Measuring equity market integration using uncorrelated information flows: Tokyo,London and New York

Equity markets do not pass all overnight information into prices instantly at the opening of trade. We adjust open-to-close return series for non-instantaneous information absorption and then use adjusted series to measure integration among three major equity markets. Because the adjusted daytime return series are uncorrelated, we can accurately measure the size, and identify the sources, of transmissions. Overnight news, as represented by foreign open-to-close returns, explains 13% of opening price variation (close-to-open returns) in New York, 14% in Tokyo and 30% in London. For New York and Tokyo, the largest influences come from the market that trades immediately prior (London and New York respectively) whereas opening price variation in London is linked closer with New York than Tokyo. Foreign volatility spillovers are also significant, and subject to asymmetric effects.     

After-Hours Stock Prices and Post-Crash Hangovers

After-hours pricing in foreign equity markets of multiple-listed U.S. securities appeared to be efficient in predicting New York prices in the weeks immediately following the October 1987 crash but relatively uninformative in succeeding months. By contrast, daily changes in New York prices appear to be efficiently incorporated in after-hours trading on both the Tokyo and London exchanges throughout the sample period. This paper suggests that the asymmetry and temporal variations in cross-market correlations are consistent with rational investor behavior in equity markets with nonzero transaction costs and time-varying share price volatility.     

Price Interactions in a Sequential Global Market: Evidence from the Cross-listed Stocks

In this paper, we investigate the pattern of dynamic interactions among the prices of those stocks that are cross-listed on the three major stock markets of the world, i.e. New York, London and Tokyo. Major findings are: first, regardless of the nationality of stocks, innovations in the 'home' market returns are always fed into the returns in the 'overseas' markets, with the former causing the latter in the Granger sense. However, innovations in the New York market returns of foreign stocks are fed back into their respective home markets, contributing to the price discovery there. Second, the 'succeeding' overseas market, which operates immediately after the home market, plays a dual-role: it conducts the home market innovations to the next-opening overseas market, as well as adds its own innovations. Third, the exchange rate changes substantially influence the overseas market returns, but not the home market returns. The exchange rates appear to play a role in the transmission mechanism mainly via the inter-market price parity.     

Bivariate Nonparametric Density Estimation of Stock Prices and Volume

This paper comprehensively investigates the joint movement of stock prices and trading volume of New York and Tokyo stock markets by undertaking nonparametric density estimation. Bivariate nonparametric density estimation has been reported as a powerful tool for revealing complicated relations between two variables. In application to finance, it is important to use a method robust for heavy-tailed densities, since the distributions of asset price changes are known to have heavy tails, and information about sudden and large price changes is contained in the tails. The empirical regularities found in this paper are mostly consistent with previous literature, but partially disagrees with the work of Gallant et al. (1992).     

Price Limit Performance: Evidence from the Tokyo Stock Exchange

Price limit advocates claim that price limits decrease stock price volatility, counter overreaction, and do not interfere with trading activity. Conversely, price limit critics claim that price limits cause higher volatility levels on subsequent days (volatility spillover hypothesis), prevent prices from efficiently reaching their equilibrium level (delayed price discovery hypothesis), and interfere with trading due to limitations imposed by price limits (trading interference hypothesis). Empirical research does not provide conclusive support for either positions. We examine the Tokyo Stock Exchange price limit system to test these hypotheses. Our evidence supports all three hypotheses suggesting that price limits may be ineffective.     

中国黄金期货价格影响因素研究

采用线性回归、Breush-Godfrey LM相关性检验、VAR模型的方差分解和脉冲响应图、价格波动率的单位根检验和Granger格兰杰因果检验等方法对中国黄金期货价格的影响因素进行实证研究。结果表明:上海、香港、伦敦的黄金现货和纽约黄金期货价格以及美元指数是影响中国黄金期货价格的主要因素,而中国黄金期货价格的波动显著受到伦敦黄金现货价格波动和纽约黄金期货价格波动的影响。虽然目前中国黄金期货市场已具备一定的规避风险功能,且初具价格发现功能,但国际影响力有待继续提升。     

人民币汇率与我国股价、房价的联动关系研究

近年来,我国人民币汇率形成机制、股票市场和房地产市场发生了巨大变化,人民币汇率和股价、房价之间的信息传导和波动关联备受瞩目。本文采用VAR-MGARCH-BEKK模型,分析了我国人民币汇率、股价和房价之间的联动关系。研究结果表明,从波动的溢出效应来看,人民币汇率的波动率、股票价格的增长率和房地产价格的增长率之间存在非常明显的波动溢出效应;从资产价格的水平影响来看,人民币汇率与股票价格、房地产价格等国内资产价格的水平相关性较弱,而股票价格对房地产价格的影响较明显,并就该结论提出了相关的理论解释和政策建议。     

A Likelihood Ratio Test of Price Volatilities: Comparing Stock Index Spot and Futures

This paper uses three methods to estimate the price volatility of two stock market indexes and their corresponding futures contracts. The classic variance measure of volatility is supplemented with two newer measures, derived from the Garman-Klass and Ball-Torous estimators. A likelihood ratio test is used to compare the classic variance measure of price volatilities of two stock market indexes and their corresponding futures contracts during the bull market of the 1980s. The stock market volatilities of the Standard & Poor's 500 (S&P 500) and New York Stock Exchange (NYSE) indexes were found to be significantly lower than their respective futures price volatilities. Since information may flow faster in the futures markets than in the corresponding stock market, our results support Ross's information-volatility hypothesis. It was also noted that the NYSE spot volatility was lower than the S&P 500 spot volatility. If the rate of information flow and firm size are positively related, then the lower NYSE spot volatility is explained by the size effect. The futures price volatilities for the two indexes were insignificantly different from each other. With stock index spot-futures price correlations approaching unity, one implication of our results for index futures activity is that smaller positions in futures contracts may suffice to achieve hedging or arbitrage goals.     

The macroeconomic determinants of technology stock price volatility

Stock prices reflect the value of anticipated future profits of companies. Since business cycle conditions impact the future profitability of firms, expectations about the business cycle will affect the current value of firms. This paper uses daily and monthly data from July 1986 to December 2000 to investigate the macroeconomic determinants of US technology stock price conditional volatility. Technology share prices are measured using the Pacific Stock Exchange Technology 100 Index. One of the novel features of this paper is to incorporate a link between technology stock price movements and oil price movements. The empirical results indicate that the conditional volatilities of oil prices, the term premium, and the consumer price index each have a significant impact on the conditional volatility of technology stock prices. Conditional volatilities calculated using daily stock return data display more persistence than conditional volatilities calculated using monthly data. These results further our understanding of the interaction between oil prices and technology share prices and should be of use to investors, hedgers, managers, and policymakers.     

Option markets and implied volatility: Past versus present

Traders in the nineteenth century appear to have priced options the same way that twenty-first-century traders price options. Empirical regularities relating implied volatility to realized volatility, stock prices, and other implied volatilities (including the volatility skew) are qualitatively the same in both eras. Modern pricing models and centralized exchanges have not fundamentally altered pricing behavior, but they have generated increased trading volume and a much closer conformity in the level of observed and model prices. The major change in pricing is the sharp decline in implied volatility relative to realized volatility, evident immediately upon the opening of the CBOE.