Artificial Intelligence for Financial Markets: The Polymodel Approach
暫譯: 金融市場的人工智慧：多模型方法

Barrau, Thomas, Douady, Raphael

Artificial Intelligence for Financial Markets: The Polymodel Approach
  • 出版商: Springer
  • 出版日期: 2023-06-02
  • 售價: $4,440
  • 貴賓價: 9.5 折 $4,218
  • 語言: 英文
  • 頁數: 172
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3030973212
  • ISBN-13: 9783030973216
  • 相關分類: 人工智慧

    • 海外代購書籍(需單獨結帳)

商品描述

This book introduces the novel artificial intelligence technique of polymodels and applies it to the prediction of stock returns. The idea of polymodels is to describe a system by its sensitivities to an environment, and to monitor it, imitating what a natural brain does spontaneously. In practice this involves running a collection of non-linear univariate models. This very powerful standalone technique has several advantages over traditional multivariate regressions. With its easy to interpret results, this method provides an ideal preliminary step towards the traditional neural network approach.
The first two chapters compare the technique with other regression alternatives and introduces an estimation method which regularizes a polynomial regression using cross-validation. The rest of the book applies these ideas to financial markets. Certain equity return components are predicted using polymodels in very different ways, and a genetic algorithm is described which combines these different predictions into a single portfolio, aiming to optimize the portfolio returns net of transaction costs. Addressed to investors at all levels of experience this book will also be of interest to both seasoned and non-seasoned statisticians.

商品描述(中文翻譯)

本書介紹了一種新穎的人工智慧技術——多模型（polymodels），並將其應用於股票回報的預測。多模型的概念是通過系統對環境的敏感度來描述系統，並模擬自然大腦自發進行監控。在實踐中，這涉及運行一組非線性單變量模型。這種非常強大的獨立技術相較於傳統的多變量回歸具有幾個優勢。由於其結果易於解釋，這種方法為傳統神經網絡方法提供了一個理想的初步步驟。

前兩章將該技術與其他回歸替代方案進行比較，並介紹了一種使用交叉驗證來正則化多項式回歸的估計方法。本書的其餘部分將這些思想應用於金融市場。某些股票回報組件使用多模型以非常不同的方式進行預測，並描述了一種遺傳算法，該算法將這些不同的預測結合成一個單一的投資組合，旨在優化扣除交易成本後的投資組合回報。本書面向各個經驗水平的投資者，對於經驗豐富和不太有經驗的統計學家也將具有吸引力。

作者簡介

Thomas Barrau is a Senior Quantitative Researcher working in the hedge fund AXAInvestment Managers Chorus Ltd. He is working on the development of an Equity MarketNeutral portfolio, from the creation of quantitative trading strategies to the portfolioconstruction. Prior to this, he worked at Societe Generale as banker and financial advisorto small businesses, and as CFO in an aerospace company. He holds a PhD in AppliedMathematics from Paris 1 Pantheon-Sorbonne University. Previously, he validated withhonors three different Masters of Science from Aix-Marseille School of Economics, Ca'Foscari University of Venice and Poitiers IAE.

Raphael Douady is a French mathematician and economist specializing in data science, financial mathematics and chaos theory at the University of Paris I-Panthéon-Sorbonne. He formerly held the Frey Chair of quantitative finance at Stony Brook University and was academic director of the French Laboratory of Excellence on Financial Regulation. He earned his PhD in Hamiltonian dynamics and has more than 25 years of experience in the financial industry. He has particular interest in researching portfolio risks, for which he has developed especially suited powerful nonlinear statistical and data science models, as well as macroeconomics and systemic risk. He founded fin tech firms Riskdata (risk management for the buyside) and Datacore (quantitative portfolio of ETFs) and is Chief Science Officer of NM Fin tech (numerical methods for fixed income trading in China).

作者簡介(中文翻譯)

托馬斯·巴羅（Thomas Barrau）是對沖基金AXA Investment Managers Chorus Ltd.的高級量化研究員。他負責開發股票市場中性投資組合，從量化交易策略的創建到投資組合的構建。在此之前，他曾在法國興業銀行（Societe Generale）擔任小型企業的銀行家和財務顧問，並在一家航空航天公司擔任首席財務官。他擁有巴黎第一大學（Paris 1 Pantheon-Sorbonne University）應用數學博士學位。此前，他以優異的成績獲得了來自艾克斯-馬賽經濟學院（Aix-Marseille School of Economics）、威尼斯卡福斯卡里大學（Ca'Foscari University of Venice）和普瓦捷IAE（Poitiers IAE）的三個不同的科學碩士學位。

拉斐爾·杜阿迪（Raphael Douady）是法國數學家和經濟學家，專注於數據科學、金融數學和混沌理論，任教於巴黎第一大學（University of Paris I-Panthéon-Sorbonne）。他曾擔任石溪大學（Stony Brook University）量化金融的弗雷講座教授，並擔任法國金融監管卓越實驗室的學術主任。他獲得了哈密頓動力學的博士學位，並在金融行業擁有超過25年的經驗。他特別關注投資組合風險的研究，為此他開發了特別適合的強大非線性統計和數據科學模型，以及宏觀經濟學和系統性風險。他創立了金融科技公司Riskdata（針對買方的風險管理）和Datacore（量化ETF投資組合），並擔任NM Fin tech（中國固定收益交易的數值方法）的首席科學官。

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