DR YVES J HILPISCH

• Python for Quant Finance, Meetup, 21. March 2019, London (Slides News from The Python Quants)
• Quant Insights Conference, 16. November 2018, London (Slides The AI Machine — Solving the Last Mile Problem in Algorithmic Trading)
• ODSC Conference, 20. September 2018, London
  (Slides Algorithmic Trading with Machine & Deep Learning,
  Gist Algorithmic Trading with Machine & Deep Learning)
• FXCM Algo Trading Summit, 15. June 2018, London
  (Slides Algorithmic Trading for the Masses)
• Thomson Reuters Developer Day, 14. June 2018, London
  (Slides TR Eikon Data API — Quant Use Cases)
• Open Data Science Conference, 14. April 2018, Kiev
  (Slides Building The AI Machine for Algorithmic Trading
• ML & AI in Quant Finance Conference, 16. March 2018, London
  (Slides AI-First Finance & Algorithmic Trading, Notebook FXCM RESTful API)
• Algo Trading & AI, 12. March 2018, Paris
  (Slides Algorithmic Trading & Artificial Intelligence, Notebook FXCM RESTful API)
• ML & AI in Quant Finance Conference, 02. March 2018, New York
  (Slides AI-First Finance & Algorithmic Trading, Notebook TR Eikon Data API & ML)
• Algo Trading & Data-Driven Finance, 19. February 2018, Berlin
  (Slides Algorithmic Trading & Artificial Intelligence, Notebook FXCM RESTful API)
• Algo Trading & AI-First Finance, 15. February 2018, Frankfurt
  (Slides Algorithmic Trading & Artificial Intelligence, Notebook FXCM RESTful API)
• Python for Quant Finance, 12. February 2018, London
  (Slides Algorithmic Trading & Artificial Intelligence, Notebook FXCM RESTful API)
• PyCon DE, Karlsruhe
  (Slides Why Python Has Taken Over Finance)
• Machine Learning & AI in Quant Finance, London (Slides Financial Singularity)
• Data Science Meetup, Duesseldorf (Slides Financial Singularity)
• PyCon DE, Karlsruhe (Slides Why Python Has Taken Over Finance)
• AICamp, Frankfurt (Slides Financial Singularity)
• ODSC Europe 2017, London (Workshop Algorithmic Trading, Gist)
• PyConf, Hyderabad (Keynote What AI Might Do To Finance,
  Workshop Time Series Analysis, Gist)
• Python for Quant Finance Meetup, London
  (Notebooks Neural Nets with Python, Market Prediction with Neural Nets)
• For Python Quants Bootcamp, May 2017, New York (Gist)
• Plotcon, 04. May 2017, Oakland (Slides | Gist)
• Bitcoin and Blockchain — Opening the Black Box with Python (Slides)
  Quant Insights London, 14. October 2016
• Hashing, Encryption, Blockchain & Bitcoin Mining with Python (YouTube)
• Machine Learning with Python for Algorithmic Trading (Slides, Code)
  ODSC Conference, London, 08. October 2016
• Python for Risk Management Tutorial (Github Repo)
  ARPM Python Conference, New York, 13. August 2016
• Chat with Traders Podcast about Python (Audio)
• How Open Source, Open Data and the Cloud are Reshaping
  Finance Education and the Financial Industry (Slides)
  PyCon Singapore, Keynote, 24. June 2016
• Technical News from the Python Financial Analytics Front (Slides)
  For Python Quants in New York on 06. May 2016
• Bitcoin Mining with Python (Slides)
  FPQ in New York on 06. May 2016 & SaarCamp on 04. June 2016
• Python for Quant Finance Meetup
  15.02.2016 in London & 02.05.2016 in New York.
  Combining Multivariate Time Series & Derivatives Analytics NEW (Slides).
• Data Science Meetup (10.02.2016) in Luxembourg.
  Combining Multivariate Time Series & Derivatives Analytics (Slides).
• QuantInsti Webinar (10.02.2016).
  Automated Trading with Python (Video).
• Python Podcast (30.12.2015)
  Yves Hilpisch about Quant Finance (Podcast).
• For Python Quants Conference (27.11.2015) in London.
  Quant Tech — Where Do We Stand? (Slides).
  Quant Platform — Bundling the Best of Open Source for Quant Tech (Slides).
• Data Natives Conference (19. to 20.11.2015) in Berlin.
  Python for Financial Data Science Workshop (Github Repo).
• Quant Insights Conference (30.10.2015) in London.
  Computational Finance — Why Python is Taking Over (Slides).
• Global Big Data Conference (01. to 03.09.2015) in Santa Clara, CA.
  Big Data and Data Science in the Browser (Slides & Demo Video).
• PyData (19. to 21.06.2015) in London. Financial Time Series Analysis & Visualization tutorial (Github repo | Video).
• Big Data in Finance (11. to 13.06.2015) in London. Open Source Revolution in Quant Finance (Slides).
• Open Source in Quant Finance Day (05.06.2015) in Frankfurt. Open Source in Quant Finance (Slides). Open Source Deployment via the Browser (Slides).
• Saarcamp (09. to 10.05.2015) in Saarbruecken.
  See the slides of my talk Data Analytics in the Browser.
• For Python Quants Conference & Bootcamps (28.04.–01.05.2015) in New York.
  My overview talk about Open Source in Quant Finance.
  My talk about Open Source Deployment via the Browser.
• Paris Financial Engineering Meetup (22.04.2015) in Paris.
  See the slides of my talk Python for Quant Finance.
• Open Source in Quant Finance (02.04.2015) in London.
  See the slides of my talk datapark — data science in the browser.
• 6th Python for Quant Finance Meetup in London. Slides of the talk New Python Data Analytics.
• Webmontag Saar (02.03.2015) in Saarbruecken. Slides of the talk Python in the Browser.

