January Returns Research Articles

The pricing of firms with expected losses/profits: The role of January

AbstractWe examine the role of January in the relation between expected losses/profits and future stock returns. We predict and find that the relation between expected losses/profits and future returns reverses from the usual positive relation in non‐January months to a negative one in January. The reverse January relation is consistent across sample years, is observed in the United States and international markets, and is incremental to other variables associated with January returns. At least part of the reverse January relation is explained by tax‐loss selling. Further analysis shows that the reverse January relation results in a temporary price drift away from fundamental value. In other words, we find that abnormal positive (negative) future returns do not always indicate past under(over)valuation. Overall, our results illustrate the importance of controlling for the effect of January when examining how investors price expected losses/profits.

Another look at anchoring and stock return predictability

The superior performance of a momentum strategy long in stocks trading near their 52-week high prices and short in stocks trading far from their 52-week high prices is well-documented. In contrast, recent research finds that a similar strategy based on historical high prices exhibits subsequent reversals instead. This paper shows that after excluding low-priced stocks and/or January returns from the sample, the stocks trading near their historical high prices, in fact, exhibit significant outperformance. In particular, in a sample without low-priced stocks, a strategy long in 10% of the stocks with prices nearest to their historical high prices and short in 10% of the stocks with prices furthest from their historical high prices earns an average monthly return of 0.93% in non-January months. The performance of 52-week high momentum strategy also improves significantly upon exclusion of low-priced stocks and/or January returns. These findings have important implications for the anchoring-based behavioral explanations of these return patterns.

Pengujian Calendar Effect di Bursa Efek Indonesia tahun 2016

Market efficiency theory stated that stock prices reflect all information in the market. There are 3 different level of market efficiency: weak form, semi-strong form and strong form. When a market is in the state of weak form, there is no investor can gain abnormal return using past information. Calendar effect that is Day of the Week, January Effect and Turn of the Month is anomaly in the stock market that opposed the efficiency market theory. The purpose of this study is to examine the Calendar Effect in Indonesia Stock Exchange during 2016. This research use daily stock price data in LQ45. Using the OLS regression with 5 dummy variables, the results showed that trading day had an effect on stock return where negative return occurred on Monday but not significant. The positive return occured in the following days and the highest return occurred on Wednesday. It can be concluded that the first hypothesis of Day of the Week phenomenon is supported. OLS regression with 1 variable dummy for return in January and 0 otherwise, the result shows that the coefficient is negative and insignificant so it can be concluded that January Effect is not supported. Third hypothesis, Turn of the Month, result shows positive and significant coefficient at level 1%. It means the stock returns in 5 trading days at the end of the month and 2 trading days at the beginning of the month are higher than in other days.

JANUARY EFFECT PADA SEKTOR PROPERTY, REAL ESTATE, DAN BUILDING CONSTRUCTION DI BEI

This research was conducted on property sector, real estate, and building construction sector that are listed in Indonesia’s stock market 2014-2016. This research used quantitive analysis. The purpose of this research was to determine if there is any significant difference between the average abnormal stock return in January and the other months (February to December).. The data used in this research were secondary data. From 56 stocks, 38 stocks were selected as a sample. The sampling method used was purposive sampling. The collected data had been analyzed with Independent sample t-test and the normality data was tested with Saphiro-Wilk test. The result confirmed that there was no January effect in property, real estate, and building construction sector in Indonesia’s stock market 2014-2016.

Return seasonality in the foreign exchange market

ABSTRACTI examine return seasonality in the foreign exchange market using currency futures during the period 1973−2015. All the G10 currency futures yield negative returns in January and this effect happens more often in the countries that have a tax year ending in December. In contrast, returns offered in April are positive. To exploit these anomalies, I use a seasonality strategy that selects portfolios based on their historical same-calendar-month returns. I find that this strategy does not work in the currency market, although I find consistent results with Keloharju et al. in the stock portfolios.

