A Closer Look At Ben Graham’s “Net Current Asset Value” (NCAV) Rule Wednesday, 9 March, 2016

A related paper has been added to:

#37 - Net Current Asset Value Effect

Authors: Oxman, Mohanty, Carlisle

Title: Deep Value Investing and Unexplained Returns

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1928694

Abstract:

Following Ben Graham’s “net current asset value” (NCAV) rule for stock selection (“net net” strategy), we provide evidence that buying stocks in companies with per share NCAV greater than the current share price produced superior risk-adjusted returns over the 1975- 2010 period. The risk factors that explain the returns associated with these firms include market risk, market liquidity, a factor capturing overreaction (long-term reversal), and a relative distress factor. The only firm characteristics that drive excess stock returns for such firms are the analyst coverage, stock price per share, and turnover. Controlling for firm size and common risk factors, we find that returns are higher among net-net stocks with low analyst coverage, low stock price per share and lower trading volume.

Notable quotations from the academic research paper:

"We document that the average monthly return on a net-net portfolio is nearly 5% while the average monthly return on the equal-weighted CRSP is only 1.4% over the same period. We find that the market risk of net- net stocks is quite high. Surprisingly, the small-firm premium in our study does not have any significant explanatory power, nor does the value premium. The momentum factor, from Carhart (1997), has some explanatory power, as does the long-term reversal factor from DeBondt and Thaler (1985). Net- net firms are good candidates for explanation by way of the reversal factor because they are likely to be incorrectly undervalued, based on the firm’s fundamental characteristics. We also note that the leverage factor, based on Ferguson and Shockley (2003), has some explanatory power. It is still puzzling that all risk factors described above leave an unexplained alpha of between 4 and 5% per month.

We explore the relation between firm characteristics and the return anomaly in some detail. We find that firms that fall into the net- net category are typically small firms with high book-to-market ratios and low analyst coverage. Such firms also have significantly lower volume than the CRSP mean, and some of those firms are actually less illiquid than the CRSP mean. Net-net firms with per-share price of $5 or greater tend to be more liquid than the CRSP mean. In contrast, net-net firms with per-share price of $3-$5 are much less liquid than the CRSP mean. Controlling for risk factors and firm characteristics we show that the trading volume and analyst coverage are two key factors explaining the excess returns available to net-net firms."


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Do the Size, Value, and Momentum Factors Exist in Emerging Markets? Wednesday, 2 March, 2016

A new related paper has been added to:

#14 - Momentum Effect in Stocks

#25 - Small Capitalization Stocks Premium
#26 - Value (Book-to-Market) Anomaly

Authors: Cakici, Tang, Yan

Title: Do the Size, Value, and Momentum Factors Drive Stock Returns in Emerging Markets?

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2727257

Abstract:

This paper investigates the size, value and momentum effects in 18 emerging stock markets during the period 1990−2013.We find that size and momentum strategies generally fail to generate superior returns in emerging markets. The value effect exists in all markets except Brazil, and it is robust to different periods and market conditions. Value premiums tend to move positively together across different markets, and such inter-market co-movements increase overtime and during the global financial crisis.

Notable quotations from the academic research paper:

"Emerging markets usually have slower information diffusion, higher transaction costs, lower institutional investor participation than developed markets. Retail investors in emerging markets tend to passively hold suboptimal portfolios due to underdeveloped financial markets. These market frictions intertwined with the mechanisms underlying the value and momentum premiums can either exacerbate or dampen the value and momentum effects on cross-sectional variation in expected stock returns.

Following Fama and French (1993), we construct factor mimicking portfolios based on size, book-to-market equity ratio, and momentum, and calculate monthly factors with respect to size (SMB), value (HML), and momentum (UMD) for individual markets. 2 We find that during the period 1990 − 2013, the size effect does not exist in all emerging markets except China. In contrast, the average SMB is negative in 14 of 18 markets, ranging from –0.10% per month in Czech Republic to –1.02% per month in Hungary. The average HML is always positive in a range from 0.41% per month in Brazil to 2.34% per month in India, and it is statistically significant in all markets except Brazil. On the other hand, the momentum effect, which tends to be stronger than the size and value effects in the U.S. and other developed markets, is surprisingly weak in most emerging markets. Although the average UMD is positive in 14 markets with a minimum of 0.05% per month in Malaysia and a maximum of 1.99% per month in India, it is statistically significant only in Chile (with a mean HML of 0.74%) and India (with a mean HML of 2.34% per month).

