The momentum strategy in Latin
America
Abstract
This paper investigates whether there can be a momentum return found in Latin America between 2003 and 2012. A winner and loser portfolio are made out of the 20 percentage best/worst performing stocks based on a certain ranking period. With buying the winner portfolio and selling the loser portfolio for a certain holding period, the momentum portfolio is created. Momentum generates no positive return in Latin America. Almost all significant returns turn out to be negative. The factors that drive this negative return are a positive return of the loser portfolio or a small return of the winner portfolio. There is evidence found that there are different momentum returns in the time periods of before the crisis, during the crisis and after the crisis. The lowest return is generated in the period before the crisis and the highest return after the crisis.
Marleen Biesjot 10018182/6230121 14-02-2014
Supervisor: S. Changoer 12 ECTS
Introduction
The Efficient Market Hypotheses (EMH) states that all relevant information is reflected in the price of a stock. So based on the known information, you cannot make an riskless excess return. If there is an investment strategy which does make an excess return it is risky or an anomaly. An anomaly is an exception of the theory. There is shown in some cases that future stock prices can be predicted based on past information. Levy (1967) was one of the first researchers who investigated this. His strategy is to buy stocks which outperform based on past information and to sell stocks which underperform based on past information. He finds a positive return for his strategy. This strategy is called momentum. Momentum is based on the idea that good or bad performance in the past continues over time. The momentum strategy is interesting to investigate at this moment because the crisis of recent years reduced the confidence of investors in the market. They are searching for investment opportunities with low risk (low beta). A momentum strategy could be an outcome for them, because if it exists it realizes a risk-free return.
This thesis investigates whether the momentum strategy is profitable for the Latin American countries over the last 10 years. Latin America is a continent with emerging economies. These economies experience industrialization and rapid growth of business activities. To become a stable economy they have to face several problems like political instability and improvement of the financial infrastructure. It is interesting to focus on Latin America because through this emerging state, their economies are still partly isolated from the developed economic markets. This creates a lot of potential financial investment opportunities for investors (Rouwenhorst 1999). In this thesis I will investigate whether a momentum strategy was profitable in Latin America for the last ten years.
A lot of research in the field of momentum is done in developed countries, often in Europe or the US, like Jegadeesh and Titman. Through the combination of small amount of stocks and high volatility of the returns of stocks in emerging countries, it is harder to get good and unbiased estimates of the strategy. Rouwenhorst (1999) makes a research on emerging stock markets to see whether there can be a momentum excess return in these developing countries. He shows that emerging markets are very similar to developed markets and finds that emerging markets exhibit momentum. Thereby does Harvey (1995) a research based on excess returns in emerging markets. He finds high returns but also high risk in the emerging countries. Important to notice is that this risk has a negative correlation with the developed country markets returns. Which means that if an investor would invest in both developed and emerging countries, a part of the high risk in emerging countries can be diversified.
In addition, in this thesis I will make a comparison between before, during and after crisis returns. Asness, Moskowitz and Pedersen(2009) find in their research that a momentum strategy seems to do better when liquidity is poor and becomes worse. Liquidity risk is negatively related to momentum. Lui and Lee(2001) examine momentum in Japan and find in their results that the momentum strategy works better in a bull market then in a bear market. So the findings of these
researches are contrary.
The contribution of this thesis to the existing literature is that I will observe the results of momentum for emerging markets. Most of the research is done in developed countries, but it is interesting to see whether the results from these papers also hold for these emerging countries, which will create new safe investment opportunities. Moreover this thesis attempts to investigate whether the crisis has an influence on the return of the strategy. A crisis is paired with more volatile stock returns and low confidence of investors in the market. This could probably influence the returns of the strategy.
The reminder of this paper is organized as follows. Section 1 will provide a short overview of the current literature on momentum strategy. First it describes the momentum strategy and thereafter follows information about momentum in crisis times and the Latin American countries. Section 2 will describe the data and will say something about the methodology used to test these data. In section 3 we will look at the results. The returns of the momentum strategy and the comparison is made between after, before and during the crisis. Section 4 is the conclusion. We start with a short summary of the results and this thesis will end with information for future investigation.
I Literature review The momentum strategy
Jegadeesh & Titman (2002) make an influential research in momentum strategy for the US stock market with data based on the period 1965 -1989. They create a winner and loser portfolio of the stocks based on the past six months performance. The winner portfolio consistent of the 10% best performing stocks and the loser portfolio the 10% worst performing stocks. This strategy gives a profit of 1% per month for the first half year. The returns are positive for the first 12 months and turn negative after this period. They also report in their research that the stocks in the loser and winner portfolio are smaller stocks than the average stocks in the study. This could imply a small stock effect. Small stocks are analyzed through less investors and so contain less public information. The effect is that there is more private information which can be reflected in the stock price, which creates higher returns.
Rouwenhorst (1996) does an international research about the returns of momentum. He makes a loser and winner portfolio based on twelve European countries for 1978-1995. Rouwenhorst documents an excess return of 1 % per month. When he compares his returns to the returns found in the US by Jeegadeesh & Titman, he calculates a correlation of 0.43. This is a positive dependence and the results are in a way comparable. So the momentum strategy seems to be not just a chance in the US.
In 1999 Rouwenhorst has studied the returns from 20 emerging markets to see whether they are different then in developed countries. He finds that the results are quite similar for developed and emerging countries. There are also momentum returns found in the emerging economies. There exists a low correlation between the momentum returns per country which suggests that the returns are local orientated and that the momentum strategy does not have the same effect in all emerging countries.
Bekeart et al. (1997) investigates the momentum returns, looking at indexes across emerging countries. They report an inconsistent momentum strategy return. When they look at investable indexes they find some better results. Otherwise, Chan et al. (2012) find almost no evidence that there are differences between developed and emerging markets. They test this with market segmentation. In the period before 1985 most foreign investors could not invest in the emerging stock market. It was therefore harder to diversify their portfolio. Chan et al. (2012) check whether the momentum returns decline when more foreign investors can invest in their stock market. They expect the momentum returns to decline because the stock returns are now easier accessible to more investors. But they cannot find evidence for this pattern.
Explanations for momentum
Many researchers try to explain the excess returns of the momentum strategy but there is still no consensus about what the main driver of this excess returns is. One potential explanation of momentum is country momentum, where the country itself is the driver of the excess return (Asness et al. (2009)). Rouwenhorst (1999) tests whether country momentum could explain the momentum effect. He corrects his returns for country composition and sees a slightly reduce in the momentum returns. These changes seem to be relatively unimportant, so controlling for country specific factors does not change his conclusions. The correlation between these countries increases and the standard deviation between them decreases. Thereby have all the countries a slightly higher standard deviation, but this can partly be diversified through controlling for country specific factors.
Another explanation is size of the firm. The loser stocks seem to be most of the time smaller size then winner stocks and the stocks in the loser and winner portfolio have a smaller size than the average stock. Rouwenhorst (1996) does control for the size factor through looking per size decile. After this control, he still reports an outperforming return across all size deciles. The outperforming return is higher by small size firms.
Risk is also a potential explanation for momentum. If you take a bigger risk, you want to be extra compensated for this risk and you expect a higher return. The risk is measured by beta, containing systematic and unsystematic risk. Most of the time only the systematic risk is measured because the unsystematic risk can be diversified away with an investment portfolio.
Jegadeesh (2002) explains part of the excess return of momentum through seasonal patterns. In a particular month or season of the year investors could behave in a certain way. In January the returns turn most of the time negative. In April the returns are higher ,in November and December also higher returns, probably because everyone sells their loser portfolios (for a better end of the year result) so the prices of loser portfolio go down. These are patterns which could make a difference in the momentum returns.
Daniel et al. (2000) and Hong & Stein (1999) claim that momentum excess returns are partly due to under and overreaction to news. Investors seem to underreact to information of momentum and overreact to information of reversals. The reaction to certain news is context driven. Investors do not react the same to a kind of news factor. DeBondt and Thaler(1985) say that investors overreact to dramatic or unexpected news events.
Fama (1998) reports that even if momentum returns are found, the Efficient Market Hypotheses still exists. He has a few explanations for the momentum effect. The main reason is bad modeling. The way the expected returns are described, can give a difference. Thereby can the sample period play a role. He claims that systematic deviation through sample periods are unavoidable. This is a bigger concern for long term. Also how tests are done can give deviations, statistical and theoretical issues are thereby important. Fama argues that Ipo’s , SEOs , mergers, stock splits, share
repurchases, exchange listings and dividends have an influence on the price of stocks. On the long-term there is a random split between over- and under-reaction. Fama says that anomalies like momentum are chance results and can disappear. It depends on the way they are measured.
Hong & Stein (1999) made a model made based on interaction between heterogeneous agents. Two types of agents play a role, who are both not fully rational. News watchers is the first type and momentum traders the second. The news watchers only see future prices and momentum traders only past price changes. When there are only news watchers, the prices adjust only slowly to new information. There seems to be under reaction, no overreaction. If there are also momentum traders, the reaction becomes faster but sometimes overreaction is measured. An explanation for this difference can be that momentum traders use simple strategies. So the momentum return can be explained by slowly adjusting prices through news watchers investors. When more momentum traders are trading, the return becomes smaller.
The momentum strategy in crisis
Following the Efficient Market Theory all the relevant information should be reflected in the stock price. In a lot of researches there has been found evidence for this theory. Stock prices seem to react to economic news, but are influenced by more events (Chen et al. (2012)) They respond to several external factors. During a crisis there are different economic shocks. Through these shocks the stock returns become more volatile (risky). Most investors get less confidence in the market. The stock prices will go down through the economic bad news factors and the investor will invest less because it is too risky. The excess returns become smaller, so you expect also a decline in the momentum excess returns. This theory is not consistent over time. The reaction can be various for different portfolios and markets (Reinhart& Kaminsky 1998).
Cooper, Gutierrez and Hameed (2004) investigate momentum returns with looking at the state of the market. They report in a the up-state, where the market returns are positive and in a down-state where market returns are negative. They find in an up-state a momentum return of 0.93%, but in a down-state -0.37% return. So a momentum strategy seems to be less profitable in a down market.
