A Roadmap for the Australian Stockmarket

7/31/2019 A Roadmap for the Australian Stockmarket

1/15


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Page 2

HERDING INVESTOR BEHAVIOUR SIR ISAAC NEWTON

First, check out Exhibit 4 in Grantham's Q4 2010 quarterly letter.

Basically, it's a chart that shows The South Seas Bubble of 1718 to 1721:

- Newton invests a small amount prior to the South Seas bubble

- Newton exits happy in the early stages before the bubble really gets going having

made some money

- Newton sees his friends getting rich as the bubble does really get going

- So Newton re-enters near the peak of the bubble with a lot of money

Then, of course...

- Newton exits broke after the stock then falls roughly back to where he had initially

invested just a small amount of money

Newton had the great good luck to get into the South Sea Bubble early. He made a

really decent investment and a very quick killing, which mattered to him. It was

enough to count. He then got out, and suffered the most painful experience that can

happen in investing: he watched all of his friends getting disgustingly rich. He lost his

cool and got back in, but to make up for lost time, he got back in with a whole lot

more (some of it borrowed), nicely caught the decline, and was totally wiped out. And

he is reported to have said something like, "I can calculate the movement of heavenly

bodies but not the madness of men."

NEWTON WAS 75 YEARS OLD WHEN HE MADE THESE INVESTMENT

DECISIONS!!


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Page 3

WHAT DRIVES SHARE PRICES?

(1) Company Intrinsic Value = Net present value of expected future cash flows

discounted by companys weighted average cost of capital

(2) Growth in the general Economy GDP Growth

Approx 6% per annum nominal

Approx 3% per annum real

(3) Interest Rates Government ten year bond yields

(4) Inflation

sometimes a significant driver eg 10% pa 1982-1987

(5) Dividends

Increases; unexpected falls

(6) An index of optimism or expectations or optimism-pessimism waves (Sahni

1951)

The largest influence of all factors on share prices?

Sahnis analysis of London share prices 1918-1947

Dividends did not recover to the heights of the middle 20s but low interest rates and

moderately buoyant expectations lifted share prices to a peak at the end of 1936 which

was higher than that of 1929. The peak of optimism coincides unmistakably with thepeak of prices which fell thereafter, despite the fact that dividends increased until as

late as the third quarter of 1938. This price fall of 1937-39 however was not entirely a

matter of pessimism; it was aided by a fall in consol prices. The accelerated rise of

interest-rates after Munich seems indeed to have helped falling dividends to offset a

minor increase in optimism. On the other hand, rising consol prices helped to mitigate

the depressing effect of both falling dividends and increasing pessimism from the

outbreak of war until nearly the end of 1940

Share prices rose fairly steadily from the end of 1940 until 1947. The main factor in

1941-42 appears to have been increasing optimism, though falling interest rates

helped in 1941. From the beginning of 1943 rising dividends began to be an

appreciable factor and continued so throughout the period under review. After the end

of 1944, anticipation of the difficulties of demobilisation caused a marked decline in

optimism extending for more than one year, but almost entirely offset, so far as its

effect on share price was concerned, by the fall of interest rates consequent upon the

cheap money policy. The marked turning point of share values in the second quarter

of 1947 seems to have been a consequence of the rise of interest rates rather than any

change in optimism (which has then been reviving for about or in dividends which

continued to rise.


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Page 4

AUSTRALIAN STOCK MARKET HISTORY 1875-2012

Based on Lamberton Index derivation

Trend line growth rate of 5.28% pa (1900 to 1950)

Index Returns (Nominal) Excludes Dividends

FROM 1875 1900 1920 1937 1950 2000

Index 5.06 8.89 22.44 72.2 116.2 3101.7

TO

1900 2.28%

1920 3.37% 4.74%

1937 4.38% 5.82% 5.82%

1950 4.27% 5.28% 5.28% 3.73%

2000 5.27% 6.03% 6.03% 6.15% 6.79%

2012 5.04% 5.66% 5.66% 5.59% 5.98% 2.67%

Inflation Rate (CPI Index)

