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Low Volatility Bond Strategy Using Momentum With Short Timing Periods

Summary Most momentum strategies utilize long timing periods, but because of inherently shorter latencies, shorter timing periods would in principle be preferable if whipsaws could be kept within acceptable limits. Shorter timing periods are more likely to work well with low volatility funds. A basket of four funds with daily standard deviations A relative strength tactical strategy named LVS is presented with a 10-day look-back period and 10-day simple moving average cash filter. One fund or two funds are selected each month. Backtested to 1988, the one fund version (LVS-1) has CAGR = 11.6% and MaxDD = -6.6%. The two fund version (LVS-2) has CAGR = 9.4% and MaxDD = -3.4%. LVS implementation is addressed by selecting NTF funds from both Fidelity and Schwab brokerages, and backtesting from 2000 – 2015 with these funds. Monthly win rates over 81% are observed. Tactical momentum strategies rely on look-back periods to establish the ranking of a basket of funds, and then select the best fund(s) to be held each month. The best funds are then filtered by absolute momentum or moving averages. If the funds do not pass their filter, then the money is diverted to a cash fund (usually a money market fund). There are a number of possible momentum strategies that can be used, such as 1) relative strength momentum with cash filters based on absolute momentum. This is commonly called dual momentum; 2) relative strength momentum with cash filters based on moving averages; and 3) a basket of funds with cash filters on each fund based on moving averages. The length of time periods, both for relative strength and for moving averages, is a parameter selected by the developer of a tactical strategy. Developers choose different lengths or combination of lengths based on extensive (or not so extensive) backtesting and/or the research literature. For relative strength, look-back periods ranging from 3-months to 6-months are commonly used. For moving averages, even longer time periods are typically used, e.g. 10-months or 12-months. For moving averages, it is well-known that the optimal moving average can change between asset groups, and can be substantially different under various market conditions. So picking a timing period is not a simple task. In my recent development of momentum strategies (e.g. see here , here , and here ), I have found that shorter timing periods are generally preferred in order to respond quickly to market trends. But short timing periods usually result in whipsaw and poor performance. So the big question is how can we effectively use short timing periods and avoid whipsaw. My answer is that we need to select low volatility funds in our basket of assets, funds with daily standard deviations [DSDs] of 0.35% or less. I arrived at this DSD number after studying what DSD level is needed for effective use of short duration timing periods in tactical strategies. In other words, I determined what DSD level is needed in order for short duration SMAs to produce returns higher than buy & hold, and for maximum drawdowns to be 33% or less of the maximum drawdown of buy & hold. In reality, a DSD of 0.35% is a rather arbitrary number, but it is in the right ball park. To get a feel for DSD numbers for various assets, I have listed DSD numbers for various ETFs and mutual funds from 2009 – 2015: SPDR S&P 500 ETF (NYSEARCA: SPY ): 1.02% Vanguard S&P 500 Index Fund (MUTF: VFINX ): 1.03% PowerShares Nasdaq-100 Index ETF (NASDAQ: QQQ ): 1.11% Vanguard Small Cap Index Fund (MUTF: NAESX ): 1.33% iShares Barclays Long-Term Treasury ETF – 20+ Years (NYSEARCA: TLT ): 0.98% Vanguard Long-Term Treasury Fund – 15+ Years (MUTF: VUSTX ): 0.84% SPDR Barclays Convertible Bond ETF (NYSEARCA: CWB ): 0.69% Vanguard Convertible Securities Fund (MUTF: VCVSX ): 0.59% Vanguard High Yield Corporate Bond Fund (MUTF: VWEHX ): 0.26% Dreyfus U.S. Treasury Intermediate Term Fund (MUTF: DRGIX ): 0.19% Barclays Low Duration Treasury ETF (NYSEARCA: SHY ): 0.06%. All equity assets have DSDs that are substantially greater than 0.35%, and so they can be eliminated from consideration. Some bond assets also have DSD numbers that are too high for use, including long-term treasuries and convertible securities. But there are some bond asset classes that meet the DSD requirement, and also have reasonably high returns. We do not want a fund to have low DSD at the expense of having low annualized return. Thus, a short-term treasury like SHY is not a viable candidate. I have shown previously that a strategy that employs short duration moving averages can be quite effective when used on a low volatility asset. One example is to use the crossover of 3-day and 25-day simple moving averages [SMAs] on the high yield mutual fund VWEHX. If the 3-day SMA is greater than the 25-day SMA, the strategy holds VWEHX. If not, then the strategy is in cash. Total returns and drawdown for this strategy from 2000 – 2014 can be found here . The strategy is quite effective. The DSD of VWEHX over this timespan is 0.25%. In comparison, another high yield asset that is commonly used in tactical bond strategies, SPDR Barclays Capital High Yield Bond ETF (NYSEARCA: JNK ), has a much higher DSD of 0.58% from 2009 – present, and short duration SMAs do not seem to work as well on it as they do for VWEHX. So if my hypothesis is correct, then we need to find a basket of funds that: 1) are non-correlated, 2) have DSDs less than 0.35%, and 3) have relatively high annualized return (> 5%). It turns out that mutual funds are our best option (rather than ETFs) to meet these criteria, and only certain bond classes of mutual funds are suitable. I have found four classes of bond mutual funds that meet the stated criteria. The asset categories are listed below: 1) High yield municipal bond, 2) High yield corporate bond, 3) Mortgage securities, and 4) Intermediate-term treasuries. To show the viability of this approach, I selected four funds that meet the criteria (one from each category). They all have early inception dates. The four funds that I selected are: 1. Oppenheimer Rochester AMT-Free Municipals Fund (MUTF: OPTAX ), 2. Federated High Yield Trust Fund (MUTF: FHYTX ), 3. Fidelity Mortgage Securities Fund (MUTF: FMSFX ), and 4. Dreyfus U.S. Treasury Intermediate Term Fund . The correlations of the funds, together with various forms of standard deviations and annualized returns, are shown below for the timeframe 3/27/1987 to present. These results are taken from Portfolio Visualizer, a commercially-free software package. It can be seen that the funds have relatively low correlation to each other except for FMSFX and DRGIX that have a correlation of 0.74. Notice that all of the funds essentially meet the DSD and annualized return criteria; the only exception is the annualized return of OPTAX that is slightly less than 5%. FHYTX has the highest DSD (0.33%) along with the highest annualized return (7.62%). (click to enlarge) The total returns of the funds from 1999 – present are shown below in a composite figure from StockCharts.com. Please note that the funds complement each other well, i.e. when one or more funds have a downtrend, one or more of the funds have a corresponding uptrend. And, of course, when all funds are trending down, the strategy should put the portfolio money into a money market fund. When all of the funds are trending up, the strategy will select the fund(s) with the greatest momentum. (click to enlarge) I was able to backtest these funds to 1988. I was hoping to go back to 1987, but I could not find an intermediate term treasury fund that had an inception date before 1987. I used the relative strength approach with a SMA as a cash filter. The safe harbor was a money market fund, i.e. CASHX in PV. Because of the low volatility of the funds, a 10-day look-back period for ranking could be used, and a 10-day SMA could be used as a cash filter. These are, obviously, much shorter timing periods