$SPY , $TLT during the last five days of August

$SPY , $TLT during the last five days of August

August last 5 trading days $SPY Seasonality

below the trading odds for the next 1/2/3/4/5 trading days , for the longs for going long at close on 5 trading days before the last trading day of August ( 22nd Aug 2014 in this year’s case)

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off Max Loss % PF OAPF
t+1 21 12 57.1 -0.10 0.06 0.37 -0.73 0.51 -2.03 0.55 0.40
t+2 21 8 38.1 -0.43 -0.12 0.45 -0.97 0.46 -3.10 0.18 0.14
t+3 21 11 52.4 -0.39 0.06 0.81 -1.71 0.47 -5.03 0.49 0.30
t+4 21 9 42.9 -0.78 -0.22 0.92 -2.05 0.45 -5.38 0.30 0.15
t+5 21 9 42.9 -0.97 -0.25 1.23 -2.61 0.47 -12.13 0.34 0.20

slightly bearish !

ps: PF: Profit Factor, and OAPF is the outlier adjusted profit factor ( which is profit factor recalculated after removing the maximum winner )

$SPY historical instances from 5 trading day’s before the last trading day of August , since 1993

Date $SPY t+1% t+2% t+3% t+4% t+5%
22-Aug-14 199.19 ?? ?? ?? ?? ??
23-Aug-13 163.41 -0.37 -1.98 -1.63 -1.47 -1.78
24-Aug-12 135.75 0.02 -0.08 0 -0.72 -0.25
24-Aug-11 110.92 -1.52 -0.1 2.78 3.05 3.5
24-Aug-10 97.18 0.39 -0.29 1.26 -0.22 -0.22
24-Aug-09 93.03 0.19 0.2 0.43 0.41 -0.48
22-Aug-08 114.07 -2.03 -1.74 -0.79 0.41 -0.67
24-Aug-07 127.92 -0.93 -3.1 -1.2 -1.47 -0.49
24-Aug-06 109.8 0.12 0.6 0.71 0.77 0.76
24-Aug-05 100.78 0.36 -0.33 0.45 -0.09 1.18
24-Aug-04 90 0.68 0.68 0.99 0.16 0.69
22-Aug-03 80.1 0.16 0.34 0.37 1 1.67
23-Aug-02 74.67 0.7 -0.47 -2.64 -2.6 -2.99
24-Aug-01 92.68 -0.59 -2.05 -2.92 -4.79 -4.09
24-Aug-00 116.53 -0.04 0.3 0.32 -0.64 0.68
24-Aug-99 104.41 1.03 -0.18 -1.39 -3.21 -3.58
24-Aug-98 82.27 0.23 -0.34 -5.03 -5.38 -12.13
22-Aug-97 68.75 -0.36 -1.83 -1.24 -2.75 -2.36
23-Aug-96 48.79 -0.49 -0.12 -0.29 -1.27 -2.3
24-Aug-95 40 0.55 0.18 0.43 0.65 0.75
24-Aug-94 32.84 -0.27 1.16 1.1 1.34 1.1
24-Aug-93 31.39 0.06 0.13 0.06 0.48 0.73

$TLT trading odds for longs for the next 1/2/3/4/5 trading days , for going long on 5 trading days before the last trading day of August ( 22nd Aug 2014 in this year’s case) 

Exit # Wins % Wins Avg% Med% Avg Win % Avg Loss % Pay Off Max Loss % PF OAPF
t+1 12 10 83.3 0.34 0.42 0.52 -0.56 0.93 -0.78 6.01 4.56
t+2 12 10 83.3 0.75 0.77 0.95 -0.27 3.60 -0.53 29.93 22.68
t+3 12 9 75.0 0.27 0.43 0.66 -0.91 0.73 -2.24 2.03 1.63
t+4 12 11 91.7 1.03 1.07 1.16 -0.36 3.22 -0.36 30.15 23.59
t+5 12 12 100.0 1.25 1.18 1.25 NA NA NA NA NA

$TLT historical instances from 5 trading day’s before the last trading day of August , since 1993

