Walt Disney Earnings Day Historical Stock Performance

Walt Disney Earnings Day Historical Stock Performance

With Walt Disney ($DIS) releasing  Q2 2013 earnings After Market Close  today ( 7th May 2013) , below the details of $DIS stock price reaction post earnings announcement since 2000 , regardless whether the management beats EPS /Revenue estimates at the earnings announcement.

Over Night Gap Movement for Walt Disney stock price after earnings are reported

here is how the $DIS stock price gap’ed before earnings are reported

below the backtest performance summary for holding the $DIS longs overnight before Walt Disney Earnings are announced 

  • Winners : 27
  • Losers : 25
  • % Winners : 52%
  • Average Change % : -0.33
  • Median Change % : 0.13
  • Maximum Gain % : 7.75
  • Maximum Loss % : -9.88
  • Average Gain %if Winner : 2.25
  • Average Loss % if Loser : -3.40
  • Average Gain % / Average Loss % : 0.66
  • Average Absolute Change% : 2.67

Intraday Movements from Open to Close  Movement for Walt Disney stock price after earnings are reported

here is how the $DIS stock price moved from market on open till market on close on the day earnings are reported , assuming one is holding on to $DIS longs

  • Winners : 25
  • Losers : 27
  • % Winners : 48%
  • Average Change % : 0.01
  • Median Change % : -0.07
  • Maximum Gain % : 6.79
  • Maximum Loss % : -7.10
  • Average Gain %if Winner : 1.82
  • Average Loss % if Loser : -1.73
  • Average Gain % / Average Loss % : 1.05
  • Average Absolute Change% : 1.74

Full day $DIS stock price movement ( change from previous close to earnings day’s close)

here is $DIS stock price moved on the day after earnings are reported ( if earnings are reported AMC, the next trading day change is considered as the earnings day change, for the earnings announcements Before Market Open , change on the earnings day is considered , as the earnings day change)

ps: assuming one is holding on to $DIS longs here are the trading odds

  • Winners : 28
  • Losers : 24
  • % Winners : 54%
  • Average Change % : -0.31
  • Median Change % : 0.37
  • Maximum Gain % : 11.72
  • Maximum Loss % : -15.62
  • Average Gain %if Winner : 2.90
  • Average Loss % if Loser : -4.05
  • Average Gain % / Average Loss % : 0.72
  • Average Absolute Change% : 3.43

Historical $DIS Stock Price Movements on Earnings day

Below the table with historical stock price movements of  Walt Disney, on  earnings reporting day

Walt Disney Earnings Day Stock Price Movements since 2000

No Volatile Movement ( as defined as average absolute movement of more than 5%) , no clear trading edge either, a 4% strangle might come handy , again we don’t suggest nor consider option strangle selling .

  • C20: Change from Current Close to Next days’s Open
  • C20 %: Change from Current Close to Next days’s Open in percentage
  • O2C : Change from Current Open to Current Close
  • O2C% : Change from Current Open to Current Close in percentage
  • C2C : Change on the Earnings Reporting day 
  • C2C% : Change on the Earnings Reporting day  in percentage

ps: The earnings data is from earnings.com

pps: Average Absolute Change% data might be useful to gauge the volatility on the earnings day , and or to calculate the straddle pay off factor for options traders

Trade Idea : Wells Fargo Stock , $WFC On Balance Volume Moved Below Zero

$WFC On Balance Volume Moved Below Zero

WFC On Balance Volume Moved Below Zero Stock Chart

Wells Fargo Stock , (WFC) On Balance Volume Moved Below Zero Trading Strategy

  • WFC Stock On Balance Volume is below Zero during the current trading session
  • While the WFC Stock On Balance Volume is above Zero during previous trading session
  • Go Short at close
  • Buy to Cover during the next trading day at close

On Balance Volume Calculation steps from Stockcharts

The On Balance Volume (OBV) line is simply a running total of positive and negative volume. A period’s volume is positive when the close is above the prior close. A period’s volume is negative when the close is below the prior close.

  • If the closing price is above the prior close price then: Current OBV = Previous OBV + Current Volume

  • If the closing price is below the prior close price then: Current OBV = Previous OBV – Current Volume

  • If the closing prices equals the prior close price then: Current OBV = Previous OBV (no change)

Below the backtest performance summary for going short when “WFC On Balance Volume Moved Below Zero ” trading strategy during the last four years.

Go Short when WFC Stock On Balance Volume (OBV) Moved Below Zero  backtest perfromance report
Total number of trades 18 Percent profitable 83%
Number of winning trades 15 Number of losing trades 3
Average profit per trade % 0.87 Median trade -0.63
Average winning trade % 1.45% Average losing trade % 2.03%
Largest winning trade % 3.74% Largest losing trade % 3.70%
Max consecutive winners 12 Max consecutive losers 2
Ratio avg win/avg loss % 0.71 T-Test -2.06
Profit Factor 4.07 Outlier Adjusted Profit Factor 3.45

below the details of next day change, change% of $WFC stock price , when WFC Stock On Balance Volume (OBV) Moved Below Zero

WFC Stock next day change , change % during last 4 years , when ever WFC OBV moves below zero.
Date Next day change Next day change %
06-May-13
18-Mar-13 -0.27 -0.72
12-Mar-13 0.11 0.3
25-Feb-13 -0.04 -0.11
15-Feb-13 -0.02 -0.06
30-Jan-13 -0.14 -0.4
17-Jan-13 -0.1 -0.29
05-Mar-12 -0.83 -2.76
13-Dec-10 -0.38 -1.32
11-Nov-10 -0.62 -2.31
08-Nov-10 -0.87 -3.15
18-Aug-10 -0.9 -3.74
01-Jul-10 -0.29 -1.22
19-Nov-09 -0.42 -1.57
01-Sep-09 -0.12 -0.49
17-Jul-09 0.49 2.08
14-Jul-09 0.85 3.7
30-Jun-09 -0.12 -0.53
11-May-09 -0.78 -3.13

 

use Quant Ideas to find high probability winning trades for tomorrow , with various filters like percentage wins %, Profit Factor , Avg win % etc.  parameters

TradeIdea : VXX Aroon Oscillator turned oversold

VXX Aroon Oscillator turned oversold

VXX Aroon Oscillator turned oversold Stock Chart

iPath S&P 500 VIX Short-Term Futures ETN ( VXX ) , Aroon Oscillator turned oversold trading strategy rules

  • VXX Stock Aroon Oscillator value is less then -70.
  • While VXX Stock’s while yesterday’s Aroon Oscillator reading is above -70
  • GO short at close during the current trading session
  • Buy to cover at the close of next trading session

The period used to calculate Aroon Oscillator is 14.  Aroon Oscillator is arrived at subtracting Aroon down from Aroon up

Below the backtest performance summary for going short when “VXX Aroon Oscillator turned oversold ” trading strategy during the last four years.

Go Short when VXX Aroon Oscillator turned oversold  trading strategy backtest perfromance report
Total number of trades 57 Percent profitable 74%
Number of winning trades 42 Number of losing trades 15
Average profit per trade % 1.2 Median trade -1.52
Average winning trade % 2.66% Average losing trade % 2.88%
Largest winning trade % 6.71% Largest losing trade % 8.61%
Max consecutive winners 11 Max consecutive losers 2
Ratio avg win/avg loss % 0.92 T-Test -2.84
Profit Factor 3.85 Outlier Adjusted Profit Factor 2.96

Below the details of next day change , change % of VXX ETF Price, when VXX Stock’s Aroon Oscillator turned oversold, during last 4 years.

Next day change , change % of VXX ETF Price , when VXX Stock’s Aroon Oscillator turned oversold, during last 4 years.
Date Next day change Next day change %
06-May-13
03-Apr-13 -0.36 -1.77
12-Mar-13 -0.12 -0.57
19-Feb-13 1.81 8.61
15-Jan-13 -0.55 -2.11
12-Dec-12 0.56 1.89
26-Nov-12 0.62 2.08
17-Oct-12 -0.1 -0.3
24-Sep-12 2.72 7.93
14-Sep-12 -0.44 -1.2
17-Aug-12 0 0
09-Aug-12 -0.84 -1.81
29-Jun-12 -3.96 -6.51
18-Jun-12 -1.36 -2
25-Apr-12 -2.36 -3.51
20-Mar-12 -3.84 -4.97
09-Mar-12 -4.28 -4.58
01-Feb-12 -3.2 -3.06
17-Jan-12 -4.28 -3.43
05-Jan-12 -1.96 -1.52
22-Dec-11 3.44 2.54
15-Dec-11 -0.56 -0.36
27-Oct-11 -0.76 -0.52
30-Jun-11 -3.4 -4.02
19-May-11 0.88 0.98
27-Apr-11 -1.12 -1.2
15-Apr-11 2.32 2.11
30-Mar-11 -0.32 -0.27
11-Feb-11 -1.16 -1.03
07-Feb-11 -1.4 -1.22
26-Jan-11 -2.52 -2.08
11-Jan-11 -6.04 -4.32
03-Jan-11 -0.64 -0.44
20-Dec-10 -2.6 -1.73
03-Dec-10 -3 -1.82
22-Nov-10 7.8 4.54
03-Nov-10 -12.96 -6.71
18-Oct-10 7.2 3.21
07-Oct-10 -11.84 -4.58
05-Oct-10 -3.2 -1.22
09-Sep-10 -6.4 -2.11
31-Aug-10 -21.28 -6.06
02-Aug-10 4.8 1.41
22-Jul-10 -6.72 -1.74
14-Jun-10 -27.68 -6.09
16-Mar-10 -12.48 -3.37
22-Feb-10 7.36 1.72
19-Jan-10 -0.16 -0.04
14-Dec-09 -9.28 -1.55
20-Nov-09 -39.04 -5.92
19-Oct-09 -3.36 -0.48
17-Sep-09 15.04 1.89
13-Aug-09 25.76 2.81
06-Aug-09 -39.52 -4.07
22-Jul-09 -28.16 -2.87
11-Jun-09 -22.56 -1.92
15-May-09 -88.8 -6.65
06-May-09 19.68 1.44

use Quant Ideas to find the trades for tomorrow , by filtering percentage wins %, Profit Factor , Avg win % etc.  parameters

First Solar Earnings Day Historical Stock Performance

First Solar Earnings Day Historical Stock Performance

With First Solar ($FSLR) releasing  Q1 2013 earnings After Market Close  today ( 6th May 2013) , below the details of $FSLR stock price reaction post earnings announcement since the stock went to IPO , regardless whether the management beats EPS /Revenue estimates at the earnings announcement.

Over Night Gap Movement for First Solar stock price after earnings are reported

here is how the $FSLR stock price gap’ed before earnings are reported

below the backtest performance summary for holding the $FSLR longs overnight before the day First Solar Earnings are announced 

  • Winners : 13
  • Losers : 12
  • % Winners : 52%
  • Average Change % : 0.66
  • Median Change % : 0.89
  • Maximum Gain % : 22.22
  • Maximum Loss % : -15.91
  • Average Gain %if Winner : 9.14
  • Average Loss % if Loser : -8.53
  • Average Gain % / Average Loss % : 1.07
  • Average Absolute Change% : 8.85

Intraday Movements from Open to Close  Movement for First Solar stock price after earnings are reported

here is how the $FSLR stock price moved from market on open till market on close on the day earnings are reported , assuming one is holding on to $FLSR longs

  • Winners : 9
  • Losers : 16
  • % Winners : 36%
  • Average Change % : 0.18
  • Median Change % : -0.58
  • Maximum Gain % : 8.38
  • Maximum Loss % : -8.58
  • Average Gain %if Winner : 5.75
  • Average Loss % if Loser : -2.96
  • Average Gain % / Average Loss % : 1.95
  • Average Absolute Change% : 3.96

Full day $FSLR stock price movement ( change from previous close to earnings day’s close)

here is $FLSR  stock price moved on the day after earnings are reported ( if earnings are reported AMC, the next trading day change is considered as the earnings day change, for the earnings announcements Before Market Open , change on the earnings day is considered , as the earnings day change)

ps: assuming one is holding on to $FSLR longs here are the trading odds

  • Winners : 10
  • Losers : 15
  • % Winners : 40%
  • Average Change % : 1.18
  • Median Change % : -5.44
  • Maximum Gain % : 30.13
  • Maximum Loss % : -21.81
  • Average Gain %if Winner : 16.51
  • Average Loss % if Loser : -9.04
  • Average Gain % / Average Loss % : 1.83
  • Average Absolute Change% : 12.03

Historical $FSLR Stock Price Movements on Earnings day

Below the table with historical stock price movements of  First Solar inc , on  earnings reporting day

First Solar Earnings Day Stock Price Movements since IPO

that’s almost 12% absolute move if only the option writers ( if the calculations made are not right ) won’t get their hands burnt !! as the moved +/- 5% on 20/25 times post earnings

  • C20: Change from Current Close to Next days’s Open
  • C20 %: Change from Current Close to Next days’s Open in percentage
  • O2C : Change from Current Open to Current Close
  • O2C% : Change from Current Open to Current Close in percentage
  • C2C : Change on the Earnings Reporting day 
  • C2C% : Change on the Earnings Reporting day  in percentage

ps: The earnings data is from earnings.com

pps: Average Absolute Change% data might be useful to gauge the volatility on the earnings day , and or to calculate the straddle pay off factor for options traders

S&P 500 Stocks Seasonality Trends for all Months

S&P 500 Stocks Trends for all Months

Stocks Seasonality

 “Just as the seasons change, so does investment sentiment toward various stocks and industries. The patterns and trends, which would seemingly be widely known and acted upon, repeat over and over and can be exploited by confident investors willing to research when stocks tend to rally and falter.”

S&P 500 Stocks Seasonality Trends

Upon a reader asking us ( who is willing to pay ) , can the seasonality sheet be generated for all Months for all S&P 500 stocks after downloading the S&P 500 Stocks May Seasonality Excel Sheet , over the weekend we did generate an Excel Sheet with S&P 500 Stocks Seasonality Trends for all the months , and is available for download.

