In this report, we take a closer look at Bitcoin’s price fluctuations by examining the detailed blockchain data that underpins market behavior. Using reliable on-chain metrics collected from 2021 to 2025, we explain how routine activities—such as miner operations, liquidity movements, and investor decisions—affect Bitcoin’s market performance.

We explore various market components, including institutional investment trends, exchange activities, user engagement, and holding patterns, to show how different factors contribute to market volatility during bullish and bearish phases.

These insights are useful for identifying early signs of market shifts and understanding the broader context of price movements. Whether you are a trader looking for a tactical edge or an institution seeking a deeper understanding of market dynamics, the findings presented here provide a practical, data-based perspective.

Review of Selected On-Chain Metrics

Building on our introduction, this section breaks down the core on-chain metrics—all available directly from Amberdata—that reveal Bitcoin’s inner workings. These metrics provide clear signals about market behavior and are grouped into five key categories:

Institutional Metrics

• Market Capitalization: The total value of all Bitcoins in circulation, indicating the overall market size.
• Realized Capitalization: Adjusts market cap to reflect only Bitcoins that have moved, offering a realistic view of value.
• Realized Price: The average price at which Bitcoins were last transacted, serving as a cost basis for investors.
• Net Unrealized Profit/Loss (NUPL): Shows whether holders are sitting on gains or losses, hinting at market sentiment.
• Market Value to Realized Value (MVRV): Compares current market value to the realized value, helping to spot over or undervaluation.

These metrics help us understand institutional perspectives and how large-scale investors might be influencing market trends.

Liquidity & Exchange Metrics

• Daily Total Exchange Volume: Reflects the amount of trading activity across major exchanges.
• Bitcoin ETF Daily Flow: Tracks the funds entering or leaving Bitcoin ETFs.
• Net Flows: Measures the movement of Bitcoin between different liquidity categories, highlighting supply shifts.
• Liquid Balances: Represents the portion of BTC that is actively traded and has been transacted recently (for example, within the past 30 days).
• Illiquid Balances: Represents coins that remain dormant and are rarely moved (typically not transacted for 90 days or more), reflecting long-term storage and investor retention.

Monitoring liquidity and exchange flows gives insight into market participation and price dynamics.

Miner Behavior Metrics

• Miner Supply Spent: The amount of Bitcoin sold by miners, providing clues about their operational choices.
• Miner Outflows & 365-Day Moving Average: Track how much Bitcoin is leaving miner wallets over time.
• Capitulation Index: Indicates periods when miners might be forced to sell due to low revenues.
• Miner Position Index: Shows whether miners are holding or offloading Bitcoin.
• Issuance: The daily count of newly mined Bitcoin.
• Puell Multiple: Compares current mining revenue against historical norms to assess profitability.

These indicators reveal how miner activity can impact market trends and overall stability.

User Activity & Address Metrics

• Total Addresses: Counts unique Bitcoin addresses, signaling network growth.
• New/Active Addresses and Transaction Counts: Monitor the creation and use of addresses to gauge engagement.
• Passive Addresses & Moving Averages: Indicate longer-term trends in user behavior.

User activity metrics shed light on retail participation and overall network health.

HODL & UTXO Metrics

• HODL Liveliness and HODL Coins: Track movement and holdings of long-term investors.
• HODL Net Position Change Daily: Shows day-to-day shifts among dedicated holders.
• UTXO Age Bands: Classify Bitcoin based on inactivity periods, helping to distinguish short-term trading from long-term holding.

These metrics help identify the strength and commitment of long-term holders, which can influence price stability.

Market Cycle Segmentation: Bear and Bull Phases

Our analysis draws on comprehensive on-chain data sourced from Amberdata’s AmberLens API, spanning January 1, 2021 through January 1, 2025. This dataset provides a detailed, real-world snapshot of Bitcoin’s blockchain activity, capturing transactions, miner operations, liquidity movements, and user behavior. Understanding this granular data is critical for understanding the complex factors that drive market volatility.

We segment the data into two distinct market states — bull and bear — each exhibiting unique volatility characteristics that tell different stories.

Bull Market (October 1, 2023 – December 16, 2024)

The bull phase witnessed Bitcoin’s price surging from roughly $26.97K to around $106.35K—a rise of approximately 294%. The period initially featured low volatility, reflective of quiet accumulation, but as momentum built, volatility began to increase. 

