Tuesday 15th June: Day 2 WQF
New Tool for Market Monitoring: MarketScribe
EDT: 09.00
BST: 14.00
CEST: 15.00
Abstract: The market group serves as “eyes and ears” of the Federal Reserve System and Treasure Department in terms of monetary policy, financial stability policy, foreign exchange policy and debt management policy. One of the key responsibility of the market group is market monitoring, which provides the rigorous analysis of how the financial markets are reacting to, and interpreting monetary policy. One importance piece of this process is the event studies of FOMC communications and other policy communications such as governor and Fed president’s speeches/interviews. This is time sensitive work, and currently is very human resource intensive because it is conducted manually. Built with advanced AI techniques, the MarketScribe is an NLP tool transcribe and summarize the public speeches, and visualize the market impact of these communications on a word-to-word basis. The tool outputs a word document including the summary and full transcription of the speech. The tool also includes an interactive dashboard to visualize the transcription analysis together with the market data movement. It is now been utilized in the market continues group for the quick overview of the market during the FOMC time.
Knarig Arabshian:
Senior Knowledge Engineer in Technology Innovation, Federal Reserve Bank of New York
Knarig Arabshian: Senior Associate Knowledge Engineer in Technology Innovation, Federal Reserve Bank of New York
I am a Senior Associate Knowledge Engineer in Technology Strategy & Innovation at theFederal Reserve Bank of New York where I conduct research in semantic web technologies and text analytics for structuring financial data.
Previously, I was an Assistant Professor in the Computer Science Department at Hofstra University in Hempstead, NY and a Member of Technical Staff at Bell Labs in Murray Hill, NJ. I have also taught as an Adjunct Professor at Columbia University twice. I received my PhD in Computer Science from Columbia University in 2008, where I worked in theIRT Lab under the advisment of Henning Schulzrinne.
Xue Rui:
Senior Associate, Enterprise Architecture, Federal Reserve Bank of New York
Xue Rui: Senior Associate, Enterprise Architecture, Federal Reserve Bank of New York
Xue graduates from University of Notre Dame with Ph.D in physics and Master in Electric Engineering. She is a Senior Associate in Federal Reserve Bank of New York. Her work focuses on developing and deploying NLP and AI technology in the bank. Prior to joining the Federal Reserve Bank, Xue has been working as Scientist in General Electric Global Research Center. Xue’s research interests focus on artificial intelligence, including natural language processing, image analysis, and computer vision. She holds 20 + peer reviewed publications and 10 + patents.
Measuring Central Bank Communication with Machine Learning
EDT: 10.00
BST: 15.00
CEST: 16.00
Abstract: We apply facial recognition methods to FOMC press conference videos, and quantify one of the most important aspects of nonverbal communication – facial expressions. Using minute-level data, we align our nonverbal communication measure with a set of financial assets to estimate the impact of the Federal Reserve Chairs’ facial expressions on investor expectations. We find that investors adversely react to negative expressions revealed during the press conference, even when controlling for the verbal component of the press conference and additional explanatory variables. The effect is heightened in meetings that draw more attention and when the Chair is discussing forward guidance.
Sophia Kazinnik:
Senior Quantitative Analyst, Federal Reserve Bank of Richmond
Sophia Kazinnik: Senior Quantitative Analyst, Federal Reserve Bank of Richmond
Sophia is currently a Sr. Quantitative Analyst within the Supervision, Regulation and Credit (QSR) department at the Federal Reserve Bank of Richmond. Prior to joining the Richmond Fed, Sophia worked at the University of Houston, teaching courses in economics. She received her bachelor’s degree from the Tel Aviv University (Tel-Aviv, Israel), and earned her doctoral degree in economics from the University of Houston. In her current role, she works on development and production of analytical tools related to financial risk management. Her research interests focus on applying Natural Language Processing (NLP) techniques in the realm of financial economics.
