Backtest Portfolio Strategy Assignment

Background

Backtesting is a simulation of an investing strategy to test how a stock, portfolio, or trading strategy would have performed had it been employed over previous time periods. Although there are a number of limitations to backtesting, this approach can give an investor a quick feel for an investment strategy that would otherwise take years using a forward approach. Although past performance is certainly not predictive of future results, it can be informative to see how certain stocks or portfolios would have fared over certain time frames or during specific economic periods, such as during major recessions.

Last week I published an article on Seeking Alpha that examined the historic returns of a group of 50 stocks, chosen by a panel of ten respected SA contributors, that was termed the "New Nifty Fifty" by SA author Mike Nadel in reference to a well-known group of growth stocks from the early 1970s that are often cited by critics of dividend growth investing (DGI) as failed examples of DGI or of over-optimistic and speculation-based investing. In fact, while a few of the original Nifty Fifty stocks are now defunct (e.g., Eastman Kodak), most are still solid performers today and include names like Walt Disney (NYSE:DIS), Procter and Gamble (NYSE:PG), and Johnson & Johnson (NYSE:JNJ), to name a few. For more on the original Nifty Fifty, see articles by Mike Nadel and Jeremy Siegel here and here.

To briefly summarize my previous article, I showed that the New Nifty 50, which I'll refer to as NN50, outperformed the Vanguard S&P 500 Index Fund (MUTF:VFIAX) and the Vanguard Dividend Growth Fund (MUTF:VDIGX) over the past ten years and during the 2007-2009 bear market in terms of total return performance. This result held true for the averaged performance of all of the NN50 stocks as well as for the majority of individual NN50 stocks compared to the two mutual fund returns. For example, over the past ten years, 30 of the NN50 stocks outperformed VDIGX while 40 NN50 stocks outperformed VFIAX. In addition, during the 2007-2009 bear market, 29 NN50 stocks had better total returns (less total loss) than VDIGX while 40 NN50 stocks did better than VFIAX.

While my previous article and its conclusions were fairly well received by SA readers and generated a lot of interesting discussion, there were a number of commenters who either see no value in backward-looking analyses or who thought the results were not valid due to the introduction of survivorship bias, i.e., the NN50 may have been picked by the panelists precisely because of those stocks' solid past performance, which makes it unfair to compare them against historical returns or to mutual funds that had no such hindsight at the time of investment. Although the purpose of my previous article was simply to examine how the NN50 stocks had performed in the past using VFIAX and VDIGX as a metric, the criticisms about survivorship bias are valid and worth examining further.

Thus the purpose of this article is to address the survivorship bias issue by directly comparing the total return performance of the consensus NN50 stocks (as a group) to the current holdings of VDIGX. This approach, as suggested by SA commenters TF17 and Illuminati Investments, is a more fair comparison as it represents the current top picks of both portfolios. That is, both the consensus NN50 stocks and the current portfolio of VDIGX stocks were specifically chosen by the fund manager for VDIGX and by the SA panelists for NN50 because those are the stocks that are thought to be good investment choices going forward. Since both portfolios can be thought of as best choices for the future, it then makes it a fair head-to-head comparison in backtesting the past performance of those two portfolios of stocks.

Thus the null hypothesis for this experiment is that there will be no difference between the NN50 portfolio and the VDIGX portfolio in total return performance over the past ten years (the time frame chosen for this article). This article is not meant as a means to predict future performance of either portfolio, but rather as an examination of past performance with issues related to survivorship bias equalized between portfolios, and to see how various weighting strategies affect total return performance of these two portfolios.

Method

To examine 10-year total return performance, I elected to backtest the NN50 and VDIGX portfolios using a weighted portfolio, an equal-weight portfolio, and a randomly-assigned-to-weight portfolio. All portfolio backtests were done with an initial investment amount of $100K per portfolio that was then distributed using one of the three weighting approaches. If a stock in either portfolio did not have 10-year data (e.g., due to recent spin-offs or IPOs), those stocks were deleted from the analysis with funds distributed and weights adjusted accordingly. Thus Anheuser-Bush InBev (NYSE:BUD) was removed from VDIGX while Kraft Foods (KRFT), Kinder Morgan (NYSE:KMI) and Philip Morris (NYSE:PM) were removed from NN50. This left a total of 49 stocks in the VDIGX portfolio and 47 stocks in the NN50 portfolio.

