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Quarterly Tactical Strategy Using Fidelity Fixed-Income Mutual Funds

Summary This strategy consists of ranking four fixed-income mutual funds based on 3-month returns, and then selecting the top-ranked fund at the end of each quarter. The top-ranked fund must pass a 3-month simple moving average filter in order to be purchased. Otherwise, the money goes into a money market asset. Backtested to 1986, the CAGR is 11.1%, the MaxDD is 5.5%, the worst year is +0.73%, and the return-to-risk ratio [CAGR/MaxDD] is 2.03. The monthly win rate is 79%. The strategy appears to be very robust in terms of relative momentum look-back period length and moving average duration. The strategy can be traded between the end of quarter [EOQ] and the next four trade days without any significant detrimental effect on performance or risk. I have recently been developing monthly tactical strategies that employ mutual funds instead of ETFs (see here and here ). There are a number of benefits in trading mutual funds instead of ETFs. First, mutual funds of a certain class tend to have much less volatility than ETFs in the same class. This permits the use of shorter duration look-back periods and moving averages in a tactical strategy without as much whipsaw. Second, there is the benefit of trading at one closing price, thus avoiding slippage losses (bid/ask losses) associated with trading ETFs. Third, mutual funds tend to have higher liquidity than ETFs. This avoids sudden price changes caused by lack of asset liquidity. Fourth, there are no fees/loads at all if Vanguard funds are traded in a Vanguard account, or Fidelity funds in a Fidelity account. And fifth, using mutual funds with long histories enables backtesting of almost 30 years, back to the mid-1980s. This is in contrast to ETFs that have very short histories, especially bond ETFs, that limit the timeframe of backtests. One of the negatives against mutual funds is the higher management expenses, but in some cases mutual funds actually have similar expenses as ETFs (e.g. Vanguard Admiral funds versus corresponding ETFs). And then there are the practical issues of trading mutual funds. These practical issues are challenging, but can be solved. Until recently, mutual funds did not permit monthly trading; severe short-term redemption penalties were charged or frequent-trading restrictions were imposed. But these penalties/restrictions have been lifted so that monthly trading is now permissible on some platforms, most notably Vanguard and Fidelity. This is the case as long as trades are made at least 30 calendar days apart. So a strict trading schedule must be followed that I have discussed previously (see here ). However, most of the trading issues are eliminated if a quarterly strategy is implemented. In past articles, I have presented monthly strategies using Vanguard mutual funds. But in this article, I am proposing a fixed-income asset allocation strategy that uses Fidelity mutual funds and trades on a quarterly basis. So the trading issues are greatly reduced. Four asset classes are used in the strategy: High yield corporate bonds: Fidelity Capital and Income Fund (MUTF: FAGIX ) High yield municipal bonds: Fidelity California Municipal Income Fund (MUTF: FCTFX ) Mortgaged-backed bonds: Fidelity Mortgage Securities Fund (MUTF: FMSFX ) Money market: CASHX (in Portfolio Visualizer). The overall objectives of this moderate growth/low risk strategy are: To attain a 10% compounded annualized growth rate [CAGR]; To achieve a maximum drawdown [MaxDD] of -5.0% (based on monthly returns); To produce a return-to-risk MAR [CAGR/MaxDD] of 2 or greater; To have positive returns every year in backtesting; and To attain a monthly win rate over 75%. The correlations between these funds are shown below, taken from Portfolio Visualizer [PV]. It can be seen that the funds have low correlation to each other, as desired. (click to enlarge) The strategy consists of ranking the 3-month total returns of each fund, and selecting the top-ranked fund at the end-of-the-quarter [EOQ]. The top-ranked fund must then pass a 3-month simple moving average [SMA] screen in order to be purchased. Otherwise, the money goes to the money market fund. It’s a pretty simple set of rules. What seems to make this strategy work is the relatively high return of FAGIX and its low correlation to FCTFX and FMSFX that have moderate return. CASHX is included as an absolute momentum filter to control risk. Backtest Results Using Portfolio Visualizer The strategy was first backtested using the PV software. All of the funds have histories that date back to at least 1985, so the backtesting went from Jan 1986 to Nov 2015. By using only Fidelity funds and trading on a quarterly basis, there are no trading costs, loads or restrictions if a Fidelity platform is used. The backtest results are shown below. Trading is done at the EOQ. (click to enlarge) (click to enlarge) (click to enlarge) (click to enlarge) The tactical strategy is compared with a buy & hold strategy in which the four funds are held continuously and rebalanced annually. The thing that jumps out at you is the large