牟两仪

作为曼彻斯特大学金融博士生和CFA持证人,我精通包括风险中性概率,市场微观结构,和最前沿的概率恢复理论等各种金融理论。具有指数期权,个股期权,以及外汇期权的丰富经验。熟悉各种常用数据库, 包括OptionMetrics, Bloomberg, Tomson Reuters DataScope, CRSP, DataStream,以及万德数据库。善于多平台工作和利用各种软件优势,例如使用Python处理tick级别大数据, 用R语言应用高级统计模型,通过MATLAB进行复杂数学计算等。

教育经历

  • 博士专业:金融学
  • 相关课程:高级金融理论,高级金融研究研讨,实证公司金融等
  • 研究课题: 期权隐含信息与高频数据
  • 导师: Yoichi Otsubo, Prof. Alexandros Kostakis
  • 全额奖学金:Alliance Manchester Business School Doctoral Studentships
  • 课题第一章:Detecting political event risk in option market.
  • 关键字:Political Event Risk, Option-Implied Information, Risk-Neutral Distribution, Implied Volatility Curve, Brexit Referendum.
  • 课题第二章:Market Quality and Price Informativeness: Evidence from Extended Trading Hours
  • 关键字:Market Design; Liquidity; Extended Trading Hours; Asymmetric Information; Informed Trading; Predictability.
  • 硕士专业:量化金融学;
  • 学位总评优秀 (Distinction);
  • 论文(优秀,Distinction):为基于欧式期权的风险中性概率以及真实概率分析,并且应用累积前景理论到真实概率分析;
  • 关键字:Risk-Neutral Distribution, 2008 crises, NDX, Cumulative prospect theory, physical distribution;
  • 2016年作为本校学生代表兰卡斯特大学参加2016 年CFA 协会举办的股票研究比赛.
  • 学士专业: 应用物理学
  • 2009年校三好学生
  • 雅思:7分

工作论文

Authors: Alexandros Kostakis, Liangyi Mu, Yoichi Otsubo

Keywords: Political Event Risk, Option-Implied Information, Risk-Neutral Distribution, Implied Volatility Curve, Brexit Referendum.

Methods: Non-parametric Risk-Neutral Distribution (Figlewski (2010)), Option-Implied Event Probability (Borochin and Golec (2016)).

Data: Daily GBPUSD FX options data from the Chicago Mercantile Exchange, 10-minute intraday OTC GBPUSD FX options data from Bloomberg, daily FTSE 100 index options data from the Intercontinental Exchange.

Key findings:

  • Option market can ex ante detect and quantify the event risk due to a scheduled political process.
  • GBPUSD options market exhibits bimodal risk neutral distribution and W-shaped implied volatility curve before the Brexit referendum date with modes indicating possible event outcomes.
  • Implied event probability and information about latent states can be extracted from option market.
  • Option market can distinguish the different impacts on different assets from the same political event.

Author: Liangyi Mu

Keywords: Market Design; Liquidity; Extended Trading Hours; Asymmetric Information; Informed Trading; Predictability.

Methods: Market quality measures (trading volume, bid ask spread, information asymmetry), Spread Decomposition models (Huang and Stoll (1997), Lin, Sanger, and Booth (1995)), Difference-in-differences analysis on market quality (Anand, Hua and McCormick (2016)).

Data: Tick-by-tick S&P 500 index weekly options and SPDR options with all strikes and expiries from Tomson Reuters DataScope.

Key findings:

  • Liquidity traders and informed traders have different intraday strategic decisions, resulting in intertemporal liquidity externality in option market.
  • Option market in extended trading hours presents low market quality and trading activity.
  • The introduction of extended trading hours has enhanced market quality in regular trading hours.
  • The option prices in extended trading hours are informative for the following regular trading hours.

A joint project with Dr. Yoichi Otsubo and Xiangjin Shen from the Bank of Canada.

学术报告

  • Alliance Manchester Business School Doctoral Conference, May 2018;
  • SoFiE Financial Econometrics Summer School (The Econometrics of Foreign Exchange Markets), Kellogg School of Management, Northwestern University, July 2019;
  • SoFiE Financial Econometrics Summer School (The Econometrics of Derivatives Markets), New York University Shanghai, August 2019.
  • 6th Young Finance Scholars Conference, University of Sussex, June 2019;
  • Federal of Business Disciplines / Southwestern Finance Association Annual Meeting, San Antonio, March 2020;
  • British Accounting and Finance Association Annual Conference, University of Southampton, Cancelled due to Covid-19, April 2020;
  • European Financial Management Association (EFMA) conference, Cancelled due to Covid-19, June 2020.

教学经历

  • 课程协助: 本科生暑期海外交换项目;
  • 助教: 投资分析(2019, 2020); 公司金融和金融工具入门(2019, 2020); 金融工程(2020);
  • 组织研讨会,为学生提供辅导,批改试卷,制作网上教学材料。

工作经历

  • 阅读研报,使用MATLAB,Python 和WIND,获取A股相关数据并清洗,进行量化分析、构建投资策略并回测;
  • 对策略进行各项指标分析,归因分析,风险分析,参数敏感性分析;
  • 建立周市场动态自动监控,对市场资金、市场情绪、以及市场风格进行周频监控跟踪;
  • 具有不同频率数据处理经验,包括日频、小时、5分钟、3分钟数据;
  • 对多种模型策略进行分析、改良,例如HMM、单项波动率、时间序列动量等;
  • 精细化研究股票市场情况,根据流动性实施不同程序化下单策略;
  • 制作并维护股票多头策略监控下单程序以及动态净值监控程序,确保下单指令与策略一致;
  • 关注其他股票多头策略基金表现,分析其采用的投资策略;
  • 跟踪券商每周发布的投资建议,并对其建议进行汇总分析;
  • 为公司制定股票多头交易流程规范;
  • 在公司内部对其他员工进行股票多头市场知识普及培训。

成就:

  • 所开发的基于沪深300 多因子选股择时策略在所管理期限内(4-2017.6)获得累计收益7.88%;
  • 所在量化股票多头策略组资金管理规模超过一亿,参与管理相关产品近20个。参与基金产品建仓,调仓,平仓全过程。
  • 定期分析宏观因素(货币,财政)和政府政策对房地产行业的影响。明确行业所处周期,并预测行业未来发展情况;
  • 整理并对比分析行业其他公司,对当地房地产市场进行投资调查分析;
  • 协助财务负责人处理公司财务运营相关事宜,协助税务规划,进行内部财务分析,定期向总经理汇报公司财务状况;
  • 管理并配置公司流动资金,进行资本预算,管理融资事宜;
  • 对公司项目开展财务与投资分析,预测现金流,分析盈亏平衡点等;
  • 协助、审阅、检查法务部起草的文件、合同。整理并执行房地产行业相关法律法规;
  • 协助公司总经理处理公司日常管理工作,管理各投资项目;
  • 管理工程施工团队。

相关证书

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推荐人

Dr. Yoichi Otsubo (Main Ph.D. supervisor)

Lecturer in Finance

University of Manchester

M15 6PB

Phone: +44 (0) 161 275 4025

Email: yoichi.otsubo@manchester.ac.uk

Prof. Alexandros Kostakis (Ph.D. Cosupervisor)

Head and Professor in Accounting and Finance

University of Liverpool

L69 7ZX

Phone: +44 (0)151 795 3820

Email: A.Kostakis@liverpool.ac.uk