Motto: "Exploring volatility, liquidity, and strategic risk factors in Bitcoin markets"
This project delivers a comprehensive exploratory data analysis (EDA) of cryptocurrency market dynamics, focusing on three major digital assets: MON, BNB, and ETH. The analysis provides actionable insights into market behavior, risk profiles, and investment viability through rigorous quantitative analysis.
Primary Source: CoinGecko
CoinGecko is a leading cryptocurrency data aggregator providing reliable, real-time market data including:
- Historical price movements
- Market capitalization trends
- Trading volume metrics
- Comprehensive asset coverage across global exchanges
Time-Series Market Data in CSV format
- MON (MON-usd-max.csv) - Emerging cryptocurrency
- BNB (bnb-usd-max.csv) - Binance Coin
- ETH (eth-usd-max.csv) - Ethereum
snapped_at- Timestamp of data captureprice- Asset price in USDmarket_cap- Total market capitalizationtotal_volume- 24-hour trading volume- Engineered features: liquidity ratios, returns, volatility metrics, time components
| Coin | Records | Date Range | Avg Market Cap | Data Quality |
|---|---|---|---|---|
| ETH | 3,707 | 2015-08-07 to 2025-09-30 | ~$151B | ✅ Deep & Reliable |
| BNB | 2,992 | 2017-09-16 to 2025-11-26 | ~$41.7B | ✅ Strong Coverage |
| MON | 3 | 2025-11-24 to 2025-11-26 | ~$0.38B |
- Imported three separate CSV files for MON, BNB, and ETH
- Consolidated datasets with coin labels for comparative analysis
- Performed chronological sorting and data integrity verification
- Converted timestamps to IST (Indian Standard Time) for localized analysis
- ✅ Verified zero null values across all datasets
- ✅ Confirmed complete data retention after concatenation (6,702 total records)
- ✅ Validated chronological coverage per coin
- Temporal Features: Extracted date, hour, weekday, and month components
- Liquidity Ratio: Calculated as
total_volume / market_cap - Returns: Computed percentage change in price per coin
- Volatility: Measured standard deviation of returns
Evaluated risk-adjusted returns using a 5% risk-free rate:
- Daily Sharpe Ratios: Measure short-term efficiency
- Annualized Sharpe Ratios: Assess long-term performance
Calculated worst peak-to-trough decline for each asset to quantify downside risk
Assessed growth stability across quarterly periods
- Monthly liquidity ratio trends
- Quarterly volatility patterns
- Market capitalization evolution
- Return distribution across assets
- Executive summary metrics (launch timing, active quarters, best/worst performance periods)
Created comprehensive visual analytics:
- Sharpe ratio comparisons (daily vs annualized)
- Quarterly market cap trends
- Volatility share area charts
- Comparative bar charts for returns, volatility, and market cap
- Time-series analysis of asset evolution
-
Market Position: Dominant with deepest liquidity (3,707 records, 41 active quarters)
-
Average Market Cap: ~$151B with peak at ~$485B (2021Q4)
-
Risk Profile:
- Moderate volatility (1.58 QoQ)
- Maximum Drawdown: -92% (significant historical risk)
- Sharpe Ratio: 0.95 (annualized) - approaching acceptable risk-adjusted threshold
-
Verdict: ✅ Stable, mature asset with reliable liquidity - best suited for risk-aware portfolios seeking balanced exposure
- Market Position: Strong mid-tier presence (2,992 records, 34 quarters)
- Average Market Cap: ~$41.7B with peak at ~$146B (2025Q4)
- Risk Profile:
- High volatility (3.12 QoQ) - highest among analyzed assets
- Maximum Drawdown: -85%
- Sharpe Ratio: 0.42 (annualized) - weak risk-adjusted returns
- Extreme early volatility (2017-2018) reflecting speculative adoption
- Verdict:
⚠️ High-growth potential but elevated risk - volatility outweighs gains, suitable only for aggressive risk tolerance
- Market Position: Late entrant with minimal history (3 records, 1 quarter)
- Average Market Cap: ~$0.38B (negligible compared to peers)
Risk Profile:
-
Liquidity Ratio: 1.88 (extremely high - signals thin market depth)
-
Sharpe Ratio: 11.2 (annualized) - anomalously high but unreliable
-
Negligible drawdown (~0%) due to data sparsity
-
Zero measurable QoQ volatility
-
Compared to BNB,ETH MON gives high returns( in crypto high returns is not always safe and gaurenteed stability.
-
Verdict: ❌ High-risk outlier with unreliable metrics - insufficient historical data makes this asset unsuitable for informed investment decisions
- Conservative Portfolios: Prioritize ETH for stability and liquidity depth
- Growth-Oriented Portfolios: Consider BNB with appropriate risk hedging strategies
- Speculative Positions: Avoid MON until sufficient market maturity is established
- Liquidity Risk: MON's thin market depth poses significant exit strategy challenges
- Volatility Exposure: BNB requires active monitoring and stop-loss mechanisms
- Drawdown Preparedness: Both ETH and BNB show substantial historical drawdowns requiring robust risk capital
The analysis reveals three distinct asset profiles:
- Established Liquidity (ETH): Deep market, proven resilience
- Mid-Range Adoption (BNB): Strong growth trajectory with volatility risk
- Late Entrant Anomaly (MON): Insufficient data for reliable assessment
- Python 3.11.13
- Libraries: pandas, numpy, matplotlib
- Platform: Kaggle Notebooks
- Data Format: CSV time-series data
- Time-series decomposition
- Financial risk metrics (Sharpe, MDD)
- Pivot table aggregation
- Rolling window analysis
- Statistical distribution analysis
This analysis is fully reproducible with the provided Kaggle dataset. All transformations, calculations, and visualizations are documented in the Jupyter notebook with inline inference statements for transparency.
Dataset ID: https://www.kaggle.com/code/dileepp22/bitcoineda
This analysis demonstrates proficiency in:
- Financial data analysis and risk assessment
- Time-series modeling and feature engineering
- Data visualization and business storytelling
- Quantitative investment research methodologies
Perfect for roles in: Data Analytics, Financial Engineering, Quantitative Research, Risk Management, Business Intelligence
"In cryptocurrency markets, historical depth matters more than headline returns. ETH's decade-long track record provides the reliability that MON's three-day history cannot. Smart investing requires both opportunity recognition and risk discipline."
Analysis completed: December 8, 2025
Data Source: CoinGecko | Computational Environment: Kaggle Notebooks