Disclaimer: While we don’t advise traders  to base their trading solely on the calendar seasonality alone  , there is evidence that the market and many stocks do indeed follow seasonal patterns. This makes our S&P 500 Stock Seasonality Trends Excel Sheet  a useful addition to every investor’s toolbox.

We went back to 1990 for our  S&P 500 Stock Seasonality Trends  and all the  500 individual stocks. For each stock, we include the following information

  • # : Total number of instances
  • Avg: Average May Monthly Returns in percentage
  • Max : Best May Monthly returns in percentage
  • Min:  Worst May Monthly returns in percentage
  • # Wins : Number of winning May Months ( i’e number of months when returns are positive)
  • Avg if Win : Average % change if the returns in May month are positive
  • # Loss: Number of loosing May Months ( i’e number of months when returns are negative)
  • Avg if Loss : Average % change if the returns in May month are negative
  • % Wins:  Percentage times that May Month had given positive returns.
  • Avg Win/ Avg Loss: Ratio of Average Win % divided by Average Loss% , a.k.a Pay-off Ratio.

Download all Months S&P 500 Stocks Seasonality Trends Excel Sheet.

S&P 500 Stocks Seasonality

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Breakaway Gap Analysis on QQQ

Breakaway Gap Analysis on QQQ

Breakaway gap on QQQ stock chart

extending previous post Breakaway Gap on COMPQ , here the study of Breakaway Gaps on PowerShares $QQQ

Case 1) $QQQ leaves an unfilled full gap of 0.5%

unfilled full gap 0.5% is defined as current day’s low is greater than 0.5% of previous trading session’s high.

below the table with the details of how $QQQ  fared over the next few trading sessions Mar 2000 . ( we are leaving the data from Mar 1999 till Mar 2000 , as we require a minimum sample of 250 to calculate whether the closing is at an yearly high or not , for the next scenarios that we are gong to study)

$QQQ after leaving an un filled full gap of 0.5% since Mar 2000
Trading Odds 1 Day Later 5 Days Later 10 Day Later 20 Days Later 62 Days Later
Winners : 31 30 30 38 34
Losers : 28 29 29 21 24
% Winners : 53% 51% 51% 64% 59%
Average Change % : 0 -0.14 -0.26 -0.1 0.98
Median Change % : 0.04 0.06 0.24 1.87 1.35
Maximum Gain % : 6.04 14.46 13.31 16.97 21.93
Maximum Loss % : -5.6 -12.36 -20.04 -29.84 -29.18
Average Gain %if Winner : 1.06 2.88 4.26 5.07 9.19
Average Loss % if Loser : -1.27 -3.27 -4.93 -9.45 -10.66
Average Gain % / Average Loss % : 0.84 0.88 0.86 0.54 0.86

Case 2) $QQQ leaves an unfilled full gap of 0.5% and closes at 250 day high

$QQQ after leaving an un filled full gap of 0.5% and closes at 52 week High since Mar 2000
Trading Odds 1 Day Later 5 Days Later 10 Day Later 20 Days Later 62 Days Later
Winners : 1 2 2 3 2
Losers : 2 1 1 0 1
% Winners : 33% 67% 67% 100% 67%
Average Change % : 0.06 1.01 0.82 1.28 3.27
Median Change % : 0 1.39 1.45 0.38 4.02
Maximum Gain % : 0.26 2.19 3.33 3.15 6.54
Maximum Loss % : -0.07 -0.54 -2.31 0.31 -0.74
Average Gain %if Winner : 0.26 1.79 2.39 1.28 5.28
Average Loss % if Loser : -0.07 -0.54 -2.31 -0.74
Average Gain % / Average Loss % : 3.53 3.34 1.03 7.17

as the sample size is too small , we will consider

Case 3) $QQQ leaves an unfilled full gap of 0.5% and closes at 20 day high

$QQQ after leaving an un filled full gap of 0.5% and closes at 20 day High since Mar 1999
Trading Odds 1 Day Later 5 Days Later 10 Day Later 20 Days Later 62 Days Later
Winners : 17 17 22 23 20
Losers : 12 12 7 6 8
% Winners : 59% 59% 76% 79% 71%
Average Change % : 0.28 0.85 2.78 4.91 9.55
Median Change % : 0.37 0.94 2.26 4.41 4.84
Maximum Gain % : 6.04 8.62 11.13 19.74 42.48
Maximum Loss % : -3.54 -6.15 -5.45 -5.38 -14.38
Average Gain %if Winner : 1.12 2.79 4.35 6.68 15.75
Average Loss % if Loser : -1 -1.91 -2.13 -1.85 -5.98
Average Gain % / Average Loss % : 1.12 1.46 2.05 3.61 2.64

that’s 80% of the times $QQQ closing higher after 20 trading days with an average change ( including the losses ) of 4.91% .. its 1999 all over again !!

