Practice of Python in Programming and Optimization of Quantitative Analysis Model of Fixed Income

Yang Li; Yanchen Zou; Yanda Qian

doi:10.54097/z441c084

Authors

Yang Li
Yanchen Zou
Yanda Qian

DOI:

https://doi.org/10.54097/z441c084

Keywords:

Python; Quantitative Analysis; Fixed Income.

Abstract

Python has become an indispensable tool in fixed income trading. This paper introduces the principles and general process of data analysis visualisation by analysing the basic operation and performance of personal investment and finance, combined with data analysis in the era of big data. The library of data analysis tools using Python has become an indispensable tool in fixed income trading. In fixed income trading, it supports fixed income traders to handle tasks such as bond pricing, interest rate modelling, and credit risk analysis Using Python's powerful data processing capabilities, traders can simplify data collection, analysis, and reporting to make better decisions. Based on the Python language, financial data is acquired from different platforms, processed and analysed step-by-step, ensuring that the model remains accurate and stable in different market conditions. Backtesting and ongoing performance evaluations have revealed that Python can be a valuable asset in the dynamic world of fixed income trading by refining trading strategies and effectively managing risk.

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