Videos

FDP Candidate Orientation Session Q4-2023

To support FDP Candidates and those considering the pursuit of the FDP Charter, we offered a brief, live webinar with our Curriculum and Operations team members to help prepare you for your exam experience. We discussed curriculum materials, Learning Objectives and provided a Practice Question review. We went over the exam structure and format, and available resources. In addition, we shared tips to prepare for exam day and what items are permitted during the exam. Formal remarks of the presentation lasted approximately 45 minutes, with 15 minutes of Q&A.

Leveraging Large Language Models (LLMs) on Domain Specific Knowledge

Large language models such as Bard and ChatGPT are rooted in natural language processing models developed decades earlier. How did we get here? This presentation took us through this fascinating journey. Dr. Hossein Kazemi moderated this presentation with Avi Patel and Raul Salles de Padua who took us on a brief journey through the evolution in NLU and NLP, from word embeddings to the current state of LLMs. We shared how to leverage adoption of LLMs, Generative AI capabilities and better understand the LLM-Ops lifecycle.

Revolutionizing the Financial Industry Through Python and Open Source

Didier Rodrigues Lopes, Founder & CEO of OpenBB discussed his journey from the pain points of doing investment research and how this led him to start building his own investment research platform in Python and raising $8.8M to democratize investment research through open source. He introduced the OpenBB Terminal - the open source investment research platform, and some of its capabilities. In addition, he presented the OpenBB SDK which allows programmatic access to the data from the OpenBB Terminal, allowing quants, analysts and developers to build custom tools and dashboards. Dr.

CAIA LatAm and CFA Society Colombia Joint Webcast Elevate your Career in Finance: Unleashing the Power of Professional Designations

CAIA LatAm & CFA Society Colombia Present: Elevate your Career in Finance - Unleashing the Power of Professional Designations

Listen in on this lively conversation about the importance and added value of pursuing professional designations. The panelists discussed employer's hiring preferences, trends, personal experiences, and career advice.

Unleashing the Power of Neural Networks: A Personal Journey into Creating and Harnessing a Neural Network for Trading Stocks

In a world where artificial intelligence is becoming complex and gaining influence, creating and using a machine learning model is not only a technical endeavor but also a personal journey of exploration, challenges, and growth. Tom Pickel shared his journey of building a neural network from the ground up. Tom shared his experience in creating a neural network using Python’s basic data science packages (Numpy and Pandas) for trying to predict movements in the stock market.

Large Language Models in Finance: Advances and Impact

Alik Sokolov and Kathryn Wilkens discussed the revolution of natural language processing in recent years, and how it applies to various areas of investment management. Our ability to work with unstructured text data, which is abundant in investment management, has undergone several evolutions from the late 2010's: from sequence-to-sequence models for machine translation, to the advent of transformers and transfer learning, to the recent breakthroughs achieved by Large Language Models popularized by Chat GPT.

CAIA Washington DC & CAIA LatAm Joint Webcast - Private Equity Secondaries & Co-Investments: Current Trends & Opportunities

The secondaries market has experienced significant growth and evolution over the past decade. The market for dedicated co-investment funds has similarly evolved, albeit it on a more limited scale. Both options present investors with significant flexibility and a complex array of considerations as they manage exposure to alternative assets. Watch our panel discussion as we explored current developments in each of these dynamic opportunities.

Can Large Language Models Produce More Accurate Analyst Forecasts?

Russ Goyenko, Associate Professor of Finance at McGill University discussed with Dr. Hossein Kazemi how large language models can, and soon they will produce more accurate analyst forecasts. Using textual information from a complete history of regular quarterly and annual (10-Q and 10-K) filings by U.S. corporations, we train machine learning algorithms and large language models, LLMs, to predict future earnings surprises. First, the length of MD&A section on its own is negatively associated with future earnings surprises and firm returns in the cross-section.

The Best of Both Worlds: Forecasting US Equity Market Returns Using a Hybrid Machine Learning-Time Series Approach

Predicting long-term equity market returns is of great importance for investors to strategically allocate their assets. Harshdeep Ahluwalia, Head of Asset Allocation, Americas for Vanguard Investment Strategy Group is one of the authors invited to discuss the exploration of machine learning methods to forecast US stock returns 10-years ahead and compare the results to the traditional Shiller regression-based forecasts more commonly used in the asset-management industry.