[Forum SIS] FDS resumes its activities! - 5th seminar of D2 Seminar Series - 15th October 2-3.30

[datascience a unifi.it]

Dear all,

Florence Center for Data Science resumes its activities after the summer 
break!

We are happy to present the fifth Seminar of the “D2 Seminar Series” 
launched by the FDS. The Seminar will be held online Friday 15th of 
October 2021, from 2-3.30 pm.
The seminar will be held by Leonardo Bargigli from the Department of 
Economics and Management of the University of Florence and Chiara Marzi 
from the Institute of Applied Physics ‘Nello Carrara’ (IFAC) - National 
Research Council (CNR).

Register in advance for this webinar:
https://us02web.zoom.us/webinar/register/WN_3tq7BbbwTSeA956KFQIK0w

After registering, you will receive a confirmation email containing 
information about joining the webinar.

We hope to see you there! You are invited to invite also your students, 
PhDs and colleagues who may be interested in the Seminar (you find a 
Flyer with all the info attached).

Kind Regards,
Florence Center for Data Science

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Speaker: Leonardo Bargigli – Department of Economics and Management, 
University of Florence
Title:  Endogenous and Exogenous Volatility in the Foreign Exchange 
Market (with G. Cifarelli)

Abstract: We study two sources of heteroscedasticity in high-frequency 
financial data. The first, endogenous, source is the behaviour of 
bounded rational market participants. The second, exogenous, source is 
the flow of market-relevant information. We estimate the impact of the 
two sources jointly by means of a Markov switching (MS) SVAR model. 
Following the original intuition of Rigobon (2003), we achieve 
identification for all coefficients by assuming that the structural 
errors of the MS-SVAR model follow a GARCH-DCC process. Using 
transaction data of the EUR/USD interdealer market in 2016, we firstly 
detect three regimes of endogenous volatility. Then we show that both 
kinds of volatility matter for the transmission of shocks, and that the 
exogenous information is channelled to the market mostly through price 
variations. This suggests that, on the FX market, liquidity providers 
are better informed than liquidity takers, who act mostly as feedback 
traders. The latter are able to profit from trade because, unlike noise 
traders, they respond immediately to the informative price shocks.

Speaker: Chiara Marzi - Institute of Applied Physics ‘Nello Carrara’ 
(IFAC) - National Research Council (CNR)

Title: Artificial Intelligence in Neuroimaging

Abstract: Life sciences data coupled with Artificial Intelligence (AI) 
techniques can help researchers accurately pinpoint novel biomarkers. AI 
can propose new indices as potential biomarkers while simultaneously 
aiding in searching for hidden patterns among "well-established" 
indices. In this webinar, we will take a brief journey through some 
applications of Machine Learning in neuroimaging. In the first part of 
the webinar, we will talk about the not so easy "marriage" between AI 
and clinical data, focusing on Big Data from Radiology Imaging and 
related issues. In the second part, we will see how we can transfer 
mathematical, physical, and statistical ideas to the Neuroimaging domain 
and how AI can help this transfer. An example is the study of the 
structural complexity of the brain starting from MRI images, using 
fractal analysis. The Fractal Dimension (FD) can be considered a measure 
of morphological changes due to healthy ageing and/or the onset of 
neurological diseases. The use of ML techniques can promote the 
candidature of FD as a biomarker for many neurological diseases.
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