http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1754388
Mukul PAL, CMT,
CEO, Orpheus Capitals
e-mail: mukul@orpheus.asia
Adrian Mitroi, CFA, Phd
CFO, MKB Nextebank
e-mail: adrian.mitroi0@gmail.com
Megh Shah, B.E.
Masters in Satistical Science
e-mail: m5shah@students.latrobe.edu.au
Abstract:
CEO, Orpheus Capitals
e-mail: mukul@orpheus.asia
Adrian Mitroi, CFA, Phd
CFO, MKB Nextebank
e-mail: adrian.mitroi0@gmail.com
Megh Shah, B.E.
Masters in Satistical Science
e-mail: m5shah@students.latrobe.edu.au
Abstract:
Robert Shiller’s "Paper on The Volatility of Stock markets Prices", published in 1987 uses dividend data and real interest rates to seek evidence that true investment value changes through time sufficiently to justify the price changes. His paper concluded that most of the volatility of the stock market prices appears unexplained. Shiller volatility or fluctuations prove that behavior of markets is not normal. Non normal distribution series is a widely followed proof of inefficiency in prices.
The authors of the current paper reanalyze Shiller’s data not for the change but for rate of change. The rate of change in dividend values, interest rates and market price is used to isolate temporal changes (time durations) defined in days. Though on one side the time duration data illustrate a non normal distribution and confirms Shiller’s non normalcy finding within value (fundamental data) and market data, it opens a larger debate suggesting temporal changes to be the reason for market volatility and inefficiency.
Keywords: Stock market volatility, Temporal Changes, Non Normal Distributions
JEL Classification: G10
REL Classification: 11B
The authors of the current paper reanalyze Shiller’s data not for the change but for rate of change. The rate of change in dividend values, interest rates and market price is used to isolate temporal changes (time durations) defined in days. Though on one side the time duration data illustrate a non normal distribution and confirms Shiller’s non normalcy finding within value (fundamental data) and market data, it opens a larger debate suggesting temporal changes to be the reason for market volatility and inefficiency.
Keywords: Stock market volatility, Temporal Changes, Non Normal Distributions
JEL Classification: G10
REL Classification: 11B
Introduction:
We took data series Long Interest Rate Rates GS10, Real Price, Real Dividend, Real Earnings (Column G,H, I, J) from Shiller's data available on his Yale page (Copy of ie_data.xls) and plotted the rate of change for the respective data series. From this rate of change date we isolate the temporal changes as explained by Nistor, Pal in their paper on "Time Duration Decay" 2010. After isolation the time duration data we created the time duration plot and tested the data for
normal distribution.
normal distribution.
Publicat pe Site-ul Social Science Research Network, 4 februarie 2011
Niciun comentariu:
Trimiteți un comentariu