Next, we correlate value and momentum factors. We show that they often move inversely together both within the same market and across different markets. Moreover, the negative correlations between the value and momentum factors are stronger for big stocks than for small stocks and in the periods when the U.S. stock market posts positive returns than in the periods of negative U.S. stock market returns. On the other hand, the value factor tends to move positively together across different markets, so does the momentum factor.

Finally, we perform subperiod analyses. We find that the value strategy in emerging markets is robust to different sample periods and market conditions, while the momentum effect is generally weak. Moreover, the value premium has become more positively correlated across emerging markets overtime, and are even more so during the global financial crisis period."


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Sell in May and Go Away in the Equity Index Futures Markets Thursday, 25 February, 2016

A new related paper has been added to:

#31 - Market Seasonality Effect in World Equity Indexes

Authors: Dzahabarov, Ziemba

Title: Sell in May and Go Away in the Equity Index Futures Markets

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2721068

Abstract:

The period May 1 to the turn of the month of November (last five trading days October) has historically produced negligible returns. The rest of the year (late October to the end of April) has essentially all the year's gains. In this paper we show that there is a statistically significant difference and conclude that the strategy go to cash in the weak period and go long in the strong period has about double the returns of buy and hold for large cap S&P500 index and triple for the small cap Russell2000 index during the period 1993-2015 in the index futures markets.

Notable quotations from the academic research paper:

"September and October have historically had low stock market returns with many serious declines or crashes occurring in October. Also the months of November to February have historically had higher than average returns. This suggests the strategy to avoid the bad months and be in cash then and only be long the stock market in the good months. Sell-in-May-and-go-away, which is sometimes called the Halloween E ffect, is one such strategy that is often discussed in the financial press.

Figure 1: S&P500 Futures Sell in May (SIM) and B&H Cumulative Returns Comparison. 1993-2015. (Entry at Close on 6th Day before End of October. Exit 1st Day of May.)

Figure 2: Russell2000 Futures Sell in May (SIM) and B&H Cumulative Returns Comparison. 1993-2015. (Entry at Close on 6th Day before End of October. Exit 1st Day of May.)

For the S&P500 a buy and hold strategy turns $1 on February 4, 1993 into $3.05 on December 16, 2015; whereas, sell in May and move into cash, counting interest (Fed funds e ffective monthly rate for sell in May) and dividends for the buy and hold, had a final wealth of $5.77, some 89.2% higher. For the Russell2000, the final wealths were $2.70 and $7.11, respectively, some 163.3% higher. Figures 1 and 2 show this strategy using the rule sell on the fi rst trading day in May and buy on the 6th trading day before the end of October, for the S&P500 and Russell2000 index futures for the years 1993-2015, respectively. This rule did indeed beat a buy and hold strategy by two and three times in nal wealth with lower standard deviation risk. The strategy works in most but not all years and in strategy design can be combined with other e ffects depending upon market conditions."


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An Interesting Cross-Asset Class Analysis of Risk Premiums Friday, 19 February, 2016

Author: Ebner

Title: Risk and Risk Premia: A Cross-Asset Class Analysis

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2711624

Abstract:

The existence of risk premia has been widely documented in the academic literature over the past decades. Until now they have typically been handled as separate phenomena for specific markets or asset classes and thus examined independently. This study analyses risk premia across a variety of asset classes and risk styles to uncover their common performance characteristics, underlying risk sources and return’s sensitivity to economic factors. Based on a set of 16 risk premia over a 22 year sample period we were able to illustrate that risk premia’s expected returns are significantly influenced by their volatility and their sensitivity to funding liquidity and market volatility. Furthermore we show that macroeconomic factors such as industrial production and inflation have a significant effect on the expected returns of the entire set of risk premia. Finally, analysing the link between premia and the global market portfolio shows that premia with unfavourable comoments possess superior expected returns.

