通货膨胀背景下的金融衍生产品创新

通货膨胀背景下,在金融衍生品市场开发通货膨胀指数型衍生证券,成为规避通货膨胀风险,保护资产价值的一种方法.本文主要通过分析金融产品创新的背景和意义,对通货膨胀指数型衍生证券定价进行理论探索,并利用蒙特卡罗模拟方法改进技术,对通货膨胀指数型欧式看涨期权进行定价分析.最终得出结论:开发通货膨胀指数型衍生证券对于规避通货膨胀风险有一定的作用,基于产品本身的复杂性,利用蒙特卡罗模拟技术为产品定价在理论上有很大的可行性,且利用蒙特卡罗模拟方法改进技术--带beta系数的控制变量技术,无论在模拟时间还是收敛性方法都效果良好.     

衍生证券定价蒙特卡罗模拟的方差减少方法述评

蒙特卡罗模拟方法是一种重要的衍生证券定价数值方法，相比基于Nack-Scholes公式的解析方法具有更广的适用性和更强的兼容性；比较其他数值模拟方法则有估计误差及收敛速度与问题的维数独立的明显优势，能够较好地解决基于多标的变量的高维衍生证券的定价问题。     

证券信用交易对市场效率的影响:一个文献综述

近年来,关于证券信用交易特别是卖空机制和卖空限制方面的研究逐渐成为西方金融学界研究的一个热点问题。相关的研究主要集中在证券信用交易对市场定价效率、市场波动率,以及市场流动性的影响,本文将对这一领域的研究进展做一简单的文献述评。     

资本资产定价模型在中国股票市场的实证研究

资本资产定价模型是在投资组合理论和资本市场理论基础上形成发展起来的,主要研究证券市场中资产的预期收益率与风险资产之间的关系,以及均衡价格的形成。它使得证券理论从以往的定性分析转入定量分析,从规范性转入实证性,进而对证券投资的理论研究和实际操作,甚至整个金融理论与实践的发展都产生了巨大影响,成为现代金融学的理论基础。本文主要利用数值分析理论对股票数据进行迭代,得到拟合参数,推导资本资产定价模型在中国股市的应用情况。对经典CAPM模型在中国股票市场进行研究分析,计算其组合的收益率与风险关系,分析其与中国股市的符合程度,进而考察其在中国股票市场的有效性和可行性。通过分析,资本资产定价模型在中国股票市场都有较好地解释,随着中国股票市场的日趋完善,资本资产定价模型将会有着更令人期待的实际应用价值。     

期权理论在公司理财中的具体应用

当今被广泛运用的世界期权交易定价的主要理论就是由Fisher Black和Myron Scholes于1973年创立并公诸于世的期权定价模型,也称为 B-S期权定价模型。B-S模型以不支付红利的欧式股票期权作为研究对象,在一系列严格的假设务件下,建立一种无风险证券组合,即买入一个股票头寸和一个以该种股票为标的物的欧式期权,在任意一个短时期内两者高度相关, 则股票头寸的盈利(或损失) 总是与期权的损失(或盈利) 相抵销,因而在短时期末证券组合的总价值也就确定了,通过数学的积分方法就可以确定欧式期权的价格。如今, B-S模型已经被广泛应用于各种金融衍生工具的定价,如股票指数期权、外汇期权及可转换债券、认股权证等等,进而又延伸到保险、抵押、实质投资和贸易等领域的风险管理上。     

由购车价差分析汽车定价中应注意的问题

一、研究背景和意义 目前价差理论多用于金融领域的研究,如：价差参数是银行在黄金买卖中为获得利润而设定的一种参数,使成交价格在买入时稍低于中间价．而卖出时稍高于中间价。在股票界,价差是指买方出价及卖方要价间的差别,即买方出价是卖出证券时所收到的价格。而卖方要价是买人证券时所要付的价格。将价差理论引入汽车定价策略与消费者感知研究中,很适合汽车市场中间商加价统一标准不明显、消费者需求价格弹性较高、各品牌竞争激烈的特点,并且具有一定创新意义。另外,掌握价差分析法对于汽车生产者合理定价、市场情况预测、制定应对竞争对手的策略占领竞争优势有指导性作用。     

用远期中性概率测度给固定收益衍生品定价研究

基于风险中性测度在一些衍生证券定价中的复杂性,提出一种新的测度变换方法——远期中性概率测度。在该测度基础上,构造鞅过程可以对一些固定收益衍生品定价,进一步给出零息债券的欧式期权、利率上限期权的定价公式。     