Griffin, Ji and Martin (2003) find very different results. They document momentum returns in up and down markets and when the economy is expanding or contracting. They do see higher market correlations during a down state in the US, which means that the stocks are moving more in the same direction. This makes it more difficult to diversify your portfolio during these times.
Latin America had to deal with a lot of crises during the lasts decades. It experienced more frequent and more several crises in comparison with other emerging markets in the world. A reason for this might be the capital inflow to Latin America. In the beginning of 1990 a flow of capital went to emerging markets, mainly to East Asia. At that time, Latin America had to deal with chronic inflation and low growth of the economy. They started with inflation regulation programs and as the economy began to grow and financial liberalization followed (Reinhart & Kaminsky ,1998).
The last crisis has hit Latin America hard, but not as severe as before. This crisis went through different channels then before. The reason for this is that during the boom in the end of 1990’s, the governments built some reserves and declined the amount of external debt. They improved the external balance sheets of their economy. So during the crisis there was some more space for the government to move in a counter cyclical way. The improvements seemed to be insufficient to deal with this recent crisis, but majorly through these improvements it was less worse than in could have been (Ocampo (2009).
The expectation is that during the crisis the momentum returns will be lower, following the results of Cooper, Gutierrez and Hemeed. Through the emerging status of the economies, the expectation is that the returns are not stable enough to hold in a down market (crisis).
Latin America and momentum
Latin America had to deal with a lot of up and down cycles during the last decade. Most of the countries in this continent are emerging countries. The International Monetary Fund lists all the countries in Latin America as emerging. Emerging countries are countries which business activities experience rapid growth and industrialization to become a developed economy. They have to face several problems to become a stable market like their financial infrastructure problems, political instability, liquidation problems and currency volatility (Garcia-Cicco et al., 2006).
Emerging countries have some empirical regularities. They have following Bekeart et al. (1998) high volatility, they are more likely to experience shocks, high long-term returns, more likely to experience shocks induces by regulatory changes, exchange rate variations and political decisions. Most of the investors use these emerging markets as a diversification potential. Through their volatility they show some non-normal returns. Political choices seem to be of big interest for these emerging markets in Latin America. There is a strong correlation between political instability and financial volatility. For example the crisis of Mexico in 1994, the crisis in Brazil in 1999 and the crisis of 2001 in Argentina were during the year of the election of the parliament (Martinez & Santiso, 2003).
All of the Latin American countries in this survey are emerging countries, but there are some important differences between them. To make a good comparison at the end of this thesis, I will give a short description of the economy per country.
Argentina is Latin Americas third largest economy and has an export-orientated economy with agricultural products and a diverse industrial sector. The average exports from 1957 till 2013 is 1539.54 USD million (TradingA, 2013). It experienced a lot of crises during the last decade and faced problems like high inflation and high external debt. Through a monetary and fiscal expensing policy of the government, the inflation is held inside the double digits during the recession. Argentina has a relative high quality of living and a relative high GDP per capita. The Gross Domestic Product in 2012 was 474.90 billion US dollar (CIA, 2012).
Brazil is the fastest expanding economy of Latin America and the largest economy of the continent with a GDP of 2435.20 USD million in 2012 (TradingB, 2013). This is mainly due to its well-developed agricultural, mining, manufacturing and service sectors. The Brazilian government is helping to build a more stable economy through making reserves and decline their outstanding debt. Brazil faces relative high interest rates, which are very attracting for foreign investors. From 1999 till 2013 the average interest rate was 16%. Brazil was one of the first countries who saw his economy reverse after the crisis. The unemployment level is at this moment historically low. The average export rate from 1954 till 2013 of 3972.72 USD million (CIA(2012).
Chile is known as the country with the most stable financial market of Latin America. It has strong financial institutions. Chile has an export orientated economy with a lot of foreign trade. The average export rate from 1991 till 2013 3016.04 USD million (TradingC, 2013). The government is using a countercyclical fiscal policy. It has built extra reserves during booms and used this for example for stimulus packages during the recession. Chile faces an almost stable growth of the economy around 5%. The GDP of Chile was in 2012 268 billion US Dollar (CIA, 2012).
Peru is mostly dependent on his minerals and metals for the export. The average exports of Peru from 1957 till 2013 are 677.73 USD Million (TradingP, 2013). It is also dependent on the imports of food products. Through this dependency on the world market, Peru is very sensitive for fluctuations in the world prices. Peru has a high growth. Lasts years the growth has been around 7%. This is mainly driven through the growth of private investment, which is 60% of Peru’s export. Peru is improving several factors like the finance of the governance, makes a leap in the social sectors and the government tries to reduce the poverty. Peru still has to deal with inequality because of the poor infrastructure. The GDP rate of 2012 in Peru was 197 billion US Dollar (CIA).
Mexico was hit hard through the recent financial crisis. Its GDP was for example declined by around 6%. The biggest sectors in the Mexican economy are industrial and service sectors. Mexico is an export-orientated country with a lot of free trade agreements. The average exports from 1980 until 2013 was 11125.05 USD Million (TradingM, 2013). The income in Mexico is unequally divided. There exist a big difference between the rich and poor and the urban and rural people. It also has to improve its weak judicial system. The government said that it will implement some structural economic reforms. It implements for example policies which support open markets. The GDP of Mexico was for 2012 1170.3 USD billion US dollars. (CIA(2012))
Summary
In different researches a momentum profit is found of 1% in developed countries. Rouwenhorst and Chen et al. find that the results of the momentum strategy in developed countries are very comparable for emerging countries, while Bekeart et al. find inconsistent returns in these emerging economies. There are various explanations for the momentum return like risk, size of the firm or seasonal patterns. Latin America has been hit hard through last crises and had to deal with high inflation and low growth.
The last financial crisis had less influence then the crises before through bigger reserves of the governments. There are contradicting returns found for the momentum strategy during crisis. Cooper, Gutierrez and Hameed find lower momentum returns during crisis, but Griffin, Ji and Martin find very similar results during up and down markets. The economies of the countries in Latin America are emerging and mainly drive on the export of products. The governments of these countries try to stimulate their economy through various policies. Brazil and Mexico have the largest economy, followed by Argentina, Chile and Peru.
II Methodology and Data Research Methodology
For this thesis I will follow the research method of Jegadeesh and Titman (1992) and the test method of de Bondt and Thaler (1985). First I will evaluate the past performance of the stocks over a period of J-months (the ranking period). On this past performance period I’m going to rank the stocks. The ranking period used will be of 1 till 12 months. Then I will rank the stocks, based on the percentage change in total return index of the ranking period. Then the top 20% performing stocks of each ranking period will be the winners portfolio and the bottom 20% performing stocks of each ranking period will be the loser portfolio. I will use 20% because this is mostly used in the literature (deBondt, Thaler).
The next step is to calculate their returns for a holding period of K months. I will use a holding period of 1 to 12 months for comparing the results. We have in total 144 different combinations of periods per country. For each combination the momentum return will be calculated through subtract (sell) the loser portfolio returns from the(buying) winners portfolio returns. To get the excess returns we need to subtract the risk free rate of the country for the same period. We need to calculate the excess returns to make a good comparison between different countries. I will use the percentage change in price index per country as risk-free rate. Then I will compute the cumulative average residual returns for all the years together per country. That will give one table with the cumulative returns over the years for different holding and ranking periods.
After this I will calculate the average cumulative average residual returns (ACAR) for all countries together. All five countries will be equally weighted. The expectation is that the ACAR for winners portfolio>0 and the ACAR for the loser portfolio<0. To check whether there is a real difference between these portfolio’s, I will report the pooled estimate of the population variance. After this I will calculate the sample standard deviation of the winner and loser portfolio to check whether each country contributes to the returns. Then I will check the returns per country. To see whether there is a certain pattern found and to see if in these countries a momentum strategy can be found that is significantly different from zero. I will use the same method as for the total continent.
After all these calculations, I can compare whether there is a difference between before, during and after the crisis. The period before the crisis will be 2003- 2007 , during the crisis 2007-2009 and after the crisis 2007-2009-2012. I will calculate the average percentage return for the winner, loser and winner-loser portfolio for the different periods. Then we can compare the different time periods per country. I would finish my research in trying to explain my results with knowledge from my literature research.
Data
The focus of these thesis is on Latin American countries for the last 10 years. During these years there was a worldwide financial crisis, which started in the United States. Not for every country in the dataset are the data of the stocks available over the last 10 years. So I have chosen to focus on the countries for which I could found sufficient data. The criteria to take a country in this investigation was if the total information was available over the last ten years of the stocks. It is checked whether the return index or the price index and stock exchange was available.The countries are: Argentina, Brazil, Chile, Mexico and Peru. Per country I will look at the biggest stock exchange per country. So for Argentina-Stock Exchange Merval Index; Brazil Bovespa Stock Exchange; Chile-Stock Exchange IPSA index; Mexico- Stock Exchange Bolsa IPC and for Peru- Stock Exchange IGBVL. I will get my data from Datastream. I will use the monthly Return Index and calculate the percentage difference in returns and use these data as a basis to form the portfolios. For some firms the data was not available for every year, I left these data out of the stock exchange for the years not available and put them back in the calculations when they were available, to avoid certain miscalculations. I calculated for every year the top 20% of the stock exchange and rounded this to total stocks.
I adjust these portfolio returns with the risk-free rate of that country to make it possible to compare different countries at various moments in time. I have used the percentage change in the price index per month of the stock index in a country as risk free rate. For Brazil (Bovespa stock index) the price index was not available, so I used the percentage change in return index as the risk free rate.
III Results
Total result all countries together
Table 1 summarizes the percentage returns of the momentum for the different ranking and holding periods of all countries together over a time span of ten years. What we see is that most of the time the winner minus loser portfolio gives a negative return. Only investing in the winners portfolio gives an average monthly return of 0.195%, only investing in the loser portfolio generates 0,212% return and investing in the momentum strategy with longing the winners and short the losers will generate a negative return of -0,125%. This negative return is mainly driven through the positive return of investing in the loser portfolio. Table 1 has some remarkable results. It seems that for every ranking period the first returns in the holding period have a negative W-L return. The losses of the W-L portfolio with a ranking period of -11 or -12 months appear to get bigger on average in absolute value. So there seems to be no strong pattern for a momentum strategy in Latin America.
