnikov, Alexander', 18)}}的其他基金
Modern Stochastics: Optional Processes and their Applications
现代随机指标:可选过程及其应用
- 批准号:
RGPIN-2019-04922 - 财政年份:2022
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
Modern Stochastics: Optional Processes and their Applications
现代随机指标:可选过程及其应用
- 批准号:
RGPIN-2019-04922 - 财政年份:2021
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
Modern Stochastics: Optional Processes and their Applications
现代随机指标:可选过程及其应用
- 批准号:
RGPIN-2019-04922 - 财政年份:2020
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
Advanced stochastic methods in mathematical finance and related fields
数学金融及相关领域的高级随机方法
- 批准号:
RGPIN-2014-05901 - 财政年份:2018
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
Advanced stochastic methods in mathematical finance and related fields
数学金融及相关领域的高级随机方法
- 批准号:
RGPIN-2014-05901 - 财政年份:2017
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
Advanced stochastic methods in mathematical finance and related fields
数学金融及相关领域的高级随机方法
- 批准号:
RGPIN-2014-05901 - 财政年份:2016
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
Advanced stochastic methods in mathematical finance and related fields
数学金融及相关领域的高级随机方法
- 批准号:
RGPIN-2014-05901 - 财政年份:2015
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
Advanced stochastic methods in mathematical finance and related fields
数学金融及相关领域的高级随机方法
- 批准号:
RGPIN-2014-05901 - 财政年份:2014
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
New developments in stochastic analysis with applications to option pricing and risk management
随机分析的新发展及其在期权定价和风险管理中的应用
- 批准号:
261855-2009 - 财政年份:2013
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
New developments in stochastic analysis with applications to option pricing and risk management
随机分析的新发展及其在期权定价和风险管理中的应用
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261855-2009 - 财政年份:2012
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
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