Category Archives: Stocks & Commodities traders tips

Portfolio Strategy Based On Accumulation/Distribution

The AIQ code based on Domenico D’Errico’s article in the August issue of Stocks & Commodities magazine, “Portfolio Strategy Based On Accumulation/Distribution,” is shown below.

“Whether you are an individual trader or an asset manager, your main goal in reading a chart is to detect the intentions of major institutions, large operators, well-informed insiders, bankers and so on, so you can follow them. Here, we’ll build an automated stock portfolio strategy based on a cornerstone price analysis theory.”

!Portfolio Strategy Based on Accumulation/Distribution
!Author: Domenic D'Errico, TASC Aug 2018
!Coded by: Richard Denning 6/10/18
!www.TradersEdgeSystem.com
!Portfolio Strategy Based on Accumulation/Distribution
!Author: Domenic D'Errico, TASC Aug 2018
!Coded by: Richard Denning 6/10/18
!www.TradersEdgeSystem.com

!SET TO WEEKLY MODE IN PROPERTIES
!ALSO VIEW CHARTS IN WEEKLY MODE

!INPUTS:
rLen is 4.
consolFac is 75. ! in percent
adxTrigger is 30.
volRatio is 1.
volAvgLen is 4.
volDelay is 4.

!CODING ABREVIATIONS:
H is [high].
L is [low].
C is [close].
C1 is valresult(C,1).
H1 is valresult(H,1).
L1 is valresult(L,1).

!RANGE ACCUMULATION/DISTRIBUTION:
theRange is hival([high],rLen) - loval([low],rLen).
Consol if theRange < consolFac/100 * valresult(theRange,rLen).
rRatio is theRange/valresult(theRange,4)*100.

!AVERAGE TRUE RANGE ACCUMULATION/DISTRIBUTION:
avgLen is rLen * 2 - 1.	
TR  is Max(H-L,max(abs(C1-L),abs(C1-H))).
ATR  is expAvg(TR,avgLen).

ConsolATR if ATR < consolFac/100 * valresult(ATR,rLen). atrRatio is ATR / valresult(ATR,4)*100. !ADX ACCUMULATION/DISTRIBUTION: !ADX INDICATOR as defined by Wells Wilder rhigh is (H-H1). rlow is (L1-L). DMplus is iff(rhigh > 0 and rhigh > rlow, rhigh, 0).
DMminus is iff(rlow > 0 and rlow >= rhigh, rlow, 0).
AvgPlusDM is expAvg(DMplus,avgLen).
AvgMinusDM is expavg(DMminus,avgLen).           	
PlusDMI is (AvgPlusDM/ATR)*100.	
MinusDMI is AvgMinusDM/ATR*100.	
DIdiff is PlusDMI-MinusDMI. 		
Zero if PlusDMI = 0 and MinusDMI =0.
DIsum is PlusDMI+MinusDMI.
DX is iff(ZERO,100,abs(DIdiff)/DIsum*100).
ADX is ExpAvg(DX,avgLen).

ConsolADX if ADX < adxTrigger. !CODE FOR ACCUMULATIOIN/DISTRIBUTION RANGE BREAKOUT: consolOS is scanany(Consol,250) then offsettodate(month(),day(),year()). Top is highresult([high],rLen,^consolOS). Top0 is valresult(Top,^consolOS) then resetdate(). Bot is loval([low],rLen,^consolOS). AvgVol is simpleavg([volume],volAvgLen). Bot12 is valresult(Bot,12). BuyRngBO if [close] > Top
and ^consolOS <= 5 and ^consolOS >= 1
and Bot > Bot12
and valresult(AvgVol,volDelay)>volRatio*valresult(AvgVol,volAvgLen+volDelay).
EntryPrice is [close].

Sell if [close] < loval([low],rLen,1).
ExitPrice is [close].

Figure 9 shows the summary backtest results of the range accumulation breakout system using NASDAQ 100 stocks from December 2006 to June 2018. The exits differ from the author’s as follows: I used two of the built-in exits — a 20% stop-loss and a profit-protect of 40% of profits once profit reaches 10%.

