A Three-Variable Benchmark for Post-GFC Covered Interest Parity Deviations

By Useong Shin

Rating

1357
Battle Count: 80

Relevance

5/10
The paper is primarily an academic benchmark contribution rather than a trading strategy. However, it is relevant to quantitative trading in several ways: (1) CIP deviations represent persistent cross-currency basis trades that can be exploited by FX swap desks and cross-currency basis traders; (2) the benchmark identifies which macrofinancial state variables (NFCI, dollar, yield curve) drive the persistent component of CIP deviations, useful for timing basis trades; (3) the out-of-sample R² of ~0.50 suggests meaningful predictive content for the background component; (4) the paper explicitly states it is NOT a high-frequency arbitrage-execution model, limiting direct trading applicability. The benchmark is more useful as a research hurdle than as a direct trading signal.

Implementation Complexity

2/10
The core benchmark is extremely simple to implement: three lagged public variables regressed on CIP deviations with panel-specific intercepts. All data are from FRED and a public website. The main complexity lies in the robustness diagnostics (cointegration tests, aggregation-difference analysis, PCA rotation, expanding-window forecasts) and the careful data alignment (weekly NFCI carried forward, one-observation lags, non-overlapping block construction). A basic implementation requires only OLS with HAC standard errors. The full paper's analysis requires more econometric sophistication but remains within standard panel regression toolkit.

Reproducibility

5/5
The benchmark is explicitly designed for reproducibility. All three regressors (NFCI, broad dollar index, Treasury 10Y-2Y slope) are available from FRED. The dependent variable (government-bond CIP deviations) is from Du et al. (2025b), publicly available on Jesse Schreger's website. The specification is intentionally simple: three lagged public variables, panel-specific intercepts, no proprietary data, no high-dimensional search. The paper provides detailed data alignment procedures (weekly NFCI carried forward, one-observation lags). No GitHub repository is mentioned, but all inputs are public.

About this paper

Methodology: Three-Variable Public-Data Regression Benchmark. Problem types: Regression, Time Series Forecasting, Dimensionality Reduction.

The interactive Everscope explorer (charts, battles, favorites) loads below.