Category Archives: EDS

The RS4r: Tracking Relative Strength In Four Dimensions

Relative strength has more information embedded within it than meets the eye. Here is a way to identify and compress several dimensions of relative strength into one single scalable value, the RS4r, which allows you to compare and then rank securities for robustness across timeframes and shifting market conditions…

The importable AIQ EDS file based on James Garofallou’s article in
Stocks & Commodities magazine September 2020 issue, “The RS4r: Tracking Relative Strength In Four Dimensions,” can be obtained on request via email to info@TradersEdgeSystems.com. The code is also available here:

! The RS4r: Tracking Relative Strength in Four Dimensions
! Author: James Garofallou, PhD, TASC Sept 2020
! Coded by: Richard Denning, 7/18/2020

!INPUTS
C is [close].
len1 is 10.
len2 is 15.
NumIndx is 4.
BuyLvl is 80.

!FORMULAS
SPYc is TickerUDF("SPY",C).      !SP500
QQQc is TickerUDF("QQQ",C).     !NASDAQ100
MDYc is TickerUDF("MDY",C).     !SP400
IWMc is TickerUDF("IWM",C).      !Russel2000

RS1spy is C/SPYc.
RS1qqq is C/QQQc.
RS1mdy is C/MDYc.
RS1iwm is C/IWMc.

FastSPY is Expavg(RS1spy,len1).
MedSPY is Simpleavg(FastSPY,7).
SlowSPY is Simpleavg(FastSPY,15).
VSlowSPY is Simpleavg(SlowSPY,30).

FastQQQ is Expavg(RS1qqq,Len1).
MedQQQ is Simpleavg(FastQQQ,7).
SlowQQQ is Simpleavg(FastQQQ,15).
VSlowQQQ is Simpleavg(SlowQQQ,30).

FastMDY is Expavg(RS1mdy,Len1).
MedMDY is Simpleavg(FastMDY,7).
SlowMDY is Simpleavg(FastMDY,15).
VSlowMDY is Simpleavg(SlowMDY,30).

FastIWM is Expavg(RS1iwm,Len1).
MedIWM is Simpleavg(FastIWM,7).
SlowIWM is Simpleavg(FastIWM,15).
VSlowIWM is Simpleavg(SlowIWM,30).

Tier1spy is iff(FastSPY>=MedSPY and MedSPY>=SlowSPY and SlowSPY>=VslowSPY,10,0).
Tier1qqq is iff(FastQQQ>=MedQQQ and MedQQQ>=SlowQQQ and SlowQQQ>=VslowQQQ,10,0).
Tier1mdy is iff(FastMDY>=MedMDY and MedMDY>=SlowMDY and SlowMDY>=VslowMDY,10,0).
Tier1iwm is iff(FastIWM>=MedIWM and MedIWM>=SlowIWM and SlowIWM>=VslowIWM,10,0).

Tier2spy is iff(FastSPY>=MedSPY and MedSPY>=SlowSPY and SlowSPY<VslowSPY,9,0).
Tier2qqq is iff(FastQQQ>=MedQQQ and MedQQQ>=SlowQQQ and SlowQQQ<VslowQQQ,9,0).
Tier2mdy is iff(FastMDY>=MedMDY and MedMDY>=SlowMDY and SlowMDY<VslowMDY,9,0).
Tier2iwm is iff(FastIWM>=MedIWM and MedIWM>=SlowIWM and SlowIWM<VslowIWM,9,0).

Tier3spy is iff(FastSPY<MedSPY and MedSPY>=SlowSPY and SlowSPY>=VslowSPY,9,0).
Tier3qqq is iff(FastQQQ<MedQQQ and MedQQQ>=SlowQQQ and SlowQQQ>=VslowQQQ,9,0).
Tier3mdy is iff(FastMDY<MedMDY and MedMDY>=SlowMDY and SlowMDY>=VslowMDY,9,0).
Tier3iwm is iff(FastIWM<MedIWM and MedIWM>=SlowIWM and SlowIWM>=VslowIWM,9,0).

Tier4spy is iff(FastSPY<MedSPY and MedSPY>=SlowSPY and SlowSPY<VslowSPY,5,0).
Tier4qqq is iff(FastQQQ<MedQQQ and MedQQQ>=SlowQQQ and SlowQQQ<VslowQQQ,5,0).
Tier4mdy is iff(FastMDY<MedMDY and MedMDY>=SlowMDY and SlowMDY<VslowMDY,5,0).
Tier4iwm is iff(FastIWM<MedIWM and MedIWM>=SlowIWM and SlowIWM<VslowIWM,5,0).

RS2spy is Tier1spy + Tier2spy + Tier3spy + Tier4spy.
RS2qqq is Tier1qqq + Tier2qqq + Tier3qqq + Tier4qqq.
RS2mdy is Tier1mdy + Tier2mdy + Tier3mdy + Tier4mdy.
RS2iwm is Tier1iwm + Tier2iwm + Tier3iwm + Tier4iwm.


RS3x is  (RS2spy+RS2qqq+RS2mdy+RS2iwm).

RS4 is (RS3x/NumIndx)*10.
RS4osc is simpleavg(RS4,3).
mvSig is simpleavg(RS4osc,5).
RS4r is round(RS4).

mvRS4 is expavg(RS4r,4).
RS4up is iff(RS4r >= 80 or RS4r > mvRS4,1,0).

X is iff(RS4 >= 80,1,0).
R5 is iff(RS4up =1,round(simpleavg(X,len2)*100),0).

