Your WinWay TradingExpert Pro service includes access to end of day data on UK and US stocks and streaming data on US stocks only. Streaming data on UK stocks will soon be available for an additional exchange fee charge.
Open EDS from the Charts Tool Bar. Open the EDS scan that you wish to run on UK stocks. Click on File, Properties and in the Tickers in List box select UKALL. click OK. You will need to change these properties on any EDS scan you wish to run on UK stocks.
Open the Reports from the Charts Tool Bar. From the Reports menu, select Global Properties. Change the Stock and Group/Sector areas to UKALL in the Daily Selection Criteria tab. Repeat for the Weekly Selection Criteria tab if desired. Click OK. When you next download data and/or generate reports, the reports will reflect the changes.
| System | Entry rule | Exit rule | Entry price formula | Exit price formula |
| 2 Param-Long | Buy2P | ExitBuy2P | Buy2Ppr | ExitBuy2Ppr |
| 2 Param-Short | Sell2P | ExitSell2P | Sell2Ppr | ExitSell2Ppr |
| 4 Param-Long | Buy4P | ExitBuy4P | Buy4Ppr | ExitBuy4Ppr |
| 4 Param-Short | Sell4P | ExitSell4P | ell4Ppr | ExitSell4Ppr |
| 6 Param-Long | Buy6P | ExitBuy6P | Buy6Ppr | ExitBuy6Ppr |
| 6 Param-Short | Sell6P | ExitSell6P | Sell6Ppr | ExitSell6Ppr |
| 8 Param-Long | Buy8P | ExitBuy8P | Buy8Ppr | ExitBuy8Ppr |
| 8 Param-Short | Sell8P | ExitSell8P | Sell8Ppr | ExitSell8Ppr |
| 9 Param-Long | Buy9P | ExitBuy9P | Buy9Ppr | ExitBuy9Ppr |
| 9 Param-Short | Sell9P | ExitSell9P | Sell9Ppr | ExitSell9Ppr |
!THE DEGREE OF COMPLEXITY
!Author: Oscar G. Cagigas, TASC Feb 2014
!Coded by Richard Denning 12/7/13
!www.TradersEdgeSystems.com
! CODING ABBREVIATIONS:
C is [close].
H is [high].
L is [low].
O is [open].
PEP is {position entry price}.
PD is {position days}.
! PARAMETERS:
donLen1 is 40.
donLen2 is 15.
atrLen is 20.
atrMult is 1.0.
atrStop is 4.0.
maLen1 is 10.
maLen2 is 100.
rsiLen is 14.
rsiUpper is 70.
rsiLower is 30.
atrMult2 is 0.6.
minMov is 0.01.
!------------------------------------------------------------------
! AVERAGE TRUE RANGE (AS DEFINED BY WELLS WILDER)
WWE is 2*(atrLen-1).
TR is Max(H - L,max(abs(valresult(C,1) - L),abs(valresult(C,1)- H))).
ATR is expAvg(TR,WWE).
ATR1 is valresult(ATR,1).
!------------------------------------------------------------------
!! RSI WILDER
!To convert Wilder Averaging to Exponential Averaging use this formula:
!ExponentialPeriods = 2 * WilderPeriod - 1.
U is C-valresult(C,1).
D is valresult(C,1)-C.
eLen is 2 * rsiLen - 1.
AvgU is ExpAvg(iff(U>0,U,0),eLen).
AvgD is ExpAvg(iff(D>=0,D,0),eLen).
rsi is 100-(100/(1+(AvgU/AvgD))).
!----------------------------------------------------------------
!BASIC SYSTEM 2P (2 parameters):
HHdL1 is highresult(H,donLen1,1).
HHdL2 is highresult(H,donLen2,1).
LLdL1 is lowresult(L,donLen1,1).
LLdL2 is lowresult(L,donLen2,1).
Buy2P if H > HHdL1.
ExitBuy2P if L < LLdL2.
Sell2P if L < LLdL1.
ExitSell2P if H > HHdL2.
Buy2Ppr is max(O,HHdL1 + minMov).
ExitBuy2Ppr is iff(ExitBuy2P,min(O,LLdL2 - minMov),C).