ps: we considered interleaving trades

Breakaway Gap on COMPQ

Breakaway Gap on COMPQ

breakaway Gaps on COMPQ

responding to the poll by Frank @ Zortrades What’s Your Best Guess , here is a look at various characteristics of that Friday gap on NASDAQ Composite ($COMPQ) that we could think of at first glance

  1. it was an unfilled full gap of o.5% length
  2. $COMPQ closed at 52 week high / 20 day high  of-course

here is how $COMPQ fared 1,5,10,20,62 days later to various combos of the above three conditions.

Case 1) $COMPQ leaves an unfilled full gap of 0.5% ( a.k.a normal breakaway gap)

unfilled full gap 0.5% is defined as current day’s low is greater than 0.5% of previous trading session’s  high.

below the table with the details of how $COMPQ fared over the next few trading sessions since Mar 1972.

$COMPQ after leaving an un filled full gap of 0.5% since Mar 1972
Trading Odds 1 Day Later 5 Days Later 10 Day Later 20 Days Later 62 Days Later
Winners : 643 633 600 608 564
Losers : 279 289 322 314 352
% Winners : 70% 69% 65% 66% 62%
Average Change % : 0.32 0.78 0.99 1.84 3.53
Median Change % : 0.34 0.97 1.37 2.55 3.68
Maximum Gain % : 5.28 14.91 15.7 19.91 43.34
Maximum Loss % : -5 -14.88 -18.35 -25.93 -34.07
Average Gain %if Winner : 0.71 2.02 3.11 5.13 10.83
Average Loss % if Loser : -0.6 -1.95 -2.97 -4.54 -8.16
Average Gain % / Average Loss % : 1.19 1.04 1.05 1.13 1.33

Case 2) $COMPQ leaves an unfilled full gap of 0.5% ( a.k.a normal breakaway gap) and closes at 250 day  high( i.e yearly high’s)

below the table with the details of how $COMPQ fared over the next few trading sessions since Mar 1972 , whenever $COMPQ leaves an unfilled gap of more than 0.5% and closes at yearly high 

$COMPQ after leaving an un filled full gap of 0.5% and closes at 52 week high since Mar 1972
Trading Odds 1 Day Later 5 Days Later 10 Day Later 20 Days Later 62 Days Later
Winners : 133 146 132 127 109
Losers : 60 47 61 66 83
% Winners : 69% 76% 68% 66% 57%
Average Change % : 0.25 0.88 1.09 2.45 2.88
Median Change % : 0.26 1.08 1.48 2.65 1.92
Maximum Gain % : 2.49 6.85 10.07 17.34 39.60
Maximum Loss % : -1.56 -7.60 -10.31 -13.01 -27.69
Average Gain %if Winner : 0.53 1.68 2.78 5.23 10.67
Average Loss % if Loser : -0.39 -1.61 -2.57 -2.91 -7.34
Average Gain % / Average Loss % : 1.36 1.05 1.08 1.80 1.45

as you can see in the above in either of the above two cases the expectancy for NASDAQ Composite ($COMPQ) is on the positive side and also more than random chances for holding the $COMPQ for similar trading days.

ps: we considered interleaving trade sample 

Be alert to big minimums on Monday as they tend to reverse !

Be alert to big minimums on Monday as they tend to reverse !

When Vic the Chair writes something , we generally tend to read the article twice at minimum. The 4th point in this 22 Things a Man Should Know About Trading, from Victor Niederhoffer “Be alert to big minimums on Monday as they tend to reverse” caught our attention and we tested that hypothesis on a lazy Sunday

 Be alert to big minimums on Monday as they tend to reverse – trading system study

for the sake of simplicity we took big minimums as a 2% down day on Monday , and here are the trading rules we applied to test that hypothesis.

  • Today is Monday & 
  • $SPY falls by more than 2% in the day 
  • Go Long at close & 
  • exit four days  later ( i.e exit the position by the weekend) 

Below the backtest performance summary for Go long when $SPY falls by more than 2% on Monday and exit four days later

 Long $ SPY and exit by weeknd on a 2% fall on a Monday , backtest report since 2000


Below the traded generated by Long $ SPY and exit by weekend on a 2% fall on a Monday ,  since 2000