Buy if R5 >= BuyLvl.
ExitBuy if R5 < BuyLvl.

ShowValues if 1.

Code for the RS4r is included in the EDS file. I also coded a system that uses the RS4r (R5). I used four independent ETFs as indexes rather than the 11 mutual funds that the author used. I used SPY, QQQQ, MDY, and IWM. The trading system buys (long only) when the R5 >= 80 and exits the long position when RS4r < 80. The summary EDS backtest report for trading this system on the Nasdaq 100 stocks (commission & slippage not subtracted) is shown in Figure 13 and a sample trade on DISH with the R5 indicator is shown in Figure 12.

Sample Chart

FIGURE 12: AIQ. Chart of DISH with R5 indicator and sample trade using R5 indicator >= 80 to buy.

Sample Chart

FIGURE 13: AIQ. Summary EDS backtest report for the R5 system that trades the Nasdaq 100 stocks over the last 4 years.

—Richard Denning
info@TradersEdgeSystems.com
for AIQ Systems

The Calm Before the Bond Storm?

The bond market was very quiet in the 3rd quarter.  Figure 1 displays ticker IEF (7-10 year treasuries ETF) in the to clip and ticker AGG (Aggregate Bond Index ETF) in the bottom clip. 

Figure 1 – Tickers IEF and AGG in narrow ranges (Courtesy AIQ TradingExpert)

Essentially the entire bond market has been flat since early June.  The market seems to be assuming that “the Fed will take of everything” and keep interest rates low and stable for the foreseeable future so…..ZZZZZZZZ.

But this type of activity often breeds complacency.  I am not making any predictions here but I do want to raise a question that investors might wish to ponder, i.e., “what would be more shocking that a spike in interest rates?”  OK, yes, I realize it is 2020 and it is pretty much hard to be shocked by anything anymore.  But still, on a relative basis how many investors are even thinking about the potential risk of higher interest rates at the moment?

Could it Happen?

The Bond Market VIX (ticker MOVE) recently fell to its lowest level ever (before spiking sharply higher on 10/5/20).  As you can see in Figure 2 this type of “quietness” often precedes a significant move in the bond market.  For the record, low readings in MOVE can be followed by large up moves in price as easily as large down moves in price.  So, a low MOVE reading is not “bearish” per se, but rather merely suggests that we are experiencing the “calm before the storm.”

Figure 2 – Bond Market VIX hit an all-time low (Courtesy Sentimentrader.com)

So why is my “Spidey sense” tingling?  Figure 3 displays the yield on 30-year treasuries (ticker TYX) on the bottom and an indicator I refer to as VFAA on the bottom (the calculation appears at the end of this piece).  VFAA is a derivative on a Larry William’s indicator he calls VixFix.

Figure 3 – 30-year treasury yields with VFAA suggesting a potential bottoming area (Courtesy AIQ TradingExpert)

As you can see in Figure 3, peaks in the VFAA indicator often occur near intermediate term lows in bond yields (reminder: bond prices move inversely to yield, so a bottom in interest rates indicates a top in bond prices).  As you can also see on the far-right hand side, the stage clearly appears to be set for “the next go round.”

Why does this matter?  If interest rates do rise in the months ahead bond prices – particularly long-term bond prices can get hit hard.  To illustrate the potential risks, Figure 4 displays the action of treasury security ETFs of various maturity during a 5-month rise in rates back in 2016.

Figure 4 – Bond ETF action during rate rise in 2016

Summary

It is possible for long and short-term bonds to “de-couple”.  In other words, the possibilities are:

*Short-term rates remain stable (as the Fed keeps pumping) while long-term rates rise (as inflation fears arise as a result of all the Fed pumping)

*Short-term rates remain stable while long-term rates plummet (if the economy appears to be weakening).  This would result in gains for long-term bonds only

*None of the above

The bottom line: Bonds have fallen asleep – but DO NOT fall asleep on bonds. 

VFAA Formula

Below is the code for VFAA

VixFix is an indicator developed many years ago by Larry Williams which essentially compares the latest low to the highest close in the latest 22 periods (then divides the difference by the highest close in the latest 22 periods).  I then multiply this result by 100 and add 50 to get VixFix.

*Next is a 3-period exponential average of VixFix

*Then VFAA is arrived at by calculating a 7-period exponential average of the previous result (essentially, we are “double-smoothing” VixFix)

Are we having fun yet?  See code below:

hivalclose is hival([close],22).

vixfix is (((hivalclose-[low])/hivalclose)*100)+50.

vixfixaverage is Expavg(vixfix,3).

vixfixaverageave is Expavg(vixfixaverage,7).

VFAA = vixfixaverageave

Jay Kaeppel

Disclaimer: The information, opinions and ideas expressed herein are for informational and educational purposes only and are based on research conducted and presented solely by the author.  The information presented represents the views of the author only and does not constitute a complete description of any investment service.  In addition, nothing presented herein should be construed as investment advice, as an advertisement or offering of investment advisory services, or as an offer to sell or a solicitation to buy any security.  The data presented herein were obtained from various third-party sources.  While the data is believed to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  International investments are subject to additional risks such as currency fluctuations, political instability and the potential for illiquid markets.  Past performance is no guarantee of future results.  There is risk of loss in all trading.  Back tested performance does not represent actual performance and should not be interpreted as an indication of such performance.  Also, back tested performance results have certain inherent limitations and differs from actual performance because it is achieved with the benefit of hindsight.

