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Python for Quantitative Analysis and Algorithmic Trading

Algorithmic trading refers to the computerised, automated trading of financial instruments based on some algorithm or rule with little or no human intervention during trading hours. Almost any kind of financial instrument — be it stocks, currencies, commodities, credit products or volatility — can be traded in such a fashion. Python has becoming the programming language for Algorithmic trading. This course teach you the basics of algorithmic trading and quantitative Analysis using Python. The topics include:

  • Option Trading with Python
  • Exotics
  • Time Series Analysis

After your registered for the course, you can apply SSG grants below

Click here to apply SkillsFuture Credit for Individual

Click here to apply WSG Absentee Payroll for Company
Course Code: CRS-N-0046836

Course Booking

$298.00 (GST-exclusive)

Course Date

Course Time

* Required Fields

Course Cancellation/Reschedule Policy

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
Note the venue of the training is subject to changes due to class size and availability of the classroom.
Note the minimal class size to start a class is 3 Pax.


Training Grant and Subsidy

All Singaporeans aged 25 and above can use their $500 SkillsFuture Credit from the government to pay for a wide range of approved skills-related courses. Visit the SkillsFuture Credit website www.skillsfuture.sg/credit to choose from the courses available on the SkillsFuture Credit course directory

Course Details

Module 1. Vanilla Options and Strategies

  • What is Vanilla Option?
  • Call and Put Options
  • European vs American Options
  • Black-Scholes Model
  • Python Implementation of BS Model
  • Greek Options
  • Option Strategies
  • Binomial Options Pricing Model

Module 2. Exotic Options

  • What is Exotic Options?
  • Bermudan Option
  • Chooser Option
  • Shout Call Option
  • Binary Option
  • Barrier Option

Module 3. Monte Carlo Simulation

  • What is Monte Carlo Simulation?
  • Random Number Generation
  • Stock Price Simulation
  • MC Simulation for Black-Scholes Model

Module 4. Time Series Analysis

  • Download Finance Data from Web
  • Correlation between time series
  • Autocorrelation
  • ARIMA

Module 5. Volatility and Implied Volatility

  • Implied Volatility

Module 6. Volue at Risk (Optional)

Who Should Attend

  • Data Scientists
  • Financial Analyst
  • Algorithmic Traders

Prerequisite

Prerequisite

This is a intermediate level course. The following prerequisite is assumed

Software Requirement

Pls download and install the following software prior to the class

Trainers

Python Quantitative Analysis and Algorithmic Trading TrainerGuan Xiao Kang. analytical, efficient and quick thinking financial professional with strong quantitative skills and capability to comprehend, translate market fundamentals and fast-changing data. With over 5 years working experience with J.P. Morgan Chase in FX Option Electronic Market Making, He is strong in option pricing / risk managing in the automated / quantitative way, and also specialize in Financial data analysis using Python. With a Financial Engineering background, He is familiar with mathematical theories and methods, such as Black-Scholes, Monte Carlo, Econometric and statistical techniques. Furthermore, He is experienced in applying / implementing these methods using current technologies (mainly Python, Pandas, Numpy etc.) to solve practical problems in the Financial industry.

Python Quantitative Analysis and Algorithmic Trading TrainerJohnson Ang has a Masters in IT Analytics from SMU and is certified and a member of GARP, CQF andFSM. He has more than 8 years of working experience, of which 4 years of experience in the Banking Wide Operations and has been particularly involved in mega IT Analytic banking projects within the Risk Management and Financial Instrument sphere.

He can offer varied solid perspectives and has experience working with folks from all sorts of background, such as Developers, Traders/Dealers, CxOs, Programmers, Project Managers, Auditors, Head/Country Directors, Regulators, RMs, which is particularly during his stint in the Front, Middle and Back Office, as well as industry such as Real Estate, FMCG, Construction and Education Sector.

Not only he is familiar with typical banking software, but also has also been acquainted with popular tools such as SAS, JMP, Oracle, VBA, Access, Python, R, C, Java and many more. He has also developed a strong passion for Mathematics, Trading and Computing at a young age and has been a self-professed Algo-Trader having a Sharpe ratio of >3 and a passionate Math Tutor having taught over hundreds of students from Primary to University level.

Python Finance TrainerDr. Cao Yongxin (Steve) has more than five years of solid industrial and research experiences in data analytics. He held PdD on operations research in National University of Singapore. After his Phd study, he worked as data analyst and scientist in manufacturing and commodity trading companies. He is specialized in analyzing, visualizing and mining complex time series data using Python tools sucha as Pandas, Numpy, Matplotlib, SK-Learn, Tensorflow etc. He did research on predictive analytics on various systems e.g., Forex and commodity trading, system performance prediction, machine maintenance, etc. Besides data analytics using Python, he also extended his expertise in Microsoft Excel VBA, Hadoop big data platforms such as AWS and Microsoft Azure. In addition, he is strong in mathematical modelling and has cross-disciplinary domain knowledge in operations research, currency and commodity trading and industrial automation.

Customer Reviews (1)

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. (Posted on 11/13/2018)

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