Thanks to all attendees and sponsors who made the first For Python Quants conference in London such a great event. Also a big thank you to CQF Institute and Fitch Learning who helped organize it and who provided an excellent venue. Slides of my talk Browser-based, collaborative Financial Derivatives Analytics.

Links to slides and other relevant links for my PyData talk:

• Slides of the talk Python for Quant Finance.
• DX Analytics Github repo.
• DX Analytics Documentation.
• Python Quant Platform Trials.
• Python Quant Platform Introduction & Overview.

My talk and tutorial at the For Python Quants conference in New York City on 14. March 2014 (Pi-Day):

• Derivatives Analytics with Python
• The slides of the talk.
• Watch the Video.
• Interactive Financial Analytics with Python & the VSTOXX Volatility Index
• The slides of the tutorial.
• The IPython Notebook of the tutorial.
• Watch the Video.

PyData London on 21. February 2014: “Interactive Financial Analytics with Python & IPython – With Examples based on the VSTOXX Volatility Index”

• The video of the tutorial.
• The slides of the tutorial.
• The IPython Notebook for the tutorial.

Solutions to exercises upon request.

Talks and tutorials during the fourth quarter of 2014:

• Pycon Ireland, Dublin, October 2014, Keynote Slides Python and the Financial Industry.
• Python Big Data Analytics Meetup, Berlin, October 2014 Slides Python Big Data Platform

Talks and tutorials during the third quarter of 2014:

• 10th Fixed Income Conference, Barcelona, Sep 2014 (additional slides)
• Thomson Reuters Quant Networx Forum, London, Sep 2014
  Slides Python and the Financial Community
• Python for Quant Finance meetup, London, Sep 2014
  Slides Python Quant Platform
• EuroPython 2014, Berlin, July 2014
  Slides Python Quant Platform
  Watch the Lightning Talk (from 46th min)
• PyData 2014, Berlin, July 2014
  Slides Interactive Analytics of (Large) Financial Data Sets
• EuroPython 2014, Berlin, July 2014
  Slides Performance Python for Numerical Algorithms

Talks and tutorials during the second quarter of 2014:

• O’Reilly Media Webcast, June 2014
  Slides Derivatives Analytics with Python
• Big Data in Quant Finance, London, June 2014
  Talk Analyze Big Financial Data with Python
• Python for Quant Finance meetup, London, June 2014
• Python for Quant Finance training, London, June 2014
• Python for Big Data Analytics meetup, Berlin, May 2014
  Talk Out-of-Memory Analytics with Python
• Python for Quant Finance meetup, London, May 2014
  Talk Python Quant Platform

In the first quarter of 2014, I have given the following talks/tutorials:

• 5. Quantified Self Meetup, Cologne, March 2014
  Datenanalyse mit Python
• Telefonica, Madrid, February 2014
  Python – A Real Contender in the Big Data Arena?!
• Universidad Politécnica de Madrid, Madrid, February 2014
  Python – A Solution to ‘Big’ Data Problems?
• CodeJam @ Supercomputing Centre, Juelich, January 2014
  Efficient In-Memory Data Analytics with Python & pandas

In 2013, I have participated in the following conferences:

• PyData, New York City, November 2013
  Talk Performance Python (Slides)
  Video Performance Python (Full Video)
  IPython NB Performance Python (Slides IPYNB)
  Material Performance Python (Exercises)
  IPython NB Performance Python (Exercises IPYNB)
• Budapest BI Forum, Budapest, November 2013
  Talk Python for Next Generation Data Analytics (Slides)
  IPython NB Python for Next Gen Data Analytics (IPYNB)

Pycon DE in 2013 took place in Cologne, Germany. I have given three talks there:

• Interactive Data Analytics
  Talk Interactive Data Analytics & Visualization Watch the Video (German)
• Scientific Publishing with Python Talk Scientific Publishing with Python (German)
  Watch the Video (German)
• Data Analytics Stack Talk Continuum Data Analytics Stack
  Watch the Video (German)