The correlation between NYC precipitation and the Dow Jones Industrial Average (DJIA) in the charts you provided is intriguing, but it’s important to approach such correlations with caution. Here are some possible explanations or considerations for this observed relationship:

1. Psychological Impact on Markets

• Weather and Sentiment: Weather can influence human behavior and mood, which in turn can affect economic activity and investor sentiment. For example, extended periods of bad weather, such as a drought, might negatively affect consumer spending or productivity, leading to market declines.
• Seasonal Affective Disorder (SAD): Wetter or gloomier weather can contribute to seasonal affective disorder, which might have subtle effects on the decisions of market participants.

2. Economic Impact of Weather

• Agricultural Production: Extreme weather conditions like droughts or excessive rain can directly impact agricultural production, which in turn affects the broader economy, particularly in sectors dependent on agriculture. This could influence market performance, especially in economies or time periods where agriculture played a significant role.
• Energy Costs: Weather can affect energy demand and prices, particularly for heating or cooling. For instance, a drought might lead to higher energy prices due to increased demand for cooling, impacting consumer spending and business costs, and thus the stock market.

3. Infrastructure and Economic Disruptions

• Infrastructure Stress: Significant deviations from normal weather patterns can strain infrastructure, leading to economic disruptions. Floods or droughts can damage infrastructure, leading to increased costs and potential market downturns.
• Economic Productivity: Weather-related disruptions can affect productivity, as extreme weather can halt construction projects, reduce outdoor economic activities, and lead to increased insurance claims, all of which can negatively impact the stock market.

4. Coincidence and Statistical Artefact

• Spurious Correlation: It’s possible that the correlation observed between NYC precipitation and the DJIA is coincidental, especially when looking at long-term data across different periods. Sometimes, patterns emerge simply due to the nature of the data sets and timeframes chosen, without any real underlying causal relationship.
• Overfitting: In the realm of financial analysis, there is a risk of overfitting, where analysts find patterns in data that may not be meaningful. The correlation between rainfall and the DJIA might be an example of such a pattern that lacks a strong causal mechanism.

5. Historical Economic Context

• Major Historical Events: The periods covered in the charts include significant historical events (e.g., the Great Depression in the second chart, the 2008 financial crisis in the first chart). These events had profound effects on both the economy and the stock market. The correlation with rainfall could reflect broader economic stresses and societal conditions during these times, rather than a direct causal relationship.

Conclusion:

While these explanations provide some possible reasons for the correlation, it is crucial to be skeptical of attributing causality. The observed correlation might not imply direct causation but could instead reflect underlying economic or psychological factors influenced by weather. It's also possible that the relationship is coincidental, with other, more powerful variables driving market behavior during these periods. Further research and analysis would be required to establish any robust causal links.