INEFFICIENT MARKET HYPOTHESIS
VINDICATED BY MOON SUN CYCLES


"The experience of being proven completely wrong is salutary. 
No economist should be denied it and none are"
.   John K Galbraith.


David McMinn

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Introduction  

Efficient Market Hypothesis (EMH) was originally proposed in the 1960s in a PhD by Eugene Fama, who believed that investors made well informed and intelligent decisions. Markets were considered to be efficient and rational in determining financial prices. At any given time, individual stocks were regarded to be priced at the correct level based on all known information. This was supposed to be ensured by the ready availability of ample information and by the vast number of rational investors avidly following each stock. Prices moved with the influx of new information. Free markets, so the hypothesis goes, could only be inefficient if investors ignored price sensitive data. Whoever used this data could make large profits and the market would readjust becoming efficient once again.

Random Walk. Economists commonly considered financial crises to occur as stray events. For example, Kindleberger (1996) viewed financial crises to be “random manifestations of mob psychology and mass hysteria rooted in the individual and collective psyche”. The timing of panics was widely deemed as being related to the chance occurrence of external events such as bankruptcies, interest rate rises and war, which change the perception of risk. According to this paradigm, investors by definition could not beat a random market, as prices could never be predicted from one moment to the next.

The random walk - efficient market theory reached its ascendancy in economics during the 1970s and 1980s, but has since suffered severe set backs. Researchers have uncovered numerous stock market anomalies that contradicted the hypothesis. The evidence is increasingly in favour of an Inefficient Market Hypothesis (IMH), which would more closely align with market reality. In the 1990s, behavioural finance discredited the theory of the 'rational investor' making informed market decisions. In the real world, investors are not rational and they consistently make serious errors in their judgments, a view supported by a multitude of studies. 

Moon Sun Hypothesis. There has emerged the 9/56 year cycle in the timing of historic financial panics, which demolished the concept of random markets. Financial activity is hypothesised to be mathematically structured in time fluctuating in tune with Moon Sun cycles. Numerous correlates can be produced to support this speculation. It is not a question of whether the Moon and the Sun influence market trading but rather to what extent. 

The first academic papers supporting a lunar phase effect in market activity were published by Yuan et al (2001) & Dichev & James (2001). Stock market indices tended to rise on a new Moon and fall on a full Moon with statistical significance something that applied to most world markets. Numerous follow up papers generally supported a lunar phase effect (refs). Alas, virtually all academic studies have been confined to lunar phase, even though such an approach is simplistic. Other Moon Sun factors could also prove highly influential, such as the lunar nodes, apogee - perigee axis (apsides), diurnal cycles and so forth.

The 9/56 Year Panic Cycle     

The 9/56 year cycle consists of a grid with intervals of 56 years on the vertical (called sequences) and multiples of 9 years on the horizontal (called subcycles). Major US and Western European financial crises cluster with statistical significance in this grid as shown in Table 1. Of the 30 panics listed by Kindleberger (Appendix b, 1996) for the 1760 - 1940 era, 16 occurred in the 9/56 year grid as presented in Table 1 (significant p < .001). Most major financial panics in US history show up in this pattern - 1792, 1819, 1837, 1857, 1873, 1884, 1893, 1920, 1929, 1931, 1933, 1987, 1998 and 2007 (ref).

Table 1
9/56 YEAR CYCLE AND FINANCIAL CRISES 1760 - 2020
Year beginning March 1

Sq
52

Sq
05

 

 

Sq
32

Sq
41

Sq
50

Sq
03

Sq
12

Sq
21

 

 

Sq
48

Sq
01

 

 

 

 

 

 

 

 

 

 

 

 

 

1761

 

 

 

 

 

 

 

1763

1772

1781

1790

1799

1808

1817

 

1765

1774

1783

1792

1801

1810

1819

1828

1837

1846

1855

1864

1873

1812

1821

1830

1839

1848

1857

1866

1875

1884

1893

1902

1911

1920

1929

1868

1877

1886

1895

1904

1913

1922

1931

1940

1949

1958

1967

1976

1985

1924

1933

1942

1951

1960

1969

1978

1987

1996

 2005

 

 

 

 

1980

1989

1998

2007

  

 

 

 

 

 

 

 

 

 

The 56 year sequences are separated by an interval of 9 years.
Years in bold contained major financial crises as listed by Kindleberger (Appendix B, 1996) in the year commencing March 1.
Source: McMinn (1995).  

