Sibbe Jan Noppert 6055249
University of Amsterdam Faculty of Economics and Business
July 2015
Abstract
Existing theory suggests that for calculating the expected return or the price of an asset, religion is not a factor. This thesis proofs otherwise.
Keywords: CAPM, Fama-French, Religion Bias, Home Bias, Cohort effect, Carhart four factor model, Risk Aversion, Religion, Islamic finance
Data availability: Excel with answers from questionnaires
Bachelor: Economics and business Specialization: Finance and Organization Field: Finance
Supervisor: Timotej Homar Number of EC: 18
I. Introduction
The financial markets are in turmoil these years. Financial crisis`, Euro area crisis and even today, Greece is on the brink of default. The economy is cause for daily headlines in newspapers. Therefore economic theory is more on the mind of society, this thesis wants to add something to the discussion.
Assets go up and down in markets, every second, but how does the price of an asset becomes its price. That’s the subject of this thesis. We will question the theory that should explain the price or is the way to price the asset.
We are examining existing theory regarding asset pricing, the most famous being the CAPM of Sharpe and Lintner and the Fama and French three factor model, with an extension you have the four factor model of Carhart. Theory does not provide a role for religion, but we found that 59% of the people in our survey choose a lower return if the money is invested in a Islamic country and 37% is willing to take on more risk if the money is invested in an Islamic country. We also find new proof for the home bias.
People with or without savings do not answer differently, nor do people answering in a mosque and income is also not relevant in explaining people their choices. Age does matter, people under 30 seem more strict in answering where those above 30 take it a little bit easier. Test were significant up to 0% probability, although 35 respondents is a little sample.
The first section of this work provides an introduction. The remainder of this paper is built up as followes. First, in section II, there is a literature review on existing papers that have been researching asset pricing, religions, biases in investments and survey`s, attitudes toward risk and more. Then, in section III, Empirical methodology provides the hypothesis and the methodology. Section IV discusses the data and some details. In section V, the results of this research are summarized, Section VI covers the robustness checks and strengths and weaknesses of the results are discussed in section VII. Finally this leads to a conclusion in section VIII.
II. Literature review
This section discusses relevant literature. In the first paragraph asset pricing will be discussed, we start with Markowitz, continue with the CAPM models and end with the four factor model of Carhart. The other paragraphs will discuss biases regarding risk aversion and the cohort effect. The review ends with the discussion of articles on the Islam, Islamic finance and Christianity.
II.1 Asset pricing
The process of selecting a portfolio can be divided into two stages according to Markowitz. The first stage starts with observation and experience and ends with beliefs about the future performances of available securities. The second stage starts with the relevant beliefs about future performances and ends with the choice of portfolio (Markowitz, 1952). Markowitz introduces the "Expected returns-variance of returns" rule or E-V rule. It points out two important things. An investor considers expected return a desirable thing (or should) and the variance of this return as undesirable (Markowitz, 1952). Markowitz was rewarded with a Nobel prize in economics In 1990, together with Sharpe and Miller for their contributions.
Sharpe (1964) states that Tobin showed that under certain conditions Markowitz`s model implies that the process of investment choice can be broken down into two phases: first, the choice of a unique optimum combination of risky assets and second, a separate choice concerning the allocation of funds between such a combination and a single riskless asset. This finding is named the "separation theorem" by Fama and French (2004).
Sharpe (1964) and Lintner (1965) add two key assumptions to the Markowitz model. The first is complete agreement: given market clearing asset prices at t - 1, investors agree on the joint distribution of asset returns from t - 1 to t. And this distribution is the true one; that is, it is the distribution from which the returns we use to test the model are drawn. This is part of what Sharpe calls homogeneity of investor expectations (1964) and what Friend and Blume call: "perhaps the most critical assumption" (1975). Lintner calls this also "idealized uncertainty" but relaxes the assumption in 1969 (French, 2003). The second assumption is that there is borrowing and lending at a risk-free rate, which is the same for all investors and does not depend on the amount borrowed or lend (Fama and French, 2004).
By adding risk-free lending Markowitz` model can be extended so that a capital market line can be constructed, Sharpe (1964). According to Sharpe the market presents two prices to the investor: the price of time, or the pure interest rate (later on, the risk free rate (French, 2003; Fama and French, 2004) and the price of risk, the expected return per unit of risk borne (Sharpe, 1964). The price of risk is called by Sharpe the R/V ratio in his paper of 1966, nowadays it goes by the Sharpe ratio (Dowd, 2000). The Sharpe ratio is equal to the slope of the capital market line.
The capital asset pricing model or CAPM as it came to be known was initially developed by Sharpe, Lintner and Mossin (French, 2003). According to French (2003) Treynor allready pointed out in 1962 (unpublished manuscript) that there is a distinction between insurable and uninsurable risk. Sharpe introduces in 1964 the term systematic risk. You have risk that is correlated to the benchmark portfolio and there is risk uncorrelated. Since the benchmark is defined as the market, Sharpe sees the correlated risk as the risk that comes from swings in the economic activity. The risk uncorrelated with the market, is also called "idiosyncratic risk" (Goyal and Santa-Clara, 2003). Diversification enables the investor to escape all but the risk resulting from swings in economic activity, this type of risk even remains in efficient combinations (Sharpe, 1964), this has a lot in common with what Treynor calls uninsurable risk. Let the insurance be diversification.
The model that Fama and French (2004) call the Sharp-Lintner CAPM in words: The expected return on any asset, is the risk-free interest rate, plus a risk premium, which is the asset`s beta (correlation with the market), times the premium per unit of beta risk, the premium is equal to the market return minus the risk free rate.
Since the Sharp-Lintner CAPM should fully explain the expected value of an assets expected excess return. This implies that the intercept term in a time series regression, Jensen 1968, should be zero, otherwise there is money to be made. The name of this money to be made came to be known as the "Jensens alpha" (Fama and French, 2004).
Fisher Black developed in 1972 a version of CAPM without risk-free borrowing or lending. He shows that the CAPM`s key result, that the market portfolio is mean-variance-efficient, can instead be obtained by allowing unrestricted short sales of risky assets (Fama and French, 2004).
