Yiuman Tse

Price discovery and common factor models

Abstract If a financial asset is traded in more than one market, common factor models may be used to measure the contribution of these markets to the price discovery process. We examine the relationship between the Hasbrouck (J. Finance (50) (1995) 1175) and Gonzalo and Granger (J. Bus. Econ. Stat. 13 (1995) 27) common factor models. These two models complement each other and provide different views of the price discovery process between markets. The Gonzalo and Granger model focuses on the components of the common factor and the error correction process, while the Hasbrouck model considers each markets contribution to the variance of the innovations to the common factor. We show that the two models are directly related and provide similar results if the residuals are uncorrelated between markets. However, if substantive correlation exists, they typically provide different results. We illustrate these differences using analytic examples plus a real world example consisting of electronic communications networks (ECNs) and other Nasdaq market makers.

Price and volatility spillovers in Scandinavian stock markets

Abstract New evidence is provided on price and volatility spillovers among the Danish, Norwegian, Swedish, and Finnish stock markets. The impact of good news (market advances) and bad news (market retreats) is described by a multivariate Exponential Generalized Autoregressive Conditionally Heteroskedastic (EGARCH) model. Volatility transmission is asymmetric, spillovers being more pronounced for bad than good news. Significant price and volatility spillovers exist but they are few in number.

Price discovery and volatility spillovers in the DJIA index and futures markets

The Dow Jones Industrial Average (DJIA) is the most widely quoted stock index worldwide. This article examines the minute‐by‐minute price discovery process and volatility spillovers between the DJIA index and the index futures recently launched by the CBOT. The Hasbrouck (1995) cointegrating model suggests that most of the price discovery takes place at the futures market. However, by examining the volatility spillovers between the markets based on a bivariate EGARCH model, a significant bidirectional information flow is found. That is, innovations in one market can predict the future volatility in another market, but the futures market volatility‐spillovers to the stock market more than vice versa. Both markets also exhibit asymmetric volatility effects, with bad news having a greater impact on volatility than good news.

Price discovery in the German equity index derivatives markets

This article examines the intraday price discovery process among stock index, index futures, and index options in Germany using DAX index securities and intraday transactions data. The three index securities contribute to a common factor, but the spot index and index futures have substantially larger information shares than index options. Moreover, the returns of the three index securities exhibit feedback effects, with futures being dominant. Because the trading costs of the futures appear to be the lowest of the three and those of the options to be the highest, the results are consistent with the transaction cost hypothesis.

Cointegration tests with conditional heteroskedasticity

Abstract We examine the performance of Johansens (1988) likelihood ratio tests for cointegration in the presence of GARCH and compare with other cointegration tests. The tests tend to overreject the null hypothesis of no cointegration in favor of finding cointegration, but the problem is generally not very serious.

Intraday Price Discovery in the DJIA Index Markets

This paper explores the dynamics of price discovery between the Dow Jones Industrial Average (DJIA) index and its three derivative products: the DIAMOND exchange-traded fund (ETF), the floor-traded regular futures, and the electronically traded mini futures. Even though the American Stock Exchange is the primary listing exchange for the ETF, the analysis indicates that the electronically traded ETF on the Archipelago (ArcaEx) electronic communications network dominates the price discovery process for DIAMOND shares. The E-mini futures contribute the most to price discovery, followed by the ArcaEx DIAMOND. The DJIA index and regular futures contribute least to price discovery. The analysis is repeated using the derivatives of the S&P 500 index as a robustness check. The results indicate that multi-market trading ensures greater pricing efficiency. Informed traders favor electronic trading because of immediate and anonymous trade execution.

The relationship between US and Canadian wheat futures

The purpose of this paper is to investigate the relationship between US and Canadian wheat futures prices in order to analyse the degree of information spillover between the futures exchanges of both countries. Although considerable research has focused on the relationship between US and Canadian equity markets, little work has been conducted on their respective future markets. The increase in market-oriented trade agreements and the decrease of governmental presence in the agricultural sector adds to the importance and timeliness of such a study. The results show that both the US and Canadian wheat futures prices are an integrated series of order one, and that the two series are cointegrated. Although the evidence shows an equilibrium relationship in the long run, short-run dynamics exhibit no such dependencies. These results are relevant for various market participants, including farmers, grain merchants, speculators, exchanges, and regulatory agencies.

Market microstructure of FT‐SE 100 index futures: An intraday empirical analysis

This article examines the market microstructure of the FT‐SE Index futures market by analyzing the intraday patterns of bid‐ask spreads and trading activity. The patterns are remarkably different from those of stock and options markets because of the futures markets open outcry system with frenzied scalpers/short‐term marketmakers. Spreads are stable over the day, but decline sharply at the close and increase when U.S. macroeconomic news is distributed. Traders actively trade at the open with narrow spreads and large trade sizes. Volatility and volume have higher values at the open and close and when U.S. news is released. The overall results suggest that information asymmetry in the index futures market is insignificant, and traders find it easy to control inventory. The results are also broadly consistent with the Grossman and Miller (1988) model that describes liquidity as the price of transaction demand for immediacy.

Round-the-clock market efficiency and home bias: Evidence from the international Japanese government bonds futures markets

Abstract This paper examines how information is processed between almost identical international futures markets: London (LIFFE) and Tokyo (TSE) JGB futures. In these markets, variations in open-to-open changes are virtually the same as those of close-to-close changes, suggesting that information is transmitted efficiently across markets with small opening pricing errors. The overall results confirm market efficiency around the clock, yet the intraday U-shaped patterns in volume/volatility of the London JGB futures suggest home bias in international investments, indicating a less global view of trading than expected. Specifically, at the LIFFE open, London investors rush to rebalance portfolios instead of doing so at the TSE close, which is only one hour before the LIFFE opens.

The international transmission of information in Eurodollar futures markets: a continuously trading market hypothesis

Abstract This paper studies the transmission of information in three Eurodollar futures markets, the IMM, SIMEX and LIFFE. The results show that relevant information is revealed during the trading hours of the IMM and LIFFE, but not the SIMEX. The interest rates of the three markets are cointegrated with a single common stochastic trend. Granger-causality runs from the market that is placed in the last trading order within 24 hours in the vector error correction model and this causal relationship is shorter than one day. An approach of variance decomposition and impulse response functions exploring the common factor in the cointegration system is employed. Analogous to the causality results, the common factor is driven by the last trading market in the 24-hour trading sequence. Specifically, each market, while it is trading, impounds all the information and rides on the common stochastic trend. The overall results suggest that these three markets can be considered one continuously trading market.