than are commonly used in tactical strategies. They can only be used because of the low volatility of the funds. The top-ranked fund was selected at the end of each month. The results of the Low Volatility Strategy selecting one fund each month (LVS-1) are shown below. Portfolio Visualizer [PV] was used to calculate the results. In addition to LVS-1, results are also presented for a buy & hold strategy (updated annually) and for the S&P 500. The S&P 500 was used as a benchmark only because PV did not have a bond benchmark. LVS-1 Using OPTAX, FHYTX, FMSFX, and DRGIX: Total Return, 1988 – 2015 (click to enlarge) LVS-1 Using OPTAX, FHYTX, FMSFX, DRGIX: Annual Returns, 1988 – 2015 (click to enlarge) LVS-1 Using OPTAX, FHYTX, FMSFX, DRGIX: Summary, 1988 – 2015 (click to enlarge) It can be seen that LVS-1 has a Compounded Annual Growth Rate [CAGR] of 11.6%, an annualized Standard Deviation [SD] of 6.3%, a worst year of +0.5%, and a Maximum Drawdown [MaxDD] of -6.6%. In terms of growth/risk, the Sharpe Ratio is 1.2, the Sortino Ratio is 2.7, and MAR (CAGR/MaxDD) is 1.8. Comparison of these numbers to those obtained with a buy & hold strategy and the S&P 500 can be seen in the summary table. Notice that the LVS-1 has the highest CAGR and the lowest MaxDD of the three scenarios. And the MAR of LVS-1 is 1.8 versus 0.5 for buy & hold and 0.2 for the S&P 500. The results for LVS when the two highest-ranked funds are selected (LVS-2) are presented below. From the summary table we see that CAGR drops to 9.4%, but the risk is significantly reduced: SD = 4.5% and MaxDD = -3.4%. The MAR is increased to 2.8. LVS-2 Using OPTAX,FHYTX,FMSFX,DRGIX: Total Return, 1988 – 2015 (click to enlarge) LVS-2 Using OPTAX,FHYTX,FMSFX,DRGIX: Annual Returns, 1988 – 2015 (click to enlarge) LVS-2 Using OPTAX,FHYTX,FMSFX,DRGIX: Summary, 1988 – 2015 (click to enlarge) I will now present a way to practically implement the LVS on Fidelity or Schwab platforms. This requires finding mutual funds with No Transaction Fees [NTF] on Fidelity and Schwab that mimic the funds that have longer historical data (that we have just discussed). I have tried to select NTF funds that do not have any redemption fees, can be traded every 30 days, and have favorable round-trip restrictions per their prospectus. I also tried to find funds that Morningstar rated four stars or higher. The basket is composed of: 1. Nuveen High Yield Municipal Bond Fund (MUTF: NHMAX ), 2. Principal Fields Inc High Yield Fund (MUTF: CPHYX ), 3. PIMCO Mortgage-Back Securities Fund (MUTF: PTMDX ), and 4. Dreyfus U.S. Treasury Intermediate Term Fund . I ran the LVS-1 and LVS-2 with this basket of funds. The backtesting is limited to 2000 – 2015 for this basket because of the limited historical data of NHMAX. The results of LVS-1 are shown below. LVS-1 Using NHMAX, CPHYX, PTMDX, DRGIX: Total Returns, 2000 – 2015 (click to enlarge) LVS-1 Using NHMAX, CPHYX, PTMDX, DRGIX: Annual Returns, 2000 – 2015 (click to enlarge) LVS-1 Using NHMAX, CPHYX, PTMDX, DRGIX: Summary, 2000 – 2015 (click to enlarge) It can be seen that CAGR = 11.7%, SD = 6.0%, Worst Year = +4.0%, MaxDD = -6.5%, and MAR = 1.8. The monthly win rate is 81%; this win rate should be compared with a 60% – 65% monthly win rate for most backtested strategies I have seen. The results compare well with the results using OPTAX, FHYTX, FMSFX, and DRGIX backtested from 1988 – 2015. This strategy is good for an investor who wants high growth and low risk. The results of LVS-2 for NHMAX, CPHYX, PTMDX and DRGIX are presented below. LVS-2 Using NHMAX, CPHYX, PTMDX, DRGIX: Total Returns, 2000 – 2015 (click to enlarge) LVS-2 Using NHMAX, CPHYX, PTMDX, DRGIX: Annual Returns, 2000 – 2015 (click to enlarge) LVS-2 Using NHMAX, CPHYX, PTMDX, DRGIX: Summary, 2000 – 2015 (click to enlarge) It can be seen that CAGR = 9.9%, SD = 4.2%, Worst Year = +3.6%, MaxDD = -2.6%, and MAR = 3.8. The monthly win rate is 83%, an exceptionally high number in a tactical strategy. There are only 33 months with negative returns, out of a total