Variations in Market Liquidity and the Intraday Interest Rate

Most central banks offer banks participating in large‐value real‐time gross settlement (RTGS) systems a free intraday overdraft facility to discourage banks from actively managing their daylight liquidity. In this paper, we ask whether this facility has kept the intraday interest rate at zero. Using a unique transaction‐level data set on collateralized interbank loans for 2006–12, we find that during periods of financial distress, rates for morning transactions are higher than those in the afternoon. Moreover, this intraday rate correlates with market liquidity, suggesting that rates contain a liquidity premium. This intraday pattern is reduced, but not eliminated by the Eurosystem's accommodative liquidity provision.     

Information arrivals and intraday exchange rate volatility

This paper investigates the link between information arrivals and intraday DEM/$ volatility. Information arrivals are measured by the numbers of news items that appeared in the Reuters News Service. We separate news stories into different categories and find that total headline news counts, US and German macroeconomic news and German Bundesbank monetary policy news all have a significant impact on intraday DEM/$ volatility. The larger quantitative effects of the German Bundesbank monetary policy news and US macroeconomic news at 15-min intervals are consistent with the findings of a two-stage adjustment process of public information arrivals [Fleming and Remolona, J. Finance (1999) 1901]. Our results suggest that the persistent of intraday exchange rate volatility set off by public information is extended by traders’ private information about 15 min later. The conclusions are obtained from ARCH models that incorporate intraday seasonal volatility terms.     

Implicit intraday interest rate in the UK unsecured overnight money market

This paper estimates the intraday value of money implicit in the UK unsecured overnight money market. Using transactions data on overnight loans advanced through the UK large value payments system CHAPS in 2003–2009, we find a positive and economically significant intraday interest rate. While the implicit intraday interest rate is quite small pre-crisis, it increases more than tenfold during the financial crisis of 2007–2009. The key interpretation is that an increase in implicit intraday interest rate reflects the increased opportunity cost of pledging collateral intraday and can be used as an indicator to gauge the stress of the payment system. We obtain qualitatively similar estimates of the intraday interest rate by using quoted intraday bid and offer rates and confirm that our results are not driven by the intraday variation in the bid-ask spread.     

Exchange rate volatility,macroeconomic announcements and the choice of intraday periodicity filtering method

Filtering out the intraday periodicity of volatility is crucial for using high frequency data in econometric analysis. This paper studies the effects of filtering on statistical inference as regards the impact of news on exchange rate volatility. The properties of different methods are studied using a five-minute frequency EUR/USD data set and simulated returns. The simulation results suggest that all the methods tend to produce downward-biased estimates of news coefficients, some more biased than others. The study supports the Flexible Fourier Form method as the best for seasonality filtering.     

Why Does the Interest Rate Decline Over the Day? Evidence from the Liquidity Crisis

We provide a simple model, able to explain why the overnight (ON) rate follows a downward intraday pattern, implicitly creating a positive intraday interest rate. While this normally reflects only some frictions, a liquidity crisis introduces a new component: the chance of an upward jump of the ON rate, which must be compensated by an intraday decline of the ON rate. By analyzing real time data for the e-MID interbank market, we show that the intraday rate has increased from a negligible level to a significant one after the start of the liquidity crisis in August 2007, and even more so since September 2008. The intraday rate is affected by the likelihood of a dry-up of the ON market, proxied by the 3M Euribor—Eonia swap spread. This evidence supports our model and it shows that a liquidity crisis impairs the ability of central banks to curb the market price of intraday liquidity, even by providing free daylight overdrafts. Such results have implications for the efficiency of the money market and of payment systems, as well as for the operational framework of central banks.     

Intraday Empirical Regularities in Interest Rate and Equity Index Futures Markets, and the Effect of Macroeconomic Announcements

This paper focuses on the intraday behaviour of returns, volatility, volume and price reversals for the Short Sterling interest rate and FTSE100 stock index futures contracts traded on the London International Financial Futures and Options Exchange (LIFFE). It also examines the effect of scheduled macroeconomic announcements and interest rate changes on the intraday behaviour of the variables of interest. We find clear differences and similarities with US studies and between the interest rate and equity contracts, which have important theoretical implications. This new evidence helps discriminate between the theories seeking to explain these intraday patterns.     

