Abstract
Complex financial markets, influenced by complex and interconnected factors, require proper decision making. Gold derivatives, as an increasingly popular trading instrument, have experienced significant growth. However, with high profit potential also comes significant risk. Market analysis, including technical analysis and leveraging seasonality, can be an important tool in reducing risk and making smart decisions. This research aims to assess the effectiveness of the Geometric Brownian Motion (GBM) model in predicting Gold Derivative prices through the application of the Mean Absolute Percentage Error (MAPE) test.In this study, the Brownian Motion Geometric Method and Simple Moving Average are combined to analyze the seasonality of gold derivative prices to provide a view of price movement patterns. The results showed that the Brownian Motion Geometric Method was effective in predicting the price of gold derivatives, with a low error rate. In addition, seasonality analysis reveals monthly price movement patterns that can be a guide for traders and investors. This research provides valuable insights for decision making in gold derivatives trading in dynamic and complex financial markets.
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