• Absolute Daily Volatility averaged 1.91%, with a maximum of 11.39%. The skewness of 1.69 and kurtosis of 3.55 reveal that while most days experienced moderate changes, there were intermittent sharp spikes that pushed the distribution’s tail to the right. 
• The 7-Day Rolling Volatility averaged 2.43% with a maximum of 5.85%, and its skewness of 1.07 with a kurtosis of 1.74 indicate moderate yet occasional short-term surges.
• Lastly, the 30-Day Rolling Volatility averaged 2.52% and peaked at 4.21%, with a low skewness (0.44) and kurtosis (0.38). This smoother distribution highlights a more stable long-term trend, punctuated by periodic corrections rather than abrupt shocks.

Bear Market (November 8, 2021 – November 21, 2022)

Conversely, during the bear phase, Bitcoin’s price plunged from approximately $67.54K to about $15.78K—a decline of nearly 76%. This dramatic downturn was accompanied by heightened volatility, driven by rapid sell-offs and pervasive market uncertainty. 

• The Absolute Daily Volatility averaged 2.42% and peaked at 17.01%, with a skewness of 2.28 and a kurtosis of 6.89. These figures indicate a heavy-tailed distribution, where extreme daily price swings occurred frequently. 
• The 7-Day Rolling Volatility averaged 3.20% and reached a maximum of 8.61%. Its skewness of 0.99 and kurtosis of 1.24 suggest that although short-term fluctuations were substantial, they were somewhat more evenly distributed than the daily extremes. 
• The 30-Day Rolling Volatility averaged 3.36%, with a top value of 5.04%. The near-zero skewness (-0.07) and slightly negative kurtosis (-0.24) in this measure imply a flatter distribution, indicating that high volatility persisted consistently throughout the month without isolated, extreme events.

Correlation Analysis

Institutional Metrics

Bull Phase (October 2023 – December 2024)

During the bull phase, the market was generally optimistic and growing. NUPL and MVRV, which measure unrealized profits, showed slight positive correlations with daily returns (+0.23 for NUPL and +0.22 for MVRV). This means that as these profits increased, so did the price swings, though only moderately. 

In addition, Market Cap had a positive correlation of +0.24 with daily returns, as expected, suggesting that rising overall valuations went hand-in-hand with increased trading activity and price movements. Realized Cap, which reflects the actual gains realized by investors, had a weak positive correlation of +0.16 with daily returns. 

Overall, these figures suggest that during bull markets, investor optimism and growing asset values contribute to price movements, while occasional profit-taking causes moderate fluctuations. The positive relationships indicate that as more capital flows into the market, prices tend to move more dynamically, yet within a controlled upward trend.

Bear Phase (November 2021 – November 2022)

In contrast, the bear phase was marked by increasing market stress and declining investor confidence. Here, NUPL and MVRV flipped to negative correlations with daily returns (-0.28 for NUPL and -0.24 for MVRV), showing that as unrealized profits fell, the market experienced larger price swings, likely due to forced selling and panic. 

Market Cap also turned negative (-0.25), meaning that as overall market value dropped, price fluctuations became more severe. Realized Cap showed an even stronger negative relationship, at -0.27 with daily returns, and was more pronounced in longer-term measures (-0.21 for 7-day and -0.18 for 30-day volatility). 

These numbers imply that during downturns, losses and capital outflows drive greater instability. The metrics suggest that as investors rush to sell, the market becomes more volatile and unpredictable (unlike in a bull market), reflecting the harsh conditions of a bear market.

Liquidity and Exchange Metrics

Bull Phase (October 2023 – December 2024)

In bullish markets, liquidity and exchange metrics indicate that long-term holdings play a notable role while short-term exchange activity is less influential. Net flows of illiquid BTC show a moderate positive correlation of +0.21 with absolute daily returns, suggesting that movements of long-term holdings contribute to price swings during uptrends. 

Conversely, daily total exchange volume in bull markets has almost no significant correlation with price movements, implying that trading activity on exchanges does not drive volatility when market sentiment is positive. Moreover, net flows of highly liquid BTC exhibit nearly no correlation with 7-day volatility, meaning that shifts in the supply of highly liquid Bitcoin have minimal impact on short-term price fluctuations in a rising market. 

Overall, these metrics point to a scenario where long-term investors and their BTC holdings have a more noticeable effect on volatility during bull phases, while high trading volumes on exchanges are absorbed by the overall upward trend.

