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REnsembling ARIMAX Model in Algorithmic Investment Strategies on Commodities Market

Author

Listed:
  • Paweł Jakubowski

    (University of Warsaw, Faculty of Economic Sciences)

  • Robert Ślepaczuk

    (University of Warsaw, Faculty of Economic Sciences, Quantitative Finance Research Group, Department of Quantitative Finance)

  • Franciszek Windorbski

    (University of Warsaw, Faculty of Management)

Abstract

This paper presents the results of investment strategies based on predictions from an ARIMA with exogenous variables (ARIMAX/ARIMAX-Garch) model, using the prices of selected commodities and companies from the DJIA index as explanatory variables. The explained variables are four Invesco ETF funds (DBE, DBA, DBP, DBB) corresponding to baskets of energy, agricultural, precious, and industrial metals. The models are optimized using the Walk-Forward technique, and the selection of exogenous variables is based on Granger causality tests. By analyzing the results, we conclude that ARIMAX/ARIMAX-Garch models are not useful tools for making buy or sell decisions for the selected commodity baskets. Out of the 80 estimated models, 44 outperform the Buy & Hold strategy, however, none achieved statistically significant results. Combining individual models into an investment portfolio reduced the risk without significantly reducing the profit, enabling us to consistently beat the benchmark. We also observe that using returns of commodities listed on stock exchanges is more effective than using stock returns. Sensitivity analysis shows instability in results with changes in the length of the training and testing windows. The highest annual return rate of 15.37% from 02.01.2008 to 01.12.2022 was characterized by an ARIMAX model with one commodity exogenous variable.

Suggested Citation

  • Paweł Jakubowski & Robert Ślepaczuk & Franciszek Windorbski, 2023. "REnsembling ARIMAX Model in Algorithmic Investment Strategies on Commodities Market," Working Papers 2023-20, Faculty of Economic Sciences, University of Warsaw.
    • Handle: RePEc:war:wpaper:2023-20
    as

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    File URL: https://www.wne.uw.edu.pl/download_file/3144/0
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    ARIMA(X); GARCH; ARIMA(X)/GARCH; Algorithmic Investment Strategies; Granger Causality; Investment Performance Evaluation; Trading Systems; Forecasting Models;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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