MATLAB and Simulink Seminars

MathWorks Finance Conference 2022 (Online)


The MathWorks Finance Conference 2022 brings together industry professionals to showcase MathWorks tools in real-world industry use cases, and offers practitioner advice through live presentations, Q&A, interactive panel discussions and in-depth demos. Topics will include AI, sustainable investing, climate risk, portfolio and risk management, cloud deployment, and the latest research developments.

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Please see below for agenda and presentation abstracts.


Eastern Time (am)

London Time (pm)

Day 1
11 October

Day 2
12 October

8:30 am

1:30 pm

Alexander Diethert, MathWorks

Productivity, Scalability, Robustness - Next generation coding with MATLAB 

Björn van Roye, Bloomberg

MATLAB for Real-time Economics

9:00 am

2:00 pm

Daniel Rubio, Swiss Re

Where Scalability Meets Efficiency: Using MATLAB and Cloud Computing to Run Our Internal Risk Model


9:30 am

2:30 am


9:45 am

2:45 pm

Ralf Elsas, LMU Munich

Multilabel Analysis of Firm Disclosures and Semantic Search

Martin Guth, Austrian National Bank

ARNIE in Action – OeNB’s Stress Test Framework including Climate Risk

10:15 am

3:15 pm

Luca Lamorte, Intesa Sanpaolo

Delivering the Fundamental Review of the Trading Book (FRTB) Internal Model: Main Benefits and Challenges

Randy Steenbergen, Kempen

Taking financial documentation to the next level: an application of the MATLAB Report Generator Toolbox

10:45 am

3:45 pm


11:00 am

4:00 pm

Richard Peterson, MarketPsych + Valerio Sperandeo, MathWorks

Improving Quant Portfolios with the MarketPsych ESG Controversies and MATLAB

Maria Palazzi-Nieves, MJ Hudson

Evaluating Climate Risk in Liquid Investment Strategies. (SBTi)

11:30 am

4:30 pm

Duan Wang, SLC Management

Analyzing Financial TimeSeries using Random Matrix Theory

Yannis Ben Ouaghrem, MathWorks

Modeling the Impact of Climate Risks on Mortgages

12:00 noon

5:00 pm

Conference closes

Presenters and Presentation Abstracts

Alexander Diethert
Alexander Diethert

Productivity, Scalability, Robustness - Next generation coding with MATLAB

Alexander Diethert, Application Engineering Manager, MathWorks

You see Financial Models as an integral part of your daily work. You constantly evaluate numeric results, derive critical business decisions, or predict economic scenarios that are the basis of critical business decisions.  Although your set-up is good enough to deliver the required results, you feel it has reached a certain limit preventing you from taking your applications to the next level. You do appreciate the value of modern programming concepts, but your day job keeps you too busy to invest the necessary time. This talk is for you.

MathWorks has invested significantly to make coding easy for financial experts. This presentation will give you a tour around the relevant recent developments. The goal is to inspire you to get started with the next generation of your applications, that your effort will be lower than you expect, and that the pay-off easily outweighs your investment.

Dr. Alexander Diethert is a senior financial application engineer at MathWorks in Munich, Germany. He is leading a team of technical experts that empower analysts, economists, and IT people around the world to optimize their use of MathWorks technology. Prior to joining MathWorks, Alexander worked as a consultant in the financial services area. Alexander holds a diploma in mathematics and a Ph.D. in physics. 

Björn van Roye
Björn van Roye

MATLAB for Real-time Economics

Björn van Roye, Head of Global Economic Modelling, Bloomberg LP

The pandemic has significantly changed the way macroeconomic analysis is being done. The rise in high frequency and alternative data availability make it possible to have a very early view on where major economies are heading. We use MATLAB as an integrated real time macro modeling platform to provide accurate nowcasts, forecasts and scenarios to our clients.

Björn van Roye is the Head of Global Economic Modelling for Bloomberg Economics in Madrid and lecturer at the University of Oxford. He previously worked as a Team Lead Economist at the European Central Bank and a Research economist at the Kiel Institute for the World Economy. He is author of several macroeconomic models and tools such the “ECB-Global model for spillover analysis” and the “BEAR toolbox" for estimating Bayesian VAR models.

Daniel Rubio
Daniel Rubio

Where Scalability Meets Efficiency: Using MATLAB and Cloud Computing to Run Our Internal Risk Model

Daniel Rubio, Head of Integrated Risk IT, Swiss Re

Swiss Re is one of the world's leading providers of reinsurance, insurance, and other forms of insurance-based risk transfer. Our internal capital adequacy model, critical for regulatory reporting and business steering, is implemented in MATLAB and deployed as the core of a complex technology ecosystem using MATLAB Production Server. The simulation workload is distributed to a computing cluster using MATLAB Parallel Server.