of 190 months. These results also compare well with LVS-2 results using OPTAX, FHYTX, FMSFX, and DRGIX backtested from 1988 – 2015. This strategy is good for an investor who desires moderate growth and very low risk. In summary, a new approach has been conceived that allows the use of short timing periods in tactical strategies without seeing the associated whipsaw effects. To enable the use of short timing periods, each mutual fund in the basket of funds must have a daily standard deviation less than 0.35%. To maximize return, each fund must have adjusted annualized returns over 5%. A tactical strategy named Low Volatility Strategy [LVS] is presented that uses relative strength ranking based on total returns of the last 10 trade days, and a 10-day SMA to filter the top-ranked fund(s). After backtesting LVS to 1988 by using mutual funds with early inception dates, the implementation of the strategy was addressed. NTF mutual funds were selected for use on Fidelity or Schwab platforms. LVS-1 and LVS-2 backtest results from 2000 – 2015 showed monthly win rates over 81%. LVS-1 had a CAGR of 11.7%, a MaxDD of -6.5%, and a MAR of 1.8. LVS-2 had a CAGR of 9.9%, a MaxDD of -2.6%, and a MAR of 3.8. There were no losing years for LVS-1 or LVS-2, with either set of mutual funds.

Practical Implementation Of Tactical Strategies Employing Vanguard Mutual Funds

Summary After further assessment of my recently-developed tactical strategies published on Seeking Alpha, I have selected two strategies for “real money” testing in Vanguard accounts. These strategies trade monthly and utilize Vanguard mutual funds. Use of these mutual funds enables backtesting to 1987 and provides substantial benefits over trading ETFs. A trading schedule has been compiled that avoids any fees and/or restrictions while trading Vanguard funds. Trading usually occurs on either the last or first trade day of the month. A methodology is presented that determines how funds can be selected before end-of-the-month data are available (for those days when it is needed). Backtested to 1987 using actual funds, a high growth strategy has CAGR = 15.0% and MaxDD = -9.1%. A more conservative strategy has CAGR = 11.4% and MaxDD = -4.7%. Over the past few months, I have written a number of articles ( here and here ) about tactical strategies that employ Vanguard mutual funds traded on a monthly basis. I see the trading of mutual funds (rather than ETFs) as a paradigm shift in tactical asset allocation strategies that trade every month. In recent days I have begun real-money trading, and in the process I have had to deal with implementation issues. This article presents some of the challenges of trading Vanguard mutual funds on a monthly basis, and how I resolved these challenges. Two tactical strategies I have developed using Vanguard mutual funds are also presented: one is a high growth/moderate risk strategy and one is a moderate growth/low risk strategy. These are the strategies I am currently trading with real money. I have decided to use Vanguard accounts in this testing. I only use mutual funds that have inception dates before 1987, that have no loads/fees, and that only have a 30-day trading restriction. Vanguard spells out what the 30-day restriction encompasses: “After selling a mutual fund, you cannot buy it back within 30 days.” Thus, we must have 30 calendar days between trades if we are to successfully trade Vanguard mutual funds. Two Challenges So my first challenge was to devise a trading schedule that met the 30-day requirement between trades. It turns out that this can be accomplished rather easily. The trading schedule through 2016 is shown in the table below. It can be seen that essentially all trading days occur either on the first trading day of the month (preferred), or the last trading day of the month. There is only one time when a trade has to occur on a day before the last trading day of the month: on December 30, 2015. I have actually assembled a trading schedule through 2019, but I only show the