Using Market Generated Information For Market Structure: Financial Stock ETFs

Jan 23, 2017

Last month we did a blog post on using high-yield bonds as a key indicator.   This month we continue with a focus of using financial stock ETFs as a second indicator.

Many people seem to want to try to simplify everything down to one variable -- often something like a P/E ratio or a moving average.   We think investors should look at a range of important indicators and then take a weight-of-the-evidence approach.   Indeed, we built ETFreplay.com so that you can easily run and update a list of strategies AND do this on a continuous basis and thereby stay in tune with the overall structure of the market.

There is no better information than that which the market itself generates.  A good market participant will learn to read what the market structure is telling you by analyzing its intermarket relationsihps.

Financial companies have business models that make our economy go.  From mortgages and credit cards for individuals to bank loans and payment services for corporations, financial companies are absolutely vital indicators on overall conditions and this is why these companies are regulated closely by government agencies.

It makes sense that when financial stocks are doing well, how bad can the market environment be??   Look back at past recessions and you will see very poor performance of financial stocks.

The backtest below is meant as an INDICATOR -- not a strategy to implement per se.

When financial stocks are beating a known risk-off stable segment like US Consumer Staples,   we will bring our portfolio Beta up above 1.00 by adding a 25% position in SSO  (the 2x S&P 500 ETF).

When financial stocks are underperforming, we will split our holdings into 50% SPY and 50% TLT.   This is the 'risk-off' portfolio.    (Note that in this example -- no matter which regime is in play, the portfolio will hold at LEAST 50% SPY -- think of that as the 'core' portfolio and the other 50% as the 'satellite').

Here are the results.   Make sure to dive-in and immerse yourself in this topic.  Alter the time periods incrementally.   Alter the risk-on risk-off portfolios.   Study sub-period backtests.   What are the good aspects to this backtest?   What are the possible limitations?  

 

 

Follow us on Follow etfreplay on Twitter

Tags:

ETF Regime Change Backtesting – update of a 2011 example

Dec 02, 2016 in Backtest

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, which can be seen here, 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.

Follow us on Follow etfreplay on Twitter

Tags:

Classic Example of ETF Market Generated Information - Junk Bond Investors

Oct 17, 2016 in Bonds

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.

 

Follow us on Follow etfreplay on Twitter

Tags:

Subscriber Loyalty Rewards

Sep 29, 2016

We are announcing that, effective immediately, subscribers to ETFreplay will now automatically benefit from loyalty based discount subscription rates.

Last year we introduced discounted annual subscriptions, to give longer term clients a better deal. We have now decided to go much further to acknowledge and reward our loyal customers. 

As of today, there are 3 discount levels; Bronze, Silver and Gold. 

Eligibility for each level is automatically determined by the number of consecutive billing periods that a live subscription has been held.

The eligibility criteria and subscription rate at each level is as follows:

 

For more information see Loyalty Discounts

Follow us on Follow etfreplay on Twitter

Tags:

Trailing Stops vs Time Interval Stops. Yes ETFreplay has stops built into its architecture.

Sep 28, 2016 in Backtest

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 on the stop-price.   

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 taking 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 but 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).

 

 

Follow us on Follow etfreplay on Twitter

Tags:

Sharpe Ratio vs ETF Relative Strength Model

Sep 14, 2016 in Relative Strength | Screener

 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 view 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: http://www.etfreplay.com/faq.aspx

 

Follow us on Follow etfreplay on Twitter

Tags:

Ratio Moving Average Backtest Example

Sep 02, 2016 in Backtest

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):

 

 

 

 

 

Follow us on Follow etfreplay on Twitter

Tags:

New: Channel backtests

Jun 08, 2016 in Backtest

We recently added Total Return percentile channels to our range of backtesting tools.

The primary focus of ETFreplay has always been on relative strength analysis and we have tended to see moving averages as serving largely as an easy to understand introduction to backtesting in general.

Like basic MAs, channels are a trend following approach that use only an ETFs own past return history. i.e. they are not relative. 

However, unlike MAs, channels are defined by two measures (highs and lows) rather than just one, which intuitively makes sense as an uptrend is a series of higher lows and higher highs.  This also means that channels automatically adjust to volatility.

i.e. in a wide swinging trading range the channel boundaries will be far apart, whereas when the market winds down into tight range the channel will be narrow.

Standard channels are simply the highest and lowest values over the prior x days, weeks or months and the use of channel breakouts in trend following is long established. However, for investors such wide channels can mean:

  • Slow responsiveness. Trade frequency is extremely low because it takes a lot to enter a position and a very large change to trigger an exit.
  • Whipsaw losses, when they occur, are painfully large.

To ameliorate these problems, the backtests allow percentiles of the channel to be employed (the defaults being the 75th percentile for buys and 25th percentile for sells).  Doing so means that positions are entered / exited sooner, but the channel still remains wide enough to mitigate against frequent quick whipsaws.

See:
Single ETF channel backtest

Portfolio channel backtest (subscribers)

Follow us on Follow etfreplay on Twitter

Tags:

Low Volatility vs Consumer Staples Sector ETF USMV vs XLP

May 20, 2016

Attached is the longer-term performance of Low Volatility (using the index that USMV tracks for its Total Return) vs Consumer Staples (using XLP, the consumer staples SPDR).

These 2 are both low vol equities but as you can see -- are not exactly the same thing.

 

 

Follow us on Follow etfreplay on Twitter

Tags:

A short note on the psychology of investing

Apr 12, 2016

Over the last eighteen months US equity low volatility and relative strength strategies have performed comparatively well, whereas moving average and international portfolios have generally struggled. The reality is that, regardless of whichever investment approach is adopted, there will be periods of both outperformance and underperformance. It was ever thus.

Good returns are fairly easy to handle; unless they lead to hubris, they largely take care of themselves. But there are no certainties in investing, only probabilities. 

Nothing works all the time. Even when the odds are strongly in your favor, the trade / position won’t always work out. Probabilities play out in the long-run. In the short-term, anything can happen. Accept it.

There will be periods of underperformance. When this happens it will be tempting to switch to a different approach that’s recently performed better. However, constantly searching for the 'answer' and bouncing between strategies is a great way to fail to capture the long term returns of any approach.

i.e. Chucking in the towel on a buy-and-hold portfolio in 2009 and switching to a trend following approach. Then changing strategy once again in 2015 after that took some whipsaw losses.

Having realistic expectations from the start makes it considerably more likely that you will have the necessary perseverance to stick with your chosen strategy.  This is where analyzing backtests, delving deep into the results, seeing that there have been adverse periods in the past, can be highly beneficial.

Pursuing any single investment approach requires mental fortitude.  Buy-and-hold investors need to be able to stomach the deep drawdowns that their portfolios will suffer in bear markets. Those investing tactically require the temperament to handle the frustration of inevitable whipsaws.

Diversifying at the strategy level (a la core-satellite), however, can provide an emotional hedge for those times when the market environment is particularly unfavorable to one approach or the other. It obviously also means not having to trust one’s objectives to the performance of a solitary model.

Regardless of the approach, it’s the process, rather than short-term results, that must be kept uppermost. It’s by sticking with the process that objectives are most likely to be achieved over the long run.

Some resources that might be useful: 

A Wealth of Common Sense: From Great to Good
A Wealth of Common Sense: The Psychology of Sitting in Cash
Morgan Housel: It Was a Good Bet
Meb Faber: Why Are You Outperforming? Why Are You Underperforming?
Bason Asset Management: Diversification Sucks

Follow us on Follow etfreplay on Twitter

Tags: