Fractal markets hypothesis and Geometric mean: Difference between pages

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imported>Doug Williamson
m (Add reference to behavioural economics.)
 
imported>Doug Williamson
(Clarify that larger negative number here means further away from zero.)
 
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(FMH).
Geometric mean returns or growth are calculated by taking account of compounding.


The fractal markets hypothesis is an evolving model of investor and market behaviour which identifies repeating patterns in market prices and conditions.
(Contrasted with the arithmetic mean, which ignores compounding).


The FMH may explain why extreme negative (and positive) outturns are observed more frequently in real financial markets than predicted by simpler efficient market models.


===<span style="color:#4B0082">Example 1: Positive returns or growth</span>===


Under the FMH, a key contributory factor is the difference in investment time horizons between different classes of market participants.
The geometric mean return calculated from sample returns of 4%, 5% and 6% is given by:


( 1.04 x 1.05 x 1.06 )<sup>(1/3)</sup> - 1


If the FMH is borne out in practice, then real financial markets are significantly less stable than predicted and described by more traditional market models.
= '''4.9968%'''.




===Relationship between geometric mean and arithmetic mean===


== See also ==
When returns or growth are positive, geometric means are smaller figures than arithmetic means.
 
In Example 1 above, the arithmetic mean is:
 
(4% + 5% + 6%) / 3 = '''5.0000%'''
 
 
''The geometric mean of +4.9968% is a smaller positive number than the [[arithmetic mean]] of +5.0000%.''
 
 
 
On the other hand, when returns or growth are ''negative'', the geometric mean is a larger negative number - further away from zero - than the arithmetic mean.
 
 
===<span style="color:#4B0082">Example 2: Negative returns or decline</span>===
 
The geometric mean return calculated from three ''negative'' sample returns of -(4)%, -(5)% and -(6)% is given by:
 
( (1 - 0.04) x (1 - 0.05) x (1 - 0.06) )<sup>(1/3)</sup> - 1
 
( 0.96 x 0.95 x 0.94 )<sup>(1/3)</sup> - 1
 
= '''-(5.0035)%'''.
 
 
The negative geometric mean of -(5.0035)% is a larger negative number - further away from zero - than the arithmetic mean of -(5.0000)%.


*  [[Efficient market hypothesis]]
(The arithmetic mean of the negative returns of -(4)%, -(5)% and -(6)% is the three items added together and divided by 3.)
*  [[Behavioural economics]]


*  [http://www.bankofengland.co.uk/publications/Pages/fsr/fs_paper23.aspx Bank of England Financial Stability Paper No 23]


[[Category:Capital_Markets_and_Funding]]
== See also ==
[[Category:Risk_Management]]
* [[Arithmetic mean]]
* [[CAGR]]

Revision as of 08:59, 1 December 2015

Geometric mean returns or growth are calculated by taking account of compounding.

(Contrasted with the arithmetic mean, which ignores compounding).


Example 1: Positive returns or growth

The geometric mean return calculated from sample returns of 4%, 5% and 6% is given by:

( 1.04 x 1.05 x 1.06 )(1/3) - 1

= 4.9968%.


Relationship between geometric mean and arithmetic mean

When returns or growth are positive, geometric means are smaller figures than arithmetic means.

In Example 1 above, the arithmetic mean is:

(4% + 5% + 6%) / 3 = 5.0000%


The geometric mean of +4.9968% is a smaller positive number than the arithmetic mean of +5.0000%.


On the other hand, when returns or growth are negative, the geometric mean is a larger negative number - further away from zero - than the arithmetic mean.


Example 2: Negative returns or decline

The geometric mean return calculated from three negative sample returns of -(4)%, -(5)% and -(6)% is given by:

( (1 - 0.04) x (1 - 0.05) x (1 - 0.06) )(1/3) - 1

( 0.96 x 0.95 x 0.94 )(1/3) - 1

= -(5.0035)%.


The negative geometric mean of -(5.0035)% is a larger negative number - further away from zero - than the arithmetic mean of -(5.0000)%.

(The arithmetic mean of the negative returns of -(4)%, -(5)% and -(6)% is the three items added together and divided by 3.)


See also