Infrequent Trading Research Articles

The lead-lag relationship between equities and stock index futures markets around information releases

This paper documents a strengthening in the lead of stock index futures returns over stock index returns around macroeconomic information releases. Some evidence of a strengthening in feedback from the equities market to the futures market and weakening in the lead of the futures market around major stock-specific information releases is also provided. This is consistent with the hypothesis that investors with better marketwide information prefer to trade in stock index futures while investors with stock-specific information prefer to trade in underlying stocks. A small weakening in the contemporaneous relationship between stock index futures returns and stock index returns around both types of releases is also documented. This is consistent with disintegration in the relationship between the two markets associated with noise induced volatility. One by-product of this study is new comparative evidence on the performance of adjustments for infrequent trading of index stocks based on a commonly used ARMA technique versus recalculation of the stock index using quote midpoints. The results suggest that the quote midpoint index performs at least as well as the ARMA adjusted index across the entire sample period, as well as around the different types of information releases. © 2000 John Wiley & Sons, Inc. Jrl Fut Mark 20:467–487, 2000

Beyond Arbitrage: Good‐Deal Asset Price Bounds in Incomplete Markets

One often wants to value a risky payoff by reference to prices of other assets rather than by exploiting full‐fledged economic models. However, this approach breaks down if one cannot find a perfect replicating portfolio. We impose weak economic restriction to derive usefully tight bounds on asset prices in this situation. The bounds assume that investors would want to buy assets with high Sharpe ratios‐“good deals”‐as well as pure arbitrage opportunities. We show how to calculate the price bounds in one‐period, multiperiod, and continuous‐time contexts. We show that the multiperiod problem can be solved recursively as a sequence of one‐period problems. We calculate bounds in option pricing examples including infrequent trading and an option written on a nontraded event, and we use the bounds to explore the economic significance of option pricing predictions. We find that much variation in S&P 500, index option prices over time and across strike prices fits within the bounds.

The Relationship Between Implied and Realized Volatility in the Danish Option and Equity Markets

In this paper we examine the information content of options on the Danish KFX share index. These options are traded very infrequently and with a low volume. We consider the relationship between the volatility implied in an option's price and the subsequently realized volatility. Recently, Christensen and Prabhala (1998) find that implied volatility in at-the-money one month OEX call options on the S&P100 index is an unbiased and efficient forecast of ex-post realized index volatility after the 1987 stock market crash. Gwilym and Buckle (1999) study the UK FTSE100 index and find that although historical volatility estimates have greater accuracy, implied volatility contains more information, based on regression tests, in particular when very short maturities are avoided. In this paper we investigate whether the UK and US markets are special, and whether the infrequent trading and low volume in the KFX case lead to bias and inefficiency in the implied volatility forecast. We examine one month at-the-money KFX calls and similar puts, and we introduce an implied volatility measure that combines information from both call and put prices. We find that implied volatility indeed contains information about realized index return volatility. In fact, implied volatility remains significant even in the multiple regression where historical volatility is included, it subsumes the information content of this, and the bias in the implied volatility forecast is insignificant. The results suggest that the finding in the OEX market may be extended to the much smaller KFX market.

Trading Volume Lead/Lag Relations Between the ASX and ASX Option Market: Implications of Market Microstructure

This study documents the intraday lead/lag relation between trading volumes of stocks and stock options traded on the ASX and ASX Options Market respectively. A stock lead of up to 15 minutes is initially documented. Differences in intraday lead/lag relations may occur because of the different nature of equities and options as instruments of investment, or market microstructure differences, or both these factors The study finds no evidence that trading on private infor Mation causes the option market to lead. Instead, market microstructure differences induce relatively infrequent trading in option markets and consequently cause stocks to lead Specifically, we find the stock lead is eliminated when only periods of frequent trading are examined. Also, the infrequent trading induced stock lead is partly explained by the different opening procedures of the two markets

Underpricing and aftermarket performance of IPOs in Shanghai, China

A-share initial public offerings (IPOs) in Shanghai were 289% underpriced, against a mere 26% for B-share IPOs. Regression analysis suggests that the `Chinese characteristic' of high equity retention by the state, a long time-lag between offering and listing and ex-ante risk of new issues were key determinants of market-adjusted IPO underpricing. After controlling for the market comovements, infrequent trading and a higher risk for new issues, the excess returns of overpriced A-share IPOs and B-share IPOs persisted over a long period of time. Rather than being a speculative conjecture, this represents a real phenomenon in that large excess returns accrue in the long run, albeit it meant less negative accumulated returns than the overall market, which had dropped sharply.

