Turn-of-the-month Research Articles

Turn of the Month and Turn of the Month Surrounding Days Effects in Istanbul Stock Exchange

We present evidence on the existence of the turn of the month and what we call turn of the month surrounding days effect in the I . stanbul Stock Exchange (ISE) for the period between 1988 and 1999, using ISE National 100 Composite Index and 30 most highly traded stocks of ISE (ISE 30 stocks). The usual definition of the turn, that is, days –1 to +4, is found to be statistically significant at the 10 per cent level for ISE National 100 Composite Index with comparably higher average returns than the rest of the month. However, the results obtained for the days surrounding the turn, that is, the period consisting of days –4 to –2 and +5 to +9, are statistically much more crucial than the results for the turn period itself. The average return in the turn of the month surrounding days is drastically smaller than the average return in the rest of the month, and the results are statistically significant at the 1 per cent level for the index. In the analysis of ISE 30 stocks individually, for the turn period, it is observed that while only seven of the ISE 30 stocks have significant F-statistics, average returns for all stocks without exception for the turn period are higher than the rest of the month. For the surrounding days, confirming the strange characteristics obtained for the index, 19 of the ISE 30 stocks have significant F-statistics (13 of them at the 1 per cent level) and there is not a single stock whose average return for the turn of the month surrounding days is higher than the average return for the rest of the month.

The turn-of-the-month effect still lives: the international evidence

This paper examines 19 country stock market indices for recent evidence of the turn-of-the-month (TOM) pattern in daily stock returns using both parametric and nonparametric measures to address concerns regarding methodologies applied in prior anomalies studies. We find that the 4-day TOM period accounts for 87% of the monthly return, on average, across countries, in the stock markets of 15 countries where the TOM pattern exists. These countries account for 77% of the foreign market capitalization value. The parametric and nonparametric results provide information regarding the degree to which distributional assumption violations may lead to incorrect conclusions.

Calendar anomalies in the Turkish foreign exchange markets

This paper investigates calendar anomalies in the Turkish foreign exchange markets during 1986–1994 period. Changes in the free market and official daily exchange rates between the Turkish lira (TL) and US dollar (USD) and the German mark (DM) are examined for empirical regularities on different days of the week, around the turn of the month and before holidays. The findings reveal that free market rates exhibit day-of-the-week and week-of-month effects. In addition free market DM returns display a holiday anomaly. These calendar anomalies are explained by cash disbursement patterns, together with currency substitution in the economy. The impact of treasury auctions and banks' management of liquidity on day-of-the-week effect is also discussed.

Dangers of data mining: The case of calendar effects in stock returns

Economics is primarily a non-experimental science. Typically, we cannot generate new data sets on which to test hypotheses independently of the data that may have led to a particular theory. The common practice of using the same data set to formulate and test hypotheses introduces data-mining biases that, if not accounted for, invalidate the assumptions underlying classical statistical inference. A striking example of a data-driven discovery is the presence of calendar effects in stock returns. There appears to be very substantial evidence of systematic abnormal stock returns related to the day of the week, the week of the month, the month of the year, the turn of the month, holidays, and so forth. However, this evidence has largely been considered without accounting for the intensive search preceding it. In this paper we use 100 years of daily data and a new bootstrap procedure that allows us to explicitly measure the distortions in statistical inference induced by data mining. We find that although nominal p-values for individual calendar rules are extremely significant, once evaluated in the context of the full universe from which such rules were drawn, calendar effects no longer remain significant.

Liquidity and the turn-of-the-month effect: evidence from Finland

This paper uses Finnish data to investigate the impact of liquidity on the turn-of-the-month (TOM) effect in stock returns. The empirical findings support the hypothesis that higher returns at the TOM than during the rest of the month is associated with increased liquidity, as measured by different measures of trading activity. Moreover, consistent with the hypothesis of increased buying pressure at the TOM, the number of bid quotes increases at the month-end. In addition, there is more in-house trading (internalization) at the TOM. This finding is consistent with the hypothesis that liquidity increases internalized trading, indicating that the TOM effect manifests itself with respect to the trading venue.

A Trading Strategy for the Indian Stock Market: Analysis and Implications

A curious seasonality reported in finance is the monthly effect which implies that the mean daily return for stock is positive and higher during the first half of the month than the second half. Another related anomaly is the turn-of-the-month effect which is said to exist when the average daily return at the turn of the month is significantly higher than the daily return on the remain ing days of the month. This paper examines both the monthly effect and the turn-of-themonth effect in the Indian stock market by applying two different approaches: calendar day approach and trading day approach. The results of both the approaches reveal significantly higher return at the first half of the month than that of the second half and abnormally high returns at the turn of the month. Various explanations for the ob served anomalies have been considered including the problem of ‘data mining,’ proxy of other anomalies, etc., but none could provide adequate explanations for the observed intra-month return regularities. However, based on the findings, the study tries to evolve certain trading strategies which would benefit in the decision making of the investors concerned with timing of stock purchases and sales.

Seasonalities and the 1987 crash: The international evidence

This paper examines several seasonal regularities in stock returns before and after the international crash of October 1987. The analysis investigates the day of the week, pre- and post-holiday, turn of the year, turn of the month, and month of the year effects in Pacific Rim and U.S. equity markets. The incidence of return regularities decreases significantly in the period following the crash. We posit that an alteration of the returns generating process in these markets is the most likely cause of the change in the trading patterns.

The CAPM and the Calendar: Empirical Anomalies and the Risk-Return Relationship

Tinic and West (1984) argue that a tradeoff between risk and return exists only in January. This study demonstrates that it is not just the January Effect on stock returns which is related to the measured risk-return relationship and how that measure is apparently affected by the calendar. Other returns anomalies can also be paired with a conclusion about the relationship between risk and return. For example, risk appears to be rewarded at the turn of the month but not during the rest of the year and late in the week but not early in the week. This paper argues that, given the returns anomalies, the corresponding calendar effects on the risk-return relationship are consistent with the CAPM. Thus, the anomaly to be explained is not the relationship between risk and return focused on by Tinic and West (1984) but rather the calendar related variations in the returns themselves.

A COMPREHENSIVE EXAMINATION OF VOLUME EFFECTS AND SEASONALITY IN DAILY SECURITY RETURNS

AbstractIn this study, an integrated model of return seasonality is developed and the hypothesis that seasonality is associated with changes in relative trading volume is examined. Return regularities associated with the turn of the month, the week of the month, and holiday closings are documented. Beyond these effects, neither the turn of the year nor the January effect is significant for large firms. Relative volume is shown to display calendar regularities similar to those in returns, and tests indicate a causal relationship flowing from volume to returns.

Anomalies: Seasonal Movements in Security Prices II: Weekend, Holiday, Turn of the Month, and Intraday Effects

This feature will report successful searches for disconfirming evidence--economic anomalies. As suggested by Thomas Kuhn, an economic anomaly is a result inconsistent with the economics paradigm. Economics is distinguished from other social sciences by the belief that most (all?) behavior can be explained by assuming that agents have stable, well-defined preferences and make rational choices consistent with those preferences in markets that (eventually) clear. An empirical result is anomalous if it is difficult to “rationalize,” or if implausible assumptions are necessary to explain it within the paradigm. In the previous issue, I reviewed the peculiar behavior of security prices in January. Stock prices tend to rise in January, particularly the prices of small firms and firms whose stock price has declined substantially over the past few years. Also, risky stocks earn most of their risk premiums in January. This issue will conclude our survey of seasonal anomalies in security prices with a review of four additional effects: the behavior of prices over weekends, before holidays, at the turn of each month, and within the day.