The world of finance is developing very rapidly today. New technologies are emerging, and commerce has become more complex. However, even though climate change has a negative impact on almost all aspects of our lives, and especially on commodity markets, it is still very little used. Ignoring the full power of weather data in financial decisions can cause traders or asset managers to incur huge losses. Investors need to adapt to this new reality, think like climate scientists, and learn to analyze climate data while calculating its market impact to stay competitive and thrive.
Weather as an important driver of market volatility
At first glance, the connection between weather and commodity markets seems obvious. Plants depend on rainfall and temperature, and frost can destroy plants. But this can be more challenging than it seems. Right now, the weather is unpredictable. In the past, calamities, such as sudden drought or frost, were rare. But today, these events are very common, which causes great price fluctuations. Volatility in commodity markets has surpassed even cryptocurrency volatility. As a clear example, since 2020, commodity prices have been very strong increasedsometimes in a very short time. The reasons for these attacks are supply chain problems and the increased frequency of extreme weather events.
Why weather data alone doesn't work
It takes more than weather data to trade successfully. We must be able to interpret weather information correctly. Knowing the temperature or humidity level in the area is just the beginning. The real benefit will come when you understand how this affects yields, supply chains, and final prices.
One real example of benefiting from market climate models is the situation with coffee market in Brazil in August 2024. What happened was that news of the coming frost forced coffee prices up by 8–9 percent. But the problem was that those were only rumours. Climate models indicated that the risk of frost was low, as temperatures in Minas Gerais (a Brazilian state) rarely drop below 10°C at that time of year. As a result, vendors with this model data benefited from the right situational assessment. Some of them opened short positions and made a profit when the market returned to previous levels.
Another example is storms over Gulf Coast. With the help of satellite data and GFS models, we can assess the extent of damage to LNG production and transportation. As a result, its impact on gas prices in Asia and Europe can also be calculated. Only based on this detailed analysis can the right investment decisions be made and yield fruitful results in volatile markets.
Risk management on the other hand
Financiers cannot do it without the help of advanced models. These tools need to match data on climate and economic factors. To do so, traders can, for example, use Monte Carlo simulations. This tool predicts the likelihood of weather events and their impact on prices. For example, the probability of a drought reducing corn yields and the associated price fluctuations can also be calculated using a Monte Carlo model.
Situational analysis also finds itself useful in interpreting weather data. This allows assessment of the impact of various weather conditions on markets using historical data and forecasts. This is particularly important in assessing long-term risks such as desertification or changes in climate cycles. Objective rules can also be a tool. A strong validation of the relationship between climate change and commodity prices makes forecasts more reliable and applicable to real-world conditions.
An example of a situation where one of the mentioned strategies would have been useful and prevented the risk is the actual connected drought El Nino happening. The anomaly caused a significant drop in Robusta coffee production in Vietnam in 2023.
Looking at the examples considered, it is clear that the current climate change requires a new way of investing in assets. To adapt to the new reality of higher volatility, investors must think like climate scientists to adapt to the volatility of emerging markets. Sophisticated models that include climate change and economics are also becoming traders' best friends. Those who learn to extract value from this data will lead the market in the future, transforming climate variability from threats to sources of new opportunities.