Beyond Arbitrage: 'Good Deal' Asset Price Bounds in Incomplete Markets

One often wants to value a given asset or risky payoff by reference to observed prices of other assets rather than by exploiting full-fledged economic models. However, this approach breaks down if one cannot find a perfect replicating portfolio. We impose weak economic restrictions to derive usefully tight bounds on asset prices in this situation. The bounds basically rule out high Sharpe ratios - good deals - as well as arbitrage opportunities. We show how to calculate the price bounds in two-period, multiperiod and continuous time contexts. We show that the multiperiod problem can be solved recursively as a sequence of two-period problems. We calculate bounds in option pricing examples including infrequent trading, an option written on a nontraded event, and in an environment with stochastic stock volatility and a varying riskfree rate.

A threshold error‐correction model for intraday futures and index returns

Index-futures arbitrageurs enter into the market only if the deviation from the arbitrage relation is large enough to compensate for transaction costs and associated interest-rate and dividend risks. Using a threshold autoregression model for the mispricing error, we estimate the band around the theoretical futures prices within which arbitrage is not profitable for most arbitrageurs. Combining these thresholds with an error correction model, we can make a distinction between the effects of arbitrageurs and infrequent trading on index and futures returns. The impact of the mispricing error on the returns is increasing with the magnitude of the mispricing error, and the effect of futures returns on index returns is significantly larger when the basis is negative.

Do Stock Market Investors Overreact?

This paper investigates the evidence on the stock market overreaction hypothesis (ORH), which holds that, if stock prices systematically overshoot as a consequence of excessive investor optimism or pessimism, price reversals should be predictable from past price performance. The ORH stands in contradiction to the efficient markets hypothesis which is a cornerstone of financial economics. This study is unique in the overreaction literature because it is restricted to larger and better‐known listed companies, whose shares are more frequently traded. This restriction more or less eliminates two alternative explanations to the overreaction hypothesis: it minimises the influence of bid‐ask biases and infrequent trading, and reduces the possibility that reversals are primarily a small‐firm phenomenon. The paper also investigates a third alternative explanation, namely that time‐varying risk explains the reversal effect. The study employs unbiased methods of return computation and uses data from 1975 to 1991 for nearly 1,000 UK companies. Overall, the evidence appears to be consistent with the overreaction hypothesis, subject to certain qualifications.

On the impact of infrequent trading on the APT systematic risk components — Evidence from a thin security market

The purpose of this note is to analyze the effects of infrequent trading on the APT systematic risk components using Finnish data. Infrequent trading is reported to influence especially the first systematic risk component produced by factor analysis on stock returns.

OPTIMAL PORTFOLIO MANAGEMENT WITH FIXED TRANSACTION COSTS

We study optimal portfolio management policies for an investor who must pay a transaction cost equal to a fixed Traction of his portfolio value each time he trades. We focus on the infinite horizon objective function of maximizing the asymptotic growth rate, so me optimal policies we derive approximate those of an investor with logarithmic utility at a distant horizon. When investment opportunities are modeled as m correlated geometric Brownian motion stocks and a riskless bond, we show that the optimal policy reduces to solving a single stopping time problem. When there is a single risky stock, we give a system of equations whose solution determines the optima! rule. We use numerical methods to solve for the optima! policy when there are two risky stocks. We study several specific examples and observe the general qualitative result that, even with very low transaction cost levels, the optimal policy entails very infrequent trading.

Measuring True Stock Index Value in the Presence of Infrequent Trading

Based on the Beveridge-Nelson (1981) decomposition of an ARIMA process, I present a measure of true stock index value that is not directly observable due to infrequent trading of stocks. The technique is illustrated with daily observations of the Russell 2000 index. This new measure might well prove useful in studies of lead-lag relationships between index derivatives and spot market and futures basis measurements.

An empirical survey of Indonesian equities 1985–1992

Using a new data base of equities listed on the Jakarta Exchange, historical returns were documented for the 1985–1992 period. Jakarta stocks had high volatility relative to other countries, and startling short-term price movements, such as several hundred percent during December 1988. A new model of microstructure suitable for markets with infrequent trading was developed and applied to Jakarta. It disclosed substantial non-random price fluctuations. Indonesian equity returns were weakly but significantly related to returns in other countries. Jakarta's value stocks (those with low market/book value ratios) performed much better than growth stocks.

Corporate Events, Trading Activity, and the Estimation of Systematic Risk: Evidence From Equity Offerings and Share Repurchases

ABSTRACTWe investigate the relation between trading activity, the measurement of security returns, and the evolution of security prices by examining estimates of systematic risk surrounding equity offerings and share repurchases. In contrast to prior studies, we find no evidence of changes in systematic risk following either equity offerings or share repurchases after correcting for biases caused by infrequent trading and price adjustment delays. Moreover, changes in ordinary least squares beta estimates are significantly related to contemporaneous changes in trading activity. Our results have implications for studies interested in the properties of security returns, particularly those examining periods in which trading activity changes.

