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    QF206 - Ting Hian Ann, Christopher

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    Hohoho134
    This document provides information on the Quantitative Trading Strategies course offered at SMU, including the course description, learning objectives, assessment methods, instructional methods, recommended readings, and weekly lesson plans. The course aims to teach students practical quantitative trading strategies through hands-on lessons using professional trading software. Key topics include different types of trading, analyzing order flow data, and using algorithms to implement trading strategies on futures contracts.

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    QF206 - Ting Hian Ann, Christopher

    Uploaded by

    Hohoho134
    158 views5 pages
    This document provides information on the Quantitative Trading Strategies course offered at SMU, including the course description, learning objectives, assessment methods, instructional methods, recommended readings, and weekly lesson plans. The course aims to teach students practical quantitative trading strategies through hands-on lessons using professional trading software. Key topics include different types of trading, analyzing order flow data, and using algorithms to implement trading strategies on futures contracts.

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    This document provides information on the Quantitative Trading Strategies course offered at SMU, including the course description, learning objectives, assessment methods, instructional methods, recommended readings, and weekly lesson plans. The course aims to teach students practical quantitative trading strategies through hands-on lessons using professional trading software. Key topics include different types of trading, analyzing order flow data, and using algorithms to implement trading strategies on futures contracts.

    Copyright:

    © All Rights Reserved
    158 views5 pages

    QF206 - Ting Hian Ann, Christopher

    Uploaded by

    Hohoho134
    This document provides information on the Quantitative Trading Strategies course offered at SMU, including the course description, learning objectives, assessment methods, instructional methods, recommended readings, and weekly lesson plans. The course aims to teach students practical quantitative trading strategies through hands-on lessons using professional trading software. Key topics include different types of trading, analyzing order flow data, and using algorithms to implement trading strategies on futures contracts.

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    of 5

    SMU Classification: Restricted

    The Lee Kong Chian School of Business


    Academic Year 2018/19
    Term 1

    QF206 QUANTITATIVE TRADING STRATEGIES


    Instructor Name : Christopher Ting
    Title : Associate Professor of Quantitative Finance (Practice)
    Tel : 6828 0364
    Email : christophert@smu.edu.sg
    Office : LKCSB #5036

    COURSE DESCRIPTION
    Like any financial investment, trading in stocks, currencies, commodities, and fixed income instruments may lead
    to substantial profits but it can also lead to substantial losses. It goes without saying that a suite of trading
    strategies is needed to keep winning the game of probability while limiting the downside risk. In this course,
    practicable trading strategies coupled with money management will be covered in detail. Algorithmic trading,
    high-frequency trading, and the likes will be demystified along with quantitative trading. Using the MSCI Singapore
    Free Index futures as a case study, students will get to see concretely what a limit-order book and its dynamics
    look like throughout the trading session. This practical course also provides students with a rare opportunity to
    learn and practise trading on a software platform used by professional traders.

    LEARNING OBJECTIVES
    By the end of this course, students will be able to:
     Distinguish and differentiate between trading and investment
     Identify and elaborate the IT infrastructure and processes needed for a trade to occur
     Compare different types of trading: quantitative, low-latency, high-frequency, algorithmic, and program
    trading
     Compute the stock index value from the component stocks and the fair value of the index futures
     Apply the knowledge acquired in computing the fair values to construct spread-trading strategies
     Analyze buying and selling pressures in the limit-order book using tick-by-tick data
     Use different orders to trade futures
     Evaluate different quantitative trading strategy by applying the relevant performance measures and
    statistics in a scientific manner
     Explain different statistical arbitrage strategies used by quantitative hedge funds
     Develop the mental strength of a professional trader in managing risks and profits
     Define and explain Kelly’s criterion
     Explain why and how trading on one’s own account (proprietary trading) is a business venture

    PRE-REQUISITE/ CO-REQUISITE/ MUTUALLY EXCLUSIVE COURSE(S)


    Please refer to the Course Catalogue on OASIS for the most updated list of pre-requisites / co-requisites for
    this particular course. Do note that if this course has a co-requisite, it means that the course has to be taken
    together with another course. Dropping one course during BOSS bidding would result in both courses being
    dropped at the same time.

    ASSESSMENT METHODS
    Mini Project: 20%
    Final Exam: 50%
    Assignments: 20%
    Class Participation: 10%
    Total: 100%

    1
    SMU Classification: Restricted

    ACADEMIC INTEGRITY
    All acts of academic dishonesty (including, but not limited to, plagiarism, cheating, fabrication, facilitation of acts
    of academic dishonesty by others, unauthorized possession of exam questions, or tampering with the academic
    work of other students) are serious offences.

    All work (whether oral or written) submitted for purposes of assessment must be the student’s own
    work. Penalties for violation of the policy range from zero marks for the component assessment to expulsion,
    depending on the nature of the offence.

    When in doubt, students should consult the course instructor. Details on the SMU Code of Academic
    Integrity may be accessed at http://www.smuscd.org/resources.html.

    ACCESSIBILITY
    SMU strives to make learning experiences accessible for all. If you anticipate or experience physical or academic
    barriers due to disability, please let me know immediately. You are also welcome to contact the university's
    disability services team if you have questions or concerns about academic provisions: included@smu.edu.sg.

    Please be aware that the accessible tables in our seminar room should remain available for students who
    require them.

