Videos

Natural Language Processing (NLP) for Financial Services

Language is one of the great untapped resources of information. Today’s NLP field covers the full cycle of recognizing and understanding speech, processing natural language and generating text including automatic coding. NLP is everywhere – when you dictate a text message to Siri, ask Alexa for the weather, search on Google, use email services that filter out spam, check out spelling and grammar, and even autocomplete an entire message.

FDP & Kaplan Schweser Discuss the OnDemand Review Package

There's never been a more crucial time to stand out. The transformative effect of data science on the finance industry requires today's finance professionals to understand the application of big data, data mining, workflow automation and machine learning in investment decisions. The Financial Data Professional (FDP) is a global designation for investment professionals with data science skills.

FDP Charter Information Session (Q4-2022 exam) - APAC

There's never been a more crucial time to stand out. The transformative effect of data science on the finance industry requires today's finance professionals to understand the application of big data, data mining, workflow automation and machine learning in investment decisions. The Financial Data Professional (FDP) is a global designation for investment professionals with data science skills.

CAIA/AIMA Alternative Investment Boot Camp Session 3: Practitioner Career Panel

In this third web seminar, Rom Beneche, Director, AIMA, as he hosted a panel of industry professionals talking about their career paths and how they made it from their university days to the roles they hold today. Panelists covered a range of investment and non-investment roles in the alternatives industry.

If you have further questions, please reach out to the panelists from the session below:

Miquel Noguer Alonso Discusses Deep Reinforcement Learning for Asset Allocation in US Equities

This webinar demonstrated the application of reinforcement learning to create a financial model-free solution to the asset allocation problem, learning to solve the problem using time series and deep neural networks. Using a deep reinforcement model on US stocks and different deep learning architectures, including Long Short-Term Memory networks, Convolutional Neural Networks, and Recurrent Neural Networks. These architectures are compared with more traditional portfolio management approaches like mean-variance, minimum variance, risk parity, and equally weighted.