Yoel125/Assignment_1_EDA

Bitcoin (BTC) Price Action & Technical Indicators Analysis

Video Presentation

Project Overview

This research analyzes the "Multi-Model Trading Data" dataset, which consists of Bitcoin (BTC) historical trading data.

this data set haves 7.26K rows and 18 columns.

The Goal: To investigate the direct relationship between Bitcoin’s Price Movements and key technical indicators (Volume ,RSI, MACD, and Stoch RSI) to understand how market momentum and trend-reversal patterns correlate with actual price changes.

source:

https://huggingface.co/datasets/AdityaaXD/Multi-Model-Trading-Data

Feature Selection :

Price Dynamics: open, high, low, close

Performance Metrics: volume, returns

Technical Indicators: RSI (Momentum), stoch_rsi_d (Sensitivity), MACD (Trend Confirmation)

Timeline: date

Data Cleaning & Decision Making

Feature Selection: first i isolated 10 core columns essential for technical analysis (e.g., Price, Volume, and Timestamp). This step served as a form of Dimensionality Reduction, ensuring our analysis focused only on relevant features.

Data Filtering: Following the feature selection process, I performed targeted row filtration on the columns that contained approximately 50% missing values. This step was strategically executed after the column selection to ensure that only relevant data was prioritized, preventing the unnecessary deletion of records based on non-essential features.

Final Cleaning: Following the initial thresholding, all remaining null values were dropped to provide a high-fidelity dataset for calculating oscillators and trend-lines.

Detection: utilized the Interquartile Range (IQR) to identify statistical anomalies in price and returns.

Decision: I made the decision to retain all outliers.

Justification: In the Bitcoin market, extreme price movements are rarely measurement errors; they represent significant market shifts and high-volatility regimes. Preserving these points is essential for our EDA, as it allows us to analyze how indicators like RSI and MACD behave during "Black Swan" events or periods of rapid price discovery. Removing them would sanitize the data to the point of losing its most valuable information.

Research Questions & Insights:

Main Research Question:

To what extent do technical indicators (RSI, MACD, Stoch RSI) reflect Bitcoin's price movements?

Key Findings & Analysis:

How do price anomalies (Outliers) behave over time?

The visualizations show that price outliers are not random noise. They appear in clusters, coinciding with major historical price rallies and crashes. This suggests that price movements follow structural volatility patterns.

Is there a linear relationship between Volume and Price Returns?

Through Correlation Analysis, we can observe a weak linear relationship (flat regression line). This confirms that volume alone does not dictate price direction, which is why we turned our focus to technical indicators.

How does Bitcoin's price behave when the RSI reaches "Overbought" or "Oversold" levels?

The visualization demonstrates a high correlation between Bitcoin’s price action and the RSI oscillator. Historically, RSI levels above 70 (Overbought) often precede a price correction or consolidation, while levels below 30 (Oversold) suggest a potential local bottom and subsequent price recovery. However, this relationship is not deterministic; during strong trending periods, the RSI can remain in extreme zones while the price continues its momentum, indicating that RSI should be analyzed alongside other features for higher predictive accuracy.

Does the Stoch RSI identify price reversals faster than the standard RSI due to its aggressive movement?

The analysis indicates that the Stoch RSI exhibits high sensitivity to Bitcoin's price movements compared to the standard RSI. While both indicators follow price trends, the Stoch RSI reacts more aggressively, reaching overbought or oversold thresholds significantly faster. This suggests that while Stoch RSI can identify potential reversals earlier, it may also introduce more 'noise' (false signals) during periods of high volatility, whereas the standard RSI provides a more filtered and stable trend confirmation.

Is there a correlation between MACD trend-line crossovers and major price breakouts?

The visualization demonstrates that MACD Zero-line crossovers serve as significant indicators for identifying shifts in Bitcoin's price trajectory. The analysis shows that when the MACD line crosses above the zero-threshold, it signals a transition into a bullish regime, often acting as a precursor to a sustained price increase. Conversely, a crossover below the zero line indicates a shift toward bearish momentum. While the MACD is inherently a lagging indicator, the data confirms a strong correlation between these crossover events and the initiation of major price breakouts, making it a reliable feature for trend confirmation within this specific dataset.

Summary & Research Insights

1.Price Outliers & Trends: In our first graph, we found that the price outliers (the red dots) aren't random. They usually appear in groups during big market crashes or huge jumps (what we call volatility clustering). We decided to keep these outliers because they represent real, important market events that the model needs to learn.

2.Trading Volume: We checked if volume can predict price moves using a scatter plot. The regression line was flat, which proves that trading volume alone isn't enough to tell us where the price is going. This is why we need more advanced indicators.

3.The Indicators (RSI, Stoch RSI, MACD): Looking at the graphs, we saw that each indicator gives us a different piece of the puzzle:

RSI: Perfect for seeing when Bitcoin is "Overbought" or "Oversold."

Stochastic RSI: Much more aggressive and fast. it gives us "early warnings" before the regular RSI even moves.

MACD: The crossovers are the best signal for confirming a new price breakout or a change in trend.

Final Conclusion

The EDA process successfully "told the story" of Bitcoin's price dynamics. We concluded that price movements are more closely correlated with momentum shifts and trend confirmations (as captured by MACD and RSI) than with simple volume spikes.

📂 Project Files & Deliverables

File	Description	Link
_Assigment_1_EDA.csv	Cleaned BTC Dataset	View File
_Assignment_1_EDA_&_Dataset_5.ipynb	Full Analysis Notebook	View Notebook