Sample Chart

FIGURE 9: AIQ. Here are the summary results of a backtest using NASDAQ 100 stocks.

Figure 10 shows a color study on REGN. The yellow bars show where the range accumulation/distribution shows a consolidation.

Sample Chart

FIGURE 10: AIQ. This color study shows range consolidation (yellow bars).

—Richard Denning

info@TradersEdgeSystems.com

for AIQ Systems

A Technical Method For Rating Stocks

The AIQ code based on Markos Katsanos’ article in this issue, “A Technical Method For Rating Stocks,” is shown below.
Synopsis from Stocks & Commodities June 2018
I’s it possible to create a stock rating system using multiple indicators or other technical criteria? If so, how does it compare with analyst ratings? Investors around the world move billions of dollars every day on advice from Wall Street research analysts. Most retail investors do not have the time or can’t be bothered to read the full stock report and rely solely on the bottom line: the stock rating. They believe these ratings are reliable and base their investment decisions at least partly on the analyst buy/sell rating. But how reliable are those buy/sell ratings? In this article I will present a technical stock rating system based on five technical criteria and indicators, backtest it, and compare its performance to analyst ratings.
!A TECHNICAL METHOD FOR RATING STOCKS
!Author: Markos Katsanos, TASC June 2018
!Coded by: Richard Denning, 4/18/18
!www.TradersEdgeSystems.com

!INPUTS:
  MAP is 63. 
  STIFFMAX is 7. 
  VFIPeriod is 130. 
  MASPY is 100. 
  MADL is 100.
  SCORECRIT is 5.
  W1 is 1.
  W2 is 1.
  W3 is 1.
  W4 is 1.
  W5 is 2.
 
!VFI FORMULA: 
  COEF is 0.2.
  VCOEF is 2.5.
  Avg is ([high]+[low]+[close])/3.
  inter is ln( Avg ) - ln( Valresult( Avg, 1 ) ). 
  vinter is sqrt(variance(inter, 30 )).
  cutoff is Coef * Vinter * [Close].
  vave is Valresult(simpleavg([volume], VFIPeriod ), 1 ).
  vmax is Vave * Vcoef.
  vc is Min( [volume], VMax ).
  mf is Avg - Valresult( Avg, 1 ).
  vcp is iff(MF > Cutoff,VC,iff(MF < -Cutoff,-VC,0)).
  vfitemp is Sum(VCP , VFIPeriod ) / Vave.
  vfi is expavg(VFItemp, 3 ).

!STIFFNESS 
  ma100 is Avg. 
  CLMA if [close] < MA100.
  STIFFNESS is countof(CLMA,MAP).

!CONDITIONS:
 ! MONEY FLOW:
   COND1 is iff(VFI>0,1,0). 
 !SIMPLEAVG:
    SMA is simpleavg([close],MADL).                              
    COND2 is iff([close]>SMA,1,0).  
 !SIMPLEAVG DIRECTION:                       
    COND3 is iff(SMA>valresult(SMA,4),1,0).  
!STIFFNESS:                          
    COND4 is iff(STIFFNESS<= STIFFMAX,1,0).  
!MARKET DIRECTION:
    SPY is TickerUDF("SPY",[close]).
    COND5 is iff(EXPAVG(SPY,MASPY)>= 
 valresult(EXPAVG(SPY,MASPY),2),1,0).            