FROM 1875 1900 1920 1937 1950 2000

Index 5.06 8.89 22.44 72.2 116.2 3101.7TO

1900 1.00%

1920 3.20% 3.20%

1937 1.50% 1.50% -0.10%

1950 2.30% 2.30% 1.60% 2.10%

2000 4.10% 4.10% 4.30% 4.80% 5.90%

2012 4.00% 3.96% 4.10% 3.63% 5.17% 2.78%

0.00

1.00

2.003.00

4.00

5.00

6.00

7.00

8.00

9.00

10.00

01-

Jan-

00

01-

Mar-

11

01-

May-

22

01-

Jul-

33

01-

Sep-

44

01-

Nov-

55

01-

Jan-

67

01-

Mar-

78

01-

May-

89

30-

Jun-

00

31-

Aug-

11

log index

log trend


5/15

Page 5

ASX SECULAR BULL AND BEAR MARKET CYCLES

As Goldilocks discovered there is more than one type of bear. Lets define these:

GRIZZLY BEAR (OR BIG BAD WOLF?) We define this as a market crash where

the index falls around 50% or more within a two year period. There have been four

such crashes in ASX history:

Bear Market Duration % Decline

Aug 29-Aug 31 24 months -46.2%

Jan 73-Sep 74 20 months -59.3%

Sep 87-Nov 87 2 months -50.0%

Nov 07-Mar 09 16 months -54.6%

PAPA BEAR No net gains over more than one decade from previous index peak.This is the classical secular bear and has typically lasted 13 to 15 years. There have

been three such periods in ASX history commencing around 39 years or one

generation apart:

1888 to 1903 (15 years)

1929 to 1942 (13 years)

1968 to 1982 (14 years)

So if history holds, there is a good chance that the November 2007 ASX/S&P200

Index peak of 6800 may not be exceeded until 2020 to 2022!

MAMA BEAR This typically five year cycle is the worst performing sub- period in

terms of investment returns of the secular papa bear market. Generally the index

bottom (as measured by 5 year rolling returns) occurs five years after the top as in

1937 to 1942 , 1969 to 1974, 1987 to 1992 (and 2007 to 2012?). During this period an

investor who bought shares at the peak has suffered a loss of around 10% pa.

BABY BEAR Since 1960 there were 14 bear markets (happening on average once

every 3 years) with an average duration of nearly 12 months and an average fall in

the All Ordinaries Index of almost one third from peak to trough. A baby bear is

characterised by a 20% correction over a period of several months.

Bear Market Duration % Decline

Sep 60-Nov 60 2 months -23.2%

Feb 64-Jun 65 16 months -20.0%

Jan 70-Nov 71 22 months -39.0%

Jan 73-Sep 74 20 months -59.3%

Aug 76-Nov 76 3 months -22.0%

Feb 80-Mar 80 2 months -20.2%

Nov 80-Jul 82 20 months -40.6%Sep 87-Nov 87 2 months -50.0%


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Page 6

Aug 89-Jan 91 15 months -32.4%

May 92-Nov92 6 months -20.3%

Feb 94-Feb 95 12 months -23.0%

Sep 97-Oct 97 1 month -21.0%

Mar 02-Mar 03 12 months -22.3%

Nov 07-Mar 09 16 months -54.6%

Average 10.6 months -32.0%

MEAN REVERSION OF STOCK RETURNS

In the long run stock index returns are mean reverting. This is logically andmathematically intuitive since aggregate company values as represented by a

developed market index cannot indefinitely grow faster than the overall economy,

which nominally grows at 5% to 6% per annum.

When 15 year rolling return exceeds 10% per annum as in 1969, 1987 and 2007 a50% market crash has followed.

When 15 year rolling return falls below 2%, it has historically marked animportant market bottom and a great time to buy stocks. This occurred in 1903,

1942, 1974, 2002 and 2009.

15 Year Rolling Returns (Nominal)

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

Jan-0

0

Jan-0

9

Jan-1

8

Jan-2

7

Jan-3

6

Jan-4

5

Jan-5

4

Jan-6

3

Jan-7

2

Jan-8

1

Jan-9

0

Jan-9

9

Jan-0

8

RR 15YR

GM


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Page 7

When 15 year real rolling return > 7%, major reversal (mean reversion) follows.eg 1937, 1968, 2007. This typically signals the peak of the optimism pessimism

wave cycle.

Major market bottoms have coincided with 15 year real rolling return fallingbelow zero eg 1903, 1942,1974,1982,2003.

Five year returns following these major market bottoms are exceptional.