Good Companies, Troubled Stocks and Potential Opportunity

Truth be told I am not much of a “stock picker”. Oh, I can pick ‘em alright just like anyone else.  They just to don’t go the right way as often as I’d like.  I also believe that the way to maximize profitability is to follow a momentum type approach that identifies stocks that are performing well and buying them when they breakout to the upside (ala O’Neil, Minervini, Zanger, etc.) and then riding them as long as they continue to perform.  Unfortunately, I’m just not very good at it. 

Back when I started out, there was such a thing as a “long-term investor.”  People would try to find good companies selling at a decent price and they would buy them and hold them for, well, the long-term.  Crazy talk, right? As I have already stated, I am not claiming that that is a better approach. I am just pointing out that it was “a thing.”

An Indicator

There is an indicator (I will call it VFAA, which is short for vixfixaverageave, which – lets face it – is a terrible name) that I follow that was developed as an extension of Larry William’s VixFix Indicator.  There is nothing magic about it.  Its purpose is to identify when price has reached an exceptionally oversold level and “may” be due to rally.  The code for this indicator appears later.

For the record, I DO NOT systematically use this indicator in the manner I am about to describe, nor am I recommending that you do.  Still, it seems to have some potential value, so what follows is merely an illustration for informational purposes only.

The Rules

*We will look at a monthly bar chart for a given stock

*A “buy signal” occurs when VFAA reaches or exceeds 80 and then turns down for one month

*A “sell (or exit) signal” occurs when VFAA subsequently rises by at least 0.25 from a monthly closing low

Seeing as how this is based solely on monthly closes it obviously this is not going to be a “precision market timing tool.”

Some “Good Companies” with “Troubled Stocks”

So now let’s apply this VFAA indicator to some actual stocks.  Again, I AM NOT recommending that anyone use this approach mechanically.  The real goal is merely to try to identify situations where a stock has been washed out, reversed and MAY be ready to run for a while.

Ticker BA

Figure 1 displays a monthly chart for Boeing (BA) with VFAA at the bottom.  The numbers on the chart represent the hypothetical + (-) % achieved by applying the rules above (although once again, to be clear I am not necessarily suggesting anyone use it exactly this way). 

Figure 1 – Ticker BA with VFAA (Courtesy AIQ TradingExpert)

From March 2019 into March 2020 BA declined -80%.  It has since bounced around and VFAA has soared to 110.88.  VFAA has yet to rollover on a month-end basis, so nothing to do here except exhibit – what’s that word again – oh right, “patience.”

Ticker GD

Figure 2 displays a monthly chart for General Dynamics (GD) with VFAA at the bottom. 

Figure 2 – Ticker GD with VFAA (Courtesy AIQ TradingExpert)

Are these “world-beating numbers”?  Not really.  But in terms of helping to identify potential opportunities, not so bad. VFAA gave a “buy signal” for GD at the end of July. So far, not so good as the stock is down about -6%.

Ticker WFC

Figure 3 displays a monthly chart for Wells Fargo (WFC) with VFAA at the bottom. 

Figure 3 – Ticker WFC with VFAA (Courtesy AIQ TradingExpert)

There are not many “signals” but the ones that occurred have been useful. Between 2018 and 2020 WFC declined -65%.  It has since bounced around and VFAA has soared to 102.44.  VFAA has yet to rollover on a month-end basis. But at some point it will, and a potential opportunity may arise.

VFAA Formula

Below is the code for VFAA

VixFix is an indicator developed many years ago by Larry Williams which essentially compares the latest low to the highest close in the latest 22 periods (then divides the difference by the highest close in the latest 22 periods).  I then multiply this result by 100 and add 50 to get VixFix.

*Next is a 3-period exponential average of VixFix

*Then VFAA is arrived at by calculating a 7-period exponential average of the previous result (essentially, we are “double-smoothing” VixFix)

Are we having fun yet?  See code below:

hivalclose is hival([close],22).

vixfix is (((hivalclose-[low])/hivalclose)*100)+50.

vixfixaverage is Expavg(vixfix,3).

vixfixaverageave is Expavg(vixfixaverage,7).

VFAA = vixfixaverageave

EDITORS NOTE: The AIQ Expert Design Studio code for the indicator is available to download from here. Save this file to your /wintes32/EDS Strategies folder https://aiqeducation.com/VFAA.EDS

Summary

One thing to note is that VFAA “signals” on a monthly chart don’t come around very often.  So, you can’t really sit around and wait for a signal to form on your “favorite company”.  You have to look for opportunity wherever it might exist.

One last time let me reiterate that I am not suggesting using VFAA as a standalone systematic approach to investing. But when a signal does occur – especially when applied to quality companies that have recently been “whacked”, it can help to identify a potential opportunity.

Jay Kaeppel

Disclaimer: The information, opinions and ideas expressed herein are for informational and educational purposes only and are based on research conducted and presented solely by the author.  The information presented represents the views of the author only and does not constitute a complete description of any investment service.  In addition, nothing presented herein should be construed as investment advice, as an advertisement or offering of investment advisory services, or as an offer to sell or a solicitation to buy any security.  The data presented herein were obtained from various third-party sources.  While the data is believed to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  International investments are subject to additional risks such as currency fluctuations, political instability and the potential for illiquid markets.  Past performance is no guarantee of future results.  There is risk of loss in all trading.  Back tested performance does not represent actual performance and should not be interpreted as an indication of such performance.  Also, back tested performance results have certain inherent limitations and differs from actual performance because it is achieved with the benefit of hindsight.

