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Economic Complexity Limits Accuracy of Price Probability Predictions by Gaussian Distributions

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  • Victor Olkhov

Abstract

We discuss the economic reasons why the predictions of price and return statistical moments in the coming decades, in the best case, will be limited by their averages and volatilities. That limits the accuracy of the forecasts of price and return probabilities by Gaussian distributions. The economic origin of these restrictions lies in the fact that the predictions of the market-based n-th statistical moments of price and return for n=1,2,.., require the description of the economic variables of the n-th order that are determined by sums of the n-th degrees of values or volumes of market trades. The lack of existing models that describe the evolution of the economic variables determined by the sums of the 2nd degrees of market trades results in the fact that even predictions of the volatilities of price and return are very uncertain. One can ignore existing economic barriers that we highlight but cannot overcome or resolve them. The accuracy of predictions of price and return probabilities substantially determines the reliability of asset pricing models and portfolio theories. The restrictions on the accuracy of predictions of price and return statistical moments reduce the reliability and veracity of modern asset pricing and portfolio theories.

Suggested Citation

  • Victor Olkhov, 2023. "Economic Complexity Limits Accuracy of Price Probability Predictions by Gaussian Distributions," Papers 2309.02447, arXiv.org, revised Apr 2024.
  • Handle: RePEc:arx:papers:2309.02447
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    1. Snowberg, Erik & Wolfers, Justin & Zitzewitz, Eric, 2013. "Prediction Markets for Economic Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 657-687, Elsevier.
    2. Victor Olkhov, 2022. "Market-Based Asset Price Probability," Papers 2205.07256, arXiv.org, revised Feb 2024.
    3. Victor Olkhov, 2021. "Three Remarks On Asset Pricing," Papers 2105.13903, arXiv.org, revised Jan 2024.
    4. Victor Olkhov, 2017. "Econophysics of Business Cycles: Aggregate Economic Fluctuations, Mean Risks and Mean Square Risks," Papers 1709.00282, arXiv.org.
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    9. Olkhov, Victor, 2023. "The Market-Based Probability of Stock Returns," MPRA Paper 116234, University Library of Munich, Germany.
    10. Olkhov, Victor, 2021. "Theoretical Economics and the Second-Order Economic Theory. What is it?," MPRA Paper 110893, University Library of Munich, Germany.
    11. Victor Olkhov, 2022. "Why Economic Theories and Policies Fail? Unnoticed Variables and Overlooked Economics," Papers 2208.07839, arXiv.org.
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    Cited by:

    1. Victor Olkhov, 2023. "Theoretical Economics as Successive Approximations of Statistical Moments," Papers 2310.05971, arXiv.org, revised Apr 2024.
    2. Olkhov, Victor, 2023. "Economic Theory as Successive Approximations of Statistical Moments," MPRA Paper 118722, University Library of Munich, Germany.

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    More about this item

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • G1 - Financial Economics - - General Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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