Real 15 Year Rolling Returns

-8.0%

-6.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

Jan-00

Jan-09

Jan-18

Jan-27

Jan-36

Jan-45

Jan-54

Jan-63

Jan-72

Jan-81

Jan-90

Jan-99

Jan-08

15 yr real RR

GM (1.7%)


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Page 8

Above chart of past 5 year rolling returns vs future 5 year rolling returns showsthat returns over medium term time frames are negatively auto-correlated at the

extremities, ie investors buying at the end of a period of high negative rolling

returns (say below 10% pa) are rewarded by outperformance in the following fiveyears.

Conversely an investor buying after a strongly performing 5 year period (sayabove 20% per annum) is likely to encounter a market crash within the following

few years.

This is best highlighted by examining 5 year rolling returns before the crash ofOctober 1987, the largest in ASX history. In a period of two months, the ASX All

Ordinaries Index fell by 50% from its peak including a one day fall of 24% on

October 20th

2007

Not a Random Walk

-20.0%

-10.0%

0.0%

10.0%

20.0%

30.0%

40.0%

-20.0% -10.0% 0.0% 10.0% 20.0% 30.0% 40.0%

Past 5YR RR

Future5YRR

R

Series1


9/15

Page 9

As can be seen above, the crash of October 1987 was preceded by the largest 5year run-up in stock prices in ASX history. The market rose by 342%

(quadrupled) between September 1982 and September 1987, representing a

CAGR of 34.7%.

The five-year period from the September 1987 peak to September 1992 proved tobe one of the worst performing in ASX history delivering an annual return of -

7.6% per annum.

The market bottomed two months later in November 1992 and commenced a 15year bull run that peaked on November 1

st2007. The index increased by 364%

over this period, delivering a rolling annual return of 10.8% and setting the stage

for the next bear market

Historically major market bottoms have occurred when the 5 year rolling returnfell below -7.5% per annum. These occurred in August 1931 (bottom after 1929

crash) March 1942 (bottom after 1929 -1942 secular bear market), September

1974 (bottom after 1973/74 crash), September 1992 (bottom after 1987 crash) and

June 2012 (bottom after 2008/9 crash?)

5-Year Rolling Returns (Nominal)

-20.0%

-10.0%

0.0%

10.0%

20.0%

30.0%

40.0%

Jan-00

Jan-06

Jan-12

Jan-18

Jan-24

Jan-30

Jan-36

Jan-42

Jan-48

Jan-54

Jan-60

Jan-66

Jan-72

Jan-78

Jan-84

Jan-90

Jan-96

Jan-02

Jan-08


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Page 10

ELLIOTT WAVES AND FRACTALS

The Elliott Wave Principle is a form of technical analysis that some traders useto analyze financial market cycles and forecast market trends by identifying

extremes in investor psychology, highs and lows in prices, and other collective

factors. Ralph Elliott discovered the underlying social principles and developed

the analytical tools in the 1930s.

He proposed that market prices unfold in specific patterns, called Elliott waves.

The Elliott Wave Principle posits that collective investor psychology, or crowdpsychology, moves between optimism and pessimism in natural sequences. These

mood swings create patterns evidenced in the price movements of markets atevery degree of trend or time scale.

The structures Elliott described also meet the common definition of a fractal (self-similar patterns appearing at every degree of scale. Elliott wave practitioners say

that just as naturally-occurring fractals often expand and grow more complex over

time, the model shows that collective human psychology develops in natural

patterns, via buying and selling decisions reflected in market prices: "It's as

though we are somehow programmed by mathematics. Seashell, galaxy,

snowflake or human: we're all bound by the same order.

In 1963, Benoit Mandelbrot discovered cotton prices time series exhibited afractal structure. Again, all charts look the same. In the case of cotton I found all


11/15

Page 11

the price variations followed the same statistical properies for days over a few

decades and for months over eighty years. All the lines were equally wiggly

Didier Sornette, UCLA Physicist applied maths and physics to anlysing stockmarket crashes He found that the underlying cause can be found months and even

years before -- in the build-up of cooperative speculation. Sornette analysed

historical precedents, from the decade-long "tulip mania" in the Netherlands thatbegan in 1585, a time of great prosperity, and wilted suddenly in 1637, to the

South Sea Bubble that ended with the first huge market crash in England in 1720,

to the bubbles and crashes that occurred every decade in the 19th century, to the

Great Crash of October 1929 and Black Monday in October 1987. He analyzes

herd behavior and the crowd effect, speculative bubbles, and precursory patterns

before large crashes, as well as the major crashes that have occurred on the

world's major stock markets.

