Всего статей в данном разделе : 24
A New Look at the Monday Effect [статья]
Опубликовано на портале: 25-10-2007Ko Wang, John Erickson, Yuming Li Journal of Finance. 1997. Vol. 52. No. 5. P. 2171-2186.
It is well documented that expected stock returns vary with the day-of-the-week (the Monday or weekend effect). In this article we show that the well-known Monday effect occurs primarily in the last two weeks (fourth and fifth weeks) of the month. In addition, the mean Monday return of the first three weeks of the month is not significantly different from zero. This result holds for most of the subperiods during the 1962-1993 sampling period and for various stock return indexes. The monthly effect reported by Ariel (1987) and Lakonishok and Smidt (1988) cannot fully explain this phenomenon.
Опубликовано на портале: 25-10-2007Jacob Boudoukh, Matthew Richardson, Robert Whitelaw Review of Financial Studies. 1994. Vol. 7. No. 3. P. 539-573.
This article reexamines the autocorrelation patterns of short-horizon stock returns. We document empirical results which imply that these autocorrelations have been overstated in the existing literature. Based on several new insights, we provide support for a market efficiency-based explanation of the evidence. Our analysis suggests that institutional factors are the most likely source of the autocorrelation patterns.
Опубликовано на портале: 22-10-2007Michael R. Gibbons, Patrick Hess Journal of Business. 1981. Vol. 54. No. 4. P. 579-596.
Day of the Week Effect and Market Efficiency - Evidence from Indian Equity Market Using High Frequency Data of National Stock Exchange [статья]
Опубликовано на портале: 22-10-2007Manoj Dalvi, Golaka C. Nath
Опубликовано на портале: 22-10-2007Ercan Balaban Applied Economics Letters. 1995. Vol. 2. No. 5. P. 139-153.
The primary objective of this paper is to investigate day of the week effects in an emerging stock market of a developing country namely Turkey. Empirical results verify that although day of the week effects are present in Istanbul Securities Exchange Composite Index (ISECI) return data for the period January 1988-August 1994, these effects change in direction and magnitude through time.
Опубликовано на портале: 22-10-2007Anat R. Admati, Paul Pfleiderer Review of Financial Studies. 1989. Vol. 2. No. 2. P. 189-223.
This article develops a model in which pattern in buy and sell volume, order imbalances, and expected price changes arise endogenously. The model covers cases in which the market maker is competitive and is a monopolist. Our results provide an explanation for the existence of patterns in mean returns within the trading day and across trading days.
Опубликовано на портале: 22-10-2007Sunil Poshakwale Finance India. 1996. Vol. X. No. 3. P. 605-616.
Stock market efficiency is an important concept, for understanding the working of the capital markets particularly in emerging stock market such as India. The efficiency of the emerging markets assumes greater importance as the trend of investments is accelerating in these markets as a result of regulatory reforms and removal of other barriers for the international equity investments. There is enough evidence on market efficiency and day of the week effect in the developed markets, however, the same is not true for the emerging stock markets. This study provides empirical evidence on weak form efficiency and the day of the week effect in Bombay Stock Exchange over a period of 1987-1994. The results provide evidence of day of the week effect and that the stock market is not weak form efficient. The day of the week effect observed on the BSE pose interesting buy and hold strategy issues.
Explaining Monday Returns [статья]
Опубликовано на портале: 25-10-2007Paul Draper, Krishna Paudyal The Journal of Financial Research. 2002. Vol. 15. No. 4. P. 507-520.
The Monday effect is reexamined using two stock indexes and a sample of 452 individual stocks that trade on the London Stock Exchange. The results based on conventional test methods reveal a negative average return on Monday. Extending the analysis to examine the effects of various possible influences simultaneously, the average Monday return becomes positive and does not differ significantly from the average returns of most other days of the week. Fortnight, ex-dividend day, account period, (bad) news flow, trading activity, and bid-ask spread effects are all controlled for. The results broadly support the trading time hypothesis.
Опубликовано на портале: 25-10-2007Wilson Tong The Journal of Financial Research. 2000. Vol. 13. No. 4. P. 495-522.
Recent studies on the U.S. market find that the Monday effect is observed mainly when the rettim on the previous Friday is negative or when the Monday falls within the last two weeks of the month. I look for international evidence and examine whether such properties of the Monday effect are related to another anomalous phenomenon—high weekend correlation. By examining twenty-three equity market indexes, I find that the negative Friday is, in general, important to the Monday effect. Furthermore, Monday returns tend to be lowest on the fourth week of the month. Although high weekend correlation is also common to these markets, it seems not related to the bad-Friday factor and shows no seasonality across weeks of the month.
