recent developments in high frequency financial ... - Index of

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fixing some intervals around the trend. This is a purely statistical method subject to
the choice of bandwidth. By contrast, we believe that the right determination of the
business cycle phases would be the one commonly accepted by the fixed income
traders since they are the ones who generate the TY process.
The ISM is largely used among traders as a measure of the business cycle. It is
constructed from a survey that asks about the state of the economy. It has only three
possible answers: better, worse or equal than the previous period. With these answers
a percentage is built. A percentage equal to 50 means that half of the respondents think
that the business conditions are good, while the other half believes the contrary. A
value below 50 is a sign of a weak economy. On the other hand, historical data shows
that an ISM above 54.5 is an indicator of expansion. Therefore, we consider the
following classification: Top if ISM is above 55, bottom if it is below 50,
expansion if it is between 50 and 55 and rising, and contraction if it is between 50
and 55 and falling. A graphical explanation is shown in the bottom plot of Fig. 2.
Finally, some autocorrelation is found on the TY and one lag suffices to take it
into account. This effect is usually found in stock prices. It does not necessarily
mean predictive capabilities but could be due to microstructure effects (see
Andersen and Bollerslev, 1998, footnote 10).
5 Results
Results are shown in Table 2 and A1–A12 in the Appendix and Figs. 3, 4, 5.
Tables A1–A5 show full quantitative results for the fundamentals that have a higher
effect in TY, that is CC, ISM, UNEM and UNEMW. Results are full in the sense
that we consider a benchmark case (no business cycle division) and the afore-
0.004
0.002
0
-0.002
-0.004
-0.006
-0.008
-0.01
1 2 3 4 5 6 7 8 9 10 11 12
D. Veredas
mentioned divisions. Results in Tables A6– A11 are for a second set of fundamentals
(PPI, CPI, RS, IP, HS and DG). They are qualitative in the sense that we do not
present the exact value of the effect but rather whether it is significant or not. For
this second set of fundamentals we do not present results for all the divisions of the
business cycle but only for the most exhaustive. We present very few results for
GDP, BI, TB and PI in Table A12 for reasons that will become clear. Last, Table 2
summarizes and gives further insights into the asymmetry of responses depending
on the sign of the forecasting error and the business cycle.
Fig. 3 Impulse respond function of a shock in CC on TY in division 1. Solid line considering all
forecasting errors. Dotted line when only considering negative forecasting errors. Dashed line
when considering positive forecasting errors. Vertical axis is the coefficient, horizontal are the
minutes (divided by ten) after the release