VDIGX Stock Weighting: To determine the VDIGX stock weightings, I started by calculating the actual percent market value of each VDIGX stock holding based on the currently reported market value per stock as of September 30, 2014 as shown on the Vanguard website here. Since BUD was removed from the list, its weighted-dollar value was evenly distributed among the remaining stocks and the weights were adjusted accordingly.

NN50 Stock Weighting: I first ranked the NN50 stocks using the number of panelists who included the same stock in the original consensus NN50 article by Mike Nadel. The stocks were than sorted alphabetically within a panelist category (e.g., there were 5 stocks named by all 10 panelists, so those stocks were sorted alphabetically within that category). Weights were then assigned based on the VDIGX weightings from high to low. This resulted in Chevron (NYSE:CVX) having the highest weighting (named by 10 panelists and the first alphabetically in the "10 panelists" category) and Omega Health Care (NYSE:OHI) having the lowest weighting (named by 3 panelists and last alphabetically in the "3 panelist" category). Weights were then slightly adjusted equivalently across all stocks to account for the different number of stocks in the two portfolios so that all percentages in a portfolio added to 100%. See the Appendix section for the tables containing the stocks and their weightings within each portfolio.

Equal-Weighted Portfolios: For the equal-weight portfolios, the $100K investment amount was simply divided evenly among all stocks in each of the two portfolios and weights evenly distributed. This resulted in an investment amount of $2,040.82 (2.04%) for each stock in the VDIGX portfolio and $2,127.66 (2.13%) in the NN50 portfolio.

Randomly-Assigned to Weights: For this weighting, each of the stocks within a portfolio was randomly assigned to one of the weights in the existing weighted portfolios. Thus the originally calculated weightings were maintained and each stock was randomly assigned to a specific weight and its investment amount adjusted accordingly. Randomization was repeated five times and the mean return is presented in Figures 1 and 2 below. Table 1 below lists the results from each of the five randomization backtests.

Results

Results of the analyses indicate that both of the weighted-portfolios far outperformed either the equal-weighted or randomly assigned investment strategies (see Figures 1 and 2). The total returns for the NN50 were again superior to current VDIGX holdings across all investment approaches tested, although they were not as dramatic as in my previous article, which did not account for possible survivorship bias. Nonetheless, the weighted NN50 portfolio had a 7.24% greater total return than the weighted VDIGX holdings over the past ten years. Returns for the equal-weight and randomly assigned strategies were not as impressive as the weighted strategy, but in both cases the NN50 portfolio had superior returns compared to the current VDIGX holdings. Total returns for the NN50 portfolio were 18.31% better than the current VDIGX portfolio using the equal-weight strategy, and 11.8% better than VDIGX for the randomly assigned strategy (based on the mean of 5 randomized trials; see Table 1).

Figure 1: Investment total returns (dividends reinvested) in dollars for the three weighting strategies. In all cases, the NN50 outperformed the current VDIGX holdings when backtested over the past ten years. The weighted approach provided the best results for both the NN50 portfolio and the current VDIGX portfolio.

Figure 2: Total-return percentages over the past ten years for NN50 and the current VDIGX portfolio of stocks across the three weighting strategies employed.

Random Assignment Trial

Dollar Return

Percent Return

VDIGX Trial 1

$206,252

106.25%

VDIGX Trial 2

$214,637

114.64%

VDIGX Trial 3

$213,051

113.05%

VDIGX Trial 4

$212,383

112.38%

VDIGX Trial 5

$206,258

106.26%

Mean:

$210,516

110.52%

NN50 Trial 1

$213,605

113.60%

NN50 Trial 2

$222,560

122.56%

NN50 Trial 3

$236,581

136.58%

NN50 Trial 4

$225,933

125.93%

NN50 Trial 5

$212,904

112.90%

Mean:

$222,316

122.32%

Table 1: Random assignment to portfolio weights for the "Randomized" comparison group shown in Figures 1 and 2 above. After calculating the weightings for each portfolio, each stock was randomly assigned to one of the weightings. This process was repeated five times and the mean of the five trials was used. Although there was a range in returns for the five trials, the average of the randomized returns were very close to those of the equal-weighted portfolio while none of the randomized results were close to the greater returns achieved with the weighted portfolio strategy.

