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THE QUANTS HUB
PROGRAMMING SCHOOL
PRESENTS
PYTHON FOR FINANCE BY YVES J. HILPISCH
QUANTS HUB PROGRAMMING SCHOOL
10 WEEK ONLINE COURSE
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THE COURSE REQUIRES NO PRIOR KNOWLEDGE OF PYTHON
BUT KNOWLEDGE OF A SIMILAR PROGRAMMING LANGUAGE AS
WELL AS OF STANDARD FINANCIAL MODELS IS RECOMMENDED.
YOU WILL LEARN
•
How to best start using Python, related tool and libraries for Quant Finance
•
How to model and store data efficiently with Python
•
How to implement compact and performant financial algorithms
•
How to visualize financial data with Python
•
How to manage and analyze financial time series data
•
How to implement performant I/O operations
•
How to increase the performance of financial Python code
CERTIFIED BY
EARLY BIRD DISCOUNT:
20% BEFORE 27TH FEBRUARY
COURSE START DATE:
13TH APRIL 2015
COURSE OVERVIEW
PYTHON FOR FINANCE WITH YVES J. HILPISCH
ABOUT THE PRESENTER
Each lecture will appear in your members area weekly,
and all webinar invites will be sent directly. You can also
contact Yves at any time with the Python forum. We
can offer additional Webinars to candidates who live in
different time zones.
Python has established itself as a real contender in the
Quant Finance world to implement efficient analytics
workflows and performant applications.
Although being an interpreted language, quantative
analysts and developers can draw on the powerful
(scientific) ecosystem that has grown around Python.
This ecosystem comprises libraries such as NumPy that
allows array management and operations both in a highly
vectorized fashion and at the speed of C code.
In addition, using the pandas library makes the
management and analysis of financial time series
both convenient and efficient. In such a context, data
visualization is also easily accomplished with Python.
The workshop also illustrates how to achieve “hardwarebound” input-output operations with Python/NumPy and
libraries such as PyTables.
In summary, against the background of financial
examples and use cases, the “Python for Finance”
workshop introduces to most important language
elements, tools and (performance) libraries that Python
as a platform technology has to offer for Quant Finance.
Dr. Yves J. Hilpisch is the
founder and managing director
of The Python Quants GmbH,
Germany.
The company provides Python-based financial and
derivatives analytics software (http://quant-platform.
com) as well as consulting services and training related
to Python and Finance. He is author of the books
“Derivatives Analytics with Python” (see http://www.
derivatives-analytics-with-python.com) as well as
“Python for Finance - Analyze Big Financial Data” (see
http://oreil.ly/1kAwNp5).
Also visit Yves’ website at http://hilpisch.com and follow
him on Twitter at http://twitter.com/dyjh.
COURSE PREREQUISITES
To take the course programming experience is expected
in some languages; C, VB, Fortran, Matlab etc. Experience
with C, C++ will also come in useful for some topics.
Object oriented programming skills are not totally
necessary but will also help. A knowledge of calculus,
statistics, signal and image processing, optimization will
all assist your learning but are not absolutely required.
COURSE FEE
With the 20% early bird discount, which runs until 27th
February, the course fee is £798.40.
Beyond this the regular course fee is £998.00.
PRMIA CERTIFICATION
The Professional Risk Managers’ International Association (PRMIA) is a non-profit
professional association, governed by a Board of Directors directly elected by its global
membership, of nearly 90,000 members worldwide. PRMIA is represented globally by
over 65 chapters in major cities around the world, led by Regional Directors appointed by
PRMIA’s Board.