Sell2Ppr is min(O,LLdL1 - minMov).
ExitSell2Ppr is max(O,HHdL2 + minMov).
!-----------------------------------------------------------------
!FOUR PARAMETER SYSTEM 4P:
Buy4P if H > HHdL1 and valrule(TR < atrMult*ATR,1).
EB4P1 if L < LLdL2.
EB4Pval is PEP - atrStop*valresult(ATR,PD).
EB4P2 if L < valresult(EB4Pval,1).
ExitBuy4P if EB4P1 or EB4P2.
Sell4P if L < LLdL1 and valrule(TR < atrMult*ATR,1).
ES4Pval is PEP + atrStop*valresult(ATR,PD) .
ES4P1 if H > HHdL2.
ES4P2 if H > valresult(ES4Pval,1).
ExitSell4P if ES4P1 or ES4P2.
Buy4Ppr is max(O,HHdL1 + minMov).
ExitBuy4Ppr is iff(EB4P1,min(O,LLdL2 - minMov),
iff(EB4P2,min(O,valresult(EB4Pval - minMov,1)),-99)).
Sell4Ppr is min(O,LLdL1 - minMov).
ExitSell4Ppr is iff(ES4P1,max(O,HHdL2 + minMov),
iff(ES4P2,max(O,valresult(ES4Pval + minMov,1)),-99)).
!----------------------------------------------------------------
!SIX PARAMETER SYSTEM 6P:
SMA1 is simpleavg(C,maLen1).
SMA2 is simpleavg(C,maLen2).
Buy6P if H > HHdL1 and valrule(TR < atrMult*ATR,1)
and valrule(SMA1 > SMA2,1).
EB6P1 if L < LLdL2.
EB6Pval is PEP - atrStop*valresult(ATR,PD).
EB6P2 if L < valresult(EB6Pval,1).
ExitBuy6P if EB6P1 or EB6P2.
Sell6P if L < LLdL1 and valrule(TR < atrMult*ATR,1)
and valrule(SMA1 < SMA2,1).
ES6Pval is PEP + atrStop*valresult(ATR,PD) .
ES6P1 if H > HHdL2.
ES6P2 if H > valresult(ES6Pval,1).
ExitSell6P if ES6P1 or ES6P2.
Buy6Ppr is max(O,HHdL1 + minMov).
ExitBuy6Ppr is iff(EB6P1,min(O,LLdL2 - minMov),
iff(EB6P2,min(O,valresult(EB6Pval - minMov,1)),-99)).
Sell6Ppr is min(O,LLdL1 - minMov).
ExitSell6Ppr is iff(ES6P1,max(O,HHdL2 + minMov),
iff(ES6P2,max(O,valresult(ES6Pval + minMov,1)),-99)).
!---------------------------------------------------------------
!EIGHT PARAMETER SYSTEM 8P:
Buy8P if H > HHdL1 and valrule(TR < atrMult*ATR,1)
and valrule(SMA1 > SMA2,1) and valrule(RSI >= rsiUpper,1).
EB8P1 if L < LLdL2.
EB8Pval is PEP - atrStop*valresult(ATR,PD).
EB8P2 if L < valresult(EB8Pval,1).
ExitBuy8P if EB8P1 or EB8P2.
Sell8P if L < LLdL1 and valrule(TR < atrMult*ATR,1)
and valrule(SMA1 < SMA2,1) and valrule(RSI <= rsiLower,1).
ES8Pval is PEP + atrStop*valresult(ATR,PD) .
ES8P1 if H > HHdL2.
ES8P2 if H > valresult(ES8Pval,1).
ExitSell8P if ES8P1 or ES8P2.
Buy8Ppr is max(O,HHdL1 + minMov).
ExitBuy8Ppr is iff(EB8P1,min(O,LLdL2 - minMov),
iff(EB8P2,min(O,valresult(EB8Pval - minMov,1)),-99)).
Sell8Ppr is min(O,LLdL1 - minMov).
ExitSell8Ppr is iff(ES8P1,max(O,HHdL2 + minMov),
iff(ES8P2,max(O,valresult(ES8Pval + minMov,1)),-99)).