Vitali Apirine’s – The Compare Price Momentum Oscillator (CPMO)

The importable AIQ EDS file based on Vitali Apirine’s article in the August, 2020 issue of Stocks & Commodities magazine, “The Compare Price Momentum Oscillator (CPMO),” can be obtained on request via email to info@TradersEdgeSystems.com.

… Here is a way you can compare at a glance the momentum of two different market indexes or securities in the same chart. It could also be used to help generate trading signals. In this first part of a three-part series, we’ll look at comparing index momentums…

The code is also available here:

!Author: Vitali Aprine, TASC August 2020
!Coded by: Richard Denning, 6/20/20
!www.TradersEdgeSystems.com

!Custom smoothing multiplier: 2 / time period
!PMO line: 20-period custom EMA of (10 × 35-period
!custom EMA of ((Today’s price – Yesterday’s price) / !Yesterday’s price × 100))
!PMO signal line: 10-period EMA of the PMO line

Len1 is 20.
Len2 is 35.
Len3 is 10.
Ticker1 is “QQQ”.
Ticker2 is “SPY”.

C is [close].
C1 is valresult(C,1).
RC1 is (C/C1*100)-100.

custSmoLen1 is Len1 – 1.
custSmoLen2 is Len2 – 1.

CustEma is 10*expavg(RC1,custSmoLen2).
PMO is expavg(CustEma,custSmoLen1).
PMOsig is expavg(PMO,Len3).

Ticker1C is tickerUDF(Ticker1,C).
RC1ticker1 is (Ticker1C/valresult(Ticker1C,1)*100)-100.
CustEmaTicker1 is 10*expavg(RC1ticker1,custSmoLen2).
PMOticker1 is expavg(CustEmaTicker1,custSmoLen1).

Ticker2C is tickerUDF(Ticker2,C).
RC1ticker2 is (Ticker2C/valresult(Ticker2C,1)*100)-100.
CustEmaTicker2 is 10*expavg(RC1ticker2,custSmoLen2).
PMOticker2 is expavg(CustEmaTicker2,custSmoLen1).

CPMO is PMOTicker1 – PMOTicker2.
List if hasdatafor(1000) >= 900.

I coded the indicator described by the author. Figure 10 shows the indicator (QQQ,SPY,20,35) on chart of IWM. When the white line is above the red line on the CPMO indicator, this indicates that the QQQ is stronger than the SPY. Generally, it is considered bullish when the QQQ is leading in strength.

Sample Chart

FIGURE 10: AIQ. The CPMO indicator is shown on a chart of IWM with parameters (QQQ,SPY,20,35).

—Richard Denning
info@TradersEdgeSystems.com
for AIQ Systems

Financials – Danger or Opportunity? Or Both?

To say that there is has been and remains a great deal of angst in the financial markets is a bit of an understatement. This is especially true when it comes to the financial sector.  The financial sector has a fairly high correlation to treasury yields (ticker FSRBX – Fidelity Select Banking Portfolio has a 0.52 correlation to ticker TNX – which tracks 10-year treasury yields).  As yields have plummeted so has the financial sector.  During the recent decline, FSRBX plunged -51% from its December 2019 peak.  With little expectation of higher rates anytime soon a lot of investors are understandably wary of diving into this sector.

But much like with the energy sector, the old adage that the time to buy is when there is “blood in the streets”, should give one pause before they turn their back completely on the financial sector.  For the time being I am keeping my eye on a little-known indicator called “Vixfixaverageave” (yes, I agree it is a really bad name).  The calculations for this indicator appear at the end of this article.  The reason I am watching it right now is that it recently reached a very oversold level that has helped to highlight some useful buying opportunities for financials in the past.

Ticker FSRBX

Figure 1 displays a monthly chart for FSRBX in the top clip and the Vixfixaverageave indicator in the bottom clip.  Note that the indicator rose above 72 at the end of April 2020.  As you can see there have been four previous occasions when this indicator, a) exceeded 72 and then b) reversed lower for one month.  For arguments sake we will call that a buy signal.

Figure 1 – Ticker FSRBX with indicator Vixfixaverageave (Courtesy AIQ TradingExpert)

Figure 2 displays the 1 to 5 year % + (-) for FSRBX following the four previous signals.  As you can see, they all proved to be exceptional buying opportunities.

Figure 2 – FSRBX returns 1 to 5 years after signal

Now for the disappointing news: if you are thinking that all we have to do is wait for this indicator to finally top out and that big profits are “guaranteed” to roll in, you are making a mistake.  As they say, “past performance is no guarantee of future results.”  (Sorry, I don’t make the rules).  So, when the Vixfixaverageave monthly reading for FSRBX does finally roll over, the proper course of action would be to:

*Decide if you really want to act based on the signal

*Decide how much capital you are willing to commit

*Decide how much of that capital you are actually willing to risk – i.e. will you stop out if a loss exceeds x%, or do you plan to simply hold it for 1 to 5 years regardless?

Summary

There are a million and one ways to trigger an entry signal.  The one discussed herein is just one more.  What really separates the winners from the losers is the answers to the three questions just posed.

Vixfixaverageave Calculations 

EDITTORS NOTE: The code sections can be copied and pasted into AIQ EDS or you can download the indicator code in an EDS file from here and save it to your /wintes32/EDS Strategies folder.

