Machine learning and causal analyses for modeling financial and economic data View Full Text


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Article Info

DATE

2018-12

AUTHORS

Lei Xu

ABSTRACT

Instead of aiming at a systematic survey, we consider further developments on several typical linear models and their mixture extensions for prediction modeling, portfolio management and market analyses. The focus is put on outlining the studies by the author’s research group, featured by (a) extensions of AR, ARCH and GARCH models into finite mixture or mixture-of-experts; (b) improvements of Sharpe ratio by maximizing the expected return and the upside volatility while minimizing the downside risk, with the help of a priori aided diversification; (c) developments of arbitrage pricing theory (APT) into temporal factor analysis (TFA)-based temporal APT, macroeconomics-modulated temporal APT and a general formulation for market modeling, together with applications to temporal prediction and dynamic portfolio management; (d) Bayesian Ying–Yang (BYY) harmony learning is adopted to implement these developments, featured with automatic model selection. After a brief introduction on BYY harmony learning, gradient-based algorithms and EM-like algorithms are provided for learning alternative mixture-of-experts-based AR, ARCH and GARCH models; and (e) path analysis for linear causal analyses is briefly reviewed, a recent development on ρ-diagram is refined for cofounder discovery, and a causal potential theory is proposed. Also, further discussions are made on structural equation modeling and its relations to modulated TFA-APT and nGCH-driven M-TFA-O. More... »

PAGES

11

References to SciGraph publications

  • 2002. Stock Price and Index Forecasting by Arbitrage Pricing Theory-Based Gaussian TFA Learning in INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING — IDEAL 2002
  • 2011-06. Radar HRRP statistical recognition with temporal factor analysis by automatic Bayesian Ying-Yang harmony learning in FRONTIERS OF ELECTRICAL AND ELECTRONIC ENGINEERING IN CHINA
  • 2010-09. Bayesian Ying-Yang system, best harmony learning, and five action circling in FRONTIERS OF ELECTRICAL AND ELECTRONIC ENGINEERING IN CHINA
  • 2011-06. An investigation of several typical model selection criteria for detecting the number of signals in FRONTIERS OF ELECTRICAL AND ELECTRONIC ENGINEERING IN CHINA
  • 2011. Rubin Causal Model in INTERNATIONAL ENCYCLOPEDIA OF STATISTICAL SCIENCE
  • 2012-03. On essential topics of BYY harmony learning: Current status, challenging issues, and gene analysis applications in FRONTIERS OF ELECTRICAL AND ELECTRONIC ENGINEERING
  • 2018-12. Deep bidirectional intelligence: AlphaZero, deep IA-search, deep IA-infer, and TPC causal learning in APPLIED INFORMATICS
  • Journal

    TITLE

    Applied Informatics

    ISSUE

    1

    VOLUME

    5

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s40535-018-0058-5

    DOI

    http://dx.doi.org/10.1186/s40535-018-0058-5

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1110958152


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