Date Loss % Change after 4 days Change % after 4 days
15-Apr-13 -2.32 0.36 0.23
31-Oct-11 -2.41 -0.02 -0.02
03-Oct-11 -2.85 5.60 5.26
08-Aug-11 -6.51 5.64 5.22
17-Aug-09 -2.46 4.32 4.74
22-Jun-09 -2.99 2.37 2.87
15-Jun-09 -2.30 -0.32 -0.37
20-Apr-09 -4.19 2.97 3.87
30-Mar-09 -3.46 5.04 6.95
02-Mar-09 -4.50 -1.54 -2.39
23-Feb-09 -3.57 -0.66 -0.97
12-Jan-09 -2.41 -1.73 -2.18
01-Dec-08 -8.86 5.28 7.09
27-Oct-08 -3.55 11.68 15.34
06-Oct-08 -5.10 -14.71 -15.49
29-Sep-08 -7.84 -0.94 -0.93
22-Sep-08 -2.26 -0.42 -0.38
15-Sep-08 -4.76 4.28 3.95
25-Aug-08 -2.03 1.60 1.40
26-Nov-07 -2.21 6.85 5.47
19-May-03 -2.34 0.91 1.20
31-Mar-03 -2.26 2.85 4.10
24-Mar-03 -3.32 0.01 0.01
10-Mar-03 -2.41 2.30 3.46
09-Dec-02 -2.74 -0.13 -0.18
07-Oct-02 -2.07 4.09 6.36
05-Aug-02 -3.47 6.08 8.97
22-Jul-02 -2.96 2.75 4.13
03-Jun-02 -2.66 -0.83 -0.99
04-Feb-02 -2.50 0.20 0.23
29-Oct-01 -2.60 1.44 1.67
17-Sep-01 -5.23 -5.31 -6.38
02-Apr-01 -2.13 -0.72 -0.79
12-Mar-01 -4.28 -2.19 -2.34
24-Jan-00 -2.85 -3.50 -3.17

with an outlier adjusted factor of more than 2 , and despite loosing -15.5% on the largest single loosing trade , the average profit % per trade stands at 1.6% for a four day holding period , next time do keep an eye on those 2% or more drops on $SPY on Mondays when everyone else is panicking  !!

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Kentucky Derby and Stock Markets

Kentucky Derby and Stock Markets

Kentucky Derby and Stock Markets

inspired the by the post Westminster Kennel Club Stock Market, from Rocky Humbert

inline with the The “Superbowl Indicator” that has earned a dubious place in stock market forecasting lore. we at paststat are looking at “Kentucky Derby Indicator”

Here are the $SPX closing values on 1st Friday ( the day before Kentucky Derby is held , which is usually held on 1st Saturday of the May) , along with Derby Winner and Odds details.

as can be seen from the table below the 1st Friday of May of one year till the next year’s 1st Friday of May ,  SPX is up 71% of the times with an average gains of 8.5% since 1950.

Date Close Derby Winner Odds SPX Change% till next race
03-May-13 1614.42 ?? ?? ??
04-May-12 1369.1 I’ll Have Another 15.3 17.92
06-May-11 1340.2 Animal Kingdom 20.9 2.16
07-May-10 1110.88 Super Saver 8 20.64
01-May-09 877.52 Mine That Bird 50.6 26.59
02-May-08 1413.9 Big Brown 2.4 -37.94
04-May-07 1505.62 Street Sense 4.9 -6.09
05-May-06 1325.76 Barbaro 6.1 13.57
06-May-05 1171.35 Giacomo 50.3 13.18
07-May-04 1098.7 Smarty Jones 4.1 6.61
02-May-03 930.08 Funny Cide 12.8 18.13
03-May-02 1073.43 War Emblem 20.5 -13.35
04-May-01 1266.61 Monarchos 10.5 -15.25
05-May-00 1432.63 Fusaichi Pegasus 2.3 -11.59
07-May-99 1345 Charismatic 31.3 6.52
01-May-98 1121 Real Quiet 8.4 19.98
02-May-97 812.97 Silver Charm 4 37.89
03-May-96 641.63 Grindstone 5.9 26.7
05-May-95 520.12 Thunder Gulch 24.5 23.36
06-May-94 447.82 Go for Gin 9.1 16.14
07-May-93 442.31 Sea Hero 12.9 1.25
01-May-92 412.53 Lil E. Tee 16.8 7.22
03-May-91 380.8 Strike the Gold 4.8 8.33
04-May-90 338.39 Unbridled 10.8 12.53
05-May-89 307.61 Sunday Silence 3.1 10.01
06-May-88 257.48 Winning Colors 3.4 19.47
01-May-87 288.03 Alysheba 8.4 -10.61
02-May-86 234.79 Ferdinand 17.7 22.68
03-May-85 180.08 Spend a Buck 4.1 30.38
04-May-84 159.11 Swale 3.4 13.18
06-May-83 166.1 Sunny’s Halo 2.5 -4.21
07-May-82 119.47 Gato Del Sol 21.2 39.03
01-May-81 132.72 Pleasant Colony 3.5 -9.98
02-May-80 105.58 Genuine Risk 13.3 25.71
04-May-79 100.69 Spectacular Bid 0.6 4.86
05-May-78 96.53 Affirmed 1.8 4.31
06-May-77 99.49 Seattle Slew 0.5 -2.98
07-May-76 101.88 Bold Forbes 3 -2.35
02-May-75 89.22 Foolish Pleasure 1.9 14.19
03-May-74 91.29 Cannonade 1.5 -2.27
04-May-73 111 Secretariat 1.5 -17.76
05-May-72 106.63 Riva Ridge 1.5 4.1
07-May-71 102.87 Canonero II 8.7 3.66
01-May-70 81.44 Dust Commander 15.3 26.31
02-May-69 104 Majestic Prince 1.4 -21.69
03-May-68 98.66 Forward Pass 2.2 5.41
05-May-67 94.44 Proud Clarion 30.1 4.47
06-May-66 87.84 Kauai King 2.4 7.51
07-May-65 89.85 Lucky Debonair 4.3 -2.24
01-May-64 80.17 Northern Dancer 3.4 12.07
03-May-63 70.03 Chateaugay 9.4 14.48
04-May-62 66.24 Decidedly 8.7 5.72
05-May-61 66.52 Carry Back 2.5 -0.42
06-May-60 54.75 Venetian Way 6.3 21.5
01-May-59 57.65 *Tomy Lee (Eng) 3.7 -5.03
02-May-58 43.69 Tim Tam 2.1 31.95
03-May-57 46.34 Iron Liege 8.4 -5.72
04-May-56 48.51 Needles 1.6 -4.47
06-May-55 37.89 Swaps 2.8 28.03
07-May-54 28.65 Determine 4.3 32.25
01-May-53 24.73 Dark Star 24.9 15.85
02-May-52 23.56 Hill Gail 1.1 4.97
04-May-51 22.77 Count Turf 14.6 3.47
05-May-50 18.22 Middleground 7.9 24.97
avearge change% 8.50
% times up 71%