This indicator is based on another indicator called VixFix which was developed many years ago by Larry Williams.

hivalclose is hival([close],22).  <<<<<The high closing price in that last 22 periods

vixfix is (((hivalclose-[low])/hivalclose)*100)+50. <<<(highest closing price in last 22 periods minus current period low) divided by highest closing price in last 22 periods (then multiplied by 100 and 50 added to arrive at vixfix value)

vixfixaverage is Expavg(vixfix,3). <<< 3-period exponential average of vixfix

vixfixaverageave is Expavg(vixfixaverage,7). <<<7-period exponential average of vixfixaverage

Jay Kaeppel

Disclaimer: The information, opinions and ideas expressed herein are for informational and educational purposes only and are based on research conducted and presented solely by the author.  The information presented represents the views of the author only and does not constitute a complete description of any investment service.  In addition, nothing presented herein should be construed as investment advice, as an advertisement or offering of investment advisory services, or as an offer to sell or a solicitation to buy any security.  The data presented herein were obtained from various third-party sources.  While the data is believed to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  International investments are subject to additional risks such as currency fluctuations, political instability and the potential for illiquid markets.  Past performance is no guarantee of future results.  There is risk of loss in all trading.  Back tested performance does not represent actual performance and should not be interpreted as an indication of such performance.  Also, back tested performance results have certain inherent limitations and differs from actual performance because it is achieved with the benefit of hindsight.

A Simple Way To Trade Seasonality


In “A Simple Way To Trade Seasonality” in the September 2019 Stocks & Commodities, author Perry Kaufman describes methods he uses for measuring the seasonality in markets and approaches he uses for trading these patterns

Editors note: The full article can be obtained from Stocks & Commodities magazine at
http://technical.traders.com/sub/sublog2.asp#Sep the system rules are from the article and are based on these rules

1. Average the monthly frequency of the past 4 years.

2. Find the last occurrence of the highest frequency and the last occurrence of the lowest frequency using the average frequency in step 1. That is, if both March and April have a frequency of 70, we use April.

3. Only trade if the high frequency is 75% or greater and the low frequency is 25% or lower.

4. If the high frequency comes first, sell short at the end of the month with the high frequency. Cover the short at the end of the month with the low frequency.

5. If the low frequency comes first, buy at the end of the month with the low frequency. Sell to exit at the end of the month with the high frequency

The importable AIQ EDS file and Excel spreadsheet for Perry Kaufman’s article can be obtained on request via email to info@TradersEdgeSystems.com. The code is also shown below

!A Simple Way to Trade Seasonality
!Author: Perry Kaufman, TASC September 2019
!Coded by: Richard Denning, 07/21/2019
!www.TradersEdgeSystem.com

C is [close].
year is 2019.
len is 4000.
OSD is offsettodate(month(),day(),year()).
FirstDate is firstdatadate().

EOM1 if Month()=2 and valresult(month(),1)=1 and year()=year.
EOMos1 is scanany(EOM1,len) then OSD+1.
EOMc1 is valresult(C,^EOMos1).
EOM2 if Month()=3 and valresult(month(),1)=2 and year()=year.
EOMos2 is scanany(EOM2,len) then OSD+1.
EOMc2 is valresult(C,^EOMos2).
EOM3 if Month()=4 and valresult(month(),1)=3 and year()=year.
EOMos3 is scanany(EOM3,len) then OSD+1.
EOMc3 is valresult(C,^EOMos3).
EOM4 if Month()=5 and valresult(month(),1)=4 and year()=year.
EOMos4 is scanany(EOM4,len) then OSD+1.
EOMc4 is valresult(C,^EOMos4).
EOM5 if Month()=6 and valresult(month(),1)=5 and year()=year.
EOMos5 is scanany(EOM5,len) then OSD+1.
EOMc5 is valresult(C,^EOMos5).
EOM6 if Month()=7 and valresult(month(),1)=6 and year()=year.
EOMos6 is scanany(EOM6,len) then OSD+1.
EOMc6 is valresult(C,^EOMos6).
EOM7 if Month()=8 and valresult(month(),1)=7 and year()=year.
EOMos7 is scanany(EOM7,len) then OSD+1.
EOMc7 is valresult(C,^EOMos7).
EOM8 if Month()=9 and valresult(month(),1)=8 and year()=year.
EOMos8 is scanany(EOM8,len) then OSD+1.
EOMc8 is valresult(C,^EOMos8).
EOM9 if Month()=10 and valresult(month(),1)=9 and year()=year.
EOMos9 is scanany(EOM9,len) then OSD+1.
EOMc9 is valresult(C,^EOMos9).
EOM10 if Month()=11 and valresult(month(),1)=10 and year()=year.
EOMos10 is scanany(EOM10,len) then OSD+1.
EOMc10 is valresult(C,^EOMos10).
EOM11 if Month()=12 and valresult(month(),1)=11 and year()=year.
EOMos11 is scanany(EOM11,len) then OSD+1.
EOMc11 is valresult(C,^EOMos11).
EOM12 if Month()=1 and valresult(month(),1)=12 and valresult(year(),1)=year.
EOMos12 is scanany(EOM12,len) then OSD+1.
EOMc12 is valresult(C,^EOMos12).
YEARavg is (EOMc1+EOMc2+EOMc3+EOMc4+EOMc5+EOMc6+EOMc7+EOMc8+EOMc9+EOMc10+EOMc11+EOMc12)/12.

AR1 is (EOMc1 / YEARavg-1)*100.
AR2 is (EOMc2 / YEARavg-1)*100.
AR3 is (EOMc3 / YEARavg-1)*100.
AR4 is (EOMc4 / YEARavg-1)*100.
AR5 is (EOMc5 / YEARavg-1)*100.
AR6 is (EOMc6 / YEARavg-1)*100.
AR7 is (EOMc7 / YEARavg-1)*100.
AR8 is (EOMc8 / YEARavg-1)*100.
AR9 is (EOMc9 / YEARavg-1)*100.
AR10 is (EOMc10 / YEARavg-1)*100.
AR11 is (EOMc11 / YEARavg-1)*100.
AR12 is (EOMc12 / YEARavg-1)*100.