Date $TLT t+1% t+2% t+3% t+4% t+5%
22-Aug-14 117.29 ?? ?? ?? ?? ??
23-Aug-13 101.01 0.5 1.76 0.94 1.75 1.63
24-Aug-12 117.99 0.58 0.83 0.39 0.91 2.33
24-Aug-11 97.52 1.09 2.08 0.67 2.29 0.71
24-Aug-10 94.78 -0.33 0.61 -2.24 -0.36 0.75
24-Aug-09 80.69 0.57 1.03 0.63 1.09 1.19
22-Aug-08 75.69 1 1.1 1.27 1.27 0.82
24-Aug-07 68.21 0.53 0.7 0.43 1.1 1.17
24-Aug-06 64.76 0.14 0.23 0.37 0.63 0.88
24-Aug-05 66.66 0.32 0.29 0.42 1.05 1.91
24-Aug-04 58.24 0.34 0.91 0.84 1.32 1.94
22-Aug-03 53.64 -0.78 0 -0.45 0.58 0.34
23-Aug-02 52.49 0.1 -0.53 -0.04 0.76 1.37

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momentum investing case for Indian Markets

momentum investing case for Indian Markets

with the new Government in place in India , below the case for momentum investing in India

momentum investing in india

image courtesy : http://www.american.com/archive/2009/november/investing-in-india-art-of-the-impossible

here are Nifty Index ( the favored benchmark for Indian markets ) returns from May end till Dec End , since 1994 

data source : http://nseindia.com/products/content/equities/indices/historical_index_data.htm

  • Winners : 11
  • Losers : 8
  • % Winners : 58%
  • Average Change % : 11.29
  • Median Change % : 6.29
  • Maximum Gain % : 86.71
  • Maximum Loss % : -39.24
  • Average Gain %if Winner : 30.19
  • Average Loss % if Loser : -14.69
  • Payoff Ratio 2.05

now with the Indian market returning positive returns at the End of May , indeed the largest India focused India ETF ,  by volume and asset size ,  $EPI (WisdomTree India Earnings Fund) had returned 27% YTD) ,

below the Nifty Index Returns , from May End till Dec End ,  since 1994 , when the Year-To-Date Returns were positive by May end

  • Winners : 8
  • Losers : 2
  • % Winners : 80%
  • Average Change % : 16.56
  • Median Change % : 18.41
  • Maximum Gain % : 42.90
  • Maximum Loss % : -17.51
  • Average Gain %if Winner : 22.94
  • Average Loss % if Loser : -8.96
  • Payoff Ratio 2.56

#FYI all the last 8 instances fared positive by Dec end , when by the May end YTD returns were positive , since 1997 ..

caveats :

  • we are using Index, which is not adjusted for dividends , usually about 1-1.5%
  • currency movements may affect the actual results

Below the Nifty Index returns from May end till Dec End , since 1994

Year Nifty Start of the Year End of the Year YTD % EOY %
2014 ~ 7263.55 6304 ?? 15.22 ??
2013 5985.95 5905.1 6304 1.37 5.31
2012 4924.25 4624.3 5905.1 6.49 19.92
2011 5560.15 6134.5 4624.3 -9.36 -16.83
2010 5086.3 5201.05 6134.5 -2.21 20.61
2009 4448.95 2959.15 5201.05 50.35 16.91
2008 4870.1 6138.6 2959.15 -20.66 -39.24
2007 4295.8 3966.4 6138.6 8.30 42.90
2006 3071.05 2836.55 3966.4 8.27 29.15
2005 2087.55 2080.5 2836.55 0.34 35.88
2004 1483.6 1879.75 2080.5 -21.07 40.23
2003 1006.8 1093.5 1879.75 -7.93 86.71
2002 1028.8 1059.05 1093.5 -2.86 6.29
2001 1167.9 1263.55 1059.05 -7.57 -9.32
2000 1380.45 1480.45 1263.55 -6.75 -8.47
1999 1132.3 884.25 1480.45 28.05 30.75
1998 1063.15 1079.4 884.25 -1.51 -16.83
1997 1050.9 899.1 1079.4 16.88 2.71
1996 1089.92 908.53 899.1 19.97 -17.51
1995 997.4 1182.28 908.53 -15.64 -8.91
1994 1187.19 1083.74 1182.28 9.55 -0.41

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Major US Indices December Monthly Seasonality Since 1990.

