---
title: "Ernest P. Chan og Hamlet Jesse Medina Ruiz Generative AI for Trading and Asset Management"
brand: "Ernest P. Chan og Hamlet Jesse Medina Ruiz"
category: "Ukategoriseret"
price_min: 499
currency: DKK
vendor_count: 1
in_stock: true
url: https://pricetracker.dk/p/generative-ai-for-trading-and-asset-management-bded41
last_checked: 2026-07-19
---

# Ernest P. Chan og Hamlet Jesse Medina Ruiz Generative AI for Trading and Asset Management

Mærke: Ernest P. Chan og Hamlet Jesse Medina Ruiz · Kategori: Ukategoriseret

Sammenlign priser på Ernest P. Chan og Hamlet Jesse Medina Ruiz Generative AI for Trading and Asset Management fra 1 forhandler. Billigste pris nu: 499 kr hos Saxo DK. Se aktuelle priser og køb hos den billigste forhandler på https://pricetracker.dk/p/generative-ai-for-trading-and-asset-management-bded41

## Priser
- **Billigste pris nu:** 499 kr hos Saxo DK

## Forhandlere
| Forhandler | Pris | Levering |
|---|---|---|
| Saxo DK | 499 kr | — |

## Om produktet
Expert guide on using AI to supercharge traders' productivity, optimize portfolios, and suggest new trading strategies Generative AI for Trading and Asset Management is an essential guide to understand how generative AI has emerged as a transformative force in the realm of asset management, particularly in the context of trading, due to its ability to analyze vast datasets, identify intricate patterns, and suggest complex trading strategies. Practically, this book explains how to utilize various types of AI: unsupervised learning, supervised learning, reinforcement learning, and large language models to suggest new trading strategies, manage risks, optimize trading strategies and portfolios, and generally improve the productivity of algorithmic and discretionary traders alike. These techniques converge into an algorithm to trade on the Federal Reserve chair's press conferences in real time. Written by Hamlet Medina, chief data scientist Criteo, and Ernie Chan, founder of QTS Capital Management and Predictnow.ai, this book explores topics including: How large language models and other machine learning techniques can improve productivity of algorithmic and discretionary traders from ideation, signal generations, backtesting, risk management, to portfolio optimization The pros and cons of tree-based models vs neural networks as they relate to financial applications. How regularization techniques can enhance out of sample performance Comprehensive exploration of the main families of explicit and implicit generative models for modeling high-dimensional data, including their advantages and limitations in model representation and training, sampling quality and speed, and representation learning. Techniques for combining and utilizing generative models to address data scarcity and enhance data augmentation for training ML models in financial applications like market simulations, sentiment analysis, risk management, and more. Application of generative AI models for processing fundamental data to develop trading signals. Exploration of efficient methods for deploying large models into production, highlighting techniques and strategies to enhance inference efficiency, such as model pruning, quantization, and knowledge distillation. Using existing LLMs to translate Federal Reserve Chair's speeches to text and generate trading signals. Generative AI for Trading and Asset Management earns a well-deserved spot on the bookshelves of all asset managers seeking to harness the ever-changing landscape of AI technologies to navigate financial markets.

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Priserne er sidst kontrolleret 2026-07-19.