Despite the superior performance of the weighted portfolios for NN50 and VDIGX, few of the top weighted stocks finished in the top 10 or top 20 on total return performance. VDIGX had only 2 of its top-10 weighted stocks finish in the top 10 on total return performance while NN50 had only 1 of its top-ten weighted stocks finish in the top 10 on total returns. Further, VDIGX had only 3 of its top-10 weighted stocks finish in the top 20 whereas NN50 had only 4 of its top-10 weighted stocks finish in the top 20 (see Tables 1A and 2A in the Appendix for weightings, returns, and return rankings). The best performing stock over the past 10-years for VDIGX, TJX Companies (NYSE:TJX), was the ninth highest-weighted stock, while the best performing stock for the NN50 portfolio, Apple (NASDAQ:AAPL), was the 33rd highest-weighted stock. While this may at first seem counterintuitive, it is not if one considers that the current portfolios are designed for future returns and not based simply on past historic performance.

One factor that may have resulted in the superior performance of NN50 is that the NN50 weighted portfolio had fewer of the more poorly performing stocks by weight in its top-10 list than did VDIGX. For NN50, five of the top-ten highest weighted stocks ranked between 30 and 39 on total return performance while none of the top ten had total return performance rankings of 40 or worse. In contrast, for VDIGX, six of the top-10 highest weighted stocks ranked between 30-39 on total returns and 3 of the top-10 weighted stocks had total return performance rankings between 40 and 49. Indeed, United Parcel Service (NYSE:UPS) was the highest-weighed stock in the VDIGX list and finished 49th in total return performance. Thus the overall superior performance of NN50 was due, at least in part, to having fewer of the poorer returning stocks in its top-10 weightings.

This result also goes against the common refrain of many critics from my previous article that the current NN50 stock picks are based on past performance. If this were indeed the case, then the NN50 portfolio would be expected to have a larger number of top performers in the top-10 and top-20 weightings. However, rather than picking solid past performers, the NN50 panelists selected stocks that they thought would be good investments going forward. In support of this, in the comments section to my previous article, several of the NN50 panelists stated that their submission list was indeed based on forward earnings potential, not past returns. This is also likely the case for VDIGX and may thus explain why some of the poorer performers of the past were more highly weighted between the two portfolios. For example, the poorer past performers may perhaps be viewed as being more fairly valued or to perhaps have greater earnings growth potential going forward (that is purely speculative on my part and is just provided as a possible example). Nonetheless, it should be clear that neither the NN50 list nor the VDIGX portfolio is simply a collection of "greatest hits."

Conclusion

The purpose of this article was to further compare the consensus New Nifty Fifty stocks to the Vanguard Dividend Growth Fund by equalizing survivorship bias across the two portfolios. This was done primarily in response to some criticisms of my previous article as well as to provide additional insight into the past performance of the consensus NN50 stocks over the past ten years. Although past performance is certainly no predictor of future success, this current analysis does provide some interesting information on how various backetested weighting strategies affect portfolio returns.

It is notable that the consensus-weighted rankings of the NN50 stocks resulted in a 7% better total return performance than did the VDIGX weighted rankings over the past decade. What's more notable is that both the weighted VDIGX and weighted NN50 portfolios had superior returns to the other strategies even though few of the best performing stocks were in the top 10 or top 20 weightings for either portfolio. This result is in direct contrast to critics who claim that the NN50 is simply a list of prior top performers, for if this were the case, then one would have expected to see a tighter correlation to weighting and performance (this is true for VDIGX as well). Despite the lack of a direct linear correspondence to weighting and performance, the results clearly indicate that weighting does make a difference in overall performance as both a equal-weighted and randomly-assigned strategy failed to match the performance of the weighted portfolios (this despite the random-assigned strategy being run five consecutive times).

One factor that may have given NN50 the superior performance returns is the heavier weighting of stalwart dividend champions (companies that have increased their annual dividend payouts for at least 25 consecutive years) in its top 10, which likely helped the NN50 perform better during the 2007-2009 bear market.

The results of this analysis also raise the interesting idea of whether a crowd-sourced stock-picking strategy might yield superior total-return performance compared to conventional stock pickers or to market indexes. While the backtesting results are intriguing, the ultimate test will be forward analysis of the NN50 as compared to VDIGX, the S&P 500, or other relevant benchmarks. Indeed, in the comments section to my previous article, Mike Nadel indicated that he plans to start a real-time, real-money portfolio containing all of the NN50 stocks and will post the ongoing returns on Seeking Alpha. This should be provide a very interesting series of articles that I personally look forward to reading, and is what I consider another example of the outstanding contributions from the Seeking Alpha community.

