Interactive Data Visualizations
Our visualizations move from a broad look at market behavior to detailed comparisons that help answer our research questions. Since crypto is known for reacting strongly to major market events, we organized the figures to highlight how these events show up in price, volatility, correlation, and trading activity.
Across our analysis, we focus on several key events from the last five years:
These events are important because they help us understand when crypto moves with the stock market and when it moves independently.
We start with overall price performance to see how strongly each asset moves over time. Then we compare their volatility, which directly answers how much more unstable crypto is compared to SPY. The volume–price plot helps us spot moments of intense trading around major events. The correlation heatmap shows when crypto and SPY move together. The drivers network map connects the assets to the companies or platforms that influence their behavior, which helps explain why certain events have such large effects.
Together, these visualizations highlight how crypto reacts to major events, how it compares to the stock market, and how its behavior changes as the market shifts.
Normalized closing prices with interactive filtering and zoom
Figure 1: Normalized Market Performance Over Time – This figure shows five years of relative price performance for SPY and major cryptocurrencies.
Figure 1 shows how SPY and the five cryptocurrencies changed over time after normalizing all assets to the same starting point. SPY stays within a steady band throughout the five-year period, while all cryptocurrencies show much sharper climbs and declines. For example, BTC, ETH, and BNB rise quickly during the 2021 bull market, then drop sharply during the 2022 crypto crash that followed events like the Terra collapse in May 2022 (marked by the vertical dashed lines). XRP and LTC show large swings during the same periods, although at different magnitudes. Some of these movements line up with market-wide events, such as the downturn in early 2022, while other periods show crypto moving independently, especially during crypto-specific shocks. This figure helps answer our first two research questions by highlighting the stronger volatility in crypto and showing that the connection between crypto and the stock market varies depending on the period.
Force-directed network showing asset-driver relationships
Figure 2: Drivers Network Map – This figure maps each asset to the companies and platforms most associated with it.
Figure 2 links each cryptocurrency to the companies and organizations that influence it. BTC connects to drivers like MicroStrategy and Coinbase, reflecting how corporate adoption and exchange activity have shaped its price. XRP connects strongly to Ripple, which aligns with market reactions to Ripple's legal developments. Several assets share ties with Coinbase and Binance, which helps explain why exchange-related events, such as the 2022 Binance–FTX fallout, affected multiple coins at the same time. This figure supports the third research question by showing how shocks linked to specific companies or platforms can trigger large market movements.
30-day rolling volatility with interactive selection
Figure 3: Volatility Distribution Across Assets – This figure compares 30-day rolling volatility across SPY and five cryptocurrencies.
Figure 3 summarizes the 30-day rolling volatility for each asset. SPY has the lowest and tightest volatility values, centered near 0.01. All five cryptocurrencies show much wider and higher distributions. ETH, XRP, and LTC display the most frequent high-volatility periods, reflecting major swings during 2021 and throughout the 2022 crypto downturn. Even BTC and BNB, which appear more stable than the other coins, still sit well above SPY. This figure directly answers the first research question by making it clear that every cryptocurrency in the dataset is significantly more volatile than the S&P 500.
Trading volume vs. price with brush selection and dynamic regression
Figure 4: Volume–Price Relationship with Interactive Zoom and Filtering – This figure shows the relationship between trading volume and average price with interactive zoom and filtering.
Figure 4 compares trading volume to the average of daily high and low price for each asset. When focusing on BTC using the filtering tool, periods of high trading volume often match with surges in price, especially during the 2021 bull market when rising prices brought in heavy trading activity. Volume spikes also appear during major declines in mid-2022, when fear-driven selling increased activity across the market. These patterns relate to our third research question by showing how major events lead to both dramatic price movements and noticeable increases in trading volume.
Daily return correlations between all assets
Figure 5: Daily Return Correlation Heatmap – This figure shows correlations between daily returns for SPY and the five cryptocurrencies.
Figure 5 shows that cryptocurrencies have relatively strong correlations with one another, especially BTC, ETH, LTC, and BNB. Their correlations with SPY are moderate, which means crypto and the stock market only move together to a limited extent. XRP stands out with weaker correlations to both SPY and the other coins. This figure answers the second research question by showing that the connection between crypto and the stock market exists but is not stable or strong. It also supports the idea seen in Figure 1 that crypto sometimes moves with broader market trends, such as during early 2022, but often shows independent behavior during crypto-specific events.
Across all five visualizations, we were able to answer our research questions by examining how SPY and major cryptocurrencies behaved over the last five years. Our volatility comparison showed that every cryptocurrency in our dataset is much more volatile than the S&P 500. This supports what we saw in the normalized price chart, where assets like BTC, ETH, and BNB had large surges during the 2021 bull run and sharp declines during the 2022 crash, while SPY moved in a much tighter and steadier range.
We also found that the connection between crypto and the stock market shifts depending on the period. The correlation heatmap showed that cryptocurrencies move more closely with each other than with SPY. Some periods line up, such as early 2022 when both markets fell, but many movements are driven by crypto-specific events. The Terra collapse in May 2022 and the FTX collapse in November 2022 both triggered major drops across the crypto market. These patterns show how crypto volatility differs from traditional equity markets.
The volume and driver network visualizations help explain where these responses come from. Trading activity tends to increase during major swings, showing how sentiment and fear can accelerate price movement. The network map shows that many cryptocurrencies share ties to exchanges like Binance and Coinbase, which explains why events involving these companies often affect multiple coins at once.
Overall, we found that crypto is significantly more volatile, only loosely connected to the stock market, and highly sensitive to events within the crypto ecosystem. These findings help clarify how digital assets behave in comparison to traditional equities.
For future analysis, there are several ways this project could be expanded to build on what we learned. One direction is to extend the time window beyond the past five years to see whether the relationship between crypto and SPY becomes stronger as the crypto market matures. Another is to include additional assets, such as stablecoins or sector-specific equity ETFs, to see whether certain categories of assets track crypto more closely than the overall market. It would also be useful to run event-based analysis around specific dates, such as policy announcements or exchange failures, to quantify how quickly shocks spread across assets.
Together, these extensions would help create a deeper understanding of how crypto fits into the broader financial landscape and whether its behavior is becoming more integrated with traditional markets.