Big Data Science in Finance

Index

• 2-norm, 135
• 3-D simulation, complexity, 5

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• Abbott Laboratories (ABT), 58
  • in-sample RMSE, 59f
  • K-NN, out-of-sample performance, 60f
• Accelerations, 71
• Activation function, 20–21, 33
  • selection, 21–27
  • types, 21
• Activation levels, 19
  • addition, 40
• Activation parameter, 19
• Adaptive estimators, 83
• Adjacency matrix, 224, 266–267, 272–273
• Adjacency/similarity matrix, 268
• Aggregate industry-based portfolios, comparison, 156f–159f
• Algorithmic modeling culture, impact, 6
• American Depository Receipts (ADRs), Boston Stock Exchange trading activity, 124
• Analyst forecasts, market-wide news (impact), 95
• Analyst forecasts, stock-specific news
  • basis (development), generative SSL (usage), 96f, 99f, 101f
  • usage, out-of-sample prediction, 95f, 101f
• Analysts
  • average predictions, 101f
  • decision-making process, 82
  • forecasts (market news development), generative SSL (usage), 99f
  • human input requirement, 80
  • importance, 82
• Annualized mean returns, 291t, 305t
• Arbitrage Pricing Theory (APT), 142
• Articles. See News articles
• Artificial intelligence
  • data science by-product, 7–8
  • understanding, 4
• Assets
  • average values, 241t
  • returns, regression coefficient, 159
  • volatility, weight division, 146
• Australian Dollar-U.S. Dollar foreign exchange rate (AUD/EUR)
  • predictability, decision tree (usage), 63f
• Australian Dollar-U.S. Dollar foreign exchange rate (AUD/EUR), classification, 62–63
• Auto/Truck dealerships, industry eigenportfolios, 160f

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• Backpropagation, 26
• Back-propagation multi-layer ...