AWS for Industries
Author: Diego Colombatto
Diego Colombatto is a Principal Partner Solutions Architect at AWS. He brings more than 15 years of experience in designing and delivering Digital Transformation projects for enterprises. At AWS, Diego works with partners and customers advising how to leverage AWS technologies to translate business needs into solutions. IT architectures, algorithmic trading and cooking are some of his passions and he's always open to start a conversation on these topics.
How to set-up a fully automated data pipeline from AWS Data Exchange to Amazon FinSpace
In previous posts we’ve presented scenarios where Amazon FinSpace data analysis capabilities are used to address different use cases. For these analyses we used data available on AWS Data Exchange and on third-party data sources. Some examples of analysis are what-if scenarios of trading strategies, ESG portfolio optimization, and Analyzing petabytes of trade and quote […]
Automated and personalized asset portfolio optimization combining ESG and financial data on Amazon FinSpace
As detailed in our previous post on the topic, Environmental, Social, and Governance (ESG) data has become an indispensable supplemental data to assess a company’s risk and performance alongside traditional financial and alternative data. Institutional investors and asset managers are increasingly integrating ESG data into investment decisions, as responsible or sustainable investing moves from niche […]
Using ESG data from AWS Data Exchange in Amazon FinSpace to correlate news sentiment with social and governance industry scores
Introduction Environmental, social and governance (ESG) data has become an indispensable data set for financial institutions – used to assess a company’s risk and performance. ESG is broadly defined as a set of non-financial criteria or metrics that reflect how a company performs as a steward of nature (measuring carbon emissions, water usage, waste management […]
How to Run What-if Scenarios for Trading Strategies with Amazon FinSpace
Introduction In an earlier blog post, we described an architecture for backtesting machine learning-based trading strategies on AWS. One of the key components in this architecture is the data management and analytics component. Depending on the specific use case, there are various options to implement this. Many companies adopt solutions based on data lakes and […]
Algorithmic Trading on AWS with Amazon SageMaker and AWS Data Exchange
It is well known that the majority of stock transactions are automated (as described here and here), for example using applications or “robots” implementing a trading strategy. More recently, an emerging trend in the financial services industry is the movement of trading solutions, such as algorithmic trading solutions, to the cloud (as described here and […]