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Smart Data Analytics for Banking and Finance

10% early bird discount until 21 November 2018

Registration deadline: 14 January 2019

 
  • General description

    Data are everywhere and the ubiquitous availability of huge amounts of data makes it necessary to develop smart data analytics. Out of the plethora of tools that are available for many scientific disciplines this course offers for the common data analyst an easy access to all levels of analysis without deep computer programming knowledge. SDA provides a wide variety of exercises. In addition a full set of slides is provided making it easier for the participants to reanalyze the presented material. The R and Python programming language are becoming the lingua franca of computational data analysis. They are the common smart data analysis software platforms used inside corporations and in academia. Both are OS independent free open-source programs which are popularized and improved by hundreds of volunteers all over the world.

  • Topics covered

    • LDA Latent Dirichlet Analysis
    • Sentiment extraction
    • DTM Dynamic Topic Modeling
    • Scagnostics
    • Cluster Analysis and Classification
    • CRIX a CRypto currency IndeX
    • R and Python tools for text mining
    • text mining in Quantitative Finance
    • TEDAS Tail Event Driven Asset Allocation
    • Network Centrality, Herding effects
    • TENAR Tail Event driven Network AutoRegression
    • DYTEC DYnamic Tail Event Curves
    • Machine learning in Economics
    • Deep Learning of Forecasts
    • Complexity in Banking, Scores and Networks

  • What you will learn

    This course presents tools and concepts for unstructured banking and finance data with a strong focus on applications and implementations. It presents the decision analytics in a way that is understandable for non-mathematicians and practitioners who are confronted with day to day number crunching statistical data analysis. All practical examples may be recalculated and modified: software and Quantlets are in www.quantlet.de This course endows the practitioner with ready to use practical tools for smart data analytics.

  • How the course will work

    Total course length: 12 hours.
    The course will present examples coded in R or in Python. The Quantlets are available at: www.quantlet.de

    A certificate of attendance will be provided to all participants after the course.

  • Meet the instructor

    Wolfgang Karl Härdle is a statistician, Professor at the Faculty of Economic Sciences at the Humboldt University of Berlin. He is also the founder of the company MD * Tech, which developed and distributed the statistical software XploRe. He is Director of the international DFG Research Training Group on “High Dimensional Non Stationary Time Series”, created in 2013, and has worked in leading roles in several Collaborative Research Centers of the Deutsche Forschungsgemeinschaft. He is a specialist in semiparametric and nonparametric estimation methods and has published several hundred books and essays on these topics.

  • Prerequisites

    A BA/MA degree in Economics or related fields is required to follow the course. Knowledge and understanding of basic/intermediate economics, finance and econometrics are recommended.

    Technical Prerequisites

    Participant are required to bring their own laptops.

  • Fees

    1750€ – Public Authorities (e.g. National Competent Authorities, Central Banks) and European Institutions

    1900€ – Private Sector

    1000€ – Academics (Assistant, Associate or Full Professors)

    850€ – Students (with certificate of studies)

    The course fee covers coffee and lunch breaks. Travel and hotel costs are not included.


    EARLY BIRD DISCOUNT

    Participants who register before 14 November will benefit from a 10% reduction of the course fees.

    The early bird discount cannot be combined with group deals.


    GROUP DEALS

    • In case of registration of 3 participants from the same organisation, the course fee is waived for one of them.
      To benefit from the deal, the names of the 3 participants have to be communicated to fbf@eui.eu before registering. We cannot communicate the names of other registered people from the same institution (it is upon your responsibility to get in touch with your HR division). A single debit note will be issued for the 3 participants followed by one payment.
    • Special deals apply for larger groups.

    CANCELLATION POLICY

    • In case a course is cancelled, registered participants will receive the full refund.
    • In case a course is moved to another date, registered participants may request a voucher to attend another FBF course.
    • Registered participants who cancel their participation will receive a voucher to attend another FBF course.

    For more details, please contact fbf@eui.eu
  • Practical information

    Recommended hotels

    Suggested restaurants in Florence city centre

    Wi-Fi

    On arrival, participants will be provided with temporary wi-fi access for the whole duration of the course.

    Privacy Notice

    The personal information you have provided will be processed in compliance with the EUI Privacy Statement for conferences. For general queries: fbf@eui.eu

     

    General information on local transport

    From Florence airport:

    Florence airport is located 8 km from the city centre, approximately 30 minutes by taxi or bus. Taxis can be found outside the arrivals terminal; no reservation is needed. A taxi ride from the airport costs about €20 and takes approximately 25/30 minutes.

    The airport is also connected to the main railway station in Florence by a shuttle bus (‘Vola in bus’) that leaves every 30 minutes (on the hour and on the half-hour) and takes 25 minutes. Tickets are available on board for €6.00.

    From the central railway station:

    Take bus n. 17 to via Venezia. Change to bus n. 7 direction ‘Fiesole’; get off at the stop ‘San Domenico 01’.  For bus routes and timetables consult:  http://goo.gl/Ydj8K

    Bus tickets are sold outside the railway station, at ATAF ticket kiosks and vending machines, tobacconists (tabacchi), newspaper kiosks (edicole), and most cafes (bar). They must be bought before boarding and stamped using the machine on the bus. A ticket costs €1.50 and it is valid for 90 minutes. Bus tickets can be purchased also on board (€ 2.50), but the driver is not obliged to give change.

    Private car

    From the A1 Milano-Napoli (Autostrada del Sole), take the Firenze Sud exit and follow directions to the city centre/Stadio. Follow the directions to the stadium (Stadio), then for Fiesole. San Domenico is on the main road to Fiesole.

    The EUI has several free parking areas available all over the Campus.