The Effect of US Economy on SPY 10-13

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1 SPY ETF

2 Index Overview 3 Sectorial Analysis 3-4 Peers Comparison 5-8 SPY VS Dow Jones & Russell Index 8-9 The Effect of US Economy on SPY Conclusion 14 Sources 14 2

3 Overview The SPY S&P 500 ETF tracks a market-cap weighted index of US large and midcap stocks selected by the S&P Committee. SPY is the best-recognized and oldest ETF and typically tops rankings for largest assets under management (AUM) and greatest trading volume. The fund tracks the massively popular US index, the S&P 500. Few realize that S&P's index committee chooses 500 securities to represent the US large-cap space, not necessarily the 500 largest by market cap, which can lead to some omissions of single names. Still, the index offers outstanding exposure to the US large cap space. Unlike direct peers IVV and VOO, SPY is a unit investment trust, an older but entirely viable structure. As a UIT, SPY must fully replicate its index (it probably would anyway) and give up the small risk and reward of securities lending. It also can t reinvest portfolio dividends between distributions; the resulting cash drag will slightly hurt performance in up markets and help in downtrends. SPY is extremely cheap to hold, but is typically edged out by IVV and VOO in this respect. SPY's phenomenal trading volume makes it the perfect vehicle for tactical traders and mom and pop investors alike. This report will be about the SPY ETF, so we will begin by making a sectorial analysis of this particular ETF, then we will compare it with its peers, also we will compare its returns with its underlying instrument which is the S&P 500 index, in addition we will talk about the effect of the unemployment rate and the Consumer price index on the SPY, also we will make a regression analysis and correlation matrix for them. Sectorial Analysis SPY is considered one of the oldest listed ETFs, as it was listed in the US in 1993, it is now considered one of the most important ETFs in the financial markets. In this section we will focus on the sectors that this ETF covers, and the top holding companies in it, so below is a graph that divides the SPY into sectors. 3

4 % Utilities 3.10% Telecommunications 2.82% Energy 7.50% Basic Materials 2.16% Technology 18.44% Consumer Non- Cyclicals 9.81% Financials 17.57% Industrials 12.64% Consumer Cyclicals 12.94% Healthcare 13.00% 3.50% 3.00% 2.50% 2.00% From the above graph we can see that the largest sector is the technology followed by the financial sector, and this should not be a surprise for US as the biggest companies in the S&P 500 is under the technology sector like Apple which is the world s largest publicly traded company by market capitalization. Below is a graph which represents the top holdings in the SPY ETF. SPY Top 10 Holdings 1.50% 1.00% 0.50% 0.00% Apple Inc. Microsoft Corporation Alphabet Inc. Class A Exxon Mobil Corporation Johnson & Johnson Berkshire Hathaway JPMorgan Chase & Co. Amazon.co m, Inc. General Electric Facebook, Inc. Class A % 3.12% 2.44% 2.36% 1.91% 1.61% 1.61% 1.56% 1.55% 1.49% 1.41% 4

5 Peers Comparison As we have mentioned in the overview section that SPY competes with IVV & VOO, mainly these ETFs are identical in many manners and have a perfect correlation with the S&P 500 Index, however they are different in their structure, NAV, Expense Ratio, Beta and returns. In the next graph we will compare the Asset under management (AUM in thousands of U.S. Dollars), Average trading volume and the yield to date for the three ETFs. SPY IVV VOO 2,299,891 $56,485, ,225, % $90,615, ,518, % $212,013, % AUM Volume YTD We can see that SPY has a $ 121,398,080 asset under management higher than IVV and a $155,528,653 more than VOO. In addition, we can also see the huge difference between SPY trading volume and its peers. Finally, we can witness the slight difference in YTD between the three ETFs and that should make sense for us as they have an approximate perfect correlation with their underlying instrument. We will now turn our attention to the rest of the fundamental analysis for the three ETFs, below is a graph that represents the net asset value (NAV), Expense Ratio and the beta for the three ETFs. 5

