diff --git a/docs/downloads.html b/docs/downloads.html index 9339b99..5f5ff42 100644 --- a/docs/downloads.html +++ b/docs/downloads.html @@ -6,81 +6,189 @@ Downloads - CommitTrader Research
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Download Research Data

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📊 Event Study Results

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Event Study Results

Complete event study results including abnormal returns and cumulative abnormal returns for all events. Includes metadata about each event. @@ -100,7 +208,7 @@

📊 Event Study Results

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📈 Aggregated Results

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Aggregated Results

Aggregated statistics by event type, including mean, median, and standard deviation of abnormal returns. @@ -110,7 +218,7 @@

📈 Aggregated Results

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📋 Summary Statistics

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Summary Statistics

High-level summary of the analysis including total events, companies analyzed, and overall statistics. @@ -120,7 +228,7 @@

📋 Summary Statistics

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📄 Full Report (HTML)

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Full Report (HTML)

Complete interactive report with all visualizations and statistical tests. Can be viewed offline. @@ -128,8 +236,8 @@

📄 Full Report (HTML)

View Report
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-

Citation

+
+

Citation

If you use this data in your research, please cite:

 @misc{committrader,
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     CommitTrader Research
     
 
diff --git a/docs/methodology.html b/docs/methodology.html
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     Methodology - CommitTrader Research
     
 
 
     
 
     

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     CommitTrader Research - Full Report
     
+    
 
 
+    ← Back to Home
+
     

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📊 CommitTrader Research - Full Report

+        
CommitTrader Research Report

         

             Quantitative Analysis of GitHub Activity and Stock Price Relationships
         

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Executive Summary

             

         

 
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Executive Summary

             
                 

                 

             
         

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Key Findings

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Research Question

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Research Question

Does public GitHub activity from open-source repositories associated with publicly traded companies have measurable impact on stock prices? @@ -217,7 +345,7 @@

Main Results

Statistical Significance

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Statistical Significance

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t_test 0.1794 ns 1413
sign_test 0.6321 ns N/A
wilcoxon_test 0.8225 ns1413N/A
cross_sectional 0.1794 ns 1413
CAR_0_0_test 0.1794 ns 1413
CAR_0_1_test 0.8090 ns 1413
CAR_-1_1_test 0.9373 ns 1413
CAR_0_5_test 0.5458 ns 1413
CAR_-5_5_test 0.5023 ns 1413
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- Significance Levels: - *** p < 0.01 (highly significant) | - ** p < 0.05 (significant) | - * p < 0.10 (marginally significant) | - ns not significant -

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Cumulative Abnormal Returns Distribution

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Abnormal Returns by Event Type

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Event Timeline Analysis

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Top Events

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Methodology

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Event Study Approach

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  1. Event Identification: GitHub releases, commit spikes, and milestones
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  2. Expected Returns: Market model with OLS parameter estimation
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  3. Abnormal Returns: AR = Actual Return - Expected Return
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  4. Statistical Testing: Multiple parametric and non-parametric tests
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  5. Aggregation: Cross-sectional analysis across all events
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+

Event Study Design

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+ This analysis employs standard event study methodology to measure abnormal stock returns + around GitHub release events. The market model is used to calculate expected returns: +

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+ E(Rit) = αi + βi × Rmt +

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+ Where Rit is the stock return, Rmt is the market return (S&P 500), + and parameters are estimated over a 100-day estimation window (-130 to -31 days before the event). +

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Event Windows

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Statistical Tests

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  • Event Window: -5 to +5 trading days around event
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  • Estimation Window: -130 to -31 days before event
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  • Market Index: S&P 500 (^GSPC)
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  • t-test: Parametric test for mean abnormal returns
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  • Sign test: Non-parametric test based on proportion of positive ARs
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  • Wilcoxon test: Non-parametric rank-based test
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  • Cross-sectional test: Tests for abnormal returns using cross-sectional variance
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Event Windows

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Multiple event windows tested: (0,0), (0,+1), (-1,+1), (0,+5), and (-5,+5) days

-

- CommitTrader - Quantitative Research Platform
- This report is for research purposes only and should not be used as investment advice.
- Past performance does not guarantee future results. +

CommitTrader Research Platform

+

This research is for educational purposes only and should not be used as investment advice.

+

+ Back to Home | + Methodology | + Downloads