Finally, I would like to conclude by stating that this article is in no way meant to represent any sort of contest between NN50 and VDIGX, or to imply that one approach is better than the other, either in the past or going forward. Rather this article was meant as purely an academic exercise in examining several backtesting portfolio strategies and to hopefully provide readers with some interesting data and information. It should be noted that investors purchase stocks, ETFs and mutual funds with different strategies in mind, and any one strategy could prove superior to another over a given time period or economic market condition.

Appendix

VDIGX 50 Holdings
(as of 9/30/2014)

Ticker

Weight

Amt
Invested

Total
Return

%
Return

% Return
Rank

United Parcel Service

UPS

3.14%

$3,140

$5,284.23

68.29

49

*Lockheed Martin

(NYSE:LMT)

2.87%

$2,874

$13,079.52

355.10

6

UnitedHealth Group

(NYSE:UNH)

2.87%

$2,872

$6,973.45

142.81

33

*Wal-Mart

(NYSE:WMT)

2.85%

$2,848

$5,507.51

93.38

44

*Johnson & Johnson

JNJ

2.63%

$2,631

$5,910.71

124.66

38

Cardinal Health

(NYSE:CAH)

2.61%

$2,605

$6,853.56

163.09

31

*Microsoft Corp.

(NASDAQ:MSFT)

2.59%

$2,592

$5,630.61

117.23

41

Merck & Co.

(NYSE:MRK)

2.59%

$2,590

$7,252.48

180.02

26

TJX Cos. Inc.

TJX

2.56%

$2,563

$14,804.61

477.63

1

*Chevron Corp.

CVX

2.55%

$2,549

$7,058.04

176.89

27

NIKE

(NYSE:NKE)

2.53%

$2,535

$12,409.43

389.52

5

Praxair Inc.

(NYSE:PX)

2.53%

$2,525

$8,722.22

245.43

14

*Automatic Data Processing

(NASDAQ:ADP)

2.51%

$2,506

$7,745.40

209.07

23

Roche Holding AG

(OTCQX:RHHBY)

2.51%

$2,506

$8,586.74

242.65

15

Accenture plc Class A

(CAN)

2.50%

$2,502

$9,277.79

270.81

12

*United Technologies Corp.

(NYSE:UTX)

2.45%

$2,448

$6,667.82

172.38

29

*Exxon Mobil Corp.

(NYSE:XOM)

2.40%

$2,404

$5,224.58

117.33

40

ACE Ltd.

(NYSE:ACE)

2.35%

$2,348

$7,820.09

233.05

20

*McDonald's Corp.

(NYSE:MCD)

2.34%

$2,338

$8,796.82

276.25

11

Medtronic Inc.

(NYSE:MDT)

2.28%

$2,284

$4,012.89

75.70

48

*Coca-Cola Co.

(NYSE:KO)

2.23%

$2,233

$5,947.04

166.33

30

*Procter & Gamble

PG

2.10%

$2,096

$4,501.07

114.75

42

BG Group plc

(NYSE:BG)

2.08%

$2,085

$3,758.91

80.28

46

Lowe's Cos. Inc.

(NYSE:LOW)

2.07%

$2,066

$5,397.46

161.25

32

Marsh & McLennan Cos.

(NYSE:MMC)

2.06%

$2,064

$4,774.50

131.32

34

Canadian National Railway

(NYSE:CNI)

2.06%

$2,061

$10,179.56

393.91

4

Oracle Corp.

(NYSE:ORCL)

2.04%

$2,040

$6,436.14

215.50

21

Honeywell International

(NYSE:HON)

1.92%

$1,917

$6,735.41

251.35

13

Diageo plc

(NYSE:DEO)

1.84%

$1,842

$5,259.33

185.52

24

CVS Health Corp.

(NYSE:CVS)

1.83%

$1,830

$8,172.46

343.67

8

Chubb Corp.

(NYSE:CB)

1.82%

$1,824

$6,140.92

236.67

18

Northrop Grumman Corp.

(NYSE:NOC)

1.81%

$1,814

$6,949.73

283.12

9

Amgen Inc.

(NASDAQ:AMGN)

1.81%

$1,809

$4,986.51

175.65

28

Enbridge Inc.

(NYSE:ENB)

1.80%

$1,803

$9,529.29

428.52

3

*Colgate-Palmolive Co.

(NYSE:CL)

1.79%

$1,790

$6,072.77

239.26

16

Ecolab Inc.

(NYSE:ECL)

1.79%

$1,790

$5,971.06

233.58

19

BlackRock Inc.

(NYSE:BLK)

1.78%

$1,780

$10,212.05

473.71

2

PNC Financial Services

(NYSE:PNC)

1.55%

$1,554

$3,133.06

101.61

43

*Wells Fargo & Co.