The obvious question arises as to what activates this cycle? The 9/56 year grid correlates perfectly with Moon Sun cycles. Critical events falling in the the same 56 year sequence will have the lunar north node sited in a narrow sector on the ecliptic with no exceptions (1st harmonic). Any events clustering in the 9/56 year grid will have the lunar north node sited in two sectors, approximately 180 degrees opposite on the ecliptic with no exceptions (1st and 2nd harmonics). Events happening at around the same time of year and in the same 9/56 year grid will have apogee in three sectors on the ecliptic 120 degrees apart with no exceptions (3rd harmonic). This outcome arises due to the very close alignment of several lunisolar cycles at 9.0 and 56.0 solar years (McMinn, 2004, 2010a). The finding was extraordinary and could not possibly arise in a random or efficient market.  

NB: The lunar nodes are two imaginary points where the ecliptic (plane of Earth's orbit around the Sun) is cut by the plane of Moon's orbit around the Earth. The north node occurs where the Moon crosses the ecliptic from south to north. Additionally, apogee is that point in the Moon's orbit that is greatest distance from the Earth. The lunar nodes and the apogee - perigee axis (apsides) are very important in terrestrial tidal harmonics.

The 9/56 year cycle may also be relevant in cycles of other phenomena, such as earthquakes (eg: California, record earthquakes, Chile-Peru, Japan-Kamchatka, Alaska and South East Asia), volcanic eruptions (Alaska) and Category 5 Atlantic hurricanes. Since 1870, world mega quakes (mag 8.6) occurred selectively in 54/56 year grids. How weak Moon Sun tidal effects can trigger such critical events remains unknown.   

Lunar Nutation Cycle  

Diagram 1
gives the ecliptic position of the lunar north (ascending) node at the time of major financial crises listed by Kindleberger (Appendix B, 1996) for the 1760-1940 period. The north node never appeared between 255 & 340 Eº, a segment of 85 degrees. Financial crises were also most likely to occur in two sectors 180 degrees opposite in the ecliptic - between 000 Eº and 90 Eº as well as between 180 Eº and 270 Eº

NB: In this paper, Eº represented degrees on the ecliptic circle, while Aº denoted angular degrees between the Moon and Sun (lunar phase). This was to avoid confusion between two different concepts. 

Diagram 1
NORTH NODE ECLIPTICAL POSITION & FINANCIAL CRISES
1760 - 1940

Source of Panic Data. Kindleberger, C P. 1996.
Manias, Panics & Crashes. John Wiley & Sons. Appendix B.
Source: McMinn, D. (1995).

Annual One Day Falls

An amazing correlate arises between lunar phase and the timing of US stock market panics. Diagram 2 shows the relationship between lunar phase and annual one day (AOD) falls over -4.50% for the Dow Jones Industrial Average (DJIA) from 1915 to 1999. Lunar phase nearly always appeared in two segments - 085-195 Eº and 285-350 Eº - which are approximately 180 degrees opposite in the angular circle. The only anomaly took place in 1930. This diagram was first presented by McMinn (2000).     

NB: The annual one day fall is the biggest one day percentage decline in the DJIA in the year commencing March 1. The corresponding AOD rise is the biggest percentage one day DJIA rise in year beginning March 1. These represent the biggest one day shifts in investor sentiment during a given year.