Merton`s Intertemporal Capital Asset Pricing model (ICAPM), published in 1973, is a natural extension according to Fama and French. It begins with a different
assumption about investor objectives. In the ICAPM, investors are concerned not only with their end-of-year payoff, but also with the opportunities they will have to consume or invest (in) the payoff.
Empirical evidence (Fama and French, 2004) points out that much of the variation In expected return is unrelated to correlation with the market. In 1977 Basu finds evidence that when common stocks are sorted on price earnings ratios, future returns on high E/P stocks are higher than predicted by the CAPM. Banz documents in 1981 a size effect: when stocks are sorted on market capitalization, average returns on smaller companies are higher than predicted by the CAPM and Bhandari (1988) that high debt-equity ratios (book value of debt divided by the market value of equity) are associated with returns that are too high relative to their market betas (Fama and French, 2004).
This last finding is also contra dictionary to Proposition I of Modigliani and Miller, which asserts that, in equilibrium, "the market value of any firm is independent of its capital structure” (1958). From this should follow that the explanation of the variance in returns of stocks or assets should also be unrelated to the capital structure of the firm.
Besides the findings mentioned there are also findings from Statman in 1980 and from Rosenberg, Reid and Lanstein in 1985 that document that stocks with high book-to-market equity ratios (B/M, book value of stock divided by the market value of equity) have high average returns that are not captured by their betas (Fama and French, 2004).
After empirical testing by Fama and French (Fama and French, 2004), they come up with the three factor model. Simply explained, it is the Sharp-Linter CAPM extended with two variables. The first new variable is SMB, which stands for small minus big, it is the difference in returns between diversified portfolios of small and big stocks. The second is HML, this stands for high minus low, it’s the difference in returns between diversified portfolios of high and low B/M stocks.
In 1993 Jegadeesh and Titman found that stocks that performed well in recent months tend to do well in the next months and similarly, bad performing stocks continued to perform bad in the next few months. Carhart extends the three factor model to a four factor model in 1995 with the extension of the "Carhart momentum factor", defined as equal-weight average of firms with the highest 30% eleven month returns lagged one month minus the equal weight average firms with the lowest 30% eleven months returns lagged one month (Carhart, 1997).
II.2 Home Bias
Diversification is what Treynor sees as a type of insurance (French, 2003). Sharpe, Markowitz, Fama and French, Carhart and others, regard diversification as crucial.
And the benefits of international diversification have been recognized for decades. In spite of this, most investors hold nearly all of their wealth in domestic assets. The lack of diversification appears to be the result of investor choices, rather than Institutional constraints. Domestic ownership of stocks in the largest 5 stock markets are: 95,7% in Japan, 92,2% in the USA, 92% In the UK, 89,4% in France and 79% In Germany (French and Poterba, 1991). They also find that between 1975 and 1989 the pairwise correlation between these 5 countries together with Canada is 0.502, this is for the pairs of these 6 countries. The results are similar if the returns are measured in Yen or Pounds, and whether or not the exchange rate is hedged (French and Poterba, 1991).
Taxes are considered a possible explanation although most investors are tax exempt and those paying taxes pay or in their home country or abroad, but regulation more often than not prevents double taxation and if not, it would reduce returns by 50 basis points (French and Poterba, 1991). Besides institutional constrains there are also possible explanations from the perspective of investor behaviour. One possibility is that return expectations vary systematically across groups of investors. A second reason could be that the statistical uncertainties associated with estimating expected returns in equity markets make it difficult for investors to learn that expected returns in domestic markets are not systematically higher than those abroad. Another reason could be that investors may impute extra "risk" to foreign investments because they know less about foreign markets, Institutions and firms (French and Poterba, 1991).
The evidence of Incomplete diversification presented here is consistent with evidence from many other markets. Lease, Lewellen and Schlarbaum showed in 1974 that in the late 1960`s many individuals held relatively few stocks/securities (French and Poterba, 1991) and Tesar and Werner conclude that there is a tendency that individuals hold ill-diversified portfolios (1995).
French and Poterba consider another example of incomplete diversification and that is the tendency of most households to own residential real estate near their work. Returns on their human and physical capital may consequently be highly correlated.
Tesar and Werner (1995) write that earlier work by Grubel, Levy and Sarnat, Solnik and Grauer and Hakansson suggest that the risk of an investment portfolio can be
reduced by incorporating foreign securities. Tesar and Werner reach some of the same conclusions as others. The two most important conclusions they draw: first, there is strong evidence of Home Bias in the national portfolios of the countries they studied. Secondly, studying US-Canada data, suggests that to the extent that foreign Investors hold foreign securities, the composition of the portfolio of foreign assets may reflect factors other than diversification of risk. Tesar and Werner cited a paper from Solnik (1974), where they found a possible reason for home bias in the bond market. "Allowing for differences in preferences over the currency denomination of the portfolio generates some heterogeneity in asset holdings, although this typically has a bigger impact on the allocation across bond markets, where the largest source of risk is due to stochastic deviations from power purchasing parity. This risk may induce a home bias toward domestic bonds, but has no effect on the portfolio allocation across equities" (Tesar and Werner, 1995). They also found that residents from the USA and Canada invest heavily in each other`s market, given the high correlation between the two aforementioned markets, this contradicts the notion that investors primarily seek portfolio diversification by choosing foreign markets which have a low correlation with the domestic market. Instead it suggests that other factors such as geographic proximity, strong trading linkages or the lack of a language barrier may matter potentially even more then the diversification motive per se for portfolio choice. The paper also mentions that state law in the US might contribute to a bias, since US Insurance companies can hold a maximum of 3% of assets overseas, of which the equity proportion cannot exceed 20%.
The final contribution of the paper of Tesar and Werner is an answer on the question: do transaction costs play a part in the Home Bias Puzzle? They find that foreign investors have relatively higher turnovers, without changing their net positions. If transaction costs would play a role, they expected a lower turnover.
Coval and Moskowitz (1999) studied the home bias in the domestic markets, they summarize the initial explanations: Governmental restrictions of capital flows, taxes and high transaction costs. Although all of these obstacles have diminished, the propensity to invest in one`s home country remains strong. They come up with two groups of possible explanations: explanations associated with the existence of national boundaries and explanations associated with the preference for geographic proximity (Tesar and Werner, 1995).