trades days through 2016 below. Trading Schedule Through 2016 Friday, 10/30/15: last trading day; Monday, 11/30/15: last trading day, 31 days; Wednesday, 12/30/15: next to last trading day, 30 days; Friday, 1/29/16: last trading day, 30 days; Tuesday, 3/1/16: first trading day, 32 days; Friday, 4/1/16: first trading day, 31 days; Monday, 5/2/16: first trading day, 31 days; Wednesday, 6/1/16: first trading day, 30 days; Friday, 7/1/16: first trading day, 30 days; Monday, 8/1/16: first trading day, 31 days; Wednesday, 8/31/16: last trading day, 30 days; Friday, 9/30/16: last trading day, 30 days; Monday, 10/31/16: last trading day, 31 days; Wednesday, 11/30/16: last trading day, 30 days; Friday, 12/30/16: last trading day, 30 days. The second challenge that presents itself is how to determine what funds to select when the trade day arrives. I used the commercially-free Portfolio Visualizer (PV) software to run these calculations, and PV determines the selections based on end-of-the-month data. So there is no issue when a trade needs to be made on the first trade day of the new month. But when fund selections are required on the last trade day of the month, we need a methodology in place to estimate what selections should be made. In the paragraphs that follow, I propose a methodology that has a very high probability to make the correct selections before end-of-the-month data are available. And for those few times when the selections do not agree with end-of-the-month selections by PV, it is probably reasonable to think that it was really a close call anyway, i.e. either selection would have worked or not worked for that month. Monthly adjusted data (that provide total return) are first obtained for each mutual fund in the basket of funds. So for a 3-month moving average, the adjusted price data at the end of the previous two months is obtained. The latest mutual fund data (on the day before the trade day) is also recorded. One way to obtain an estimate of the end-of-the month price is to just use the price data of the next-to-last trade day as the end-of-month price. But a better way to estimate the end-of-month price of a mutual fund is to find an ETF that can be used as a proxy for the mutual fund. For instance, the SPDR Barclays Capital Convertible Bond ETF (NYSEARCA: CWB ) can be used as a proxy for VCVSX. The ETF can be tracked in real time during the trading day, and its return can be applied to the mutual fund. So if the ETF has increased 0.5% near the close of the market, then the mutual fund is assumed to increase by 0.5% from its previous day price. In this way, the end-of-month mutual fund price can be estimated, and the moving average calculated. Then the mutual fund selection can be determined and appropriate action taken on the trading day (before market close). A spreadsheet, produced by Terry Doherty, has been created that will help facilitate this calculation. It is available to readers upon request in SA private messages. Two Tactical Strategies Using Vanguard Mutual Funds My two best Vanguard mutual fund strategies will now be discussed: one (Vanguard High Growth, VHG) for the high-growth, moderate-risk investor and one (Vanguard Capital Preservation, VCP) for the conservative, moderate-growth, low-risk investor. Vanguard High Growth Strategy For the VHG Strategy, the objectives are high growth (Compounded Annual Growth Rate [CAGR] greater than 15%) and moderate risk (Standard Deviation [SD] and Maximum Drawdown on a monthly basis [MaxDD] less than 10%). Having no negative annual returns is also an objective. And a final objective is for the MAR Ratio (CAGR/MaxDD) to be greater than 1.5. These objectives are much better than the performance/risk metrics of the Vanguard 60/40 Balanced Index Fund (MUTF: VBINX ) that many money managers like to use as a benchmark for a combined equity-bond strategy. The overall metrics of VBINX from its inception in 1992 are: CAGR = 8.06%, SD = 9.05%, MaxDD = -35.06%, MAR = 0.23, and two negative return years. VHG holds three