Daniel discusses the financial and operational benefits of the platform, Swiss Re’s cloud transformation journey, and how they are partnering with MathWorks to customize the reference architecture for Azure™ in a way that maximizes the business value.

Daniel Rubio is an IT Director at Swiss Re in Zürich, Switzerland. He has worked in the financial services industry for over 20 years delivering business initiatives where technology played a major role. He is interested in cloud computing and currently he focuses on the public cloud transformation of Swiss Re's Risk Management technology landscape.

He holds a doctoral degree in Physics from the Swiss Federal Institute of Technology.

Martin Guth
Martin Guth

ARNIE in Action – OeNB’s Stress Test Framework including Climate Risk

Martin Guth, Stress Test Analyst, Austrian Central Bank (Österreichische Nationalbank)

How the Austrian central bank (OeNB) conducts stress tests to assess the resilience of the banking system and to analyze potential drivers of systemic risk, complemented by more specialized exercises (e.g. climate risk) – with the ARNIE MATLAB based Stress-Testing platform.

Martin Guth is a stress test analyst at the Oesterreichische Nationalbank (OeNB) within the department of Supervision Policy, Regulation and Strategy with previous work experience at the European Central Bank (ECB). His main responsibilities evolve around network contagion models, credit risk satellite models and scenario design. He holds a MSc with distinction in economics from the Vienna University of Economics and Business and currently pursues a PhD in social and economic sciences.

Luca Lamorte
Luca Lamorte

Delivering the Fundamental Review of the Trading Book (FRTB) Internal Model: main benefits and challenges

Luca Lamorte, Risk Manager, Market and Financial Risk Management, Intesa SanPaolo

The financial industry is preparing the transition to the new regulation for market risk capital (FRTB), upcoming in 2025. In this context we are able to make a brief summary of the main benefits and challenges that a bank must face in order to capitalize its trading desks according to the FRTB internal model approach (IMA). In particular the validation tests at individual desks level required by the FRTB are very challenging, which makes much more complicated the application of the IMA to the entire perimeter of the trading book. We analyze these cases in detail, showing where MATLAB can be of great use in performing analyses and benchmarkings of the new legislation.

Luca Lamorte is an expert risk manager for Intesa SanPaolo IMA Market Risk office, in particular the calculation of market risk weighted asset for the internal model. He has over 7 years of experience with Intesa SanPaolo, with a part in the market data unit and last years in implementation and calculation of market risk measures (VaR, Stressed VaR, IRC). He is a functional referent for FRTB project in Intesa SanPaolo working on the develop of methodology and implementation of FRTB features (Expected shortfall, IMCC, Default Risk Charge, Profit&Loss Attribution).

Luca holds a degree in Mathematical Engineering.

Randy Steenbergen
Randy Steenbergen

Taking financial documentation to the next level: an application of the MATLAB Report Generator Toolbox

Randy Steenbergen, Quant Research Analyst, Kempen & Co

Van Lanschot Kempen, the oldest independent financial institution of the Netherlands, is a specialized wealth manager. As one of the investment solutions it offers Structured Products to its clients. To offer these tailor-made instruments, the team needs to provide a lot of mandatory documentation. By integrating the MATLAB Report Generator Toolbox in an AppDesigner GUI, designed according to the MVP principles, we managed to create a (fully) automated Document Generator.

Randy Steenbergen is a quant analyst at the Quant, Efficiency and Data team at Van Lanschot Kempen. He is responsible for developing and maintaining the pricing library of the Structured Products desk, and building quant solutions for multiple departments within the bank. He holds a master’s in Applied Mathematics with a specialization in Financial Engineering from the Delft University of Technology.

Richard Peterson
Richard Peterson


Valerio Sperandeo
Valerio Sperandeo

Improving Quant Portfolios with the MarketPsych ESG Controversies and MATLAB

Richard Peterson, CEO, MarketPsych / Valerio Sperandeo, Application Engineer, MathWorks

Identifying companies’ trend in ESG controversies can provide valuable insight for mitigating risk in equity and fixed income portfolios. Refinitiv MarketPsych ESG Analytics data, via Refinitiv, provides sentiment scores distilling a massive collection of news and social media content through an extensively curated language framework. Richard Peterson, CEO of MarketPsych introduces the dataset and Valerio Sperandeo of MathWorks shows how to quickly build a quantitative investment strategy using the data, in MATLAB.