Keynote: Key Considerations when Implementing a Modeling Program within a Global, Highly Regulatory Environment
EDT: 11.00
BST: 16.00
CEST: 17.00
Abstract:
During this segment, Caitlin will discuss the key internal and external factors to consider when planning, organizing and executing a modeling-related program within a global, highly regulated financial institution. This includes a view on the overall ecosystem in which these programs are implemented, including strategy, governance, change management, data and infrastructure, and where there are common missteps that may derail the program.
Caitlin Cani:
Portfolio Manager, Consumer Risk & Finance CRO, Citi
Caitlin Cani: Portfolio Manager, Consumer Risk & Finance CRO, Citi
Caitlin Cani has been with Citi for 10 years and is currently the Portfolio Manager for two functions within the Risk organization’s IT Program Delivery Office (IT PDO). Her responsibilities include delivery of technology-based programs sponsored by the Chief Risk Officers for Citi’s Global Consumer Bank and Finance organizations.
Prior to joining the IT PDO, Caitlin lead the Data, Process and Infrastructure Workstream as part of Citi’s Strategic Regulatory Initiatives team, which provides governance and oversight to the firm’s Comprehensive Capital Analysis and Review and Dodd-Frank Act Stress Test (CCAR / DFAST) processes. She also spent five years as a Program Manager within Citi’s Chief Technology Office Strategic Planning function, where she supported a range of global initiatives which impacted Operations & Technology and the Global Functions.
Caitlin started her career as a Project Manager at Sughrue Mion, PLLC – an intellectual property law firm, based in Washington, DC.
Caitlin is a member of the Citi Women organization. She holds a Master’s Degree in Technology Management from Columbia University and a Bachelor’s degree from The George Washington University. She is PMP certified by the Project Management Institute (PMI). Caitlin is a married with one son.
PANEL: Talent Attraction & Retention
EDT: 12.00
BST: 17.00
CEST: 18.00
Topics:
- What are QR Financial Services currently doing and what should they be doing to attract more female talent?
- What can Universities and Recruitment companies do to help?
- What strategies are financial companies using at present if any?
- What are QR Financial Services currently doing and what should they be doing to retain female talent?
- What top positions besides Asset Management can QF- profiled women occupy?
- For each position open, the percentage of female CVs submitted is very small (if not none). Why is this happening and how can universities/headhunters/companies work together to improve the numbers?
- At more senior levels the number of women is even lower than at entry level which means that the female population retention rate is low or/and women are not being promoted. Discuss.
- Mentoring programmes that could specifically help Diversity & Inclusion.
- Are quantitative positions too specialised which prevents women (and men) to move horizontally to different (and possibly more senior) roles?
Moderator:
Burcu Karabork:
Quantitative Developer, NatWest Markets
Burcu Karabork: Quantitative Developer, NatWest Markets
Burcu joined NWM in 2012 on the Technology Graduate Scheme and is currently a quant developer at NWM. She holds an MEng (Hons) in Aeronautical Engineering from the University of Bristol. She has spent the last few years working on the bank’s unified risk engine and has more recently returned to her more maths-centric roots in the eFI space.
Oksana Kitaychik:
Quantitative Analyst, Barclays
Oksana Kitaychik: Quantitative Analyst, Barclays
Oksana Kitaychik is a quant at Trading Cross Product Quant Analytics team at Barclays. She develops quantitative models for a range of products and asset classes within the bank, with focus on market risk models. Prior to joining Barclays, Oksana worked as an economic consultant and directed numerous projects in the areas of financial economics, quantitative finance, statistics and valuation. In that role, Oksana provided expert testimonies in court on a number of matters involving fixed income securities, municipal markets, leveraged investment strategies, and various data analytics and statistical issues.
