The 1 reference with contexts in paper Angelo Ranaldo, Paul Söderlind (2007) “Safe Haven Currencies” / RePEc:usg:dp2007:2007-22

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Griliches, Z., 1986, “Economic data issues,” in Zvi Griliches,andMichael D. Intriligator (ed.),Handbooks in Econometrics III, North-Holland, Amsterdam.
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    three-hour horizon, the Treasury note futures returns are only available for 4 of the 8 three-hour intervals of a day (and night), while the most of the other data is available for 7 or 8 intervals. To avoid loosing to much data in the intraday regressions, we do two things. First, the lagged Treasury note futures is excluded (that is,ˇ5in (2) is restricted to zero). Second, we apply the
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    two-step approach to handle the still missing data points of the Treasury note futures. Effectively, this means that we estimate theˇ2coefficient in (2) on the 4 three-hour intervals with complete data, but the other coefficients on the 7 or 8 three-hour intervals.

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    Table 3reports results from estimating the regression equation (2) (with CHF/USD as the dependent variable) for different horizons: from 3 hours up to 4 days. For the intraday data we use a global equity series (NIKKEI, DAX, and S&P) instead of only S&P to get an almost round-the-clock series (see Section 3) and apply the
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    twostep approach to handle the still missing data points of the Treasury note futures (see Section 4). The safe have effect is clearly visible on all these horizons, even if magnitude of the coefficients of S&P and currency market volatility is considerably smaller at the shorter horizons—and seem to peak around 1 to 2 days.

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    The t-statistics are based on a Newey-West estimator with two lags. See Table 1 for details on the data. The regressions on hourly data do not include the lagged Treasure notes futures as a regressor, and apply
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    two-step approach to handle the still missing data points for the Treasury notes. into the Swiss franc value at any time granularity. This suggests the genuine character for the Swiss franc as a safe asset.