!----------------------------------------------------------------
!NINE PARAMETER SYSTEM 9P:
Buy9P if H > HHdL1 and valrule(TR < atrMult*ATR,1)
and valrule(SMA1 > SMA2,1) and valrule(RSI >= rsiUpper,1)
and valrule(TR > atrmult2*ATR,1) .
EB9P1 if L < LLdL2.
EB9Pval is PEP - atrStop*valresult(ATR,PD).
EB9P2 if L < valresult(EB9Pval,1).
ExitBuy9P if EB9P1 or EB9P2.
Sell9P if L < LLdL1 and valrule(TR < atrMult*ATR,1)
and valrule(SMA1 < SMA2,1) and valrule(RSI <= rsiLower,1)
and valrule(TR > atrmult2*ATR,1) .
ES9Pval is PEP + atrStop*valresult(ATR,PD) .
ES9P1 if H > HHdL2.
ES9P2 if H > valresult(ES9Pval,1).
ExitSell9P if ES9P1 or ES9P2.
Buy9Ppr is max(O,HHdL1 + minMov).
ExitBuy9Ppr is iff(EB9P1,min(O,LLdL2 - minMov),
iff(EB9P2,min(O,valresult(EB9Pval - minMov,1)),-99)).
Sell9Ppr is min(O,LLdL1 - minMov).
ExitSell9Ppr is iff(ES9P1,max(O,HHdL2 + minMov),
iff(ES9P2,max(O,valresult(ES9Pval + minMov,1)),-99)).
!----------------------------------------------------------------
Hi, my name is Jay and I am a Seasonalaholic.
Now typically when someone confesses to being an “aholic” of some sort or another it because they recognize they have a problem and wish to correct it. That’s not the case here. In fact the “support” group that I belong to is not “Seasonalaholics Anonymous” but rather “Seasonalaholics Unanimous!” (OK, in the interest of full disclosure, so far I am the only member and yes, the monthly meetings aren’t terribly lively, but I digress).
Still I can’t help but think there are others out there who might join someday – especially after they consider things like the seasonal tendencies for retailing stocks. To whit: what would have happened had an investor invested in Fidelity Select Sector Retailing fund (ticker FSRPX):
-During the months of February, March, October and November
-And then earned 1% of annualized interest while out of the market the other 8 months.
The answer is contained in Figure 1 which displays the growth of $1,000 invested as described above.
Figure 1 – Growth of $1,000 invested in FSRPX during February, March, October, November (blue line) versus buying and holding the S&P 500 red line) since January 1988.Now it is pretty impossible to not notice the, ahem, “slight drawdown” experienced during the October, November 2008 period. Still, despite the fact that I have tried very hard scrub that particular time period from my memory bank, I still have some vague recollection that virtually no sector of the stock market was left unscathed during that period. And the rebound has been pretty nice.
So is this really a viable strategy? Well, under the category of “Everything is Relative”, Figure 2 displays the year-by-year performance of this “system” versus buying and holding the SP 500.
