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LAMBDA's Roundtable: "AI: Benefits and Challenges for Business."

I am pleased to announce that Liverpool Advanced Methods for Big Data Analytics (LAMBDA) is organizing a Roundtable scheduled for June 7th. The theme for this second edition is "AI: Benefits and Challenges for Business." We have confirmed the following speakers:

Pauline Norstrom, Founder and CEO, Anekanta® Consulting and Anekanta® AI

Radhika Jakkula, Big Data & Analytics Prototyping Architect at Amazon

Michael O'Keefe, Data Scientist at Raytheon

Olivia Bridgewater-Smith, Data Scientist at Heimdal Satellite Technologies

Edgar Everardo Garcia Aguilar, Data Scientist at AXA

Please register online to guarantee a place at the event. You can do it using the following link:

'AI: Benefits and Challenges for Business' Roundtable 'AI: Benefits and Challenges for Business' Roundtable- Management School - University of Liverpool

Virtual Workshop for Junior Researchers in Time Series

We now have the program for the Virtual Workshop for Junior Researchers in Time Series on the 18 of April ready to circulate. It can be found here:

https://sites.google.com/view/vtss/workshop

Zoom link: Please register here. The same registration gives access to the workshop and all seminars.

You can follow the workshop and seminars updates on Twitter.

2024 LAMBDA’s Machine Learning and High-Dimensional Data Analysis Workshop, 22nd of April, Liverpool, UK

I am pleased to inform you that the LAMBDA centre is organizing a quantitative workshop on Machine Learning and High-Dimensional Data Analysis scheduled for the 22nd of April. We have a great list of speakers:

Professor Roberto Renò, ESSEC Business School

Professor Anders Kock, University of Oxford

Professor Valentina Corradi, University of Surrey

Professor Jeroen Rombouts, ESSEC Business School

The program can be found here: here

For the registration, please click here

Virtual Time Series Seminar, 2024 Winter-Spring Edition started! Please check here:

Virtual Time Series Seminar (google.com)

LAMBDA Workshop on Data Science, AI, and Social Sciences

November 30, 2023

Liverpool Advanced Methods for Big Data Analytics (LAMBDA) is organizing a workshop on Data Science, AI, and Social Sciences.

Time: 11h45AM to 5pm, November 30, 2023

For registration and place, visit:

'Data Science, AI and Social Science' workshop 'Data Science, AI and Social Science' workshop- Management School - University of Liverpool

Speakers:

Christophe Mues, Professor of Data Science and Info Systems, Southampton University

Talk’s title: Deep learning methods in credit scoring: empirical insights into when and how they can add value

Simon Rudkin, Senior Lecturer in Data Science, Social Statistics, University of Manchester

Talk’s title: Hidden in Plain Sight: The Messages in Social Science Data

Slava Jankin, Chair in Data Science and Government and Director of the Centre for the Centre for Artificial Intelligence in Government (CAIG) at the University of Birmingham

Talk’s title: Uncovering Causal Mechanisms in Political Texts: How Natural Language Processing Can Aid Social Science Research

Francisco Rowe, Professor in Population Data Science, University of Liverpool School of Environmental Sciences

Talk’s title: Unleashing the potential of digital footprint data to understand human mobility: Opportunities, challenges and practice

Fellow of Econometric Society

October 9, 2023

Extremely privileged and honored to have been elected as a Fellow of the Econometric Society:

Stories - Management School - University of Liverpool

https://www.econometricsociety.org/society/news/The-Econometric-Society-Announces-its-2023-Fellows.html#:~:text=The%20Society%20is%20pleased%20to,Fellows%20of%20the%20Econometric%20Society.&text=The%202023%20FNC%20consisted%20of,Michele%20Terlit%2C%20and%20Yaw%20Nyarko.

The Econometric Society Africa Training Workshop will be held on December 13-15, 2023 (fully remote).

APPLY AS SOON AS POSSIBLE: Before Oct. 15th!

