Bitcoin Through the Years: A Data-Driven Analysis of Growth, Volatility, and Market Cycles (2014–2026)

By abhishek.verma75000 · June 10, 2026

A comprehensive analysis of Bitcoin's historical price and trading data reveals the asset's remarkable growth trajectory, extreme volatility, evolving…

The analysis identified the largest single-day percentage moves in the Close price. A bar chart has been generated showing the top gains and losses side by side, color-coded in green and red for easy comparison. The biggest single-day gain was an impressive +25.25% on December 7, 2017, when the Close price reached $17,899.70. The chart and accompanying tables provide a full breakdown of the top 5 gains and top 5 losses across the dataset.

Two charts and data tables were generated showing Bitcoin's year-end closing prices and year-over-year growth rates across each calendar year. The bar chart displays how Bitcoin's price has grown over time, while the line chart highlights the percentage growth (or decline) from one year to the next.

The yearly average trading volume has shown a dramatic upward trend from 2014 to 2026. A line chart has been generated showing this growth trajectory, along with supporting data tables. Overall, average volume increased massively — starting at just ~23.8 million in 2014 and reaching ~40.1 billion by 2026, representing an extraordinary multi-thousand-fold increase over the dataset period.

The analysis reveals that January shows the highest daily price volatility based on the High-Low spread as a percentage of the Low price. A bar chart has been generated ranking all months by their average daily volatility, making it easy to compare seasonal patterns.

Trading volume has a strong positive relationship with the size of daily price changes in Close (correlation: 0.63), but essentially no relationship with the direction of those changes. In other words, high-volume days tend to see bigger price swings — but you can't use volume alone to predict whether the price will go up or down.

Yes, Bitcoin's historical returns do show meaningful seasonal patterns across calendar months. The analysis produced two bar charts and supporting data tables breaking down average daily and monthly compounded returns by month. October stands out as the strongest month with an average daily return of 0.489%, while September is the weakest at -0.068%. The spread between the best and worst months is about 0.557 percentage points.

The analysis identified 204 outlier trading days out of 4,280 total days (about 4.8%) where Bitcoin's daily price range exceeded the 2 standard deviation threshold of 11.25%. The average daily range was 4.29% with a standard deviation of 3.48%. Two charts were generated: a time series showing all daily range percentages with outliers highlighted in red, and a bar chart ranking the top 15 most extreme outlier days.

The analysis successfully computed Bitcoin's 30-day and 200-day rolling moving averages and plotted them alongside the actual Close price. A time series chart was generated showing all three lines, with green upward triangles marking Golden Cross (bullish) events and red downward triangles marking Death Cross (bearish) events. In total, 10 Golden Crosses and 10 Death Crosses were detected across the dataset, indicating multiple major trend shifts in Bitcoin's price history.

The correlation analysis for Bitcoin's numeric columns has been completed, with a heatmap and a scatter plot generated to visualize the relationships. All price-related columns (Open, High, Low, Close, Adj Close) are almost perfectly correlated with each other (≈1.00), which makes sense since they all track the same asset's price. Volume shows a moderate positive correlation with Close price (0.704). When examining whether high-volume days produce larger price movements, the absolute daily price change ( Close - Open ) correlates with Volume at 0.628 — a moderately strong positive relationship — confirming that high-volume days do tend to produce larger price swings. However, the signed price change (Close - Open) has nearly zero correlation with Volume (-0.027), meaning volume doesn't predict the direction of the move, only its magnitude.

Comprehensive summary statistics were calculated for all Bitcoin price columns (Open, High, Low, Close) and Volume, with two visualizations and supporting data tables generated. The average closing price across the dataset is approximately $28,636, with a median of $11,564 — indicating a right-skewed distribution driven by Bitcoin's massive price surges. Prices range from a low of ~$172 to a high of ~$124,752. The average daily price range (High minus Low) is $1,168.58, reflecting substantial intraday volatility. The average daily price change (Close minus Open) is just $13.12, showing a very slight upward bias on a per-day basis. A grouped bar chart compares Mean, Median, Min, Max, 25th, and 75th percentile values across Open, High, Low, and Close columns. A histogram shows the distribution of daily price changes, centered near zero with wide tails.