| System | SP 500 | System | SP 500 | ||
| Annual % | Annual % | Difference |
$1,000
|
$1,000
|
|
|
1988
|
18.6
|
12.4
|
6.2
|
1,186
|
1,124
|
|
1989
|
(1.0)
|
27.3
|
(28.2)
|
1,174
|
1,430
|
|
1990
|
21.3
|
(6.6)
|
27.8
|
1,424
|
1,336
|
|
1991
|
16.2
|
26.3
|
(10.1)
|
1,654
|
1,688
|
|
1992
|
20.4
|
4.5
|
15.9
|
1,992
|
1,763
|
|
1993
|
6.2
|
7.1
|
(0.9)
|
2,115
|
1,888
|
|
1994
|
(1.5)
|
(1.5)
|
0.0
|
2,083
|
1,859
|
|
1995
|
2.3
|
34.1
|
(31.8)
|
2,131
|
2,493
|
|
1996
|
17.4
|
20.3
|
(2.9)
|
2,500
|
2,998
|
|
1997
|
11.9
|
31.0
|
(19.1)
|
2,798
|
3,927
|
|
1998
|
40.1
|
26.7
|
13.4
|
3,919
|
4,975
|
|
1999
|
10.8
|
19.5
|
(8.7)
|
4,344
|
5,946
|
|
2000
|
8.5
|
(10.1)
|
18.7
|
4,714
|
5,343
|
|
2001
|
3.1
|
(13.0)
|
16.1
|
4,859
|
4,646
|
|
2002
|
12.8
|
(23.4)
|
36.2
|
5,480
|
3,561
|
|
2003
|
9.1
|
26.4
|
(17.3)
|
5,977
|
4,500
|
|
2004
|
12.8
|
9.0
|
3.8
|
6,744
|
4,905
|
|
2005
|
8.5
|
3.0
|
5.5
|
7,316
|
5,052
|
|
2006
|
9.2
|
13.6
|
(4.4)
|
7,991
|
5,740
|
|
2007
|
(2.4)
|
3.5
|
(6.0)
|
7,797
|
5,943
|
|
2008
|
(32.0)
|
(38.5)
|
6.5
|
5,303
|
3,656
|
|
2009
|
23.7
|
23.5
|
0.2
|
6,559
|
4,513
|
|
2010
|
26.0
|
12.8
|
13.2
|
8,263
|
5,090
|
|
2011
|
13.2
|
(0.0)
|
13.2
|
9,355
|
5,090
|
|
2012
|
17.3
|
13.4
|
3.9
|
10,976
|
5,772
|
|
2013
|
10.7
|
29.6
|
(18.9)
|
12,155
|
7,481
|
| Average |
10.9
|
9.6
|
1.3
|
+1,115% | 648% |
| StdDev |
12.8
|
17.9
|
|||
| Ave/SD |
0.849
|
0.540
|
Summary
The difference in the average annual return is not large (+10.9% for the system versus +9.6% for the S&P 500). But this difference adds up over time. Since January 1988 the system has gained +1,115% versus + 648% for the S&P 500 (while only being in the market 33% of the time. The true “numbers geeks” will notice that the standard deviation of annual returns for the system is only 2/3rds as large as that for the S&P 500 – i.e., much less volatility).
So I ask again, is this really a viable strategy? Perhaps. But the truth is that it can get a whole lot better – as I will detail the next time I write.
Jay Kaeppel
There are a virtually unlimited number of ways to play the financial markets. This is especially true in the area of options trading, where a bullish trader can pick from at least at a dozen different strategies (buy call, buy a bull call spread, sell a bull put spread, collar, out-of-the-money calendar spread, etc., etc.).
At some point it can all become a bit overwhelming to the quote, unquote, “average investor.” So sometimes the place to start is, well, anywhere, so long as that anywhere has a beginning and an end and a logical progression to it. What does that mean? It means I am going to walk through “one way to play.” I make no claim that it is the “best” way, or even a “great” way. But that’s OK because the purpose here is not for you to rush out and start trading with it, but rather to stimulate your own thinking on the subject. In other words, hopefully in reading this a “light” will go on for you in regards to your own trading. So here goes.
Jay’s “Light” Option Trading Strategy
This strategy involves a set of steps designed to generate a bullish option trade based on a logical set of criteria. For this strategy we will look for a couple of things:
1. A “catalyst” to tell us when to buy call options.
2. Stocks that enjoy good option trading volume and tight bid-ask spread.
3. Stocks that are performing well overall.
4. Stocks that have experienced a recent pullback and may now be due for a bounce.
#1. The “Catalyst”
We will look for ticker SPY to be above its 200-day moving and for the 3-day RSI to drop to 20 or below and then reverse to the upside. Figure 1 displays a number of such signals.
Figure 1 – “Catalyst” Buy Signals (Courtesy AIQ TradingExpert)
#2. Stocks with good option volume and tight bid/ask spreads.
In Figure 2 we see the “Stock List Filter” report from www.OptionsAnalysis.com. This list contains 493 stocks that trade at least 1,000 options a day and those options have an average bid/ask spread of less than 2% (only the top part of the list is visible in Figure 2).