Adjusting for the interval effect bias in beta coefficients on a thin security market: application of a lag distribution model

The problems of measuring the systematic risk of a security are discussed. Prior research indicates that estimates for systematic risk, i.e. beta coefficients, are greatly affected by infrequent trading and the selected return interval. This is the case especially in thin stock markets. A lag distribution model to estimate betas is introduced. In addition, the empirical properties of these betas are compared with several alternative beta estimates using data from a thin security market. The empirical evidence suggests that the estimated betas based on this model are less biased by infrequent trading than the betas based on several other estimation procedures proposed in the literature.

Thin trading and estimation of systematic risk: An application of an error-correction model

Financial economics literature indicates that estimates for securities' systematic risk, i.e. the beta coefficients, are highly affected by infrequent trading. This is an especially serious problem in small security markets. In this study, the applicability of an error-correction model is investigated for modeling the risk behavior of thinly traded securities. The empirical results from a small stock market, i.e. the Helsinki Stock Exchange, indicate the estimated error-correction term to be highly dependent on the underlying trading frequency of the stock, while the direct effect is dependent merely on the market value of the firm. The model thus appears to produce useful information about the risk characteristics of thinly traded stocks.

Why Option Prices Lag Stock Prices: A Trading‐based Explanation

ABSTRACTWhile many studies find that option prices lead stock prices, Stephan and Whaley (1990) find that stocks lead options. We find no evidence that options, even deep out‐of‐the‐money options, lead stocks. After confirming Stephan and Whaley's results, we show their results can be explained as spurious leads induced by infrequent trading of options. We show that the stock lead disappears when the average of the bid and ask prices is used instead of transaction prices. Hence, we find no evidence of arbitrage opportunities associated with the stock lead.

The relationship between accounting earnings and bond returns

In this study, the theoretical and empirical research documenting the association between accounting earnings changes and bond returns is addressed. The bond price model is discussed in the Black-Scholes option pricing context combined with additional assumptions about the relationship between accounting earnings and economic income (or permanent earnings). Analysis of the model suggests a positive association between bond prices and accounting earnings. To reduce the errors-in-variables problem due to measurement error in accounting earnings, reverse regressions were used in testing the hypothesis. In order to mitigate the so-called infrequent trading problem of bonds, a mean adjusted returns model developed and used by Handjinicolaou and Kalay (1984) and bonds traded at least once in every two business weeks were used. The tests were conducted in an event-study context. Results are essentially consistent with the hypothesis, i.e. first, there is a positive association between the sign of bond returns and accounting earnings changes. Second, there is a positive association between the magnitude of bond returns and accounting earnings changes.

The Estimation of Quality-Adjusted Auction Returns with Varying Transaction Intervals

Previous research has separately addressed the problem of estimating risk in the presence of infrequent trading and the problem of estimating quality-adjusted returns in markets with quality variation in the observed price series. This paper simultaneously addresses both problems by applying a signal extraction method for unequally spaced data to decompose the observed price series with varying times between transactions into a quality-adjusted, permanent component (which would be observable in the absence of quality variation) plus a stationary, transitory quality variation component. Stamp auction transaction prices provide an application. Auction quality grading is treated in a manner analogous to bond ratings. Almost all of the observed variance is attributed to the auction quality variation. The observed auction returns and stock index returns are not well related.

Swiss real estate: Return, risk, and diversification opportunities

Summary Financial and real estate markets have become increasingly international in recent years. Today, portfolio managers wishing to hold well‐diversified portfolios must invest globally, i.e. not only consider different classes of assets in their own country but also foreign assets. These foreign assets should include stocks, bonds, and real estate. However, in order to make informed decisions, investors need data on the risk and return characteristics of the various asset classes. Whereas data on financial assets are widely available, measuring the risk and return on real estate is a more complex issue mainly due to the infrequent trading of real property. Besides the measurement of the return and risk of real estate, it is of interest to analyse how this asset class fits into a portfolio of stocks and bonds. Numerous studies have demonstrated the positive impact of including real estate in American mixed‐asset portfolios (see, for example, Fogler (1984) and Webb, Curcio and Rubens (1988)). Most of th...

An econometric analysis of nonsynchronous trading

We develop a stochastic model of nonsynchronous asset prices based on sampling with random censoring. In addition to generalizing existing models of nontrading, our framework allows the explicit calculation of the effects of infrequent trading on the time series properties of asset returns. These are empirically testable implications for the variances, autocorrelations, and cross-autocorrelations of returns to individual stocks as well as to portfolios. We construct estimators to quantify the magnitude of nontrading effects in commonly used stock returns data bases, and show the extent to which this phenomenon is responsible for the recent rejections of the random walk hypothesis.