Intraday periodicity, calendar and announcement effects in Euro exchange rate volatility

This paper provides an analysis of intraday volatility using 5-min returns for Euro-Dollar, Euro-Sterling and Euro-Yen exchange rates, and therefore a new market setting. This includes a comparison of the performance of the Fourier flexible form (FFF) intraday volatility filter with an alternative cubic spline approach in the modelling of high frequency exchange rate volatility. Analysis of various potential calendar effects and seasonal chronological changes reveals that although such effects cause deviations from the average intraday volatility pattern, these intraday timing effects are in many cases only marginally statistically significant and are insignificant in economic terms. Results for the cubic spline approach imply that significant macroeconomic announcement effects are larger and far more quickly absorbed into exchange rates than is suggested by the FFF model, and underscores the advantage of the cubic spline in permitting the periodicity in intraday volatility to be more closely identified. Further analysis of macroeconomic announcement effects on volatility by country of origin (including the US, Eurozone, UK, Germany, France and Japan) reveals that the predominant reactions occur in response to US macroeconomic news, but that Eurozone, German and UK announcements also cause significant volatility reactions. Furthermore, Eurozone announcements are found to impact significantly upon volatility in the pre-announcement period.     

Asymmetric effects of federal funds target rate changes on S&P100 stock returns,volatilities and correlations

We study the effects of FOMC announcements of federal funds target rate decisions on individual stock returns, volatilities and correlations at the intraday level. For all three characteristics we find that the stock market responds differently to positive and negative target rate surprises. First, the average response to positive surprises (that is, bad news for stocks) is larger. Second, in case of bad news the mere occurrence of a surprise matters most, whereas for good news its magnitude is more important. These new insights are possible due to the use of high-frequency intraday data.     

Estimating daily volatility in financial markets utilizing intraday data

This study proposes a new approach to the estimation of daily realised volatility in financial markets from intraday data. Initially, an examination of intraday returns on S&P 500 Index Futures reveals that returns can be characterised by heteroscedasticity and time-varying autocorrelation. After reviewing a number of daily realised volatility estimators cited in the literature, it is concluded that these estimators are based upon a number of restrictive assumptions in regard to the data generating process for intraday returns. We use a weak set of assumptions about the data generating process for intraday returns, including transaction returns, given in den Haan and Levin [den Haan, W.J., Levin, A., 1996. Inferences from parametric and non-parametric covariance matrix estimation procedures, Working paper, NBER, 195.], which allows for heteroscedasticity and time-varying autocorrelation in intraday returns. These assumptions allow the VARHAC estimator to be employed in the estimation of daily realised volatility. An empirical analysis of the VARHAC daily volatility estimator employing intraday transaction returns concludes that this estimator performs well in comparison to other estimators cited in the literature.     

Forecasting Intraday Volatility and Value-at-Risk with High-Frequency Data

In this paper, we develop modeling tools to forecast Value-at-Risk and volatility with investment horizons of less than one day. We quantify the market risk based on the study at a 30-min time horizon using modified GARCH models. The evaluation of intraday market risk can be useful to market participants (day traders and market makers) involved in frequent trading. As expected, the volatility features a significant intraday seasonality, which motivates us to include the intraday seasonal indexes in the GARCH models. We also incorporate realized variance (RV) and time-varying degrees of freedom in the GARCH models to capture more intraday information on the volatile market. The intrinsic tail risk index is introduced to assist with understanding the inherent risk level in each trading time interval. The proposed models are evaluated based on their forecasting performance of one-period-ahead volatility and Intraday Value-at-Risk (IVaR) with application to the 30 constituent stocks. We find that models with seasonal indexes generally outperform those without; RV can improve the out-of-sample forecasts of IVaR; student GARCH models with time-varying degrees of freedom perform best at 0.5 and 1 % IVaR, while normal GARCH models excel for 2.5 and 5 % IVaR. The results show that RV and seasonal indexes are useful to forecasting intraday volatility and Intraday VaR.     