Table 1- Percentage returns for all counties per ranking/holding period 1 2 3 4 5 6 7 8 9 10 11 12 -1 Winner -0,44 0,58 2,38 0,77 -1,51 0,00 2,25 -0,30 3,64 -1,24 0,28 3,95 Loser -1,31 2,05 2,05 -0,26 0,67 -2,04 1,11 -0,67 1,30 -2,05 0,47 1,44 W-L -2,35 -3,33 -0,97 -2,80 -4,16 -0,18 0,52 -1,34 2,14 -2,50 -1,21 1,48 T-Test -3,70*** -4,34*** -1,50 -3,40*** -11,77*** -0,58 1,55 -2,05** 5,60*** -4,87*** -1,89* 3,29*** -2 Winner -0,30 2,22 0,71 -2,14 -0,44 -1,26 2,08 -0,18 1,79 -1,57 -1,12 2,32 Loser -0,76 -1,03 3,72 -1,21 1,83 -1,17 1,47 -0,90 2,73 -0,60 -0,05 1,27 W-L -2,75 1,39 -4,31 -4,77 -4,26 -2,32 -0,01 -0,97 -1,13 -4,29 -2,09 0,01 T-test -5,68*** 1,96** -6,93*** -11,88*** -6,48*** -6,32*** -0,05 -2,03** -2,68*** -7,18*** -2,89*** 0,03 -3 Winner -1,94 0,30 1,70 -2,56 -0,99 -1,24 0,63 -1,73 1,67 -2,48 -0,77 2,34 Loser -0,12 0,91 2,08 0,19 0,45 -0,49 1,41 0,53 4,17 -1,04 2,61 6,80 W-L -5,03 -2,47 -1,68 -6,57 -3,43 -2,97 -1,40 -3,96 -2,69 -4,76 -4,41 -5,51 T-Test -8,50*** -3,39*** -2,40** -10,15*** -9,25*** -7,37*** -10,08*** -7,05*** -6,28*** -11,30*** -4,75*** -4,07*** -4 Winner -1,00 1,24 2,15 -1,36 0,64 -1,86 2,49 -0,41 2,91 -1,85 0,72 1,59 Loser -0,48 -0,39 3,57 -0,99 0,37 -1,31 0,74 -1,33 3,41 -2,08 0,59 2,81 W-L -3,72 -0,24 -2,71 -4,20 -1,71 -2,78 1,12 -0,78 -0,69 -3,08 -0,89 -2,26 T-test -5,80*** -0,62 -3,73*** -8,47*** -3,26*** -8,49*** 5,05*** -1,94* -2,05** -5,74*** -1,29 -5,21*** -5 Winner -0,18 0,56 3,00 -1,28 -0,97 -0,87 1,72 -0,90 2,12 -1,64 -0,98 2,91 Loser -1,04 0,63 2,19 -0,47 0,89 -2,28 2,34 -0,90 2,94 -1,09 2,49 3,34 W-L -2,35 -1,94 -0,48 -4,65 -3,85 -0,81 -1,24 -1,69 -1,01 -3,86 -4,49 -1,47 T-test -4,86*** -3,16*** -0,75 -10,44*** -7,11*** -1,49 -3,78*** -3,71*** -2,11** -6,98*** -6,26*** -2,84***
-6 Winner -1,12 2,04 1,48 -1,60 0,06 -0,93 2,07 -0,75 2,70 -1,89 -0,07 1,87 Loser -0,73 -0,58 3,40 -0,85 -1,00 -0,75 1,66 -1,47 3,18 -2,11 1,56 6,54 W-L -3,60 0,76 -3,21 -4,58 -0,93 -2,41 -0,21 -0,99 -0,68 -3,09 -2,65 -5,71 T-Test -7,35*** 1,22 -5,94*** -8,93*** -3,51*** -6,86*** -0,98 -2,12** -1,06 -5,03*** -3,90*** -4,46*** -7 Winner -0,97 0,81 3,28 -2,25 0,44 -0,77 1,96 -0,44 2,93 -1,62 1,29 3,51 Loser -0,04 0,43 1,87 -1,10 -0,13 -1,48 2,29 -0,94 2,81 -1,31 -0,72 2,32 W-L -4,15 -1,48 0,11 -4,99 -1,41 -1,52 -0,95 -1,20 -0,07 -3,62 0,99 0,15 T-Test -6,21*** -2,22** 0,21 -8,69*** -4,88*** -7,25*** -3,12*** -2,36** -0,13 -7,04*** 1,50 0,27 -8 Winner -0,46 -0,49 3,86 -2,03 -0,98 -0,73 1,13 -1,21 2,73 -1,31 2,89 5,71 Loser -0,73 0,03 2,02 -0,94 -0,70 -1,84 1,73 -1,39 2,00 0,05 0,37 2,36 W-L -2,95 -2,38 0,55 -4,93 -2,27 -1,12 -1,22 -1,51 0,54 -4,68 1,50 2,31 T-Test -6,47*** -7,99*** 0,99 -9,44*** -6,14*** -2,07** -6,76*** -2,40** 1,48 -7,95*** 2,25** 2,28** -9 Winner -0,81 -0,13 2,64 -0,48 -1,21 -1,67 1,73 -1,28 2,24 -2,10 1,27 3,37 Loser 1,08 2,27 2,55 -0,59 1,91 -1,24 1,11 0,88 2,88 -1,72 0,02 1,82 W-L -5,10 -4,26 -1,21 -3,72 -5,11 -2,66 0,00 -3,86 -0,83 -3,70 0,23 0,51 T-Test -6,81*** -6,12*** -1,78* -6,53*** -9,45*** -10,58*** -0,01 -8,90*** -1,55 -7,16*** 0,33 0,87 -10 Winner 0,31 0,09 2,43 -2,32 -0,41 -1,17 1,37 -1,03 3,39 -2,49 -0,16 2,53 Loser -0,34 1,11 1,66 0,49 -0,49 -0,73 1,11 -1,12 2,48 -1,49 0,15 7,52 W-L -2,56 -2,89 -0,52 -6,64 -1,91 -2,68 -0,35 -1,61 0,71 -4,32 -1,33 -6,03 T-Test -3,31*** -3,46*** -0,76 -9,64*** -4,12*** -8,56*** -1,23 -2,98*** 1,16 -8,22*** -2,15** -4,23*** -11 Winner 0,59 -0,05 3,00 -2,74 -0,24 -1,96 0,56 -1,10 2,98 -1,57 0,52 2,67
Loser -1,55 -0,92 2,19 -0,02 0,20 -0,71 2,29 -1,27 2,32 -0,16 0,58 0,98 W-L -1,38 -0,85 -0,50 -6,43 -2,13 -3,80 -2,42 -1,62 0,09 -5,78 -1,43 1,15 T-Test -2,40** -2,42** -1,22 -12,55*** -4,96*** -9,93*** -8,28*** -3,73*** 0,15 -12,67*** -2,68*** 3,69*** -12 Winner -0,57 1,54 1,50 -2,24 -0,53 -2,70 2,75 -0,50 3,67 -0,89 -0,40 1,63 Loser -0,88 -1,61 3,29 -1,80 -0,24 -0,26 0,62 -0,90 1,38 0,03 2,87 6,42 W-L -2,90 1,28 -3,09 -4,27 -2,29 -4,67 1,51 -1,30 2,10 -4,23 -4,29 -5,83 T-Test -4,32*** 2,07** -3,67*** -6,35*** -6,79*** -9,20*** 7,77*** -3,30*** 4,08*** -6,42*** -4,91*** -3,90***
The table provides the percentage returns of all five countries together for the winner, loser and winner-loser portfolio. The calculations are based on a -1 till -12 month ranking period and the portfolios are kept for a period of 1 till 12 months. The monthly returns are calculated through ranking stocks and create from the 20% best/worst stocks the winner and loser portfolio per country and then combine the results of all countries. All these returns are rounded numbers over the different ears and countries, therefore a dispersion of the W-L portfolio can arise.
Country results Argentina
In table 3 the average percentage returns of the different portfolios for Argentina of the last 10 years are summarized. By only investing in the winner portfolio you will receive a return of 0,14%, with the loser portfolio 0,89% and in the momentum portfolio of Winner-Loser you will get a negative return of -2,44%. This negative result is mainly driven through the 11th and 12th holding period based on the 3rd ranking period. These show very negative returns which influences the total outcome of the strategy.
The highest positive return is at ranking period -8 months and with a holding period of 12 months, with a positive value of 19,75%. The lowest return is found in ranking period -3 and holding period of 11 months of -22,27%.
Table 2- Value of the Winner- Loser returns in Argentina
Total Significant Positive value Negative value
90% 144 57 13 44
95% 144 46 11 35
99% 144 28 6 22
In table 3 report some remarkable results. We see that most significant returns can be found over different ranking periods in the 11th and 12th month of the holding period. This is mainly caused by the higher returns from the loser portfolio in the 11th and 12th months. Almost all these returns turn positive through the larger positive results of the loser portfolio.