EOMc if firstdate < makedate(1,20,2019-20).
AR if EOMc.

The EDS code is not a trading system but a way to get the data needed into an Excel spreadsheet to enable you to make the seasonal calculations. The EDS file should be run on a date after the end of the year being calculated. Each year for which data is needed must be run separately by setting the “year” variable. Multiple symbols can be run at the same time by using a list of the desired symbols. Each time a year is run, the “AR” report must be saved as a “.csv” file. Once all the years needed have been run and saved to separate “.csv” files, they all should be cut and pasted to a single Excel sheet. They then can be sorted by symbol and each symbol can be copied and pasted to a tab for that symbol.

Figure 6 shows the rolling four-year frequency for the S&P 500 ETF (SPY) and Figure 7 shows the annual trades resulting from applying the seasonal rules to the frequency data.

Sample Chart

FIGURE 6: AIQ. Shown here is the rolling four-year frequency for the SPY.

Sample Chart

FIGURE 7: AIQ. Shown here are the annual trades resulting from applying the seasonal rules to the frequency data for SPY.

—Richard Denning
info@TradersEdgeSystems.com
for AIQ Systems

What it Will Take to Get Commodities Moving

I keep seeing headlines about the “imminent” re-emergence of commodities as a viable investment as an asset class.  And as I wrote about here, I mostly agree wholeheartedly that “the worn will turn” at some point in the years ahead, as commodities are historically far undervalued relative to stocks.

The timing of all of this is another story.  Fortunately, it is a fairly short and simple story.  In a nutshell, it goes like this:

*As long as the U.S. Dollar remains strong, don’t bet heavy on commodities.

The End

Well not exactly. 

The 2019 Anomaly

The Year 2019 was something of an anomaly as both the U.S. Dollar and precious metals such as gold and silver rallied.  This type of action is most unusual.  Historically gold and silver have had a highly inverse correlation to the dollar.  So, the idea that both the U.S. Dollar AND commodities (including those beyond just precious metals) will continue to rise is not likely correct.

Commodities as an Asset Class

When we are talking “commodities as an asset class” we are talking about more than just metals.  We are also talking about more than just energy products. 

The most popular commodity ETFs are DBC and GSG as they are more heavily traded than most others.  And they are fine trading vehicles.  One thing to note is that both (and most other “me too” commodity ETFs) have a heavy concentration in energies.  This is not inappropriate given the reality that most of the industrialized world (despite all the talk of climate change) still runs on traditional fossil fuel-based energy.

But to get a broader picture of “commodities as an asset class” I focus on ticker RJI (ELEMENTS Linked to the Rogers International Commodity Index – Total Return) which diversifies roughly as follows:

Agriculture          40.90%

Energy               24.36%

Industrial Metals 16.67%

Precious Metals    14.23%

Livestock               3.85%

Note that these allocations can change over time, but the point is that RJI has much more exposure beyond the energy class of assets than alot of other commodity ETFs.

RJI vs. the Dollar

As a proxy for the U.S. Dollar we will use ticker UUP (Invesco DB US Dollar Index Bullish Fund).  Figure 1 displays the % gain/loss for UUP (blue line) versus RJI (orange line) since mid-2008.

Figure 1 – UUP versus RJI; Cumulative Return using weekly closing prices; May-2008-Sep-2019

*Since May of 2008 UUP has gained +17.2%

*Since May of 2008 RJI has lost -60%

The correlation in price action between these two ETFs since 2008 is -0.76 (a correlation of -1.00 means they are perfectly inverse), so clearly there is (typically) a high degree of inverse correlation between the U.S. dollar and “commodities”.

Next, we will apply an indicator that I have dubbed “MACD4010501” (Note to myself: come up with a better name).  The calculations for this indicator will appear at the end of the article (but it is basically a 40-period exponential average minus a 105-period exponential average).  In Figure 2 we see a weekly chart of ticker UUP with this MACD indicator in the top clip and a weekly chart of ticker RJI in the bottom clip.

Figure 2 – UUP with Jay’s MACD Indicator versus ticker RJI (courtesy AIQ TradingExpert )

Interpretation is simple:

*when the MACD indicator applied to UUP is declining, this is bullish for RJI

*when the MACD indicator applied to UUP is rising, this is bearish for RJI.

Figure 3 displays the growth of equity achieved by holding RJI (using weekly closing price data) when the UUP MACD Indicator is declining (i.e., RJI is bullish blue line in Figure 3) versus when the UUP MACD Indicator is rising (i.e., RJI is bearish orange line in Figure 3).

Figure 3 – RJI cumulative performance based on whether MACD indicator for ticker UUP is falling (bullish for RJI) of rising (bearish for RJI)

In sum:

*RJI gained +45.8% when the UUP MACD indicator was falling

*RJI lost -72.3% when the UUP MACD indicator was rising

The bottom line is that RJI rarely makes much upside headway when the UUP MACD Indicator is rising (i.e., is bearish for RJI).

Summary

Commodities as an asset class are extremely undervalued on a historical basis compared to stocks.  However, the important thing to remember is that “the worm is unlikely to turn” as long as the U.S. Dollar remains strong.

So, keep an eye on the U.S. Dollar for signs of weakness.  That will be your sign that the time may be coming for commodities.

