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@article{205689,
        author = {Shrinivas R Patil and Dr. R R Kulkarni and Dr. Prakash Rao KS},
        title = {Institutional Channels of Geopolitical Risk Transmission to Foreign Exchange Volatility: Mixed-Frequency Models and Externally Instrumented Local Projections},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {8241-8253},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=205689},
        abstract = {Why do geopolitical risk shocks propagate with four to five times greater force to emerging-market currencies than to developed-market currencies? We develop a theoretical model showing that the exchange rate variance response to geopolitical risk is inversely proportional to a country's composite institutional buffer—comprising central bank independence, reserve adequacy, and the foreign-currency debt burden—and test this prediction using a unified four-model econometric strategy. As the primary estimation framework, GARCH-MIDAS-X models correctly handle the mixed-frequency mapping from monthly geopolitical risk to daily exchange rate returns, overcoming the temporal aggregation bias in prior GARCH-X studies. A heterogeneous autoregressive realised volatility (HAR-RV) panel with continuous institutional interaction terms provides the primary cross-country evidence. For identification, we construct a geographic distance- and trade-adjusted external geopolitical risk instrument—a Bartik-type measure that isolates globally transmitted geopolitical shocks orthogonal to each country's domestic macroeconomic conditions—and embed it within two-stage local projections (2SLS-LP). The first-stage F-statistic of 18.4 indicates a strong instrument; 2SLS-LP impulse responses are virtually identical to OLS-LP responses, allaying reverse-causality concerns for the average currency pair. Applying the Perron-Qu (2010) test to discriminate genuine long memory from structural-break-induced spurious persistence, we confirm fractional integration d > 0.5 for the Russian ruble and Turkish lira, while reclassifying Brazil and South Africa as break-driven rather than long-memory currencies—a corrective finding relative to prior work. Across four geopolitical shock events, emerging-market currencies exhibit 2.7 to 12.1 times larger abnormal volatility than developed-market currencies, with the disparity systematically larger in countries scoring below median on all three institutional dimensions. The GARCH-MIDAS-X model reduces out-of-sample RMSE by 25–40% over 2019–2023, confirmed by Diebold-Mariano tests.},
        keywords = {Geopolitical risk; GARCH-MIDAS; local projections; HAR-RV; institutional transmission; external instrument; emerging markets; long memory JEL Codes: F31, F52, G15, C22, C23},
        month = {June},
        }