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PKW Shouldn’t Be Able To Outperform SPY Reliably, But It Did

Summary I’m taking a look at PKW as a candidate for inclusion in my ETF portfolio. The risk level is reasonable and the correlation is high. The performance is surprisingly good. The liquidity is solid, so I expect the statistics to be reliable. Despite the higher expense ratio, the ETF has stacked up very well to SPY over the last several years. Investors should be seeking to improve their risk adjusted returns. I’m a big fan of using ETFs to achieve the risk adjusted returns relative to the portfolios that a normal investor can generate for themselves after trading costs. I’m working on building a new portfolio and I’m going to be analyzing several of the ETFs that I am considering for my personal portfolio. One of the funds that I’m considering is the PowerShares Buyback Achievers Portfolio (NYSEARCA: PKW ). I’ll be performing a substantial portion of my analysis along the lines of modern portfolio theory, so my goal is to find ways to minimize costs while achieving diversification to reduce my risk level. What does PKW do? PKW attempts to track the total return (before fees and expenses) of NASDAQ Buyback Achievers® Index. At least 90% of the assets are invested in funds included in this index. PKW falls under the category of “Large Blend”. Does PKW provide diversification benefits to a portfolio? Each investor may hold a different portfolio, but I use (NYSEARCA: SPY ) as the basis for my analysis. I believe SPY, or another large cap U.S. fund with similar properties, represents the reasonable first step for many investors designing an ETF portfolio. Therefore, I start my diversification analysis by seeing how it works with SPY. I start with an ANOVA table: (click to enlarge) The correlation is just under 96%. That’s a very high level of correlation and relatively unattractive for investors hoping for diversification benefits. As an investor using modern portfolio theory, I would prefer to see lower levels of correlation. Of course, the low value correlation wouldn’t mean much if the values were being distorted by poor liquidity. The average volume of nearly 500,000 shares per day suggests that liquidity shouldn’t be a concern. That’s a good sign for investors wanting verification of the statistics or wanting to know that they can exit the position with less concern about it deviating from NAV. Standard deviation of daily returns (dividend adjusted, measured since November 2013) The standard deviation is fairly reasonable. For PKW, it is .787%. For SPY, it is 0.748% for the same period. The ETF is definitely showing a little more volatility than SPY when we compare returns on a daily basis. Mixing it with SPY I frequently run comparisons on the standard deviation of daily returns for the portfolio, assuming that the portfolio is combined with the S&P 500. However, for PKW, I don’t think that adds much value. The correlation being nearly 96% really destroys the benefits of diversification. Why I use standard deviation of daily returns I don’t believe historical returns have predictive power for future returns, but I do believe historical values for standard deviations of returns relative to other ETFs have some predictive power on future risks and correlations. Yield and Taxes The distribution yield is 1.06%. I like to see strong yields for retiring portfolios, because I don’t want to touch the principal. By investing in ETFs I’m removing some of the human emotions, such as panic. Higher yields imply lower growth rates (without reinvestment) over the long term, but that is an acceptable trade off in my opinion. This ETF doesn’t have a high yield, but I am far enough away from retirement to be willing to work with the weaker yields. Expense Ratio The ETF is posting an expense ratio of .68%. That’s high compared to most of the ETFs that are appealing to me, but the expense ratio may reflect the premium being charged for the trading methodology the ETF is using to determine the positions within the ETF. Market to NAV The ETF is at a .06% discount to NAV currently. Premiums or discounts to NAV can change very quickly, so investors should check prior to putting in an order. Generally speaking, that discount to NAV isn’t big enough to be a big deal. However, even a small discount to NAV is fairly attractive when we are talking about a high quality ETF. Largest Holdings The diversification in the holdings isn’t going to be a strong selling point. (click to enlarge) Conclusion PKW was one of the most difficult ETFs to make a decision about. The ETF posts a very high correlation to SPY and a high expense ratio. Some screeners don’t have a portfolio turnover ratio for the ETF, but the prospectus states that in the last fiscal year the turnover ratio was 92%. I expect that kind of turnover to require some costs, but I generally don’t want to pay higher turnover ratios because my use of ETFs involves relying on markets to be reasonably efficient. If the markets are thoroughly efficient, then creating a proprietary trading system to select which positions to enter and which ones to end should not result in any reliable excess returns. However, history