Source for the past Kentucky Derby Winner odds http://horseracing.about.com/od/history/l/blderbywin.htm

Scenario 1 : Kentucky Derby Winner paid odds of equal or less than 5

below the trading odds for $SPX longs till next one year ( or holding till next Kentucky Derby Race is held) if  Kentucky Derby winner paid less than 5 dollars for 1

  • Winners : 18
  • Losers : 14
  • % Winners : 56%
  • Average Change % : 4.58
  • Median Change % : 4.59
  • Maximum Gain % : 37.89
  • Maximum Loss % : -37.94
  • Average Gain %if Winner : 15.31
  • Average Loss % if Loser : -9.22
  • Average Gain % / Average Loss % : 1.66

Scenario 2 : Kentucky Derby Winner paid odds of more than 10 , our Kentucky Derby Indicator 🙂

below the trading odds for $SPX longs till next one year ( or holding till next Kentucky Derby Race is held) if  Kentucky Derby winner paid more than than 10 dollars for 1

  • Winners : 17
  • Losers : 2
  • % Winners : 89%
  • Average Change % : 12.51
  • Median Change % : 13.18
  • Maximum Gain % : 39.03
  • Maximum Loss % : -15.25
  • Average Gain %if Winner : 15.67
  • Average Loss % if Loser : -14.30
  • Average Gain % / Average Loss % : 1.10
  • Average Absolute Change% : 5.23

Our Kentucky Derby Indicator give a buy signal only if the following Horses with odds of more than 10 at the time writing for Kentucky Derby 2013 wins the race

  • Oxbow 25/1
  • Golden Soul 31/1
  • Mylute 14/1
  • Giant Finish 44/1
  • Overanalyze 14/1
  • Palace Malice 26/1
  • Lines of Battle 42/1
  • Itsmyluckyday 11/1
  • Falling Sky 49/1
  • Verrazano 11/1
  • Charming Kitten 32/1
  • Will Take Charge 31/1
  • Frac Daddy 15/1
  • Java’s War 22/1
  • Vyjack 43/1

help on paststat backtest report

help on paststat backtest report

Example of detailed backtest for SLV (iShares Silver Trust)  when the price is up for 3 days in row ->

backtest report screen shot

User can change the lookback period by selecting the “lookback period” drop down menu (can select, over last 1, 2, 3, 4 years)

User can change the exit period by selecting the “exit after “drop down menu (can select, @Next Open, 1, 2, 3,4,5,10,20 days)

User is presented on the right hand side with all the previous instances (dates) when the trading signal triggered in the historical backtesting period. The chg , chg% are the change and change% details for the particular symbol and the next 1,2,3,4,5,10,20 ( depending on the user selected values , default is 1 day) days , for that particular trading strategy.

