JP Morgan Quantitative Research Virtual Internship on Forage

Task-1 : Natural Gas Price Analysis and Extrapolation

Analyze monthly natural gas prices to estimate prices at any date and extrapolate for an additional year.

Objectives

1. Analyze data to identify patterns and trends.
2. Develop a model to estimate prices at any date.
3. Extrapolate the model for an additional year.
4. Visualize data to identify seasonal trends.

Deliverables

1. Python script to estimate prices.
2. Data visualization.
3. Written report discussing findings.

Task-2 : Prototype Pricing Model for Gas Storage Contracts

Develop a Python function to estimate the value of a gas storage contract based on input parameters.

Input Parameters

1. Injection dates
2. Withdrawal dates
3. Prices at which the commodity can be purchased/sold
4. Rate at which the gas can be injected/withdrawn
5. Maximum volume that can be stored
6. Storage costs

Objectives

1. Develop a prototype pricing model
2. Test with sample inputs
3. Provide a basis for further validation and testing

Deliverables

1. Python function implementing the pricing model
2. Sample input data and expected output values

Task-3 : Loan Default Prediction and Expected Loss Estimation

Build a predictive model that can estimate the probability of default for a loan borrower and calculate the expected loss on a loan, taking into account a recovery rate of 10%.

Objectives

1. Predict probability of default (PD) for loan borrowers based on their characteristics
2. Estimate expected loss on a loan with a recovery rate of 10%

Deliverables

1. A random forest classifier to predict PD
2. A Python function estimate_expected_loss to estimate expected loss
3. Supports input features: income, total loans outstanding, credit score, employment length, and more
4. A dataset of loan borrowers with features and target variable