Major US  Indices December Monthly Seasonality Since 1990.

Below the details of historical average returns of 26 Major US Indices during the month of December since 1990 , to get an idea about December month Seasonality of various major indices.

We’ve also included the percentage of times that the Index had positive returns during the month of December , as a result, investors can get a good idea of which areas of the market December has been good.

As shown in the table below

  • Best performing index in terms average for December is NASDAQ Biotechnology , with average gains of 4.44% for the month of December
  • 13-WEEK TREASURY BILL( Code:IRX) had wild swings in December , with gains of 500% and loss of 100%
  • NYSE ARCA NETWORKING INDEX is the worst performing sector in December in terms of average gains , with an average gains of -0.23%
  • S&P 500 Index average returns in December month are 1.92% , with 20/24 wins  , i.e 83% times giving positive returns

Below the big table with December Month Seasonality of 26 Major Indices since 1990 ( pls click the image to see the full table)

26 Major Indices December Month Seasonality since 1990

Definitions:

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

check out Day of Month Seasonality  for December from MarketSci

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Major US Indices November Monthly Seasonality Since 1990.

Major US  Indices November Monthly Seasonality Since 1990.

Below the details of historical average returns of 26 Major US Indices during the month of November since 1990 , to get an idea about November month Seasonality of various major indices.

We’ve also included the percentage of times that the Index had positive returns during the month of November , as a result, investors can get a good idea of which areas of the market November has been good.

As shown in the table below

  • Best performing index in terms average for November is INTERACTIVE WEEK INTERNET INDEX , with average gains of 5.14% for the month of November
  • 13-WEEK TREASURY BILL( Code:IRX) is the worst performing asset in the November with an average loss of -3.67%
  • Treasury Yield 30 Years  is the worst performing sector in November , from percentage wins perspective. ( lost 65% times)
  • S&P 600 ( code: SML) is the best performing sector in November, from percentage wins perspective ( gained 78% times)
  • S&P 500 Index average returns in November month are 1.35% , with 15/23 wins  , i.e 65% times giving positive returns

Below the big table with November Month Seasonality of 26 Major Indices since 1990 ( pls click the image to see the full table)

26 Major Indices November Month Seasonality since 1990

Definitions:

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

check out Day of Month Seasonality for November  from MarketSci

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Announcing Seasonality Feature

Seasonality Feature From Paststat

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.”

its bull markets you know !! and the team at @paststat is charged up , and we are pleased to release new additional feature “Seasonality

do check out the feature here -> http://paststat.com/stat/seasonality.php

pls do let us know the improvements and suggestions on the same

@paststat

bullish high odds seasonal trades from S&P 500 Stocks for September

S&P 500 Stocks bullish high odds seasonal trades for September

Four_seasons

image courtesy : ashdenizen.blogspot.com/2008/05/there-are-various-blogs-discussing.html

here are three S&P 500 Stocks that meet the following criteria of high odds seasonal trades of gaining in the month of September from seasonal perspective.

With the aid of ” S&P 500 Stocks September Month Seasonality” Excel Working Sheet

  • Current S&P 500 Constituents and the stock is trading since 1990 ( or with a minimum trading history of 20 years)
  • The Average gain in August is at-least 2%
  • Percentage win rate for August is at-least 75 %
  • Pay-Off Ratio ( defined as Avg win% divided by Avg Loss% ) more than 1

below the three most bullish S&P 500 stocks which qualifies for the bullish high odds seasonal trades for September