Bear Phase (November 2021 – November 2022)

In bearish markets, liquidity and exchange metrics highlight a stronger impact of trading activities on price volatility. Net flows of illiquid BTC in the bear phase correlate moderately with absolute daily returns at +0.15, indicating that movements of long-term holdings have less influence when the market is declining. 

However, daily total exchange volume during downturns exhibits a strong correlation (+0.39) with absolute daily returns and a moderate correlation (+0.23) with 7-day volatility, reflecting that heightened trading activity on exchanges drives larger price swings and short-term fluctuations in stressed market conditions. 

Furthermore, net flows of liquid BTC show a moderate positive correlation of +0.25 with 30-day volatility, suggesting that increased availability of liquid Bitcoin, possibly due to selling pressure, contributes to sustained market instability. Additionally, net flows of highly liquid BTC correlate with 7-day volatility at +0.13, underscoring that short-term supply movements play a role in amplifying price volatility during bearish phases.

User Activity and Address Metrics

Bull Phase (October 2023 – December 2024)

During bullish periods, user activity metrics indicate a relatively stable environment where shifts in engagement have a moderate effect on price movements. New addresses, active addresses, and new outputs show lower correlations with absolute daily returns than they do in bearish conditions. 

The 365-day new address moving average, with a correlation of -0.12 with 30-day volatility, suggests that new users entering during uptrends are likely genuine long-term investors, contributing to smoother market dynamics. Additionally, the 30-day new address moving average exhibits a mild positive correlation (approximately +0.12) with both 7-day and 30-day volatility, implying that occasional spikes in user activity can trigger short-term fluctuations. 

Finally, passive addresses display a small negative correlation (-0.12) with 30-day volatility, indicating that long-term holders tend to remain inactive, which helps to dampen volatility during sustained bull markets.

Bear Phase (November 2021 – November 2022)

In bearish markets, user activity and address metrics play a more pronounced role in driving volatility. New addresses, active addresses, and new outputs show higher correlations with absolute daily returns—around +0.20—suggesting that changes in user engagement strongly influence price swings during market downturns. 

The 365-day new address moving average demonstrates a small positive correlation (+0.19) with 30-day volatility, indicating that new users during these periods may be speculating on a rebound or engaging in panic selling, thereby contributing to increased volatility. Moreover, the 30-day new address moving average maintains mild correlations of roughly +0.12 with both 7-day and 30-day volatility, reinforcing the link between bursts in new user activity and short-term price fluctuations. 

Passive addresses exhibit a very weak negative correlation (-0.04) with 30-day volatility, implying that during bear markets, even long-term holders are more likely to move funds, which adds to market instability.

Miner Metrics

Bull Phase (October 2023 – December 2024)

During the bull phase, miner behavior metrics reveal that profitability and volatility are modestly linked. The Puell Multiple shows a moderate positive correlation with 7-day volatility (+0.18) and 30-day volatility (+0.22), suggesting that when miners earn more, there is a slight increase in volatility. This may be due to higher prices driving profitable conditions that encourage miners to sell a portion of their holdings. 

However, miner outflows do not show a significant correlation with absolute daily returns, indicating that strong buying pressure during uptrends helps absorb miner sell-offs, thereby limiting their impact on daily price movements.

Bear Phase (November 2021 – November 2022)

In the bear phase, miner behavior displays contrasting trends compared to the bull market. The Puell Multiple turns negatively correlated with 30-day volatility (-0.15), implying that higher miner revenue during downtrends may help stabilize prices. 

Miner outflows, however, exhibit a weak positive correlation (+0.12) with absolute daily returns, suggesting that miner sell-offs contribute to sharper daily price swings. This effect is amplified by lower liquidity and heightened market stress, where rapid selling can trigger larger fluctuations. 

Overall, these metrics indicate that in bearish conditions, miner actions play a more disruptive role in driving volatility.

HODL and UTXO Metrics

Bull Phase (October 2023 – December 2024)

In the bull phase, UTXO metrics reveal that medium-term holdings significantly influence market volatility. UTXO values held between one week and one month show a strong correlation (+0.58) with 30-day volatility, linking these holdings to medium-term price fluctuations. UTXO held for under one day have a moderate correlation (+0.30) with absolute daily returns but minimal impact on 7-day and 30-day volatility (+0.11 each). This indicates that while short-term trading affects daily movements, the overall uptrend is largely driven by swing trading and medium-term investor actions, with robust buying demand mitigating rapid price changes.

