Explaining volatility and serial correlation in opening and closing returns:a study of the FT-30 components

In this paper the performance of opening and closing returns, for the components of the FT-30 will be studied. It will be shown that for these stocks opening returns have higher volatility and a greater tendency towards negative serial correlation than closing returns. Unlike previous studies this contrasting performance cannot solely be attributed to differences in the trading mechanism across the trading day. All the stocks used in our sample trade thought the day using a uniform trading mechanism. In this paper, we suggest that it is differences in the speed that closing and opening returns adjust to new information that causes differences in return performance. By estimating the Amihud and Mendelson (1987) [Amihud, Yakov, & Mendelson, Haim (1987). Trading mechanisms and stock returns: An empirical investigation, Journal of Finance, 62 533-553.] partial adjustment model with noise, we show that opening returns have a tendency towards over-reaction, while closing returns have a tendency towards under-reaction. We suggest that it is these differences that cause a substantial proportion (although not all) of the asymmetric return patterns associated with opening and closing returns. © 2005 Elsevier Inc. All rights reserved.

The trading mechanism, cross listed stocks:A comparison of the Paris Bourse and SEAQ-International

This paper studies the behaviour of returns for a sample of cross-listed stocks, listed on both the Paris Bourse and SEAQ-International in London. The aim of the paper is to discover which market adjusts to fundamental news more quickly, the home market of Paris or SEAQ-International. We find that prices in London adjust to changes in their fundamental value more slowly than Paris prices, despite the ability to quickly arbitrage between the two markets. We suggest that this finding may reflect the type of trading, which takes place in the two markets and differences associated with the reporting of large trades. We also estimate the amount of noise present in the two markets and show that the Paris market is more noisy than London. © 2003 Published by Elsevier B.V.

Illiquidity shocks and the comovement between stocks:new evidence using smooth transition

This paper extends the smooth transition conditional correlation model by studying for the first time the impact that illiquidity shocks have on stock market return comovement. We show that firms that experience shocks that increase illiquidity are less liquid than firms that experience shocks that decrease illiquidity. Shocks that increase illiquidity have no statistical impact on comovement. However, shocks that reduce illiquidity lead to a fall in comovement, a pattern that becomes stronger as the illiquidity of the firm increases. This discovery is consistent with increased transparency and an improvement in price efficiency. We find that a small number of firms experience a double illiquidity shock. For these firms, at the first shock, a rise in illiquidity reduces comovement while a fall in illiquidity raises comovement. The second shock partly reverses these changes as a rise in illiquidity is associated with a rise in comovement and a fall in illiquidity is associated with a fall in comovement. These results have important implications for portfolio construction and also for the measurement and evolution of market beta and the cost of capital as it suggests that investors can achieve higher returns for the same amount of market risk because of the greater diversification benefits that exist. We also find that illiquidity, friction, firm size and the pre-shock correlation are all associated with the magnitude of the correlation change. © 2013 Elsevier B.V.

Short-horizon excess returns and exchange rate and interest rate effects

stocks. We examine the effects of foreign exchange (FX) and interest rate changes on the excess returns of U.S. stocks, for short-horizons of 1-40 days. Our new evidence shows a tendency for the volatility of both excess returns and FX rate changes to be negatively related with FX rate and interest rate effects. Both the number of firms with significant FX rate and interest rate effects and the magnitude of their exposures increase with the length of the return horizon. Our finding seems inconsistent with the view that firms hedge effectively at short-return horizons.

Market quality changes in the London Stock Market

This paper examines the impact that the introduction of a closing call auction had on market quality at the London Stock Exchange. Using estimates from the partial adjustment with noise model of Amihud and Mendelson [Amihud, Y., Mendelson, H., 1987. Trading mechanisms and stock returns: An empirical investigation. Journal of Finance 42, 533–553] we show that opening and closing market quality improved for participating stocks. When we stratify our sample securities into five groups based on trading activity we find that the least active securities experience the greatest improvements to market quality. A control sample of stocks are not characterized by discernable changes to market quality.

The effect of universal futures on opening and closing stock market prices

Purpose – In 2001, Euronext-Liffe introduced single security futures contracts for the first time. The purpose of this paper is to examine the impact that these single security futures had on the volatility of the underlying stocks. Design/methodology/approach – The Inclan and Tiao algorithm was used to show that the volatility of underlying securities did not change after universal futures were introduced. Findings – It was found that in the aftermath of the introduction of universal futures the volatility of the underlying securities increases. Increased volatility is not apparent in the control sample. This suggests that single security futures did have some impact on the volatility of the underlying securities. Originality/value – Despite the huge literature that has examined the effects of a futures listing on the volatility of underlying stock returns, little consensus has emerged. This paper adds to the dialogue by focusing on the effects of a single security futures contract rather than concentrating on the effects of index futures contracts.