SCORE is  W1*COND1+W2*COND2+W3*COND3+
   W4*COND4+W5*COND5.

 buy if Score>=SCORECRIT and hasdatafor(300)>=268. 
Figure 11 shows the summary results of a backtest using NASDAQ 100 stocks during a generally bullish period from April 2009 to April 2018. Figure 12 shows the backtest using the same list of NASDAQ 100 stocks during a period that had two bear markets (April 1999 to April 2009). The average results are similar except that there are fewer trades during the period that contained the two bear markets. Both backtests use a fixed 21-bar exit.
Sample Chart

FIGURE 11: AIQ, BULL MARKET. Here are the summary results of a backtest using NASDAQ 100 stocks during a generally bullish period from April 2009 to April 2018.
Sample Chart

FIGURE 12: AIQ, BEAR MARKET. Here are the summary results of a backtest using NASDAQ 100 stocks during a period from April 1999 to April 2009 that contained two bear markets.
—Richard Denning info@TradersEdgeSystems.com for AIQ Systems

Weekly & Daily Percentage Price Oscillator

The AIQ code based on Vitali Apirine’s article in Stocks & Commodities issue, “Weekly & Daily Percentage Price Oscillator,”  Modifying a traditional indicator can make you look at a chart differently. You can compare indexes, look at price movements during extended periods of time, and make trading decisions based on your observations is provided here:

!WEEKLY & DAILY PPO
!Author: Vitali Apirine, TASC Feb 2018
!Coded by: Richard Denning 12/17/17
!www.TradersEdgeSystems.com

!INPUTS:
S is 12.
L is 26.

EMA1 is expavg([Close],S).
EMA2 is expavg([Close],L).
EMA3 is expavg([Close],S*5).
EMA4 is expavg([Close],L*5).
DM is (EMA1 - EMA2)/EMA4*100.
WM is (EMA3 - EMA4)/EMA4*100.
WD_PPO is WM + DM.
Figure below shows the daily and weekly PPO indicator on a chart of the Nasdaq 100 index (NDX) from 2015 to 2017.

 

Sample Chart

 Here, the daily & weekly PPO is displayed on a chart of the NDX.

 

 

—Richard Denning info@TradersEdgeSystems.com for AIQ Systems

	

Weekly and Daily MACD

The AIQ code based on Vitali Apirine’s article in December 2017 issue of Stocks and Commodities magazine, “Weekly & Daily MACD,” is provided below.
The moving average convergence/divergence oscillator (MACD), developed by Gerald Appel, is one of the more popular technical analysis indicators. The MACD is typically used on a single timeframe, but what if we looked at two timeframes on one chart?

Traders can look for relative daily MACD line crossovers, weekly and daily centerline crossovers, and divergences to generate trading signals. 
Figure 5 shows the daily & weekly MACD indicator on a chart of Apple Inc. (AAPL) during 2016 and 2017, when there was a change from a downtrend to an uptrend.
Sample Chart

FIGURE 5: AIQ. Here is an example of the daily & weekly MACD on a chart of AAPL.
The code and EDS file can be downloaded from http://aiqsystems.com/dailyweeklyMACD.EDS, or copied here:
!WEEKLY & DAILY MACD
!Author: Vitali Apirine, TASC Dec 2017
!Coded by: Richard Denning 10/13/17
!www.TradersEdgeSystems.com

!INPUTS:
S is 12.
L is 25.

EMA1 is expavg([Close],S).
EMA2 is expavg([Close],L).
EMA3 is expavg([Close],S*5).
EMA4 is expavg([Close],L*5).
MACD is EMA1 - EMA2.
MACDW is EMA3 - EMA4.
rdMACD is MACD + MACDW.
—Richard Denning
info@TradersEdgeSystems.com
for AIQ Systems

System Development Using Artificial Intelligence

The AIQ code based on Domenico D’Errico and Giovanni Trombetta’s article in August 2017 Stock & Commodities issue, “System Development Using Artificial Intelligence,” is shown here. You can also download the EDS file from here

Are humans or computers better at trading? This question has been around on many fronts since the era of punch cards, and as technology advances, you question whether machines have limits. It’s the same with trading, and here’s an algorithm that may shed some light on which performs better…

!ARTIFICAL INTELLIGENCE FOR SYSTEM DEVELOPMENT
!Authors: Domenico D'Errico & Giovanni Trombetta, TASC August 2017
!Coded by: Richard Denning, 6/08/2017
!www.TradersEdgeSystems.com

!INPUTS:
O is [open].
C is [close].
H is [high].
L is [low].
exitBars is 8.
exitBarsP is 6.
enterGap is -0.08.

