Tag Archives: consumer

Are Commission-Free Sector ETFs Really The Better Choice?

Summary Fidelity offers nine S&P Sector ETFs commission-free to its clients. The SPDR Select Sector funds have a long history and are widely used in various sector-switching strategies. How do the relative performances of these two sets of funds compare if we consider them for the short intervals that are typically used in such strategies? As I described previously ( here ), I maintain a dual-momentum S&P sector-switching portfolio which I rebalance every 30 days. To avoid commissions, I use Fidelity’s S&P Sector ETFs. The alternative, and the basis for most published sector-switching strategies would be SPDR’s long-established series of S&P Sector Select ETFs. The SPDR funds have been in existence since 1998; Fidelity’s offerings are just over two years old. Using the two-years data on the Fidelity funds I compared their performance with the SPDR funds. In doing so, I looked at intervals of 1, 3, 6, 12 and 24 months plus YTD. The results were informative but didn’t really give a satisfactory answer to my question, which was: Is the savings on commissions worthwhile, or might the SPDR funds performance be strong enough to wipe out the commission-free advantage of the Fidelity funds? The reason that exercise was inadequate to answer the question was that I used a single, fixed end-point. What is needed is the full history for the full period. If the funds are traded every 30 days (the minimum to qualify for the free trades), the funds’ relative performances to date is not the most relevant metric. Rather, it’s their performance over rolling 30-day periods for the entire history. I should note here that the actual intervals between trades vary from 30 to as many as 33 calendar days depending on when non-trading weekends and holidays relative to the 30-day minimum holding period. For the purposes of the strategy there’s a $48 fixed-cost for commissions on trading three funds every 30-days if using the SPDR funds. That’s $8/trade for each for three round trips. Funds that have commission costs associated with them would, therefore have to beat the commission-free funds by that $48 a month to justify foregoing the commission free funds. The $48 is a fixed cost regardless of the size of the trades, so the margin of outperformance required will depend on the size of the total portfolio. I’ll use three examples as I proceed. A $10,000 portfolio would need to beat by 0.48 percentage points on average to break even. For a $50K portfolio it would only need to beat by 0.096 points; for $100K, it is a near-trivial 0.048 points. The list of funds I examined is: Fidelity MSCI Consumer Discretionary Index ETF (NYSEARCA: FDIS ) Fidelity MSCI Consumer Staples Index ETF (NYSEARCA: FSTA ) Fidelity MSCI Energy Index ETF (NYSEARCA: FENY ) Fidelity MSCI Financials Index ETF (NYSEARCA: FNCL ) Fidelity MSCI Health Care Index ETF (NYSEARCA: FHLC ) Fidelity MSCI Industrials Index ETF (NYSEARCA: FIDU ) Fidelity MSCI Materials Index ETF (NYSEARCA: FMAT ) Fidelity MSCI Information Technology Index ETF (NYSEARCA: FTEC ) Fidelity MSCI Utilities Index ETF (NYSEARCA: FUTY ) Consumer Discretionary Select Sector SPDR ETF (NYSEARCA: XLY ) Consumer Staples Select Sector SPDR ETF (NYSEARCA: XLP ) Energy Select Sector SPDR ETF (NYSEARCA: XLE ) Financials Select Sector SPDR ETF (NYSEARCA: XLF ) Health Care Select Sector SPDR ETF (NYSEARCA: XLV ) Industrials Select Sector SPDR ETF (NYSEARCA: XLI ) Materials Select Sector SPDR ETF (NYSEARCA: XLB ) Technology Select Sector SPDR ETF (NYSEARCA: XLK ) Utilities Select Sector SPDR ETF (NYSEARCA: XLU ) It’s important to note that these are not strictly comparable in two cases. The Fidelity information technology ETF does not include telecoms; the SPDR information ETF does. SPDR also has a separate financial services fund which has no counterpart in Fidelity’s lineup, so the financial funds take somewhat differing approaches to the sector. My approach to this was to download the full data sets from Yahoo.finance for the Fidelity funds and for the SPDR funds for the same dates (for any interested readers, I use Samir Khan’s Multiple Stock Quote Downloader for Excel to do this efficiently, and highly recommend it.). I computed rolling 30-day returns using adjusted close data to account for dividends. I then plotted the differences between each SPDR fund and its Fidelity counterpart. Results The charts