is providing some support for the methodology PKW is using. I was suspicious about their outperformance of SPY in the test period, so I extended my sample to a five-year period and looked at the returns on a time line. The result is that PKW outperformed SPY meaningfully over that five-year period. Looking at the lines, it isn’t a single period where PKW outperformed either. The fund’s performance has been strong and steady, which makes it appear more repeatable. I wanted to eliminate the ETF for the high expense ratio and relative weakness in diversification, but I can’t do it. Maybe it is just chance that eventually an ETF had to deliver this kind of strong performance over an extended period, but I won’t toss out an ETF that makes a fairly impressive case for itself without digging deeper. Disclosure: The author has no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. (More…) The author wrote this article themselves, and it expresses their own opinions. The author is not receiving compensation for it (other than from Seeking Alpha). The author has no business relationship with any company whose stock is mentioned in this article. Additional disclosure: Information in this article represents the opinion of the analyst. All statements are represented as opinions, rather than facts, and should not be construed as advice to buy or sell a security. Ratings of “outperform” and “underperform” reflect the analyst’s estimation of a divergence between the market value for a security and the price that would be appropriate given the potential for risks and returns relative to other securities. The analyst does not know your particular objectives for returns or constraints upon investing. All investors are encouraged to do their own research before making any investment decision. Information is regularly obtained from Yahoo Finance, Google Finance, and SEC Database. If Yahoo, Google, or the SEC database contained faulty or old information it could be incorporated into my analysis. The analyst holds a diversified portfolio including mutual funds or index funds which may include a small long exposure to the stock.

Investing For Retirement Using Northern Mutual Funds

Summary A set of just three Northern mutual funds, a bond, a large cap stock plus a mid cap fund generates good returns with relatively low risk. From January 2005 to January 2015, a Northern portfolio with fixed allocation could allow a safe 5% annual withdrawal rate with 1.36% increase of the capital. Same portfolio with rebalancing at 25% deviation from the target allowed a safe 5% annual withdrawal rate and 2.05% annual increase of the capital. Same portfolio with momentum-based adaptive allocation could have produced a safe 10% annual withdrawal rate and 1.26% annual increase of the capital. This article belongs to a series of articles dedicated for investing in various mutual fund families. In previous articles we reported our research on Fidelity , Vanguard , T Rowe Price , American Century , and Schwab mutual fund families. The current article does the same for Northern family of mutual funds. In addition, this article is the first in which a detailed study of the volatility of the returns using Sharpe and Sortino’s ratios is included. The series of these articles is aimed at a broad spectrum of investors. They may be useful to small individual investors as well as to any large institution managing retirement accounts. The general methodology we use in selecting the funds for the portfolio was presented in a previous article. The portfolio includes three funds: one bond fund and two equity funds. The equity funds are complementary: one covers large capitalization; the other fund contains medium capitalization stocks. The mutual funds selected for investment are the following: Northern us Treasury Index fund (MUTF: BTIAX ) Northern Stock Index fund (MUTF: NOSIX ) Northern Mid Cap Index fund (MUTF: NOMIX ) As in the previous articles, three different strategies are considered: (1) Fixed asset allocation. The portfolio is initially invested 50% in the bond fund and 50% equally divided between the two stock funds, without rebalancing. (2) Target asset allocation with rebalancing. The portfolio is initially invested 50% in the bond fund and 50% equally divided between the two stock funds and is rebalanced when the allocation to any fund deviates by 25% from its target. (3) Momentum-based adaptive asset allocation. The portfolio is at all times invested 100% in only one fund. The switching, if necessary, is done monthly at closing of the last trading day of the month. All money is invested in the fund with the highest return over the previous 3 months. The data for the study were downloaded from Yahoo Finance on the Historical Prices menu for three tickers: BTIAX, NOSIX, and NOMIX. We use the monthly price data from January 2005 to January 2015, adjusted for dividend payments. The paper is made up of two parts. In part I, we examine the performance of portfolios without any income withdrawal. In part II, we examine the performance of portfolios when income is extracted periodically from the accounts. Part I: Portfolios without withdrawals We report the performance of the portfolios under