Table 3- Significance of percentage portfolio returns in Argentina
Ranking Holding period
Period 1 2 3 4 5 6 7 8 9 10 11 12 -1 Winner 0,94 -1,99 -2,02 8,03 0,74 1,47 1,38 -0,38 6,30 -1,47 -5,08 7,13 Std dev 10,98 15,55 13,31 28,60 9,40 11,41 10,73 8,84 7,65 18,93 15,40 9,59 Loser -4,78 -1,82 -1,61 -4,62 0,79 -0,93 2,92 -6,22 3,80 -1,28 2,68 5,20 Std dev 11,36 11,66 14,47 11,29 12,59 10,84 12,29 7,26 11,82 18,05 17,57 10,68 W-L 0,29 -3,20 -1,45 11,01 -0,15 0,42 -2,05 3,96 5,22 -4,97 -11,55 3,18 T-test 0,13 -1,18 -0,52 2,76** -0,07 0,19 -0,89 2,46** 2,68*** -1,34 3,5*** 1,57 -2 Winner 0,49 -2,34 -3,40 -1,72 2,21 -2,40 3,10 -4,50 5,72 -0,83 -7,75 4,18 Std dev 12,97 10,12 13,73 11,63 11,34 14,88 13,27 7,47 12,30 21,62 12,81 12,81 Loser -1,88 -1,27 3,03 -2,27 4,48 -0,92 3,95 -2,64 4,99 1,66 -1,87 0,06 Std dev 13,89 11,83 12,84 9,67 13,00 9,37 10,12 6,98 7,29 18,52 12,52 5,88 W-L -3,07 -4,11 -7,47 -1,09 -2,37 -3,47 -1,36 -3,73 3,45 -7,27 -9,67 5,38 T-test -1,14 1,87* -2,81*** -0,51 -0,98 -1,43 -0,58 -2,58*** 1,76* -1,81* -3,82*** 2,88*** -3 Winner -2,34 -1,33 -2,27 -0,85 0,71 -0,81 0,53 -6,38 4,07 -2,56 -7,54 7,10 Std dev 14,72 13,24 12,01 11,19 13,88 16,37 13,82 6,30 13,61 21,68 13,35 12,00 Loser -1,01 -5,62 -0,92 5,18 3,08 -1,17 0,89 -2,89 5,82 -0,95 10,94 25,79 Std dev 11,42 13,19 16,09 24,81 12,18 8,86 9,48 8,91 7,64 20,86 33,99 50,09 W-L -6,77 1,25 -2,39 -7,67 -2,47 -1,62 -0,87 -5,36 0,96 -6,39 -22,27 -17,43 T-test -2,59*** 0,47 -0,85 -2,13** -0,95 -0,64 -0,37 -3,52*** 0,45 -1,50 -4,70*** -2,81*** -4 Winner 0,29 0,69 -0,56 -1,64 5,92 -0,72 2,78 -2,00 4,84 -5,38 -4,02 2,52 Std dev 14,43 13,56 12,62 10,54 16,30 14,85 13,40 6,81 12,03 21,71 15,69 11,12 Loser -3,91 -4,25 -1,72 4,16 1,93 -1,92 1,37 -4,10 6,40 -2,99 -0,53 7,98 Std dev 9,37 14,73 13,83 23,55 11,82 13,53 8,94 7,80 9,73 20,49 14,86 8,70 W-L -1,24 1,90 0,12 -7,44 3,89 -0,77 0,90 0,23 1,16 -7,17 -7,28 -4,20
T-test -0,52 0,67 0,04 -2,18** 1,38 -0,27 0,40 0,15 0,53 -1,70* -2,38** -2,12** -5 Winner 1,40 -1,02 -1,92 0,24 0,66 1,27 0,67 -2,99 4,74 -2,66 -6,45 6,80 Std dev 15,21 12,51 11,40 12,25 13,64 15,90 11,30 8,39 13,85 19,22 13,54 12,05 Loser -1,53 -3,31 -0,05 0,09 3,27 -6,48 2,40 -5,03 6,99 -5,42 0,83 7,35 Std dev 7,59 13,79 17,82 22,58 11,52 16,86 11,00 8,21 7,51 19,87 20,26 13,22 W-L -2,50 -0,75 -2,91 -1,49 -2,71 5,77 -2,25 0,17 0,46 -2,02 -11,07 0,71 T-test -1,10 -0,28 -1,00 -0,43 -1,08 1,76* -1,01 0,10 0,21 -0,52 -3,28*** 0,28 -6 Winner 0,49 -1,47 0,68 -0,04 -0,22 -2,10 1,70 -4,40 8,81 -0,10 -4,59 5,47 Std dev 16,81 14,88 15,42 9,46 14,24 16,06 11,99 7,21 11,49 15,93 13,56 10,13 Loser -1,86 0,14 -1,46 -2,55 -1,24 1,32 0,95 -4,01 7,11 -4,19 3,01 25,43 Std dev 10,76 10,40 13,11 13,81 8,81 11,68 10,72 8,86 9,37 23,02 34,15 51,22 W-L -3,09 -4,66 1,11 0,86 0,91 -5,39 0,24 -2,27 4,41 -0,69 -11,39 -18,70 T-test -1,12 -1,84* 0,39 0,37 0,40 -1,94* 0,11 -1,41 2,11** -0,18 -2,39** -3,05*** -7 Winner -1,53 -0,81 3,25 -2,90 0,28 -1,30 2,47 -3,47 6,71 -1,47 5,29 3,47 Std dev 12,66 13,25 16,99 9,63 13,61 15,16 15,23 7,11 11,24 19,04 19,88 9,64 Loser -0,52 -3,97 -1,95 -3,18 1,17 -1,13 3,32 -2,23 7,01 -0,89 -6,31 8,02 Std dev 13,24 10,29 12,15 14,80 14,10 14,37 9,68 6,87 11,35 20,12 19,12 9,61 W-L -6,44 0,12 4,15 -1,37 -1,00 -2,15 -1,37 -3,11 2,42 -5,36 7,81 -3,29 T-test -2,49** 0,05 1,42 -0,56 -0,36 -0,73 -0,55 -2,22** 1,07 -1,37 2,00** -1,71* -8 Winner 0,80 -2,72 -0,72 -3,89 -1,92 -1,54 1,48 -7,27 4,58 -3,89 7,44 21,93 Std dev 9,99 10,45 14,44 11,79 13,42 18,10 7,34 7,25 10,59 22,38 36,36 50,75 Loser -0,42 -0,90 -1,39 0,28 -0,63 -2,34 1,88 -4,79 4,92 3,19 -3,73 3,43 Std dev 18,26 11,48 17,26 15,34 9,83 14,66 10,89 9,56 12,20 20,64 14,07 11,89 W-L -4,22 -4,86 -0,37 -5,82 -1,40 -1,18 -0,91 -4,34 2,37 -11,86 7,38 19,75 T-test -1,49 -2,22** -0,12 -2,14** -0,60 -0,36 -0,50 -2,58*** 1,04 -2,75*** 1,46 3,15***
-9 Winner -2,58 -2,18 -1,99 4,20 1,81 -1,19 1,04 -1,45 5,31 -5,45 -3,28 11,05 Std dev 10,29 14,17 14,43 19,27 9,67 16,40 11,40 6,85 12,72 16,40 17,56 12,17 Loser 3,87 -1,57 -1,39 -0,63 3,90 -0,11 -0,25 -3,27 8,19 0,97 -2,91 2,25 Std dev 14,16 12,63 14,30 17,97 13,86 11,13 10,18 8,58 8,77 21,64 14,93 6,68 W-L -11,88 -3,65 -1,65 3,19 -2,19 -3,06 0,78 -0,05 -0,17 -11,20 -4,16 10,05 T-test -4,86*** -1,36 -0,57 0,86 -0,93 -1,11 0,36 -0,04 -0,08 -2,94*** -1,28 5,33*** -10 Winner -1,33 -1,68 -1,30 -3,54 0,35 -2,42 1,65 -4,15 10,40 -1,83 -5,22 8,81 Std dev 14,80 11,14 16,33 10,97 11,84 14,66 10,37 7,88 12,42 23,12 14,74 11,91 Loser -0,32 -6,27 -3,75 8,08 2,30 1,61 -1,13 -5,90 4,78 -2,78 -0,05 26,35 Std dev 12,77 12,58 12,45 27,94 13,16 14,04 8,59 6,74 10,04 18,41 34,23 51,19 W-L -6,45 1,55 1,42 -13,26 -2,05 -6,01 2,27 -0,13 8,33 -3,83 -8,96 -16,28 T-test -2,34** 0,65 0,49 -3,41*** -0,82 -2,09** 1,20 -0,09 3,71*** -0,92 -1,83* -2,58*** -11 Winner 1,38 -1,89 -0,44 -4,47 1,13 -4,12 -0,73 -4,81 8,26 -3,42 -0,42 5,41 Std dev 15,04 13,17 13,13 12,89 13,57 15,06 9,31 8,46 15,52 20,21 17,66 10,31 Loser -2,03 -3,98 0,98 0,59 1,99 2,02 3,02 -2,65 7,26 0,10 -2,72 2,16 Std dev 13,07 13,12 15,12 9,12 12,85 11,32 11,95 6,44 8,70 21,48 17,51 6,66 W-L -2,03 -0,95 -2,46 -6,70 -0,97 -8,12 -4,26 -4,04 3,71 -8,30 -1,49 4,51 T-test -0,72 -0,36 -0,87 -3,05*** -0,37 -3,08*** -2,00** -2,71*** 1,53 -1,99** -0,42 2,65*** -12 Winner -2,37 -2,06 0,39 -4,54 -1,34 -6,21 2,25 -3,74 7,94 -2,00 -5,05 7,94 Std dev 8,72 11,82 13,31 11,11 12,58 16,26 10,63 7,31 14,28 23,09 18,18 11,60 Loser 1,34 -4,78 -1,89 -2,99 -1,12 -0,46 -0,25 -4,32 5,25 2,15 10,01 22,90 Std dev 13,33 8,24 10,51 12,18 10,93 13,13 10,57 6,73 10,44 16,43 33,20 50,86 W-L -9,14 -0,32 1,24 -3,19 -0,33 -7,73 1,99 -1,29 5,41 -8,93 -18,86 -13,70 T-test -4,15*** -0,16 0,52 -1,37 -0,14 -2,63*** 0,94 -0,92 2,19** -2,26** -3,67*** -2,19** The table provides the percentage returns of Argentina for the winner, loser and winner-loser portfolio. The calculations are based on a -1 till -12 month ranking period and the portfolios are kept for a period of 1 till 12 months. The monthly returns are calculated through ranking stocks and create from the 20% best/worst stocks the winner and loser portfolio. The standard deviation of the stocks is calculated with the formula : √(VAR/n). The T-test indicates whether the percentage return of the W-L portfolio is statistically different from zero and is calculated with the formula : Return W-L /√(VAR/n). *, **, *** means significant at 90%, 95% and 99% respectively.
Brazil
In table 5 the average percentage returns of the different portfolio’s for Brazil of the last 10 years are summarized. By only investing in the winner portfolio you will get a return of 0,47%, with the loser portfolio 0,74% and in the momentum portfolio of WinnerLoser you will receive a negative return: -1,94%. This negative result is mainly driven through the small returns of the winner portfolio.
The highest positive return of the W-L portfolio is at ranking period -6 months and with a holding period of 2 months, this creates a positive return of 10.00%. The lowest return is found in ranking period -10 and holding period of 2 months with a return of -9.37%.