6 SPY VOO IVV 0.04% % 0.05% % 0.09% % E X P E N S E R A T I O B E T A D I V I D E N D Y I E L D The above graph contains three important valuation analysis, we will begin with the expense ratio which measures the percentage of fund assets used to cover the funds expenses, so this is the fees that the investor should pay every year and, of course, the lower the ratio the better for the investor, so in terms of expense ratio we can see that SPY has the highest expense ratio among its peers but it is still small compared to other methods of investments. Second, we can see that all the three ETFs have the same beta which is 1, and this makes sense because as we have said previously that they track the same underlying asset and have almost a perfect positive correlation with the S&P500. Beta equals covariance of the instrument divided by the variance of the market, so in our case the covariance between the SPY and S&P500 equals the variance of the market so the result will be 1. Finally, we can see that SPY & VOO have higher dividend yield than IVV. The three ETFs distribute cash dividends quarterly, however VOO and IVV are much faster to distribute the dividends both pay out within a week of their ex-dividend dates. IVV and VOO reinvest dividends from their underlying stocks until the payout date arrives. SPY is restricted by its Unit Investment Trust legal structure to hold dividends in cash until they are paid out. It is worth mentioning that if you want to take advantage from the dividend, you only have to buy the ETF before one day of the ex-dividend date. Next we will discuss another important fundamental measure which is the net asset value (NAV), so below is a graph which compares the percentage change in NAV for the three ETFs with their underlying asset the S&P

7 1.28% 1.37% 3.05% 3.09% 5.61% 5.60% 7.09% 7.16% 14.85% 15.00% % Growth Chane Over Net Asset Value 18.00% 16.00% 14.00% 12.00% 10.00% 8.00% 6.00% 4.00% 2.00% 0.00% NAV(1 Year) NAV(3 Years) NAV(5 Years) NAV(10 Years) SPY IVV VOO S&P 500 An ETF s net asset value is calculated by taking the current value of the fund s net assets (the value of all securities inside minus liabilities) divided by the total number of shares outstanding. The net asset value, or NAV, is published every 15 seconds throughout the trading day. But the ETF s NAV isn t necessarily its market price. All the observation in the above graph have approximately the same NAV as they have nearly the same assets, except for the NAV (10 Years) for VOO as its inception date is 7 th of September The next graph compares the different returns for both the SPY ETF and the S&P 500 index, we SPY VS S&P 500 RETURNS SPY S&P M O N T H 3 M O N T H YTD 1 Y E A R 1 0 Y E A R S 7

8 will see that they approximately equal, so the question arise why should any investor buy the ETF instead of the index itself? The answer is: Investing in ETFs have many advantages like, lower cost, tax efficiency and diversification, so this why ETFs are gaining popularity. SPY VS Dow Jones & Russell Index In this section we will try to compare the SPY with another equity ETFs that tracks different indices, like the Dow Jones and the Russell So below is a graph that compares the SPY with top Dow Jones ETF (DIA) and top Russell 2000 ETF (IWM). AUM & Trading Volume IWM DIA SPY $- $50,000,000.0 $100,000,000.0 $150,000,000.0 $200,000,000.0 $250,000,000.0 $300,000,000.0 $350,000,000.0 SPY DIA IWM AUM $212,013,824.0 $14,701,155.0 $38,727,149.0 Volume 88,518,632 3,754,817 32,650,568 We can see that SPY has the largest assets under management, also it has the highest trading volume compared with the other ETF in the graph. That s another reason for the popularity of the SPY. However, we should perform our due diligence in terms of fundamental analysis between the ETFs, so below is a graph that contains the most important valuation analysis for the three funds. 8