The first group of explanations is covered by Tesar and Werner. We will discuss the second group here. A key point largely overlooked in the debate according to Coval and Moskowitz, is that not all home bias explanations rely on properties unique to the international economy. For instance, the existence of national boundaries may amplify information asymmetries and the concern for hedging non-tradeable goods, but these frictions also arise when there is no country border and it is the geographic distance that separates an investor from potential investments. Investors might have for example easier access to information about companies located near them, local investors can talk with employees and suppliers of the firm. Local media might provide them with better information. All these possible situations could provide an information advantage in local stocks (Coval and Moskowitz, 1999). Likewise, investors may prefer proximate investments in order to hedge against price increases in local services or in goods not traded easily outside the local area. More generally, investors might feel simply more comfortable about local companies, or they may have a psychological desire to invest in the local community, local stock brokers could also play a role, by encouraging local investments (Coval and Moskowitz, 1999).
Coval and Moskowitz also find that local equity preference is strongly related to three firm characteristics: firm size, leverage and output tradeability. Specifically, locally held firms tend to be small and highly levered.
The extrapolation to a global level and findings of the paper are not shared by me. Their conclusions are that fund managers are on average 1,654 km. to 1,663 km. away from the securities they choose to hold, and 1,814 km. to 1,847 km. away from their benchmark portfolio. Thus the average manager invests in securities 160 km. to 184 km. closer to him, I consider this very weak, but it is cited a lot.
Coval and Moskowitz talk about information asymmetries, holding local firms and talking to managers, the writer disagrees that a distance of 1,654 km. is to be considered local, so that these benefits can be accrued and that 160 km. further away, this is not the case anymore. This is 2 hours by airplane or 10 minutes extra.
Concluding Coval and Moskowitz mention that in terms of geographic distance it might be more useful to think in economic distance, they point to airfares and phone rates as signals for this.
Portes and Rey come up with a gravity model that explains international transactions in financial assets at least as well as goods trade. They find that transaction
flows depend on market size in source- and destination country as well as trading costs. Another finding is that a greater distances between countries corresponds to lower correlations between business cycles of countries, which in its way should mean that there is more to gain when it comes to diversification, this is the complete opposite of the home bias (2005).
With relation to language, Portes and Rey point out that when looking at the results made on the German stock market, German speaking people; those from Germany and Switzerland have better returns then foreign non-German speaking investors, they cite a paper by Hau from 2001.
The Gravity model made by Portes and Rey accounts for 70% of the variance in transaction flows. The results are robust to various dummy variables, which were already mentioned earlier: adjacency, language and currency- or trade bloc.
Countries populated by more patriotic individuals tend to more severely overinvest in domestic equities according to Niszczota (2014).
II.3 Generational biases
The first bias is called the "Cohort Effect", the (main) cohort effect is that people who are born in a large cohort or generation, have a higher overall earnings level than those born in a small cohort and they have also a different shape of earnings profile. Furthermore, cohorts born in an upswing of a boom have a higher earnings level then cohorts born in a downswing, these results are fairly significant and consistent also across gender, not across education level (Dahlberg and Nahum, 2003).
When the results of the survey are analysed, this is something to keep in mind. Standard models in economics assume that individuals are endowed with stable risk preferences, unaltered by economic experiences. Standard models also assume that individuals incorporate all available historical data when forming beliefs about risky outcomes. In contrast, the psychology literature argues that personal experiences, especially recent ones, exert a greater influence on personal decisions than statistical summary information in books or via education (Malmendier and Nagel, 2009). More recent literature as cited by Malmendier and Nagel, suggest that the cultural and political environment in which individuals grow up affect their preference and belief formation, such the level of trust in financial institutions or stock market participation.
Using data from 1964 to 2004, they find that individuals who have experienced low stock-market or bond returns throughout their lives report lower willingness to take financial risk, are less likely to participate in the stock or bond market, and, conditional on participating, invest a lower fraction of their assets in stocks. Something that might cause a lower accumulation of wealth (D`Acunto et. al., 2014). Their estimates indicate that recent return experiences have stronger effects, but experiences early in life still have significant influences, even decades later (Malmendier and Nagel, 2009).
II.4 Risk aversion
K.J. Arrow (1965) and J.W. Pratt (1964) introduced two formulas, two utility functions. The Arrow-Pratt absolute and relative risk aversion functions. Pratt also talks about the propensity to insure besides "risk aversion" (Pratt, 1964). The importance of one of the functions arises when considering an individual’s aversion to risk as wealth Is varied but the risk remains unchanged, while the other becomes relevant when wealth and risk are changed in the same proportion (Menezes and Hanson, 1970). The theory shows that people have different attitudes towards risk, this might be a factor in the survey we held. People have different incomes and so, they might choose different outcomes and not because of religion, but because they just have different attitudes towards taking risk. Since an increase in wealth tends to lower risk aversion (Brunnermeier and Nagel, 2008), people with higher incomes might choose riskier options.
Instead of taking more risk, a higher income devalues the utility of every marginal currency unit of income. Therefore, one might start to care more about Islamic economic choices after a certain amount of money earned regardless of risk-functions.
II.5 Social responsible Investment
Wilson (1997) talks about Social responsible investment and its opportunities, 40% of the market might want to invest in social responsible investments, but they still expect a higher than average or abnormal return. Wilson calls Islamic or Halal finance another form of social responsible investing, but with different ethical criteria. Western ethical investors have "green" criteria, where Halal investors look amongst others to "riba", "gharar" and "maysir", or interest, transparency and gambling (Hoepner et. al., 2010).
Wilson states also that "ethical finance" could be a marketing ploy, to attract environmental concerned, pacifist or leftist investors. Or even worse, managers could use it so that they have an argument when the returns are lower than expected.
In 2008 (Galema et. al.) there is a newer study, that finds that 10% of all US investments are screened for social responsible concerns. But in contradiction to the excess return mentioned by Wilson, they cite a paper that finds that stocks from sectors with negative ethical issues, alcohol, tobacco, gambling, nuclear power, firearms and military, have higher expected returns.
II.6 Islamic finance and Islam
Economics is fundamentally atheistic. Religious beliefs, practices and behaviour play no role in the homo economicus, is how the paper of Tomes (1985) starts. This thesis is about the opposite, investment choices or expected return requirements do have a relation with religion or Islam here in this paper.
Shariah (Islamic law) considers a few things illegal, already mentioned where: interest and gambling, besides this transparency is required in every transaction. Investing in the pork industry, adult entertainment or alcohol is not allowed under Shariah, regardless of the financial structure.
To deal Shariah compliant there are several financial structures under which financing can take place. Wilson (1997) mentions a few: musharakah, murabaha, mudarabah and ijara. Musharakah is regarded by many Shariah scholars as the mode of financing which comes closest to the Islamic ideal. Musharakah is a form of partnership, where the contract states the amount of funding, the proportion of profit sharing, what happened in the event of losses and the terms of divestment. Murabaha is for short term financing, where musharakah and murabaha are mostly used in long term projects. Ijara is comparable with leasing (Wilson, 1997).
In these four forms there is no interest paid, risks are shared but there is no gambling and when done correctly, transparency is provided.
Hoepner et. al. talks about haram purification, when a Muslim invests in a retail chain that derives 5% of its profits from the sale of pork and alcohol, then 5% of profit should be donated to charity. Hoepner also cites the Dow Jones (2009) and a paper of Derigs and Marzban (2008) where they point out that the Shari`ah Supervisory Board of the DJ Islamic Index, tolerates corporations, whose ratios of total debt, cash, interest
bearing securities and receivables are less than a third of the corporations market capitalisation, other Islamic indexes use similar ratios. This follows from the interest and gambling restrictions.
Niszczota (2014) studied the effect of the Islamic "moral code" (Shariah here) on investment in foreign debt securities. These papers have a lot in common, here we study commonality with existing CAPM theory, the survey asked questions with regard to investment choices.
Niszczota points out (also heard during taking the survey), that there is a debate amongst Islamic scholars if Islam prohibits paying or receiving "normal" interest or excessive interest. In his regression, the following variables are used: geographic distance, common language, legal origination, common religion also as a proxy for cultural similarities, this paper will discuss this In the final discussion and results.
II.7 Christianity
D`Acunto et. al (2014) points out that the reason that Jews have been associated with financial services for centuries is that Christians and Muslims were banned from lending money at interest.
When reading the bible; there is a chapter called "Laws about repayment" Exodus 22, where you as a Christian are not allowed to accept interest. Leviticus 25 is called "Loans to the poor" where charging Interest is prohibited as well. The books of Deuternomium (23:19-20) and Ezekiel (18:8) also prohibited the payment of interest. Deuternomium (15;1) also mentions that loans should be cancelled after 7 years.
We have to point out that although the bible shares the prohibition on the payment of interest, Christians do not seem to act on it.
III. Empirical Methodology III.1 Hypothesis
Existing capital asset pricing theory provides us with six variables that need to be taken into account for calculating the expected return of an asset: The risk-free rate, market risk premium, SML, HMB and the momentum factor. The home bias is also discussed, people tend to invest in their home country, their geographic home, the place closest to them, where their language is spoken and culture is shared.
This thesis points out the different view Muslims have in relation to theory. We want to test if the CAPM models itself apply and its foundations. Do Muslims choose less risk and higher returns?
I think that Muslims might agree to a lower rate of return on investments when the money is invested in their "religious home" country or they might agree to accept a higher risk for the same return. This is contra dictionary to existing theory. The home bias makes the point even more difficult to prove, but might also be able to provide some argumentation why people would invest abroad in a country sharing the same culture, language and religion.
From the above and available data we take our hypothesis:
Hypothesis 1: Lower return
This hypothesis tests if Muslims their return preferences are different from theory. H0: Muslims take the highest return when their money is invested, all other things being
equal (ceteris paribus).
H1: Muslims accept a lower return when their money is invested in a country where Islam is
the major religion (ceteris paribus) Hypothesis 2: More risk
This hypothesis tests if Muslims their risk preferences are different from theory. H0: Muslims take the lowest risk when their money is invested (ceteris paribus).
H1: Muslims accept more risk when their money is invested in a country where Islam is the
major religion (ceteris paribus) Hypothesis 3: Place of survey
This hypothesis tests if Muslims who answered around a mosque answered differently than Muslims in or around a shop.
H0: Muslims who were questioned at the mosque, answer similar to those answering
somewhere else (ceteris paribus).
H1: Muslims who were questioned at the mosque, answer differently from those answering
Hypothesis 4: General consistency
Some people choose the more Islamic option 4 out of 4 times, so very consistent, this hypothesis tests if these answers came more from around the mosque than from the shops.
H0: Muslims who were questioned at the mosque, answer the more Islamic choice in a
similar ratio than those answering outside the mosque (ceteris paribus).
H1: Muslims who were questioned at the mosque, answer the more Islamic choice in a
different ratio than those answering outside the mosque (ceteris paribus) Hypothesis 5: Age
People at certain ages have different preferences, in general older people experienced more in their lives, we test if age matters in answering the survey.
H0: Muslims who are under 30 years old, answer similar to those above 30 years old
(ceteris paribus).
H1: Muslims who are under 30 years old, answer differently from those above 30 years old
(ceteris paribus).
Hypothesis 6: Income
Theory provides proof that people with different levels of income behave differently regarding risk. This hypothesis tests if people with different incomes also answer different.
H0: Muslims who earn between 500€ and 1,500€, answer similar compared to Muslims
earning more than 1,500€ (ceteris paribus).
H1: Muslims who earn between 500€ and 1,500€, answer differently compared to Muslims
earning more than 1,500€ (ceteris paribus).
Hypothesis 7: Consistency in risk (Home Bias)
This hypothesis tests if the people who answered question I regarding risk also answer more often question III regarding risk, the questions can be found in table 2, so that we can say that there is a relation ans that the answers are not random.
H0: Muslims who are willing to take more risk, answer the other risk question similarly to
those not willing to take more risk in the first question (ceteris paribus).
H1: Muslims who are willing to take more risk, answer the other risk question differently
Hypothesis 8: Consistency in return
This hypothesis tests if the people who answered question II regarding the return also answer more often question IV regarding returns, the questions can be found in table 2, so that we can say that there is a relation and that the answers are not random.
H0: Muslims who are willing to accept a lower return, answer the other return related
question similar as those accepting the higher return in the first question (ceteris paribus). H1: Muslims who are willing to accept a lower return, answer the other return related
question differently from those accepting the higher return in the first risk related question (ceteris paribus).
Hypothesis 9: Savings risk
People who have money might make other risk related decisions than those without money, this is what we test here.
H0: Muslims who have savings take similar risks as those without savings (ceteris paribus).
H1: Muslims who have savings take different risks than those without savings (ceteris
paribus).
Hypothesis 10: Savings return
People who have money might make other wealth or income related decisions than those without money, this is what we test here.
H0: Muslims who have savings choose the same return as those without savings (ceteris
paribus).
H1: Muslims who have savings choose more often the higher return as those without
savings (ceteris paribus). III.2 Binominal test
In the survey we have questions with two different outcomes, people can accept the higher versus the lower risk or the higher versus the lower return. The expected value of p, the chance, is 0. From the theory we do not expect anybody to pick a lower return for the same risk, or a higher risk for the same return.
The expected value is = μ= n*p = 35*0=0 The variance is = σ2= n*p*(1-p) = 35*0*(1-0)=0
Here we see that the expected value is 0 and variance as well, from this follows that the standard deviation is 0 as well.
When the expected value is 0 and the variance and standard deviation as well, we do expect 0 times an expect outcome contra dictionary to the theory and we do not expect any deviation from this. So if we do find more than 0 outcomes different from what we expect, we can already reject the H0. (Keller, 2009).
III.3 Chi Squared test
Other data we collected will be used to test if there are statistically significant differences between parts of our populations. We will for example compare answers from age groups, groups with the same income, those who answered around the mosque compared to those answering in a shop and the group of people who have savings against those that do not. The test in short works as followed, you make a contingency table, where you put the actual values of the two answers you cross examine and you calculate the expected values of the amount of answers of each box. If 10 out of 20 people answer a question with yes and 10 of them answer another question with yes, you expect 5 of them to have answered the other question with yes and 5 of them to have answered no, this is how it looks.
Table 1 Q1 Total Q2 Yes No Yes Actual Expected 5 5 10 No Actual Expected 5 5 10 Total 10 10 20
Here you have an table with the expected values, with the Chi-squared test of a contingency table, you test the proportions of the expected values against the proportions of the actual value (Keller, 2009) we use Stata 13 software to do the calculations. If you find statistical strong proof, you have found that the proportions are different from what could be expected from the population.
IV. Data
To test the two hypothesis I held a survey amongst people in mosques or other places which are frequently visited by Muslims. I mailed with 11 Islamic institutions out of which none replied and called 10 days in a row with the head of the mosque near me. Because of Ramadan they did not have time to answer and did not allow me to survey people in their mosque when they had time to answer after two weeks. It took a month to get the first 24 responses I went a few nights to the surroundings of the mosque and got finally 35 responses after a lot of work.
The survey is included in appendix A. The survey asks some background questions, that gives us the possibility to test on proportion of answers regarding age, income, possibly gender and where the persons filled in the survey. It provides us with data about the person behind the choice. Is someone taking more risk, without having any money or income, or are the people with the highest incomes taking the most risk, or just avoiding it? Answering the survey in a shop, where you are busy with money, or answering besides the mosque after prayer might alter choices as well.
IV.1 Description of the dataset
My survey was answered by 38 people, but 3 people only answered the background questions, so I threw them out of the sample. This leaves us with 35 questionnaires with 10 questions, besides the answers from the questions, we also know where they were filled in.
The survey was answered by 5 woman and 30 man.
The age profile of the people filling in the survey was very good for analysing. The survey was filled in by two people of 18 and 19 and two people above 50. The three mid sections all have about the same size.
Regarding the income, two people earned less than 500€ a month. Of one person we do not know the income. 13 earned between 500€ and 1,500€ a month, 19 people earned more monthly than 1,500€.
Figure 3 Figure 2
There was also a question regarding the "type" of Islam, most Sunni I spoke don`t consider Shiite people to be Muslim. One person did not answer this question and another answered that he believed in his own way.
As you can see, most people come from a Moroccan background, where the Turkish and Egyptians come second. One person had a mixed background and there was also one person from the Netherlands who was converted to Islam.
To get answers and to be able to put them in a context I also asked people if they had savings, this might become important in testing for differences between the choices made. Maybe there are significant differences in choices made by people with savings and those without.
Figure 4
The survey was distributed to four
shops, where they were for about three weeks. I also interviewed people inside and in front of the mosque. The people in the shop where there without me and might have been surrounded by others, who could
have potentially influenced them. The shops were a restaurant, satellite store, phone
shop and hairdresser.
The percentage wise ratios are the people who answered the Islamic option Table 2
Questions
I - Would you invest your money in The Netherlands, Germany, Spain, France or for the same return in Indonesia, Pakistan, Morocco, Turkey or Iran with a little bit more risk
II - Would you lend your money for 4% to a country where Islam is big or 5% to a country where Islam is small
III - To what country would you loan your money, to an Islamic country with a little bit more risk or to non-Islamic country with a little bit less risk and the returns are the same
IV - To what country would you loan your money, to an Islamic country with a little bit more interest or to non-Islamic country with a little bit less interest and the risks are the same
Question I II III IV Full sample 26% 59% 37% 49% Savings Yes 29% 50% 21% 43% No 24% 65% 48% 52% Income 500€/1,500€ 38% 54% 23% 54% 1,500€+ 21% 67% 47% 47%
Place of Survey Mosque 33% 45% 33% 50%
Shop 22% 65% 39% 48%
Age Under 30 25% 67% 58% 50%
30 + 26% 55% 26% 48%
Respondents 35 34 35 35
Above you will find a table with all the answers on the four main questions, the questions are also summarized, in the appendix A you can find the survey in Dutch language. The table also shows all the differences between the groups of people questioned.
In the next section you will find the results of the statistical testing on the data. The test-data consists out of four questions regarding risk taking and wanting a lower or higher return, when the money is invested in an Islamic country.