Опубликовано на портале: 03-12-2007Fisher Black Journal of Finance. 1986. Vol. 21. P. 529-543.
The effects of noise on the world, and on our views of the world, are profound. Noise in the sense of a large number of small events is often a causal factor much more powerful than a small number of large events can be. Noise makes trading in financial markets possible, and thus allows us to observe prices for financial assets. Noise causes markets to be somewhat inefficient, but often prevents us from taking advantage of inefficiencies. Noise in the form of uncertainty about future tastes and technology by sector causes business cycles, and makes them highly resistant to improvement through government intervention. Noise in the form of expectations that need not follow rational rules causes inflation to be what it is, at least in the absence of a gold standard or fixed exchange rates. Noise in the form of uncertainty about what relative prices would be with other exchange rates makes us think incorrectly that changes in exchange rates or inflation rates cause changes in trade or investment flows or economic activity. Most generally, noise makes it very difficult to test either practical or academic theories about the way that financial or economic markets work. We are forced to act largely in the dark
Опубликовано на портале: 01-11-2007Michael D. Atchison, Kirt C. Butler, Richard R. Simonds Journal of Finance. 1987. Vol. 42. No. 1. P. 111-118.
The theoretical portfolio autocorrelation due solely to nonsynchronous trading is estimated from a derived model. This estimated level is found to be substantially less than that observed empirically. The theoretical and empirical relationship between portfolio size and autocorrelation also is investigated. The results of this study suggest that other price-adjustment delay factors in addition to nonsynchronous trading cause the high autocorrelations present in daily returns on stock index portfolios
Partial Adjustment or Stale Prices? Implications from Stock Index and Futures Return Autocorrelations [статья]
Опубликовано на портале: 03-11-2007Dong-Hyun Ahn, Jacob Boudoukh, Matthew Richardson, Robert Whitelaw Review of Financial Studies. 2002. Vol. 15. No. 2. P. 655-689.
We investigate the relation between returns on stock indices and their corresponding futures contracts to evaluate potential explanations for the pervasive yet anomalous evidence of positive, short-horizon portfolio antocorrelations. Using a simple theoretical framework, we generate empirical implications for both microstructure and partial adjustment models. The major findings are (i) return autocorrelations of indices are generally positive even though futures contracts have autocorrelations close to zero, and (ii) these autocorrelation differences are maintained under conditions favorable for spot-futures arbitrage and are most prevalent during low-volume periods. These results point toward microstructure-based explanations and away from explanations based on behavioral models.
Portfolio Return Autocorrelation [статья]
Опубликовано на портале: 25-10-2007Timothy S. Mech Journal of Financial Economics. 1993. Vol. 34. No. 3. P. 307-334.
This paper investigates whether portfolio return autocorrelation can be explained by time-varying expected returns, nontrading, stale limit orders, market maker inventory policy, or transaction costs. Evidence is consistent with the hypothesis that transaction costs cause portfolio autocorrelation by slowing price adjustment. I develop a transaction-cost model which predicts that prices adjust faster when changes in valuation are large in relation to the bid-ask spread. Cross-sectional tests support this prediction, but time-series tests do not.
Price Momentum and Trading Volume [статья]
Опубликовано на портале: 02-11-2007Charles M.C. Lee, Bhaskaran Swaminathan Journal of Finance. 2000. Vol. 55. No. 5. P. 2017-2069.
This study shows that past trading volume provides an important link between ‘momentum’ and ‘value’ strategies. Specifically, we find that firms with high (low) past turnover ratios exhibit many glamour (value) characteristics, earn lower (higher) future returns, and have consistently more negative (positive) earnings surprises over the next eight quarters. Past trading volume also predicts both the magnitude and persistence of price momentum. Specifically, price momentum effects reverse over the next five years, and high (low) volume winners (losers) experience faster reversals. Collectively, our findings show that past volume helps to reconcile intermediate-horizon ‘underreaction’ and long-horizon ‘overreaction’ effects
Опубликовано на портале: 01-11-2007Jennifer Conrad, Mustafa N. Gultekin, Gautam Kaul Journal of Business and Economic Statistics. 1997. Vol. 15. No. 3. P. 379-386.
In recent years, several researchers have argued that the stock market consistently overreacts to new information, which, in turn, results in price reversals. Lehmann and others showed that a contrarian can make substantial profits in the short run by simply buying losers and selling winners. We, however, demonstrate that these profits are largely generated by the bid-ask bounce in transaction prices; accounting for this "bounce" by using bid prices eliminates all profits from price reversals for NASDAQ-NMS stocks and most of the profits for NYSE/AMEX stocks. Moreover, any remaining profits (regardless of their source) disappear at trivial levels of transactions costs.