For this second edition, the focus is on Computational Macroeconomics. Come and learn how to solve dynamic equilibrium models and improve your coding skills with two excellent instructors, Jesus Fernandez-Villaverde and Pablo Winant!

Financial support is available for Africa-based PHD students and scholars.

More info here: https://lnkd.in/dH3kFZss

Virtual Time Series Seminar series (VTSS):

We re-start again this week (week of September 12, 2023). Please register and check for the list of speakers here:

https://sites.google.com/view/vtss/home

LAMBDA Research Cluster: Big Data Analytics Roundtable

Date: 26 June 2023

Time: 3-5pm

Place: University of Liverpool Management School - Seminar Room 5 (first floor)

Keynote speakers:

Janet Bastiman, Chief Data Scientist, Chair of the RSS Data Science and AI Section, Napier AI

Matthew Whittle, Data Science Manager at Meta

Geoff Wainwright, Chief Operating Officer, Impact Data Metrics Ltd

Gary Leeming, Director, LCR Civic Data Cooperative.

Abderrahim Taamouti, Moderator

After the preliminary remarks and discussion, we will open the floor to questions from the audience.

The 10th Days of Econometrics for Finance jointly organized with The 12th Workshop on High Dimensional Data Analysis (HDDA-XII)

April 26-28th, 2023, Mohammed V University in Rabat (UM5R) and ESSEC Africa, Morocco

Please see the program here

The registration for this workshop is free. Everyone is welcome to attend!

Organizers:

Ejaz Ahmed, Brock University, Canada

Mohamed Amezziane, Central Michigan University, USA

Taoufik Bouezmarni, Université de Sherbrooke, Canada

Ahmed El Ghini, Mohammed V University in Rabat, Morocco

Christian Francq, ENSAE and Université de Lille, France

Mohamed Ndaoud, ESSEC Business School, France

Jeroen Rombouts, ESSEC Business School, France

Abderrahim Taamouti, University of Liverpool Management School, UK

Virtual Workshop for Junior Researchers in Time Series on 20 April 2023:

Please see the program here

The videos of all presentations can be found here

The registration for this workshop is free and access to it can be obtained by registering to the VTSS seminar here and joining the meeting at the listed time.

Organizers:

Majid Al-Sadoon, Durham University

Adriana Cornea-Madeira, ISEG, Lisbon

Dimitris Korobilis, Glasgow University

Alessandra Luati, Imperial College London and University of Bologna

Geert Mesters, Pompeu Fabra University

Michele Piffer, King's College London

Abderrahim Taamouti, University of Liverpool Management School

Economics Workshop 2023

17th and 18th of April, 2023, University of Liverpool Management School

Please see the program here

Celebrating the 20th anniversary of the University of Liverpool Management School (ULMS), the Economics group is organising a two-day Economics conference on Monday 17 - Tuesday 18 April at the ULMS Atrium.

Launching a Virtual Time Series Seminar series (VTSS):

With group of friends and colleagues, we are launching a new initiative: a Virtual Time Series Seminar series (VTSS). The new series starts on September 15 and takes place regularly on Thursday at 16:00 UK time. All info and registration are available at:

https://sites.google.com/view/vtss/home

We are all enjoying going back to in-person events. But online seminars can still help the community after the Covid era, since they keep the two sides of the Atlantic closer to each other.

Post-doc opportunity at Liverpool University Management School

Please check here:

Job Specification (corehr.com)

MMF Sponsored Workshop 2022

Econometric and Big Data Analyses of Global Economy, Financial Markets and Economic Policies

28-29 June, 2022

Liverpool University Management School

Day 1: Tuesday, 28 June

09:00 – 09:25 Coffee Reception

09:25 – 09:30 Welcome Address

09:30 – 10:30 Keynote 1

Meredith Crowley (University of Cambridge)

TBC

10:30 – 10:45 Coffee Break

10:45 – 12:45 Invited Session 1 (International Trade)

Jun Du (Aston Business School)

TCA, Non-tariff Measures and UK Trade

Yuan Tian (University of Nottingham)

Trade Disruptions along the Global Supply Chain

Dennis Novy (University of Warwick)

Urban-Biased Structural Change

13:00 – 14:00 Lunch Break

14:15 – 15:15 Keynote 2

Glenn Magerman (Université libre de Bruxelles, ULB, CEPR)

The Impact of Covid Rescue Policies on Productivity Growth and Reallocation

15:15 – 15:30 Coffee Break

15:30 – 17:30 Invited Session 2 (Productivity and Change)

Gert Bijnens (National Bank of Belgium)

Emissions and Carbon Pricing: Do Firms Strive or Shrink?