!CODE:
AvgP is (O+C+H+L)/4.
MedP is (H+L)/2.
MedB is (O+C)/2.

AvgP1 is valresult(AvgP,1).
AvgP2 is valresult(AvgP,2).
AvgP3 is valresult(AvgP,3).

MedP1 is valresult(MedP,1).
MedP2 is valresult(MedP,2).
MedP3 is valresult(MedP,3).
MedP4 is valresult(MedP,4).

MedB1 is valresult(MedB,1).
MedB2 is valresult(MedB,2).
MedB3 is valresult(MedB,3).
MedB4 is valresult(MedB,4).

!ENTRY & EXIT RULESl
Gandalf if 
  (AvgP1exitBars-1)
 or ({position days}>=exitBars-1)
 or ({position days}>=exitBarsP-1 and (C-{position entry price}>0)).

EntryPr is min(val([low],1) + enterGap,[open]).

Buy if Gandalf and [low] <= EntryPr.

See Figure 10 for how to set up the pricing in a backtest.
Sample Chart

FIGURE 10: AIQ. This shows the EDS backtest settings for entry pricing.
—Richard Denning
info@TradersEdgeSystems.com
for AIQ Systems

Detecting Swings

The AIQ code based on Domenico D’Errico’s article in the May 2017 issue of Stoks Commodities, “Detecting Swings,” is provided below.

I tested the author’s four systems using the NASDAQ 100 list of stocks on weekly bars, as did the author, from 3/16/2005 through 3/14/2017. Figure 7 shows the comparative metrics of the four systems using the four-week exit. The results were quite different than the author’s, probably due to a different test portfolio and also a 10-year test period rather than the author’s 20-year period. In addition, my test results show longs only, whereas the author’s results are the average of both the longs and shorts.

Sample Chart
 
FIGURE 7: AIQ. As coded in EDS, this shows the metrics for the author’s four systems run on NASDAQ 100 stocks (weekly bar data) over the period 3/16/2005 to 3/14/2007.

The Bollinger Band (Buy2) system showed the worst results, whereas the author’s results showed the Bollinger Band system as the best. The pivot system (Buy1) showed the best results, whereas the author’s results showed the pivot system as the worst. I am not showing here the comparative test results for the Sell1 thru Sell4 rules, as all showed an average loss over this test period.

!DECTECTING SWINGS
!Author: Domenico D'Errico, TASC May 2017
!Coded by: Richard Denning, 3/15/17
!www.TradersEdgeSystems.com

!Set to WEEKLY in properties

Low is  [low].
Low1  is valresult(Low,1).
Low2  is valresult(Low,2). 
High is [high].
High1  is valresult(High,1).
High2  is valresult(High,2). 
PivotLow if Low1 < Low2  and Low1 < Low.
PivotHigh if High1 > High2  and High1 > High.

Buy1 if  PivotLow.  
Sell1 if  PivotHigh.    

!Set parameter for bollinger bands to 12 with 2 sigma (weekly) in charts:
Buy2 if [close] > [Lower BB] and valrule([close] <= [Lower BB],1).
Sell2 if [close] < [Upper BB] and valrule([close] >= [Upper BB],1).

!Set parameter for Wilder RSI to 5 (weekly) in charts:
Buy3 if [RSI Wilder] > 40 and valrule([RSI Wilder] <= 40,1).
Sell3 if [RSI Wilder] < 60 and valrule([RSI Wilder] >= 60,1).

Buy4 if [RSI Wilder] < 40  And Low > Low1.
Sell4 if [RSI Wilder] > 60  And High < High1.    