annual returns in 2003 and 2009; the rest of the time the tactical strategy has more modest returns as expected. The overall results show that the tactical strategy has a much higher CAGR (11.1% to 6.5%) and much lower MaxDD (-5.5% to -10.0%) than the buy & hold strategy. The worst year for the tactical strategy is a positive 0.7% (in 2008), while the buy and hold strategy has a worst year of negative 8.6%. It can be seen that the tactical strategy matches the buy & hold strategy over much of the timeframe, but in times of market stress, the tactical strategy performs much better than buy & hold. Backtest Results Using the Haynes’ Backtester The next step in backtesting was to assess the effects of look-back period length, SMA length, number of assets held, and trade day on the performance and risk of the tactical strategy. These calculations were performed using Herbert Haynes’ backtester. We first made sure that the Haynes’ backtester matched PV’s results for EOQ calculations. The comparative results are: PV’s Summary Results, CAGR = 11.1%, MaxDD = 5.5% (monthly basis); Haynes’ Summary Results, CAGR = 11.2%, MaxDD = 5.5% (monthly basis). Overall, we see very good agreement. All of the quarterly selections were exactly the same. The very small difference between CAGRs is probably caused by small variations in the adjusted price data between the two calculations. We proceeded to look at the effects of SMA duration. Rather than looking at calendar months, the SMA duration was switched to trade days. Twenty-one trade days corresponds to one calendar month, forty-two trade days corresponds to two calendar months, etc. The SMA duration was varied from 20 trade days to 70 trade days, and it was seen that SMA length had little impact on the results. CAGR varied from 11.2% to 11.3%, and MaxDD remained fixed at 5.5% Next, we studied the effect of the relative momentum lookback period. The lookback period was varied between 20 trade days and 84 trade days while the SMA screen was varied between 20 trade days and 50 trade days. As long as the SMA duration was 40 trade days or greater, the lookback period could be 2-months (42 trade days), 3-months (63 trade days) or 4-months (84 trade days) without any significant difference in CAGR or MaxDD. A final matrix was run in which the number of assets (1 to 3) and trade day (EOQ-20 to EOQ+20) were independently varied. For this matrix, the lookback period was fixed at 3 calendar months and the SMA screen duration was maintained at 63 days. The tabulated values and heatmaps are shown below for CAGR, MaxDD, and MAR. The tabulated values have the trade day on the top line (EOQ-20, EOQ-18, etc.) and the number of assets (1 to 3) in the first column. CAGR Results: Range = 6.1% [red] to 11.2 [blue] (click to enlarge) (click to enlarge) MaxDD Results: Range = -16.7% [red] to -4.0% [blue] (click to enlarge) (click to enlarge) MAR Results: Range = 0.5 [red] to 2.0 [blue] (click to enlarge) (click to enlarge) As expected, increasing the number of assets results in lower performance and lower risk. In terms of the return-to-risk metric [MAR], the optimal number of assets is one. One asset also produces the highest CAGR. The optimal trade days for one asset is seen to be EOQ to EOQ+4. It should be noted that this is not the equivalent of making a selection using EOQ data and waiting up to four days before making the trade. The way the program assessed the effect of trade day was to determine the fund selection and make the trade on the same day. Conclusions from Backtesting The tactical strategy is very robust in terms of the lookback duration length and SMA duration length. Significant variation of these parameters does not seem to greatly affect the backtest results. The selection of one asset each quarter (versus two or three assets) produces the best overall performance and risk adjusted returns. When only one fund is selected each quarter, the optimal trade day is EOQ to EOQ+4. Other trade days produce inferior results based on backtesting. 30-years of backtest results (1986 – 2015) show a CAGR of 11.1%, a MaxDD of 5.5%, and a MAR of 2.03. There are no losing years, and the monthly win rate is 79%. Some Practical Considerations These funds distribute their dividends on a monthly basis at the end of the month [EOM]. The dividend distribution does not make its way into the daily data until a number of days later. Thus, the selection that PV makes at EOQ may be in error until the correct data is available. The problem is that we don’t know exactly when the latest distribution information has been added to the adjusted data in PV’s selections. So a quarterly fund selection made by PV at the latest EOQ might change a few days later. Thus, each investor cannot just blindly use PV’s selection at the EOQ. Rather, each investor needs to look at the 3-month returns of the funds based on data that include the latest dividend distribution. There are two ways to determine the correct 3-month returns. One way is to take adjusted data from Yahoo and correct it for the latest dividend distribution. A second way is to use stockcharts.com (after the dividend distribution has been added to