The January Effect: Evidence from Four Arabic Market Indices

This study examines the existence of January effect in four Arabic market indices for the recent time period, February 1988 to May 2014. These market indices include Jordan, Egypt, Lebanon and Morocco. Using the OLS and GARCH (1, 1) approach, the results of this paper indicate that January returns provide positive profits and highly statistical significant, especially in Jordanian and Moroccan market indices. For the Egyptian and Lebanese market indices, the current study documents a large economic profit in January month. These results are useful to investors who can formulate their investment strategies accordingly. This study is the first to conduct a comprehensive January effect analysis of four Arabic market indices in an emerging stock market. The results of this paper support literature that indicates the presence of the January effect in market indices returns and it is still providing a serious challenge to the efficient market hypothesis.

Revisiting calendar anomalies: Three decades of multicurrency evidence

We examine the day-of-the-week, the January, and the turn-of-month effects in developed, advanced and emerging currencies from 1985 to 2014. The returns on Monday, Tuesday and Wednesday are found to be positive and significantly different from zero. The returns on Thursday and Friday are negative and significantly smaller than the returns during first three days of the week. January returns are higher than the returns during the rest of the year. TOM returns are negative and significantly lower than that of non-TOM returns. The calendar anomalies are found to be stronger for emerging currencies compared to advanced and developed currencies. The subsample analysis shows that the calendar anomalies are stronger during the initial subsample and gradually diminish by the last subsample. We also show that for each calendar anomaly, our implied trading strategy can outperform the buy-and-hold strategy in the initial subsamples not so in the last subsamples. Overall, our results indicate that the calendar anomalies have disappeared in the recent times and the markets have become efficient.

The January effect anomaly: effect on the returns-earnings association

Purpose – The purpose of this paper is to examine the January effect, a well-documented capital markets pricing anomaly in which January return premiums are observed to be on average higher than in other months of the year. Extant literature focusses primarily on investor trading behaviors and incentives. This study is different in that it investigates the link between the unusually high returns characteristic of the January effect and accounting earnings, a popular measure that investors use to judge firm value. Design/methodology/approach – The empirical model used in this study is derived from the analytical framework of Ohlson (1995) and Feltham and Ohlson (1995), which explains returns as a function of current and future accounting earnings. Isolating firms that exhibit January effect return premiums from those that do not offers a deeper look at the characteristics of the anomaly. Regression analyses are carried out using a modified Fama-MacBeth (1973) methodology. Quarterly earnings and returns data are drawn from Compustat and CRSP. Findings – The main finding is that the association between January returns and first quarter earnings is unexpectedly and significantly negative, not positive as predicted by the model. Coefficient signs for the other three quarters behave as expected. Additional analyses highlight a difference in the returns-earnings association between firms affected by the anomaly and those that are not. Robustness checks indicate that the findings are not spurious. Originality/value – Rather than applying trading or multifactor economic models that rely on some level of market inefficiency or irrational investor behavior, this study uses an accounting valuation approach that relies on neither. The unexpected negative association between January effect returns and earnings suggests that other factor(s) besides earnings may play into valuation judgments for investors in such firms, and invites further research.

A New January Barometer: The Index of Consumer Sentiment

We examine the ability of the Index of Consumer Sentiment (ICS) to predict stock returns over subsequent 11 months and to explain the other January effect (OJE) puzzle (stock returns in January predicting monthly returns for the remainder of the year). We find that the change in the ICS in January predicts the subsequent 11 months returns and the 11-month holding-period returns and when controlling for this prediction, the stock return OJE vanishes. The empirical results suggest that such predictive power of the ICS may derive from the correlation between the ICS and the unexpected proportion of equity mutual fund net cash flow in the subsequent 11 months.