funds in equal proportions most of the time: Vanguard Convertible Securities Fund (MUTF: VCVSX ), Vanguard High Yield Corporate Fund (MUTF: VWEHX ), and Vanguard Health Care Fund (MUTF: VGHCX ). Each fund is owned every month except when a fund does not pass its 2-month Exponential Moving Average [EMA]. When the fund fails to pass its filter, the money for that fund goes to the Vanguard Long-Term Treasury Fund (MUTF: VUSTX ) for that month. The backtest results from 1987 through October, 2015 are shown below. The CAGR is 15.04%, the SD is 7.57%, the MaxDD is -9.06%, MAR is 1.55 and there are no negative years. The 2015 YTD return is 12.04%. VHG: Total Return, 1987 – 2015 (click to enlarge) VHG: Summary Table, 1987 – 2015 (click to enlarge) VHG: Annual Returns, 1987 – 2015 (click to enlarge) Some readers may object to the use of VGHCX as the equity fund in the basket. I selected it because of its superior performance and risk metrics from 1987 to present. Alternatively, the Vanguard Small Cap Equity Fund (MUTF: NAESX ) may be substituted for VGHCX. The backtest results (1987 – 2015) using NAESX in place of VGHCX are: CAGR = 13.60%, SD = 8.84%, MaxDD = -10.56%, and MAR = 1.29. Although there are three negative years of return (1987, 1994 and 2002), the returns are essentially zero in those years. So, the strategy with NAESX instead of VGHCX does not breakdown, but the performance and risk are somewhat worse using NAESX instead of VGHCX. For that reason, I decided to use VGHCX as the equity in the VGH Strategy. The robustness of the VGH Strategy (with VGHCX) is seen in its performance with different moving averages. Comparable performance and risk are seen over a wide range of moving averages, e.g. 2-month Simple Moving Average [SMA], 2-month EMA, 3-month SMA, 3-month EMA, 4-month SMA and 4-month EMA. Here are the overall results (CAGR, MaxDD and MAR) using the various moving averages: 2-month SMA: CAGR = 15.44%, MaxDD = -11.94%, MAR = 1.29 2-month EMA: CAGR = 15.04%, MaxDD = -9.06%, MAR = 1.66 3-month SMA: CAGR = 14.73%, MaxDD = -10.97%, MAR = 1.34 3-month EMA: CAGR = 14.10%, MaxDD = -9.37%, MAR = 1.50 4-month SMA: CAGR = 13.67%, MaxDD = -11.77%, MAR = 1.16 4-month EMA: CAGR = 13.85%, MaxDD = -9.97%, MAR = 1.39 As can be seen, varying the moving averages produces a fairly tight range of CAGRs (13.67% to 15.44%), MaxDDs (-9.06% to -11.94%) and MARs (1.16 to 1.66) Vanguard Capital Preservation Strategy The second strategy I will present is called Vanguard Capital Preservation [VCP]. VCP is more conservative than VHG. The objectives of VCP are: 1) CAGR greater than 10%, 2) MaxDD less than 5%, 3) MAR greater than 2.0, and 4) no negative annual returns. The basket of funds is: VCVSX; VWEHX; Vanguard High Yield Tax-Exempt Fund (MUTF: VWAHX ); Vanguard GNMA Fund (MUTF: VFIIX ); Fidelity Limited Term Government Fund (MUTF: FFXSX ), a substitute for Vanguard Short Term Treasury Fund (MUTF: VFISX ). FFXSX was used to enable backtesting to 1987; VUSTX; and VGHCX. The correlation between funds is presented below. It can be seen that the funds are not well-correlated, as desired. (click to enlarge) A dual momentum approach is utilized for VCP. The relative momentum at the end of each month is determined using one-month lookback total returns. CASHX (money market) is used as the absolute momentum filter. The three top-ranked funds are selected each month unless they do not pass the absolute momentum filter. If the absolute momentum filter is not passed, then the money for that fund goes to money market. This is in contrast to VUSTX being the safe haven in VHG. For VCP, the money market is the safe haven. What is somewhat unusual about the VCP Strategy is the short duration lookback period that is used to rank the funds each month. In many dual-momentum strategies, much longer duration lookback periods are used, e.g. 10 months or 12 months. But for some reason, perhaps because less volatile bond mutual funds are used except for VGHCX, a short duration lookback period is optimal. Usually, short lookback periods cause whipsaw in a strategy, but this does not seem to be the case in this strategy. The backtest results for VCP are shown below: VCP: Total Return, 1987 – 2015 (click to enlarge) VCP: Summary Table, 1987 – 2015 (click to enlarge) VCP: Annual Returns, 1987 – 2015 (click to enlarge) The CAGR is 11.4%, the SD is 5.61%, and the MaxDD is -4.70%. The Sharpe Ratio is 1.36, the Sortino Ratio is 2.82, and the MAR Ratio is 2.43. The only negative is that the worst annual return is 2015 YTD: +0.6%. VCP also exhibited robustness in that the lookback period could be changed from 15 trading days to 24 trading days without any significant change in performance or drawdown. VCP actually uses one calendar month (~ 21 trading days on average) for its lookback period. Summary In summary, this article has presented a way to practically implement tactical strategies using Vanguard mutual funds. To avoid trading frequency penalties, a viable trading schedule has been compiled. In order to decide what selections to make before month-end data are available, a methodology has been presented to estimate month-end data before market close. The results are presented for two tactical mutual fund strategies that I consider to be the best strategies I have developed in recent months. One strategy (Vanguard High Growth, VHG) should interest investors who want high growth (~15%) with moderate risk (less than 10% SD and MaxDD). For more conservative investors, one strategy (Vanguard Capital Preservation, VCP) produces moderate growth (~11.5%) with very low risk (SD less than 6% and MaxDD less than 5%). Currently, for November 2015, both strategies are invested in VCVSX, VWEHX, and VGHCX.

Simple Pair – Switching Bond Strategy Using Mutual Funds

Summary This strategy switches between a high yield corporate bond fund and a high yield municipal bond fund based on 3-month returns. A 3-month simple moving average filter is also used. The strategy is very low risk (i.e. low standard deviation and low maximum drawdown) while maintaining reasonable growth (~10% CAGR). Backtesting from 1986 using FAGIX and MMHYX produces CAGR = 11.3%, standard deviation = 5.5%, and maximum drawdown (based on monthly returns) = -5.5%. There are essentially no losing years. No load/no fee mutual funds must be selected for practical application. They are platform-dependent; for Schwab, I selected JAHYX and NHMAX as the best available no load/no fee mutual funds. Using JAHYX and NMHAX and backtesting to 2000, the strategy produces CAGR = 9.7%, standard deviation = 4.8%, and maximum drawdown = -3.5%. There are no losing years. This article explains a rather simple strategy that tactically switches between a high-yield corporate bond mutual fund and a high-yield municipal bond mutual fund, with money market being a safety net. The goal was to develop a low risk, capital-preservation strategy with reasonable growth (CAGR ~ 10%). I also desired to use mutual funds rather than ETFs to reduce volatility. This necessitated that the strategy be updated on a quarterly basis rather than a monthly basis (my usual preference). The reason these two bond asset classes were chosen was because they are not well-correlated; typically, their correlation is about 0.15. To show the feasibility of the strategy, I used two representative mutual funds that could be backtested to 1986 in Portfolio Visualizer (PV): Fidelity Capital and Income Fund (MUTF: FAGIX ) and MFS Municipal High Yield Bond Fund (MUTF: MMHYX ). Some might object to the usage of FAGIX as the high-yield corporate bond mutual fund because a small percentage of the fund is invested in equities rather than bonds. Fidelity Advisor High Income Advantage Class A (MUTF: FAHDX ) is actually a better representative of this class, but its history starts in 1987 in PV. I wanted to include 1987 in the analysis, so I used FAGIX instead of FAHDX. But I will show results using both FAGIX and FAHDX later in this article. The strategy uses 3-month relative strength momentum ranking