Joep Konings (Nazarbayev University Graduate School of Business, ULMS, CEPR)

FDI and Superstar Spillovers: Evidence from Firm-to-Firm Transactions

Balazs Murakozy (University of Liverpool)

Technological Change and Skill Demand in Non-Competitive Labor Markets

18:30 – 20:30 Conference Dinner (by Invitation)

Day 2: Wednesday, 29 June

09:30 – 10:30 Keynote 3

Sudipto Karmakar (Bank of England)

(Un-)Intended Consequences of Government Support Measures During Covid-19

10:30 – 10:45 Coffee Break

10:45 – 12:45 Invited Session 3 (Economic Policies)

Jiaqi Li (Bank of Canada)

Predicting the Demand for Central Bank Digital Currency: A Structural Analysis with Survey Data

Tim Jackson (University of Liverpool)

Optimal Central Bank Balance Sheets

Mingli Chen (University of Warwick)

Deep Reinforcement Learning in a Monetary Model

13:00 – 14:00 Lunch Break

14:15 – 15:15 Keynote 4

Caio Almeida (Princeton University)

Can a Machine Correct Option Pricing Models

15:15 – 15:30 Coffee Break

15:30 – 17:30 Invited Session 4 (Financial Markets and Risks)

Marco Bardoscia (Bank of England)

TBC

Shixuan Wang (University of Reading)

TBC

Michael Ellington (University of Liverpool)

Persistence in Economic Networks

Sponsors:

· Money Macro & Finance Society

· The Economics Group, ULMS

· Econometrics and Big Data Research Cluster, ULMS

Organizers:

· Ruijun Bu

· Oliver de Groot

· Lu Han

· Tim Jackson

· Joep Konings

· Balazs Murakozy

· Abderrahim Taamouti

Registration Details:

· Participation to the conference including coffee and lunches are free of charge. Please email Ruijun Bu at ruijunbu@liv.ac.uk to register your interest.

· MMF society members seeking financial support from the society, please indicate this in your email and also contact the society for more details.

Conference Venues:

· Welcome address and all presentations (ULMS SR6 at the University of Liverpool)

· Coffee reception and breaks (ULMS SR6 Breakout Area)

· Lunches and Dinners (TBC)

N.B. The programme and venues are provisional and may be subject to minor amendments. Please contact Ruijun Bu at ruijunbu@liv.ac.uk for queries.

QRFE - Econometrics and Big Data Cluster (University of Liverpool Management School) Workshop on Econometrics

June 6th, 2022

Venue: 405 MHL (Durham Business School)

To attend the workshop online, please register here

Preliminary program

09:00-09:45 Liangjun Su ( School of Economics and Management, Tsinghua University)

Estimation of Heterogeneous Panel Data Models with an Application to Program Evaluation

09:45-10:30 Hashem Pesaran (University of Southern California)

Trimmed Mean Group Estimator for Ultra Short T Panels with Correlated Random Coefficients

10:30-11:00 Coffee

11:00-11:45 Bas Werker (Tilburg University)

Ancillarity and Semiparametric Efficiency

11:45-12:30 Jean-Marie Dufour (McGill University)

Approximation bounds for conditional expectations and nonparametric regressions:

theory and inference

12:30-13:30 Lunch

13:30-14:15 Barbara Rossi (Universitat Pompeu Fabra & CREI)

TBA

14:15-15:00 Fabio Canova (Norwegian Business School)