Diagram 2
LUNAR PHASE & MAJOR DJIA AOD FALLS ≥ -4.50%
1915 - 1999

Source: McMinn, D. 2000. Lunar Phase & US Crashes. 
The Australian Technical Analysts Assoc Jour. p 20-29, Jan/Feb.


The following events may be included, if the time frame was extended from 1910 to 2015.

Date

DJIA Event

DJIA % AOD Fall

Phase
Angle

Jan 20, 1913

AOD fall.

-4.90

153

Jul 30, 1914

Outbreak of WW 1.

-6.63

099

Apr 14, 2000

After Greenspan Bubble.

-5.64

130

Sep 11, 2001

WTC attack.

(a)

281

Jul 23, 2002

AOD fall.

-4.64

122

Jan 21, 2008

Worldwide market panics.

 (b)

169

Oct 15, 2008

Black October.

-7.85

191

Aug 08, 2011

Euro distress. 

-5.55

118

(a) Market did not open on the day of the terrorist attack and was closed for four trading days.
(b) Worldwide stock market panics occurred on this day. However, the US stock market was closed, due to the Martin Luther King Jr holiday. Even so, it was taken as the DJIA AOD fall for 2007.

Of the total 33 DJIA AOD falls (≥ -4.50%) since 1910, only the 1930 event did not have lunar phase within the two segments noted in Diagram 1 (extremely significant p < 10-6). This lunar phase effect did not apply before 1910 or to DJIA AOD falls below -4.50%. It also did not show up in FT-30 daily data post 1935.

54/56 Year Grid  

The 54/56 year grid (see Table 2) contained numerous major financial crises and panics and was first presented by McMinn (1986 & 1995). Years in bold experienced major financial crises as listed by Kindleberger (Appendix B, 1996), while additional crises and DJIA AOD falls were presented in Appendix 1. Remarkably, lunar phase for the 21 crises/panics within this grid occurred with lunar phase between 090 & 190, as well as between 290 and 350, with no exceptions. This gave a similar lunar phase distribution to that established for DJIA AOD falls (1910 - 2010 era) in Diagram 2.

Curiously, all 9 DJIA AOD falls (≥ -3.60%) within the 54/56 year grid happened in the four months to November 15, with 6 in the three weeks ended October 28.

Strangely, 54/56 year grids were also very important in the timing of world mega quakes (mag ≥ 8.6) since 1870. These patterns overlapped with similar 54/56 year grids established for large earthquakes (mag ≥ 7.8) in Chile-Peru, Japan-Kamchatka, Alaska and South East Asia.

Table 2
54/56 YEAR PANIC CYCLE
Year beginning March 1

 

 

 

 

Sq 05

 

Sq 03

 

Sq 01

 

 

 

 

 

 

 

 

 

 

1761

+ 54

1815

 

 

 

 

 

 

1763

+ 54

1817

+ 54

1871

 

 

 

 

1765

+ 54

1819

+ 54

1873

+ 54

1927

 

 

1767

+ 54

1821

+ 54

1875

+ 54

1929

+ 54

1983

1769

+ 54

1823

+ 54

1877

+ 54

1931

+ 54

1985

 

 

1771

+ 54

1825

+ 54

1879

+ 54

1933

+ 54

1987

 

 

 

 

1827

+ 54

1881

+ 54

1935

+ 54

1989

 

 

 

 

 

 

1883

+ 54

1937

+ 54

1991

 

 

 

 

 

 

 

 

1939

+ 54

1993

 

 

 

 

 

 

 

 

 

 

1995

Years in bold contained major financial crises as listed by Kindleberger (1996).
Sources: McMinn (1986, 1995).


1929 & 1987 October Panics  

One of the most remarkable parallels in financial history occurred between the October panics of 1929 & 1987. Intervals of precisely 717 lunar  months appeared between the spring lows, the record highs, the autumn highs, the black days, the recoveries and several other major shifts in investor sentiment (see Table 3). Intervals of 718 lunar months were established for the post-crash lows, as well as the spring lows and AOD falls in 1930 and 1988. 

