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Working Paper
Trading activity and exchange rates in high-frequency EBS data
The absence of data has, until now, precluded virtually all research on trading volume in the foreign exchange market. This paper introduces a new high-frequency foreign exchange dataset from EBS (Electronic Broking Service) that includes trading volume in the global interdealer spot market. The dataset gives volumes and prices at the one-minute frequency over a five-year time period in the euro-dollar and dollar-yen currency pairs. We first document intraday volume patterns in euro-dollar and dollar-yen trading, noting the effects of macroeconomic news announcements but also purely ...
Working Paper
The high-frequency impact of news on long-term yields and forward rates: Is it real?
This paper uses high-frequency intradaily data to estimate the effects of macroeconomic news announcements on yields and forward rates on nominal and index-linked bonds, and on inflation compensation. To our knowledge, it is the first study in the macro announcements literature to use intradaily real yield data, which allow us to parse the effects of news announcements on real rates and inflation compensation far more precisely than we can using daily data. Long-term nominal yields and forward rates are very sensitive to macroeconomic news announcements. We find that inflation compensation is ...
Working Paper
Identifying the effects of monetary policy shocks on exchange rates using high frequency data
This paper proposes a new approach to identifying the effects of monetary policy shocks in an international vector autoregression. Using high-frequency data on the prices of Fed Funds futures contracts, we measure the impact of the surprise component of the FOMC-day Federal Reserve policy decision on financial variables, such as the exchange rate and the foreign interest rate. We show how this information can be used to achieve identification without having to make the usual strong assumption of a recursive ordering.
Working Paper
Forecasting professional forecasters
Survey of forecasters, containing respondents' predictions of future values of growth, inflation and other key macroeconomic variables, receive a lot of attention in the financial press, from investors, and from policy makers. They are apparently widely perceived to provide useful information about agents' expectations. Nonetheless, these survey forecasts suffer from the crucial disadvantage that they are often quite stale, as they are released only infrequently, such as on a quarterly basis. In this paper, we propose methods for using asset price data to construct daily forecasts of upcoming ...
Working Paper
Log-periodogram estimation of long memory volatility dependencies with conditionally heavy tailed returns
Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that the choice of volatility measure makes little difference to the log-periodogram regression estimator if the ...
Working Paper
The U.S. Treasury yield curve: 1961 to the present
The discount function, which determines the value of all future nominal payments, is the most basic building block of finance and is usually inferred from the Treasury yield curve. It is therefore surprising that researchers and practitioners do not have available to them a long history of high-frequency yield curve estimates. This paper fills that void by making public the Treasury yield curve estimates of the Federal Reserve Board at a daily frequency from 1961 to the present. We use a well-known and simple smoothing method that is shown to fit the data very well. The resulting estimates ...
Discussion Paper
The Sensitivity of Long-Term Interest Rates: A Tale of Two Frequencies
The sensitivity of long-term interest rates to short-term interest rates is a central feature of the yield curve. This post, which draws on our Staff Report, shows that long- and short-term rates co-move to a surprising extent at high frequencies (over daily or monthly periods). However, since 2000, they co-move far less at lower frequencies (over six months or a year). We discuss potential explanations for this finding and its implications for the transmission of monetary policy.
Working Paper
Uncovered interest parity: it works, but not for long
The failure of uncovered interest parity can be ascribed to the existence of a risk premium. The size of this risk premium may shrink to zero over sufficiently small intervals of time. In contrast, because no interest is paid on intradaily positions and interest is instead paid discretely at the point when a position is rolled over from one day to the next, the size of the interest differential remains fixed over any interval that covers the time of the discrete interest payment. This is true no matter how short that interval is. Using a large dataset of high frequency exchange rate data, we ...
Report
Rate-Amplifying Demand and the Excess Sensitivity of Long-Term Rates
Long-term nominal interest rates are surprisingly sensitive to high-frequency (daily or monthly) movements in short-term rates. Since 2000, this high-frequency sensitivity has grown even stronger in U.S. data. By contrast, the association between low-frequency changes (at six- or twelve-month horizons) in long- and short-term rates, which was also strong before 2000, has weakened substantially. This puzzling post-2000 pattern arises because increases in short rates temporarily raise the term premium component of long-term yields, leading long rates to temporarily overreact to changes in short ...
Working Paper
Bond risk premia and realized jump volatility
We find that adding a measure of market jump volatility risk to a regression of excess bond returns on the term structure of forward rates nearly doubles the R square of the regression. Our market jump volatility measure is based on the realized jumps identified from high-frequency stock market returns using the bi-power variation technique. The significant enhancement of bond return predictability is robust to different forecasting horizons, to using non-overlapping returns and to the choice of different window sizes in computing the jump volatility. This market jump volatility factor also ...