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Q1 Asset Class Returns

The first question we had to ask ourselves after looking at the returns in March was, “Are the asset classes becoming increasingly correlated?” Here’s what happened in March by the numbers: 7 of the 8 Asset Classes recorded positive returns in March 4 of the 8 Asset Classes posted significant returns in March (Above 4%) 10.32% – The return of Real Estate in March 4 – Number of slots Real Estate moved up in the asset class scoreboard after March 2nd place – Where Managed Futures currently ranks despite a down month in March Real Estate: A double-digit return in a month is something you cannot ignore. What’s with Real Estate? The ETF we use (NYSEARCA: IYR ) tracks 100 different real estate companies , but the rebound could have something to do with another asset class… bonds (interest rates). Bonds: Depending on what Bond Market you watch, it was a big month. With the ETF we use is only up around 3% on the year, but the High Yield bonds cracked the Top 25 for best all-time monthly performance {Disclaimer: Past performance is not necessarily indicative of future results}. For those that have been following along the low interest rate environment we’ve been living in for almost a decade, low interest rates are good for people looking to purchase a home or refinance their mortgage. World Stocks, U.S. Stocks, and Commodities: Is the fact that these three asset classes all moved in tandem in March a coincidence or are these markets showing their true colors or being highly correlated? Last Week, we charted the current rolling 30 day correlation of the S&P 500 has to Crude Oil and not only has the correlation been increasing, 2016 has shown the highest correlation over a two year period. Managed Futures: Finally, Managed Futures had a tough month with the U.S. Dollar experiencing a choppy downward market. Combine that with the $VIX returning to the lows we saw constantly throughout 2014 and some of 2015 , and it was a struggle for managers to capture trends in choppy markets. We know the managers that we work with were long commodities but late reversals in the markets took away any gain made earlier in the month. The good news is that combined with the strong first two months of 2016 is enough to keep Managed Futures in 2nd place, despite a down March. Here’s the full look at the Q1 performance of 8 asset classes. Click to enlarge Click to enlarge (Disclaimer: past performance is not necessarily indicative of future results.) Source: All ETF performance data from Morningstar.com Sources: Managed Futures = SGA CTA Index, Cash = 13 week T-Bill rate, Bonds = Vanguard Total Bond Market ETF (NYSEARCA: BND ), Hedge Funds= IQ Hedge Multi-Strategy (NYSEARCA: QAI ) Commodities = iShares GSCI ETF (NYSEARCA: GSG ); Real Estate = iShares DJ Real Estate ETF ( IYR ); World Stocks = iShares MSCI ACWI ex US Index Fund ETF (NASDAQ: ACWX ); US Stocks = SPDR S&P 500 ETF (NYSEARCA: SPY )

Tactical Asset Allocation – April 2016 Update

March was good month for risk assets. Let’s see if it continues in April. Here is the tactical asset allocation update for April 2016. Below are the updates for the AGG3, AGG6, and GTAA13 portfolios. The source data can be found here . These signals are valid after every trading day. So, while I maintain these month-end updates, this means that you can implement your portfolio changes on any day of the month, not just month end. FINVIZ will at times generate signals that are slightly different than Yahoo Finance. Note: I am not maintaining the Yahoo Finance versions any more. All portfolios now use FINVIZ data. Click to enlarge This month, AGG3 has one new holding with real estate, VNQ , back in the mix. AGG6 also has MTUM and VTV as new holdings. Approximate monthly and YTD performance is below. In a new change, global asset allocation is working well in 2016. Click to enlarge For the Antonacci dual momentum , GEM and GBM portfolios, GEM is back in SPY , and the bond portion of GBM is in MBB . I have changed the MBS tracking ETF to MBB, from VMBS , due to errors in FINVIZ. I also now compare the FINVIZ data to Yahoo Finance for the bond portion. The Antonacci tracking sheet is shareable, so you can see the portfolio details for yourself. The Bond 3 quant model , see spreadsheet , ranks the bond ETFs by 6-month return and uses the absolute 6-month return as a cash filter to be invested or not. The Bond 3 quant model is invested in IGOV , EMB , and VGLT . That’s it for this month. These portfolios signals are valid for the whole month of April. As always, post any questions you have in the comments.

Happy Hour: Build Your Own Smart Beta

I don’t own smart beta funds because I don’t believe they fit my strategy. Instead, I stick with a simple approach, four funds – a U.S., developed international, emerging markets, and treasury bonds – adjusting the allocation based on valuation. Basically, I move from expensive to cheap and if all equities are expensive then move from expensive to bonds. That’s the simplified version. I don’t believe smart beta would add enough “extra return” due to the adjustments. It’s very possible – I haven’t tested it – that I’d get a lower return from smart beta funds due to poor timing and higher costs, so I just stick with the lowest cost approach. Why pay more for something that I might not get? That’s the way I see it. It’s not perfect but it fits my mentality and it’s easy to manage. But if I could design the ideal smart beta fund around my strategy, it’d be based off a global index weighted by quality and price. The highest weighting would go to the highest quality, lowest priced stocks and move down from there. And I really see no reason to own every stock in said index. I’d eliminate all the highest priced, lowest quality stocks or expensive junk. And it would maintain a “cash position” if too many stocks exceeded a specific low quality and/or expensive limit. And it would do it all at a low cost. Pipe dreams, I know. Maybe someday it will be possible to build personally customized funds at a low cost. If it happens, I’m certain someone will screw it up. Anyways, the point of this was because of a slew of smart beta articles I saw this week. Smart betas “market-beating returns” are nice to look it. That’s the draw and the downfall. Too often people pick funds based on performance – not what best fits their strategy – because they don’t have a strategy or their strategy is to chase performance. So most investors will never see those returns. They’re not willing to accept periods of less than market returns to get the excess return over time. Most investors will get better returns simply by being more robotic. Less mistakes lead to higher returns over time. Doing nothing more often with a basket of basic index funds will get you a better return than chasing the best performing smart beta funds. All their doing is spending more money (via higher fees) to make the same costly mistakes. Once you’ve got doing nothing down pat, then look into smart beta and factor tilts. If it fits your strategy, then use it. And if not, then don’t. Last Call