数学在金融中的应用研究

数学作为现代科学的重要基础之一,自古以来就扮演着推动全领域发展的重要角色,其重要性不言而喻。金融领域作为统领世界资本要素流动的主要领域,在经济全球化发展的时代,赢得了社会各界的广泛关注。基于这一基础,浅析数学在金融中的应用,从金融数学的概念定义出发,解析了期权定价模型,证券投资组合模型和资产估价模型三种经典的金融问题,并解释了数学在其中扮演的强大作用。     

金融互换再衍生限定化制度初探

针对2008年金融海啸中所反映出来的金融衍生产品的再衍生性是否需要被限定的重大现实问题,本文通过对金融海啸以及金融互换类金融衍生工具衍生性的侧重性分析,认为衍生层数过多是导致金融海啸与经济危机的重要原因,应当对金融互换产品以及其他金融衍生品的衍生层数进行必要的限定,并进一步在此基础上提出了金融互换再衍生限定化制度的初步理论与内容构想,并认为金融互换再衍生限定化制度的思想方法完全适用于其他金融衍生品的再衍生限定化制度的创建.     

基于Black-Scholes公式的供应链期权契约的定价研究

在Stackelberg博弈理论的L-F(Leader-Follower)方式下,一个两级化供应链通过引入供应链期权契约,实施风险分担。供应商作为领导者,需要提供一套行之有效的价格参数,以达到供应链协调。因为期权本身属于金融衍生工具,所以考虑引入金融期权的定价方式对期权供应链契约中的期权定价进行讨论。结果得到计算期权价格以及期权执行价格方程组。     

国债金融效应:基准利率视角的分析

本文从我国金融市场的发展现状出发,分析了国债利率成为我国金融市场基准利率的必然性和现实性。市场基准利率及其期限结构是一切金融产品的公正定价的基础,因此,作为基准利率的提供者,发达的国债市场是企业债券市场发展、衍生产品创新的前提条件。同时,金融市场的有效性有赖于金融产品的正确定价,本文以股票市场为例证明国债利率对于金融市场效率的提升具有重要作用。     

Recent advances in reinforcement learning in finance

The rapid changes in the finance industry due to the increasing amount of data have revolutionized the techniques on data processing and data analysis and brought new theoretical and computational challenges. In contrast to classical stochastic control theory and other analytical approaches for solving financial decision-making problems that heavily reply on model assumptions, new developments from reinforcement learning (RL) are able to make full use of the large amount of financial data with fewer model assumptions and to improve decisions in complex financial environments. This survey paper aims to review the recent developments and use of RL approaches in finance. We give an introduction to Markov decision processes, which is the setting for many of the commonly used RL approaches. Various algorithms are then introduced with a focus on value- and policy-based methods that do not require any model assumptions. Connections are made with neural networks to extend the framework to encompass deep RL algorithms. We then discuss in detail the application of these RL algorithms in a variety of decision-making problems in finance, including optimal execution, portfolio optimization, option pricing and hedging, market making, smart order routing, and robo-advising. Our survey concludes by pointing out a few possible future directions for research.     

Exchange traded contracts for difference: Design,pricing, and effects

Contracts for Difference (CFDs) are a significant financial innovation in the design of futures contracts. Over‐the‐counter trading in the UK is significant and has created controversy, but there is no published academic research into the design, pricing, and effects of CFDs. This study analyzes CFD contract design and pricing. It uses a unique database of trades and quotes on exchange traded equity CFDs introduced by the Australian Securities Exchange to test theoretical pricing relationships, and draws out implications for successful design and trading arrangements for the introduction of new derivative contracts. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark     

General equilibrium and preference free model for pricing options under transformed gamma distribution

The gamma class of distributions encompasses several important distributions, either as special or limiting cases or through simple transformations. Here we derived closed form and preference free European option pricing formulae for various (transformed) gamma distributions under the general equilibrium RNVR framework. The gamma class of distributions is used historically in hydrology for modelling natural events. Our models can be used to price derivatives associated with these natural phenomena, which will help to encourage greater risk sharing through financial securitization. Our pricing formulae are theoretically sound even if the underlyings and the derivative instruments are not (frequently) traded. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:409–431, 2010     