9 FUNDAMENTAL ANALYSIS SPY(S&P500) DIA(Dow Jones) IWM(Russell) % 1.38% % % % 2.03% B E T A E X P E N S E R A T I O D I V I D E N D Y I E L D P / E We can see that SPY and DIA has the same sensitivity to their underlying asset measured by almost 1 beta for both, while IWM is 20% more volatile than the market as it has 1.2 beta. Moreover, SPY has the lowest cost compared with both DIA and IWM, we can see that IWM charge a 0.20% annual fees also DIA charge 0.17%, while SPY charge only 0.09%. In addition, DIA has the largest dividend yield compared to SPY and IWM, but SPY dividend yield is a little bit close to DIA s. In terms of price to earnings ratio, SPY has the highest P/E compared to others and this tells US that it is overvalued. So you need to pay $20.33 to gain a 1$ earnings per share. Finally, all the above valuations should make sense because the SPY & DIA covers large cap stocks while IWM covers small cap stocks, small cap stocks are much riskier than large cap stocks because they are small companies and their future success is not certain yet, also Largecap stocks frequently offer dividends as an incentive for investors, providing a steady source of income and a financial motive to purchase shares. Dividends are payments to shareholders 9

10 Jan-11 Apr-11 Jul-11 Oct-11 Jan-12 Apr-12 Jul-12 Oct-12 Jan-13 Apr-13 Jul-13 Oct-13 Jan-14 Apr-14 Jul-14 Oct-14 Jan-15 Apr-15 Jul-15 Oct-15 Jan-16 Apr-16 Jul-16 Oct-16 SPY Prices CPI & Unemployment Rate from a company's profits and are distributed at regular intervals. Small-cap stocks do not offer dividends to their investors nearly as often as large-cap stocks. Instead of issuing dividends with their profits, small-cap stocks are more likely to reinvest those profits into the company, helping to fuel growth. The Effect of US Economy on SPY This is one of the most important sections in this report as we will talk about the effect of the US economy on the S&P 500 which is the underlying asset of this ETF. There are many economic factors that could affect the performance of the US equities and indices, but we will focus only on the Consumer Price Index and the Unemployment rate. First we will see the historical chart beginning in January 2011 until December 2016, then we will calculate the correlation matrix between them and finally we will perform a regression analysis on the SPY prices against the CPI & Unemployment rate. Relationship between SPY and the US Economy Date SPY Price CPI Unemployment Rate We can see from the above chart that there is an inverse relationship between the Unemployment rate and the SPY prices, also there is a no direct relationship between the CPI and the SPY prices, but to confirm this relationship we draw a correlation matrix for the three variables. (The data was taken from January 1st 2011 to December 2016) 10

11 SPY Price 1 We can see from the above matrix that there is almost perfect negative correlation between the unemployment rate and the SPY prices, however it seems that there is no relationship between the CPI and the SPY Prices. Before we made the regression analysis, we will explain the economic effect of unemployment rate and CPI Unemployment Rate/Jobs Report SPY Price CPI Unemployment Rate CPI Unemployment Rate Like GDP, rate of employment illustrates the development and the strength of the economy. The jobs report is reported monthly by the U.S. Bureau of Labor Statistics and accounts for approximately 80% of the workers who produce the entire gross domestic product of the United States. The statistic is used to assist government policy makers and economists in determining the current state of the economy and in predicting future levels of economic activity. Investors follow this number closely as well. The jobs report and unemployment rates are critical measures of an economy s overall health. Essentially, more people with jobs equates to higher economic output, retail sales, savings and corporate profits. As such, stocks generally rise or fall with above or below expectations employment reports, as investors digest the potential changes in these areas. Consumer Price Index The Consumer Price Index points out the average change in the price of consumer goods and services across more than 200 different categories. The data contains prices for homes, energy, food and medical items that people use on a daily basis, for investors high consumer prices for basic goods mean that there won t be any leftover money to buy stocks so the demand will fall and the prices will go down. To confirm our numbers we performed a regression analysis in which the SPY Prices is the dependent variable and the Unemployment rate and the CPI are the independent variables 11