Table 3
LUNAR MONTH PARALLELS &
THE 1929 & 1987 PANICS

Key Dates

Interval

 

1929

1987

Lunar Mths

DJIA Events

May 27, 1929

May 20, 1987

717.12

Spring Lows

Sept 03, 1929

Aug 25, 1987

717.05

Record Highs       

Oct 10, 1929

Oct 02, 1987

717.09

Autumn Highs

Oct 23, 1929

Oct 16, 1987

717.12

Pre-Crash OD falls

Oct 28, 1929

Oct 19, 1987

717.05

AOD falls  

Oct 30, 1929

Oct 21, 1987

717.05

AOD Rises

Nov 06, 1929

Oct 26, 1987

716.99

Major OD Falls (a)

Nov 13, 1929

Dec 04, 1987

718.07

Post-Crash Lows

May 03, 1930

May 23, 1988

718.07

Spring Lows

Sept 24, 1931

Oct 13, 1989

718.04

AOD Falls

Aug 12, 1932

Aug 06, 1990

717.15

AOD Falls

(a) Major one day falls were recorded after the black days: -9.92% on November 6, 1929 and -8.04% on October 26, 1987. These were among the 10 biggest one day falls ever recorded for the DJIA.
The Lunar Month of 29.53 days is the time taken for the Moon to complete one cycle New Moon to New Moon. 
Abbreviations: AOD or annual one day movement is the biggest % one day rise or fall in the year commencing March 1. BML - Bear market low
Source: Carolan (1992, 1998);
David McMinn.


In both 1929 and 1987, there were 55 days between the record high and the AOD fall, which in turn were followed two days later by the AOD rise (see Table 4).

 

Table 4
DJIA TRENDS IN 1929 & 1987

Record Peak

Interval
Days

AOD
Fall

Interval
Days

AOD Rise

Interval
Days

OD
Fall (a)

Sept 03, 1929

55

Oct 28, 1929

2

Oct 30, 1929

7

Nov 6, 1929

Aug 25, 1987

55

Oct 19, 1987

2

Oct 21, 1987

5

Oct 26
1987

(a) Major one day falls were recorded after the panics on Nov 6, 1929 (-9.92%) and Oct 26, 1987 (-8.04%). These were among the 10 biggest percentage DJIA one day falls ever recorded.

 
October Panics & Lunar Phase       

There are two types of October panics - those that occur a few days prior to a new Moon and those taking place around the full Moon. Five major October panics were listed by Kindleberger (Appendix B, 1996). Additionally, there have been 10 DJIA AOD falls (≥ -3.60%) since 1896 that took place in October. (NB: The annual one day (AOD) rise or fall is the greatest percentage one day movement in the year commencing March 1.) Combining these two lists (see Table 5) gave 12 events, all of which have lunar phase between:    
*    150 & 205 Aº, 1847, 1897, 1907, 1927, 1937, 1989, 2008. (Within a few days of 180 Aº - a full Moon.)
*    315 & 350 Aº, 1857, 1903, 1929, 1987, 1997. (A few days prior to 000 Aº - a new Moon.)

The Moon was always located on the ecliptic circle between 340 and 045 Eº as well as between 165 and 195 Eº.

Table 5
OCTOBER PANICS AND LUNAR PHASE

October Panic

Sun
E
º

Moon
E
º

Phase
A
º

Oct 23, 1847

210

023

173

Oct 14, 1857

201

165

324

Oct 12, 1897

200

042

202

Oct 19, 1903

205

193

348

Oct 22, 1907

208

044

196

Oct 08, 1927

194

344

150

Oct 28, 1929

215

168

313

Oct 18, 1937

205

009

164

Oct 19, 1987

206

170

324

Oct 13, 1989

200

004

164

Oct 27, 1997

214

174

320

Oct 15, 2008

203

034

192

Strangely, 8 of the 12 events happened in a year ended in 7, whereas 1.3 could have been expected by chance. Presumably this has something to do with the well-known decennial cycle in US stock market trends (see subsequently).