two scenarios: (1) no withdrawals are made during the time interval of the study, and (2) withdrawals at a fixed rate of the initial investment are made periodically. In table 1 we show the results of the portfolios managed for 10 years, from January 2005 to January 2015. Table 1. Portfolios without withdrawals 2005 – 2015. Strategy Total increase% CAGR% Number trades MaxDD% Fixed-no rebalance 93.45 6.82 0 -21.87 Target-25% rebalance 104.52 6.36 3 -31.09 Momentum-Adaptive 224.84 12.84 39 -13.35 In table 2 we show the results of a study on the volatility of the returns, including the much celebrated Sharpe and Sortino ratios. For completeness we give the definitions of these ratios. Sharpe ratio is the ratio of the compound annual growth rate (CAGR%) and the volatility of the returns (VOL%), where the volatility is defined as the annualized standard deviation of the returns. Sortino ratio is the ratio of the compound annual growth rate (CAGR%) and the volatility of the negative returns (NEG VOL%), where the volatility is defined as the annualized standard deviation of the negative returns. Table 2. Volatility performance of portfolios without withdrawals 2005 – 2015. Strategy CAGR% VOL% NEG VOL% Sharpe Sortino MaxDD% Fixed-no rebalance 6.82 7.18 6.29 0.95 1.08 -21.87 Target-25% rebalance 7.42 7.61 6.51 0.98 1.14 -31.09 Momentum-Adaptive 12.84 10.46 7.24 1.23 1.77 -13.35 By analyzing these results, one can see that the target portfolio has higher Sharpe and Sortino ratios than the fixed portfolio. On the other hand, the fixed portfolio has much lower maximum drawdown than the target portfolio. Which one is a better metric of risk: the volatility or the maximum drawdowns? Most investors, including the author of this article, are mostly concerned about large drawdowns, and pay less attention to Sharpe or Sortino ratios. The time evolution of the equity in the portfolios is shown in Figure 1. (click to enlarge) Figure 1. Equities of portfolios without withdrawals. Source: This chart is based on EXCEL calculations using the adjusted monthly closing share prices of securities. From figure 1 it is apparent that the rate of increase of the adaptive portfolio is substantially greater than the rate of the fixed and target allocation portfolios. Part II: Portfolios with withdrawals Assume that we invest $1,000,000 for income in retirement. We plan to withdraw monthly a fixed percentage of the initial investment. That amount is increased by 2% annually in order to account for inflation. In table 3 we show the results of the portfolios managed for 10 years, from January 2005 to January 2015. Money was withdrawn monthly at a 5% annual rate of the initial investment plus a 2% inflation adjustment. Over the 10 years from January 2005 to January 2015, a total of $535,920 was withdrawn. Table 3. Portfolios with 5% annual withdrawal rate 2005 – 2015. Strategy Total increase% CAGR% Number trades MaxDD% Fixed-no rebalance 14.51 1.36 0 -25.27 Target-25% rebalance 22.51 2.05 2 -26.77 Momentum-Adaptive 111.84 8.22 38 -16.56 The time evolution of the equity in the portfolios is shown in Figure 2. (click to enlarge) Figure 2. Equities of portfolios with 5% annual withdrawal rates. Source: This chart is based on EXCEL calculations using the adjusted monthly closing share prices of securities. To illustrate the advantage of the adaptive allocation strategy and the effect of withdrawal rates on the evolution of the capital, we give in Table 4 the results of simulations for the following withdrawal rates: 0%, 5%, 8%, and 10%. Table 4. Adaptive Portfolios with various annual withdrawal rates 2005 – 2015. Withdrawal rate % Total increase% CAGR% MaxDD% 0 224.84 12.84 -13.35 5 111.84 8.22 -13.97 8 52.33 4.53 -16.56 10 12.67 1.26 -20.25 The time evolution of the equity in the portfolios is shown in Figure 3. (click to enlarge) Figure 3. Equities of momentum-based portfolios with various annual withdrawal rates. Source: This chart is based on EXCEL calculations using the adjusted monthly closing share prices of securities. Conclusion The set of three Northern mutual funds, selected for this study, perform well for all three strategies and generate sustainable returns at relatively low drawdowns. Between 2005 and 2015, the fixed target allocation with rebalancing was able to sustain withdrawal rates of up to 5% annually. The adaptive allocation algorithm was able to sustain withdrawal rates up to 10% annually without any decrease of capital. Additional disclosure: This article is the sixth in a sequence on investing in mutual funds for retirement accounts. To help the reader compare the past performance of various mutual fund families, I selected a benchmark 10-year time interval starting on 1 January 2005 and ending on 31 December 2014. The article was written for educational purposes and should not be considered as specific investment advice. Disclosure: The author has no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. (More…) The author wrote this article themselves, and it expresses their own opinions. The author is not receiving compensation for it (other than from Seeking Alpha). The author has no business relationship with any company whose stock is mentioned in this article.