Though it has been a few decades since Chaos Theory made its way into Economics and Finance through the works of Baumol & Benhabib, Alison Butler, David Levy, Philip Mirowski, Michael McKenzie, Robert Gilmore and Blake LeBaron
(among others), it is observed that most of the mainstream economics and finance journals are reserved towards publishing empirical papers on chaos in financial markets. Publications to this end are very few and most of them are published in a handful of journals.
As I am looking forward to write empirical papers examining the evidence of chaos in commodity markets, I wish to know the odds of my work seeing the light of the day. Any useful suggestion/information in this regard would be highly appreciated.
In my opinion the Chaos Theory in recent years has not been developed. The Game Theory in applications on financial markets, including capital markets, on the securities markets, was developed to a greater extent.
I invite you to the discussion.
Dear Mr. Verghese,
Exploring chaos theory in Finance would be a good idea but we have done work on nonlinear models of finance like "Market String" spacetime Econophysics models and found that asset markets even in Emerging Markets are efficient in even astrophysical type resources like information-energy and spacextime. We have discovered that under natural conditions on cybernetic stock exchange systems nonlinear models fit dynamic general equilibrium specification of asset markets quite well and even string matching field variables like bounded rationality and complexity does not give dynamic instability. So models of chaos might be explaining something which has nothing to do with financial or economic or ecen physical fundamentals of primary markets. You can take a look at our paper "A mathematical-statistical pricing model of emerging markets" on www.researchgate.net/profile/Soumitra_Mallick. However there is evidence of nonlinear pricing.
S.K.Mallick (CA)
for S.K.Mallick, S.Raychaudhury, S.Mallick
of RHMHM School,
USA, Japan, India.
Thanks for the reply Ahaloudine Assani
, Sir Soumitra Kumar Mallick, and Dariusz Prokopowicz. I really appreciate your gesture to help.However, if you have missed out, my main worry (as discussed earlier) is the inclination of mainstream economics and finance journals to overlook empirical studies on chaotic dynamics in asset prices. While non-linearity in asset prices is a stylised fact across asset categories and across geographies, low dimensional chaos could in fact be a possibility in certain noisy time series such as that of crude oil prices. After all chaos, as such is a special case of non-linearity and evidence in support (or against) of this phenomenon is highly informative in various ways. Still most of the mainstream journals that are open to papers on nonlinear dynamics are little conservative towards publishing articles on chaos. I wonder why? Why aren't studies on chaotic dynamics in financial time series taking off?
Looking forward to see some interesting and intuitive discussion here.
We detected (wherever it is present) and modelled chaos in a few FOREX times series. We subsequently developed 2-stage prediction models. The entire framework yielded very good results. We published the works in Swarm and Evolutionary Computation and Applied Soft Computing Journals apart from a few International Conferences.
Proponents of chaos theory believe that price is the very last thing to change for a stock, bond or other security. This suggests that periods of low price volatility do not necessarily reflect the true health of the market.
In my opinion, even though i believe nonlinearity is the next evolutionary step mainly in econometris (in financial or macroeconomic data), chaos theory is difficult to apply to a number of applications and I don't know of any application that produced good longterm forecasts...
Using chaos theory, a change in price is determined through mathematical predictions of the following factors: a trader's personal motivations (such as doubt, desire, or hope, all of which are nonlinear and complex), changes in volume, the acceleration of changes, and momentum behind the changes.
Using chaos theory, a change in price is determined through mathematical predictions of the following factors: a trader's personal motivations (such as doubt, desire, or hope, all of which are nonlinear and complex), changes in volume, the acceleration of changes, and momentum behind the changes.
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