to determine which asset to pick each quarter. In addition, the top-ranked asset must pass a 3-month simple moving average, MA, filter in order to be selected. If the asset does not pass this filter, then the money goes to the money market. This is a pretty simple set of parameters, and others have shown that a 3-month lookback period for bonds is most satisfactory. The backtesting was performed using the free Portfolio Visualizer (PV) software. Any investor can run these calculations and trade this strategy. The backtest results are shown below for FAGIX and MMHYX. CASHX (PV’s ticker for money market) is the cash filter asset. The timeframe is 1986 – present. It can be seen that the CAGR = 11.3%, the standard deviation, SD = 5.5%, the maximum drawdown based on monthly returns (MaxDD) = -5.5%, and the worst year = -0.3%. Risk adjustment return-on-investment can be seen using CAGR/SD and/or CAGR/MaxDD. In this strategy, CAGR/SD = 2.04, and CAGR/MaxDD = 2.02. Summary Table for FAGIX – MMHYX: 1986 – present (click to enlarge) Total Return for FAGIX – MMHYX: 1986 – present (click to enlarge) Annual Returns for FAGIX – MMHYX: 1986 – present (click to enlarge) It should be noted that results are also shown for an equal-weight portfolio, i.e. both assets are held continually and rebalanced annually. This is commonly referred to as a buy & hold strategy. The equal-weight strategy has a CAGR of 7.7%, but it has a MaxDD of -27.6% and a worst year return of -25.9%. The benefit of the tactical strategy I am proposing can readily be seen: almost 50% higher growth compared to the passive buy & hold strategy (CAGR of 11.3% versus 7.7%) and much less drawdown (-5.5% versus -27.6%). If FAHDX is substituted for FAGIX, the backtest timeframe becomes 1988 – present. The results are shown below. It can be seen that CAGR = 10.5%, SD = 5.6%, MaxDD = 6.5%, and worst year = +0.2%. The CAGR/SD = 1.89, and CAGR/MaxDD = 1.62. Summary Table for FAHDX – MMHYX: 1988 – present (click to enlarge) Total Return for FAHDX – MMHYX: 1988 – present (click to enlarge) Now comes the difficult task of picking mutual funds for a real application of the strategy. I needed to find mutual funds with no loads and no redemption fees, and operating expenses (including 12b-1 fees) that are kept to a minimum. Of course, every platform has different funds that meet these requirements. I use the Schwab platform, and they provide a lot of no load/no fee options. After extensive searching, I selected Janus High-Yield T Shs Fund (MUTF: JAHYX ) as the best high yield corporate bond mutual fund, and Nuveen High Yield Municipal Bond Fund Class A (MUTF: NHMAX ) as the best high yield municipal bond mutual fund. These funds only permit backtesting to 2000. So the results shown below have a timeframe from 2000 – present. It can be seen that CAGR = 9.7%, SD = 4.8%, MaxDD = -3.4%, and the worst year = +1.6%. The CAGR/SD = 2.03, and the CAGR/MaxDD = 2.66 (a very good number). Summary Table for JAHYX – NHMAX: 2000 – Present (click to enlarge) Total Return for JAHYX – NHMAX: 2000 – Present (click to enlarge) Annual Returns for JAHYX – NHMAX: 2000 – Present (click to enlarge) The robustness of the strategy is seen in the table below. The MA has been varied between 2 months and 4 months, and the lookback timing period (TP) was changed between 3 months and 4 months. The overall results do not change appreciably. Robustness of Strategy (click to enlarge) In summary, this article presents a very conservative tactical strategy that produces reasonable growth with very low risk. It is a quarterly updating strategy that uses less volatile mutual funds rather than ETFs. The basic strategy can be implemented on any platform, but care must be exercised in finding the best no load/no fee mutual funds for any given platform. For the Schwab platform, I believe the best mutual funds for this strategy are JAHYX and NHMAX. The pick for last quarter (July – September, 2015) was CASHX. The selection for this quarter (October – December, 2015) is NHMAX.