Symbol Company Name # Avg Max Min # Wins Avg if Win # Loss Avg if Loss % Wins Avg Win/ Avg Loss
ACT Actavis, Inc. 20 5.05 29.31 -14.8 15 8.46 5 -5.19 75 1.63
ESRX Express Scripts Inc. 21 4.85 22.38 -21.03 16 8.88 5 -8.06 76 1.1
PAYX Paychex, Inc. 23 6.67 35.71 -15.01 18 10.4 5 -6.7 78 1.55
PDCO Patterson Companies Inc. 20 6.51 24.12 -6.52 16 9.01 4 -3.48 80 2.59
ROP Roper Industries Inc. 21 5.33 32.28 -12.22 16 8.91 5 -6.11 76 1.46
SO Southern Company 23 2.53 11.25 -4.92 18 3.69 5 -1.65 78 2.24

have you downloaded yet , “S&P 500 Stocks September Month Seasonality” Excel Sheet 

High Odds Seasonal Trades definitions

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

warning ! Seasonality alone never justifies a trade all by itself, but it deserves as yet another tool in trader’s toolbox for market timing .

pls do us a favor by tweeting to us  http://clicktotweet.com/09aAf

after downloading   S&P 500 Stocks September Seasonality Excel Sheet

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$SPY Returns Around Labor Day

$SPY Returns Around Labor Day

Vintage-Labor-Day-Trade-Card-2

image courtesy : http://purplesageoriginals.blogspot.com/2012/09/labor-day.html

responding to query from on twitter time line from Phoenix Rising

below the trading odds for the longs, for holding during the week before Labor Day holiday ( i.e from  23 Aug 2013 close 30 Aug 2013 , in 2013 case)

  • Winners : 9
  • Losers : 11
  • % Winners : 45%
  • Average Change % : -0.49
  • Median Change % : -0.18
  • Maximum Gain % : 3.77
  • Maximum Loss % : -5.44
  • Average Gain %if Winner : 1.22
  • Average Loss % if Loser : -1.89
  • Average Gain % / Average Loss % : 0.64

five the six last years pre-labor-day weeks were marginally down

below the $SPY returns during each day of trading, and for the whole week , prior to the Labor Day Holiday

$SPY during pre Labor holiday week since 1993

below the $SPY returns during each day of trading, and for the whole week , post Labor Day Holiday since 1993.

$SPY post Labor Day holiday week since 1993

the Friday during the Labor Day week has a good winning odds for the longs , below the trading odds for the Friday ( , long at close on 5 Sep 2013 and exit at 6 Sep 2013 close)

  • Winners : 14
  • Losers : 6
  • % Winners : 70%
  • Average Change % : 0.46
  • Median Change % : 0.39
  • Maximum Gain % : 2.06
  • Maximum Loss % : -0.68
  • Average Gain %if Winner : 0.80
  • Average Loss % if Loser : -0.35
  • Average Gain % / Average Loss % : 2.31
  • Average Absolute Change% : 0.74

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bearish high odds seasonal trades from S&P 500 Stocks for August

S&P 500 Stocks bearish high odds seasonal trades for August

Four_seasons

image courtesy : ashdenizen.blogspot.com/2008/05/there-are-various-blogs-discussing.html

here are six S&P 500 Stocks that meet the following criteria of high odds seasonal trades of loosing in the month of August from seasonal perspective.

With the aid of ” S&P 500 Stocks May Month Seasonality” Excel Working Sheet

  • Current S&P 500 Constituents and the stock is trading since 1990 ( or with a minimum trading history of 20 years)
  • The Average gain in August is less than at-least -2% ( well -1.97 , to accommodate Union Pacific Corporation stock’s August  average performance )
  • Percentage win rate for August is less than or equal to 20% , in other word the loosing rate is more than 70%
  • Pay-Off Ratio ( defined as Avg win% divided by Avg Loss% ) less  than 1

below the six most bearish S&P 500 stocks which qualifies for the “bearish  high odds seasonal trades “ for August