The detailed backtest report will have the following fields and the description below

Trading Strategy:  This is the Trading Strategy the user is performing the backtest

LookBack Period: can be set to either 1,2,3,4 years, the default value is 4 years if the user doesn’t select any value

Exit After: can be set to either @ Next Open, 1, 2, 3,4,5,10,20 days, the default value is 1 day if the user doesn’t select any value.

If the user selects 2 years as look back period and 5 days as the exit after, values, the back test report will be performed over the last 2 years on the stock for the selected predefined screener , assuming the exit period is after 5 trading days at close.

@Next Open  Option enables the user to test a trading strategy under the assumption that the trade is entered at the next day open and exit at next day close.

Total # Trades: Number of trades generated by the trading strategy on a stock over the last four years, or if the user selects any other look back period like 1,2,3,4 years

Preference: Long or short, based on the Historical Backtesting Report. Arrived at summing all the change% values and if negative usually going short was profitable, if positive going long was profitable.

Percent Profitable: Number of winning trades expressed as percentage.

# Win Trades: Number of winning trades generated by the trading strategy.

# Loss Trades: Number of losing trades generated by the trading strategy.

Avg Trade (%): The average profit per trade (in percentage) for all the trades has been in the last four years, minus commission and slippage.

Average Win Trade (%) : The average profit per winning trades for all the winning trades has been in the last four years, minus commission and slippage. The average Win Trade is sum of the percentage profits for all the winning trades divided by number of winning trades.

Average Loss Trade (%) : The average profit per losing trades for all the losing trades has been in the last four years, minus commission and slippage. The average loss trade is sum of the percentage profits for all the losing trades divided by number of losing trades.

Median % : in probability theory and statistics, median is described as the numerical value separating the higher half of a sample, a population, or a probability distribution, from the lower half. The median of a finite list of numbers can be found by arranging all the observations from lowest value to highest value and picking the middle one. If there is an even number of observations, then there is no single middle value; the median is then usually defined to be the mean of the two middle values.

The median can be used as a measure of location when a distribution is skewed, so, it’s important to view the median profit per trade (and profit percentage per trade as well) to be in trading strategies favour. For example if the average profit per trade is, let’s say 0.5% and median profit per trade is -0.2%, avoid the system.

Largest Win Trade (%): This is more important than the largest single losing trade. Why? Suppose, for example, your total hypothetical profit was 40%, and say 20% of this is attributed to only one trade, and then what you have is a distorted average trade figure. It’s often a good idea to remove such an exceptional single trade from the overall results and re-compute the system performance in order to confirm whether the trading system is actually good enough to trade. In real life trading, be as realistic as possible and be prepared that you may never encounter that largest winning trade derived from the back tested results.

Largest Loss Trade (%): This measure indicates how much of the drawdown the result of a single losing trade is. In real-life trading, this helps you adjust the initial stop loss. For example, if the average losing trade was 1% and the largest single losing trade was 3% as you would readily guess, a good portion of the average losing trade is borne by the largest losing trade. If you had a better way of managing the largest loser, your overall system performance would be considerably better. In real life trading be prepared to encounter an even higher largest loss, than thrown up by back tested results and brace yourself to handle such situation.

Max Consec Wins:  The maximum number of consecutive winning trades generated by the trading strategy.

Max Consec Loss: The maximum number of consecutive winning trades generated by the trading strategy.

Ratio Avg Win / Avg Loss %:  Also referred as Payoff Ratio, Payoff Ratio is the system’s average profit in percentage terms per winning trade, divided by the average loss in percentage terms per losing trade. Unless the trading system has a particularly high win/loss ratio, look for payoff ratios of more than 2.

Profit Factor: Profit factor is the system’s gross profit in rupee terms divided by gross loss in rupee terms. Look for systems that have a profit factor of 2.5, or higher.

Outlier Adj Prof Factor:  With any trading system, you are going to have one or two exceptional wins. The chances of these trades recurring in the future are very slim and shouldn’t be considered in the overall performance summary. It is often a good idea to remove the largest single winning trade while calculating the outlier adjusted profit factor.

T-Test: The t-Test is a simple statistical test that tells you how likely these test results are to have occurred by chance alone. A t-Test of less than 1.6 favors chance, above 1.6 and one is more likely to have found something real – a tradable key idea. The higher the score given (over at least 20 sample size) the more likely one has found a tradable history.

The t-test is calculated as

t -test= square root (n) * (average trade %/ standard deviation of trades %)

A more stringent t-test value to look for is 2.1 for degrees of freedom 25 (or sample size). As the two tailed P value at t-test of 2.1 for a sample size of 25 equals 0.046 which by conventional criteria, is considered to be statistically significant.