Date
Time

6pm:  tea/coffee

6.30pm:  meeting

Venue
Chartered Accountants House, Pearse Street, Dublin 2

Python-implemented Techniques for Reading the Tea Leaves of Past Investment Performance & Risk Management of Funds

The paper, the Python code, and the presentation explore a wide range of graphical and numerical techniques for analysing:

  1. The past performance of an investment fund in an attempt to validate the claims of investment management firms and to assess the repeatability of the trading strategy’s ability to make money;
  2. The quality of the fund’s risk management; and
  3. The efficacy of adding an investment fund to an existing portfolio.

The production of the range of graphs and the statistics suggested above from a data file containing the daily returns of an investment fund is an extremely labour intensive task particularly where: (i) several funds with different trading history length are involved; and (ii) spreadsheets are used to carry out the analysis.  As part of the paper, the authors will release the code for a Python programme which can read daily data from a file such as a spreadsheet and produce the graphs and statistics in a matter of minutes.

According to The Economist, “… in the past 12 months Google users in America have searched for Python more often than for Kim Kardashian, ... The rate of queries has trebled since 2010, while inquiries after other programming languages have been flat or declining …”  

Python has a simple syntax and coding in Python is easy to learn.  There are many Python courses offered for free on-line.  Python also has a wide range of third-party packages some of which have been used in the programming of the techniques in the paper.  The Economist also reports that Python is used by the Central Intelligence Agency for hacking, Pixar for producing films, Google for crawling web pages, and Spotify for recommending songs.

Cost (members)
0
Cost (non-members)
€50
Event Type
CPD Event
Speakers/Presenters
John Caslin FSAI, Dave Kavanagh
File attachments
Date Attachment Size
12/10/2018 Python Code Files 389.41 KB Download
12/10/2018 Python Code Paper - John Caslin & Dave Kavanagh 3.23 MB Download
12/10/2018 181010 Python-Implemented Techniques - Presentation 1.72 MB Download