The Normality Assumption and Fractal Nature of Asset Prices

[Flojomojo 10]

self similar? please explain.... I mean if the trend on the 60 min chart is "down", obviously its because price on the 5 min chart is moving "down" and not the other way around (since the 60 min chart is made up of sequential 5 min intervals). So how can analysis of a higher time frame aid in the analysis of price movement on the 5 min chart?

 

Thanks!

 

Hi Davelansing,

I suggest you check out these three threads:

 

Multiple Timeframes

Waves and Timeframes

Riding the Wyckoff Wave

 

Eventually it boils down to a process like this:

On the higher timeframe

1) Determine the current trend

2) Determine in which stage the trend is

3) Determine proper entry timing

On the lower timeframe

4) Confirm your macro view

5) Finetune your entry

6) Act

[Mindset 10]

There is a relationship between price and time. Volatility ie risk is generally a square root relationship. (volatility power of 0.5)

For example, to obtain a 10-day volatility, multiply the one-day volatility by the square root of 10 .

However this is not an exact rule - some studies have found the relationship to increase with time horizon BUT it always hovers around 0.4 - 0.6.

[zdo 20]

...and that hovering btwn 0.4 – 0.6 is the only linear cycle found to hold up in mkts (so far) and =’s a (slow, rather stodgy) edge in options trading…

 

(btw, I seriously don’t know if this post is off topic or not… hope not…)

[Mindset 10]

I merely postulate that markets are fractal in terms of volatility but it is not quite a square root relationship - close enough to be useful but not exact.

 

There have been a no of studies from Hurst to Mandelbrot that have tried to encapsulate this mathematically.

 

Edit - correction, OTHERS have used Hurst's work on the Nile flooding and translated his theories of persistence into markets.