Exit if {position days} >= 4.
—Richard Denning
info@TradersEdgeSystems.com
for AIQ Systems
Editor note: The code and EDS file can be downloaded from http://aiqsystems.com/Detecting_Swings_TASC_May_2017.EDS

Exponential Standard Deviation Bands

The AIQ code based on Vitali Apirine’s article in the 2017 issue of Stocks & Commodities magazine, “Exponential Standard Deviation Bands”

Editor note: “Author Vitali Apirine presented a method intended to help traders see volatility while a stock is trending. These bands, while similar to Bollinger Bands, are calculated using exponential moving averages rather than simple moving averages. Like Bollinger Bands, they widen when volatility increases and narrow as volatility decreases. He suggests that the indicator can be used as a confirming indication along with other indicators such as the ADX. Here’s an AIQ Chart with the Upper, Lower and Middle Exponential SD added as custom indicators.”

 

 

To compare the exponential bands to Bollinger Bands, I created a trend-following trading system that trades long only according to the following rules:
  1. Buy when there is an uptrend and the close crosses over the upper band. An uptrend is in place when the middle band is higher than it was one bar ago.
  2. Sell when the low is less than the lower band.
Figure 8 shows the summary test results for taking all signals from the Bollinger Band system run on NASDAQ 100 stocks over the period 12/9/2000 to 12/09/2016. Figure 9 shows the summary test results for taking all signals from the exponential band system on NASDAQ 100 stocks over the same period. The exponential band system improved the average profit per trade while reducing the total number of trades.

Sample Chart

FIGURE 8: AIQ. Here are summary test results for taking all signals from the Bollinger Band system run on NASDAQ 100 stocks over the period 12/9/2000 to 12/09/2016.

Sample Chart

FIGURE 9: AIQ. Here are summary test results for taking all signals from the exponential band system run on NASDAQ 100 stocks over the period 12/9/2000 to 12/09/2016.
The EDS file can be downloaded from http://aiqsystems.com/EDS/Exponential_Standard_Deviation_Bands.EDS 
and is also shown here:
!Exponential Standard Deviation Bands
!Author: Vitali Apirine, TASC February 2017
!Coded by: Richard Denning 12/11/2016
!www.TradersEdgeSystems.com!INPUT:
xlen is 20.
numSD is 2.

!INDICATOR CODE:
ExpAvg is expavg([close],xlen).
Dev is [close] – ExpAvg.
DevSqr is Dev*Dev.
SumSqr is sum(DevSqr,xlen).
AvgSumSqr is SumSqr / xlen.
ExpSD is sqrt(AvgSumSqr).

!UPPER EXPONENTIAL SD BAND:
UpExpSD is ExpAvg + numSD*ExpSD.  !PLOT ON CHART

!LOWER EXPONENTIAL SD BAND:
DnExpSD is ExpAvg – numSD*ExpSD.   !PLOT ON CHART

!MIDDLE EXPONENTIAL SD BAND:
MidExpSD is ExpAvg.

!BOLLINGER BANDS FOR COMPARISON:
DnBB is [Lower BB].  !Lower Bollinger Band
UpBB is [Upper BB].  !Upper Bollinger Band
MidBB is simpleavg([close],xlen). !Middle Bollinger Band
!REPORT RULE TO DISPLAY VALUES:
ShowValures if 1.

!TRADING SYSTEM USING EXPPONENTIAL SD BANDS:
UpTrend if MidExpSD > valresult(MidExpSD,1).
BreakUp if [close] > UpExpSD.
BuyExpSD if UpTrend and BreakUp and valrule(Breakup=0,1).
ExitExpSD if [Low] < DnExpSD.  ! or UpTrend=0.

!TRADING SYSTEM USING BOLLINGER BANDS:
UpTrendBB if MidBB > valresult(MidBB,1).
BreakUpBB if [close] > UpBB.
BuyBB if UpTrendBB and BreakUpBB and valrule(BreakupBB=0,1).
ExitBB if [Low] < DnBB.  ! or UpTrend=0.

