Today’s financial world is developing very rapidly. New technologies emerge and transactions become more complex. However, despite the crucial impact that weather changes have on nearly every aspect of our lives, especially commodity markets, they remain underexploited. Ignoring the full potential of weather data in financial decision-making can result in significant losses for a trader or asset manager. Investors need to adapt to this new reality, think like climate scientists, and learn to analyze weather data while considering its market impact to stay competitive and progress.
Weather is a major driver of market volatility
At first glance, the connection between weather and commodity markets seems obvious. Crops depend on rain and temperature, and frost can damage crops. But it may be more challenging than it seems. For now, the climate is becoming more unpredictable. Previously, disasters such as sudden drought or frost were rare. But today, these events are more frequent, leading to wild price swings. Volatility in commodity markets has even exceeded that of cryptocurrencies. To give an obvious example, commodity prices have risen sharply since 2020 Increasesometimes within a short period of time. The reasons behind this surge are supply chain issues and an increase in the frequency of extreme weather events.
Why weather data alone is ineffective
Successful trading requires more than weather data. We must be able to interpret weather information competently. Knowing an area’s temperature or humidity levels is just a starting point. The real advantages come when you understand how these factors impact yield, supply chain, and final price.
A real-life example of benefiting from weather models on the market is Brazilian coffee market August 2024. But the problem is, these are just rumors. Weather models show that there is little risk of frost, as temperatures in Minas Gerais (a region of Brazil) rarely fall below 10°C at this time of year. Therefore, traders using this model profile can benefit from correct situation assessment. Some of them open short positions and profit when the market returns to previous levels.
Another example is a hurricane gulf coast. Using satellite data and the GFS model, we can assess the extent of damage to LNG production and transportation. From this, its impact on gas prices in Asia and Europe can also be calculated. Only based on this detailed assessment can correct investment decisions be made and fruitful results achieved in volatile markets.
Another perspective on risk management
Financiers cannot do this without the help of advanced models. These tools require data that matches weather conditions and economic factors. To do this, traders can use methods such as Monte Carlo simulation. This tool predicts the likelihood of climate events and their impact on prices. For example, the probability of a drought-induced decline in corn yields and its corresponding price fluctuations can also be calculated using a Monte Carlo model.
Scenario analysis is also useful in weather data interpretation. These allow the use of historical data and forecasts to assess the impact of various weather conditions on the market. This is particularly useful for analyzing long-term risks such as desertification or changes in climate cycles. Objective rules can also be a tool. Rigorous formalization of the relationship between weather variables and commodity prices makes forecasts more reliable and applicable to real-world situations.
An example where one of the above strategies could have worked and prevented the risk would be a real drought associated with: El Niño Phenomenon. This anomaly led to a significant reduction in Vietnam’s robusta coffee production in 2023.
Given the examples considered, it is clear that modern climate change requires a new approach to commodities investing. To adapt to the new reality of extremely high volatility, investors must think like climate scientists to adapt to growing market volatility. Complex models that incorporate meteorological and economic variables are also becoming traders’ best friends. Those who learn to extract value from this data will lead the markets of the future, transforming climate anomalies from a threat into a source of new opportunities.
