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Generation of Synthetic Data

In: Advanced Portfolio Optimization

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  • Dany Cajas

    (Orenji EIRL)

Abstract

This chapter explains three approaches that allow readers to generate synthetic data to backtest our multiassets investment strategies: block bootstrap, copulas, and econometric models. These techniques will allow readers to create several types of scenarios that will help them to backtest their strategies during different market conditions. This chapter does not delve much into the theory; it mainly focuses on showing how to use each approach to generate synthetic data using Python code.

Suggested Citation

  • Dany Cajas, 2025. "Generation of Synthetic Data," Springer Books, in: Advanced Portfolio Optimization, chapter 0, pages 399-435, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-84304-4_14
    DOI: 10.1007/978-3-031-84304-4_14
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