How atharva0123/customer-stock-lifetime-value-risk-prediction- works
This repository is a notebook-based financial analytics prototype that combines market and client signals to estimate survival-adjusted customer lifetime value (CLV). Its documented workflow runs from Yahoo Finance and client data through risk, cohort, feature, survival, and revenue-model stages to client-level scores and business outputs. The README documents these capabilities and relationships; notebook source was not provided, so implementation details beyond that documentation are not represented.
Main entry points: Customer_Stock_Lifetime_Value&Risk_Bankruptcy.ipynb Feature Engineering
Components 13
Market Analysis
- Market Risk
Customer_Stock_Lifetime_Value&Risk_Bankruptcy.ipynb - Stress Index
Customer_Stock_Lifetime_Value&Risk_Bankruptcy.ipynb - Bankruptcy Screen
Customer_Stock_Lifetime_Value&Risk_Bankruptcy.ipynb
Client Analytics
- Client Data
Customer_Stock_Lifetime_Value&Risk_Bankruptcy.ipynb - Cohort Analysis
Customer_Stock_Lifetime_Value&Risk_Bankruptcy.ipynb - Feature Engineering
Customer_Stock_Lifetime_Value&Risk_Bankruptcy.ipynb
CLV Modeling
- Survival Models
Customer_Stock_Lifetime_Value&Risk_Bankruptcy.ipynb - CLV Regression
Customer_Stock_Lifetime_Value&Risk_Bankruptcy.ipynb - Blended CLV
Customer_Stock_Lifetime_Value&Risk_Bankruptcy.ipynb
Business Outputs
- Business Dashboard
Customer_Stock_Lifetime_Value&Risk_Bankruptcy.ipynb - CLV Scorecard
Customer_Stock_Lifetime_Value&Risk_Bankruptcy.ipynb
Other components
- Yahoo Finance
- Client CSVs
Connections 14
- Yahoo Finance → Market Risk: provides prices
- Yahoo Finance → Bankruptcy Screen: provides fundamentals
- Market Risk → Stress Index: feeds indicators
- Stress Index → Feature Engineering: adds stress signals
- Client CSVs → Client Data: supplies CSVs
- Client Data → Cohort Analysis: feeds transactions
- Client Data → Feature Engineering: feeds client history
- Cohort Analysis → Feature Engineering: provides cohort context
- Feature Engineering → Survival Models: provides features
- Feature Engineering → CLV Regression: provides features
- Survival Models → Blended CLV: adjusts for survival
- CLV Regression → Blended CLV: provides revenue estimate
- Blended CLV → Business Dashboard: supplies client values
- Business Dashboard → CLV Scorecard: exports CSV