Financial Math & Python Modeling Expert
Budget: €30 – €250 EUR
Hello,
I am looking for a freelancer with expertise in financial mathematics and Python programming for an interest rate modeling project. The goal is to study lognormal interest rate models, implement the Black-Derman-Toy (BDT) model in Python by constructing a binomial tree for interest rates, use this model to price interest rate options such as caps, floors, and swaptions, analyze the issues related to Euro-dollar contracts, evaluate how the BDT model can address these issues, and compile a structured report presenting the results and analysis.
The project is divided into several phases. The first phase consists of a theoretical study of the model, including an explanation of key concepts such as spot rates, forward rates, and the yield curve, a presentation of classical models like Vasicek and CIR, and a detailed explanation of the Black-Derman-Toy model, covering its assumptions, equations, and the construction of the binomial tree. This part should be documented clearly with illustrative content.
Next, the implementation of the BDT model in Python will involve developing a function to generate a binomial tree for interest rates, calibrating the model based on market data, and performing simulations of interest rate evolution. The expected deliverables include a well-documented Python script and a Jupyter notebook illustrating the results.
The third phase consists of using the binomial tree to price interest rate options by developing functions to evaluate caps, floors, and swaptions, comparing the results obtained with other models like Vasicek, and presenting the findings in the form of graphs and detailed analysis. This part will include testing the model’s accuracy in pricing derivatives and analyzing its strengths and limitations compared to alternative models.
The fourth phase will focus on analyzing issues related to Euro-dollar futures contracts, explaining their mechanics, identifying the limitations of standard models for these contracts, and assessing how the BDT model can improve the modeling approach. A report should be written summarizing the findings and proposing adjustments or improvements.
The final phase involves compiling all sections into a structured and professional report, ensuring consistency and clarity. This report should include figures, graphs, and detailed explanations of the methodologies used, as well as a critical analysis of the results.
I am looking for a freelancer with expertise in financial mathematics and Python programming for an interest rate modeling project. The goal is to study lognormal interest rate models, implement the Black-Derman-Toy (BDT) model in Python by constructing a binomial tree for interest rates, use this model to price interest rate options such as caps, floors, and swaptions, analyze the issues related to Euro-dollar contracts, evaluate how the BDT model can address these issues, and compile a structured report presenting the results and analysis.
The project is divided into several phases. The first phase consists of a theoretical study of the model, including an explanation of key concepts such as spot rates, forward rates, and the yield curve, a presentation of classical models like Vasicek and CIR, and a detailed explanation of the Black-Derman-Toy model, covering its assumptions, equations, and the construction of the binomial tree. This part should be documented clearly with illustrative content.
Next, the implementation of the BDT model in Python will involve developing a function to generate a binomial tree for interest rates, calibrating the model based on market data, and performing simulations of interest rate evolution. The expected deliverables include a well-documented Python script and a Jupyter notebook illustrating the results.
The third phase consists of using the binomial tree to price interest rate options by developing functions to evaluate caps, floors, and swaptions, comparing the results obtained with other models like Vasicek, and presenting the findings in the form of graphs and detailed analysis. This part will include testing the model’s accuracy in pricing derivatives and analyzing its strengths and limitations compared to alternative models.
The fourth phase will focus on analyzing issues related to Euro-dollar futures contracts, explaining their mechanics, identifying the limitations of standard models for these contracts, and assessing how the BDT model can improve the modeling approach. A report should be written summarizing the findings and proposing adjustments or improvements.
The final phase involves compiling all sections into a structured and professional report, ensuring consistency and clarity. This report should include figures, graphs, and detailed explanations of the methodologies used, as well as a critical analysis of the results.