In this episode our guest is Argyro (Iro) Tasitsiomi, Head of Investments Data Science at T. Rowe Price. Iro has extensive experience in AI and data science within the financial markets. Early in her career Iro held significant roles focusing on Quantitative Research & Risk Management, where she developed advanced trading strategies and econometric forecasting tools. 

Later, as a Data Scientist in Investment Banking, she led initiatives in business intelligence, market intelligence, and machine learning infrastructure development. Her work has spanned various domains, including asset portfolio optimization, enterprise risk management, and mergers and acquisitions.

She joins us on the podcast to discuss her professional journey at leading financial institutions such as Goldman Sachs, BlackRock, Prudential, and T. Rowe Price, and explore how AI is transforming various aspects of financial markets. We'll discuss advancements in financial modeling, the opportunities and risks of integrating AI into financial analysis, and the impact of fake data on market stability. Additionally, we'll cover the importance of quality data, the enduring value of human expertise, and emerging skills in the era of AI.

Topics:

Career Journey: Iro’s professional journey working at top financial institutions such as Goldman Sachs, BlackRock, Prudential, and T. Rowe Price

Earlier Modeling Techniques: time series,  trading strategies and risk modeling

AI Applications in Financial Markets: How is AI being applied across different areas of the financial markets today?

Fundamental Analysts in the Age of AI: How can fundamental analysts leverage their skills alongside AI tools to create a more comprehensive approach to financial analysis?

Advancements in Financial Modeling: With the rise of AI, have modeling techniques advanced beyond traditional methods like Monte Carlo simulations and the Black-Scholes models?

Opportunities and Risks of AI: What are the opportunities and risks of integrating AI into fundamental financial analysis?

Impact of Fake Data and Fake News: Exploring the influence of fake data and fake news on social media and its impact on financial markets.

Importance of Quality Data: The significance of quality data for AI in financial markets and how the evolving data landscape is shaping robust quantitative models.

Crowding: In traditional finance, popular trading strategies often become less effective as more market participants adopt them (crowding). Looking ahead, with the rise of AI and everyone potentially having access to similar LLM tools, do we foresee a similar phenomenon of "crowding" occurring?

Synthetic Data Usage: Discussing the use of synthetic data in financial market modeling and analysis.

Economic forecasting: The potential benefits and challenges associated with using AI for this purpose

Astrophysics: Iro’s research focused on large-scale structure formation in the universe using cosmological simulations.

Show Notes:

Learn more about Iro Tasitsiomi:

https://www.linkedin.com/in/argyrotasitsiomi/

Bits and Brainwaves Newsletter: https://www.linkedin.com/newsletters/bits-brainwaves-7151965921455046657/

Argyro (Iro) Tasitsiomi's  Google Scholar Astrophysic Citations: https://scholar.google.com/citations?user=-dtAtwIAAAAJ&hl=en

Chronos: Learning the Language of Time Series:

https://arxiv.org/abs/2403.07815

Monte Carlo methods in finance:

https://en.wikipedia.org/wiki/Monte_Carlo_methods_in_finance

Stochastic process

https://en.wikipedia.org/wiki/Stochastic_process

Black swan theory

https://en.wikipedia.org/wiki/Black_swan_theory

Black-Scholes Model:

https://www.investopedia.com/terms/b/blackscholes.asp#:~:text=The%20Black%2DScholes%20model%2C%20aka,free%20rate%2C%20and%20the%20volatility.

Latent Dirichlet allocation (LDA) for Topic Modeling:

https://en.wikipedia.org/wiki/Latent_Dirichlet_allocation

Backtesting: Definition, How It Works, and Downsides:

https://www.investopedia.com/terms/b/backtesting.asp

CUSIP Numbers:

https://www.investopedia.com/terms/c/cusipnumber.asp

Synthetic data:  

https://en.wikipedia.org/wiki/Synthetic_data

Model Collapse Demystified: 

https://arxiv.org/html/2402.07712v1

On cosmology, investment strategies and ergodicity:

https://www.linkedin.com/pulse/cosmology-investment-strategies-ergodicity-tasitsiomi-phd-aec0f

This episode was sponsored by:  

Ai+ Training https://aiplus.training/ 

Home to hundreds of hours of on-demand, self-paced AI training, ODSC interviews, free webinars, and certifications in in-demand skills like LLMs and Prompt Engineering

And created in partnership with ODSC https://odsc.com/ 

The Leading AI Training Conference, featuring expert-led, hands-on workshops, training sessions, and talks on cutting-edge AI topics and

Never miss an episode, subscribe now!