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Using Economic Indicators To Time The Market

If you pay attention to the financial market news, you may have noticed a lot of attention being focused on the slowing US/Global economy and the implications it has for financial markets. Just do a search on ‘slowing global PMI’ and watch the hours waste away. Basically, the US/Global economy is slowing which means recession is right around the corner, which means financial markets will tank. That seems to be the predominant bear case now, or one of the many. There is some merit to this argument. The worst market downturns occur during recessions. The trick is that you need to know that before the recessions actually happen. In this post, I’ll point you to some research in this area, then focus on just one indicator that does a decent job of forecasting recessions and how it can potentially be used as a market timing indicator on its own. To try and predict recessions, there are all kinds of metric and techniques used (ECRI, Conference board indicators, etc.). You can spend many many hours looking at all of these and their histories. Believe me. Me and an investor friend have spent tons of hours looking at and studying these. And the history of indicators predicting recessions is mixed to say the least. But I won’t bore you with that here. Instead, if you’re interested, you should read this by Philosophical Economics (which I’ll call PhiloEcon) and some of the linked posts in that piece. There is some incredible work and insight in the post (pretty much anything he/she writes is worth your time). Turns out that historically, the change in the trend in unemployment rate has been a pretty good indicator of recessions. It has also been decent at signaling when the economy has come out of a recession. Below is the key chart. Not bad. When the unemployment rate crosses above the 12-month moving average to the upside, a recession is likely coming, when it crosses below the 12-month moving average, the economy is out of the recession. Can this be used to time the stock market? And does it work better than other market timing indicator such as the popular 200-day simple moving average of prices? Basically, yes. You can read through the post and see how using the unemployment rate improves returns and risk over buy and hold and a trend following system. As usual, I wanted to run some numbers myself. Let’s take a look at that. I first wanted to see how the unemployment rate indicator (UI from now on) performed on its own versus buy and hold and other trend indicators, specifically the 200-day SMA and 12-month absolute returns. I also wanted to use real investable products, including fees. I looked at returns going back to the beginning of 1999 through April 26, 2016, for the S&P 500 ETF (NYSEARCA: SPY ), which fortunately started in 1993. This time period encompasses two of the biggest market downturns in history. I compared buy and holding the SPY versus using the 200-day SMA, 12-month total return, and the UI to exit and enter the market. When the timing systems are out of the market they are not invested, i.e. 0% cash return. Below are the results. Very impressive. This simple indicator delivered returns 3.4% per year greater than buy and hold and more than doubled risk-adjusted returns. It also beat both other timing systems by a long shot. In addition, the simple UI system produced fewer false positives and traded a lot less. Definitely worthy of consideration. You can probably see where I’ll be going next with this. In some following posts, I’ll look at adding a risk-free asset to the mix during times of risk-off, combining the UI with other indicators (which is what PhiloEcon has done in the GTT system), and adding some global risk assets to the mix. To give you a preview, they are all better than what I’ve shown here. Finally, before I end this post, what is the unemployment indicator saying right now. Does it support the bear case I noted in the opening paragraph. No, it doesn’t. The current unemployment rate is 5.0% where the 12-month moving average stands at 5.2%. If the unemployment rate increases by 0.1% each of the next two months (April and May – remember the reported unemployment rate is for the previous month), then the rate would cross above the 12-month moving average. We won’t find out until the May unemployment rate is reported at the beginning of June. And we’ll know this week what the April rate is. This seems unlikely but you never know. The FOMC’s own projections don’t support a change but they are notoriously poor forecasters. Others think that more realistically the end of the year would be the time frame we could possibly see a trigger. But there is no need to forecast to use the UI system. For now, if you were using this system it would be risk on still. In summary, historically, the change of trend in the unemployment rate has been a good signal to time the market. Better than the two most popular trend indicators around.

Are Alternative Mutual Funds Eating From The CTA Pie?

