FX Risk Assessment & Management Model
Khal Ben
Project Overview
This FX Risk Management project for Lumon, a UK-based client, involved designing a data-driven application to help manage currency exchange rate risks. By leveraging Pandas for data manipulation and Streamlit for building an interactive web app, the solution allows users to assess their exposure to currency fluctuations and employ forward contracts to mitigate FX risk. Additionally, Plotly was used for visualizing complex data trends, giving users intuitive, interactive insights into currency fluctuations and strategy performance.
Objectives
FX Risk Assessment: Equip users to evaluate the financial impact of currency rate fluctuations on their holdings.
Forward Contracts for Risk Mitigation: Provide a framework for users to implement forward contracts to manage currency exposure.
Backtesting of Strategies: Allow users to backtest FX risk strategies on historical data, helping to fine-tune risk mitigation.
Methodology
Data Analysis and Risk Evaluation with Pandas Pandas was used to manage and analyze historical currency exchange data, including calculating volatility, risk metrics, and performing scenario-based projections of currency movements. This setup allowed for efficient data handling, which could be directly integrated with the app's front-end.
Forward Contract Strategy Implementation The model incorporated forward contract calculations, allowing users to experiment with different scenarios. By specifying contract terms, users could see projected financial impacts, helping them decide when and how to implement forward contracts for optimal risk management.
Backtesting of Risk Management Strategies The backtesting module enabled users to test forward contract strategies on historical data, giving insights into how different approaches would perform over time. This feature helps users refine their strategies, making data-driven decisions in mitigating currency risks.
Solution Architecture
Data Processing with Pandas All data manipulation, including reading historical FX rates, calculating forward rates, and generating risk metrics, was done using Pandas. This allowed for rapid data transformation and integration with the interactive Streamlit app.
Interactive Streamlit Application The custom-built Streamlit app provides an intuitive interface for users to assess and manage FX risk. Key sections include:
Risk Assessment Tool: Users can input their currency exposures and instantly assess the risk level based on current rates.
Forward Contract Simulator: Allows users to simulate the use of forward contracts, viewing potential gains or losses based on hypothetical future exchange rates.
Backtesting Module: Users can apply their strategies on historical data, with Plotly providing interactive graphs to illustrate the potential effectiveness of different forward contract scenarios.
Plotly Visualizations Using Plotly, interactive charts were created to illustrate FX rate trends, forward contract results, and backtesting outcomes. This helped make complex data accessible and easy to interpret, enabling Lumon to visualize historical patterns and potential strategy outcomes effectively.
Demonstration
Results and Benefits
Risk Mitigation Visibility: The app enables Lumon to understand exposure levels and experiment with forward contracts for hedging, reducing potential losses from exchange rate changes.
Strategic Optimization with Backtesting: Backtesting gives Lumon a clear view of potential success or failure of strategies, allowing for refined decision-making.
Conclusion
The FX Risk Management Model for Lumon combines Pandas-driven data processing with a Streamlit interface and interactive Plotly visualizations to deliver a powerful, user-friendly tool. The model allows Lumon to assess, manage, and backtest FX risks in real-time, providing a strategic edge in currency risk management.
