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Topic 8. Selection and Decision. CMT II Topic 8. Selection and Decision. CMT II. 2016. TOPIC 8. SELECTION AND DECISION. Exam Exam CMT Level II Exam Topics, Learning Objectives and Question Weightings Weights Questions Topic 8. Selection and Decision. 10% 15 Uncorrelated assets. Determine appropriate asset selections based on correlation data. Relative strength. Determine appropriate asset selections based on relative strength. Forecasting techniques (pattern and trend recognition). Determine appropriate asset selections based on trend and pattern forecasts. Chapter 4 Intermarket Analysis Markos Katsanos, Intermarket Trading Strategies (Hoboken, New Jersey: John Wiley & Sons, 2008), Chapter 3 Determining Intermarket Relations (*) Using Intermarket Correlations for Portfolio Diversification Chapter 5 Correlation Markos Katsanos, Intermarket Trading Strategies (Hoboken, New Jersey: John Wiley & Sons, 2008), Chapter 2 All sections included Chapter 14 A Stock Market Model Added in 2016 Ned Davis, Being Right or Making Money (Hoboken, New Jersey: John Wiley & Sons, 2014), Chapter 3 All sections included Chapter 15 A Simple Model for Bonds Added in 2016 Ned Davis, Being Right or Making Money (Hoboken, New Jersey: John Wiley & Sons, 2014), Chapter 4 All sections included Chapter 40 Relative Strength Strategies for Investing Mebane Faber, Relative Strength Strategies for Investing, Cambria Investment Management. All sections included (*) This section is included in Topic 6 Confirmation. Pag. 250/476 ©FINANCER TRAINING Alexey De La Loma CFA, CMT, CAIA, FRM, EFA, CFTe CMT II. 2016. Topic 8. Selection and Decision. 8.1. Using Intermarket Correlations for Portfolio Diversification (Katsanos). Investors and portfolio managers all over the world know the huge benefits of diversification. For example, U.S. stock portfolio managers usually include international equities, bonds and cash in their portfolios. However, globalization has reduced the benefit of international equities because all equities tend to move in the same direction (positive correlation). On the other side, commodities and currencies (foreign exchange) are less used to diversify because of the false impression that these securities are excessively risky. This is an erroneous perception and most commodities are excellent candidates to diversify a stock portfolio. For example, in bear equity markets, commodities act as a hedge, and commodities are usually considered as an important inflation hedger. Just as the standard deviation is a standard in terms of financial risk, the correlation coefficient is an essential tool for investment management. The correlation coefficient is used to determine whether two investments or asset classes move together or in opposite direction. A portfolio is effectively diversified if it is composed of assets that are not correlated (low or negative correlation coefficient), that is, assets that do not move in the same direction. High positive correlation is negative in terms of portfolio diversification, and low or negative correlation increases the benefits of diversification and reduces downside volatility (standard deviation). However, as we reduce the risk of our portfolio, our portfolio return will also suffer. The key concept here is trying to maximize the risk to return ratio of our portfolio. Markos Katsanos introduces an example to illustrate the benefits of diversification: the equity line of a portfolio consisting of 70% equities (S&P 500 index) and 30% oil futures is more stable than the equity lines of both securities individually. In a second and more comprehensive example, Markos Katsanos creates some portfolios using as inputs the annual returns of a great variety of securities (stock market indices, fixed income, commodities, cash and currencies). Table 8-1 illustrates the annual returns from 1997 to 2006, as well as the mean and standard deviation (σ) of these financial time series. The last three rows are represented in bold letters. refers to the arithmetic mean of these returns. refers to the standard deviation (volatility), and is the risk-adjusted return. According to this statistical measure, cash is the best security followed by bonds and the GBP (Great Britain Pounds), although all these three securities have lower annual returns than stock market indices or commodities. Annual Returns from 1997 to 2006 (10 years) Year S&P 500 FTSE Hang Seng Bonds GBP Gold Crude Oil Cash 1997 33.36% 23.98% -17.30% 9.65% 2.31% -21.8% -31.90% 5.25% 1998 28.58% 17.02% -2.15% 8.69% 6.47% -0.26% -31.70% 