Institutional shareholdings and the January effects in Taiwan

Many studies have documented the “January Effect” across stock markets. In this paper, we investigate the existence of a January Effect in the Taiwanese market. We document a statistically significant January return, consistent with previous research. However, we also document a new pricing anomaly that appears to exist during the post-liberalization “Great Recession” period of 2005–2010, namely, a “Reverse January Effect”, of statistically significant lower returns during January. Furthermore, we examine the role of three types of institutional investors, and their differential impact on market efficiency in Taiwan. Our results indicate that for the overall time period, foreign institutional investors and domestic investors mitigate the January effect, whereas domestic trusts do not. However, when we segment across time periods, we find that pre-liberalization, when foreign institutional ownership was low, only the domestic institutions promoted efficiency by reducing the January effect. In the 2005–2010 post liberalization period, we find that while FIIs reduce the magnitude of the “Reverse January Effect”, domestic institutions exacerbated it. Domestic trusts appear to have no impact on the January Effect. Taken together, our results provide interesting insights into liberalization and emerging markets. We find that an explanation for the January Effect is related to the participation by various types of institutions in the market. Further, it appears that foreign institutions require a learning curve in terms of efficient pricing, but that greater foreign institutional ownership can ultimately promote greater market efficiency.

Economic Growth Risk and Stock Market Performance: Cross-Sectional Evidence from 70 Countries

This study investigates the impact of economic growth risk on stock market performance in 70 countries. Based on the analysis of the full sample, on average, 1% increase in economic growth risk is associated with 0.23% (p = 0.058) increase in stock market return. Looking at stock market return calculated using January returns only, on average, 1% increase in economic growth risk is associated with 0.647% (p = 0.013) increase in stock market return. On average, 1% increase in economic growth risk is associated with 0.469% (p = 0.025) increase in stock market January return across developed markets. Likewise, on average, 1% increase in economic growth risk is associated with 0.695% (p = 0.069) increase in stock market January return across frontier markets. Finally, economic growth risk does not appear to have any impact on stock market return across emerging markets.

The turn-of-the-year effect and tax-loss-selling by institutional investors

Prior studies attribute the turn-of-the-year effect whereby small capitalization stocks earn unusually high returns in early January to tax-loss-selling by individual investors and window-dressing by institutional investors. My results suggest that a significant portion of the effect on turn-of-the-year returns that prior studies attribute to window-dressing is actually attributable to tax-loss-selling by institutional investors. Among small capitalization stocks, I find that institutional investors with strong tax incentives and weak window-dressing incentives realize significantly more losses in the fourth quarter than in the first three quarters of the calendar year, and that their fourth quarter realized losses have a significant impact on turn-of-the-year returns. A one percentage point change in these institutional investors' fourth quarter realized losses scaled by a firm's market capitalization results in an increase of 47 basis points in the firm's average daily return over the first three trading days of January, which represents a 46 percent change for the mean firm.

The Monthly Barometer Of The Indian Stock Market

The January Barometer or the Other January effect suggests that January returns can predict future performance of the stock market. In this study, it is examined if any particular calendar month return can effectively be used as a monthly barometer to accurately predict future direction of the Indian stock market. The results indicate none of the calendar month returns has consistent ability to accurately predict the performance of the Indian stock market over the next twelve months. The accuracy of prediction did not substantially improve whether the predictor month had generated positive or negative returns. The results continue to remain remarkably consistent when the predictability accuracy was analyzed over time by examining the effect separately over years. The findings of this study clearly demonstrate that the Indian stock market does not possess a monthly barometer that can accurately predict future direction of the stock market.

Analisis January Effect pada Saham Perusahaan LQ-45 di Bursa Efek Indonesia

<span class="fontstyle0">The purpose of this research is to examine about the existence of a January Effect in the Indonesia stock exchange. Research samples used purposive sampling. Sample consists 30 companies based on sampling criteria. Analysis of data used one sample kolmogorov-smirnov to test data normality and to test hypotheses using one sample t-test. The result shows January Effect didn’t exist in Indonesia stock exchange in the period 2011- 2012. This can be seen that although the value of average return in January showed significant but the average return was not the highest, the highest average return was occurred on June.</span>

The January effect for individual corporate bonds

We examine the presence, magnitude and determinants of a January effect for individual corporate bonds. Our results provide empirical evidence of positive and statistically (but not economically) significant abnormal returns in January across different event windows and models. Our results suggest that, in the addition to the term and default factors, the excess stock returns, size and book-to-market factors are priced for individual bond returns. We investigate a number of determinants of the January abnormal returns for individual bonds. Our findings suggest that the reversal and tax-loss selling effects are important determinants of the abnormal returns on individual bonds.