of the difference between the Sector Select SPDR ETF and the Fidelity MSCI Sector Index ETF follow. (click to enlarge) (click to enlarge) (click to enlarge) (click to enlarge) For these charts, positions above the zero line represent outperformance by the SPDR fund and those below the zero line show outperformance by the Fidelity fund for each of the rolling 30-day period from 11 Dec 2013 through 9 Nov 2015(n=482). The +0.5ppts line is a relevant marker because it’s the break-even point for commission costs on the $10K portfolio. In the next chart we can see that with two exceptions — health care and the poorly matched technology funds — the SPDR funds consistently have greater numbers of higher performing 30-day intervals. (click to enlarge) On a level playing field the choice would seem to favor the SPDR ETFs. But what about the original question? Now that we know the SPDR funds outperform in seven of the nine cases, we need to know if they outperform by sufficient margins and with sufficient frequency to overcome their commission costs. In this table, I list the percent of 30-day rolling returns where the SPDR ETFs met the minimum difference excess return required for break-even for each of three portfolio sizes, $10K, $50K and $100K. For the $10,000 portfolio it’s not even close. The commission costs would have been covered by superior returns from the SPDRs only 15.6% of the time on average. For much larger portfolios, $50 or $100K, it’s a near-wash, but even there the SPDRs fall short of clearing the break-even bar, albeit by a trivial amount. Summary S&P sector funds fill a niche in the market for a diverse range of switching strategies. Many of these involve short-term hold times and thirty days is not an uncommon choice. For traders who seek to save the commission costs associated with those frequent trades, the Fidelity offerings may be the only game in town. (Merrill Edge does offer 30 to 100 free trades a month for stocks or ETFs but requires a minimum of $25,000 in a cash account at either Merrill or Bank of America. For some, this can be an ideal choice.) I wanted to know if the Fidelity alternatives performed as well as the SPDRs or if the commissions (which are, after all, modest) might be a small price for getting better performance. I felt it was useful to put the results here because I’m sure I’m not alone in looking to the Fidelity sector funds as the cheaper alternative to the SPDR Select Sector ETFs. Results are interesting. The SPDR funds do outperform the Fidelity funds in all but two cases. One of these, Technology, is not a fully parallel comparison, so we can discount it. The other, Health Care, is a clear win for Fidelity unless I’ve missed nuances in the way the funds are structured. However, the differences are small enough to not justify moving to the SPDR funds. And, even if they were enough to push the over the break-even point, for my purposes I would opt for the Fidelity Health Care and InfoTech funds anyway. Indeed, I may change my pool to include the SPDR funds in the Consumer Discretionary, Energy and Industrial sectors where they are providing stronger returns. Realize, too, that I’ve treated the returns as a binary condition; they either make a cut or don’t. I’ve not considered the extent of outperformance, which can, of course, make a bit difference. A strictly qualitative look seems to indicate that the results are close enough that the analysis may not be worth the effort it will take, but I will spend some time thinking about how to go about doing it. Brokers are competing for our investing dollars. One front on these competitive battles is offering commission-free ETFs. These can be a boon to many of us who regularly invest modest amounts. I am much more willing to attempt to implement momentum strategies having a range of commission-free options available. At this time I have active three such strategies, all based on 30-day intervals using Fidelity’s cost-free ETFs (and all in IRA accounts, so there are no tax-consequences from the frequent trading). I’ve been wondering for some time if the commission-free funds were truly competitive. Superficial looks led me to the conclusion that they may not be my first choice for a buy and hold position, but for frequent trading commission-free, they are more than adequate. I’m satisfied that this casually validated finding is borne out by this more detailed look in the case of the sector funds.