V. Results
Here we will discuss the results of our data collection and statistical calculations. We will mention the original hypothesis and then explain what we found.
Hypothesis 1: Lower return
We had two questions regarding a lower versus a higher return. Question 2 and 4 can be found in table 2.
Out of the 35 people who answered the survey, 20 people choose to lend money to a country where Islam is a big religion for 4% instead of 5% to a country where the Islam was smaller, risk was not a variable in this question (maybe it was implicitly), chosen by 14 (one did not answer the question). The other question asked if people would lend money to an Islamic country for a little bit less than they would charge the non-Islamic country, the risk was the same. 17 people choose the Islamic option for a lower interest rate against 18 who did choose the higher rate.
In this binominal experiment we expected everybody to choose for the higher return and 0 for the lower return, with a standard deviation of 0, there was no statistical room for other answers, with 17 and 20 people choosing the lower return, we reject H0.
H0: Rejected
Hypothesis 2: More risk
We had two questions regarding risk, questions 1 and 3, which can be found in table 2. Out of the 35 people who answered the survey, 26 people the saver option over Indonesia, Pakistan, Iran, Turkey and Morocco, 9 people choose the latter group, which was defined as more risky. When asked if they would lend money to an Islamic country
with more risk or a non-Islamic country with less risk, 22 choose for less risk, but 13 choose for more risk and an Islamic country.
In this binominal experiment we expected everybody to choose for the lower risk. H0: Rejected
Hypothesis 3: Place of survey
People where asked in and around a mosque between fellow believers and people could answer the survey "on their own". We tested if there was a significant difference in the two groups.
We tested on the answers of the two return and the two risk questions. Stata provided a expected ratio, relative ratio, Chi squared output and probability.
For all the four questions there was no significant difference between the groups. Here you can see the Stata output, with the cross-table, expected ratio`s, real ratio, Chi² value and the probability.
Table 3 Return Total
0,04 0,05 Place of survey Mosque Actual 5,0 6,0 11 Expected 6,5 4,5 Shop Actual 15,0 8,0 23 Expected 13,5 9,5 Total 20 14 34 Pearson Chi² 1,1999 Probability 0,273
In this output can be seen that people who answered in the mosque choose 6 times for the higher return versus 4,5 expected (if the ratio`s would be equal). Outside the mosque 15 people choose the lower return versus 13,5 expected. There is no statistical proof that people in or around a mosque answer differently than those somewhere else.
Hypothesis 4: General consistency
Some people who answered choose 4 times the "more Islamic" option, so two times the lower return and two times the higher risk, some answered tree times in this way and some two times.
We tested if these people where more often from the mosque than from the shop, it was tested on the people answering 4, 3 and 2 times more Islamic. People who answered four times the Islamic option did not come more often from the mosque statistically speaking, those answering two or three times did not come more often from the mosque nominally and statistically speaking, see section VI for extra Stata output.
Table 4 The “more Islamic” option 4/4
No Yes Total Place of survey Mosque Actual 9,0 3,0 12 Expected 10,3 1,7 Shop Actual 21,0 2,0 23 Expected 19,7 3,3 Total 30 5 35 Pearson Chi² 1,7120 Probability 0,191 H0: Not rejected Hypothesis 5: Age
We expect Muslims to respond the same regardless of age, but when testing this on the people who answered 3 times the more Islamic option or 2 times, we found that those under 30 answered more often on both questions, but we tested if the two age groups answered differently. We also tested if this was the case with the people who answered 4 times the more Islamic option, but this last test of 4 out of 4 was not significant.
Table 5
Answering the more Islamic option 3 times Answering the more Islamic option 2 times QII and QIV
Total No Yes No Yes Age Under 30 Actual 5,0 7,0 5,0 7,0 12 Expected 8,2 3,8 7,9 4,1
30 and above Actual 19,0 4,0 18,0 5,0 23
Expected 15,8 7,2 15,1 7,9 Total 24 11 23 12 35
Pearson Chi² 6,1336 Pearson Chi² 4,687
Probability 0,013 Probability 0,03
When looking at table 6 the four questions regarding risk or return itself, there
was only a statistical proof with 6,1% probability that people under 30 took different risks than those above 30, it looked like they take more risk.
Table 6
Q III - Taking more or less risk
Total No Yes
Age
Under 30 Actual 7,0 5,0 12
Expected 4,5 7,5
30 and above Actual 6,0 17,0 23 Expected 8,5 14,5 Total 13 22 35 Pearson Chi² 3,5121 Probability 0,061 H0: Rejected
Hypothesis 6: Income
We test if Muslims with different incomes, answer statistically significant similar or differently. There are three income groups, we tested on the three groups and on the two bigger groups, so leaving the two people who earn less than 500€ monthly out.
People within the two groups made some different choices both ways, but it was not significant.
Table 7 Income and risk Q I Income and risk Q III
Total Income More risk Less Risk More risk Less Risk
500€ - 1,500€ Actual 5,0 8,0 3,0 10,0 13
Expected 3,7 9,3 4,9 8,1
1,500€ + Actual 4,0 15,0 9,0 10,0 19
Expected 5,3 13,7 7,1 11,9
Total 9 23 12 20 32
Pearson Chi² 1,1572 Pearson Chi² 1,9433
Probability 0,282 Probability 0,163
Here we can see that those with higher incomes take more risk in the more or less risk question, but choose more often the saver over the unsafe countries in the other question, although statistically insignificant.
H0: Not rejected
Hypothesis 7: Consistency risk (Home Bias)
Muslims who take more risk in the one question should also do this in the other risk related question, otherwise the survey could be bias invoking.
This output shows that people taking more risk in the one question also do so in the other, although not one on one. A reason could be that in the one question we talk about anonymous Islamic countries versus non-Islamic countries mentioning the Netherlands and some other neighboring countries.
Table 8 Risk Q III
Total Risk Q I More risk Less Risk
More risk Actual 6,0 3,0 9
Expected 3,3 5,7
Less risk Actual 7,0 19,0 26
Expected 5,3 13,7
Total 13 22 35
Pearson Chi² 4,5233 Probability 0,033 H0: Rejected
Hypothesis 8: Consistency return
Muslims who take the lower return in the one question should also do this in the other return related question, otherwise the survey could be bias invoking.