60 Year October Intervals     

Intervals of 60 years can be strongly linked to the timing of historic October panics. According to McMinn (2010a), “Since 1885, some 10 major DJIA AOD falls (≥ -3.60%) occurred between September 10 and October 31. Adding or subtracting 60 years to each of these dates gave a corresponding AOD fall (≥ -2.45%) between August 19 and December 20, with no exceptions.”  (see Table 6). Over recent centuries there have only been two exceptions to the 60 year rule. The major banking panics of 1847 (UK Oct 23) and 1907 (USA Oct 22) failed to produce a crisis in 1967, while the 1873 US Black Friday (Sep 19) gave a DJIA AOD fall in July 21, 1933 (-7.84%), about a month earlier than could have been expected.

 

Table 6
EXAMPLES OF 60 YEAR INTERVALS &
US OCTOBER PANICS

Date

DJIA
% AOD Fall

Event

Oct 09, 1839

na

US banking panic.

Dec 18, 1899

-8.72

Two leading NY financial firms failed.

 

Oct 14, 1857

na

US banking panic.

Nov 01, 1917
Nov 08, 1917

-4.16
-4.14

Bolshevik Revolution in Russia.

 

 

 

Oct 09, 1927

-3.65

DJIA AOD fall.

Oct 19, 1987

-22.61

Black Monday.

 

 

 

Sep 24, 1869

na

US Black Friday. Gold panic.

Oct 28, 1929

-12.83

US Black Monday.

Oct 13, 1989

-6.91

Friday 13 panic.

 

 

 

Oct 09, 1871

na

Chicago Fire panic.

Sep 24, 1931

-7.07

UK suspends gold standard.

Nov 15, 1991

-3.91

DJIA AOD fall.

 

 

 

Oct 18, 1937

-7.75

DJIA AOD fall.

Oct 27, 1997

-7.65

US Blue Monday.

 

 

 

Nov 03, 1948

-3.65

Upset Truman presidential win.

Oct 15, 2008

-7.75

After Lehman Bros failure.

 

 

 

Dec 18, 1895

-6.61

Monroe Doctrine scare.

Sep 26, 1955

-6.54

President’s heart attack.

Aug 24, 2015

-3.39

Chinese Black Monday

 

 

 

Sep 21, 1897
Oct 12, 1897

-3.95
-3.90

DJIA AOD falls.

Oct 28, 1957

-2.54

USSR launches Sputnik.

2017

???

 

 

 

 

Aug 19, 1903
Oct 19, 1903

-4.07
-4.17

DJIA AOD falls.

Nov 22, 1963

-2.89

DJIA AOD fall. JFK assassination.

NB: The AOD fall was the biggest percentage one day fall in the DJIA during the year beginning March 1.
Summarised from McMinn (2010a).

 

60 year intervals were also evident for the 11 major DJIA AOD rises (≥ +4.00%) happening between September 24 and November 5 since 1885 (McMinn, 2010a). By adding or subtracting 60 years, most of these rises had a corresponding DJIA AOD rise (≥ +2.50%) between August 20 and December 30. There were two exceptions. In 1974, the DJIA rose +4.71% on October 9 – minus 60 years from that date gave 1914. However, the US stock market was closed for over four months in 1914 following the outbreak of WW I. Presumably, a rally would have taken place once the US Government confirmed that it would remain neutral in the conflict. The stock market rose +7.65% on September 5, 1939, after President Roosevelt announced that the USA would not enter WW II. In 2008, the AOD rise happened on October 13 (+11.08%), minus 60 years gives 1948. However, this year did not record any significant one day rises over +2.20% and was anomalous.