(NYSE:WFC)

1.54%

$1,540

$3,524.27

128.85

36

Schlumberger Ltd.

(NYSE:SLB)

1.53%

$1,530

$4,315.03

182.03

25

Walt Disney Co.

DIS

1.42%

$1,423

$5,394.68

279.11

10

Mattel Inc.

(NASDAQ:MAT)

1.34%

$1,343

$3,023.75

125.15

37

General Dynamics Corp.

(NYSE:GD)

1.34%

$1,342

$4,505.47

237.73

17

Public Storage

(NYSE:PSA)

1.29%

$1,295

$5,813.10

348.89

7

*Emerson Electric Co.

(NYSE:EMR)

1.29%

$1,288

$2,971.01

130.67

35

Pfizer Inc.

(NYSE:PFE)

1.28%

$1,281

$2,303.20

79.80

47

*Dominion Resources

(NYSE:D)

1.05%

$1,054

$3,308.36

213.89

22

*IBM

(NYSE:IBM)

1.03%

$1,030

$1,986.61

92.87

45

Omnicom Group Inc.

(NYSE:OMC)

0.82%

$816

$1,792.56

119.68

39

Sum

$ Invested

$ Return

% Return

100.00%

$100,000

$310,713.81

210.71%

Table 1A: Current holdings and investment weightings of the Vanguard Dividend Growth Fund as last reported on 9/30/2014 (table sorted by Weight). The current holdings were backtested with an initial $100,000 investment on December 1, 2004, with the investment amount distributed according to the indicated weighting for each stock. The last column (% Return Rank) indicates the relative return ranking within the table based on the 10-year return percentages. Note that ten-year data was not available for Anheuser-Busch InBev and this stock was not included (dollar amounts and weightings were adjusted to account for the missing stock). *Indicates stocks that are in both the VDIGX and the New Nifty Fifty portfolios, although the weightings differ between the two portfolios.

Nifty 50 Holdings

Ticker

Panelist
Pick

Weight

Amt
Invested

Total
Return

%
Return

% Return
Rank

*Chevron

CVX

10

3.20%

$3,202

$8,866.17

176.89

19

*Coca-Cola

KO

10

2.94%

$2,939

$7,827.30

166.33

23

*Johnson & Johnson

JNJ

10

2.94%

$2,937

$6,598.16

124.66

35

Kimberly-Clark

(NYSE:KMB)

10

2.91%

$2,914

$7,466.09

156.21

25

*Procter & Gamble

PG

10

2.70%

$2,701

$5,800.29

114.75

38

*ExxonMobil

XOM

9

2.68%

$2,676

$5,815.71

117.33

36

*McDonald's

MCD

9

2.66%

$2,663

$10,019.65

276.25

8

PepsiCo

(NYSE:PEP)

9

2.66%

$2,661

$6,379.24

139.73

28

Southern Company

(NYSE:SO)

9

2.63%

$2,634

$5,999.11

127.76

32

AT&T

(NYSE:T)

8

2.62%

$2,621

$5,580.36

112.91

39

*Colgate-Palmolive

CL

8

2.61%

$2,607

$8,844.54

239.26

9

General Mills

(NYSE:GIS)

8

2.60%

$2,597

$7,177.99

176.40

20

Realty Income

(NYSE:O)

8

2.58%

$2,578

$8,221.20

218.90

11

Target

(NYSE:TGT)

8

2.58%

$2,578

$4,289.41

66.39

46

3M

(NYSE:MMM)

7

2.57%

$2,574

$6,395.19

148.45

26

Altria

(NYSE:MO)

7

2.52%

$2,521

$15,074.74

497.97

3

Genuine Parts

(NYSE:GPC)

7

2.48%

$2,478

$7,995.65

222.67

10

*Lockheed Martin

LMT

7

2.42%

$2,423

$11,027.03

355.10

4

*Microsoft

MSFT

7

2.41%

$2,414

$5,243.94

117.23

37

Walgreen

(WAG)

7

2.31%

$2,310

$4,824.59

108.86

40

AFLAC

(NYSE:AFL)

6

2.18%

$2,176

$4,035.61

85.46

45

Baxter Int'l

(NYSE:BAX)

6

2.17%

$2,165

$5,615.88

159.39

24

ConocoPhillips

(NYSE:COP)

6

2.15%

$2,147

$5,758.56

168.21

22

Deere

(NYSE:DE)