their data). Either way will work. There is an added benefit that can be achieved from this strategy that I want to discuss. It turns out that high yield mutual funds have a unique characteristic that I do not totally understand: when distributions occur on ex-div day, the price of the fund doesn’t drop by the amount of the distribution. For most funds, ETFs and stocks, whenever a dividend distribution occurs on ex-div day, the price of the asset drops by that amount. However, this does not occur for high yield mutual funds. I’m not exactly sure why the actual price does not drop on ex-div day, but it doesn’t. We can use this aspect of high yield mutual funds to our benefit. Thus, it will be better to always move from money market to FAGIX or FCTFX on EOQ-1 rather than on EOQ or later. In this way, you will receive the dividend without any accompanying loss in price. It’s like getting a free dividend payment. Likewise, if you are moving from FAGIX or FCTFX to money market, it will always be better to sell on EOQ or later (after the distribution is given). Because FMSFX has a relatively small distribution, the same rules apply to it too, i.e. selling FMSFX and buying FAGIX or FCTFX should be done on EOQ-1, and selling FAGIX or FCTFX and buying FMSFX should be done on EOQ or later. An Alternate Basket of Funds for Schwab Accounts For those investors who have Schwab accounts, an alternative basket of funds is recommended. Although there will be small costs for trading some of these funds, the costs will not be excessive because only one fund is traded each quarter. The basket of funds I recommend for use on the Schwab platform are the following: FAGIX, the Nuveen High Yield Municipal Fund (MUTF: NHMAX ), the Vanguard GNMA Fund (MUTF: VFIIX ), and a Schwab money market fund [CASHX in PV]. These funds can only be backtested from 2000 – 2015, and the results using PV are shown below, compared to the Fidelity version over the same years. Schwab Version (2000 – 2015) (click to enlarge) Fidelity Version (2000 – 2015) (click to enlarge) It can be seen that the Schwab version gives superior results in terms of CAGR (13.2% to 12.0%) while maintaining the same MaxDD (-5.5%). This is mainly caused by the superior returns of NHMAX compared to FCTFX.

As Oil Prices Plummet, Investors Flee Natural Resources Funds

By Patrick Keon Over the past two months, we witnessed a repeat of last summer’s oil price activity. As in 2014, prices of the U.S. and global oil benchmarks (West Texas Intermediate Crude [WTI] and Brent Crude) peaked near the end of June and then headed into decline. Last year, this resulted in seven consecutive months of negative price performance for both WTI and Brent, during which time they lost 54.9% and 57.2%, respectively. As the end of August approaches, the descent for both benchmarks has been more volatile than that in 2014; both WTI and Brent have recently traded at six-year lows, and are down roughly 36% and 30% from their highs at the end of June 2015. This slump in oil prices has impacted the performance and fund flows activity as well as the buy/sell decisions for funds in Lipper’s Global Natural Resources (GNR) Funds and Natural Resources (NR) Funds classifications. Mutual funds in the GNR and NR categories invest primarily in the equity securities of domestic and foreign companies engaged in the exploration, development, production, or distribution of natural resources (including oil, natural gas, and base minerals) and/or alternative energy sources (including solar, wind, hydro, tidal, and geothermal). For the purposes of the current discussion, we look only at those funds that invest the majority of their assets in oil companies; these types of funds account for the lion’s share of the funds in the GNR and NR classifications. Since July 2014, the returns on funds in the GNR and NR categories showed a positive correlation to the movement in oil prices. As illustrated in the table below, the average performance for GNR funds and NR funds followed the direction of WTI and Brent prices during the vast majority of the period. The only times all four groups did not move in the same direction occurred during August 2014 and May 2015. In August 2014, both NR (+3.2%) and GNR (+1.8%) experienced slight bumps when WTI (-0.4%) and Brent (-3.6%) trended downward, while in May 2015, WTI prices appreciated slightly (+1.1%) as the other groups fell off a bit. During the latest slide for WTI and Brent prices (late June through August), funds in the GNR (-24.2%) and NR (-24.5%) categories also experienced a similar sharp downward trend. There was also consistency within the universe: every fund in the two categories suffered at least a double-digit loss during this time frame. Lipper’s data indicates that a positive correlation also existed between the direction of oil prices and fund flows for the GNR and NR categories. During the most recent period in which WTI (-36%) and Brent (-30%) were both down significantly, we saw net outflows from both the fund classifications. GNR funds saw over $480 million leave their coffers, while NR funds had net negative flows of approximately $330 million. Within GNR, three funds were responsible for most of the money leaving the group. Leading the way was the T. Rowe Price New Era Fund No Load (MUTF: PRNEX ) with outflows of over $165 million, followed closely by the Prudential Jennison Natural Resources Fund B (MUTF: PRGNX ) and the Vanguard Energy Fund Inv (MUTF: VGENX ), down $146 million and $126 million, respectively. Within the NR grouping, one fund family accounted for the bulk of the net outflows: Fidelity Management & Research. Fidelity, which has six NR funds, had roughly $240 million leave during this time, with the Fidelity Select Energy Service Portfolio No Load (MUTF: FSESX ) and the Fidelity Select Natural Gas Portfolio No Load (MUTF: FSNGX ) (with net outflows of $71 million and $63 million) taking the two biggest hits. (click to enlarge) When oil prices rose this year (from the late first quarter to the late second quarter), the GNR and NR classifications both responded with overall net inflows. The NR group took in over $840 million, once again paced by the Fidelity family of funds. Fidelity accounted for $340 million in net new money total, with the Fidelity Select Energy Portfolio No Load (MUTF: FSENX ) taking in the largest chunk (+$183 million). Also contributing significantly to NR’s positive showing during this time frame was the Invesco Energy Fund Inv (MUTF: FSTEX ), which registered $118 million of positive net flows. The net flows into GNR (+$423 million) were roughly half of the NR net intake. The largest positive net flows were recorded by VGENX and the RS Global Natural Resources Fund A (MUTF: RSNRX ), at $353 million and $167 million. Of note, going against this trend was PRNEX, which posted net outflows (-$153 million) during the time of oil price appreciation to go along with its $165 million of negative flows during the current oil price decline. Focusing our scope on the changes in holdings in oil company stocks for GNR and NR funds during the current oil price slump, we see the selling was fairly concentrated within NR, but spread out among more stocks within GNR. Within the NR classification, four companies saw their net overall shares reduced by over one million shares, while this number grew to sixteen for the GNR category. The four companies within NR that experienced the most selling were Vantage Drilling (NYSEMKT: VTG ) (-27.6 million shares), BG Group Plc ( OTCQX:BRGXF ) (-3.1 million shares), Halliburton (NYSE: HAL ) (-2.7 million shares), and Weatherford International Plc (NYSE: WFT ) (-2.1 million shares). The number of shares of Vantage Drilling sold represented 8.8% of the company’s shares outstanding (SHOUT). Four funds completely sold out of Vantage, led by FSENX, which closed out an 18.1-million-share position. For the remainder of the group, the shares sold of each accounted for less than 1% of the company’s SHOUT. Weatherford’s activity was the result of four funds liquidating their positions, while BG Group had three funds close out their entire positions. We observe that for the selling within GNR, nine companies went from having a total aggregate position of over one million shares of their stock being held to being completely liquidated. The companies that had the largest positions closed out were Pacific Exploration and Production Corporation ( OTCPK:PEGFF ) (-3.9 million shares) and Brightoil Petroleum Holdings Ltd. ( OTC:BRTPF ) (-2.2 million shares). In each case for these nine stocks, one fund accounted for the entire initial position. The most widely held stocks within NR were essentially static during this period. Schlumberger (NYSE: SLB ) (11 funds) and Baker Hughes (NYSE: BHI ) (10 funds) were the most widely held within NR, and their totals did not change. The GNR classification showed a little more movement in its most widely held stocks. GNR started with five stocks being held by a double-digit number of funds: EOG Resources (NYSE: EOG ) (held by 15 funds), Cabot Oil & Gas (NYSE: COG ) (12 funds), Anadarko Petroleum (NYSE: APC ) (11 funds), Concho Resources (NYSE: CXO ) (11 funds), and Antero Resources (NYSE: AR ) (10 funds). Within this group, EOG Resources was unchanged, while Cabot Oil & Gas, Anadarko Petroleum, and Concho Resources all added one fund each to their totals. Antero Resources had three funds liquidate their positions, to reduce the funds holding Antero to seven. For Antero Resources, the Putnam Global Natural Resources Trust A (MUTF: EBERX ), the AllianzGI Global Natural Resources Fund Inst (MUTF: RGLIX ), and the Putnam Global Energy Fund A (MUTF: PGEAX ) liquidated positions of 4.9 million shares, 550,400 shares, and 353,200 shares, respectively. Oil prices as well as their impact on the performance and fund flows activity of natural resources funds warrant continued observation going forward. The glut in the oil supply does not show signs of abating anytime soon, since the U.S. and OPEC have not indicated any plans to reduce production. If this summer’s downturn in oil prices stretches out as long as last year’s (seven months), we can expect to see additional significant net outflows from funds in Lipper’s natural resources classifications, as well as negative returns for the groups.