EOD: This Global Equity Fund Could Bounce Back

Summary 15% Discount to NAV is near 5 Year Highs. High 11% Distribution Rate Combined with Discount Produces Alpha. The fund uses dividend capture and an options overlay to increase distributable income. The Wells Fargo Advantage Global Dividend Opportunity Fund (NYSE: EOD ) is a covered call global equity closed-end fund, created in March 2007, with about $365 Million in assets under management. The primary objective of the fund is to provide a high level of current income, with a secondary objective of long term capital growth. (Data below is sourced from the Wells Fargo Advantage website unless otherwise stated.) The fund is currently selling at a 15% discount to NAV which is near its five year high. Here is a five year history of the premium/discount from cefconnect: (click to enlarge) The Fund invests in global equities with an emphasis on companies with attractive dividend policies and/or those with the potential to grow their dividends over time. The Fund focuses on companies in the utilities, telecom and energy sectors. They also employ dividend capture and an options overlay to increase distributable income. Within the equity covered call CEF sector, I generally prefer funds that use index options over those that use options on individual stocks. Aside from the tax advantage, the options on stock indexes generally trade with a lower bid-asked spread and are more liquid. This means reduced “slippage” costs resulting in less drag on performance. EOD uses both kinds of options. But the options holdings are modest (around 7%) of equity value, so the slippage factor is not a big deal here. As with many covered call funds, the fund uses a high managed distribution plan where they currently are paying out $0.18 per quarter. Five years ago the fund was paying out $0.28 per quarter, but the NAV has fallen because the total return has not kept up with the large distributions. EOD usually “earns its distribution” because of the options overlay and dividend capture strategies, but occasionally will use return of capital if there is a small shortfall. The quarterly distribution was reduced to $0.21 in November, 2012 and was lowered again to $0.18 in November, 2013. The distribution cuts have been successful in preventing major drops in NAV the last three years. This was the top eight country allocation as of July 31, 2015: U.S. 51.3% U.K. 11.4% Italy 8.2% Bermuda 7.4% France 6.8% Canada 5.4% Spain 5.2% Germany 4.2% The top equity sector allocations as of Sep. 30, 2015 are listed below. Note that there was zero exposure to the Basic Materials, Technology, Consumer Defensive or Healthcare sectors. Equity Sector Allocation Utilities 31.8% Real Estate 20.3% Communications 16.1% Financials 11.3% Consumer Cyclical 9.4% Industrials 5.6% Energy 5.5% Source: Morningstar Here is the total return NAV performance record since 2008 along with its percentile rank compared to Morningstar’s World Allocation category.   EOD NAV Performance World Allocation NAV Percentile Rank in Category 2008 -33.55% -39.30% 31% 2009 +13.33% +46.71% 100% 2010 + 3.13% +23.98% 100% 2011 – 4.44% – 3.21% 65% 2012 +9.23% +19.81% 85% 2013 +12.65% +11.07% 85% 2014 + 8.29% + 6.14% 30% YTD – 4.42% + 0.06% 91% Source: Morningstar Here are the top ten holdings for EOD as of Sep. 30, 2015: (click to enlarge) Fund Management Timothy P. O’Brien, CFA: Managing partner at Crow Point Partners LLC. Previously worked with the Value Equity team of Evergreen Investments. Has been in the investment management industry since 1983. Kandarp Acharya, CFA, FRM: Senior portfolio manager at WellsCap. Has a background in quantitative research, development of capital markets expectations, multi-asset class market risk modeling, risk management and hedging and optimization strategies. Christian L. Chan, CFA: Senior portfolio manager at WellsCap. Prior positions include roles as head of investments on several asset allocation funds at Wells Fargo, and quantitative research manager at an institutional investment consultancy. The discount to NAV as of November 6 is -14.83%. The one year discount Z-score is -1.24 and the one year average discount is -10.69%, which means that the current discount to NAV is more than one standard