6

2.15%

$2,145

$6,177.37

187.99

15

*Emerson Electric

EMR

6

2.14%

$2,142

$4,940.91

130.67

30

*IBM

IBM

6

2.12%

$2,122

$4,092.79

92.87

44

Visa

(NYSE:V)

6

2.00%

$2,000

$8,804.71

340.24

5

*Wal-Mart

WMT

6

1.93%

$1,927

$3,726.46

93.38

43

Becton Dickinson

(NYSE:BDX)

5

1.92%

$1,915

$5,514.96

187.99

16

General Electric

(NYSE:GE)

5

1.91%

$1,909

$1,864.00

-2.36

47

Verizon

(NYSE:VZ)

5

1.90%

$1,900

$3,947.01

107.74

41

*Wells Fargo

WFC

5

1.89%

$1,894

$4,334.39

128.85

31

Apple

AAPL

4

1.89%

$1,889

$48,503.11

2,467.66

1

*Automatic Data Processing

ADP

4

1.88%

$1,876

$5,798.23

209.07

13

Caterpillar

(NYSE:CAT)

4

1.88%

$1,876

$4,529.47

141.44

27

Clorox

(NYSE:CLX)

4

1.87%

$1,866

$4,206.85

125.45

34

*Dominion Resources

D

4

1.64%

$1,644

$5,160.29

213.89

12

J.M. Smucker

(NYSE:SJM)

4

1.63%

$1,631

$4,890.07

199.82

14

McCormick

(NYSE:MKC)

4

1.52%

$1,516

$3,564.54

135.13

29

Starbucks

(NASDAQ:QCOM)

4

1.44%

$1,437

$4,091.71

184.74

18

Qualcomm

(NASDAQ:SBUX)

4

1.44%

$1,437

$2,825.78

96.64

42

*United Technologies

UTX

4

1.39%

$1,390

$3,786.06

172.38

21

Wisconsin Energy

(NYSE:WEC)

4

1.38%

$1,384

$5,531.65

299.69

6

HCP

(NYSE:HCP)

3

1.38%

$1,376

$3,956.66

187.55

17

Hershey

(NYSE:HSY)

3

1.15%

$1,154

$2,611.00

126.26

33

NextEra Energy

(NYSE:NEE)

3

1.13%

$1,130

$4,312.54

281.64

7

Omega Healthcare

OHI

3

0.92%

$924

$5,924.20

541.15

2

Sum

$ Invested

$ Return

% Return

100.00%

$100,000

$317,951.17

217.95%

Table 2A: Consensus Nifty Fifty picks and panelist rankings as reported in the Mike Nadel Seeking Alpha article on October 15, 2014 (table sorted by Weight). The list of stocks was sorted by panelist ranking and then alphabetically within the panelist category. Weightings were then assigned based on those from the VDIGX portfolio and adjusted to account for the difference in stock numbers between the two portfolios (ten-year data for Kraft Foods , Kinder Morgan and Philip Morris was not available and these stocks were removed from the original data). Portfolio was backtested as described in Table 1 above.

Disclosure:The author is long CVX, KO, PG, DIS, TJX, MO, WFC, SLB, VFIAX, VDIGX.

The author wrote this article themselves, and it expresses their own opinions. The author is not receiving compensation for it (other than from Seeking Alpha). The author has no business relationship with any company whose stock is mentioned in this article.

Download The "Ultimate" Options Strategy Guide


It's finally here! After years of research, development, and testing the doors are open to purchasing access to our incredible new options backtesting and trade optimization software we're calling the "Trader's Toolbox". Given that we've now got a whole suite of tools and scanners for you to use we have to consolidate it under one roof which is why we believe having a Toolbox is the most clear and logical route. You can learn more about the new software release including demos for by clicking here.

Key Points from Today's Show:

Ground-Breaking Backtesting Software

  • Intuitive software that produces extremely powerful results.
  • Made up of two components:
  1. The ability to backtest different trades and strategies across different ticker symbols.
  2. Trade optimization software.

The Trader's Toolbox

  • The toolbox consists of two versions, Toolbox Light and Toolbox Plus.
  • The Toolbox Light purchase comes with access to the watchlist and the earnings calendar.
  • The Toolbox Plus includes the backtesting software and the trade optimization software.

Backtesting Software

  • The backtesting software itself is the ability to test any trading strategy with a million combination of variables across different tickers and frequencies.
  • The software is set up in two steps:

Step 1:

  • Choose a strategy to test.
  • Choose a specific ticker symbol.
  • Choose the frequency variables; daily, weekly, or sequential.

