AWS Hedge Fund Innovation Day

Keywords

AWS Hong Kong for Capital Markets
www.linkedin.com/groups/14601617/
Thursday, 3 July 2025
AWS office, 20/F, Tower 535, 535 Jaffe Road, Causeway Bay

● Alpha Factor Zoo

● Alternative Backtesting Strategies

● Quantitative Investment Research Framework

● Portfolio Risk Management

● Compliance with Trading Regulations

Transcript

Hello everyone, welcome to the podcast. Today we are talking about a very interesting event we attended: Hedge Fund Innovation Day. The Amazon Web Services capital markets team brought some distinctive value to the room.

It sounded promising, so we wanted to share the highlights with you.

First: what is Hedge Fund Innovation Day, and how was it organized?

It was held on 3 July 2025 at the AWS office in Causeway Bay, Hong Kong, on Jaffe Road. The AWS capital markets team taught and shared five core topics: the Alpha Factor Zoo, alternative backtesting strategies, a quantitative investment research framework, plus portfolio risk management and trading-regulation compliance. The agenda was rich.

As a participant, what stood out?

I work in macro hedge trading. In that work you constantly talk with strategy leads, risk, and compliance. That kind of cross-team conversation strengthens how you operate at work and how you run cross-department projects. The event was useful in exactly that way.

Among the five core value points, which ones stayed with you, and how were they implemented technically?

The first was the Alpha Factor Zoo. It can surface signals from alternative assets. Using AWS Batch, Lambda, and S3, it helps improve the portfolio’s return-to-risk ratio.

The second was alternative backtesting strategies. They support multi-market, multi-asset backtests. That helps you avoid crowding risk in mid- and small-cap names. This is implemented with AWS Step Functions.

The other three?

The third was the quantitative investment research framework. Using EC2, ClickHouse, and Streamlit, it builds multidimensional reports and can improve trade-execution efficiency.

The fourth was portfolio risk management. It uses an AI/ML model to run time-series analysis on trading data, so you can control market tail risk more precisely. This is implemented with AWS EMR Studio.

The last was regulatory compliance. It uses Amazon Bedrock Nova to pull SEC regulatory documents and uses a large language model to help check whether any behavior may be non-compliant.

That is a lot of ground: from the Alpha Factor Zoo to regulatory compliance. Each point makes quantitative investing more interesting, and it also shows the technical strength of AWS in this space.

That is the full episode. Thanks for listening. See you next time. Bye.