Explaining Forward Exchange Bias…Intraday

Intraday interest rates are zero. Consequently, a foreign exchange dealer can short a vulnerable currency in the morning, close this position in the afternoon, and never face an interest cost. This tactic might seem especially attractive in times of fixed-rate crisis, since it suggests an immunity to the central bank's interest rate defense. In equilibrium, however, buyers of the vulnerable currency must be compensated on average with an intraday capital gain as long as no devaluation occurs. That is, currencies under attack should typically appreciate intraday. Using data on intraday exchange rate changes within the European Monetary System, we find this prediction is borne out.     

Forecasting EUR–USD implied volatility: The case of intraday data

This study models and forecasts the evolution of intraday implied volatility on an underlying EUR–USD exchange rate for a number of maturities. To our knowledge we are the first to employ high frequency data in this context. This allows the construction of forecasting models that can attempt to exploit intraday seasonalities such as overnight effects. Results show that implied volatility is predictable at shorter horizons, within a given day and across the term structure. Moreover, at the conventional daily frequency, intraday seasonality effects can be used to augment the forecasting power of models. The type of inefficiency revealed suggests potentially profitable trading models.     

Information transfer,microstmctures and intraday price return spikes

Previous research has identified overnight public information as the cause of higher opening returns and mean reversion in security markets. This paper tests this hypothesis by using an intervention and transfer function time series model to filter out the dynamic effects of an overnight information set on the opening, and subsequent, intraday AOI stock and SPI futures intraday price returns. A further research objective was to analyse the process by which information is transferred into prices and whether there is a differential impact across stock and futures markets. It was determined that the information contained in the overnight US stock market had: (i) a differential impact on the Australian stock and futures market, and (ii) after filtering out the impact of overnight information, a significant reversal tendency remained in both markets after opening. Further analysis supported the conclusion that price spikes at opening were not wholly related to overnight information. Other possible explanations, such as different trading mechanisms, did not provide a satisfactory explanation. Overall, it appears that the uncertainty participants face at the beginning of a trading session may induce a number of subtle market reactions (both rational and irrational), in markets with different microstmctures and trading clientele.     

The Intraday Price of Money: Evidence from the e‐MID Interbank Market

We provide empirical evidence, based on tick‐by‐tick data for the e‐MID euro area interbank market covering 2003 and 2004, that the overnight interest rate shows a clear downward pattern throughout the operating day. Thus, a positive hourly interest rate (half basis point) implicitly emerges from the intraday term structure of the overnight rate. Such a pattern was not detected in the mid‐1990s: we explain this evolution as an outcome of the recent trend toward real‐time settlement. The estimated intraday interest rate is lower than in the United States: this is due to the different cost of central bank daylight credit.     

Intraday data and hedging efficiency in interest spread trading

Three government bond futures contracts and their respective 3-month interest rate futures contracts traded on LIFFE are examined. The data period covers three years of observations, January 1994-December 1996, sampled at half-hourly intervals. Borrowing from the calculation of minimum variance hedge ratios, half-hourly minimum variance spread ratios (the ratio of one contract to another, which provides the minimum variance) are estimated for the above contracts. The hypothesis under examination is whether there is any value-added in estimating minimum spread ratios based on intraday data. Three spread ratios are defined: two ratios calculated from daily data and a third one based on intraday data. Evidence tends to indicate that spread ratios calculated from intraday data exhibit a substantially lower variance than the other two spread ratio speciications. Thus, it is shown that intraday data, in comparison with daily data, allow for lower hedging costs. Moreover, the use of intraday-based spread ratios might be a contributing factor to reducing the maximum cumulative loss potentially incurred while holding a spread position.     

Optimal pricing of intraday liquidity

This paper presents a general equilibrium model where intraday liquidity is needed because the timing of payments is uncertain. A necessary and sufficient condition for an equilibrium to be efficient is that the nominal intraday interest rate be zero, even when the overnight rate is strictly positive. Because a market for liquidity may not achieve efficiency, this creates a role for the central bank. I allow for the possibility of moral hazard and study policies commonly used by central banks to reduce their exposure to risk. I show collateralized lending achieves the efficient allocation, while, for certain parameters, caps cannot prevent moral hazard.     

