Dec 02, 2016
in Regime Change
Back in 2011 we produced a little video that compared the performance of two very different 60-40 allocations: an aggressive portfolio invested in Emerging Markets, Financials and High Yield; and a defensive strategy based around Treasury Bonds, Utilities and Healthcare.
The purpose of that video, was not to show which allocation was best but rather to illustrate that 'that different sectors perform differently during the course of the business cycle'. It therefore makes sense that when there is a change in the overall regime, allocations should be materially adjusted.
Below is an update to that original example. The same two aggressive and defensive allocations are used, but this time we have employed the Regime Portfolios Backtest to dynamically switch between them depending on the prevailing regime. For this example with have used a simple credit spread style ratio to define the regime. When high yield bonds are outperforming treasuries, the backtest invests in the aggressive allocation. When the opposite is true, it switches to the defensive portfolio.
This is not meant to be a comprehensive strategy by any means, it's just a simple example to illustrate the concept of adapting to change. Hopefully though it provides a solid starting point for subscribers to conduct their own regime based research.
Oct 17, 2016
in Ratio
Every recession has something in common: investors flee junk bonds. You do NOT have to predict this, you only need to monitor it.
Junk bond investors got worried in late 2014 and much of 2015 -- and the stock market went effectively nowhere during that time (while High-Quality and Low Volatility segments outperformed strongly).
Most of 2016 has seen a decent bull market in junk bonds. Since fixed-income investors are very sensitive to their income actually being fixed --- and not variable, this group of investors is a very useful group to track.
Sep 28, 2016
in Stop Loss
From subscriber on email: "I would like to put a trailing stop on the backtest and/or investigate what would happen if I stopped and moved to cash."
This is one of the more common questions we get on email from members.
First off, built into the ETFreplay architecture IS a natural form of stop. A stop is of course a point at which you exit -- either by moving to cash or moving to another security. A good relative strength backtest will naturally move towards the performing ETF(s) and away from the non-performers. We have different trade interval choices on ETFreplay and if you choose say monthly, then you have a stop built-in -- it is just a 'time-interval (monthly) stop.'
Yes you are essentially locking in a full months performance and not exiting immediately and people often view this as risky -- but that is NOT what the evidence shows. Having the perception of being 'less risky' instead just means you 'feel emotionally better because you are out of the market.' Holding on until month-end and accepting that extra time-risk is often dramatically better than locking in a loss at a percentage.
Why? Because first, stops usually get hit as market gets oversold and then it bounces back and you end up rotating at a dis-advantageous price on the stop-loss order.
But importantly there is a second reason, the market often not only bounces -- it recovers back strongly and sometimes back to a new swing high and you end up NOT rotating and are sitting on a paper non-taxable gain rather than having taken a real loss and now in cash and out of the market potentially missing more upside.
This second case has happened many times during the bull market that began a few years ago. If you stopped out, did you get back in higher?? Many times that might be emotionally tough to do. If you accept the calendar month return, you might occassionally be worse off -- but this is usually offset by the 'death by a thousand cuts' underperformance risk so many twitchy traders suffer from....
But what about stops as many people read about in all those trading books?
Trading books are almost always based on things that have no ETF research or backtest support, many no backtest support at all. Some recommend a 'percentage based stop' (ie, stop if XYZ drops by -8% from your purchase price). Those that say they have research behind their method don't present the actual results and instead have done limited testing and made conclusions based on one set of detailed assumptions. These are also almost always done on individual stocks -- not ETFs. We are experts in ETF backtests and people should be aware that backtesting an ETF is NOT the same thing as backtesting an individual stock. We have done a fair bit of work on individual stocks too -- but find that individual stocks are extremely noisy and it takes a tremendous amount of trading activity (many small positions to offset the added noise) to actually implement anything where the statistics can back it up. Many invstment advisors simply can't do such things as trade hundreds and thousands of individual stocks every month or quarter. (And as you can see in hedge fund results, neither can hedge funds that try to do it).
Also with individual stocks, you are always worried about a total cratering -- your stock potentially becoming a penny stock or bankrupt. But even if you forget that ultimate risk, many stocks can lose tremendously more than a typical index ETF and simply not recover wheras an index of many stocks will recover. Many past stocks that had large weightings in an index collapsed and the index not that soon after went back to new highs -- think Bank of America or Cisco Systems or worse Worldcom and countless others that were at one point considered core holdings. With individual stocks, you cannot take hits like that that and never rotate away. The losses can be huge and importantly, the opportunity cost of sitting in a dead stock long past its prime can cause you to dramatically underperform.
Some of the hidden beauty of an index is that they by rules-based methodology let winning stocks and groups of winning stocks grow in weighting while broken stocks of past cycles lose their significance (weighting).
While time-interval stops can work for individual stocks too, we are more concerned with how this all applies to ETFs since ETFs work much better for trading practicality reasons (after all, trading an ETF is exactly the same thing as trading a large basket of stocks all at once). You get hundreds or even thousands of trades (and the associated altered exposure) for the cost of zero (assuming you are in a free trading program like Schwab, Ameritrade or others have).
Sep 14, 2016
in Relative Strength
Why does your Relative Strength ranking of ETFs, work better than ranking them using the Sharpe Ratio?
The ETFreplay Relative Strength ranking methodology has the Sharpe Ratio concept at its core but it also reflects some more modern financial modelling methodologies.
So the Sharpe Ratio has volatility in the denominator. The thing about this is that the Sharpe Ratio effectively overrates very low volatility ETFs. In reality, investors value returns more than they do extreme low volatility. For example, a 12% return with 8% volatility is viewed much more positively than an 8% return with 4% volatility. That move from 8% down to 4% is not nearly as meaningful as the return differential. What investors really want is a solid return with acceptable volatility. Investors can tolerate some level of drawdown with a long-term focus -- just not large drawdowns.
Another thing we did was enable the user to use 2 timeframes for return. The reason is that it is well-accepted that a model can have up to 3 factors as the factors can help each other out. More than 3 factors starts to run into data-mining, which is something we need to be careful of.
Sometimes 1 factor which backtests well over longer time periods can have a rough patch. Another factor can help mitigate the problems and by using 2 return periods, we are not overly reliant on a single return factor.
Hope that helps and let us know if you have any other questions or comments.
See also our FAQ's for common questions
Sep 02, 2016
in Ratio
There are lots of ways to skin a cat of course. Here is a look at results of using a simple total return ratio between Emerging Markets (VWO) and an iShares Treasury ETF (IEF):
