Dutch asset manager turns to decision trees for currency predictions
APG has improved prediction accuracy for G10 currency movements after adopting decision tree-based machine learning.
Decision trees are among the more popular applications of machine learning in the capital markets. Uses include finding patterns in request-for-quote (RFQ) datasets and predicting stock prices. Decision trees employ a tree-like model to map out decisions, or “nodes,” and the probabilities of consequences branching out from these nodes, to work through a database and calculate outputs.
Amsterdam-based pension fund APG Asset Management, with $690 billion in assets under management, is using
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@waterstechnology.com or view our subscription options here: https://subscriptions.waterstechnology.com/subscribe
You are currently unable to print this content. Please contact info@waterstechnology.com to find out more.
You are currently unable to copy this content. Please contact info@waterstechnology.com to find out more.
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@waterstechnology.com
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@waterstechnology.com
More on Data
Repricing risk in a global rate reset
Firms are reallocating risk exposure, evolving forecasting models and leveraging deep macroeconomic data to uncover patterns and challenge assumptions.
Unleashing the power of data and technology in an age of digital transformation
How Bloomberg is helping its Apac clients’ digital transformations across system interoperability, decision-making and automation
Mastering regulatory compliance through reliable data access
Firms continue to struggle with regulatory updates and sourcing accurate data
Real-time market data—Preventing vendor lock-in
The future of market data distribution, leveraging modern technologies, migration paths and outsourcing non-value-added data workflows.
A fireside chat with SmartStream’s Akber Jaffer
A fireside chat with SmartStream’s chief executive to discuss his first 15 months at the helm of the business and SmartStream Air 9.0—the firm’s new AI-driven reconciliations platform.
A fireside chat with FactSet’s David Mellars
FactSet’s private markets data strategy, the relationship between risk and performance on the buy side and fixed income track record.
Client success story: Münchener Hypothekenbank—NeoXam DataHub
Münchener Hypothekenbank (MünchenerHyp) has been faced with increasing and tightening regulatory parameters and obligations within its business activity, demanding a strategic focus and planning to ensure that information to meet these requirements is…
Portfolio trading vs RFQ: Understanding transaction costs in US investment-grade bonds
The MarketAxess research team explores how such factors as order size, liquidity profiles and associated costs determine whether a portfolio trade or an RFQ list trade is the optimal choice.