Based on 60 year intervals, McMinn (2010a) correctly anticipated a DJIA AOD fall in the latter part of 2015, which was triggered by the Chinese Black Monday on August 24. A significant AOD rise and AOD fall may also be expected in the latter portion of 2017 assuming the effect again holds

DJIA Peaks, Seasonality and Lunar Phase

The listing of all peaks at the beginning of a DJIA bear market will not correlate with lunar phase nor will it show seasonality. However, by rearranging this list by month - day (year ignored), then excellent relationships can be established between the peaks and lunar phase (McMinn 2010a). Those peaks forming around the same time of year usually have similar lunar phase. It has been a persistent trend over the past 125 years and some examples have been given in the ensuing text. Only the time frame between September 26 and December 10 did not exhibit this phenomenon for whatever reason. The findings have been summarised in Table 7

Table 7
A SUMMARY
LUNAR PHASE & SEASONAL DJIA PEAKS

Season

Number
of Peaks

Sun

Moon

Phase

Jan 16 – Feb 9

3

295 - 325

195 - 235

235 - 295

Feb 10 – Apr 28

3
3

350 – 040
345 - 000

310 – 325
030 - 065

270 – 335

Apr 29 – Jun 30

4

055 - 090

040 - 105

340 - 015

Jul 01 – Jul 31

2

110 - 120

035 - 040

280 - 290

Aug 01 – Sep 10

3
2

150 – 165
160 - 170

160 -180
340 - 350

000 – 015
175 - 185

Sep 11 – Sep 25

2

160 – 180

150 - 160

330 - 350

Sep 26– Dec 10

8

No overall pattern.

Dec 11 – Jan 15

3

260 - 295

335 - 030

230 - 295

NB: The Mar 1 – Apr 15 and Aug 1 – Sep 10 seasons each had two lunar phase clusterings.
Source of Raw Data.
 Bespoke Investment Group (2008) for the beginning of all bear markets post 1900. The author expanded this listing to cover the period 1885 to 1899 and included five additional DJIA corrections with declines from -18.5% to -19.9%.

 
Phi and Fibonacci - Lucas Numbers

Phi (1.618) and Fibonacci numbers are commonly used in technical analysis to predict market trends. According to the Moon Sun Hypothesis, market trends are structured mathematically in time in tune with lunisolar cycles. Taking these two strands of thinking, Phi and Fibonacci numbers were speculated to show up in Moon Sun cycles. Such a connection can be achieved and a proof has been offered in Fibonacci - Lucas Numbers, Moon Sun Cycles and Financial Timing. This provided theoretical support for the use of Phi and additive numbers in stock market forecasting.

Other Anomalies

Numerous other anomalies arise, which further discredit the EMH.

The Decennial Cycle is another anomaly that shows up in US stock market patterns. Under this scenario, the US market bottoms in a year ended in ‘2’ and then progressively rises to a peak in a year ended in a ‘6’ or ‘7’ and experiences a crisis and slump. The market rises to another peak in a 9 or 0 ended year, followed by another market collapse.

The decennial cycle can be used effectively for stock market speculating. According to
R W Miller of Triple Screen Trading, “if one were out of the market at the beginning of the ‘0’ year, entered the S&P 500 on June 30 of the ‘2’ year, then were out from August through October of the ‘7’ year, and finally re-entered until the end of the ‘9’ year, the value of $1 invested in 1900 would be worth $6,660.86 in 2002 versus just $148.41 were you instead fully invested over the entire period of time. An awareness of the 10-year cycle would have produced 44.9 times the return”. An investor obviously would have done very well over the long term, by playing the market according to the decennial cycle. This could not possibly arise if markets were random or efficient.    

Additional anomalies may be given as follows:     
Sunny Day Effect  - weather (Hirshleifer & Shumway)   
Seasonal Affective Disorder - solar photoperiod (Kamstra, Kramer & Levi)  
Daylight Savings Anomaly - solar photoperiod (Kamstra, Kramer & Levi)   
Temperature - warm/cold weather (
Cao & Wei)     
Geomagnetic Storms - sunspots (Krivelyova & Robotti).
Numerous other anomalies were listed by Russell & Torbey (2002).   