FFFEX: Need A Target Date Fund? Keep Looking

Summary FFFEX offers investors a high expense ratio to go with a needlessly complex portfolio. By incorporating an enormous volume of other mutual funds the target date fund incorporates a higher expense ratio with suboptimal holdings. If the fund needs exposure to the total US market, they can ditch the complicated combination of funds and just use FSTVX. The bond holdings of FFFEX are suboptimal. Since the portfolio is so heavy on equity, the bond holdings should emphasize long term treasury securities. Lately I have been doing some research on target date retirement funds. Despite the concept of a target date retirement fund being fairly simple, the investment options appear to vary quite dramatically in quality. Some of the funds have dramatically more complex holdings consisting with a high volume of various funds while others use only a few funds and yet achieve excellent diversification. My goal is help investors recognize which funds are the most useful tools for planning for retirement. In this article I’m focusing on the Fidelity Freedom® 2030 Fund (MUTF: FFFEX ). What do funds like FFFEX do? They establish a portfolio based on a hypothetical start to retirement period. The portfolios are generally going to be designed under Modern Portfolio Theory so the goal is to maximize the expected return relative to the amount of risk the portfolio takes on. As investors are approaching retirement it is assumed that their risk tolerance will be decreasing and thus the holdings of the fund should become more conservative over time. That won’t be the case for every investor, but it is a reasonable starting place for creating a retirement option when each investor cannot be surveyed about their own unique risk tolerances. Therefore, the holdings of FFFEX should be more aggressive now than they would be 3 years from now, but at all points we would expect the fund to be more conservative than a fund designed for investors that are expected to retire 5 years later. What Must Investors Know? The most important things to know about the funds are the expenses and either the individual holdings or the volatility of the portfolio as a whole. Regardless of the planned retirement date, high expense ratios are a problem. Depending on the individual, they may wish to modify their portfolio to be more or less aggressive than the holdings of FFFEX. Expense Ratio The expense ratio of Fidelity Freedom® 2030 is .74%. That expense ratio is simply too high. Investors using a target date fund need to keep an eye on those expenses. It is possible to create a very efficient portfolio using only a few funds. Ideally the funds selected for building the portfolio would be selected for offering excellent diversified exposure at very low expense ratios. At the most simplistic level, an investor is looking for domestic equity, international equity, domestic bonds, and international bonds. If any of those had to be left out, the international bond allocation is the least important. In my opinion, there is no need to use both growth and value indexes. There is no need to individually use large, medium, and small-cap allocations. For instance, the Fidelity Spartan® Total Market Index (MUTF: FSTVX ) has a net expense ratio of .05% and offers exposure to the vast majority of the U.S. market. If you were building a target date fund from Fidelity funds, you could simply use FSTVX and eliminate all other domestic equity funds. This method would provide investors with a low expense ratio on the underlying domestic equity position and excellent diversification. That is precisely why I am including FSTVX as a holding in my portfolio. The Vanguard Target Retirement 2030 Fund (MUTF: VTHRX ) has an expense ratio of .17%. Just so investors have a healthy comparison of how much it costs to run a very efficient target retirement fund, the Vanguard expense ratio gives a pretty clear indication. Holdings / Composition The following chart demonstrates the holdings of Fidelity Freedom® 2030: If you were making a target date fund, how many allocations would you need? Hopefully it wouldn’t be that many. Note that the holdings chart above simply showed the equity funds. There is simply no need for a portfolio to be this complex. The list below shows the bond portfolios: A Major Problem When you look at the equity portfolio, it is very complex. When you look at the bond portfolio, it is quite simple. The issue I’m noticing is that the portfolio is not holding any allocations specifically to treasury securities. There is one allocation to investment grade bonds, but that is