5.06% 1999 21.04% 17.22% 71.51% -0.82% 2.37% 0.00% 112.40% 4.74% 2000 -9.10% -15.60% -8.96% 11.63% -1.85% -5.55% 4.69% 5.95% 2001 -11.90% -17.60% -22.0% 8.44% 1.39% 2.48% -26.00% 4.09% 2002 -22.1% -8.79% -15.1% 10.26% 13.56% 24.80% 57.30% 1.70% 2003 28.68% 27.60% 38.55% 4.10% 14.35% 19.09% 4.23% 1.07% 2004 10.88% 18.43% 16.30% 4.34% 12.25% 5.58% 33.61% 1.24% 2005 4.91% 9.70% 7.82% 2.43% -5.78% 18.00% 40.48% 3.00% 2006 15.79% 27.77% 37.35% 4.33% 18.85% 23.17% 0.02% 4.76% 10.01% 9,97% 10,60% 6,31% 6,39% 6,55% 16,31% 3,69% σ 19.14% 17,52% 30,36% 4,00% 8,02% 14,74% 45,66% 1,80% 0.52 0,57 0,35 1,58 0,80 0,44 0,36 2,05 Source: Markos Katsanos. Table 8-1 Table 8-2 shows the Pearson’s correlation coefficient of these securities using monthly returns from 1997 to 2006. According to this table, U.S. equities (S&P-500) are highly correlated with international equities (FTSE and Hang Seng) due to the globalization factor. However, the correlation with fixed income, Alexey De La Loma ©FINANCER TRAINING Pag. 251/476 CFA, CMT, CAIA, FRM, EFA, CFTe Topic 8. Selection and Decision. CMT II. 2016. commodities, and currencies is negative, which is excellent in terms of diversification. The lowest correlation corresponds to GBP and FTSE with a negative 0.30 correlation coefficient. 10-year correlation matrix of monthly percentage returns S&P Hang Crude FTSE Bonds GBP Gold 500 Seng Oil S&P 1.00 0.81 0.57 -0.06 -0.09 -0.04 -0.03 500 FTSE 0.81 1.00 0.57 -0.02 -0.30 -0.06 0.03 Hang 0.57 0.57 1.00 0.05 0.00 0.11 0.18 Seng Bonds -0.06 -0.02 0.05 1.00 0.10 0.08 0.11 GBP -0.09 -0.30 0.00 0.10 1.00 0.36 0.00 Gold -0.04 -0.06 0.11 0.08 0.36 1.00 0.18 Crude -0.03 -0.19 0.18 0.11 0.18 0.18 1.00 Oil Source: Markos Katsanos. Table 8-2 Finally, in Table 8-3 Markos Katsanos illustrates the performance of four simulated passive portfolios in order to show the positive effects of diversification from the perspective of a U.S. equity investor. Portfolio A only contains US stocks and this is our reference point. Portfolio B contains a typical asset allocation mix with a 70% invested in equities, 10% in cash, and 20% in fixed income securities. By including uncorrelated assets (bonds and cash) with the US equities, we reduce both risk and return, but the reduction is risk is bigger than the return’s reduction and this is reflected in the increase of the risk-adjusted return (0.66). Then, portfolio C maintains the allocation in bonds and cash and introduces international equities (FTSE, Hang Seng) into the asset allocation. The results are very modest with a slight increment in the risk-adjusted return (0.70). Finally, portfolio D excludes international equities and Cash, includes commodities (Crude Oil and Gold) and increases the fixed income’s allocation. In this case, the inclusion of commodities plays a key role reducing relevantly our portfolio risk. The results are impressive with a risk-adjusted return of 1.28. Portfolio Minimum Risk Maximum Return Portfolio A Portfolio B Portfolio C Portfolio D Allocation Portfolio Portfolio S&P 500 100% 70% 50% 40% 10% 60% Cash 10% 10% FTSE 10% Hang Seng 10% 10% Bonds 20% 20% 40% GBP 55% Gold 10% Crude Oil 10% 15% 30% 10.01% 8.64% 8.69% 8.81% 8.92% 11.96% σ 19.14% 13.1% 12.5% 6.86% 6.38% 18.70% 0.52 0.66 0.70 1.28 1.40 0.64 Source: Markos Katsanos. Table 8-3 Pag. 252/476 ©FINANCER TRAINING Alexey De La Loma CFA, CMT, CAIA, FRM, EFA, CFTe CMT II. 2016. Topic 8. Selection and Decision. Markos Katsanos uses the Excel’s Solver tool to create two final portfolios, the first is a minimum risk portfolio, and the second a maximum return portfolio. Of course, the future performance rarely measures up fully to past results, and finding the maximum return and minimum risk portfolios using past data and the Solver tool cannot be used to create a portfolio. Rates of return are often less predictable, and correlation coefficients can also change over time. Alexey De La Loma ©FINANCER TRAINING Pag. 253/476 CFA, CMT, CAIA, FRM, EFA, CFTe Topic 8. Selection and Decision. CMT II. 2016. 8.2. Correlation (Katsanos). 8.2.1. Relationships between variables (Pearson’s correlation coefficient). If you consider more than one variable in our analysis, the measure of dispersion that is commonly used is the covariance. Therefore, we could say that covariance is the two-variable version of the variance (standard deviation). If you have two variables (A and B), the covariance between both variables is: ( 8.1) In our example, A and B could be stock market time series with a number of returns equal to “n”.
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