Table 4- Value of the Winner- Loser returns in Brazil
Total Significant Positive value Negative value
90% 144 56 8 48
95% 144 53 7 46
99% 144 24 3 21
In table 5 we can find some remarkable results. We can see that for a ranking period of -12 months almost all holding periods create a high significant return. Thereby it is notable that for almost all ranking periods, the first holding period gives a significant negative return. These negative returns are mainly driven through the negative returns of the winners portfolio for this first holding period.
Table 5- Significance of the percentage portfolio returns of Brazil 1 2 3 4 5 6 7 8 9 10 11 12 -1 Winner -4,48 5,52 -0,28 -1,53 0,82 0,90 3,38 3,34 2,37 -0,52 2,60 1,49 Std dev 7,85 7,58 14,87 6,98 7,60 12,26 8,11 10,21 6,10 15,12 8,54 6,73 Loser -2,75 9,58 0,77 -0,33 0,75 -2,73 1,90 4,71 -0,01 -3,52 3,90 -0,70 Std dev 9,31 26,50 16,06 11,23 10,20 11,82 11,14 12,94 10,80 13,03 10,92 6,14 W-L -5,33 -4,92 -2,31 -4,66 -0,29 2,76 2,08 -2,47 0,35 -0,52 -2,15 -0,51 T-test -3,11*** -1,44 -0,75 -2,56** -0,16 1,15 1,08 -1,07 0,20 -0,18 -1,11 -0,40 -2 Winner -4,11 11,85 -1,40 -2,48 -1,37 -0,24 2,65 3,55 -0,09 -3,74 2,32 0,78 Std dev 12,90 26,38 13,18 9,52 8,86 11,71 8,07 9,83 10,70 12,91 8,21 7,62 Loser -2,24 1,39 1,48 -0,35 5,09 0,20 1,27 1,79 0,58 0,85 3,39 -0,57 Std dev 6,73 10,52 14,20 7,78 10,94 11,08 10,32 9,54 8,23 15,21 8,81 6,05 W-L -5,47 9,60 -4,14 -5,59 -6,82 -1,31 1,98 0,66 -2,70 -8,10 -1,92 -1,35 T-test -2,79*** 2,60*** -1,51 -3,23*** -3,45*** -0,57 1,07 0,34 -1,43 -2,88*** -1,13 -0,98 -3 Winner -4,93 2,12 0,45 -3,52 -0,19 -0,91 0,71 2,44 -0,04 -4,65 0,04 -0,32 Std dev 8,72 8,70 10,08 7,67 7,74 12,75 8,48 8,79 9,61 12,47 8,66 8,95 Loser -4,11 10,14 -2,20 -0,05 0,13 0,04 2,20 2,92 2,25 -0,49 2,59 2,66 Std dev 8,72 8,70 10,08 7,67 7,74 12,75 8,48 8,79 9,61 12,47 8,66 8,95 W-L -4,41 -8,88 1,38 -6,94 -0,69 -1,83 -0,90 -1,59 -4,33 -7,68 -3,39 -6,01 T-test -2,53** -5,10*** 0,68 -4,53*** -0,44 -0,72 -0,53 -0,91 -2,25** -3,08*** -1,96** -3,36*** -4 Winner -2,95 2,72 -0,20 -1,25 -1,46 -1,00 3,95 2,82 1,37 -0,13 5,10 0,83 Std dev 10,69 9,68 12,07 6,64 9,41 14,45 8,29 8,66 9,58 13,21 10,32 6,62 Loser -5,56 1,22 1,85 -3,58 1,07 -1,17 1,55 1,90 2,26 -2,25 1,51 1,74 Std dev 7,85 9,26 14,11 7,85 10,74 10,49 8,85 11,45 9,58 11,88 10,62 7,76 W-L -0,99 0,64 -3,32 -1,14 -2,90 -0,71 3,00 -0,19 -2,92 -1,39 2,74 -3,94 T-test -0,53 0,34 -1,27 -0,78 -1,44 -0,28 1,75* -0,09 -1,53 -0,56 1,31 -2,74***
-5 Winner -3,98 1,32 1,83 -2,01 1,00 -2,25 4,56 2,14 -1,14 -3,11 3,17 0,43 Std dev 8,76 11,77 13,13 11,16 8,18 12,92 11,40 8,38 10,70 14,26 9,56 6,78 Loser -3,76 8,88 -0,92 -2,00 -1,03 -0,01 2,42 2,25 1,05 2,14 4,76 -0,25 Std dev 10,34 27,48 15,43 6,97 7,35 12,77 8,74 10,24 7,76 13,53 10,18 8,42 W-L -3,82 -8,42 1,48 -3,47 1,66 -3,11 2,74 -1,22 -4,22 -8,77 -2,44 -2,35 T-test -2,00** -2,15** 0,52 -1,92* 1,07 -1,21 1,36 -0,65 -2,29** -3,16*** -1,24 -1,55 -6 Winner -4,26 11,35 -0,20 -3,20 2,42 -0,76 1,86 2,23 -2,08 -3,51 3,13 0,15 Std dev 10,48 25,73 12,06 8,47 8,00 12,86 8,04 11,61 7,35 11,38 9,10 7,05 Loser -4,06 0,49 3,48 -0,05 -1,27 1,00 3,34 1,34 0,88 -4,07 4,00 0,21 Std dev 10,20 9,54 11,22 10,36 9,25 13,72 10,65 8,38 9,74 10,96 11,22 8,35 W-L -3,80 10,00 -4,95 -6,62 3,32 -2,64 -0,89 -0,22 -4,99 -2,96 -1,72 -3,09 T-test -1,84* 2,83*** -2,13** -3,51*** 1,93* -0,99 -0,48 -0,11 -2,92*** -1,32 -0,85 -2,01** -7 Winner -4,30 3,79 0,93 -2,46 2,99 0,31 2,98 3,65 -0,41 -3,81 1,38 1,33 Std dev 7,19 8,74 11,86 8,31 12,13 13,38 7,65 11,76 9,41 10,42 7,98 7,85 Loser -3,40 8,37 -0,85 -2,11 0,28 -1,61 1,40 2,74 -0,17 -0,06 1,68 -0,22 Std dev 11,36 27,12 13,34 9,47 10,08 11,62 9,76 9,21 7,57 16,35 10,33 6,59 W-L -4,50 -5,43 0,51 -3,83 2,34 1,05 2,17 -0,19 -2,27 -7,27 -1,14 -1,48 T-test -2,42** -1,52 0,20 -2,15** 1,05 0,42 1,25 -0,09 -1,34 -2,72*** -0,62 -1,02 -8 Winner -4,95 1,73 4,12 0,51 0,45 3,87 3,79 4,06 0,62 -3,22 4,10 1,45 Std dev 7,88 8,91 11,87 7,48 6,65 15,53 11,23 10,97 9,53 10,14 10,26 8,67 Loser -3,04 0,81 0,39 -4,61 0,63 -3,29 1,72 1,07 0,57 -0,93 1,42 0,97 Std dev 9,60 10,18 10,70 9,50 11,63 10,96 7,47 7,90 6,92 16,05 9,04 6,33 W-L -5,51 0,07 2,46 1,65 -0,55 6,29 2,67 1,88 -1,99 -5,81 1,83 -2,55 T-test -3,15*** 0,04 1,09 0,97 -0,30 2,37** 1,43 1,00 -1,21 -2,22** 0,95 -1,70**
-9 Winner -3,34 3,50 0,82 -2,89 -0,90 -2,16 4,33 0,96 -0,12 -1,49 2,59 0,50 Std dev 9,25 9,81 11,40 7,55 7,41 12,67 8,42 8,61 10,69 15,54 11,20 7,52 Loser -2,18 10,49 1,03 0,58 2,59 -1,30 1,11 4,73 -1,17 -2,37 2,17 -0,81 Std dev 11,04 26,10 15,63 10,13 8,17 12,13 9,37 14,00 9,98 12,75 7,64 7,93 W-L -4,76 -7,84 -1,47 -6,94 -3,85 -1,74 3,81 -4,87 -0,98 -2,64 -0,43 -1,72 T-test -2,35** -2,18** -0,54 -3,93*** -2,47** -0,70 2,14** -2,16** -0,47 -0,93 -0,23 -1,11 -10 Winner -2,45 2,65 -0,77 -2,53 1,29 0,26 2,20 1,44 -2,30 -3,43 1,88 0,39 Std dev 10,49 10,02 14,31 8,49 8,27 9,26 8,84 9,71 11,09 13,05 10,42 8,80 Loser -4,69 11,16 0,17 -2,86 -0,56 -1,28 2,73 3,16 2,55 -3,87 3,47 0,40 Std dev 9,13 28,81 13,69 7,91 8,83 11,40 9,65 12,63 7,96 11,52 9,35 7,22 W-L -1,36 -9,37 -2,20 -3,14 1,49 0,67 0,07 -2,83 -6,88 -3,08 -2,43 -3,05 T-test -0,69 -2,41** -0,79 -1,91* 0,87 0,33 0,04 -1,27 -3,61*** -1,25 -1,23 -1,90* -11 Winner -2,69 0,83 3,36 -2,06 -0,63 -0,67 3,06 1,45 0,41 -2,64 1,79 0,95 Std dev 10,38 10,71 13,60 7,60 8,13 11,39 7,31 11,05 8,46 11,74 7,74 6,70 Loser -4,39 1,55 1,41 -1,25 0,38 -0,34 2,69 1,78 0,68 -0,02 5,11 -1,22 Std dev 9,24 8,45 12,81 9,45 11,73 10,78 10,56 9,05 10,57 15,18 12,59 6,71 W-L -1,90 -1,57 0,68 -4,28 -1,37 -1,20 0,97 -1,44 -2,30 -6,14 -4,17 -0,87 T-test -0,97 -0,82 0,26 -2,51** -0,69 -0,54 0,54 -0,71 -1,21 -2,28** -2,05** -0,65 -12 Winner -3,79 9,81 0,17 -3,51 2,81 -1,81 4,86 1,45 1,76 -2,53 1,77 -1,43 Std dev 10,91 24,25 14,26 7,94 9,03 12,48 9,56 11,99 9,42 11,43 10,62 7,58 Loser -2,98 0,46 3,61 1,31 -0,92 3,74 1,27 2,48 -0,66 0,19 3,49 1,17 Std dev 9,94 8,25 9,85 9,24 7,92 14,79 9,32 8,86 9,82 14,48 8,62 8,38 W-L -4,41 8,49 -4,71 -8,28 3,37 -6,43 4,19 -2,14 0,39 -6,24 -2,57 -5,63 T-test -2,11** 2,61*** -1,95* -4,82*** 1,99** -2,36** 2,22** -1,02 0,20 -2,41** -1,33 -3,53***
Chile
In table 7 the average percentage returns of the different portfolio’s for Chile of the last 10 years are summarized. By only investing in the winner portfolio you will receive a return of 0.37%, with only investing in the loser portfolio 0.48% and with the momentum portfolio of Winner-Loser you will receive a negative return of -1.48%. This negative result is mainly driven through the positive returns of the loser portfolio.