Intraday Return Volatility Process: Evidence from NASDAQ Stocks

This paper presents a comprehensive analysis of the distributional and time-series properties of intraday returns. The purpose is to determine whether a GARCH model that allows for time varying variance in a process can adequately represent intraday return volatility. Our primary data set consists of 5-minute returns, trading volumes, and bid-ask spreads during the period January 1, 1999 through March 31, 1999, for a subset of thirty stocks from the NASDAQ 100 Index. Our results indicate that the GARCH(1,1) model best describes the volatility of intraday returns. Current volatility can be explained by past volatility that tends to persist over time. These results are consistent with those of Akgiray (1989) who estimates volatility using the various ARCH and GARCH specifications and finds the GARCH(1,1) model performs the best. We add volume as an additional explanatory variable in the GARCH model to examine if volume can capture the GARCH effects. Consistent with results of Najand and Yung (1991) and Foster (1995) and contrary to those of Lamoureux and Lastrapes (1990), our results show that the persistence in volatility remains in intraday return series even after volume is included in the model as an explanatory variable. We then substitute bid-ask spread for volume in the conditional volatility equation to examine if the latter can capture the GARCH effects. The results show that the GARCH effects remain strongly significant for many of the securities after the introduction of bid-ask spread. Consistent with results of Antoniou, Homes and Priestley (1998), intraday returns also exhibit significant asymmetric responses of volatility to flow of information into the market.     

A duscrete-time model of high-frequency stock returns

A model of intraday financial time series is developed. The model is a dynamic factor model consisting of two equations. First, a rate of return of a ‘stock’ in a single day is assumed to be generated by serveral common factors plus some additive erros (‘intraday equation’). Secondly, the joint distribution of those common factors is assumed to depend on the hidden state of the day, which fluctuates according to a Markov chain (‘day-by-day equation’). Together the equations compose a hidden Markov model.

We investigate properties of the model. Among them is a central limit theorem for cumulative returns, which agrees with the well-known empirical phenomenon in the stock markets that the distributions of longer-horizon returns are closer to the normal. We propose a two-step procedure consisting of the method of principal components and the EM algorithm to estimate the model parameters as well as the unboservable states. In addition, we propose a procedure for predicting intraday returns. Finally, the model is fitted to empirical data, the Standard&Poors 500 Index 5 min return data, to see if the model is capable of describing intraday movements of the index.     

The intraday determination of liquidity in the NYSE LIFFE equity option markets

We exploit an extensive high-frequency data set of all individual equity options trading at New York Stock Exchange London International Financial Futures and Options Exchange (Amsterdam, London and Paris) in order to study the determination of liquidity during the trading day. In particular, we focus on two main aspects of option liquidity: (i) the intraday behaviour of equity option liquidity and its determinants and (ii) the influence of macroeconomic events and commonality on intraday equity option liquidity. Inventory management models cannot explain the intraday variation in option spreads and depths. Instead, we show that the option liquidity measures are strongly correlated with option volatility. Increases in volatility are associated with decreases in liquidity, a finding that is in line with information asymmetry models and the derivatives hedging theory. However, the relationship between spreads and volume varies across the three markets. Option liquidity reacts strongly to macroeconomic news announcements, especially US events. The average systematic liquidity component is 12% for Amsterdam, 14% for London and 16% for Paris.     

Deutsche Mark–Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies

This paper provides a detailed characterization of the volatility in the deutsche mark–dollar foreign exchange market using an annual sample of five-minute returns. The approach captures the intraday activity patterns, the macroeconomic announcements, and the volatility persistence (ARCH) known from daily returns. The different features are separately quantified and shown to account for a substantial fraction of return variability, both at the intraday and daily level. The implications of the results for the interpretation of the fundamental "driving forces" behind the volatility process is also discussed.