Step 2:

  • Choose days until expiration on average, from 10 to 80 days.
  • Choose minimum implied volatility level.
  • Choose a starting portfolio value.
  • Choose your overall allocation, between 10 and 50%.
  • Choose the profit-taking exit; 25, 50, or 75%.
  • Choose a stop loss or none.
  • Choose the strategy-specific parameters, at the money or out.

SPY Backtest

  • Did a weekly SPY short straddle, 40 days to average expiration.
  • No IV rank, 20% overall, which means 80% of our portfolio sits in cash during this time period.
  • Profit taking at 25%, and no stop loss level. 
  • Short strikes at a 50 Delta, effectively selling at the money options.

Results:

  • Total return for this strategy was 79% over the testing period.
  • 6% annual CAGR, which is a compound growth rate.
  • Sharpe ratio was 1.67%, with a smooth, steady equity curve that outperforms the market. 
  • Total profit of $197,000 with a starting portfolio of $250,000.
  • 22% drawdown that only lasted for 32 days, which is really low.

Performance Page

  • Allows you to print on PDF.
  • Shows total profit, and annual compound growth rate, which is indicative of how a strategy will perform long term.
  • The Sharpe ratio is really important in the financial space, especially in the hedge fund and investment space; it is a measure of risk-adjusted returns. 
  • High Sharpe ratios are indicative of getting a lot of excess return for not taking on too much excess risk. 
  • The strategy is graphed out, compared to the S&P to see the return values.
  • Consistency metrics are also shown, displaying how often the strategy won based on parameters set.
  • Shows how the distribution of monthly returns affect the portfolio, and average monthly gain.
    The drawdown days were calculated to show how many days it took to recover from drawdowns. 
  • A table of monthly distributions shows how often you are gaining every single month or losing. 
  • The final table shows all the monthly return numbers, as well as the annual return for each year. 

Optimization Software

  • The software was built to answer the question of which is the best possible strategy for you at this exact moment.
  • The software gives you all the information you need to make a trade based on whatever market conditions are present right now, at this exact moment. 
  • It is not just about one strategy; it is about figuring out that strategy that works best for you.
  • You can make a decision based on which strategy best suits your personality and portfolio.

Using the Optimization Software:
1. Select an optimization factor - what you optimize your strategies based off of.
2. Choose a market a market outlook - bullish, bearish, or neutral.
3. Pick which type of account you have - margin, retirement.
4. Choose the market situation or setup - how far until expiration on average, and whether IV is low or high. 

Free Options Trading Courses:

[FREE Download] Podcast Show Notes & Transcript PDF: No time to read the show notes right now? We've made it incredibly easy for you to save time by giving you instant access to the complete digital version of today's show. Click Here to Download Your FREE Copy

  • Options Basics [20 Videos]: Whether you're a completely new trader or an experienced trader, you'll still need to master the basics. The goal of this section is to help lay the groundwork for your education with some simple, yet important lessons surrounding options.
  • Finding & Placing Trades [26 Videos]: Successful options trading is 100% dependent on your ability to find and enter trades that give you an "edge" in the market. This module helps teach you how to scan properly for and select the best strategies to execute smarter option trades each day.
  • Pricing & Volatility [12 Videos]: This module includes lessons on mastering implied volatility and premium pricing for specific strategies. We'll also look at IV relativeness and percentiles which help you determine the best strategy to use for each and every possible market setup.
  • Neutral Options Strategies [7 Videos]: The beauty of options is that you can trade the market within a neutral range either up or down. You'll learn to love sideways and range bound markets because of the opportunity to build non-directional strategies that profit if the stock goes up, down or nowhere at all.
  • Bullish Options Strategies [12 Videos]: Naturally everyone wants to make money when the market is heading higher. In this module, we'll show you how to create specific strategies that profit from up trending markets including low IV strategies like calendars, diagonals, covered calls and direction debit spreads.
  • Options Expiration & Assignment [11 Videos]: Our goal is to make sure you understand the logistics of how each process works and the parties involved. If you don’t feel confident in the expiration processes or have questions that you just can't seem to get answered, then this section will help you.
  • Portfolio Management [16 Videos]: When I say "portfolio management" some people automatically assume you need a Masters from MIT to understand the concept and strategies - that is NOT the case. And in this module, you'll see why managing your risk trading options is actually quite simple.
  • Trade Adjustments/Hedges [15 Videos]: In this popular module, we'll give you concrete examples of how you can hedge different options strategies to both reduce potential losses and give yourself an opportunity to profit if things turn around. Plus, we'll help you create an alert system to save time and make it more automatic.
  • Professional Trading [14 Videos]: Honestly, this module isn't just for professional traders; it's for anyone who wants to have eventually options replace some (or all) of their monthly income. Because the reality is that mindset is everything if you truly want to earn a living trading options.