Inefficient Market Hypothesis

"I'd be a bum in the street if the markets were efficient." Warren Buffet.

According to Roll (1997), "EMH (is) one of the most controversial and well-studied propositions in all the social sciences. It is disarmingly simple to state, has far-reaching consequences for academic pursuits and business practice and yet is surprisingly resilient to empirical proof or refutation. Even after three decades of research and literally thousands of journal articles, economists have not yet reached a consensus about whether markets - particularly financial markets - are efficient or not". Much of EMH is untestable, unverifiable and non-science and thus can never be confirmed or negated through rigorous assessment. This resulted in protract disputes between those academics who supported the EMH and those who did not.     

In contrast, the Moon Sun Hypothesis is scientifically testable and thus competing views relating the Moon and Sun to Earthly experiences may be confirmed or negated. Such findings are reproducible in subsequent studies and have a high degree of predictability, both of which are scientific criteria. Numerous hypotheses can be tested and, based on the findings, can be expanded upon or rejected. Thus, a valid scientific theory based Moon Sun tidal effects can be developed to assess their impact upon market activity. 

Clearly, EMH will have to be revised in the light of the numerous inefficient anomalies. Hence the proposed Non-random - IMH, for which there are three forms:

The "Weak" form regards there being only a limited correlation between the stock market and Moon Sun cycles. The weak form would be of limited use in making accurate predictions or profitable trading, but would be of scientific interest.

The "Semistrong" form asserts that there is a general trend for the markets to follow Moon Sun cycles. This has been confirmed by various academic papers that have linked lunar phase with financial activity (
refs).     

The "Strong" form considers there to be an intimate link between Moon Sun cycles and market activity.

Surprisingly, there is firm support for the strong version, especially during times of extreme market behaviour and numerous examples have been given by McMinn (2004, 2010a).

The Moon and Sun are hypothesised to emit weak tidal forces, which influence the physiological cycles of the general population and thereby impact upon peoples’ feelings of wellbeing. The collective mood fluctuates through cycles of optimism - crisis - fear, in harmony with the Moon and Sun. These mood swings must filter through the financial structures and fashions prevailing in a particular era before showing up in patterns of financial prices and indices.

Evidence to support the Moon Sun Hypothesis is only statistically significant in relation to large populations. It is impossible to foresee how one person will behave during acute market events. Even so, the prospect of predicting when millions of investors are likely to react adversely on extreme days is becoming increasingly promising. If Moon Sun cycles can be unravelled to predict financial trends accurately, it will be curious to see how the main players react. According to EMH, this new information would be fully exploited by rational investors and the Moon Sun anomalies would disappear from financial patterns. As always only time will tell. 

Conclusions

The EMH "represents one of the most remarkable errors in the history of economic thinking."                                                       Robert Shiller.

How does EMH stand up in the face of the 9/56 year panic cycle, Moon Sun effects and the many other anomalies? Not very well unfortunately, as:
*       Investors do not behave rationally in their decisions.  
*        Financial markets function with mathematical structure in time and thus occur nonrandomly.
*        Free markets allocate financial resources and determine prices very inefficiently.
These findings completely devastate the EMH. Clearly there is a contradiction and one of them has to be completely wrong - the Moon Sun Hypothesis or EMH orthodoxy.

The main theme to emerge is the need for much more research. Numerous questions remain unanswered. How relevant are 9/56 year patterns and Moon Sun cycles in recent decades, especially with the global economy of the 21st century? What role do tidal harmonics and the Fibonacci - Lucas numbers play in the markets? How important is tidal resonance in solving the 9/56 year enigma? Some of this research may have already been done. If excellent correlates were produced, the results may never be published due to the potential profits to be made. Do major world earthquakes and volcanic eruptions cluster selectively within the 9/56 year grid? Are they activated by Moon Sun tidal triggers? Is weather similarly influenced?

