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Transactions Data (transactions + data)

Distribution by Scientific Domains
Business, Economics, Finance and Accounting100%

Selected Abstracts

An Intraday Examination of the Components of the Bid,Ask Spread

FINANCIAL REVIEW, Issue 4 2002
Thomas H. McInish
Using transactions data for a sample of NYSE stocks, we decompose the bid,ask spread (BAS) into order,processing (OP) and asymmetric information (AI) components using the techniques of George, Kaul, and Nimalendran (1991) and Madhavan, Richardson, and Roomans (1997). McInish and Wood (1992) demonstrate that the intraday behavior of BASs can be explained by variables measuring activity, competition, risk, and information. We investigate whether these variables explain the behavior of the OP and AI components of the spread over the trading day. We conclude that, on balance, the variables that determine the aggregate BAS also determine its intraday components. [source]

Information, Trading, and Product Market Interactions: Cross-sectional Implications of Informed Trading

THE JOURNAL OF FINANCE, Issue 1 2008
HEATHER E. TOOKES
ABSTRACT I present a simple model of informed trading in which asset values are derived from imperfectly competitive product markets and private information events occur at individual firms. The model predicts that informed traders may have incentives to make information-based trades in the stocks of competitors, especially when events occur at firms with large market shares. In the context of 759 earnings announcements, I use intraday transactions data to test the hypothesis that net order flow and returns in the stocks of nonannouncing competitors have information content for announcing firms. [source]

Box-spread arbitrage efficiency of Nifty index options: The Indian evidence

THE JOURNAL OF FUTURES MARKETS, Issue 6 2009
VipulArticle first published online: 1 APR 200
This study examines the market efficiency for the European style Nifty index options using the box-spread strategy. Time-stamped transactions data are used to identify the mispricing and arbitrage opportunities for options with this modelfree approach. Profit opportunities, after accounting for the transaction costs, are quite frequent, but do not persist even for two minutes. The mispricing is higher for the contracts with higher liquidity (immediacy) risk captured by the moneyness (the difference between the strike prices and the spot price) and the volatility of the underlying. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 29:544,562, 2009 [source]

Cross-market efficiency in the Indian derivatives market: A test of put,call parity

THE JOURNAL OF FUTURES MARKETS, Issue 9 2008
VipulArticle first published online: 30 JUL 200
This study examines the cross-market efficiency of the Indian options and futures market using model-free tests. The put,call,futures and put,call,index parity conditions are tested for European style Nifty Index options. Thirty-five-month time-stamped transactions data are used to identify mispricing. Frequent violations of both forms of put,call parity are observed. The restriction on short sales largely accounts for the put,call,index parity violations. There are numerous put,call,futures arbitrage profit opportunities even after accounting for transaction costs, which vanish quickly. Put options are overpriced more often than call options. The mispricing shows specific patterns with respect to time of the day, moneyness, volatility, and days to expiry. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:889,910, 2008 [source]

The Impact of Day-Trading on Volatility and Liquidity,

ASIA-PACIFIC JOURNAL OF FINANCIAL STUDIES, Issue 2 2009
Jay M. Chung
Abstract We examine day-trading activities for 540 stocks traded on the Korea Stock Exchange using transactions data for the period from 1999 to 2000. Our cross-sectional analysis reveals that day-traders prefer lower-priced, more liquid, and more volatile stocks. By estimating various bivariate VAR models using minute-by-minute data, we find that greater day-trading activity leads to greater return volatility and that the impact of a day-trading shock dissipates gradually within an hour. Past return volatility also positively affects future day-trading activity. We also find that past day-trading activity negatively affects bid-ask spreads, and past bid-ask spreads negatively affect future day-trading activity. Finally, we find that day-traders use short-term contrarian strategies and their order imbalance affects future returns positively. This result is consistent with a cyclical behavior of day-traders who concentrate their buy or sell trades at the bottom or peak of the short-term price cycles, respectively. [source]

Do Sales Prices Overstate Underlying House Prices in Market Downturns?

CANADIAN JOURNAL OF ADMINISTRATIVE SCIENCES, Issue 4 2002
Evidence from the Canadian House Price Crash of 199
Over the last decade there has been a mounting realization that the quality-adjusted price of properties that sell may be quite different from the quality-adjusted price of all properties (Gatzlaff & Haurin, 1998). The difference is apt to be especially marked during downturns. Dependence on price indexes based on transactions data could result in overoptimistic appraisals by mortgage lenders during the early quarters of downturns. This paper provides evidence on this issue by examining the residential real estate crash at the start of the 1990s in Canadian cities, especially Toronto. The plunge in prices estimated here for Toronto is 17%. We estimate the drop in the transactions price using MLS data, which are not quality adjusted, supplemented by Royal LePage data, which are. We estimate the drop in the price of houses in the stock using hedonic indexes based on home owners' valuations; outlier observations are cut from the sample on the basis of the DFFITS criterion. The hypothesis of equality of the drop shown by the two measures is strongly rejected, for Toronto, and is also rejected for several other cities. Résumé Au cours de la dernière décennie, on s'est progressivement rendu-compte du fait que le prix, ajusté pour la qualité, des maisons vendues peut être différent du prix, ajusté pour la qualité, des maisons en général (Gatzlaff & Haurin, 1998). La différence entre ces prix est particulièrement marquée en période de marasme. La dépendance sur des indexes de prix basés sur des données transactionnelles peut amener les prêteurs hypothécaires à faire des évaluations trop optimistes durant les premiers trimestres d'une période de marasme. L'article qui suit s'interroge sur la justesse de cette hypothèse en étudiant l'effondrement du marché immobilier au début des années 90 dans des grandes villes canadiennes, en particulier, dans la ville de Toronto. Nous estimons que la chute des prix à Toronto s'élève à 17 %. Nous évaluons la chute des prix de transactions immobilières à partir d'une banque de données MLS, qui n'est pas ajustée pour la qualité, et nous ajoutons celles-ci à d'autres données de Royal LePage, qui elles sont ajustées pour la qualité. Nous évaluons la chute des prix des maisons dans l'inventaire à l'aide d'indicateurs hédoniques basés sur les évaluations des propriétaires; les données excentrées sont enlevées de l'échantillon à partir du critère DFFITS. L'hypothèse de l'égalité des chutes de prix indiquée dans les deux mesures ne s'applique absolument pas à Toronto, ni à plusieurs autres villes. [source]