The highest positive return is at ranking period -11 months and a holding period of 3 months, which creates a positive value of 3.65%. The lowest return is found at a ranking period of -5 months and holding period of 5 months with a return of -9.16% .
Table 6- Value of the Winner- Loser returns in Chile
Total Significant Positive value Negative value
90% 144 44 8 36
95% 144 33 6 27
99% 144 25 5 20
In table 7 we can find some remarkable patterns. We can see that for a holding period of 12 months, almost all W-L portfolios have a positive return. This is mainly driven through the positive return of the winner portfolios. The most significant returns are found in a holding period of 4 or 5 months. All of these returns have a negative return in the W-L portfolio. This is mainly caused by the low winner portfolio returns.
The table provides the percentage returns of Brazil for the winner, loser and winner-loser portfolio. The calculations are based on a -1 till -12 month ranking period and the portfolios are kept for a period of 1 till 12 months. The monthly returns are calculated through ranking stocks and create from the 20% best/worst stocks the winner and loser portfolio. The standard deviation of the stocks is calculated with the formula : √(VAR/n). The T-test indicates whether the percentage return of the W-L portfolio is statistically different from zero and is calculated with the formula : Return W-L /√(VAR/n). *, **, *** means significant at 90%, 95% and 99% respectively.
Table 7- Significance of percentage portfolio returns in Chile 1 2 3 4 5 6 7 8 9 10 11 12 -1 Winner 1,56 -0,99 3,09 -0,10 -2,16 -0,11 -0,34 -1,47 1,64 0,10 -1,82 2,13 Std dev 8,46 7,04 7,73 5,57 4,60 10,73 6,18 6,70 4,86 9,83 6,82 4,27 Loser -0,15 -0,83 0,89 5,76 1,36 -1,99 1,24 -0,22 0,78 1,10 -3,08 0,31 Std dev 4,73 8,31 7,56 14,39 10,91 10,67 7,41 6,43 7,24 10,61 7,35 4,51 W-L 0,80 -2,10 1,61 -8,09 -6,56 -0,61 -3,04 -2,75 0,85 -2,72 -0,56 3,04 T-test 0,61 -1,37 1,05 -4,06*** -4,23*** -0,28 -2,24** -2,09** 0,70 -1,33 -0,39 3,47*** -2 Winner 1,50 -0,25 3,44 1,21 0,58 -0,34 0,78 -0,62 2,68 0,92 -2,15 2,49 Std dev 5,99 10,01 5,26 9,62 8,24 9,90 6,60 6,28 8,18 11,97 8,89 2,93 Loser -0,07 -0,93 1,65 1,18 -0,35 -1,25 0,62 -1,29 1,30 0,17 -3,91 1,51 Std dev 7,28 9,39 6,19 7,64 11,65 10,91 4,62 6,24 7,32 10,73 7,69 4,31 W-L 0,66 -1,25 1,21 -2,20 -2,11 -1,58 -1,29 -0,83 1,38 -0,97 -0,06 2,21 T-test 0,50 -0,65 1,06 -1,27 -1,06 -0,76 -1,15 -0,66 0,89 -0,43 -0,03 3,05*** -3 Winner 1,09 -1,29 3,77 1,77 -2,09 1,93 1,49 -1,00 -0,51 0,46 -1,68 1,96 Std dev 7,16 9,34 8,41 7,95 6,94 9,54 6,56 6,77 7,03 11,64 6,98 4,21 Loser 0,14 -0,75 1,81 1,74 0,36 -1,30 0,35 0,10 5,13 0,01 -2,30 1,18 Std dev 5,60 8,88 5,08 8,44 8,61 9,40 5,43 6,63 6,84 10,04 7,61 4,21 W-L 0,03 -2,48 1,37 -2,20 -5,48 0,75 -0,30 -2,59 -5,65 -1,26 -1,19 2,00 T-test 0,03 -1,36 1,02 -1,34 -3,53*** 0,39 -0,25 -1,93* -4,07*** -0,58 -0,82 2,37** -4 Winner 0,58 -0,16 3,06 0,70 0,14 -2,30 1,63 -1,03 1,98 1,40 -3,16 0,91 Std dev 7,74 9,52 5,70 6,98 4,04 8,79 6,92 7,65 7,03 10,59 7,93 5,17 Loser 3,22 -1,17 2,36 1,31 -0,52 -1,20 -1,36 -1,71 1,87 -0,45 -3,66 0,49 Std dev 5,83 9,70 6,96 8,77 12,12 11,45 5,43 6,44 6,04 10,76 7,42 3,93 W-L -3,55 -0,93 0,12 -2,84 -2,37 -3,58 1,55 -0,81 0,10 0,14 -1,30 1,64 T-test -2,61*** -0,48 0,09 -1,80* -1,47 -1,77* 1,25 -0,58 0,07 0,06 -0,85 1,80*
-5 Winner 1,40 -0,45 3,19 0,33 -2,35 0,63 0,50 -1,82 1,24 0,82 -3,52 1,50 Std dev 6,45 9,07 6,52 7,10 5,40 8,24 6,07 7,44 8,26 11,81 7,47 4,90 Loser 0,54 -1,37 1,42 4,50 3,78 -0,63 0,75 -0,83 2,42 2,38 -2,28 2,36 Std dev 7,23 8,39 8,78 12,81 9,44 9,58 5,56 5,32 4,70 9,76 9,05 4,53 W-L -0,05 -1,02 1,18 -6,39 -9,16 -1,23 -1,70 -2,49 -1,19 -3,28 -3,06 0,37 T-test -0,04 -0,58 0,77 -3,21*** -6,17*** -0,69 -1,46 -1,95* -0,92 -1,52 -1,85* 0,39 -6 Winner 0,16 0,15 1,86 0,84 -1,09 -0,98 2,05 0,38 2,07 0,33 -0,89 2,24 Std dev 7,36 10,01 6,59 7,84 4,61 9,85 8,14 5,92 7,79 11,67 8,53 5,03 Loser 1,12 -1,45 0,78 4,35 -0,65 -0,81 -0,15 -1,30 1,63 1,96 -4,94 1,85 Std dev 4,53 7,61 5,35 10,40 11,32 10,01 5,01 5,96 6,38 10,15 7,45 3,89 W-L -1,86 -0,34 0,49 -5,74 -3,48 -2,66 0,75 0,18 0,44 -3,35 2,23 1,61 T-test -1,57 -0,19 0,41 -3,14*** -2,18** -1,34 0,57 0,16 0,31 -1,54 1,40 1,81* -7 Winner 0,19 -0,54 2,96 2,10 -0,21 -2,07 1,40 0,78 1,84 1,38 -2,59 2,41 Std dev 6,32 9,57 5,30 9,53 7,09 8,85 6,51 6,68 7,89 12,21 8,92 2,61 Loser 0,85 -1,63 0,65 4,53 -0,34 -2,17 1,27 -1,28 2,02 -0,52 -2,56 1,63 Std dev 6,50 7,62 6,75 8,56 8,17 9,61 5,90 6,58 5,91 9,61 6,05 2,93 W-L -1,57 -0,85 1,72 -4,66 -2,90 -2,38 -1,32 0,57 -0,19 0,18 -1,85 2,01 T-test -1,23 -0,50 1,43 -2,58*** -1,90* -1,29 -1,06 0,43 -0,14 0,08 -1,23 3,62*** -8 Winner 1,71 0,72 4,20 -0,29 -1,93 -1,53 0,22 -0,88 3,30 1,10 -1,97 0,58 Std dev 7,26 10,13 5,27 4,46 5,61 10,00 5,47 6,74 6,56 9,91 7,72 4,52 Loser 0,30 -1,07 2,26 1,86 -1,03 -1,18 1,96 0,29 2,48 2,40 -1,72 1,85 Std dev 4,48 8,07 6,24 10,16 4,54 9,44 6,31 6,18 6,46 10,95 8,48 3,43 W-L 0,50 -0,15 1,35 -4,38 -3,94 -2,83 -3,19 -2,66 0,82 -3,02 -2,07 -0,05 T-test 0,42 -0,08 1,17 -2,99*** -3,88*** -1,46 -2,71*** -2,06** 0,63 -1,45 -1,28 -0,06 -9 Winner 1,31 -0,15 2,18 -0,25 -3,51 -1,08 -0,67 -0,77 2,14 -0,41 -2,84 2,19
Std dev 6,03 9,36 7,54 5,85 6,77 8,62 5,22 5,82 7,38 11,50 8,28 5,01 Loser 0,75 -0,71 1,33 3,26 1,91 -1,31 2,27 0,41 2,30 0,57 -2,58 2,94 Std dev 5,65 8,88 6,96 8,75 8,36 9,76 8,57 5,72 5,17 8,60 7,20 3,46 W-L -0,35 -1,38 0,27 -5,75 -8,45 -2,26 -4,39 -2,66 -0,18 -2,70 -2,08 0,48 T-test -0,30 -0,76 0,18 -3,94*** -5,59*** -1,23 -3,18*** -2,31** -0,14 -1,34 -1,34 0,56 -10 Winner 1,66 0,27 3,85 0,13 -2,70 -1,94 0,22 -0,41 2,76 0,90 -2,24 1,25 Std dev 6,80 10,43 5,03 7,99 7,12 9,11 5,63 6,52 6,32 11,26 7,63 3,13 Loser 2,95 -1,68 2,68 4,45 0,52 -0,54 1,73 -0,72 0,85 2,03 -3,57 2,19 Std dev 8,40 8,48 7,16 11,45 7,28 11,01 7,39 5,79 6,11 10,23 8,31 5,29 W-L -2,20 0,01 0,58 -6,55 -6,26 -3,88 -2,97 -1,18 1,90 -2,84 -0,49 0,28 T-test -1,45 0,01 0,48 -3,37*** -4,35*** -1,93* -2,28** -0,95 1,53 -1,32 -0,31 0,34 -11 Winner 2,90 -0,69 4,62 0,17 -1,87 -2,24 0,17 -0,49 1,67 0,05 -2,30 2,16 Std dev 7,49 9,75 5,24 7,59 6,31 10,44 6,85 4,47 6,75 12,87 9,07 5,04 Loser 1,08 -0,65 0,39 4,47 0,32 -1,25 0,51 -0,19 1,06 3,11 -2,96 0,93 Std dev 4,75 9,36 6,71 11,09 7,60 9,30 5,28 6,43 6,45 10,70 7,33 4,16 W-L 0,92 -1,99 3,65 -6,53 -5,22 -3,46 -1,78 -1,79 0,61 -4,78 -1,15 2,45 T-test 0,75 -1,04 3,05*** -3,49*** -3,75*** -1,76* -1,47 -1,65* 0,46 -2,03** -0,70 2,67*** -12 Winner 0,45 -0,16 0,46 2,73 -1,05 -0,69 0,74 -0,15 2,24 1,67 -2,12 0,60 Std dev 5,85 9,31 7,41 7,93 6,04 9,35 6,67 6,77 5,02 10,25 7,63 3,74 Loser 0,72 -1,32 1,02 1,22 0,81 -1,02 1,19 0,54 1,50 1,76 -4,06 2,27 Std dev 7,27 8,41 8,47 7,39 5,77 9,48 7,02 6,74 5,07 9,59 5,54 3,88 W-L -1,18 -0,79 -1,14 -0,72 -4,90 -2,15 -1,90 -2,19 0,74 -1,81 0,13 -0,45 T-test -0,90 -0,44 -0,72 -0,47 -4,15*** -1,14 -1,39 -1,62 0,73 -0,91 0,10 -0,60
Mexico
In table 9 the average percentage returns of the different portfolio’s for Chile of the last 10 years are summarized. By only investing in the winner portfolio you will get a return of 0.59%, with the loser portfolio a return of 0.65% and in the momentum portfolio of Winner-Loser you will receive a negative return: -1.90%. This negative result is mainly driven through the positive returns of the loser portfolio.