FYI: Code for Jay’s MACD4010501 Indicator (AIQ TradingExpert EDS)

The indicator is essentially a 40-period exponential average minus a 105-period exponential average as shown below:

Define ss3 40.

Define L3 105.

ShortMACDMA3 is expavg([Close],ss3)*100.

LongMACDMA3 is expavg([Close],L3)*100.

MACD4010501 is ShortMACDMA3-LongMACDMA3.

Jay Kaeppel

Disclaimer: The information, opinions and ideas expressed herein are for informational and educational purposes only and are based on research conducted and presented solely by the author.  The information presented does not represent the views of the author only and does not constitute a complete description of any investment service.  In addition, nothing presented herein should be construed as investment advice, as an advertisement or offering of investment advisory services, or as an offer to sell or a solicitation to buy any security.  The data presented herein were obtained from various third-party sources.  While the data is believed to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  International investments are subject to additional risks such as currency fluctuations, political instability and the potential for illiquid markets.  Past performance is no guarantee of future results.  There is risk of loss in all trading.  Back tested performance does not represent actual performance and should not be interpreted as an indication of such performance.  Also, back tested performance results have certain inherent limitations and differs from actual performance because it is achieved with the benefit of hindsight.

Exponential Deviation Bands

The importable AIQ EDS file based on Vitali Apirine’s article in July 2019 Stocks & Commodities issue, “Exponential Deviation Bands,”

and a recreated Excel spreadsheet similar to the one shown in the article can be obtained on request via email to info@TradersEdgeSystems.com. The code is also shown here:

Exponential deviation (ED) bands are plotted above and below a moving average (MA) from which the bands are calculated. An exponential deviation from the moving average is used to set the bands. ED bands can be used with either a simple moving average (SMA) or an exponential moving average (EMA). The moving average dictates direction, and the exponential deviation sets band width. Breakouts from the band and changes in the band’s direction can help identify price trends and price reversals. These bands can be used on a variety of securities with its standard settings.

!EXPONENTIAL DEVIATION BANDS
!Author: Vitali Apirine, TASC July 2019
!Coded by: Richard Denning, 5/15/2019
!www.TradersEdgeSystems.com

C is [close].
Periods is 20. 

MA20 is simpleavg(C,Periods).   !expavg(C,Periods).  !or simpleavg(C,Periods). 
MDev20 is (Abs(MA20-C)+Abs(MA20-valresult(C,1))+Abs(MA20-valresult(C,2))+Abs(MA20-valresult(C,3))
      +Abs(MA20-valresult(C,4))+Abs(MA20-valresult(C,5))+Abs(MA20-valresult(C,6))+Abs(MA20-valresult(C,7))
     +Abs(MA20-valresult(C,8))+Abs(MA20- valresult(C,9))+Abs(MA20- valresult(C,10))+Abs(MA20- valresult(C,11))
     +Abs(MA20- valresult(C,12))+Abs(MA20- valresult(C,13))+Abs(MA20- valresult(C,14))+Abs(MA20- valresult(C,15))
      +Abs(MA20- valresult(C,16)) +Abs(MA20- valresult(C,17))+Abs(MA20- valresult(C,18))+Abs(MA20- valresult(C,19)))/20.

Dev is Abs(MA20-C).  
Rate is 2/( Periods +1).  

DaysInto is ReportDate() - RuleDate().
Stop if DaysInto >= 200.
stopEXD is iff(Stop,Mdev20, EXD).
EXD is Dev*Rate + valresult(stopEXD,1)*(1-Rate).

UpperExp is MA20+2*EXD.  
MidExp is MA20.  
LowerExp is MA20-2*EXD. 

ShowValues if 1.

Figure 9 shows the exponential deviation bands centered on a 20-bar simple moving average on a chart of the New York Composite Index (NYA).

Sample Chart

FIGURE 9: AIQ. Here are exponential deviation bands centered on a 20-bar simple moving average on a chart of the New York Composite Index (NYA).

—Richard Denning
info@TradersEdgeSystems.com
for AIQ Systems

Backtesting A Mean-Reversion Strategy In Python

The importable AIQ EDS file based on Anthony Garner’s article in May 2019 Stocks & Commodities “Backtesting A Mean-Reversion Strategy In Python,” can be obtained on request via email to info@TradersEdgeSystems.com. The code is also shown below.

I backtested the author’s mean-reversion system (MeanRev.eds) using both the EDS module, which tests every trade on a one-share basis, and also via the Portfolio Manager, which performs a trading simulation.

The short side strategy showed a loss overall in the EDS test so I tested only the long side in the Portfolio Manager. I selected trades using the z-score, taking the lowest values.

For capitalization, I used max of three trades per day with a max total of 10 open trades at one time, 10% allocated to each position. I did not deduct slippage but did deduct commissions. I used a recent list of the NASDAQ 100 stocks to run the test. The equity curve and account statistics report are shown in Figure 7.

Sample Chart

FIGURE 7: AIQ. This shows the equity curve (blue line) from long-only trading the NASDAQ 100 list of stocks from 1999 to March 15, 2019. The red line is the NDX index.

!Backtesting a Mean-Reversion Strategy In Python !Author: Anthony Garner, TASC May 2019 !Coded by: Richard Denning 3/14/19 !www.TradersEdgeSystems.com 

!ABBREVIATIONS:
C is [close].

!INPUTS:
meanLen is 10.
longZmult is -1.
shortZmult is 1.
meanMult is 10.