it. This portfolio suffers from almost every sector allocation having positive correlation with the other sector allocations. When investors give up the negative beta of long term treasuries it is extremely difficult to be on the efficient frontier. When you combine missing out on the benefits of negative beta with having a very high expense ratio, you have a very poor choice for a retirement fund. Looking Deeper Since there is only one bond fund that is has an allocation greater than 4%, I decided to look deeper into that holding. The Fidelity® Series Investment Grade Bond Fund (MUTF: FSIGX ) is closed to new investors, has an expense ratio of .45%, and has a fairly weak allocation to treasuries as demonstrated by the following chart: (click to enlarge) Treasury securities are making up 20.4% of the portfolio. The resulting portfolio clearly deviates quite dramatically from the selected index fund. When I used Invest Spy to run a regression on FSIGX, the negative beta was only -.08. Fidelity has other long term bond funds like the Fidelity Spartan® Long Term Trust Bond Index Fund (MUTF: FLBAX ) which have dramatically lower betas. How much lower is the beta for FLBAX? It is around -.46. Simply put, FLBAX belongs in most Fidelity target date funds because it offers a great negative correlation to equity holdings. Of course, allocating money to FLBAX may be less profitable since it only has a .1% expense ratio. Volatility An investor may choose to use FFFEX in an employer sponsored account (if their employer has it on the approved list) while creating their own portfolio in separate accounts. Since I can’t predict what investors will choose to combine with the fund, I analyze it as being an entire portfolio. (click to enlarge) When we look at the volatility on FFFEX, it is only moderately lower than the volatility on the SPDR S&P 500 Trust ETF (NYSEARCA: SPY ). For a fund that has the option to include long term treasuries, international diversification, and in general has an enormous combination of underlying funds, it is very disappointing that the target date fund for investors that are only 15 years from retirement has demonstrated almost as much volatility without offering even close to as much in the way of returns. Granted, the S&P 500 has thoroughly defeated international markets over the last several years. Having weaker returns is perfectly acceptable for FFFEX; the problem is that it also had a similar max drawdown. If the fund included a substantial position in FLBAX, that max drawdown would not have been near as bad. I’ve demonstrated a combination of FFFEX with a 20% allocation to FLBAX: (click to enlarge) Even though FLBAX also has a huge max drawdown, the extremely negative beta results in the max drawdown events occurring at different times for each funds and the combined portfolio has a max drawdown of only 9.4%. For the investor that is only 15 years out from retirement (20 years from when the sample period began), having a max drawdown of 9.4% sounds much better than 17.5%. Of course, investors should not rely on historical results as predicting future results. The example is simply to demonstrate that a portfolio of domestic equities and long term treasuries has been capable of maintaining fairly low portfolio volatility due to the historical negative correlation of the two asset classes. Conclusion When an investor takes on an expense ratio that is even .3% higher and pays that ratio for 20 years, they are looking at losing 6% of the value of the portfolio without accounting for compounding. If investors account for the benefits of compounding and assume annual returns are positive, the potential value lost is even greater than 6%. FFFEX is an expensive option for investors looking for a simple “set it and forget it” retirement plan from their employer sponsored retirement accounts. The volatility of the fund is not a problem and the total exposures are not unreasonable. The problem comes down to two issues. One is that the fund has needlessly complicated the portfolio holdings and the other is that the expense ratio is simply too high when compared to similar products offered by competitors. There are some great funds offered by Fidelity and I have positions in a few of them. Unfortunately, this fund just falls short of the mark. To improve the allocations within the fund, the managers should dramatically simplify the portfolio and use low expense funds for allocations to each core section. Those sections would be domestic equity, international equity, treasuries, and international bonds. Having a small allocation to junk bonds would be fine as well.