AI summary · arXiv: 2302.01010v1 · q-fin.RM

Performance attribution with respect to interest rates, FX, carry, and residual market risks

Jan-Frederik Mai

Original paper · DOI Submitted to arXiv on 02 Feb. 2023 License: NONEXCLUSIVE-DISTRIB 1.0

The essentials

  • Jan-Frederik Mai introduces a method for decomposing portfolio profit and loss (PnL) into four components:
  • PnL attributed to changes in foreign exchange (FX) rates
  • PnL related to fluctuations in interest rates
  • Carry gains resulting from the passage of time
  • PnL stemming from changes in residual market risks such as credit risk, liquidity risk, and volatility risk
  • Practical application showcased through dissecting performance of FX- and interest rate-hedged negative basis position within fund XAIA Credit Basis II
  • Methodology extended to analyze performance of fund XAIA Credit Debt Capital during first quarter of 2022
  • Demonstrates how method provides valuable insights into drivers of portfolio performance by breaking down PnL contributions of individual positions within funds
  • Study offers comprehensive framework for attributing portfolio returns to specific risk factors, enabling better understanding of profitability sources within portfolios

Key points written by AI: they may contain errors, check them against the paper.

AI-generated keywords: Performance attribution Interest rates FX Carry gains Residual market risks

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  • Original abstract
In their paper titled "Performance Attribution with Respect to Interest Rates, FX, Carry, and Residual Market Risks," Jan-Frederik Mai introduces a comprehensive method for decomposing the profit and loss (PnL) of a portfolio into four distinct components. These components include PnL attributed to changes in foreign exchange (FX) rates, PnL related to fluctuations in interest rates, carry gains resulting from the passage of time, and PnL stemming from changes in residual market risks such as credit risk, liquidity risk, and volatility risk. The authors showcase the practical application of their approach by dissecting the performance of an FX- and interest rate-hedged negative basis position within their fund XAIA Credit Basis II. Furthermore, they extend their methodology to analyze the performance of another fund, XAIA Credit Debt Capital during the first quarter of 2022. By breaking down the PnL contributions of individual positions within these funds, Mai demonstrates how their method can provide valuable insights into the drivers of portfolio performance. Overall,this study offers a comprehensive framework for attributing portfolio returns to specific risk factors,enabling investors and fund managers to better understand the sources of profitability within their portfolios.The detailed analysis presented by Mai sheds light on how different market dynamics impact overall portfolio performance and highlights the importance of considering various risk factors when evaluating investment strategies.

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