—Richard Denning
info@TradersEdgeSystems.com
for AIQ Systems

Zero In On The MACD

The AIQ code based on Barbara Star’s article in May issue of Stocks and Commodities “Zero In On The MACD,” is provided at www.TradersEdgeSystems.com/traderstips.htm, and is also shown below.
Sample Chart
FIGURE 7: AIQ. Here is a sample chart of VIAB with MACDhist, the color bars, and the 34- and 55-bar EMAs.
Figure 7 shows the MACD histogram on a chart of Viacom (VIAB) with the color bars and the 34- and 55-bar exponential moving averages (EMA). Note that I did not code the weighted moving average (WMA) but substituted the EMA for the WMA. I chose to view the chart of VIAB by running the EDS “Zero MACD.eds” on 3/14/2016 and examining the alert messages on the report “List.” VIAB is the only one on that date that showed a cross up on the MACDhist (see Figure 8 for a look at part of this report for 3/14/2016).
Sample Chart
FIGURE 8: AIQ. This shows part of the EDS custom report “List” that shows the MACDhist values on 3/14/2016, the color status, and any alerts that were generated for that day.
! ZERO IN ON THE MACD

! Author: Barbara Star, TASC May 2016

! Coded by: Richard Denning 3/14/16

! www.TradersEdgeSystems.com



! INPUTS:

macd1  is  12.

macd2  is  26.

macdSig is  1.



! INDICATORS:

emaST  is expavg([Close],macd1).

emaLT  is expavg([Close],macd2).

MACD  is emaST - emaLT.  ! MACD line

SigMACD is expavg(MACD,macdSig). ! MACD Signal line

MACDosc is MACD - SigMACD. ! MACD Oscillator



HD if hasdatafor(macd2) = macd2.

MACDhist is MACD.                                 ! plot as historigram

MACDblue if MACDhist > 0.  ! use these rules to color MACDhist

MACDred  if MACDhist < 0.  ! use these rules to color MACDhist

MACDcolor is iff(MACDblue and HD,"Blue",iff(MACDred and HD,"Red","White")). !for report list

List if 1.



!ALERTS:

EMA1 is expavg([close],34).

EMA2 is expavg([close],55).

xupEMA1 if [close] > EMA1 and valrule([close] < EMA1,1).

xdnEMA1 if [close] < EMA1 and valrule([close] > EMA1,1).

xupEMA2 if [close] > EMA2 and valrule([close] < EMA2,1).

xdnEMA2 if [close] < EMA2 and valrule([close] > EMA2,1).

xupMACD if MACDhist > 0 and valrule(MACDhist < 0,1).

xdnMACD if MACDhist < 0 and valrule(MACDhist > 0,1).

UpAlerts is iff(xupEMA1,"xupEMA1",iff(xupEMA2,"xupEMA2",iff(xupMACD,"xupMACD"," "))).

DnAlerts is iff(xdnEMA1,"xdnEMA1",iff(xdnEMA2,"xdnEMA2",iff(xdnMACD,"xdnMACD"," "))).

The code and EDS file can be downloaded from www.TradersEdgeSystems.com/traderstips.htm.

Trading Gap Reversals

The AIQ code based on Ken Calhoun’s article in April 2016 issue of Stock & Commodities Trading Gap Reversals”, is provided below. 
AIQ has also posted the EDS file at “ is provided for downloading at 
Save this file to your/wintes32/EDS Strategies folder.
Since I mainly work with daily bar strategies, I wanted to test the gap-down concept on a daily bar trading system rather than on one-minute bars. I set up a system that buys after a stock has gapped down at least 10% in the last two days and then trades above the high of the gap-down bar. The entry is then at the close of that bar. For exits, I used the built-in exit, the profit-protect exit set at 80% once profit reaches 3% or more combined with a stop-loss using the low of the gap-down bar and also a time exit set to five bars. 
I then ran this system on the NASDAQ 100 list of stocks in the EDS backtester over the period 12/31/1999 to 1/11/2016 (Figure 7). The system generated 303 trades with an average profit of 1.09% per trade with a reward-to-risk ratio of 1.35. Slippage and commissions have not been deducted from these results.
Sample Chart
FIGURE 7: AIQ. This shows the EDS test results for the example system.
Again, the code and EDS file can be downloaded from www.TradersEdgeSystems.com/traderstips.htm, and is also shown below.
!TRADING GAP REVERSALS
!Author: Ken Calhoun, TASC April 2016
!Coded by: Richard Denning 2/1/2016
!www.TradersEdgeSystems.com

!INPUTS:
GapSize is 10.
GapLookBack is 5.
MaxBars is 5.