The highest positive return is at ranking period -2 months and a holding period of 2 months, with a positive return of 3,78%. The lowest return is found in ranking period -3 and a holding month of 1 month with a return of -7.98% .
Table 8- Value of the Winner- Loser returns in Mexico
Total Significant Positive value Negative value
90% 144 49 2 47
95% 144 41 1 40
99% 144 28 1 27
In table 9 we can find some outstanding patterns. We can see that for a holding period of 1 month and with a holding period of 12 months, almost all periods have a significant W-L portfolios with a negative return. But this same pattern has different causes. In the first holding period the pattern is driven through the low winner portfolio returns. For the 12 month holding period the loser portfolio returns seem to be high. Further is notable that ranking period -7 ; -8 ; -12 only have 2 significant returns for the different holding periods. Which means that the returns of the portfolios were close to zero.
Table 9- Significance of percentage portfolio returns for Mexico 1 2 3 4 5 6 7 8 9 10 11 12 -1 Winner -3,10 0,27 5,74 -3,79 -2,26 0,40 3,23 -3,65 1,83 -0,96 2,80 4,87 Std dev 11,54 5,92 11,38 7,78 8,96 9,56 6,61 7,22 7,54 9,39 6,48 11,85 Loser -2,42 -0,72 6,14 -0,64 1,80 -0,19 1,00 0,14 0,50 1,36 -0,44 1,17 Std dev 9,62 4,85 9,88 8,92 11,74 11,27 10,03 3,81 8,95 13,49 4,92 9,77 W-L -4,43 0,71 0,37 -7,74 -4,92 -0,98 0,65 -5,22 0,56 -4,63 2,07 -0,24 T-test -2,09** 0,66 0,17 -4,64*** -2,38** -0,47 0,39 -4,73*** 0,34 -2,02** 1,81* -0,11 -2 Winner -1,42 1,25 5,41 -2,26 1,19 1,50 0,86 0,54 0,36 1,41 2,70 2,03 Std dev 11,54 6,49 11,27 8,76 7,60 11,45 6,43 4,51 7,43 11,84 6,08 11,34 Loser -2,63 -2,81 4,71 -1,65 3,73 -0,69 0,55 -2,59 3,39 0,07 2,32 3,43 Std dev 9,11 6,32 10,70 7,38 11,78 10,10 11,00 6,06 8,07 13,40 5,08 10,48 W-L -2,53 3,78 1,47 -5,22 -3,40 0,62 -1,27 1,71 -3,81 -0,97 -0,78 -5,33 T-test -1,22 2,95*** 0,67 -3,23*** -1,75* 0,29 -0,73 1,62 -2,46** -0,39 -0,70 -2,44** -3 Winner -4,38 0,68 5,90 -4,39 -0,21 -0,53 0,26 -1,66 -0,66 -0,30 1,68 2,50 Std dev 9,48 5,09 10,71 6,80 7,05 10,82 5,97 8,77 8,42 9,28 6,32 9,61 Loser -0,15 -0,13 6,87 -2,48 1,41 1,37 1,26 -0,42 3,56 0,12 0,22 1,24 Std dev 9,78 5,58 8,94 8,17 10,36 12,00 10,74 4,78 6,92 13,85 3,93 9,15 W-L -7,98 0,54 -0,21 -6,52 -2,48 -3,47 -2,58 -2,66 -5,00 -2,74 0,30 -2,68 T-test -4,14*** 0,51 -0,11 -4,35*** -1,43 -1,52 -1,54 -1,97** -3,26*** -1,18 0,29 -1,43 -4 Winner -3,43 0,58 5,69 -3,05 -0,37 0,08 1,37 -0,85 2,69 -0,36 3,83 0,16 Std dev 8,73 6,65 8,26 8,60 7,24 10,55 6,90 6,49 6,35 8,72 7,56 6,81 Loser -0,85 -0,52 4,36 -2,40 2,47 0,41 1,04 -1,51 1,97 0,65 2,10 1,54 Std dev 10,97 4,61 9,96 6,88 10,46 9,66 8,13 4,32 9,25 13,76 5,99 9,81 W-L -6,32 0,83 2,09 -5,25 -3,70 -1,90 -1,26 -0,76 -0,06 -3,33 0,56 -5,31 T-test -3,21*** 0,74 1,15 -3,39*** -2,09** -0,94 -0,84 -0,70 -0,04 -1,48 0,41 -3,20***
-5 Winner -3,02 0,48 7,75 -2,89 0,85 0,12 1,51 -0,61 1,86 0,33 1,64 2,65 Std dev 9,38 4,78 10,77 8,15 9,05 11,16 7,44 7,67 7,73 11,05 7,31 9,54 Loser -0,50 -0,68 5,51 -2,04 1,13 0,65 1,17 0,19 0,82 -0,77 3,41 3,96 Std dev 10,29 5,30 10,13 7,77 8,99 10,81 5,07 4,60 7,76 13,44 5,15 10,23 W-L -6,26 0,89 3,01 -5,45 -1,14 -2,10 -1,25 -2,22 0,26 -1,22 -2,94 -5,24 T-test -3,18*** 0,89 1,44 -3,42*** -0,63 -0,96 -1,00 -1,81* 0,17 -0,50 -2,36** -2,65*** -6 Winner -2,53 0,10 3,97 -3,51 0,74 -0,28 1,39 -2,35 2,46 -1,74 2,69 0,70 Std dev 7,75 5,37 7,97 7,33 8,68 9,46 7,27 6,63 6,85 10,33 6,46 9,27 Loser -1,74 -1,58 6,42 -2,27 0,52 0,33 1,65 -0,61 2,21 2,41 2,41 3,90 Std dev 8,87 4,90 10,38 7,56 8,98 8,63 7,48 5,70 6,75 13,56 6,31 10,53 W-L -4,54 1,41 -1,68 -5,84 -0,64 -2,19 -1,84 -3,17 -0,52 -6,47 -0,88 -7,13 T-test -2,73*** 1,37 -0,91 -3,92*** -0,36 -1,21 -1,25 -2,57** -0,38 -2,71*** -0,69 -3,60*** -7 Winner -3,97 -0,27 5,91 -3,63 1,34 -0,59 1,80 -2,15 3,08 1,21 2,60 3,47 Std dev 10,29 4,29 12,27 7,78 8,27 9,53 6,78 9,03 5,96 10,46 6,92 7,47 Loser -1,65 0,11 6,14 -3,00 -1,54 0,28 -0,25 -3,35 1,30 -0,02 2,54 -0,35 Std dev 11,52 5,34 8,36 8,07 7,23 9,32 7,83 6,96 8,14 8,29 7,73 7,96 W-L -6,07 -0,65 0,53 -5,23 2,02 -2,45 0,47 -0,22 1,00 -1,08 -1,10 -0,12 T-test -2,78*** -0,67 0,26 -3,30*** 1,30 -1,30 0,32 -0,14 0,71 -0,58 -0,75 -0,08 -8 Winner -1,81 -0,63 5,64 -1,21 2,77 1,51 0,43 -0,91 0,98 2,47 2,80 1,29 Std dev 7,72 6,41 11,18 8,03 9,86 9,63 10,22 6,48 9,82 12,84 5,96 8,31 Loser -1,64 -0,44 6,06 -3,05 -0,35 0,85 1,60 -1,81 1,22 -0,06 1,06 2,30 Std dev 11,87 6,15 8,86 7,19 8,31 9,85 7,82 6,53 6,39 9,66 5,24 6,87 W-L -3,91 -0,46 0,35 -2,76 2,26 -0,91 -2,75 -0,52 -1,02 0,21 0,57 -4,94 T-test -2,00** -0,37 0,18 -1,81* 1,25 -0,47 -1,52 -0,40 -0,63 0,09 0,51 -3,26*** -9 Winner -2,81 -1,02 5,18 -1,44 1,18 -0,31 1,98 -2,81 1,83 -0,37 2,85 1,00
Std dev 14,15 6,62 12,36 6,72 8,25 9,43 7,06 8,14 6,69 11,62 7,77 9,18 Loser -4,11 2,01 6,06 -1,48 3,66 -0,25 2,36 1,48 1,51 -1,14 2,86 2,92 Std dev 8,92 4,35 10,04 5,94 10,03 9,61 9,79 5,60 7,65 11,00 6,19 10,15 W-L -2,45 -3,30 -0,11 -4,56 -3,34 -1,63 -1,97 -5,72 -0,45 -1,54 -1,18 -5,84 T-test -1,06 -3,00*** -0,05 -3,60*** -1,83* -0,85 -1,17 -4,16*** -0,32 -0,68 -0,84 -3,02*** -10 Winner -3,11 0,38 4,55 -3,25 0,87 -0,27 1,41 -1,86 1,86 -2,52 2,99 1,55 Std dev 8,06 5,28 11,17 7,22 7,66 9,92 7,36 6,87 8,07 10,29 6,78 7,29 Loser -3,27 -1,48 5,85 -3,57 0,55 0,31 -1,20 -2,09 1,51 1,22 1,91 3,06 Std dev 10,03 5,21 9,59 7,87 8,02 10,13 8,21 6,20 8,01 12,09 7,18 10,43 W-L -3,59 1,58 -0,53 -4,28 -0,55 -2,16 1,02 -1,19 -0,43 -6,06 -0,09 -5,44 T-test -1,98** 1,51 -0,26 -2,84*** -0,35 -1,08 0,66 -0,91 -0,26 -2,71*** -0,07 -3,07*** -11 Winner -1,92 -0,54 4,61 -1,88 3,19 0,39 0,77 -1,13 2,55 1,77 