【作者】 刘鹏；

【导师】 杜亚斌；

【作者基本信息】 南京大学 ， 金融硕士（专业学位）， 2020， 硕士

【摘要】 金融衍生产品因具有非线性与杠杆性,在金融市场发挥着价格发现,风险转移等诸多不可替代作用。期权作为现代衍生品定价理论的发端,一直占据着学术界和实务界研究热点。以布莱克-斯科尔斯期权定价模型为代表是现代期权定价的基础性工作,但是一直以来对市场微观结构缺少足够的关注。现代金融市场创新层出不穷,不仅新的金融产品被不断地开发出来,金融监管者也在持续地进行监管创新以适应市场需要。本文的主要研究对象就是一项特殊的监管条款而引起的特殊价格模型。本文主要的工作集中在模型的基础理论修正,数值算法和实证比较三个方面。2005年,美国证券交易委员会(SEC)实施了SHO监管规则以约束卖空尤其是裸卖空。该规则要求卖空者必须在自身损失到达一定水平后必须回购一部分的标的来减少对手方的清算风险。且回购价格订单必须高于市场成交价格,导致这种回购行为对价格产生了冲击。期权交易者尤其是做市商,需要频繁多空交易来对冲期权头寸,受价格冲击影响十分明显。尽管主观上并非要从价格下跌中获利,将价格冲击纳入期权定价模型中成为必要的课题。Avellaneda与Lipkin(2009)提出了一种带补偿的泊松过程(Hard-to-borrow Model),将泊松过程强度与股票价格耦合在一起,用来描述这种特殊的卖空-购回行为引发的价格冲击现象。本文在之前Guiyuan Ma(2018),Guiyuan Ma(2019)工作的基础上,修正了HTB模型风险中性测度的错误,给出基于蒙特卡洛模拟下改进方法。中国金融市场市场是处在一个蓬勃发展的新兴市场,市场波动性较大,自身存在着较多的交易限制例如涨跌停和T+1交割。同时中国也在积极发展衍生品市场,其中值得注意的是于2015年推出了基于上证50的ETF期权,为投资者提供了新投资渠道和风险转移的工具。然而衍生品的发展离不开现货市场的积累,现货市场有一个重要的特点就是所谓的卖空限制。中国于2005年立法推出融资融券制度,但是融资融券的标的股票依旧有限。本文用Heston模型,SABR模型,HTB模型对上证50ETF做了参数估计。的时候,本文使用了马尔科夫蒙特卡洛方法估计Heston模型,在估计SABR模型的时候,采用了非线性系数参数估计方法。对于波动率的估计上本文选用了GARCH家族。本文得到的实证结果是,HTB模型的表现稍逊于SABR模型,而优于Heston模型。本文的创新之处在于将期权定价的研究角度扩展至金融市场的微观结构方面,充分考虑监条款的变动而产生的资产交易行为。金融市场的复杂度日益提高,这就要求研究者们更加细致对市场上的各类参与者进行分析。本文有待完善的工作集中在模型的校准,参数估计方面。更多还原

【Abstract】 Financial derivatives play an irreplaceable role in the financial markets as price discovery and risk transfer due to their non-linear and leveraged nature..Options,as the originator of modern derivatives pricing theory,have been occupying academic and practical research hotspots.The Black-Scholes model is the fundamental work of modern option pricing,but there has been a strong focus on market micro structure lacking sufficient attention.Modern financial markets are rife with innovation,and not only are new financial products being developed,but financial regulators are also continuously Regulatory innovation to meet market needs.The main object of this paper is a special price model arising from a particular regulatory provision.The main work in this paper focuses on three aspects of the model: grounded theory modifications,numerical algorithms and empirical comparisons.In 2005,the U.S.Securities and Exchange Commission(SEC)implemented the SHO regulatory rule to govern short selling,especially naked short selling.The rule requires short sellers to repurchase a portion of the underlying to reduce the counterparty’s liquidation risk after their losses reach a certain level..And the repurchase price order must be higher than the market traded price,causing this repurchase to have a price impact.Options traders,especially market makers,are significantly affected by price shocks as they require frequent long and short trades to hedge their options positions.Although it is not subjectively intended to profit from price declines,incorporating price shocks into option pricing models becomes a necessary topic.Avellaneda and Lipkin(2009)propose a Poisson process with compensation(Hard-to-borrow model),which couples the strength of the Poisson process to stock prices,is used to describe this particular The phenomenon of price shocks triggered by shortselling-buyback behavior.This paper is based on previous work by Guiyuan Ma(2018),Guiyuan Ma(2019)Based on the HTB model risk-neutral measurement,the errors are corrected,and the improvement method based on Monte Carlo simulation is given.China’s financial market market is in a booming emerging market,with high market volatility and its own trading restrictions Examples include upside and downside stops and T+1 delivery.China is also actively developing its derivatives market,notably launching an ETF based on the SSE 50 in 2015 Options,which provide investors with new investment channels and risk transfer tools.However,the development of derivatives cannot be separated from the accumulation of the spot market,which has an important feature of the so-called short selling restrictions.In 2005,China legislated the introduction of the financing and securities financing system,but the underlying stocks of financing and securities financing are still limited.In this paper,we use the Heston model,SABR model,and HTB model to estimate the parameters of the SSE 50 ETF.The paper uses Markov Monte Carlo method to estimate the Heston model when estimating the SABR model.The nonlinear coefficient parameter estimation method is used.For the estimation of volatility,the GARCH family is chosen in this paper.The empirical results in this paper show that the HTB model performs slightly worse than the SABR model and better than the Heston model.The innovation of this paper is to extend the research perspective of option pricing to the microstructure of financial markets,taking into account the regulatory provisions.The trading behavior of assets resulting from changes.The increasing complexity of financial markets requires researchers to analyze the various types of market participants in more detail.The work to be done in this paper focuses on the calibration of the model and parameter estimation.更多还原