deviation below the average discount over the last year. Source: cefanalyzer Alpha is Generated by High Discount + High Distributions The high distribution rate of 11.46% along with the 15% discount allows investors to capture alpha by recovering a portion of the discount whenever a distribution is paid out. Whenever you recover NAV from a fund selling at a 15% discount, the percentage return is 1.00/ 0.85 or about 17.6%. So the alpha generated by the 11.46% distribution is computed as: (0.1146)*(0.176)=0.0201 or about 2% a year in discount capture alpha. Note that this is way more than the 1.07% baseline expense ratio, so you are effectively getting the fund management for free with a negative effective expense ratio of -0.93%! Ticker: EOD Wells Fargo Advantage Global Dividend Opportunity Fund pays quarterly Total Assets= $361 Million Annual Distribution (Market) Rate= 11.46% Fund Expense ratio= 1.07% Discount to NAV= -14.83% Portfolio Turnover rate= 76% Average Daily Volume= 192,000 Average Dollar Volume= $1.2 million Call Options as a % of total assets= 6.62% No leverage used This looks like a good time to start buying EOD. It is liquid and easy to purchase. Tax loss selling may still be depressing the price, so there may be more purchase opportunities as we approach year end. For those in a high tax bracket, it is probably best to purchase EOD in a tax deferred IRA account since most of the distributions are taxable income. Full Disclosure: Long EOD.

Expanding The Smart Beta Filter: Does It Help?

Summary iShares factor ETFs provide a source of well tested algorithms for factor-based stock selection. Previous examination of QUAL, MTUM and USMV have shown that this approach can produce actionable investing ideas. Can adding other, well-documented, factors improve the selective powers of this approach?. I continue to think about mining the iShares smart beta ETFs for investing ideas. In this article, I want to discuss expanding the source of data to include ETFs for risk premium factors beyond those I looked at previously. Let me start by reviewing some recent results from this exercise. My starting premise is that the set of ETFs offered by Blackrock iShares emphasizing individual risk-premium factors provides a rich source of securities that have passed their quantitative filters for the target factors. Previously I looked at three of these ETF focused on low volatility, quality and momentum factors. My goal was to find stocks that appeared in the holdings from more than one of these ETFs with the idea that such stocks have passed the MSCI index screen for more than one factor. I identified 14 stocks that occur in all three ( A Quest for the Smartest Beta ) and 60 more that occur in at least two ( Can We Find Smarter Beta From 2 Factor Portfolios? ). I found the results intriguing. First, The ETFs all beat the market, as represented by the SPDR S&P 500 Trust ETF ( SPY), as does the equal-weighted portfolio of ETFs. By analyzing a hypothetical portfolio, I was able to show that the 14 holdings from the set occurring in all three ETFs has soundly beaten all of the ETFs as well as the equal-weighted portfolio of the ETFs. This is fully documented in the second article referenced in the previous paragraph. Readers commented on my omission of two of the classic risk-premium factors and offered suggestions on incorporating them into the models. The missing factors, value and size, are, of course, important, and I’m going to look at how much, if anything, they add to the exercise as I go on. But first, let me digress here for a paragraph or two and consider why I felt these factors could, or should, be left out. Let’s start with the objective: It is to mine the quantitative algorithms of MSCI’s factor indexes for high-potential stocks. As I explained in the second article, I wanted to keep this exercise to a manageable number of funds and holdings. I thought three was optimal. Also, value and size are much less straightforward to deal with in this context. These factors form the basis for the traditional classifications of stocks: Value vs Growth and Large-, Mid-, Small-Cap. It’s the Morningstar style box. Value is variously defined and it’s not at all unusual to see the same securities turning up in growth