1,16 3,01 Std dev 10,03 3,93 10,90 6,89 10,39 9,77 7,37 5,97 8,76 10,92 5,47 10,11 Loser -4,40 -0,58 5,46 -3,32 1,16 -0,41 1,23 -3,31 0,48 -1,12 2,39 0,77 Std dev 11,28 6,23 11,44 6,02 9,97 10,88 8,32 8,59 8,56 11,43 5,80 7,01 W-L -2,81 0,51 -0,13 -2,58 2,70 -2,35 -2,39 0,25 -0,60 -4,67 -4,16 0,76 T-test -1,32 0,50 -0,06 -2,00** 1,33 -1,14 -1,52 0,17 -0,35 -2,09** -3,69*** 0,44 -12 Winner -3,38 -1,51 6,61 -1,73 -0,73 -0,72 2,96 -0,62 2,52 0,56 1,88 1,06 Std dev 9,93 5,22 10,32 9,15 7,36 11,02 6,31 7,71 7,16 11,49 4,33 7,32 Loser -3,95 -0,31 6,53 -3,54 1,06 0,87 0,01 -0,41 0,00 1,33 1,62 2,59 Std dev 9,72 5,13 12,37 5,63 8,39 9,56 7,01 4,59 8,01 8,34 5,97 9,70 W-L -3,17 -1,48 0,84 -2,80 -2,65 -3,16 1,36 -1,63 1,74 -3,09 -0,91 -5,46 T-test -1,61 -1,43 0,37 -1,89* -1,68* -1,53 1,02 -1,33 1,15 -1,56 -0,88 -3,21*** The table provides the percentage returns of Mexico for the winner, loser and winner-loser portfolio. The calculations are based on a -1 till -12 month ranking period and the portfolios are kept for a period of 1 till 12 months. The monthly returns are calculated through ranking stocks and create from the 20% best/worst stocks the winner and loser portfolio. The standard deviation of the stocks is calculated with the formula : √(VAR/n). The T-test indicates whether the percentage return of the W-L portfolio is statistically different from zero and is calculated with the formula : Return W-L /√(VAR/n). *, **, *** means significant at 90%, 95% and 99% respectively.
Peru
In table 11 the average percentage returns of the different portfolio’s for Peru of the last 10 years are summarized. By only investing in the winner portfolio you will get a return of 0.14%, with the loser portfolio a return of 0.35% and in the momentum portfolio of Winner-Loser you will receive a negative return: -2.97%. This negative result is mainly driven through the positive returns of the loser portfolio.
The highest positive return is in ranking period -9 months and holding period of 11 months, with a positive value of 9.01%. The lowest return is found in Ranking month -8 and holding period of 4 months with a return of -13.34% .
Table 10- Value of the Winner- Loser returns in Peru
Total Significant Positive value Negative value
90% 144 54 7 47
95% 144 43 5 38
99% 144 18 2 16
In table 11 we can find some outstanding results. We can see that for all holding periods , ranking period -3 has the most significant results. Most of the significant results have a negative return, this is mainly driven through the high positive loser portfolio returns. The most significant results are at holding period 5, all of these returns are negative and driven through low winner portfolio performance.
Table 11- Significance of percentage portfolio returns for Peru 1 2 3 4 5 6 7 8 9 10 11 12 -1 Winner 2,86 0,09 5,36 1,21 -4,68 -2,64 3,59 0,64 6,05 -3,34 2,92 4,02 Std dev 15,16 12,71 14,39 25,99 11,84 16,77 9,92 9,92 13,83 8,90 14,92 9,31 Loser 3,56 4,02 4,07 -1,49 -1,37 -4,36 -1,51 -1,75 1,44 -7,91 -0,70 1,30 Std dev 13,70 15,42 23,20 17,29 19,55 17,21 7,47 12,83 16,66 9,78 9,87 6,47 W-L -3,07 -7,15 -3,07 -4,52 -8,90 -2,52 4,94 -0,20 3,74 0,34 6,13 2,00 T-test -1,06 -2,54** -0,82 -1,05 -2,83*** -0,74 2,84*** -0,09 1,23 0,18 2,47** 1,27 -2 Winner 2,04 0,62 -0,52 -5,47 -4,82 -4,83 3,01 0,14 0,29 -5,62 -0,70 2,05 Std dev 12,76 12,09 13,76 21,52 13,30 14,82 10,86 9,61 14,44 12,16 13,16 10,18 Loser 3,03 -1,54 7,75 -2,94 -3,81 -3,20 0,97 0,21 3,40 -5,73 -0,17 2,01 Std dev 9,29 14,95 29,74 20,78 18,52 16,70 8,56 10,35 13,17 6,29 12,88 9,53 W-L -3,35 -1,06 -12,63 -9,75 -6,60 -5,88 1,88 -2,67 -3,97 -4,12 1,99 -0,69 T-test -1,52 -0,39 -2,90*** -2,31** -2,08** -1,86* 0,97 -1,34 -1,44 -2,23** 0,76 -0,35 -3 Winner 0,85 1,33 0,65 -5,78 -3,17 -5,87 0,16 -2,06 5,49 -5,37 3,64 0,44 Std dev 7,49 10,17 17,11 18,35 11,84 15,01 9,32 8,05 13,56 8,27 9,54 9,61 Loser 4,51 0,91 4,82 -3,47 -2,73 -1,41 2,37 2,93 4,07 -3,87 1,63 3,14 Std dev 12,61 17,13 27,22 18,43 17,45 14,74 9,24 15,76 11,83 9,90 12,40 10,99 W-L -6,03 -2,80 -8,53 -9,54 -6,03 -8,70 -2,36 -7,58 0,56 -5,73 4,53 -3,42 T-test -3,00*** -1,03 -1,93* -2,59*** -2,06** -2,92*** -1,27 -3,18*** 0,22 -3,15*** 2,06** -1,66* -4 Winner 0,51 2,34 2,77 -1,57 -1,01 -5,37 2,71 -0,99 3,67 -4,79 1,86 3,51 Std dev 7,00 8,03 19,39 17,50 12,14 16,80 8,64 11,20 11,57 7,96 14,34 11,96 Loser 4,68 2,78 10,99 -4,44 -3,11 -2,66 1,11 -1,24 4,55 -5,37 3,55 2,29 Std dev 11,57 18,44 29,68 18,93 18,95 17,25 8,74 10,34 16,88 10,99 15,11 8,75 W-L -6,53 -3,65 -12,58 -4,36 -3,49 -6,96 1,44 -2,35 -1,74 -3,65 0,82 0,50 T-test -3,52*** -1,38 -2,56** -1,20 -1,12 -2,04** 0,83 -1,09 -0,61 -1,93* 0,28 0,24 -5 Winner 3,28 2,46 4,15 -2,08 -5,00 -4,10 1,34 -1,23 3,89 -3,58 0,26 3,16 Std dev 11,08 17,25 15,24 22,39 14,94 16,65 10,10 7,21 16,32 10,59 7,52 8,31 Loser 0,05 -0,35 4,98 -2,88 -2,70 -4,94 4,94 -1,11 3,40 -3,77 5,71 3,26 Std dev 9,41 11,97 21,48 21,75 15,19 16,18 10,75 9,17 13,68 10,00 11,32 9,10 W-L 0,86 -0,41 -5,18 -6,42 -7,88 -3,41 -3,76 -2,72 -0,37 -4,04 -2,93 -0,82 T-test 0,42 -0,14 -1,41 -1,46 -2,62*** -1,04 -1,80* -1,66* -0,12 -1,96** -1,56 -0,47 -6 Winner 0,53 0,06 1,10 -2,06 -1,56 -0,52 3,35 0,39 2,21 -4,43 -0,71 0,81 Std dev 15,28 17,46 15,95 18,46 16,58 20,13 9,33 12,13 14,13 8,13 10,38 6,41 Loser 2,89 -0,53 7,76 -3,74 -2,39 -5,57 2,49 -2,75 4,08 -6,67 3,32 1,33 Std dev 8,99 12,96 26,58 19,97 18,31 14,67 7,80 10,83 12,63 8,67 13,71 8,21 W-L -4,72 -2,63 -11,02 -5,54 -4,75 0,80 0,71 0,53 -2,73 -1,99 -1,52 -1,24 T-test -1,95* -0,86 -2,59** -1,44 -1,36 0,23 0,41 0,23 -1,02 -1,18 -0,63 -0,85 -7 Winner 4,74 1,88 3,35 -4,38 -2,17 -0,19 1,13 -1,00 3,43 -5,40 -0,23 6,87