Notable quotations from the academic research paper:

"This study initiates with the analysis of return characteristics for 16 risk premia over a 22 year sample period.

We show that the expected return of a risk premium is significantly affected by its volatility. In other words, higher risk premia volatilities go hand in hand with higher expected returns. However, the analysis of risk premia’s skewnesses and kurtoses does not provide significant results. Subsequently, we build a global cross-asset market portfolio and analyse how risk premia comoments determine their expected returns. The idea behind this is that investors are not compensated for diversifiable risk in equilibrium, but for their systematic risk exposure. The results are in line with the efficient market hypothesis and show that risk premia when adding positive cokurtosis or negative coskewness to a diversified market portfolio have significantly higher expected returns. However, we do not find significant results for a risk premium’s beta exposure to the global cross-asset market portfolio. The second part of the analysis studies the relevance of economic conditions affecting risk premia returns. Considered factors are change in industrial production and inflation, market volatility and market- and funding liquidity. We start with a regime analysis which documents considerable differences in a risk premia’s return given subject to economic conditions.

Comparing risk premia over different regime classifications, this analysis shows the intuitive result that the risk premium “government market” generates attractive returns during unfavourable market regimes and serves as a “safe haven” investment. However, it is not the only risk premium with higher returns during unfavourable periods. For example “commodity momentum” and “FX value” also generate attractive returns during unfavourable market conditions. Afterwards we analyse the expected return of risk premia contingent on each of the economic conditions. We see that during periods of high industrial production changes and low inflation changes, risk premia per se possess higher expected returns. This is also true during periods of high funding liquidity. This study concludes with an analysis of how risk premia’s expected returns are linked to their sensitivities to economic factors. We show that risk premia with higher sensitivities to funding liquidity and market volatility possess significantly higher expected returns."


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An Examination of The Turn-of-the-Month-Effect Friday, 12 February, 2016

A new related paper has been added to:

#41 - Turn of the Month in Equity Indexes

Authors: Giovanis

Title: The Turn-of-the-Month-Effect: Evidence from Periodic Generalized Autoregressive Conditional Heteroskedasticity (PGARCH) Model

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2584213

Abstract:

The current study examines the turn of the month effect on stock returns in 20 countries. This will allow us to explore whether the seasonal patterns usually found in global data; America, Australia, Europe and Asia. Ordinary Least Squares (OLS) is problematic as it leads to unreliable estimations; because of the autocorrelation and Autoregressive Conditional Heteroskedasticity (ARCH) effects existence. For this reason Generalized GARCH models are estimated. Two approaches are followed. The first is the symmetric Generalized ARCH (1,1) model. However, previous studies found that volatility tends to increase more when the stock market index decreases than when the stock market index increases by the same amount. In addition there is higher seasonality in volatility rather on average returns. For this reason the Periodic-GARCH (1,1) is estimated. The findings support the persistence of the specific calendar effect in 19 out of 20 countries examined.

Notable quotations from the academic research paper:

"

The purpose of this paper is to investigate the turn of the month effect in stock market indices around the globe and to test its pattern, which can be used for the optimum asset allocation with result the maximization of profits. Because each stock market behaves differently and presents different turn of the month effect patterns, the trading strategy should be formed in this way where the buy and sell signals and actions will be varied in each stock market index. Haugen and Jorion (1996) suggested that calendar effects should not be long lasting, as market participants can learn from past experience. Hence, if the turn of the month effect exists, trading based on exploiting this calendar anomaly pattern of returns should yield extraordinary profits – at least for a short time. Yet such trading strategies affect the market in that further profits should not be possible: the calendar effect should break down.

However, the results show that the turn of the month effect is persistent in 19 out of 20 stock market indices during the whole period examined. Moreover, sub-sample periods have been explored too supporting the same concluding remarks. In addition, when the post financial crisis period sample 2010-2013 is excluded from the analysis, the turn of the month effect is present in all stock market indices."


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