Sornette concludes that most explanations other than "cooperative self-organisation" fail to account for the subtle bubbles by which markets lay the

foundation for catastrophe.

Sornette said "Collective behavior theory predicts robust signatures of speculativephases of financial markets, both in accelerating bubbles, as well as decelerating

'antibubbles, "These precursory patterns have been documented for essentially all

crashes on developed as well as emergent stock markets."

The charts of rolling returns for the ASX indices display a fractal structure andsimilarity to Elliott waves.


12/15

Page 12

MARKET CRASH PREDICTORS

(1) Pogos Rolling Returns Indicator

A stock market crash is likely when

15 year nominal rolling return > 10% 15 year real rolling return > 7%

5 year nominal rolling return > 20%

This is mathematically intuitive

Suppose Index starts at 1000

At growth of 5.5% pa GDP rate for 15 years it will grow to 2232

At growth of 10% pa in bull market for 15 years it will grow to 4177. A 50%

correction will take it back to long term trend line.

(2) Buffett Market Capitalisation to GNP Indicator

This indicator has been described by Warren Buffet as "probably the best single

measure of where valuations stand at any given moment." It compares the total price

of all publicly traded companies to GNP. This metric can also be thought of as an

economy wide price to sales ratio.

Buffett said For me, the message of that chart is this: If the percentage relationship

falls to the 70% or 80% area, buying stocks is likely to work very well for you. If the

ratio approaches 200% as it did in 1999 and a part of 2000 you are playing withfire.

In October 2007 ASX market cap to GNP ratio hit 150%

In July 2012, ASX market cap to GNP ratio is approx 86%

(3) Ziemba bond yield to earnings Indicator

William Ziemba found that when long bond interest rates (30 year bonds) get too

high relative to stock returns as measured by the earnings over price yield method

(inverse of P/E ratio) then there almost always is a crash.

The tipping point is when the bond yield gets to 4% above the earnings yield, eg if 30

year bond is at 9% with P/E at 20 (earnings yield of 5%)


13/15

Page 13

CONCLUSIONS & INVESTMENT IMPLICATIONS

In the long run, the stockmarket is broadly predictable (just like the weather). It islikely to grow around a trend line of around 5% per annum in nominal terms.

Human behavior will create above trend growth bubbles or cycles and these will

be followed by crashes.

At 4150 on the ASX/S&P200 Index, the market is within 10% of a historical lowthat have marked the low points of previous bear markets.

The Index is likely to spend the next four years within a trading range of 4000 to5000, and could be back near 4000 in 2016 after a periodic 20% correction.

With no net capital growth over such a cycle, the only source of returns toinvestors will be dividends.

Selling call options and put options in this type of market can add significantincremental returns to investment portfolios

The 2007 index high of 6800 may not be exceeded until 2022 at which time themarket may commence a five year bull run ending (of course) in the crash of

2027.

Ten year government bond yields which have hit three-hundred year lows in UKand US may be in one of the greatest speculative bubbles in history. Financial

planners should rethink exposing their clients to Balanced Funds.