Bear Phase (November 2021 – November 2022)

In the bear phase, short-term UTXO metrics play a critical role in driving volatility. The UTXO category representing holdings between one day and one week shows a strong correlation (+0.44) with both 7-day and 30-day volatility, indicating that rapid movements are closely linked to market instability. Additionally, UTXO held for under one day correlates with absolute daily returns at +0.37 and exhibits higher correlations with 7-day (+0.33) and 30-day volatility (+0.27) than in the bull phase. These statistics suggest that in downtrends, panic selling and liquidations amplify volatility, as speculative short-term trading significantly impacts price movements.

UTXO Age Distribution Analysis

Bull Phase (October 2023 – December 2024)

During the bull phase, the UTXO age distribution shows strong long-term commitment and active short-term trading. The 8-year-plus UTXO band consistently dominates, indicating that a significant portion of Bitcoin remains held by long-term investors, reflecting solid conviction amid rising prices. 

Meanwhile, short-term UTXOs (less than 6 months) exhibit increased activity, suggesting that traders are engaging in profit-taking during uptrends. The 1-month to 6-month UTXO bands experience the most fluctuation, likely due to mid-term holders adjusting their positions as the market rallies. When high volatility occurs, there is a noticeable surge in movement among younger UTXOs, which points to active repositioning by short-term traders. 

Conversely, older UTXOs tend to decline slightly during these spikes, implying that even long-term holders may reposition during periods of uncertainty. As volatility settles, the stabilization of younger UTXOs signals a move toward accumulation, reflecting a balanced mix of trading and holding strategies in a bullish market.

Bear Phase (November 2021 – November 2022)

In the bear phase, the UTXO age distribution reflects significant market stress and shifting investor behavior. The 8-year-plus UTXO band remained dominant, showing that long-term holders largely stayed inactive as Bitcoin’s price fell from around $67K to $15K. Mid-term UTXOs (6 months to 3 years) increased slightly, hinting at some movement—likely due to panic selling. 

Short-term UTXOs (1 week to 6 months) spiked early on, indicating strong selling pressure, but then decreased near the market bottom in November 2022, suggesting the onset of accumulation. Additionally, volatility spikes aligned with increased activity in younger UTXOs (less than 6 months old), highlighting intense trading during uncertain times. 

Conversely, low-volatility periods corresponded with stability among older UTXOs, underlining the persistence of long-term holders. Overall, these trends illustrate a transition from panic-driven sell-offs toward cautious accumulation as the market stabilized later in the bear phase.

Recognizing Market States

On-chain metrics help uncover distinct market behaviors during bull and bear phases, offering valuable signals for traders and institutions. 

In bull markets, rising prices are generally accompanied by moderate volatility. Institutional metrics such as NUPL and MVRV, which correlate positively (around +0.23 and +0.22) with daily returns, indicate that increasing unrealized profits tend to drive controlled price swings. Market cap and realized cap also support this view, suggesting that robust capital inflows and measured profit-taking are key. Meanwhile, UTXO metrics show that medium-term holdings (1 week to 1 month) have a strong correlation (+0.58) with 30-day volatility, implying that swing traders and medium-term investors heavily influence price trends. In these environments, liquidity indicators reveal that exchange trading volume has minimal impact, as long-term holders help stabilize the market.

Conversely, bear markets are characterized by extreme volatility and rapid price declines. Here, institutional metrics reverse—NUPL and MVRV turn negative (around -0.28 and -0.24), signaling that falling unrealized profits trigger forced liquidations and panic selling. Short-term UTXO metrics (1 day to 1 week) correlate strongly (+0.44) with both 7-day and 30-day volatility, highlighting the disruptive role of speculative, rapid trading. Moreover, high trading volumes on exchanges during downturns correlate strongly with price movements (up to +0.39 with absolute daily returns), emphasizing that liquidity shifts can exacerbate market instability.

Market participants should closely monitor these metrics—especially shifts in UTXO activity, reversals in institutional sentiment indicators, and sudden spikes in trading volumes. All these on-chain metrics are available directly from Amberdata and can serve as the foundation for trading systems designed to recognize different market states. By tracking these signals, investors can identify early signs of market transitions, refine risk management strategies, and make more informed trading decisions in the crypto landscape.

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