Serial correlation in the returns of UK capitalization based portfolios

This article examines whether UK portfolio returns are time varying so that expected returns follow an AR(1) process as proposed by Conrad and Kaul for the USA. It explores this hypothesis for four portfolios that have been formed on the basis of market capitalization. The portfolio returns are modelled using a kalman filter signal extraction model in which the unobservable expected return is the state variable and is allowed to evolve as a stationary first order autoregressive process. It finds that this model is a good representation of returns and can account for most of the autocorrelation present in observed portfolio returns. This study concludes that UK portfolio returns are time varying and the nature of the time variation appears to introduce a substantial amount of autocorrelation to portfolio returns. Like Conrad and Kaul if finds a link between the extent to which portfolio returns are time varying and the size of firms within a portfolio but not the monotonic one found for the USA.

Noise and the trading mechanism:the case of SETS

On 20 October 1997 the London Stock Exchange introduced a new trading system called SETS. This system was to replace the dealer system SEAQ, which had been in operation since 1986. Using the iterative sum of squares test introduced by Inclan and Tiao (1994), we investigate whether there was a change in the unconditional variance of opening and closing returns, at the time SETS was introduced. We show that for the FTSE-100 stocks traded on SETS, on the days following its introduction, there was a widespread increase in the volatility of both opening and closing returns. However, no synchronous volatility changes were found to be associated with the FTSE-100 index or FTSE-250 stocks. We conclude therefore that the introduction of the SETS trading mechanism caused an increase in noise at the time the system was introduced.

Opening returns, noise and overreaction

In this article a partial-adjustment model, which shows how equity prices fail to adjust instantaneously to new information, is estimated using a Kalman filter. For the components of the Dow Jones Industrial 30 index I aim to identify whether overreaction or noise is the cause of serial correlation and high volatility associated with opening returns. I find that the tendency for overreaction in opening prices is much stronger than for closing prices; therefore, overreaction rather than noise may account for differences in the return behavior of opening and closing returns.

Do external funds yield lower returns? Recent evidence from East Asian economies

One of the central explanations of the recent Asian Crisis has been the problem of moral hazard as the source of over-investment and excessive external borrowing. There is however rather limited firm-level empirical evidence to characterise inefficient use of internal and external finances. Using a large firm-level panel data-set from four badly affected Asian countries, this paper compares the rates of return to various internal and external funds among firms with low and high debt financing (relative to equity) among financially constrained and other firms. Selectivity-corrected estimates obtained from random effects panel data model do suggest evidence of significantly lower rates of return to long-term debt, even among firms relying more on debt relative to equity in our sample. There is also evidence that average effective interest rates often significantly exceeded the average returns to long-term debt in the sample countries in the pre-crisis period. © 2006 Elsevier Inc. All rights reserved.

Using non-parametric search algorithms to forecast daily excess stock returns

Are the learning procedures of genetic algorithms (GAs) able to generate optimal architectures for artificial neural networks (ANNs) in high frequency data? In this experimental study,GAs are used to identify the best architecture for ANNs. Additional learning is undertaken by the ANNs to forecast daily excess stock returns. No ANN architectures were able to outperform a random walk,despite the finding of non-linearity in the excess returns. This failure is attributed to the absence of suitable ANN structures and further implies that researchers need to be cautious when making inferences from ANN results that use high frequency data.

Using monthly returns to model conditional heteroscedasticity

This empirical study examines the extent of non-linearity in a multivariate model of monthly financial series. To capture the conditional heteroscedasticity in the series, both the GARCH(1,1) and GARCH(1,1)-in-mean models are employed. The conditional errors are assumed to follow the normal and Student-t distributions. The non-linearity in the residuals of a standard OLS regression are also assessed. It is found that the OLS residuals as well as conditional errors of the GARCH models exhibit strong non-linearity. Under the Student density, the extent of non-linearity in the GARCH conditional errors was generally similar to those of the standard OLS. The GARCH-in-mean regression generated the worse out-of-sample forecasts.

Predicting returns in U.S. financial sector indices

This study focuses on: (i) the responsiveness of the U.S. financial sector stock indices to foreign exchange (FX) and interest rate changes; and, (ii) the extent to which good model specification can enhance the forecasts from the associated models. Three models are considered. Only the error-correction model (ECM) generated efficient and consistent coefficient estimates. Furthermore, a simple zero lag model in differences which is clearly mis-specified, generated forecasts that are better than those of the ECM, even if the ECM depicts relationships that are more consistent with economic theory. In brief, FX and interest rate changes do not impact on the return-generating process of the stock indices in any substantial way. Most of the variation in the sector stock indices is associated with past variation in the indices themselves and variation in the market-wide stock index. These results have important implications for financial and economic policies.

Stock price reaction following large one-day price changes: UK evidence

We examine the short-term price reaction of 424 UK stocks to large one-day price changes. Using the GJR-GARCH(1,1), we find no statistical difference amongst the cumulative abnormal returns (CARs) of the Single Index, the Fama–French and the Carhart–Fama–French models. Shocks bigger or equal to 5% are followed by a significant one-day CAR of 1% for all the models. Whilst shocks smaller or equal to -5% are followed by a significant one-day CAR of -0.43% for the Single Index, the CARs are around -0.34% for the other two models. Positive shocks of all sizes and negative shocks maller or equal to -5% are followed by return continuations, whilst the market is efficient following larger negative shocks. The price reaction to shocks is unaffected when we estimate the CARs using the conditional covariances of the pricing variables.