14/15

Page 14

Appendix 1 - Australian Bear Markets, 1960 2010

NOMINAL

Start

Finish

BearMarket

Duration

%D

ecline

5

10

15

5

10

15

Sep

60-Nov

60

2mon

ths

-23

.20%

13.9%

7.4

%

8.2%

10

.9%

4.9

%

6.5

%

Fe

b64-Jun

65

16mon

ths

-20

.00%

9.9%

9.5%

6.9%

-1.4%

5.8

%

4.8

%

Ju

l-68

12.9%

11.0%

10.1%

Jan

70-Nov

71

22mon

ths

-39

.00%

12.1%

6.9

%

9.2%

5.9

%

3.4

%

5.9

%

Jun-7

2

Jan

73-Sep

74

20mon

ths

-59

.30%

11.7%

7.6

%

7.9%

-13.0%

-2.2

%

-0.4%

Aug76-Nov76

3months

-22.00%

1.7%

4.6%

3.5%

0.2%

3.0

%

2.3%

Fe

b80-Mar

80

2mon

ths

-20

.20%

20.1%

3.6

%

6.5%

17

.3%

3.0

%

6.1

%

Nov

80-Ju

l82

20mon

ths

-40

.60%

21.7%

7.6

%

8.5%

8.7

%

1.6

%

4.1

%

Sep

87-Nov

87

2mon

ths

-50

.00%

34.7%

22.4%

12.4%

19

.1%

14.7

%

7.8

%

Aug

89-Jan

91

15mon

ths

-32

.40%

18

.6%

15

.1%

14

.8%

19

.8%

10.3

%

12

.8%

May

92-Nov

92

6mon

ths

-20

.30%

-1.6

%

12

.6%

11

.9%

2.1

%

10.9

%

10

.9%

Sep-9

2

-7.6%

11.6

%

11

.5%

Fe

b94-Fe

b95

12mon

ths

-23

.00%

8.6%

11.6%

12.3%

2.7

%

9.1

%

7.8

%

Sep

97-Oc

t97

1mon

th

-21

.00%

11.2%

1.8

%

11.8%

12

.0%

6.9

%

11

.2%

Mar

02-Mar

03

12mon

ths

-22

.30%

6.9

%

7.9

%

4.9

%

0.3%

5.3

%

4.8%

Nov

07-Mar

09

16mon

ths

-54

.60%

17.9%

9.8%

10.8%

-0.4

%

1.2

%

3.0

%

Fe

b-1

1-Sep-1

1

9mon

ths

-16

.40%

0.6%

4.3

%

5.3%

-3.7%

3.2

%

4.2%

Average

10.6months

-32.00%

Feb-29-Aug-31

34months

-46.20%

9.6

%

9.6

%

6.2

%

-7.5

%

0.4

%

2.5

%

Mar-37-Mar-42

60month

-32.00%

18

.9%

5.6

%

7.1

%

-7.4

%

4.9

%

1.1

%

May-51Dec-52

19months

-33.50%

11.3%

8.7

%

5.7

%

7.5

%

3.7

%

2.1

%

Feb-2011-Sep2011

9months

-16.30%

0.6

%

4.3

%

5.3

%

-3.7

%

3.2

%

4.2

%


15/15

P 15

REAL

Start

Finish

BearMarket

Duration

%Decline

5

10

15

5

10

15

Sep

60-Nov

60

2mon

ths

-23

.20%

Fe

b64-Jun

65

16mon

ths

-20

.00%

4.8%

4.5%

2.0%

-5.5%

1.3

%

0.4

%

J

ul-68

10.2%

8.4%

7.6%

Jan

70-Nov

71

22mon

ths

-39

.00%

9.2%

4.

1%

6.3%

3.8

%

1.1%

3.3

%

Jan

73-Sep

74

20mon

ths

-59

.30%

3.0%

4.

0%

4.3%

-16.6%

-6.3%

-4.5%

Aug

76-Nov

76

3mon

ths

-22

.00%

-3.8

%

-1.

1%

-2.0

%

-5.2

%

-2.5

%

-3.2

%

Fe

b80-Mar

80

2mon

ths

-20

.20%

11.3%

-4.

0%

-1.3%

8.8

%

-4.5

%

-1.7

%

Nov

80-Ju

l82

20mon

ths

-40

.60%

12.8%

-0.

3%

0.6%

-0.2

%

-6.7%

-4.4

%

Sep

87-Nov

87

2mon

ths

-50

.00%

22.3%

11.2%

2.1%

8.4

%

4.4%

-1.9

%

Aug

89-Jan

91

15mon

ths

-32

.40%

8.9%

4.6%

5.8%

-4.2%

-1.9%

1.5%

May

92-Nov

92

6mon

ths

-20

.30%

-8.5

%

4.8%

4.1%

-5.0%

3.1

%

3.2

%

Fe

b94-Fe

b95

12mon

ths

-23

.00%

1.9%

4.7%

5.4%

-3.3

%

2.7

%

1.5

%

Sep

97-Oc

t97

1mon

th

-21

.00%

6.9%

-3.

0%

6.5%

7.4

%

-1.5

%

6.2

%

Mar

02-Mar

03

12mon

ths

-22

.30%

3.4

%

4.3%

1.5

%

-2.7%

2.2%

1.7%

Nov

07-Mar

09

16mon

ths

-54

.60%

14.9%

7.0%

7.9%

-3.1

%

-1.5

%

0.2

%

Average

10.6months

-32.00%

Feb-2011-Sep2011

9months

-16.30%

-2.1

%

1.5%

2.6

%

-6.3

%

0.4

%

1.4

%

Jun-12

-10

.2%

0.1%

1.2

%

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A Roadmap for the Australian Stockmarket

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