Leading indicators in macroeconomics to better understand business cycles and predict commodity trading

Patrick Oberschmidleitner

Research output: ThesisMaster's Thesis

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The objective of this thesis was to assess, develop and implement a forecast model based on macroeconomic and technical indicators, to predict business cycle changes before their occurrence to better understand business cycles and predict commodity trading, with a specific focus on the short- and medium-term cycles of the commodities of oil, copper, and uranium. The theoretical foundation of business cycles for a better understanding of cyclic movements is covered. Business cycles are then analyzed and divided into long-, medium-, and short-term business cycles according to Kondratieff, Schumpeter, Juglar, Kuznets, and Kitchin. It highlights the importance of understanding and predicting these cycles and explains how they affect investors, policymakers, researchers, and corporations. An introductory insight into the commodity market and commodity trading process is provided and afterwards, economic cycles in commodity markets of oil, copper and uranium are evaluated. The thesis then provides an extensive overview of technical and economic indicators with a first evaluation of their leading ability. Additionally, influencing economic factors of commodities are identified and evaluated. The theoretical findings are then applied in a built model, which ranks each analyzed indicator on its predictive ability and evaluates which indicators correlate in a suitable way with each other to combine them and use them for price movement forecasting. Therefore, the indicators are applied to available price chart data from past events and reversal points to gain proof of applicability. The proposed model evaluates 18 different indicators of which 8 are technical and 10 are economic indicators. Via a correlation matrix the correlation between different indicators will be evaluated to identify highly correlating indicators with leading tendency. The outcome shows that for oil and copper a combination of RSI, CCI, and BB indicators show the most promising results. For uranium a combination of RSI, SO, and W%R indicators show the most promising result. At the end a price outlook for oil, copper, and uranium is carried out which concludes that energy prices are on an upward trend in the long term.
Translated title of the contributionFrühindikatoren in der Makroökonomie, um Konjunkturzyklen besser zu verstehen und den Rohstoffhandel vorherzusagen
Original languageEnglish
Awarding Institution
  • Montanuniversität
  • Siegmeth, Franz, Co-Supervisor (internal)
  • Posch, Wolfgang, Supervisor (internal)
Award date20 Oct 2023
Publication statusPublished - 2023

Bibliographical note

no embargo


  • Leading Indicators
  • Commodity Price Prediction
  • Commodities
  • Oil
  • Copper
  • Uranium
  • Business Cycles
  • Technical Indicators
  • Economic Indicators
  • Price Trend Reversal

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