Liangyi Mu

As a fourth-year Ph.D. student in finance and a Chartered Financial Analyst (CFA) certificate holder, I have expertise in business accounting & balance sheet and a variety of finance theories & methods, including Risk-Neutral Distribution, Market Microstructure, and the cutting-edge Recovery Theorem.

With the experience in options based on equity indices, U.S. individual stocks, and FX currencies, I am familiar with OptionMetrics, Bloomberg, Tomson Reuters DataScope, CRSP, and DataStream datasets. I am proficient in utilizing the advantages of multi-software environment on the Big Data, such as handling tick-by-tick option big data with Python, conducting advanced statistical tests with R packages, and performing complex numerical computing with MATLAB.

Education

  • Alliance Manchester Business School Doctoral Studentships
  • Research Topic: Option implied information with high-frequency data
  • Supervisors: Dr. Yoichi Otsubo and Prof. Alexandros Kostakis
  • Expected completion of degree: September 2021
  • Chapter One: Detecting Political Event Risk in the Option Market.
  • Chapter Two: Has the Introduction of Extended Trading Hours Enhanced Market Quality?
  • Expected Chapter Three: Beliefs and Preferences in the Option Market: Evidence from Climate Change Events.
  • MSc Quantitative Finance with overall Distinction
  • Master Dissertation with Distinction: Empirical applications in NDX option market: Risk-neutral distribution and period-varying Risk Aversion analysis;
  • Keywords: Risk-Neutral Distribution, 2008 crises, NDX, Cumulative prospect theory, physical distribution;
  • Participated in the CFA Institute Research Challenge 2016.
  • BSc Applied Physics
  • Awarded by university as Merit Student in 2009;

Working Papers

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.

Conferences and Presentations

  • 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, April 2020;
  • European Financial Management Association (EFMA) conference, Cancelled due to Covid-19, June 2020.

Teaching Experience

  • Course Facilitation: Young Undergraduates Overseas Immersion Programme 2018;
  • Teaching Assistant: Investment Analysis (2019, 2020); Introduction to Corporate Finance and Financial Instruments (2019, 2020); Financial Engineering (2020);
  • Organised workshops and seminars. Provided students tutorials. Marked exam papers. Prepare online materials.

Work Experience

  • Analysed research report. Collected and cleaned relevant data from China stock market. Conducted quantitative analysis. Built and back-tested investment strategies with MATLAB, Python, and WIND;
  • Conducted performance analysis on trading strategies, such as attribution analysis, risk analysis, and sensitivity analysis;
  • Built weekly market dynamic monitoring on capital flow, sentiment, and styles. Developed different programmed trading execution strategies based on market liquidity;
  • Provided internal training courses of stock market for other employees in company.

Achievements:

  • Developed a long-only trading strategy based on multifactorial and quantitative timing model in HS300 index. It achieved total return of 7.88% under management from April 2017 to Jun 2017;
  • The asset under management was over 1000 million yuan. The number of funds under management was about 20.
  • Tested a variety of trading strategies in China stock market, such as Dual Thrust and R-breaker;
  • Developed a new trading strategy with outperformance in back-testing.
  • Analysed the impacts of Monetary and Fiscal factors and government policies on real estate industry;
  • Compared and analysed rivals in this industry. Performed financial analysis on local real estate market;
  • Helped the accountant with corporation finance, tax planning, financial operation. Reported the financial status to the executive manager. Conducted finance and investment analysis on projects, such as predicting cash flow and analysing breakeven point.

Achievements:

  • The estate investment projects under management achieved a cumulative return over 60%;
  • The engineering services projects under management achieved a net profit over 23% within one year.

SKILLS/CERTIFICATES​

Languages/IT

Nationality

References

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