Oksana co-authored a chapter on credit derivatives and mortgage-backed securities in “The Handbook of Mortgage-Backed Securities” (Fabozzi, ed., 2016). She holds MS in Mathematics in Finance from Courant Institute of Mathematical Sciences at NYU, MBA with specialization in Statistics and Quant Finance from Stern School of Business at NYU, and MA in Economics from Wesleyan University. In addition, Oksana holds Bachelor’s degrees in Electrical Engineering and International Economics. In 2012, she received the W. Edwards Deming academic award for “demonstrated excellence in the field of statistics” from NYU.
Lara El Sabbagh:
Quantitative Analyst, Bank of America
Lara El Sabbagh: Quantitative Analyst, Bank of America
Jill Zhao:
Director, Global Consumer Bank Risk Appetite Framework, Citi
Jill Zhao: Director, Global Consumer Bank Risk Appetite Framework, Citi
Jill is currently managing Global Consumer Bank Risk Appetite Framework for Citi. Prior to that, Jill was global head of Citi’s consumer bank risk and finance management reporting and analysis group and she also led key Citi-wide Risk Appetite and Stress Testing initiatives as part of the Quantitative Risk and Stress Testing group. Jill is a seasoned risk leader with 15+ years of experience and expertise in risk management (First and Second Lines of defense, Risk Appetite, Analytics, Reporting, Policy and Governance) and Consumer Bank (In-depth product P&L knowledge, FP&A, Credit Risk Management). She is also experienced in building/leading high performing global teams and driving large scale global transformation efforts. Jill has an MBA from New York University with concentration in Finance.
Edith Mandel:
Principal, Greenwich Street Advisors, LLC
Edith Mandel: Principal at Greenwich Street Advisors, LLC
Edith Mandel is a seasoned finance professional with 20 years of experience. She held a number of senior roles both on the sell and buy sides of the Fixed Income business.
Edith has extensive hands-on experience in developing quantitative trading models, and building systematic risk-taking businesses from the ground up.
As a principal at Greenwich Street Advisors, LLC, Edith advises both established participants in the Fixed Income market and those companies considering opportunities for expansion. As an expert in the Fixed Income market, Edith evaluates the opportunity cost, advises on trading infrastructure build-out, electronic and quantitative trading, risk management, alpha research and algorithmic execution.
In the last two-and-a-half years, Edith Mandel was the head of Fixed Income Mid-Frequency Trading at KCG (formerly GETCO). While there, she spearheaded a development of a new quantitative and systematic business within the Global Fixed Income group.
Edith started her professional career at Goldman Sachs, where she held a number of positions in the Fixed Income division. As a Managing Director, Edith ran a team of quantitative strategists responsible for algorithmic trading in US Treasuries and Swaps, for risk management of a broad set of interest rate products, including vanilla and exotic options, and for the development of a toolkit for systematic risk-taking.
Prior to joining KCG, Edith Mandel worked at Citadel as a Managing Director, Head of Fixed Income Quantitative Research. There she was instrumental to a significant revamp and expansion of the Fixed-Income Asset Management business and a development of new profitable systematic trading strategies in liquid rates.
Sandrine Ungari:
Head of Cross-Asset Quantitative Research team, Société Générale
Sandrine Ungari: Head of Cross-Asset Quantitative Research team, Société Générale
Sandrine Ungari is currently Head of Cross-Asset Quantitative Research team at Société Générale. Within the Cross-Asset Research group, the Quantitative Research team is active in risk premia strategies, derivatives and structured products, portfolio risk modelling, and provides research to investors worldwide. The group has been recognised as a market leader in quantitative research, and was ranked #1 in the Extel survey in the Quantitative Strategies category. Sandrine’s research topics cover systematic strategies across asset classes, interest rate modeling, machine learning, statistical analysis and portfolio construction. She joined Société Générale in 2006. Prior to that, she worked as a quantitative analyst at HBOS Treasury and at Reech Sungard in London. She is a graduate of ENSTA (Paris) and hold a Master’s in Quantitative Finance from Paris VI University. She is a guest lecturer at University Paris Diderot.
