Overnight and Daytime Stock Return Dynamics on the London Stock Exchange

Overnight and Daytime Stock Return Dynamics on the London Stock Exchange
Author: Victor Ng
Publisher:
Total Pages: 14
Release: 2006
Genre:
ISBN:

We explore the time series properties of overnight and daytime returns on the London Stock Exchange's primary stock market index, the FTSE-100 on the over the 1984-1991 period. We use a modified GARCH model to specify daytime and overnight return dynamics where (a) intra-day returns can have different impacts and persistence on stock return volatility, (b) return effects on volatility can be asymmetric and (c) intra-day returns can follow conditional distributions with different fourth moments. We uncover important changes in return dynamics and conditional fourth moments following the stock exchange's major restructuring called quot;Big Bangquot;, which merged broker and dealer functions and after the1987 stock market crash.

Information, Trading and Stock Returns

Information, Trading and Stock Returns
Author: K. C. Chan
Publisher:
Total Pages: 60
Release: 1994
Genre: Stock quotations
ISBN:

This paper compares the intra-day patterns on the NYSE and AMEX of volatility, trading volume and bid-ask spreads for European dually- listed stocks, Japanese dually-listed stocks also listed in London, and Japanese dually-listed stocks not listed in London with American stocks of comparable average trading volume and volatility. It is shown that the intra-day patterns for these stocks are remarkably similar even though the public information flows differ markedly across these stocks during the trading day. In the morning, Japanese stocks have the greatest volatility and volume, followed by European stocks and American stocks. These rankings are reversed in the afternoon. We argue that these patterns are consistent with markets reacting to the overnight accumulation of public information which is greatest for Japanese stock and smallest for American stocks and inconsistent with the view that early morning volatility can be attributed to monopolistic specialist behavior.

Returns Synchronization and Daily Correlation Dynamics between International Stock Markets

Returns Synchronization and Daily Correlation Dynamics between International Stock Markets
Author: Martin Martens
Publisher:
Total Pages: 34
Release: 1999
Genre:
ISBN:

The use of close-to-close returns underestimates returns correlation because international stock markets have different trading hours. With the availability of 16:00 (London time) stock market series, we find dynamics of daily correlation and daily covariance, estimated using two non-synchroneity adjustment procedures, to be substantially different from their synchronous counterparts. We find volatility spillovers from the US to the UK and France, and there is also evidence of reverse spillovers which is not documented before. Daily covariance increases during volatile periods. But, unlike previous findings, the increase in daily correlation is prominent only under extremely adverse conditions when a large negative return has been registered.

Is Risk Higher During Non-Trading Periods? The Risk Trade-Off for Intraday Versus Overnight Market Returns

Is Risk Higher During Non-Trading Periods? The Risk Trade-Off for Intraday Versus Overnight Market Returns
Author: Christoph Riedel
Publisher:
Total Pages: 36
Release: 2015
Genre:
ISBN:

We study the magnitude of tail risk -- particularly lower tail downside risk -- that is present in intraday versus overnight market returns and thereby examine the nature of the respective market risk borne by market participants. Using the Generalized Pareto Distribution for the return innovations, we use a GARCH model for the conditional market return components of major stock markets covering the U.S., France, Germany and Japan. Testing for fat-tails and tail index equality, we find that overnight return innovations exhibit significant tail risk, while intraday innovations do not. We illustrate this volatility versus tail risk trade-off based on conditional Value-at-Risk calculations. Our results show that overnight downside market risk is composed of a moderate volatility risk component and a significant tail risk component. We conclude that market participants face different intraday versus overnight risk profiles and that a risk assessment based on volatility only will severely underestimate overnight downside risk.

Stock Returns in Thinly Traded Markets

Stock Returns in Thinly Traded Markets
Author: Kirt C. Butler
Publisher:
Total Pages:
Release: 1998
Genre:
ISBN:

We examine the share-price behavior of thinly traded NASDAQ National Market System stocks during periods when financial markets are open but the individual stocks do not trade. The absence of trade allows us to isolate the effect of nontrading from that of market closure. We find that nontrading stocks have negative mean returns and lower variances regardless of whether markets are open or closed. Two-day returns that include one nontrading day have a mean daily return of -0.226% compared to +0.164% for two-day returns over consecutive trading days. Two-day returns that include one nontrading day have only a 3.8% higher variance than one-day returns. We conclude that the relation between transaction arrival, mean returns, and volatility depends on whether a stock is trading and not simply on whether the market is open.

Statistical Methods in Finance

Statistical Methods in Finance
Author: G. S. Maddala
Publisher:
Total Pages: 760
Release: 1996-12-11
Genre: Business & Economics
ISBN:

A comprehensive reference work for teaching at graduate level and research in empirical finance. The chapters cover a wide range of statistical and probabilistic methods applied to a variety of financial methods and are written by internationally renowned experts.

Market Liquidity

Market Liquidity
Author: Thierry Foucault
Publisher: Oxford University Press
Total Pages: 531
Release: 2023
Genre: Capital market
ISBN: 0197542069

"The process by which securities are traded is very different from the idealized picture of a frictionless and self-equilibrating market offered by the typical finance textbook. This book offers a more accurate and authoritative take on this process. The book starts from the assumption that not everyone is present at all times simultaneously on the market, and that participants have quite diverse information about the security's fundamentals. As a result, the order flow is a complex mix of information and noise, and a consensus price only emerges gradually over time as the trading process evolves and the participants interpret the actions of other traders. Thus, a security's actual transaction price may deviate from its fundamental value, as it would be assessed by a fully informed set of investors. The book takes these deviations seriously, and explains why and how they emerge in the trading process and are eventually eliminated. The authors draw on a vast body of theoretical insights and empirical findings on security price formation that have come to form a well-defined field within financial economics known as "market microstructure." Focusing on liquidity and price discovery, the book analyzes the tension between the two, pointing out that when price-relevant information reaches the market through trading pressure rather than through a public announcement, liquidity may suffer. It also confronts many striking phenomena in securities markets and uses the analytical tools and empirical methods of market microstructure to understand them. These include issues such as why liquidity changes over time and differs across securities, why large trades move prices up or down, and why these price changes are subsequently reversed, and why we observe temporary deviations from asset fair values"--