Using Structural and Nonstructural Shocks in the Estimation of DSGE Models

15:00-15:30 Coffee

15:30-16:15 Lynda Khalaf (Carlton University)

Identification-robust beta pricing, spanning, mimicking portfolios, and the benchmark neutrality of catastrophe bonds

16:15-18:00 Walk to Durham Cathedral

18:00-19:30 Dinner

Organizers:

Abderrahim Taamouti (Econometrics and Big Data Cluster at University of Liverpool Management School)

Majid Al Sadoon (QRFE at Durham University Business School)

Bo Zhou (Durham University Business School)

Please check the website of Econometrics and Big Data Cluster at University of Liverpool Management School and get in touch if you are interested in the research agenda/activities of the cluster:

Econometrics and Big Data - Management School - University of Liverpool

Very useful information: Econometric Society-Africa Region offers every year a limited number of sponsored Econometric Society membership to students and young scholars from low income regions who do not have financial support. To apply see here:

Econometric Society Membership | Africa Econ. Society (africaeconometricsociety.com)

See below some PhD scholarships at University of Liverpool Management School [Deadline 25 of March 2022]. Please get in touch if you are interested:

ULMS Economics PhD Funding Call: October 2022 entry at University of Liverpool (jobs.ac.uk)

QRFE seminars (Durham Business School) that I organized since 2014:

https://www.dur.ac.uk/business/research/economics/qrfe/seminars/

Forthcoming QRFE seminars: Autumn 2021/2022

Thursday, October 14, 2021, 3:00pm

Timothy Christensen (New York University)

Title: Robust Forecasting

Abstract: We use a decision-theoretic framework to study the problem of forecasting discrete outcomes when the forecaster is unable to discriminate among a set of plausible forecast distributions because of partial identification or concerns about model misspecification or structural breaks. We derive “robust” forecasts which minimize maximum risk or regret over the set of forecast distributions. We show that for a large class of models including semiparametric panel data models for dynamic discrete choice, the robust forecasts depend in a natural way on a small number of convex optimization problems which can be simplified using duality methods. Finally, we derive “efficient robust” forecasts to deal with the problem of first having to estimate the set of forecast distributions and develop a suitable asymptotic efficiency theory. Forecasts obtained by replacing nuisance parameters that characterize the set of forecast distributions with efficient first-stage estimators can be strictly dominated by our efficient robust forecasts.

Zoom link (To register):durhamuniversity.zoom.us/webinar/register/WN_fbe_9y8qQhG6EdQ_-OKoYA

Thursday, October 21, 2021, 3:00pm

Sophocles Mavroeidis (Oxford University)

Title: Testing the effectiveness of unconventional monetary policy in Japan and the United States

Abstract: Unconventional monetary policy (UMP) may make the effective lower bound (ELB) on the short-term interest rate irrelevant. We develop an empirical test of this `irrelevance hypothesis,' based on a simple idea that under the hypothesis, the short rate can be excluded in any empirical model that accounts for alternative measures of monetary policy. We develop a theoretical model that underpins this hypothesis, and test it empirically for Japan and the United States using a structural vector autoregressive model with the ELB. For each country, we firmly reject the hypothesis but find that UMP has had strong delayed effects.

Zoom link (To register):durhamuniversity.zoom.us/webinar/register/WN_fbe_9y8qQhG6EdQ_-OKoYA

Thursday, 28 of October, 2021, 3:00pm

Laura Coroneo (York University)

Title: Testing the predictive accuracy of COVID-19 forecasts

Abstract: We test the predictive accuracy of forecasts of the number of COVID-19 fatalities produced by several forecasting teams and collected by the United States Centers for Disease Control and Prevention for the epidemic in the United States. We find three main results. First, at the short horizon (1-week ahead) no forecasting team outperforms a simple time-series benchmark. Second, at longer horizons (3- and 4-week ahead) forecasters are more successful and sometimes outperform the benchmark. Third, one of the best performing forecasts is the Ensemble forecast, that combines all available predictions using uniform weights. In view of these results, collecting a wide range of forecasts and combining them in an ensemble forecast may be a superior approach for health authorities, rather than relying on a small number of forecasts.