    EMERGENCY PREPAREDNESS FOR TEACHING AND LEARNING (EPTL)


    Where there is an emergency that makes it infeasible to have classes on campus, classes will be conducted
    online via WebEx, with no disruption to the schedule. To familiarize students with the WebEx platform, part
    of this course may be conducted online. The instructor will inform students of which classes, if any, will be
    conducted as part of this EPTL initiative.

    INSTRUCTIONAL METHODS AND EXPECTATIONS


    Instructional Methods
    This course is very hands-on. Instructors will explain the techniques and methods, demonstrate them on the
    professional trading software and students will emulate on the computer terminals assigned to them individually.

    Class Participation
    This course is highly practical in nature, so interactive participation is a central part of the learning process for
    you and your classmates.

    Paper Trading
    You will take on the role of a proprietary trader and trade a number of CME, Eurex and SGX futures contracts.

    Final Examination
    The final exam is closed-book. The format of the test and exam papers is mainly MCQ and short questions.

    CONSULTATIONS AND TEACHING ASSISTANTS


     Before coming for consultation, an email appointment is needed.
     Prepare a list of questions before coming for consultation.

    CLASS TIMINGS
    There will be one 3-hour seminar each week according to the class schedule, which is tabulated below. Due to
    unforeseen circumstances, some adjustments to the class timings may arise.

    RECOMMENDED TEXT AND READINGS


     Quantitative Trading: How to Build Your Own Algorithmic Trading Business (2009) Ernest P. Chan,
    Wiley & Sons

    2
    SMU Classification: Restricted

     Statistical Arbitrage: Algorithmic Trading Insights and Techniques (2007) Andrew Pole, Wiley & Sons
     Course materials by instructor

    WEEKLY LESSON PLANS

    Week Topics (subject to change) Remarks


    1 Introduction to Quantitative Trading
    Overall view of products
    A. An overview of tradable financial instruments for trading and investment
    a. Four major asset classes: equities, currencies,
    commodities, and fixed income You will have installed
    Python 2.7x
    b. Cash markets versus derivative markets
    Note that some libraries
    c. Exchange versus OTC are not compatible to
    d. Financial instruments with maturities versus those Python 3.x
    without maturities
    e. Linear payoff versus nonlinear payoff
    B. Trading versus investment
    a. Holding period or investment horizon
    b. Portfolio rebalancing versus market timing
    c. Hedging versus scalping
    d. Market making
    C. Intro to Python programming

    2 Futures
    A. Underlying asset, futures market price, expiration date, term Practical lesson on
    structure Trading Technologies
    B. Contract size/unit, (TT), a trading software
    C. Daily settlement price and mark-to-market used by professional
    D. Theoretical fair value traders in the Simulated
    E. Spot futures parity theorem Trading Room (QF Lab)

    3 Electronic Trading
    You will use the TT to
    A. MSCI Singapore free index: A case study submit market orders,
    a. Free float limit orders, marketable
    b. Divisor limit orders etc.
    B. Electronic markets and tradable futures
    C. Electronic orders You will use the live-feed
    D. Algorithmic orders data from SGX, CME, and
    E. Batch auction Eurex to compute bid-ask
    spread and market depth.

    4 Tick Data, Order Flow, and Tick-by-Tick Data Analysis


    You will analyze tick data
    A. TAQ data and see how order flows
    B. Bloomberg’s intraday tick data are computed in analysis
    C. State-of-the-art Level II data from SGX and in real time.
    D. Free time and sales data from SGX
    E. Order flow
    F. Price impact
    G. High-frequency and dark pools

    3
    SMU Classification: Restricted

    5 Technical Indicators
    You will use Python codes
    A. Overview of technical analysis to conduct technical
    B. Indicators indicators.
    C. Trends
    D. Sentiments
    A. When does the trend reverse?

    6 Back-Testing a Quantitative Trading Strategy


    Back-testing is very
    A. Backtesting framework important to quantitative
    B. Finding and using historical databases trading. You will use
    a. Adjustments for stock splits and dividends Python codes to perform
    back-testing of simple
    b. Survivorship bias
    trading strategies.
    c. High and low of the day
    C. Performance measurement
    D. Common backtesting pitfalls to avoid
    d. Look-ahead bias
    e. Data-snooping bias
    B. Transaction costs

    7 Hands-on Trading with TT


    You will play the role of a
    proprietary trader.
    8 Recess

    9 Advanced Technical Indicators


    You will run Python codes
    A. Triangular double exponential, adaptive, and weighted to generate advanced
    moving average technical indicators for
    B. Average directional movement index, parabolic stop and quantitative trading.
    reverse
    C. Aroon oscillator, and commodity channel index
    D. Ichimoku system

    10 Statistical Arbitrage

    A. Overview of hedge funds


    B. Trading with margin You will run Python codes
    C. Short selling to perform Dickey-Fuller
    D. Introduction to pairs trading test for pair trading.
    E. Stationary versus Non-stationary time series models
    F. Essence of pair trading
    G. Dickey-Fuller test

    11 Spread Trading Strategy


    You will use TT and
    A. Calendar spread trading Bloomberg to pull in live-
    feed data to analyze
    B. Inter-market spread trading
    spread trading in real-
    C. Quanto spread trading time.
    D. Mishedges and risk management

    4
    SMU Classification: Restricted

    12 Proprietary trading
    You will learn how a prop
    A. Proprietary trading as a business trading firm or small
    B. Margin hedge fund is typically
    C. Money & risk management organized.
    D. Kelly’s criterion

    13 Project Presentations

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