Symbol Company Name # Avg Max Min # Wins Avg if Win # Loss Avg if Loss % Wins Avg Win/ Avg Loss
F Ford Motor Co. 23 -4.68 25.58 -21.69 7 7.71 16 -10.11 30 0.76
FLIR FLIR Systems, Inc. 20 -6.51 15.47 -37.25 4 10.6 16 -10.79 20 0.98
LUV Southwest Airlines Co. 23 -4.84 6.81 -18.8 5 4.1 18 -7.32 22 0.56
NUE Nucor Corporation 23 -3.6 13.83 -17.41 7 4.85 16 -7.29 30 0.66
STJ St. Jude Medical Inc. 23 -2.6 8.96 -27.69 7 4.46 16 -5.68 30 0.78
UNP Union Pacific Corporation 23 -1.97 6.33 -10.37 7 3.17 16 -4.22 30 0.75

have you downloaded yet , “S&P 500 Stocks August Month Seasonality” Excel Sheet 

High Odds Seasonal Trades definitions

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

warning ! Seasonality alone never justifies a trade all by itself, but it deserves as yet another tool in trader’s toolbox for market timing .

pls do us a favor by tweeting to us  http://clicktotweet.com/09aAf

after downloading   S&P 500 Stocks August Seasonality Excel Sheet

you might want to consider subscribing to our daily quant rants email  !

Subscribe to Free-1-week-trail of Quant Alerts !!

2 trading days before July Opex week is bit bullish for $SPY

$SPY performance 2 trading days before July Opex week

Caution :  Seasonality based trades never justifies a trade all by itself, but we think it deserves to be one of many tools in the trader’s toolbox.

Below the $SPY returns , assuming one is holding on to longs , 2 trading days before July Opex week since 1993 ( typically the Wednesday during the July Opex Week , if Friday is not holiday , otherwise it is Tuesday)

  • Winners : 12
  • Losers : 8
  • % Winners : 60%
  • Average Change % : 0.40
  • Median Change % : 0.20
  • Maximum Gain % : 2.92
  • Maximum Loss % : -1.10
  • Average Gain %if Winner : 0.98
  • Average Loss % if Loser : -0.48
  • Average Gain % / Average Loss % : 2.04

Not a high hit rate in terms of winners , bu the payoff ratio ( average win% divided by average loss%) at little more than 2, favors the bulls

Below the table with $SPY perfromance on each day during the July Opex week since 1993.

$SPY performance during July Opex week

t-1, is the change% for $SPY , one trading day before the opex day , similarly t-2 is the $SPY perfromance during two trading days before Opex day ( usually Wednesday) 

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S&P 500 Stocks July Seasonality Excel Sheet

S&P 500 Stocks July Seasonality Excel Sheet

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 July Seasonality Excel Sheet 

Contains July Month Seasonality for all the S&P 500 Stocks since 1990 , with the following columns as shown below

Sample First 10 Columns ( in alphabetical order)  in the S&P  500 Stocks July  Seasonality Excel Sheet

Symbol Company Name # Avg Max Min # Wins Avg if Win # Loss Avg if Loss % Wins Avg Win/ Avg Loss
A Agilent Technologies Inc. 13 -6.7 14.31 -44.74 4 10.22 9 -14.21 31 0.72
AA Alcoa, Inc. 23 2.18 17.46 -17.92 13 8.29 10 -5.78 57 1.44
AAPL Apple Inc. 23 5 27.15 -29.76 14 14.15 9 -9.25 61 1.53
ABC AmerisourceBergen Corporation 18 0.77 15.92 -11.85 10 7.01 8 -7.04 56 1
ABT Abbott Laboratories 23 0.96 12.11 -9.84 11 6.08 12 -3.74 48 1.63
ACE ACE Limited 20 -0.56 28.32 -17.73 9 7.09 11 -6.81 45 1.04
ACN Accenture plc 12 0.29 10.46 -13.14 7 4.49 5 -5.61 58 0.8
ACT Actavis, Inc. 20 0.93 17.65 -16.62 9 8.34 11 -5.13 45 1.63
ADBE Adobe Systems Inc. 23 -2.99 23.77 -23.8 11 8.2 12 -13.25 48 0.62
ADI Analog Devices Inc. 23 -2.52 18.28 -18.86 11 7.53 12 -11.73 48 0.64

Definitions

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

warning ! Seasonality alone never justifies a trade all by itself, but it deserves as yet another tool in trader’s toolbox for market timing .

download the S&P 500 Stocks July Seasonality Excel Sheet

check out Day of Month Seasonality for July from MarketSci

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