Here we can see with statistical certainty that the people answering the two questions do not do this in the same proportions as the full sample, and we find that those choosing the lower return in one question also do this more often in the other question.
Table 9 Return Q IV
Total Return Q II Higher return Lower return
Lower return Actual 5 15 20
Expected 40 10
Higher return Actual 12 2 14
Expected 7 7
Total 17 17 34
Pearson Chi² 12,1429 Probability 0,000 H0: Rejected
We also tested if the people who answered more Islamic on the return questions also where more Islamic on the risk questions, because if not, the relation or positive answers could be due to other causes than religion. We found that people who answered the returns questions differently also more often answered the risk questions in
different proportions. This proofs that the proportions are different, but does not necessarily proof a relation between the two.
Table 10 Return QII Return QIV
Total Total
QI Risk Lower return Higher return Lower return Higher return
More risk Actual 8,0 1,0 9 8,0 1,0 9
Expected 5,3 3,7 4,4 4,6
Less risk Actual 12,0 13,0 25 9,0 17,0 26
Expected 14,7 10,3 12,6 13,4
Total 20 14 34 17 18 35
Pearson Chi² 7,8838 Pearson Chi² 4,5679
Probability 0,005 Probability 0,033
Hypothesis 9: Savings risk
People who have savings might act less religious and choose for less risk, because they do not make a hypothetical decision.
Table 11 Savings and risk Q I Savings and risk Q III
Total Savings More risk Less Risk More risk Less Risk
Yes Actual 4,0 10,0 3,0 11,0 14
Expected 3,6 10,4 5,2 8,8
No Actual 5,0 16,0 10,0 11,0 21
Expected 5,4 15,6 7,8 13,2
Total 9 26 13 22 35
Pearson Chi² 2,4679 Pearson Chi² 0,0997
Probability 0,116 Probability 0,752
Hypothesis 10: Savings return
Like with hypothesis 9, people with actual savings might choose differently regarding returns and interest rates, since it is real money forgone for them.
Table 12 Return QII Return QIV
Total Total
Savings Lower return Higher return Lower return Higher return
Yes Actual 7,0 7,0 14 6,0 8,0 14
Expected 8,2 5,8 6,8 7,2
No Actual 13,0 7,0 20 11,0 10,0 21
Expected 11,8 8,2 10,2 10,8
Total 20 14 34 17 18 35
Pearson Chi² 0,765 Pearson Chi² 0,305
Probability 0,382 Probability 0,581
Here we also do not find evidence that people with savings choose for a different rate of return or interest rate than people without savings.
H0: Not rejected
VI. Robustness checks
To test the quality of our statistics, we made 20 extra tests that were not mentioned in this thesis. Here we will summarize them very briefly:
H3
- We tested this hypothesis also on the other return question, very insignificant, Chi² of 0,0149 and pr. of 0,903.
H4
- We tested this hypothesis also on the times the Islamic option was chosen 3 or 2 times, both very insignificant, Chi² of 0,0307 and pr. of 0,861, for 3 times and Chi2 of 0,0106
and pr. of 0,918 for 2 times (QII and QIV).
H5
- For age I also tested the other risk related question (QI), The Chi2 was 0,0049 and the
pr. was 0,944, so very insignificant.
- We also tested age on the two return questions (QII and QIV), the Chi2 was 0,471 and
H6
- We tested QI, QII, QIII and QIV on income with all the three groups, Chi2 was
respectively 1,9669; 0,6200; 2,0532 and 0,1296, the probabilities were 0,374; 0,733; 0,358 and 0,937 respectively. So all insignificant.
- We also tested QII and QIV with the two main income groups on income, and found a Chi2 of 0,5529 and 0,1296 respectively with a pr. of 0,470 and 0,719 respectively. Also
similar results, insignificant.
H8
- We tested also if the other risk and return questions had significantly different ratios, we found they did with a Chi2 of 9,7428 and pr. of 0,002.
Extra tests that were also insignificant:
- We tested if place of survey resulted in a significant different outcome on QIV, this was not the case, Chi2 of 0,1135 and pr. of 0,736.
- We tested if the place of survey mattered for QI, also nothing significant, Chi2 of 0,5549
and pr. of 0,456.
- We tested if age and place of survey were related, Chi2 of 0,4415 and pr. of 0,506.
- We also tested if income and place of survey had a relation, we found a Chi2 of 1,5314
and a pr. of 0,465.
- We also tested If savings and place of survey had a relation, we found a Chi2 of 1,7120
and a pr. of 0,191.
Extra tests that were significant:
- We tested if those choosing a more Islamic option two or three times, also picked more risk in QI significantly.
Table 13 2 Times more Islamic 3 times more Islamic Total
QI No Yes No Yes
More risk Actual 2,0 7,0 3,0 6,0 9
Expected 5,1 3,9 6,2 2,8
Less risk Actual 18,0 8,0 21,0 5,0 26
Expected 14,9 11,1 17,8 8,2
Total 20 15 24 11 35
Pearson Chi2 6,0328 Pearson Chi2 6,9806
Here we see that those answering more Islamic on QI, do answer more often also more often Islamic on other questions.
VII. Limitations and suggestions
The survey was asked by me personally, so people could have wanted to proof me their dedication to Islam, they also wanted to teach me. In the question I mention interest as a Shariah compliant investment, but a few people I spoke said that Interest can`t be compliant in any possible way.
So the way the questions were asked could have caused for some "noise", the people around the people answering the survey albeit alone or with me, these people might have altered their choices. So this experiment could be done again, but there should be less noise; a more controllable environment.
35 people answered the survey, that is also not a lot. For testing more responses would be nice. I held my survey during Ramadan, this is not convenient. There was only one mosque where I asked the questions, so the visitors represent one way of thinking, there were only Sunni Muslims and most people were Moroccan. More nationalities and different thinking within Islam are welcome and make the research stronger. Al the subjects live in the city, Amsterdam, maybe people in villages have different opinions, or people in different provinces, near the German or Belgian border might think differently. I think the results are strong and not biased, but it could be done better.
