Handbook of the Economics of Finance

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.

A Tale of Three Schools: Insights on Autocorrelations of Short-Horizon Stock Returns

The Investment Behavior and Performance of Various Investor Types: A Study of Finland's Unique Data Set

This paper investigates the relationship between stock indices, asset portfolios and macroeconomic variables in ten European countries. It is shown that employment, imports, inflation and interest rates are inversely related to stock prices. Expectations about future real activity, measures for money and the U.S. yield curve are positively related to stock prices. A portfolio of European stock indices was constructed and it is shown that this portfolio is the variable that most strongly explains the variation in the stock prices. The associations between stock prices and macroeconomic variables are shown to be strongest in Germany, the Netherlands, Switzerland and the United Kingdom. There is a high degree of similarity between the effects in the first three of these countries. In several instances the stock prices are related to historic value of economic variables indicating that predictive models can be constructed.

Stock prices, asset portfolios and macroeconomic variables in ten European countries

Beginning with Banz (1981), I review 30 years of research on the size effect in equity returns. Since Fama and French (1992), there has been a vigorous, ongoing debate on whether the size premium is a compensation for systematic risk. Since the late 1990s, research on the size effect has been characterized by two developments that are seemingly contradictory. At last, theoretical models have emerged in which the size effect arises endogenously as a result of systematic risk. However, recent empirical studies assert that the size effect has disappeared after the early 1980s. In this review, I address this disconnect between recent theoretical and empirical research.

Is Size Dead? A Review of the Size Effect in Equity Returns

This paper examines the properties of different market risk (beta) measures computed on daily data for a thin security market i.e. the Helsinki Stock Exchange in Finland. In accordance with the results by Dimson and Marsh (1983) the paper shows that differences in trading frequency between different stocks produce a serious bias towards what appears to be stability in estimated betas. Furthermore the paper shows that when betas are computed the exclusive use of stock prices based on actual trades will not solve the problem of a thin trading bias in measured stability of these beta estimates. In fact other methods proposed to cope with the thin trading problem seem to be at least as efficient as use of trade-to-trade returns. Finally betas corrected for differences in trading frequency are still shown to be statistically related for firm size.

Estimating betas on daily data for a small stock market

THIS NOTE REPORTS ON an empirical investigation into the relative importance of different explanations of market serial correlation. Market serial correlation taken as the first-order serial correlation in the logarithmic differences of a market index may apparently be explained by the serial correlation of individual stock returns. The other, less apparent, explanation advanced in the literature concerns nonsynchronous trading in individual stocks. Recently, Perry [9] and Atchinson, Butler, and Simonds [1]1 have shown that there seems to be yet an additional unexplained component present that tends to induce serial correlation in portfolio returns, at least in U.S. data. In this paper, the actual contribution of these explanations to the first-order autocorrelation of changes in the value-weighted market index on a markedly thin security market, the Helsinki Stock Exchange (HeSE)2 in Finland, will be examined. The HeSE is a specific case in the sense that its trading procedure may create additional first-order market serial correlation. We will show that the rules of the exchange produce additional intraday nonsynchroneity in stock returns and thus aggravate the problem of market serial correlation. An attempt to assess the importance of this additional cause of market serial correlation will also be made. In 1966, Lawrence Fisher [7] observed that an index return calculated on the basis of the latest recorded trading prices will tend to be serially correlated if share prices tend to react similarly to certain types of news. This will be the case when some share prices react almost immediately whereas others, simply because of an absence of trading, will experience a reaction delay. If nonsynchronous trading is taken to be the first cause of market serial correlation, the second one is the serial correlation of individual stock returns. Cohen, Hawawini, Maier, Schwartz, and Whitcomb [6] review the literature on why individual stock returns, especially in thin markets, may be serially corre-

Market Serial Correlation on a Small Security Market: A Note

This paper tests the Fisher hypothesis that real stock returns are independent of inflationary expectations, on data for the Finnish economy. A significant negative relationship is found when stock returns are regressed on the rate of inflation. A possible explanation is that higher inflation may proxy a drop in the money demand induced by a lower growth in real activity, which simultaneously implies a drop in expected future profits and thus a drop in stock prices. To test this hypothesis actual growth in real activity is included in the regression equation for aggregate stock returns. Significant negative coefficients are, however, still obtained for expected as well as unexpected inflation. It is further shown that these relations are quite insensitive to the specification of the expectations formation mechanism.

Stock returns, inflationary expectations and real activity

This paper advocates two ways to make more efficient use of available information in reducing the bias of the risk premium estimate in two-pass tests of the CAPM. First, explicit modelling of the time-variability of betas can improve the accuracy of the beta forecasts. Second, the cross-sectional information available can be exploited more efficiently using individual stocks instead of portfolios provided that noisy beta predictions are given a smaller weight than more accurate ones. This paper proposes an adjustment of the cross-sectional regressions of excess returns against betas to give larger weights to more reliable beta forecasts. A significant positive relationship between returns and the beta forecast is obtained when the proposed approach is applied to data from the Helsinki Stock Exchange, while the traditional Fama–MacBeth approach as such finds no relationship at all.

Accounting for the Accuracy of Beta Estimates in CAPM Tests on Assets with Time‐varying Risks

This note adds to previous Scandinavian evidence produced by the Jennergren & Korsvold (1974, 1975),' Jennergren (1975), Jennergren & ToftNielsen (1977), Korhonen (1977) and S0rensen (1982) studies of stock market return randomness. In daily data sets from the Oslo and Stockholm Stock Exchanges, Jennergren & Korsvold (1975) found evidence of nonrandomness in a majority of the 45 stocks studied. A similar result was later reported for the Copenhagen exchange by Jennergren & Toft-Nielsen (1977). Subsequent studies by Jennergren (1975) and S0rensen (1980) further indicated that the serial correlation inherent in Stockholm and Copenhagen data was strong enough to allow supernormal yields on simple filter strategies.2 The data for our study consist of daily trading or, when closings did not occur, bid prices adjusted for dividends and issues for all stocks quoted on the Helsinki Stock Exchange (HESE) between February 2, 1970 and December 31, 1981, along with data on daily trading volumes for the years 1977-81.3 The price file is based on the KOP-index file.4 Throughout this note, comparisons with previous results for other Scandinavian exchanges are made. Allowing for variations in sample periods, we attempt a study of whether a smaller annual turnover of an exchange effects the degree of nonrandomness exhibited by its stock returns. Of the

https://www.jstor.org/stable/info/3439949

Tom Berglund

Papers

Estimating betas on daily data for a small stock market

Market Serial Correlation on a Small Security Market: A Note

Stock returns, inflationary expectations and real activity

Accounting for the Accuracy of Beta Estimates in CAPM Tests on Assets with Time‐varying Risks

The Weak-Form Efficiency of the Finnish and Scandinavian Stock Exchanges: A Comparative Note on Thin Trading