and value funds from the same group. Size is easy, but pairs poorly with other factors depending on how one makes size cuts. By contrast, quality, momentum and low volatility are less rigorously defined (even considering the vagueness of how value is defined) and, in my view, more amenable to quantitative analysis that can produce unique, actionable results. So, I went with quality, momentum and low volatility. Quality is something I’ve been thinking about a lot, and I like the algorithm QUAL is using to define the factor (discussed here ). Momentum is another factor that can add serious alpha. I’ve been maintaining some momentum-based investing strategies in moderate-size portfolios using commission-free ETFs for several years to modest success. A problem with momentum is it tend to generate volatility and I’ve tried to modulate that in my own investing by adding a weighting for volatility (some day I may write an article on this). This reflects my appreciation for low volatility and the thinking that led me to include USMV in this project. The Factor ETFs All this is a bit subjective and intuitive, which is always something to guard against in an evidence-based approach, so I’ve decided to take readers’ advice and look at two more of iShares MSCI factor-index funds. I wanted to see if adding value and size to the analyses can improve the results. To this end, I’ll be deconstructing five ETFs looking for common holdings. The list of five, starting with the three considered earlier: iShares MSCI USA Minimum Volatility ETF (NYSEARCA: USMV ), iShares MSCI USA Momentum Factor ETF (NYSEARCA: MTUM ) iShares MSCI USA Quality Factor ETF (NYSEARCA: QUAL ) iShares MSCI USA Value Factor ETF (NYSEARCA: VLUE ) iShares MSCI USA Size Factor ETF (NYSEARCA: SIZE ) One problem right off the bat is the size of SIZE. At 636 holdings, it’s nearly four times the size of the next largest fund (USMV with 165). Perhaps as a consequence, it adds little value to the analysis, although, despite having 636 holdings, it is the least correlated with the broader market of the five ETFs. (click to enlarge) Pay particular attention to the last column in that table. SIZE is the least correlated with SPY, much lower than I would have anticipated. Note too, that VLUE is less correlated with SPY than any of the other three ETFs. I’ll start by looking at the performance of these ETFs and ask if the two new additions look likely to add any value. (click to enlarge) For the past year, they have lagged the previously considered three. But this has not been a good year for value stocks, and SIZE may add an advantage from that low correlation coefficient that will only become evident when it becomes an important variable. Deconstruction the ETF Portfolios As I did previously, I downloaded the full holdings of each of the ETFs into a spreadsheet and analyzed all five for stocks that appeared in more than one of the funds. Here’s a summary of the results. As anticipated, it quickly gets unwieldy. Only a single stock is in all five funds, and there are 20 that appear in four of the ETFs. Beyond that, there are too many to be useful for my purposes. What’s interesting is the 14 stocks that formed the basis of the earlier analysis by occurring the holdings of QUAL, MTUM and USMV, are all included in the 21 four- or five-fund stocks here. Thirteen of the 14 occur in either VLUE or SIZE; only one is in both. So, if we take the top 22 stocks here, i.e. those occurring in at least four funds, we have added eight to the previous list. So far, so good, we have increase our candidate pool; but not excessively, it’s still a manageable number. Here, for the record, are the 22 stocks with the 14 from MQLV set in italics: Axis Capital Holdings Ltd (NYSE: AXS ), Accenture Plc (NYSE: ACN ), Ace Ltd (NYSE: ACE ), Arch Capital Group Ltd (NASDAQ: ACGL ), Assurant Inc (NYSE: AIZ ), AT&T Inc (NYSE: T ), Chevron Corp (NYSE: CVX ), Chipotle Mexican Grill Inc (NYSE: CMG ), Chubb Corp (NYSE: CB ), Eli Lilly (NYSE: LLY ), Home Depot Inc (NYSE: HD ), Nike Inc Class B (NYSE: NKE ), O’Reilly Automotive Inc (NASDAQ: ORLY ), Partnerre Ltd (NYSE: PRE ), Reynolds American Inc (NYSE: RAI ), Sigma Aldrich Corp (NASDAQ: SIAL ), Starbucks Corp (NASDAQ: SBUX ), Target Corp (NYSE: TGT ), Travelers Companies Inc (NYSE: TRV ), United Health Group Inc (NYSE: UNH ), Visa Inc Class A (NYSE: V ), WR Berkley Corp (NYSE: WRB ). The first entry, Axis Capital, is the single name in all five ETFs. Sector representation is dominated by Financials and Consumer Discretionary, but it is more diverse than the set of 14 derived from three ETFs. (click to enlarge) Here is how these 22 stocks are allocated among the ETFs. As we see, all are in SIZE. SIZE is therefore acting as a binary filter to select among funds that are in three of the four funds but do not pass the size-factor filter. This is potentially a useful filter. USMV holds all but one, so it’s a similar filter. VLUE is a stronger filter. Less than half the funds are in VLUE’s holdings. I find this interesting and would have expected a result like this from MTUM, which only misses four, none of which is likely to be mistaken for a momentum stock in the current market. As I refine my thinking on this whole exercise, I have to spend more time considering how VLUE affects results. Portfolio Analysis As previously, I wanted to see the results of this filtering process. There is only one record to analyze. The funds rebalance at the end of May and November and, to my knowledge, do not publish past index allocations. Thus, there is only one analyzable record, that for the current cycle which is about 5 months old. We can see how various permutations of these results have fared since the last rebalance. I ran analyses on Portfolio Visualizer for equal-weighted portfolios comprising the following with the coding I’ve used in the tables: Five ETFs: 5ETFs EW QUAL, USMV, MTUM: 3ETFs (QVM) EW Stocks present in holdings of at least 4 of the ETFs: VQMVS(4+) VQMVS(4+) stocks in QUAL and MTUM only: QxM VQMVS(4+) stocks in QUAL and VLUE only: QxV VQMVS(4+) stocks in MTUM and VLUE only: MxV I pulled out the last three sets because USMV and SIZE were doing little more than serving as a final filter for the other three ETF holdings’ overlaps, so I thought it useful to see how those components were contributing to the results. Here are those results. (click to enlarge) As we can see, the five ETFs as an equal-weighted portfolio beat SPY, but lagged the subset of three ETFs. Let’s not forget, however, that this is only a five-month result. Longer term results can show benefit to holding all five factor ETFs, or at least four of them. For this we do have a longer record. The full record is still limited as the youngest fund only dates to July 2013. From July 2013, equal-weighted portfolios, rebalanced semiannually, of combinations of five, four and three of the ETFs turned in the following performance results. (click to enlarge) Removing either SIZE or VLUE added return and reduced maximum drawdown. Removing both, i.e. going to only QUAL, MTUM and USMV, as previously considered, improved both metrics. Volatility did increase slightly, but in all cases it remained lower than the S&P 500. These results indicate that there has been no advantage to adding VLUE or SIZE to a factor-based ETF portfolio. I’d like to say this validates my decision to use only MTUM, QUAL and USMV in my analyses, but the fact remains that the data set is too limited to draw such a conclusion. Let’s return to the previous table – and our main topic – and see how stocks filtered from the ETFs on the basis of their presence in four or more funds fared. Over the past five months, the combined ETFs returned 1.40% CAGR for all five, and 5.75% CAGR for the MQLV three. A portfolio of the 22 stocks found in four or more ETFS 29.67% CAGR and did so with a max drawdown of only -3.35% vs. -6.52% for the better performing of the two ETF portfolios. Separating out the component ETFs we see that the combination of QUAL an MTUM added a remarkable level of value, far outpacing a combination of either of the two factors with value as represented by VLUE. Yet again, I must emphasize the limited data available. But the results certainly begin to suggest that these ETFs, especially MTUM, QUAL and USMV, are attractive sources for filtered lists of stocks that rank strongly for risk-premium factors which can be further filtered for having been selected by the quite different quantitative criteria by multiple funds.