Something that needs special attention is the two-way possibility of risk and return, since return might feel like interest and therefore bad, more people could have chosen the 4% than the 5%, just because of a bad feeling through the wording. This is similar with risk, maybe for the same return they would accept for example the political extra risk, but not the extra risk of a bankruptcy, one subject said: ,,in Morocco nobody lost his money in a bank ever, so why more risky". Risk is considered bad in Islam, so maybe the wording here had also some influence. The perception is also different of risk, I feel that they consider the Islamic options as less risky then I portray them, they sometimes do not see it as risky at all I heard.
We also found some evidence of a Home Bias, 13 people were willing to take more risk for a little bit of extra return. But when the choice was between the Netherlands, a few other European countries and an group Islamic Countries including Morocco, home of the ancestors of 66% of the people. There were only 9 left willing to
take more risk. This is an interesting finding and if we look at table 2, we can see that the more Islamic answer is given 59% of the times on QII, 37% on QIII and 49% on QIV, we think that these proportions are significantly different from the answers on QI with 26% and could proof home bias, when we consider the Netherlands as the home country of the respondents and not their ancestral home country as a home country.
These percentages also point out something else interesting that should be researched further and that is that both risk questions have lower positive scores, than the return questions. This might point to the Shariah dislike of risk.
What also can be found in table 2 is that the people with the higher income of 1,500€ plus, answer more often the Islamic choice on QIII (47%) compared to those earning less (23%), where they answer QIV in the same percentage (47%), this is risk versus return. When we look at those earning between 500€ and 1,500€, we see that 23% chooses the more Islamic choice when it comes to risk, but 54% chooses the more Islamic answer when it comes to return, this is a very different behaviour, what needs more thinking.
A finding not mentioned before is that since Muslims are not allowed to gain or pay interest, it should follow that investing in an investment where the return depends for a part on the "risk-free rate" which is interest, should not be allowed. Not being allowed to receive interest is a very different point of view from the view people in the western world hold, and more importantly, very different from al the existing theory (discussed in section two). This way of thinking prohibits investing in all stock I feel, yes you share profit and risk, but a part of the return comes regardless of the risk. This is prohibited, earning money just by having it.
VIII. Conclusion
There is a lot written about the way to price assets, but nowhere does religion play a part. With our survey we found that Muslims do answer differently from the existing theory.
59% would take a lower return if they could lend it to an Islamic country and according to the Shariah. When asked if they would accept more risk, 37% chooses for more risk, without a premium, this is also unexpected.
This finding that 59% of the questioned Muslims is willing to take a lower return and 37% is willing to accept a higher risk, are significantly different. This might be due
to the fact that interest or returns are a little bit considered dirty and risk as well, so you accept 4%, what is less of something bad and you accept a little bit extra risk (but in a lower proportion than you are willing to accept a lower return, for the same cause), since risk is also considered as something unwanted in Islam. This is a little bit stretching the results, since higher risk can have a price, but that price was not mentioned and the price of a lower return was. Another possible reason for the bias; people might wanted to invest in an Islamic country, but not if they knowingly accept a higher risk.
People who were asked around a mosque seemed to respond the same way as those outside, income did not matter, nor did it matter if a person had savings or not.
What did matter was the age of someone, a person below 30 was a little bit more consistent and answered more willingly to take risk than a person above 30 years old. People answering around a mosque where not more consistent than those answering somewhere else.
So CAPM does not apply 1-on-1 for Muslims and the Home Bias also seems to matter in our survey, but this should be researched better. This also counts for differences In risk aversion between different incomes and different answers between the choice of more risk versus a lower return. The home bias could have been a reason that our survey would not work, but it did not; people could have chosen for the Netherlands, what might have looked like they choose for less risk, but they still choose for more risk, regardless of the home bias. Thank you for reading.
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Appendix A The Survey:
Ik zou u graag een paar vragen willen stellen, met de beantwoording draagt u bij aan het wetenschappelijke begrip voor de Islam vanuit een financieel perspectief.
Ik hoop op u medewerking en dank u bij voorbaat!
1) Uit welk land komen uw voorouders of uit welk land komt u zelf als u niet in Nederland bent geboren?
……… 2) Wat is ongeveer uw inkomen per maand?
a) 0€ tot 500€ b) 500€ t/m 1.500€ c) Meer dan 1.500€
3) Hou oud bent u? ……….. Jaar. 4) Ik ben een: man/vrouw
5) Met welke stroming binnen de Islam voelt u zich het meest verbonden? a) Soennitisch
b) Sjiitisch c) Anders: …………..
6) Stel dat u uw geld kunt investeren in een zonne energie project en dat het rendement 5% per jaar zou zijn en het in overeenstemming is met de regels die de Islam er aan stelt, welke optie zou u dan kiezen:
a) 5% rendement en het geld wordt geïnvesteerd in landen waar Islam een kleine godsdienst is, maar waar u geld weinig risico loopt zoals in Nederland, Duitsland, Spanje en Frankrijk.
b) 5% rendement en uw geld wordt geïnvesteerd in een land waar Islam de grootste godsdienst is, maar waar u geld meer risico loopt zoals in Pakistan, Turkije, Marokko, Iran en Indonesië.
7) Heeft u spaargeld? a) Ja
b) Nee
8) Stel dat u uw geld uit kunt lenen aan een regering van een land waar de Islam geen rol speelt of u zou het uit kunnen lenen aan een land waar Islam de grootste godsdienst is?
a) Zou u het dan 1 jaar voor 4% rendement willen uitlenen aan land waar Islam groot is
b) Zou u het dan 1 jaar voor 5% rendement willen uitlenen aan een land waar Islam klein is
9) Stel u kunt uw geld uitlenen in overeenstemming met de koran (Sharia) en de landen hebben evenveel risico?
a) Kiest u voor een islamitisch land tegen een iets lagere rente? b) Kiest u voor een niet islamitisch land tegen een iets hogere rente?
10) Stel u kunt uw geld uitlenen in overeenstemming met de koran (Sharia) aan 2 landen met dezelfde rente?
a) Kiest voor een niet islamitisch met iets minder risico? b) Kiest u voor een islamitisch land met iets meer risico?
