Volatility, Tail Risk and Scaling Diagnostics in Coffee, Brent Oil and Gold Futures: Evidence from Processed Daily Series for Colombia

This article examines volatility, tail risk, temporal dependence, scaling behavior and simulation-based uncertainty in daily futures price series for coffee, Brent oil and gold during 2016-2025. The empirical object is defined as a set of provider-reported historical futures series obtained from Investing.com and transformed into logarithmic prices, logarithmic returns, absolute returns, squared returns, annualized 30-day rolling volatility, standardized returns and base-100 indices. In response to the methodological limitations inherent in secondary market-data aggregation, the study does not treat the downloaded series as exchange-certified individual contract histories, nor does it infer unobserved maturity-specific rollover rules. Instead, it positions the data as a transparent financial-risk input and evaluates the consequences of source status, contract identification and calendar irregularity for empirical interpretation. The results show non-Gaussian returns, heavy tails, heterogeneous volatility and stronger dependence in squared returns than in simple returns. Brent oil records the largest tail exposure, the highest kurtosis and the deepest maximum drawdown, while gold exhibits the most visible calendar irregularity. DFA exponents remain close to 0.5, indicating that strong long-memory claims are not supported without additional robustness tests. MF-DFA curves and Monte Carlo fan charts are therefore interpreted as exploratory risk-diagnostic tools rather than confirmatory evidence of multifractality or calibrated forecasts. The article contributes to risk and financial management by offering a cautious, reproducible and empirically delimited framework for comparing commodity futures relevant to Colombia.