Zoom link (To register): https://durhamuniversity.zoom.us/webinar/register/WN_grVi9mZXS2KJIsQJ-zqiOg

Thursday, 4 of November 2021, 3:00pm

Stefano Giglio (Yale School of Management)

Title: A Quantity-Based Approach to Constructing Climate Risk Hedge Portfolios

Abstract: We propose a new methodology to build portfolios that hedge climate change risks. Our quantity-based approach explores how mutual funds holdings change when the fund adviser experiences a local extreme heat event that shifts beliefs about climate risks. We use the observed trading behavior to predict how investors will reallocate their capital when “global” climate news shocks occur, which shift the beliefs and asset demands of many investors simultaneously and thus move equilibrium prices. We show that a portfolio that holds stocks that investors tend to buy after experiencing a local heat shock appreciates in value in periods with aggregate climate news shocks. Our quantity-based approach yields superior out-of-sample hedging performance compared to traditional methods of identifying hedge portfolios. The key advantage of the quantity-based approach is that it learns from cross-sectional trading responses rather than time-series price information, which is limited in the case of climate risks. We also demonstrate the efficacy and versatility of the quantity-based approach by constructing successful hedge portfolios for aggregate unemployment and house price risk.

Zoom link (To register): https://durhamuniversity.zoom.us/webinar/register/WN_5yYNcNCIRj-iKU-oRGPiGw

Thursday, 11 November, , 2021, 3:00pm

Rasmus Tangsgaard Varneskov (Copenhagen Business School)

Title: Consistent Local Spectrum (LCM) Inference for Predictive Return Regressions

Abstract: This paper studies the properties of predictive regressions for asset returns in economic systems governed by persistent vector autoregressive dynamics. In particular, we allow for the state variables to be fractionally integrated, potentially of different orders, and for the returns to have a latent persistent conditional mean, whose memory is difficult to estimate consistently by standard techniques in finite samples. Moreover, the predictors may be endogenous and ``imperfect". In this setting, we show that the Local speCtruM (LCM) procedure is consistent and delivers asymptotically Gaussian inference. Furthermore, we provide a new LCM-based estimator of the conditional mean persistence that leverages biased regression slopes as well as new LCM-based tests for significance of (a subset of) the predictors, which are valid even without estimating the return persistence. Simulations illustrate the theoretical arguments. Finally, in an empirical application to monthly S&P 500 return predictions, we provide evidence for a fractionally integrated conditional mean component. Moreover, using our new LCM procedure and tools, we document significant predictive power for key state variables such as the price-earnings ratio and the default spread.

Zoom link (To register): https://durhamuniversity.zoom.us/webinar/register/WN_wGU9jWV2QHaPcJJCtCWH4w

Thursday, 18 of November 2021, 2021, 3:00pm

Stephane Bonhomme (University of Chicago)

Title: Estimating Individual Responses when Tomorrow Matters

Abstract: We consider a class of response functions that depend not only on current covariates, but also on the process of covariates. We obtain those as the nonparametric reduced forms of structural dynamic models of individual choice. We model the process of covariates using a hidden Markov structure. We are interested in estimating the effects of changes in this process on decisions and other outcomes. We decompose the total effect of such a change into a contemporaneous effect and an effect accounting for expectations. We illustrate the method in two settings. In a model of consumption and savings, we show how to estimate the effects of a change in the income process on consumption decisions. In a model of agricultural production, we show how to identify both the effects of changes in weather and changes in the weather process (i.e., the ``climate''), thereby accounting for the possibility of adaptation. We take this second illustration to data on weather and crop yields in the US since 1950.

