A few months ago I posted (here) the distribution of the values of The Bubble Index on a given day (June 27, 2014). Building upon that idea, by creating an index which shows the distribution evolving through time, The Bubble Index Composite is an index which plots the median of the distribution for all monitored stocks. I plan to produce these composite indices for every global market. For example, I have about 1,400 US Stocks which have 1260 and 1764 day indices. Taking the median of these 1,400 values each trading day and plotting gives the following graphs:
Category: markets
DAX – Week Ending May 20, 2013
May 20, 2013
I do not see any chances of there being a bubble in the DAX Index at this time.
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| Figure 1 |
Figure 1 produced with C++ code. DAX Index. Six year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. January 2, 2002 – followed by a 33% drop
2. May 26, 2008 – followed by a 38% drop
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| Figure 2 |
Figure 2 produced with C++ code. DAX Index. Seven year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. January 2, 2002 – followed by a 33% drop
S&P500 and DJIA – Week Ending May 20, 2013
NOTE:
The posts before this one had some errors in the C++ code. I believe I have worked the most of the bugs out and this post contains the best plots to date.
I have been working on code to make a single plot which combines multiple sizes of data. When this has been finished there will only be one plot, not a six and seven year window together.
Also, the weekly data will now begin and end on Mondays, since I obtain my data from finance.yahoo.com.
Week ending May 20, 2013 for the S&P 500.
Based on the figures, there appears to be no indication of a current bubble.
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| Figure 1 |
Figure 1 was produced with C++ code. S&P 500. Six year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. Sept. 28, 1987 — followed by a 31.7% drop
2. August 28, 2000 — followed by a 36.5% drop
3. April 19, 2010 — followed by a 16% drop
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| Figure 2 |
Figure 2 was produced with C++ code. S&P 500. Seven year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
Same lines as Figure 1.
Week ending May 20, 2013 for the Dow Jones Industrial Average.
Based on the figures, there appears to be no indication of a current bubble.
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| Figure 3 |
Figure 3 was produced with C++ code. Dow Jones Industrial Average. Six year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. December 31, 1909 — followed by a 23% drop
2. October 2, 1929 — followed by a 43% drop
3. March 12, 1937 — followed by a 40% drop
4. September 23, 1955 — followed by a quick 8.7% drop and then recovery
5. January 8, 1960 — followed by a 15.6% drop
6. October 2, 1987 — followed by a 31.7% drop
7. July 27, 1990 — followed by a 17% drop
8. September 8, 2000 — followed by a 36% drop
9. October 12, 2007 — followed by a drop in excess of 42%
10. July 8, 2011 — followed by a 16% drop
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| Figure 4 |
Figure 4 was produced with C++ code. Dow Jones Industrial Average. Seven year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
Numbers correspond to same as Figure 3.
KLSE – Week Ending May 10, 2013
May 10, 2013:
Looking at the Figure 1, I do not see any chances of there being a bubble in the KLSE Index at this time.
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| Figure 1 |
Figure 1 produced with C++ code. KLSE Index. Six year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. March 15, 2004 – followed by a 12.5% drop
2. June 19, 2006 – no drop
3. February 12, 2007 – no drop
4. September 22, 2009 – no drop
Bovespa – Week Ending May 10, 2013
May 10, 2013:
I do not see any chances of there being a bubble in the Bovespa Index at this time.
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| Figure 1 |
Figure 1 produced with C++ code. Bovespa Index. Six year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. January 5, 2004 – followed by a 23.5% drop
2. March 26, 2008 – followed by a 57% drop
3. January 4, 2010 – followed by a quick 10.7% drop and then recovery
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| Figure 2 |
Figure 2 produced with C++ code. Bovespa Index. Seven year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. January 5, 2004 – followed by a 23.5% drop
2. November 12, 2007 – followed by a 12.4% drop
3. March 26, 2008 – followed by a 57% drop
4. January 4, 2010 – followed by a quick 10.7% drop and then recovery
5. January 10, 2011 – followed by a 28% drop
DAX – Week Ending May 10, 2013
May 10, 2013:
I do not see any chances of there being a bubble in the DAX Index at this time.
 |
| Figure 1 |
Figure 1 produced with C++ code. DAX Index. Six year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. January 2, 2002 – followed by a 33% drop
2. December 1, 2003 – no drop
3. May 2, 2006 – followed by a quick 12% drop and recovery
4. May 26, 2008 – followed by a 38% drop
5. January 4, 2010 – followed by a quick 10% drop and recovery
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| Figure 2 |
Figure 2 produced with C++ code. DAX Index. Seven year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. May 21, 2001 – followed by a 39% drop
2. January 2, 2002 – followed by a 33% drop
3. December 1, 2003 – no drop
4. May 2, 2006 – followed by a quick 12% drop and recovery
5. January 4, 2010 – followed by a quick 10% drop and recovery
6. July 4, 2011 – followed by a 30% drop
FTSE – Week Ending May 10, 2013
May 10, 2013:
I do not see any chances of there being a bubble in the FTSE Index at this time.
