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

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contrast, price responses to positive earnings surprises do not necessarily increase
in bad times with respect to good times.
In this paper we find similar results to the above studies and more, as our set of
news is much richer. The basic conclusions we reach are: First, the signs of the
responses are all intuitive and the fundamentals that cause most the bond future
changes are (see Table 1 for the acronyms) CC, ISM, UNEM, NFP, PPI, CPI, RS
and IP. On the other hand, HS, GDP, PI, BI and TB have little or no statistical
significance on the bond future. Second, the responses to positive and negative
forecast errors are statistically different. This is the case, for instance, for UNEM,
NFP, CPI and RS. Third, and more importantly, we observe an asymmetry in
responses to positive and negative forecasting errors at different phases of the
business cycle. In fact, our findings agree with Conrad et al. (2002). Bad news has
the strongest effect when the business cycle is at the top and in contraction. This
suggests that when the economy is at the top of the cycle, traders know that sooner
or later the downward part of the cycle will start, and hence bad news may be a
signal of the beginning of the contraction. For equivalent (but inverse) reasons, the
smallest effect of bad news is when the economy is in expansion. Overconfidence
in the state of the economy may be an explanation. Our findings regarding positive
news also agree with Conrad et al. (2002): They are ambiguous. When the economy
is expanding good news has barely any effect. This is again a sign that the
market is overconfident. However, when the economy is contracting, positive and
negative news have similar effect. This suggests that, regardless of the sign of the
error, news increases uncertainty. Fourth, timeliness matter, i.e. the sooner the
fundamental is released, the more it influences the bond future. This is strongly
related to the first conclusion. For example, CC is the first number released, at the
end of the month it is reporting on, and it has an important influence. On the
contrary, BI is released two months after the month it is covering and has barely
any influence. These findings are also found by Flemming and Remolona (1999)
and Hess (2004).
The rest of the paper is organized as follows; Section 2 shows the financial
model, Section 3 explains the econometric methodology, Section 4 discusses the
data, Section 5 shows and discusses the results and Section 6 draws conclusions.
2 On the components of short run price movements
D. Veredas
The hypothesis underlying this paper is that temporary jumps observed in the
pricing of financial assets reflect: 1) the market expectation of fundamental factors
driving the asset valuation (e.g. inflation or unemployment) and 2) the time in the
business cycle where these expectations are formed (and potential signs of reversal
of the cycle) i.e. the idea of looking past the immediate macroeconomic release.
To measure the effect on market expectation of fundamentals driving asset
valuation, we need an asset and a set of fundamentals. Among all the financial
markets, we chose the bond market. Bonds are the most widely used of all the
financial instruments. In particular, we chose the 10 year Treasury Note 6% day
session Future (TY) because it is a liquid and important contract and reflects the
general response of the yield curve to news. The ten year future is a reflection of
the state of the US bond market with maturities between seven and ten years. It is
an efficient way of constructing a long time series that is not subject to the prob-