The Other Month Effect: A Re-Examination of the "Other January" Anomaly

Cooper et al. (2006) find support for the "other January" effect in the US market over the period from January 1940 to December 2003 whereby the 11-month holding period returns following positive January returns are on average higher than those 11 months following negative January returns. Under this scenario, January returns can predict the subsequent 11-month holding period returns implying the potential for abnormal profits. We revisit this "anomaly" in the US stock market using the extended period from July 1926 to January 2012. Over the shorter period of 1940–2003 used by CMO, the results are supportive of the "other January" effect and they do so for several alternative holding periods. However, this alleged "other January" effect disappears once we expand the period. Moreover, we find similar and perhaps stronger anomalies for non-January months, particularly February and September. The evidence we uncover in this paper suggests that this alleged "other January" effect is likely sample-period sensitive and further, it is not specific to the month of January.

Is the January Effect Present on the Romanian Capital Market?

The January effect implies that small firms experience large returns in January and exceptionally large returns during the first few trading days of January. This paper examines the January effect pattern on the Romanian stock market. The observation period was divided into sub–periods: January 2003 – December 2007 (before crisis) and January 2008 – December 2010 (during crisis). We found that the January effect occurs before the financial crisis, but during the crisis the effect had been observed as being present only for the third portfolio (which contains the companies that have the smallest capitalization value). The observation of this effect can help the investors to establish a profitable investment strategy.

The January effect, does options trading matter?

This study examines the effect of options trading on the January effect in the period 1996–2009. The options market offers investors an alternative trading venue that circumvents several trading limitations in the equity market and hence enables a higher level of arbitrage activities. In a cross-sectional setting, we find that optioned stocks exhibit significantly lower risk-adjusted returns in January than non-optioned stocks. This effect is not attributed to firm size, illiquidity, or transaction costs. We also find that the January effect is not only smaller but also considerably more short-lived for optioned stocks than for non-optioned stocks. In a firm-specific setting, January risk-adjusted returns are found to be significantly lower in the post-options-listing period than in the pre-options-listing period. These findings support the proposition that options trading enhances information-based trading activities and hence improves the informational efficiency of the equity market. JEL classifications: G10, G11, G12, G14

Northern Exposure: How Canadian Small Stock Investments Can Benefit Investors

We investigate the extent to which investors from around the world can benefit from investing in small market capitalization Canadian stocks. Using monthly data from 1950 to 2009, we show that the size effect has not lessened over the decades in Canada, despite earlier evidence to the contrary in the U.S. We show that with their low correlation to large stocks in Canada and other developed markets, Canadian small stocks represent a unique asset class, and as such an international investor who included a portion of Canadian small stocks would have had a much better return-to-risk reward than from including only large stocks from ten developed equity markets. Based on daily trading volume, we examine and discuss important investabilty issues overlooked in most similar studies. Finally, we corroborate U.S. findings that highlight the importance of returns in January in explaining the bulk of the size effect and examine the size effect in a variety of economic conditions including crises.

Investing in the turn-of-the-year effect

The January effect is concerned with high stock returns in January, especially by small cap stocks. Transactions costs, especially price pressures, make it difficult to take advantage of this anomaly. However, these costs are minimal in the futures markets. This paper discusses the results of small minus large capitalized US stocks since futures trading began in 1982. There is some anticipation of the effect and in the futures markets; the anomaly still exists but is now totally in December.