无套利分析在非完美条件下远期合约定价中的运用

无套利分析方法是现代金融理论的基石之一,已成为金融衍生品定价的一种重要方法,传统的金融工程教科书很少涉及非完美条件下远期合约的定价问题。在介绍无套利分析方法的基础上,通过现金流复制技术,研究了三种非完美条件下远期合约的定价问题。     

细胞神经网络在通信信号处理中的研究进展

本文旨在通过分析亚洲区域经济合作所面临的艰难和曲折的原因,并在简要介绍和分析亚洲区域经济合作出现的新动向的基础上,提出中国应对经济全球化和参与亚洲区域经济合作的因应对策。     

How far have we come and where should we go after 30+ years of research on Africa's emerging financial markets? A systematic review and a bibliometric network analysis

In this study, we perform a systematic literature review and a bibliometric network analysis of studies on Africa's financial markets from 1992 to 2021. The findings are as follows. First, we observe a steady growth of financial markets research in Africa over the 30-year period under consideration, which is suggestive of increasing interest and commitment to research on financial markets in Africa. Additionally, we note a lack of collaboration between or among researchers of financial markets studies in Africa, which implies very little knowledge exchange, ideas sharing, and innovations. We identify seven major areas of research based on the thematic network and content analysis, which are as follows: (i) asset pricing, (ii) financial integration, (iii) contagion, herding and extreme global events, (iv) efficiency and predictability of stock returns, (v) market interdependencies-sources and channels, (vi) portfolio diversification and risk management strategies, and (vii) impact of economic and financial news. We offer several avenues for future research that can set the agenda for financial market research in Africa in the coming years.     

From Discrete to Continuous Financial Models: New Convergence Results For Option Pricing

In this paper we develop a new notion of convergence for discussing the relationship between discrete and continuous financial models, D ²-convergence. This is stronger than weak convergence, the commonly used mode of convergence in the finance literature. We show that D ²-convergence, unlike weak convergence, yields a number of important convergence preservation results, including the convergence of contingent claims, derivative asset prices and hedge portfolios in the discrete Cox-Ross-Rubinstein option pricing models to their continuous counterparts in the Black-Scholes model. Our results show that D ²-convergence is characterized by a natural lifting condition from nonstandard analysis (NSA), and we demonstrate how this condition can be reformulated in standard terms, i.e., in language that only involves notions from standard analysis. From a practical point of view, our approach suggests procedures for constructing good (i.e., convergent) approximate discrete claims, prices, hedge portfolios, etc. This paper builds on earlier work by the authors, who introduced methods from NSA to study problems arising in the theory of option pricing.     

The Personnel Earthquake Continuum: Consequences of Collective Turnover — A Case Study of Qidian Founders’ Collective Turnover

Unlike previous studies that have primarily focused on the causes and processes, this research emphasizes the consequences of collective turnover. Starting from a literature review, we use event chains to explore the consequences of collective turnover. Based on the case study of the Qidian founders’ collective turnover, we build a holistic theoretical framework to show the dynamics and continuity over time, influenced by the complexity of context. Our main conclusions are as follows: (1) collective turnover has a cascade effect, causing a series of secondary and derivative events, (2) collective turnover has both proximal and distal impacts on human capital flow, operational performance and financial performance, (3) whether or not a collective turnover has a positive or negative effect depends on the context factors. An event chain perspective that extends collective turnover theory and organizational behavior theory is used. We advocate for an integrate understanding of the consequences of collective turnover. In addition, this research will provide practical, instructive policies to intervene in collective turnover.     

Has financial attitude impacted the trading activity of retail investors during the COVID-19 pandemic?

Financial attitude influences the financial behavior of retail investors. Although the extant research has acknowledged and examined this relationship, the measures of financial attitude and behavior still vary widely and are generally posed as a series of questions rather than statements. In addition to this, there is insufficient knowledge regarding retail investors' behavior in the face of a health crisis, such as the current COVID-19 pandemic. This study addresses these gaps in the prior literature by examining the relative influence of six dimensions of financial attitude, namely, financial anxiety, optimism, financial security, deliberative thinking, interest in financial issues, and needs for precautionary savings, on the trading activity of retail investors during the pandemic. Data were collected from 404 respondents and analyzed using the artificial neural network (ANN) method. The results revealed that all six dimensions had a positive influence on trading activity, with interest in financial issues exerting the strongest influence, followed by deliberative thinking. The study thus contributes important inferences for researchers and managers.