It seems like everywhere you look, you see a chart showing the upward AUM growth of liquid mutual funds, as well as the number of new funds. These charts left us with one main lingering question that we think is on the mind of many in the Managed Futures space. How big is the Liquid Mutual fund compared to the rest of the industry? And is that growth in addition to, or at the expense of, the rest of the industry? We explored this question in the latest article featured in CTA Intelligence , seen below. Are alt mutuals eating from the CTA pie? There’s no doubt that the packaging of managed futures into liquid mutual funds (’40 Acts’ as they’re called in the biz) has changed the managed futures space forever. It just depends which side of this particular aisle you’re on whether you view that as a good or bad change. On one hand, you can argue the $11bn AQR which has been brought into the space is good for the industry (in a sort of rising tide lifts all boats argument). On the other hand, there were the snickers and jeers in the audience at last year’s managed futures Pinnacle Awards when Cliff Asness won a lifetime achievement award. Many said he should have won the lifetime damage award for undercutting everyone on fees and essentially switching $11bn in money from 2/20 to 125bps). So which is it? Are managed futures mutual funds good for the industry as a whole? This may all seem like semantics, but it is surely important for those playing their particular brand of managed futures to investors. If mutuals are grabbing assets at the expense of others, then that’s surely not helpful to the grand majority of fund managers out there, not to mention the exchanges, brokerage firms, and the rest of the industry which need new money brought into the space to grow, not just the same money switching to mutual funds. Which brings us to the numbers. We gathered the data on the assets in managed futures mutual funds to trace the growth of the category since 2013. Then, we looked to compare that growth to the growth of managed futures as a whole from the BarclayHedge database. Now, a few details to consider: One, we made one big assumption, that all of the managed futures mutual fund AuM is included in the BarclayHedge CTA database, to make the math as simple as subtracting the ‘liquid AuM’ from the BarclayHedge AuM to arrive at the ‘non-liquid AuM’. Second, we subtracted Bridgewater’s AuM from the BarclayHedge numbers ( we don’t consider them to be managed futures ). And finally, we’re talking growth of assets here and sort of commingling that with inflows and outflows, as that term is known in the mutual fund world. Our methodology is considering the change in assets, so the growth or decline is both inflows/outflows and performance. As for what we would anticipate to see if there’s a rising tide effect, we would expect both curves to be up varying amounts. If there is ‘liquid’ growth at the expense of private funds, we would expect sort of mirror image curves, with private on the bottom and liquid on top. So what did we find – more of the mirrored look, albeit with private funds more mirrored than just mutual funds would explain – meaning they didn’t lose a dollar in assets for every one mutual funds brought in – they appear to have lost more. Going with BarclayHedge numbers, private funds lost around $40bn in assets through the middle of 2014 before pulling in around $20bn to end the period down roughly $19bn. Meanwhile, their liquid alt counterparts showed a slow but consistent growth of around $13bn over two years (amazingly, AQR was about $7.5bn of that amount according to Brightscope ). All in all, the managed futures mutual funds in the Morningstar managed futures mutual fund category outgrew private funds by $33bn. Click to enlarge This is interesting but it doesn’t completely answer the question we are after. Growth in assets are a good indicator of which vehicle investors are adding or subtracting from, but it doesn’t quite tell us how much of the industry is controlled by each type. Here’s a look at the percentage of managed futures assets controlled by mutual funds compared to the amount that is not. In 2013, our estimation of the total assets in managed futures through both private and liquid funds was about $206bn. The Morningstar category had around $9.6bn of that number, meaning 4.7% of the managed futures pie was controlled by mutual funds (cue pie chart): Click to enlarge Click to enlarge Fast forward to 2015, and we estimate managed futures overall actually went down in AuM by about $8.1bn to $198bn, while mutual funds grew by $13.9bn over the same time to a new high of $23.7bn, meaning managed futures mutual funds now represent 12% of the industry. The last two years have seen mutual funds share of the managed futures pie jump from 4.6% to 12%. That’s sort of impressive, but not as big of a jump as we might have thought before crunching the numbers. Perhaps, it’s important to apply context to what was going on during this growth. Managed futures was experiencing its worst drawdown in a generation throughout 2013 and the first half of 2014, then following it up by posting its best performance since 2008 in the second half of 2014.Grabbing a bigger slice of the pie with what’s generally considered ‘hotter’ money investing in mutual funds is certainly a feat. There’s no denying mutual funds are making up more of the managed futures space, but private funds still control There’s no denying mutual funds are making up more of the managed futures space, but private funds still control nine tenths of AuM – that’s a big number. The question is, what does the future trajectory look like? You would think mutual funds would continue making hay and taking a bigger and bigger slice of the pie, and indeed more and more managers we talk to are asking when, not if, they should consider switching to a mutual fund format. But then there are reports that institutional investors are looking to increase their exposure to private funds in 2016. And last but not least, it’s not a wide open road ahead for liquid alts products with new SEC derivatives rules on the horizon , potentially meaning you would need millions of dollars to trade a single Euro Dollar future, effectively putting the managed futures mutual fund complex out of business. Stay tuned…this is one battle definitely worth watching

Ivy Portfolio May Update

The Ivy Portfolio spreadsheet tracks the 10-month moving average signals for two portfolios listed in Mebane Faber’s book The Ivy Portfolio: How to Invest Like the Top Endowments and Avoid Bear Markets. Faber discusses 5, 10 and 20 security portfolios that have trading signals based on long-term moving averages. The Ivy Portfolio spreadsheet on Scott’s Investments tracks both the 5 and 10 ETF Portfolios listed in Faber’s book. When a security is trading below its 10-month simple moving average, the position is listed as “Cash.” When the security is trading above its 10-month simple moving average, the position is listed as “Invested.” The spreadsheet signals update once daily (typically in the late evening) using dividend/split adjusted closing price from Yahoo Finance. The 10-month simple moving average is based on the most recent 10 months including the current month’s most recent daily closing price. Even though the signals update daily, it is not an endorsement to check signals daily or trade based on daily updates. It simply gives the spreadsheet more versatility for users to check at his or her convenience. The page also displays the percentage each ETF within the Ivy 10 and Ivy 5 Portfolio is above or below the current 10-month simple moving average, using both adjusted and unadjusted data. If an ETF has paid a dividend or split within the past 10 months, then when comparing the adjusted/unadjusted data you will see differences in the percent an ETF is above/below the 10-month SMA. This could also potentially impact whether an ETF is above or below its 10-month SMA. Regardless of whether you prefer the adjusted or unadjusted data, it is important to remain consistent in your approach. My preference is to use adjusted data when evaluating signals. The current signals based on April 29th’s adjusted closing prices are below. This month ( GSG ) is below its moving average and the balance of the ETFs are above their 10-month moving average. The spreadsheet also provides quarterly, half year and yearly return data courtesy of Finviz . The return data is useful for those interested in overlaying a momentum strategy with the 10-month SMA strategy: Click to enlarge I also provide a “Commission-Free” Ivy Portfolio spreadsheet as an added bonus. This document tracks the 10-month moving averages for four different portfolios designed for TD Ameritrade, Fidelity, Charles Schwab and Vanguard commission-free ETF offers. Not all ETFs in each portfolio are commission free, as each broker limits the selection of commission-free ETFs and viable ETFs may not exist in each asset class. Other restrictions and limitations may apply depending on each broker. Below are the 10-month moving average signals (using adjusted price data) for the commission-free portfolios: Click to enlarge Click to enlarge Disclosure: None