Richard Peterson is CEO of MarketPsych Data, a producer of media perceptions data focused on financial and sustainability themes. MarketPsych’s data is consumed by funds, banks, consultancies, and governments in more than 25 countries. The data has been the subject of more than 100 academic papers. Dr. Peterson is an associate editor of the Journal of Behavioral Finance, a Board-certified psychiatrist, authored books including "Trading on Sentiment" (Wiley, 2016), and performed postdoctoral neuroeconomics research at Stanford University.

As a member of the Application Engineering team at MathWorks, Valerio Sperandeo assists customers in the development and deployment of financial applications. He holds a M.Sc. in Quantitative Finance from the University of Perugia with focus on risk and asset management.

Before joining MathWorks, he worked as Analyst at the investment department of a global asset management company. There, he contributed to the development of several tools for risk overlay, portfolio optimization and strategic asset allocation.

Maria Palazzi-Nieves
Maria Palazzi-Nieves

Evaluating climate risk in liquid investment strategies

Maria Palazzi-Nieves, Analyst, MJ Hudson

The current climate emergency has led companies and governments to take action to help mitigate this crisis and to transition toward a low-carbon economy. Financial institutions are not exempt from taking part in such a transition, as they are increasingly pushed to assess their exposure to climate risk and to consider sustainability objectives in their investment strategies.

Building on SBTi methodology and employing a varied set of MATLAB toolboxes, in this talk we introduce our carbon screening and temperature scoring tool, developed to evaluate internal security for liquid investment portfolios. The tool allows institutions to evaluate their alignment with current GHG emissions reduction and temperature goals, which can potentially influence their investment decisions.

Maria Palazzi-Nieves is a Research Data Analyst at MJ Hudson Quantitative Solutions. Her role involves exploratory analyses of client data and the implementation of new functionalities to enhance risk reporting, primarily for alternative fund managers and UCITS. This work includes the development of an ESG reporting solution and the implementation of an SBTi climate impact assessment for public market issuers, in collaboration with MathWorks. Before joining MJ Hudson, Maria worked as a Postdoctoral Researcher at Universitat Oberta de Catalunya. Maria holds a Ph.D. in Networks and Information Technologies from Universitat Oberta de Catalunya and a bachelor’s and a master’s degree in Physics.

Duan Wang
Duan Wang

Analysing Financial Time-Series using Random Matrix Theory

Duan Wang, Director, Derivatives and Quantitative Strategies, SLC Management

Random matrix theory (RMT) is a useful tool for noise reduction in the sample covariance matrix in financial time series analysis. In this presentation we demonstrate how to implement RMT in MATLAB to produce an improved estimator for the sample covariance variance. We also show a couple of examples in portfolio optimization and asset allocation.

Duan Wang is a quantitative analyst at the Derivatives and Quantitative Strategies team of SLC Management. He is responsible for developing models for derivatives trading strategies, derivatives valuation and portfolio optimization, and implementing the models in MATLAB. He holds a Ph.D. in Physics in Boston University.

Yannis Ben Ouaghrem
Yannis Ben Ouaghrem

Modeling the Impact of Climate Risks on Mortgages

Yannis Ben Ouaghrem, Application Engineer, MathWorks

Regulators, customers, investors, and other stakeholders are driving financial institutions to do their part to transition to a low-carbon economy and manage exposure to climate-related risks. Central Banks are conducting Climate Stress Test exercises. They are using new data sources and developing new types of models, often leveraging methods from other scientific and engineering fields. Practitioners need software that provides a broad range of modeling functionality, flexible interfaces, rich visualization capabilities, collaboration, and review features to keep up with the pace of change in this area.

Learn how MATLAB can get you started modeling both physical and transition climate risks. In a live demonstration, you will learn how to:

  • Visualize flooding and subsidence risk within a city (physical risk).
  • Understand the impact of remediation costs or policies aimed at increasing the energy efficiency of buildings (transition risk).
  • Model the impact of these on the credit risk exposure in a portfolio of mortgages.

Yannis Ben Ouaghrem is an Application Engineer at MathWorks, helping Financial Services customers get the best use of our tools, particularly in Climate Risk. He actively contributes to resolving some great sustainability challenges by delivering pieces of software aiming to decarbonize the aviation industry.

Yannis holds a master’s in computer science with a specialization in data science from the University of Technology of Compiegne (France).

MathWorks Finance Conference 2022

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