Option Trader Q&A

Remember, if you’d like to get your question answered here on the podcast or LIVE on Facebook & Periscope, head over to OptionAlpha.com/ASK and click the big red record button in the middle of the screen and leave me a private voicemail. There’s no software to download or install and it’s incredibly easy.

PDF Guides & Checklists:

  • The Ultimate Options Strategy Guide [90 Pages]: Our most popular PDF workbook with detailed options strategy pages categorized by market direction. Read the whole guide in less than 15 mins and have it forever to reference.
  • Earnings Trading Guide [33 Pages]: The ultimate guide to earnings trades including the top things to look for when playing these one-day volatility events, expected move calculations, best strategies to use, adjustments, etc.
  • Implied Volatility (IV) Percentile Rank [3 Pages]: A cool, simple visual tool to help you understand how we should be trading based on the current IV rank of any particular stock and the best strategies for each blocked section of IV.
  • Guide to Trade Size & Allocation [8 Pages]: Helping you figure out exactly how to calculate new position size as well as how much you should be allocating to your each position based on your overall portfolio balance.
  • When to Exit/Manage Trades [7 Pages]: Broken down by option strategy we'll give you concrete guidelines on the best exit points and prices for each trade type to maximize your win rate and profits long-term.
  • 7-Step Trade Entry Checklist [10 Pages]: Our top 7 things you should be double-checking before you enter your next trading. This quick checklist will help keep you out of harms way by making sure you make smarter entries.

Real-Money, LIVE Trading:

  • EWZ Iron Butterfly (Closing Trade): After nearly pinning the stock at our short strikes, and thanks to the volatility drop, we netted a $600 profit on this iron butterfly trade.
  • VXX Short Call (Closing Trade): One of the most consistent and profitable options trades we can make is shorting pure volatility with VXX and today we closed this naked short call in VXX after a couple days for a $420 profit.
  • DIA Iron Condor (Adjusting Trade): This neutral iron condor in DIA is need of a quick adjustment early this week as the market continues to rally. In this video, we'll discuss why I'm adding an additional put credit spread while also choosing NOT to close out of our current put credit spread due to pricing reasons.
  • COP Short Put (Closing Trade): These single short puts in COP acted as a great hedge for our other bearish bets in oil this month and helped smooth out our returns after we closed them for a nice big profit.
  • TSLA Put Debit Spread (Closing Trade): Although many people thought we were crazy for getting bearish in TSLA this pre-earnings put debit spread trade made us $200 today. After the huge run up from $140 to $260 and getting some technical sell signals, we were pretty sure this stock would pull back.
  • MON Iron Condor (Closing Trade): Following a huge drop in implied volatility we worked hard to close this MON iron condor trade adjusting the order multiple times to fill before the end of the day.
  • IBB Call Debit Spread (Opening Trade): We'll show you how I started searching for a new bullish trade and eventually found a low volatility trade in IBB looking for a move higher to hedge our portfolio.
  • TLT Iron Butterfly (Closing Trade): Following the Brexit vote TLT and bonds traded in a nearly $8 range really quickly - even still the drop in implied volatility helped generate a $330 profit for us.
  • XBI Call Debit Spread (Closing Trade): Got lucky picking the exact bottom for our entry in this call debit spread for the XBI biotech ETF which ultimately was closed for a profit of $165 today on the rally higher.
  • COH Iron Butterfly (Earnings Trade): Shortly after the market open we close out of our COH earnings trade for about a $160 profit, leaving just 1 leg on to expire worthless.
  • EWW Debit Spread (Closing Trade): Using some of the technical analysis signals we discovered in our backtesting research, we were able to make a quick $130 profit on this bearish EWW debit spread trade.
  • IBM Iron Condor (Earnings Trade): Shortly after the market opened you'll follow along with me as we watch volatility drop and liquidity come into the market before closing out the position for $250 profit.
  • SLV Short Straddle (Opening Trade): Using our watch list software we decided to continue to add to our existing SLV short straddle position with a new set of strike prices reflective of the move lower in the ETF recently.

Thank You for Listening!

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