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| Figure 1 |
Figure 1 produced with C++ code. FTSE Index. Six year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. Februray 15, 1996 – followed by a small 4.8% decrease and then quick recovery
2. August 29, 2000 – followed by a 20% drop
3. April 18, 2006 – followed by a quick 8.7% drop and quick recovery
4 . January 4, 2010 – followed eventually by a 12.6% drop
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| Figure 2 |
Figure 2 produced with C++ code. FTSE Index. Seven year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. September 29, 1997 – followed by a quick 11% drop
2. July 12, 1999 – followed by a quick 9.5% drop
3. June 4, 2001 – followed by a 25% drop
4. January 4, 2010 – followed by a 12% drop
5. July 4, 2011 – followed by a 15.9% drop
6. September 10, 2012 – followed by a small 5% drop and quick recovery
Nikkei – Week Ending May 10, 2013
May 10, 2013:
I do not see any chances of there being a bubble in the Nikkei Index at this time. Although, there appears to have been a recent bubble.
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| Figure 1 |
Figure 1 produced with C++ code. Nikkei Index. Seven year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. June 24, 1996 – followed by a 23.2% drop
2. May 20, 2002 – followed by a 35.7% drop
3. September 29, 2008 – followed by a 34% drop
4. March 29, 2010 – followed by a 20% drop
5. March 12, 2012 – followed by a 16.7% drop
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| Figure 2 |
Figure 2 produced with C++ code. Nikkei Index. Six year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. May 1, 1995 – followed by a 15% drop
2. November 18, 1996 – followed by a 18% drop
3. September 17, 2001 – exact bottom of downturn (or perhaps related to Sept. 11, 2001)
4. March 29, 2010 – followed by a 20% drop
5. March 12, 2012 – followed by a 16.7% drop
S&P500 and DJIA – Week Ending May 10, 2013
May 10, 2013:
Looking at the following graphs, I believe only Figure 1 forecasts any bubble. Towards the end of the index there lies strong spike and decline. However, this signal is not present in the other figures.
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| Figure 1 |
Figure 1 produced with C++ code. S&P 500. Seven year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. January 17, 1966 — followed by a 20.9% drop
2. January 15, 1973 — followed by a drop in excess of 23%
3. December 27, 1976 — followed by a drop in excess of 14.7%
4. March 26, 1984 — followed by a 11.8% drop
5. Sept. 28, 1987 — followed by a 31.7% drop
6. July 9, 1990 — followed by a 17.4% drop
7. August 28, 2000 — followed by a 36.5% drop
8. October 1, 2007 — followed by a drop in excess of 42%
9. July 18, 2011 — followed by a 16.5% drop
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| Figure 2 |
Figure 2 was produced with C++ code. S&P 500. Six year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. Sept. 28, 1987 — followed by a 31.7% drop
2. August 28, 2000 — followed by a 36.5% drop
3. April 19, 2010 — followed by a 16% drop
 |
| Figure 3 |
Figure 3 was produced with C++ code. Dow Jones Industrial Average. Six year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. December 31, 1909 — followed by a 23% drop
2. October 2, 1929 — followed by a 43% drop
3. March 12, 1937 — followed by a 40% drop
4. January 8, 1960 — followed by a 15.6% drop
5. October 2, 1987 — followed by a 31.7% drop
6. July 27, 1990 — followed by a 17% drop
7. September 8, 2000 — followed by a 36% drop
8. October 12, 2007 — followed by a drop in excess of 42%
 |
| Figure 4 |
Figure 4 was produced with C++ code. Dow Jones Industrial Average. Seven year window of data. Every data point is a new week. Every peak in the market is represented by a red vertical line.
1. December 31, 1909 — followed by a 23% drop
2. October 2, 1929 — followed by a 43% drop
3. March 12, 1937 — followed by a 40% drop
4. September 23, 1955 — followed by a quick 8.7% drop and then recovery
5. January 8, 1960 — followed by a 15.6% drop
6. October 2, 1987 — followed by a 31.7% drop
7. July 27, 1990 — followed by a 17% drop
8. September 8, 2000 — followed by a 36% drop
9. October 12, 2007 — followed by a drop in excess of 42%
10. July 8, 2011 — followed by a 16% drop