The Moon Sun finance firmly endorses those analysts who consider past performance to be a strong indicator of future market trends. There are reasonably regular financial patterns rather than randomness. The problem is to decipher such patterns, which are complex and hard to decode. Even so, there may be emerging a simple unified theory based on the Moon Sun influences in market activity. This would reduce the complexity of market cycles to a few basic principles, which could be of immense benefit in understanding many phenomena. It also offers the potential to make accurate forecasts of critical events many years in advance. 

IMH reduces the whole concept of free markets to an absurdity. Trillions of dollars in financial assets are traded every day worldwide. This is supported by a massive investment in research, trading infrastructure, communications and so forth. All this activity for a world financial market that is highly dependant upon the  heavenly positions of the Moon and Sun. Free markets are inefficient and at times ridiculously inefficient, as witnessed by the numerous manias and panics of recent centuries. A more realistic evaluation is essential if economic theory is to progress. This will take years given the intellectual rigidities within academia. Alas good conservatives are always slow learners. By definition, they cannot cope with new ideas, not even good new ideas. Conservatism should be seen for what it really is - a learning disability.

© Copyright. 2005-2017. David McMinn. All rights reserved.


References

Carolan, C. 1992. The Spiral Calendar. New Classics Library.
Carolan, C.
1998. Autumn Panics. The Market Technician. Journal of the Society of Technical Analysts. p 12. July.
Dichev, I & J, T.
2001. Lunar Cycle Effects in Stock Returns. University of Michigan Business School working paper. 
Funk, J M.
1932. The 56 Year Cycle in American Business Activity. Privately published.
Kindleberger, C P. 1996. Manias, Panics and Crashes. John Wiley & Sons. 3rd Edition.
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Appendix 1
FINANCIAL CRISES IN THE 54/56 YEAR GRID

Black Days

Event

Sun
Eo

Moon
Eo

Phase
Ao

Crises - Kindleberger (Appendix B, 1996)

Jul 25, 1763

Dutch panic. DeNeufville failed.

122

309

189

Jun 19, 1815

British panic. Waterloo war fears.

087

241

154

Dec 17, 1825

British panic. Argentine speculations.

265

358

093

May 09, 1873

Austrian Black Friday

049

193

144

Sep 19, 1873

US Black Friday

177

155

338

Jan 30, 1882

French panic. Union Generale failed.

311

089

148

Oct 28, 1929

US Black Monday

215

168

313

May 11, 1931

Austrian crisis. Creditanstalt failed.

050

341

290

Jul 13, 1931

German crisis. Danatbank failed.

110

087

337

Sep 20, 1931

Britain abandons the gold standard.

177

286

109

Mar 06, 1933

US bank holiday imposed.

346

101

115

Sep 22, 1985

US$ crisis. Plaza Accord.

180

285

102

Oct 19, 1987

US Black Monday

206

170

324

Additional Black Day

May 13, 1927

German Black Friday

052

195

143

Additional Crisis - Kitchin (1933)

Jun 15, 1875

British crisis. Alexander Collie failed.

084

226

142

DJIA AOD Falls ≥ -3.60%

Oct 09, 1871

Chicago fire panic (a).

195

139

303

Oct 08, 1927

AOD fall (-3.65%)

194

344

150

Oct 28, 1929

AOD fall (-12.83%)

215

168

313

Sep 24, 1931

AOD fall (-7.07%)

181

338

157

Jul 21, 1933

AOD fall (-7.84%)

118

108

350

Oct 18, 1937

AOD fall (-7.65%)

205

009

164

Oct 19, 1987

AOD fall (-22.61%)

206

170

324

Oct 13, 1989

AOD fall (-6.91%)

200

004

164

Nov 15, 1991

AOD fall (-3.91%)

233

335

102

(a) This event caused the biggest one day percentage fall in the New York stock market in 1871.