Agenda

17 Dec 2021 08:50

Machine Learning for Finance

Online workshop

The attendance is free. The workshop will be streamed via the ZOOM platform. For receiving the meeting’s address, ID and passcode, it is necessary to communicate the email address of the attendee to the organizer Marco Corazza corazza@unive.it. All the attendees are kindly asked to keep the microphone in mute mode all presentation long.

Program:

MORNING

08:50-09:00 - Opening
09:00-09:30 - He X., Cong L. W., Feng G., He J. - Asset pricing with Panel Trees under global split criteria
09:30-10:00 - Barbopoulos L. G., Dai R., Putniņš T., Saunders J. A. - Market Efficiency in the age of Machine Learning
10:00-10:30 - Caliciotti A., Corazza M., Fasano G. - Regression models and Machine Learning approaches for Bitcoin price forecast
10:30-11:00 - Kumar P. - Deep Hawkes process for high-frequency market making
11:00-11:30 - Lam D.K., Ravagnani A., Tsaknaki I.-Y., Bormetti G., Lillo F. - Short-term prediction of CO2 emission futures price  with limit order book data
11.30-11.40 - Break
11:40-12.10 - Al-Ameer A., Alshehri K. - Conditional Value-at-Risk for quantitative trading: A Direct Reinforcement Learning approach
12:10-12:40 - Daluiso R., Nastasi E., Pallavicini A., Polo S. - Reinforcement Learning for options on target  volatility funds
12:40-13:10 - Dell’Era M. - Local volatility and Hopfield Neural Network
13.10-13.40 - Garcin M., Stéphan S. - Credit scoring using neural networks and SURE  posterior probability calibration
13:40-14:00 - Break

AFTERNOON

14:00-14:30 - Goudenège L., Molent A., Zanette A. - Moving average options: Machine Learning and  Gauss-Hermite quadrature for a double non Markovian problem
14:30-15:00 - Jaydip S., Dutta A., MAehtab S. - Portfolio optimization using Deep Learning models - A comparative study of risk-based portfolio design  approaches
15:00-15:30 - Lillo F., Livieri G., Marmi S., Solomko A., Vaienti S. - Analysis of bank leverage via dynamical systems and  deep neural networks
15:30-16:00 - Salko A. - New insights on Loss Given Default for Shipping  Finance: Parametric and non-parametric estimations
16:00-16:30 - Scholz M. - Forecast combinations for benchmarks of long-term  stock returns using Machine Learning methods
16:30-16:40 - Break
16:40-17:10 - Ameridad B., Cattaneo M., Luciano E., Kenett R. - AI and Adversarial AI in insurance: Background,  examples and future implications
17:10-17:40 - Gnoatto A., Picarelli A., Reisinger C. - Deep XVA Solver - A Neural Network based  counterparty Credit Risk management framework
17:40-18:10 - Mansouri S., Momtaz P.P. - Financing sustainable entrepreneurship: ESG  measurement, valuation, and performance in token  offerings
18:10-18:40 - Modina M., Zedda S. - A quantitative identification and description of the  default syndromes affecting the Italian SMEs
18:40-19:10 - Carrillo Menéndez S., Hassani B. - Expected Shortfall reliability – Added value of  traditional statistics and advanced Artificial  Intelligence for market risk measurement purposes
19:10-19:15 - Closings

Language

The event will be held in English

Organized by

Department of Economics; VERA - Venice centre in Economic and Risk Analytics for Public Policies (CVera); CEQ - Centro di Economia Quantitativo; EGONON - Risk Management & Advisor; Redexe - Risk Management and Finance

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