For more information visit: http://www.prmia.org
CONTACT:
Tel: +44 (0)1273 201 352 / Fax: +44 (0)1273 201 360
www.quantshub.com / [email protected]
10 WEEK COURSE SCHEDULE
WEEK 1. LECTURE 1. PYTHON AND TOOLS
The first lecture shows how to efficiently set-up a Python and develeopment environment for Quant Finance. It also
introduces into IPython, and in particular into the Notebook version which allows interactive, browser-based financial
analytics with Python
WEEK 2. LECTURE 2. INTRODUCTORY FINANCIAL USE CASES
This lecture immediately dives into three canonical use cases: calculating and plotting implied volatilities, implementing
performant Monte Carlo simulations, backtesting a trend based trading strategy. These use cases illustrate the benefits of
the major Python libraries (NumPy, pandas), explained in detail in later lectures.
WEEK 3. LECTURE 3. DATA TYPES/STRUCTURES AND VISUALIZATION
This lecture is all about data modeling and storage with Python and the visualization of data. It introduces the basic
data types and structures in Python, shows how to make use of NumPy’s array capabilities and how to write vectorized
numerical code with Python/NumPy.
WEEK 4. PRACTICAL EXERCISE & WEBINAR WEEK
This will cover the first 3 weeks of the course. The practical exercise will be marked and feedback given.
WEEK 5. LECTURE 4. FINANCIAL TIME SERIES
This lecture is about the use of the pandas library for the management and analysis of financial time series. It shows
examples implementing simple and advanced analytics as well as time series visualization. It also shows how to work with
High Frequency data.
WEEK 6. LECTURE 5. INPUT-OUTPUT OPERATIONS
Financial analytics and financial application development mainly rests on the efficient and performant management and
movement of (large, big) data. This lecture illustrates how to make sure that data reading and writing (to HDDs, SSDs) takes
place at the maximum speed that any given hardware component allows. Examples also illustrate how to make use of
compression techniques in such a context.
WEEK 7. LECTURE 6. PERFORMANCE LIBRARIES
The Python ecosystem has to offer a number of powerful performance libraries. For example, using the Numba dynamic
compling library allows to compile Python byte code at call-time to machine code by using the LLVM infrastructure. The
resulting compiled functions are directly callable from Python. Similarly, using the Multiprocessing module of Python
makes parallelization of Python function executions a simple and efficient task.
WEEK 8. PRACTICAL EXERCISE & WEBINAR WEEK
This will cover weeks 5-7 of the course. The practical exercise will be marked and feedback given.
WEEK 9. REVISION WEEK.
WEEK 10. FINAL PRACTICAL PROJECT WEEK.
THE FINAL PROJECT WILL BE MARKED WITH FEEDBACK AND A PASS OR FAIL WILL GIVEN. ONE RETAKE IS ALLOWED IF
YOU FAIL.
THIS COURSE IS AVAILABLE GLOBALLY AND CAN ONLY BE ACCESSED ONLINE.
BOOK YOUR PLACE NOW: http://www.wbstraining.com/php/events/showevent.php?id=244#booking
PYTHON FOR FINANCE
10 WEEK ONLINE COURSE
13TH APRIL 2015
CONFERENCE FEE STRUCTURE
Early Bird Discount:
Regular Event Fee
20% Before 27th February
 Online Workshop:
£798.40 inc. UK VAT
£998.00 inc. UK VAT
 Special Discount Code:
50% Academic Discount / FULL-TIME Students Only
DELEGATE DETAILS
TO REGISTER, PLEASE FAX THE COMPLETED BOOKING FORM TO:
COMPANY:
+44 (0)1273 201 360
NAME:
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Quants Hub offer sponsorship opportunities for all workshop, e-mail
headers and the website. Contact sponsorship via telephone on:
+44 (0)1273 201 352
NAME:
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DISCLAIMER:
Quants Hub command the right to cancel or alter any part of this
programme.
CANCELLATION:
By completing this form, the client hereby enters into a agreement
stating that if a cancellation is made by fax or writing within two
weeks of the event date no refund shall be given. However in certain
circumstances a credit note may be issued for future events.
Prior to the two week deadline, cancellations are subject to a fee of
25% of the overall course cost.
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REGISTRATION:
Tel: +44 (0)1273 201 352 / Fax: +44 (0)1273 201 360
www.quantshub.com / [email protected]