!CODING ABBREVIATIONS:
H is [high].
C is [close].
C1 is val([close],1).
L is [low].
O is [open].

GapD is (O / C1 - 1) * 100.
GapOS is scanany(GapD < -GapSize,GapLookBack) <> nodate()
  then offsettodate(month(),day(),year()).
Hgap  is valresult(H,^GapOS).
Lgap  is valresult(L,^GapOS).
SU if  scanany(GapD < -GapSize,GapLookBack).
SU1 if  scanany(GapD < -GapSize,GapLookBack,1).
SU2 if  scanany(GapD < -GapSize,GapLookBack,2).
LE if ((SU1 then resetdate()) or (SU2 then resetdate())) 
 and H > Hgap.
ExitLong if {position days} > maxBars
 or C < Lgap.
EntryPr is max(O,Hgap).
List  if C > 0.
—Richard Denning

Back to Basics with MACD (Part 2)

In this article I detailed one relatively “simple” approach to using the MACD indicator to identify potentially bullish opportunities.  In this piece we will look at one to actually put those signals to use.
The Limited Risk Call Option
One possibility upon generating a bullish signal as described in the last article is to buy shares of the stock/ETF/index/etc in question.  Not a thing wrong with that.  But there is a less expensive alternative.
Figure 1 reproduces Figure 1 from the last piece showing ticker XLF.  Let’s look at the signal generated on 2/12/16.
1Figure 1 – Ticker XLF (Courtesy AIQ TradingExpert)
One alternative that I like is to use the “Percent to Double” routine at www.OptionsAnalysis.com to find an inexpensive call option that has lot of upside potential.  The input screen with a few key input selections highlighted appears in Figure 1a (if it looks intimidating please note that a reusable set of criteria can be captured in a “Saved Wizard”, which appear towards the lower right of of Figure 1a.  Once a set of criteria is saved it can be reused by simply clicking on the Wizard name and clicking “Load”.)
NOTE: My own personal preference is to consider options that have at least 45 days left until expiration (as time decay can become a very negative factor as option expiration draws closer).

1a

Figure 1a – Percent to Double Inputs (Courtesy www.OptionsAnalysis.com)

Figure 1b displays the output screen.
NOTE: For my own purposes I like to see a Delta of at least 40 for the option I might consider buying (nothing “scientific” here.  It is just that the lower the Delta the further out-of-the-money the option strike price is. I prefer to buy a strike price that is not too far from the current price of the stock; hence I look for a Delta of 40 or higher).  With XLF trading at $20.49, in Figure 1b I have highlighted the 2nd choice on the list – the April 21 call – which has a delta of 43.1bFigure 1b – Percent to Double Output (Courtesy www.OptionsAnalysis.com)
So a trader now has two alternatives:
*Buy 2 Apr 21 strike price XLF calls for $70 apiece ($140 total cost; 86 total deltas)
*Buy 86 shares of XLF at $20.49 apiece ($1,760 total cost, 86 total deltas)
Figure 1c displays the particulars for buying a 2-lot of the April 21 call for a total cost of $140.1cFigure 1c – XLF Apr 21 call (Courtesy www.OptionsAnalysis.com)
By 3/18 the shares had gained 11% and the Apr 21 call had gained 143%.  See Figure 1d.1dFigure 1d – XLF Apr 21 call (Courtesy www.OptionsAnalysis.com)
Summary
Obviously not every trade works out as well as this one.  Still, the key things to remember are:
*The option trade cost $140 instead of $1760
*The worst case scenario was a loss of $140.
Something to think about.
Chief Market Analyst at JayOnTheMarkets.com and TradingExpert Pro client