Figure 2 – Stocks with good option volume and tight bid/ask spreads (Courtesy: www.OptionsAnalysis.com)
#3. Stocks that are performing well overall
Next we take the stocks shown in Figure 2 and run them through the “Channel Finder” routine in www.OptionsAnalysis.com. We will look for the top 100 stocks based on the strength of their “Up Channel”. We overwrite “My Stock List” with just those 100 stocks. The output list appears in Figure 3.
In Figure 4 we see ticker SFUN with a very strong recent Up Channel
Figure 4 – Ticker SFUN with Up Channel (Courtesy: www.OptionsAnalysis.com)
#4. Stocks that have experienced a “pullback”
Lastly, we will look through the 100 stocks still on our list for those that have experienced a 3-day RSI of 35 or less within the past 5 trading days. As you can see in Figure 5, only 19 stocks now remain for consideration.
Figure 5 – Stocks that have had a 3-day RSI reading of 35 or less in past 5 days (Courtesy: www.OptionsAnalysis.com)
The Next Step: Finding a Trade
From here a trader can use whatever bullish option strategy they prefer to find a potentially profitable trade among these 19 stocks. For illustrative purposes we will:
-Consider buying calls with 45 to 145 days left until expiration and Open Interest of at least 100 contracts.
-Initially sort the trades by a measure known as “Percent to Double”, as in “what type of percentage move does the underlying stock have to make in order for the option to double in price?”
-Once we get that list e will sort by “Highest Gamma” in an effort to get the most “bang for the buck.”
We see the output list in Figure 6.
The top trade listed in to buy the MRVL Feb 2014 14 Call @ $0.73 (or $73 per option)
In Figure 7, we see that MRVL rallied nicely within a few weeks from 13.61 to 15.81.
Figure 7 – MRVL rallies (Courtesy: www.OptionsAnalysis.com)
In Figure 8 we see that the Feb 14 call option gained 169.9%.
Figure 8 – MRVL 14 call rallies sharply (Courtesy: www.OptionsAnalysis.com)
Of course there is also the whole topic of what to do with this trade: close it, sell some, adjust it, etc. Sorry folks, that’s beyond the scope of this article.
Summary
So does every trade work out this well? That reminds me of a joke. A salesman rings he doorbell of a home and a 12–year old boy answers the door. The boy has a beautiful woman on each side, a drink in one hand and a big cigar in his mouth. Momentarily stunned the salesman finally manages to ask hesitantly, “Um, is your mother home?”
The boy removes the cigar from his mouth, looks straight at the salesman and asks, “What do you think?”
Same answer here. Still, a logical set of steps is a good place to start.
Jay Kaeppel
Risk denotes the probability of an outcome, when an individual places an investment of value in the path of forces outside their control. Straightaway the madness of this practice is revealed, yet the pages of history are littered with those that have brought about the greatest advances mankind has ever made in return for risking something of value.
It may be interesting to note that the volatility of the recent global financial crisis saw the advent of many newcomers onto the BRW Rich List in 2008, and the contention that risk is defined by the market falling is not to the point. Today, due to the very existence of derivatives such as options, swaps and forward rate agreements, an individual can direct risk and return to almost every possible market contingency, regardless of the volatility exhibited.
The Bell Curve represents a distribution of events, with the ‘bell’ representing those events that are most likely; events that are in close proximity to present market price. These resemble at-the-money options.
As we get further away from conditions prevailing at the time, the likelihood of particular events occurring will not only decrease, but will decrease in probability at an increasing rate. These less likely events take their place along the tapering edges of the bell, extending to both extremes. A pricing model attributes time value in this very fashion.
The standard deviation is the unit used to measure the probabilities transgressed from the status quo, to the market price when a particular event occurs. These measured intervals decrease in size, as the two poles of this dimension are approached; the difference between a movement of one standard deviation and two standard deviations will be far greater than that of seven deviations and eight standard deviations.
Primarily, this is due to the fact that there is little difference between probabilities that are small with other probabilities of that class, and similarly, little difference between probabilities that are high with members of that class also. They are described at a high level of abstraction that classifies them broadly as ‘high’ or ‘low’ probability.