12 Multiple R. This is the correlation coefficient. It tells you how strong the linear relationship is. For example, a value of 1 means a perfect positive relationship and a value of zero means no relationship at all. It is the square root of r squared. R squared. This is R2, the Coefficient of Determination. It tells you how many points fall on the regression line. For example, 80% means that 80% of the variation of y-values around the mean are explained by the x-values. In other words, 20% of the values don t explain the variation in the dependent variable. Adjusted R square. The adjusted R-square adjusts for the number of terms in a model. You ll want to use this instead of #2 if you have more than one x variable. Standard Error of the regression: An estimate of the standard deviation of the error μ. This is not the same as the standard error in descriptive statistics. The standard error of the regression is the precision that the regression coefficient is measured; if the coefficient is large compared to the standard error, then the coefficient is probably different from 0. Observations. Number of observations in the sample. In this case we took the monthly prices of each variable. For our numbers we can see that there is a strong linear relationship which is shown by a high Multiple R (98%), also high R 2 indicates that the model, as a whole, explains 96% of the variation in the dependent variable, also because we used a 71 observation, our distribution is a normal distribution because we used more than 30 observation. But, we can t rely only on these numbers without a statistical test of significance, so we will test the statistical significance of the 12

13 independent variables (Unemployment rate & CPI). We can see that the p values are too small for both of our independent variables, so we can reject the null hypothesis and conclude that unemployment rate and CPI are statistically significant. The final section of our report will focus on the latest US events and the relationship between the dollar index and the SPY prices. There were two recent events in the US market, first the presidential election and the hiking of interest rate by the FED. Historically there were a negative correlation between the dollar value and the US equity markets, but recently we saw a break of this general rule as the prices of the US indices hits its all-time highs that s even after the fed raised the interest rates which directly affect the US equities as people withdraw their money from their investments and put them into banks. The reason for this exception is what markets called the Trump effect. Donald Trump s vows to 13

14 ramp up infrastructure spending and ease banking regulations are giving a burst to the US equities. We can witness this relationship by looking at the above graph, as we can see that the gap between the two variables are minimized because of the trump effect. Conclusion SPY is considered one of the best ETFs in terms of AUM, trading volume and expense ratio, also it is the oldest American listed ETF. However investors should always pay attention to the factors that could affect the underlying instruments of the ETF. In our report we talked about two important factors that affects the price of the SPY which are the unemployment rate and the CPI, however there are many factors that investors should put their eyes on, including but not limited to interest rates, GDP, non-farm payroll, inflation rates. Also, investors should also watch the top holdings in the SPY ETF because any change in one of the top holdings will affect the performance of the ETF itself. Finally, investors should keep in mind that the exception of the negative correlation between the dollar index and the US equity markets is temporarily due to trump effect and it should be back to its normal levels, so we encourage investors not to take it as a general rule. Sources Thomson Reuters Eikon The material contained in this document is provided solely for general information and educational purposes and is not, and should not be construed as, an offer to buy or sell, or as a solicitation of an offer to buy or sell any product, security or investment. Nothing in this document should be taken as making any recommendations or providing any investment or other advice with respect to the purchase, sale or other disposition of any product, security or investment, including without limitation, any advice to the effect that any product related transaction is appropriate for any investment objective or financial situation of a prospective investor. A decision to invest in any report related products, security or investment should not be made in reliance on any of the statements in this document. Before making any investment decision, prospective investors should seek advice from their financial advisors, take into account their individual financial needs and circumstances and carefully consider the risks associated with such investment decision. Without limiting any of the foregoing, in no event will Ingot Brokers or any of its affiliates be liable for any decision made or action taken in reliance on the information in this document and, in any event, Ingot Brokers and its affiliates shall not be liable for any consequential, special, punitive, incidental, indirect or similar damages arising from, related to or connected with this document, even if notified of the possibility of such damages. 14