Investment Analytics in the Dawn of Artificial Intelligence

A class of highly mathematical algorithms works with three-dimensional (3D) data known as graphs. Our research challenge focuses on applying these algorithms to solve more complex problems with financial data, which tend to be in higher dimensions (easily over 100), based on probability distributions, with time subscripts and jumps. The 3D research analogy is to train a navigation algorithm when the way-finding coordinates and obstacles such as buildings change dynamically and are expressed in higher dimensions with jumps.

Our short title 'ia≠ai' symbolizes how investment analytics is not a simplistic reapplication of artificial intelligence (AI) techniques proven in engineering. This book presents best-of-class sophisticated techniques available today to solve high dimensional problems with properties that go deeper than what is required to solve customary problems in engineering today.

Dr Bernard Lee is the Founder and CEO of HedgeSPA, which stands for Sophisticated Predictive Analytics for Hedge Funds and Institutions. Previously, he was a managing director in the Portfolio Management Group of BlackRock in New York City as well as a finance professor who has taught and guest-lectured at a number of top universities globally.
Contents: IntroductionNavigation and VocabularyConstruct Portfolios:Understanding RiskObjective Functions in Portfolio ConstructionRisk and Return AttributionPortfolio-Level Factor AnalysisA Hedging Use CaseSelect Assets:Alpha Selection Using FactorsStandard Derivative InstrumentsDecide and Execute:RebalancingForward Scenarios and Historical SimulationsCombining Upside with Black Swan ScenariosDeliver Reports:Customary Back Office ReportingAdditional ReportingCompliance AnalysisData Integrity ValidationDeploy:Deployment Best PracticesImplications of a Post-IA/AI Society
Readership: Professionals looking for a step-by-step 'cookbook' on algorithms to build and deploy their own investment analytics processes; C-level executives at leading investment firms to technologists doing hands-on deployments. Financial Technology;Investment Analytics;Artificial Intelligence;Asset Managers;Investment Management;Asset Liability Management;Asset Selection;Multi-asset Investing;Risk Management;Market Risk;Extreme Risk;Tail Risk;Scenarios;Historical Simulation;Black Swan;Compliance;Maximizing Returns;Retirement;Wealth Management;Investment Advisor;Investment Company;Investment Objective;Long-Term Investment;Portfolio;Portfolio Construction;Rebalancing;Reinvestment;Relative Risk and Potential Return;Investment Horizons;Valuation;Total Return;Indexing;Alpha;Beta;Asset Allocation;Diversification;Investment Reporting;Performance Reporting;Performance Attribution;Risk Attribution0Key Features:This book is designed as practical teaching materials to go with a master's level or professional education course, with one on-line version is already accessibleRigorous use cases that were accepted as stand-alone papers at some of the best recognized academic conferences such as the Joint Statistical MeetingsStep-by-step algorithms with the clarity required for customary compliance clearanceQuick and logical navigation to relevant topics for those in different asset management functions without assuming logical chapter-by-chapter progressSupplementary teaching aids will be made available to instructors