Prediction and analysis of gold prices

It aims to forecast the price of gold using time series analysis techniques. The main objective of this study is to predict the future prices of gold so that investors can make informed decisions about buying and selling gold. Inventory forecasting plays a crucial role in the financial success of a business, and forecasting the prices of gold can be particularly challenging due to its volatility and dependence on a variety of economic and geopolitical factors. We have utilized various time series models such as Exponential smoothing and Auto Regressive Integrated Moving Average (ARIMA) to analyse historical gold price data and generate forecasts. We have also conducted an exploratory data analysis (EDA) to identify any trends or patterns in the data and to assess the stationarity of the time series. Overall, the study demonstrates the usefulness of time series analysis techniques in predicting the price of gold and can be a valuable resource for investors and financial analysts.

Authors

Publication Details

Journal
International Journal of Statistics and Applied Mathematics
Published
2025-02-01
DOI
https://doi.org/10.22271/maths.2025.v10.i2b.1982
Primary Topic
Market Dynamics and Volatility
Type
article
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article

Prediction and analysis of gold prices

M Naresh, Anil Kumar, P Sriyshnavi
International Journal of Statistics and Applied Mathematics
Market Dynamics and Volatility
article

Prediction and analysis of gold prices

M Naresh, Anil Kumar, P Sriyshnavi
article en

Abstract

It aims to forecast the price of gold using time series analysis techniques. The main objective of this study is to predict the future prices of gold so that investors can make informed decisions about buying and selling gold. Inventory forecasting plays a crucial role in the financial success of a business, and forecasting the prices of gold can be particularly challenging due to its volatility and dependence on a variety of economic and geopolitical factors. We have utilized various time series models such as Exponential smoothing and Auto Regressive Integrated Moving Average (ARIMA) to analyse historical gold price data and generate forecasts. We have also conducted an exploratory data analysis (EDA) to identify any trends or patterns in the data and to assess the stationarity of the time series. Overall, the study demonstrates the usefulness of time series analysis techniques in predicting the price of gold and can be a valuable resource for investors and financial analysts.

International Journal of Statistics and Applied MathematicsVol. 10(2)
Decent work and economic growth
Openalex Percentile: Top 96%
Market Dynamics and Volatility
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Prediction and analysis of gold prices — M Naresh, Anil Kumar, et al. · International Journal of Statistics and Applied Mathematics (2025) | TGRS Research Map | TGRS