Zoom link (To register): https://durhamuniversity.zoom.us/webinar/register/WN_vLZ2Xo_dTfe0lxnIiOtLgg

Thursday, November 25, , 2021, 3:00pm

Jia Li (School of Economics, Singapore Management University)

Title: Reading the Candlesticks: An OK Estimator for Volatility

Abstract: The nonparametric inference on “spot” volatility has mostly relied on high-frequency returns data. In this paper, we exploit the richer information in high-frequency candlesticks and propose an Optimal candlesticK (OK) estimator for the spot volatility at a given time point. Under a standard infill asymptotic setting for Ito semimartingale price processes, we show that the OK estimator is asymptotically unbiased and has minimal asymptotic variance within a class of linear estimators. In addition, its estimation error can be coupled by a Brownian functional, whose distribution is pivotal and known in finite-sample. Optimal confidence intervals can be constructed using the highest density interval of the (nonstandard) coupling distribution. Our theoretical and numerical results suggest that the proposed candlestick-based estimator is much more accurate than the conventional spot volatility estimator based on high-frequency returns. An empirical illustration is provided, which documents the intraday spot volatility dynamics of various assets during the Fed Chairman’s recent congressional testimony.

Zoom link (To register): https://durhamuniversity.zoom.us/webinar/register/WN_63vwwbdPT06FE_GF9MOPGQ

Thursday, 2nd of December, 2021, 3:00pm

David Preinerstorfer (University of St. Gallen)

Title: Consistency of p-norm based tests in high dimensions: characterization, monotonicity, domination

Abstract: Many commonly used test statistics are based on a norm measuring the evidence against the null hypothesis. To understand how the choice of a norm affects power properties of tests in high dimensions, we study the consistency sets of p-norm based tests in the prototypical framework of sequence models with unrestricted parameter spaces, the null hypothesis being that all observations have zero mean. The consistency set of a test is here defined as the set of all arrays of alternatives the test is consistent against as the dimension of the parameter space diverges. We characterize the consistency sets of p-norm based tests and find, in particular, that the consistency against an array of alternatives cannot be determined solely in terms of the p-norm of the alternative. Our characterization also reveals an unexpected monotonicity result: namely that the consistency set is strictly increasing in p∈(0,∞), such that tests based on higher p strictly dominate those based on lower p in terms of consistency. This monotonicity allows us to construct novel tests that dominate, with respect to their consistency behavior, all p-norm based tests without sacrificing size.

Zoom link (To register): https://durhamuniversity.zoom.us/webinar/register/WN_EIc2SxoNR5WQMnBDXmKgIw

Past QRFE seminars/Workshops

Virtual QRFE Workshop on Financial Econometrics, June 14-15, 2021

Venue: Zoom

To attend the workshop and for the link to zoom, please register here:

Webinar Registration - Zoom

Program

June 14, 2021

16:25 - 16:30PM Opening remarks

16:30 - 17:15PM Torben Andersen (Kellogg School of Management)

On Measurement Errors and Inference for Option-Based Volatility Indices

17:15 - 17:20PM Break

17:20 - 18:05PM Dacheng Xiu (Booth School of Business, University of Chicago)

Test Assets and Weak Factors

18:05 - 18:10PM Break

18:10 - 18:55PM Giuseppe Cavaliere (University of Bologna and University of Exeter Business School)

Bootstrap Inference for Hawkes and General Point Processes

18:55 - 19:00PM Closing remarks

June 15, 2021

16:25 - 16:30PM Opening remarks

16:30 - 17:15PM Jesus Gonzalo (University Carlos III de Madrid)

Long-Term Climate Forecasts

17:15 - 17:20PM Break

17:20 - 18:05PM Christiane Baumeister (University of Notre Dame)

Advances in Structural Vector Autoregressions with Imperfect Identifying Information

18:05 - 18:10PM Break

18:10 - 18:55PM Domenico Giannone (Senior Principal Economist at Amazon.com)

Nowcasting with Large Bayesian Vector Autoregressions

18:55 - 19:00PM Closing remarks

Organizers: Bo Zhou, Majid Al-Sadoon, Abderrahim Taamouti

End of Workshop

QRFE seminars for 20/21 Academic Year

Thursday, 8 October, 3:00pm

Luca Fanelli (University of Bologne)