However, when events of low probability are compared with those that are of high probability, a happening may be for example, said to be effected by a movement across seven standard deviations. In this event it is a rare occurrence indeed. When volatility is high, it is useful to note that not only are the entire bell and its tapered edges lifted higher on the plane, but the edges of the bell, move closer in gradient to the body. In higher volatility, this is directly due to the indiscriminate application of an increased probability in all possible events. The opposite will be found in low volatility with in this case, the actual bell of the curve becoming much smaller.
Accordingly, a matrix of probabilities is able to be placed in perspective.
Heavily reliant on reason, the contention that price and quality are inexorably attached is well founded in history. Even more so in perfect markets, at very least we can state with confidence that low risk and high risk are not uniformly priced. While the perception of value is a personal value judgment, what is most definite is that markets provide returns that are commensurate with the risk undertaken.
Consideration of the capital needed to fund a position, and also a variety of possible market outcomes must firmly occupy the consciousness of every trader. Insight into one’s own ability to function under the weight of risk is also crucial to profitability, as decision making needs to be carried out as free of subjective influences as possible. At any length, a good rule of thumb will be to allow 25% of risk capital to remain free for unexpected contingencies.
To date, Hank Swiencinski aka The Professor, has delivered two sold out premium webinars to traders, his powerful ‘Rifle Trades’ and his widely acclaimed ‘Trading the Turns’.
The demand for these courses exceeded our quota both times, so much so that we had to offer the recording and the seminar book as a product after the events.
The Professor’s next premium event will be on March 13, 2014 and it’s sure to sell out.
So what’s with the title? The Professor, will be presenting another webinar on March 14th that will focus on the techniques he uses to trade the markets on event driven days like the Fed Announcement.
He calls these techniques ‘Going to the Candy Store’. Like all of the techniques in the Professor’s Methodology, they are extremely easy to understand and apply. With the right setup and technical analysis, these special days in the market can be money in the bank. It’s not rocket science, it’s commonsense and simple technique.
Copy and paste the code below to a New EDS file. Click on File, Save, name it Bothvolumeandcloseupdown.eds
PosVol if [volume]>val([volume],1).
NegVol if [volume]<val([volume],1).
PosClose if [close]>val([close],1).
NegClose if [close]<val([close],1).
Phasedown if Val([Phase],2)< Val([phase],1) and Val([Phase],1)> [Phase].
Phaseup if Val([Phase],2)> Val([phase],1) and Val([Phase],1)< [Phase].
Go to Charts
Click on the “Define Studies” button (up top)
Where it shows EDS Files up top…click on the button that looks like it has three periods in it (…)
Browse and select the Both Volume and Close UP Down.EDS file
Click on “Create New Color Study”
Select “Price Plot” and click Next
Select “Price Bar” and click Next
Select “NegClose” and click Next
Click on “Change Color” and select RED and click OK
Click Next
Click Finish
Click on “Create New Color Study”, again
Select “Price Plot” and click Next
Select “Price Bar” and click Next
Select “PosClose” and click Next
Click on “Change Color” and select GREEN and click OK
Click Next
Click Finish
Click on “Create New Color Study”
Select “Indicator” and select “VOLUME” then click Next
Select “Volume” and click Next
Select “NegVol” and click Next
Click on “Change Color” and select RED and click OK
Click Next
Click Finish
Click on “Create New Color Study”, again
Select “Indicator” and select “VOLUME” then click Next
Select “Volume” and click Next
Select “PosVol” and click Next
Click on “Change Color” and select GREEN and click OK
Click Next
Click Finish
Click on “Create New Color Study”
Select “Indicator” and select “PHASE” then click Next
Select “HISTOGRAM” and click Next
Select “PHASEDOWN” and click Next
Click on “Change Color” and select RED and click OK
Click Next
Click Finish
Click on “Create New Color Study”, again
Select “Indicator” and select “PHASE” then click Next
Select “HISTOGRAM” and click Next
Select “PHASEUP” and click Next
Click on “Change Color” and select GREEN and click OK
Click Next
Click Finish
Click OK to leave color studies
English