Nonstationarity of Beta and Tests of Market Efficiency

McDonald, Bill; Nichols, William D.

doi:10.1111/j.1475-6803.1984.tb00383.x

Cited by 10 publications

(3 citation statements)

References 16 publications

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“…The greater the amount and significance of instability, the more doubt is cast on early studies that have (often implicitly) relied on parameter stability. Examples are studies of market efficiency [29] or those using the cumulative residuals technique [25]. To the extent that the techniques used here are capable of identifying shift points and stable regimes, the problem of nonstationarity can be reduced by using timedependent parameters, and more accurate studies are possible.…”

Section: Introductionmentioning

confidence: 99%

A Shifting Regimes Approach to the Stationarity of the Market Model Parameters of Individual Securities

Hays¹,

Upton²

1986

The Journal of Financial and Quantitative Analysis

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Section: Introductionmentioning

confidence: 99%

A Shifting Regimes Approach to the Stationarity of the Market Model Parameters of Individual Securities

Hays¹,

Upton²

1986

The Journal of Financial and Quantitative Analysis

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“…As a result, stock price movements are become more varying and have an effect on the difficulty of predicting the returns of securities because they become unstable all the time [11]. The consequences of the difficult conditions of predicting returns are that the distribution of historical data in the stock market tends to be non-normal [19]), clustered volatility [7]), heteroskedastic [15], and nonstationary [13], [14).…”

Section: Rit -Rft = αI + Bi(rmt -Rft) + Sismbt + Hihmlt + Mimomt + εImentioning

confidence: 99%

How Well the Implementation of Carhart Model in Market Overreaction Condition? Evidence in Indonesia Stock Exchange

Sembiring¹

2018

IJET

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This study aims to determine an ability of the four-factor model of Carhart in explaining the portfolio returns formed in condition of market overreaction. The four-factor model is basically a model proposed by Fama and French and then developed by Carhart which adds price momentum factor into the model. While market overreaction is a market condition caused by excessive reactions from investors when receiving information. The portfolios used are the winner and loser formed based on the returns of each portfolio to the average of the returns. Both portfolio consist are the stocks of non-financial sector in Indonesia Stock Exchange during the period July 2005 - December 2015. The data used are the Composite Stock Price Index (CSPI), stock market capitalization, book to market ratio of each shares and the difference of returns of the loser over of the winner, as an indicator of price momentum factor that formed in market overreaction condition characterized by occurance the reversal of returns.The results show that the four-factor model can explain the portfolio return well. Implementation of the GARCH (1,1) model to improve the accuracy of the estimation results also shows similar findings.

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“…Eighteen months of post-announcement data were needed to calculate the t + 1 through t + 18 residual returns. Therefore, the sample included no stock announcement dates that occurred after June 1975 ( - 18). The maximum number of monthly portfolios that could have been formed was 175 'Since the Nichols and Brown [ZO] study reported market inefficiencies in the 1968 to 1975 period (the late period), the Group I securities were further split into early and late periods.…”

Section: Endnotesmentioning

confidence: 99%

Stock Splits and Market Anomalies

Nichols

McDonald

1983

The Financial Review

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Previous studies of market efficiency have reported conflicting results when examining stock splits. Recent studies reporting market inefficiencies have made several methodological improvements, but have failed to control for the possible confounding effects of “unexpected” changes in corporate earnings announced near the stock split event. Stock splits are often issued around the time that firms experience large increases in corporate earnings. Therefore, an explicit treatment of earnings announcements in an event study of stock splits may yield further insights. This study found no market inefficiencies associated with splitting securities that experienced moderate changes in corporate earnings. However, anomalies were associated with splitting securities that experienced large increases in corporate earnings. These results suggest that previous findings of market inefficiencies, attributable solely to the stock split event, may be due in part to unexpected changes in corporate earnings.

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Nonstationarity of Beta and Tests of Market Efficiency

Cited by 10 publications

References 16 publications

A Shifting Regimes Approach to the Stationarity of the Market Model Parameters of Individual Securities

A Shifting Regimes Approach to the Stationarity of the Market Model Parameters of Individual Securities

How Well the Implementation of Carhart Model in Market Overreaction Condition? Evidence in Indonesia Stock Exchange

Stock Splits and Market Anomalies

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