!FORMULAS:

SMA is simpleavg(C,meanLen).
LMA is simpleavg(C,meanLen*meanMult).
STD is sqrt(variance(C,meanLen)).
zScore is (C - SMA) / STD.

!TRADING SIGNALS & EXITS:

buyLong if zScore < longZmult and SMA > LMA.
sellShort if zScore > shortZmult and SMA < LMA.
exitLong if valresult(zScore,1) < -0.5 and zScore > 0.5.
exitShort if valresult(zScore,1) > 0.5 and zScore < -0.5.

showValues if 1.

—Richard Denning
info@TradersEdgeSystems.com
for AIQ Systems

What the Hal?

Some industries are cyclical in nature.  And there is not a darned thing you – or they – can do about it.  Within those industries there are individual companies that are “leaders”, i.e., well run companies that tend to out earn other companies in that given industry and whose stock tends to outperform other companies in that industry.

Unfortunately for them, even they cannot avoid the cyclical nature of the business they are in.  Take Halliburton (ticker HAL) for example.  Halliburton is one of the world’s largest providers of products and services to the energy industry.  And they do a good job of it. Which is nice.  It does not however, release them from the binds of being a leader in a cyclical industry.

A Turning Point at Hand?

1

A quick glance at Figure 1 clearly illustrates the boom/bust nature of the performance of HAL stock.Figure 1 – Halliburton (HAL) (Courtesy AIQ TradingExpert)

Which raises an interesting question: is there a way to time any of these massive swings?  Well here is where things get a little murky.  If you are talking about “picking timing tops and bottoms with uncanny accuracy”, well, while there are plenty of ads out there claiming to be able to do just that, in reality that is not really “a thing”.  Still, there may be a way to highlight a point in time where:

*Things are really over done to the downside, and

*For a person who is not going to get crazy and “bet the ranch”, and who understands how a stop-loss order works and is willing to use one…

..there is at least one interesting possibility.

It’s involves a little-known indicator that is based on a more well-known another indicator that was developed by legendary trader Larry Williams roughly 15 or more years ago.  William’s indicator is referred to as “VixFix” and attempts to replicate a VIX-like indicator for any market.  The formula is pretty simple, as follows  (the code is from AIQ Expert Design Studio):

*hivalclose is hival([close],22).

*vixfix is (((hivalclose-[low])/hivalclose)*100)+50.

In English, it is the highest close in the last 22-periods minus the current period low, which is then divided by the highest close in the last 22-periods. The result then gets multiplied by 100 and 50 is added.

Figure 2 displays a monthly chart of HAL with William’s VixFix in the lower clip.  In a nutshell, when price declines VixFix rises and vice versa.

2

Figure 2 – HAL Monthly with William’s VixFix (Courtesy AIQ TradingExpert)

Now let’s go one more step as follows by creating an exponentially smoothed version as follows (the code is from AIQ Expert Design Studio):

*hivalclose is hival([close],22).

*vixfix is (((hivalclose-[low])/hivalclose)*100)+50. <<<Vixfix from above

*vixfixaverage is Expavg(vixfix,3).  <<<3-period exponential MA of Vixfix

*Vixfixaverageave is Expavg(vixfixaverage,7). <<<7-period exp. MA

I refer to this as Vixfixaverageave (Note to myself: get a better name) because it essentially takes an average of an average.  In English (OK, sort of), first Vixfix is calculated, then a 3-period exponential average of Vixfix is calculated (vixfixaverage) and then a 7-period exponential average of vixfixaverage is calculated to arrive at Vixfixaverageave (got that?)

3

Anyway, this indicator appears on the monthly chart for HAL that appears in Figure 3.Figure 3 – HAL with Vixaverageave (Courtesy AIQ TradingExpert)

So here is the idea:

*When Vixfixaverageave for HAL exceeds 96 it is time to start looking for a buying opportunity.

OK, that last sentence is not nearly as satisfying as one that reads “the instant the indicator reaches 96 it is an automatic buy signal and you can’t lose”.  But it is more accurate.  Previous instances of a 96+ reading for Vixfixaverageave for HAL appear in Figure 4.

4

Figure 4 – HAL with previous “buy zone” readings from Vixfixaverageave (Courtesy  AIQ TradingExpert)

Note that in previous instances, the actual bottom in price action occurred somewhere between the time the indicator first broke above 96 and the time the indicator topped out.  So, to reiterate, Vixfixaverageave is NOT a “precision timing tool”, per se.  But it may be useful in highlighting extremes.

This is potentially relevant because with one week left in May, the monthly Vixfixaverageave value is presently above 96.  This is NOT a “call to action”.  If price rallies in the next week Vixfixaverageave may still drop back below 96 by month-end.  Likewise, even if it is above 96 at the end of May – as discussed above and as highlighted in Figure 4, when the actual bottom might occur is impossible to know.

5

Let me be clear: this article is NOT purporting to say that now is the time to buy HAL.  Figure 5 displays the largest gain, the largest drawdown and the 12-month gain or loss following months when Vixfixaverageave for HAL first topped 96.  As you can see there is alot of variation and volatility.  

Figure 5 – Previous 1st reading above 96 for HAL Vixfixaverageave

So HAL may be months and/or many % points away from an actual bottom.  But the main point is that the current action of Vixfixaverageave suggests that now is the time to start paying attention.

Jay Kaeppel

Disclaimer:  The data presented herein were obtained from various third-party sources.  While I believe the data to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  The information, opinions and ideas expressed herein are for informational and educational purposes only and do not constitute and should not be construed as investment advice, an advertisement or offering of investment advisory services, or an offer to sell or a solicitation to buy any security.