Detection of Trends and Anomalies with MACD and RSI Market Indicators for Temperature and Precipitation


KAYA Y. Z.

Symmetry, cilt.17, sa.8, 2025 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 17 Sayı: 8
  • Basım Tarihi: 2025
  • Doi Numarası: 10.3390/sym17081268
  • Dergi Adı: Symmetry
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Communication Abstracts, INSPEC, Metadex, zbMATH, Directory of Open Access Journals, Civil Engineering Abstracts
  • Anahtar Kelimeler: anomaly detection, hydro-climatological trends, MACD, RSI, trend variability
  • Ankara Üniversitesi Adresli: Evet

Özet

The changes in climatological variables are a critical concern for climatologists, hydrologists, and water resources managers. In the face of global climate change, a more profound understanding of the recent changes in climatological conditions of a specific region is becoming increasingly urgent. To this end, hydro-climatological time series are being investigated in various ways, from traditional approaches to state-of-the-art techniques. This manuscript investigates the trend changes of surface temperature and total precipitation hydro-climatological parameters over a long period, using two of the most popular market price trend detection indicators, MACD and RSI. The RSI indicator evaluation methodology has been modified for the hydro-climatological time series. Minimum, maximum, mean surface temperatures, and precipitation parameters were analyzed. The length of the data sets is 122 years, starting in 1901 and ending in 2022. The application of these indicators to the mentioned parameters underscores their potential as powerful tools in the detection of climatological trends and trend variability over time, highlighting the need for proactive climate management strategies. The results revealed that the MACD and RSI indicators are effective tools not only for trend detection but also for determining climatological anomalies. These tools can be used to complement traditional statistical trend analysis. Moreover, their visual capabilities allow the methods to offer a more comprehensive understanding of climate management strategies.