## Research Papers and Features

Starting with the fundamental idea of an “emerging market economy”, its role, utility and dynamics in the current global set up as a balancing economic block, the paper analysis Goldman Sach’s emerging BRIC’s countries model in context of the pre and post 2008 financial crisis. The paper looks at micro and macroeconomic valuations, currency and the economic cycles to illustrate changes in the four economies. Using Japan as a developed economy, the paper also makes a comparative approach and tries to forecast the economic development of the block and respective relation among these countries.

The BRIC Model from a Japanese Perspective - Pre and Post Financial Crisis Review and Forecasts

The enclosed research reworks the Mandelbrot Multifractal from a time cycle rather than trend perspective to prove that time fractal is more proportionate than the price fractal and is the real law of nature, which drives everything in nature. The case is validated by illustrating power law curves in time cycle periodicities. Power law is seen across nature and in diverse social trends. The power law in prices is a subject of extended study, but there has been no research attempt made to prove power law in time cycle periodicities.

The Time Fractals

Classic studies of the probability density of price fluctuations $g$ for stocks and foreign exchanges of several highly developed economies have been interpreted using a {\it power-law} probability density function $P(g) \sim g^{-(\alpha+1)}$ with exponent values $\alpha > 2$, which are outside the L\’evy-stable regime $0 < \alpha < 2$. To test the universality of this relationship for less highly developed economies, we analyze daily returns for the period Nov. 1994-June 2002 for the 49 largest stocks of the National Stock Exchange which has the highest volume of trade in India. We find that $P(g)$ decays as an {\it exponential} function $P(g) \sim \exp(-\beta g)$ with a characteristic decay scales $\beta = 1.51 \pm 0.05$ for the negative tail and $\beta = 1.34 \pm 0.04$ for the positive tail, which is significantly different from that observed for developed economies. Thus we conclude that the Indian stock market may belong to a universality class that differs from those of developed countries analyzed previously.

Scale-Dependent Price Fluctuations for the Indian Stock Market

(Page 88) Competitiveness is a comparative concept of the ability and performance of a firm, sub-sector or country. It’s a ranking system based on a host of parameters. The Global competitiveness report 2009-2010 from the World Economic Forum measures competitiveness based on 12 pillars.

Cycles of Competitiveness. Rieki. Bulgarian Sofix vs. Eurozone Indices

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.

Temporal Changes in Shiller’s Exuberance Data

Divergence is an understudied subject loosely defined as an unpredictable random error. The classification of divergences as small or large is also at the heart of efficient or inefficient market theory debate. This paper explains how divergence is cyclical and can be quantified and used as a predictive model.

The Divergence Cyclicality

Classic studies of the probability density of price fluctuations g for stocks and foreign exchanges of several highly developed economies have been interpreted using a power-law probability density function P(g)~g-(α1) with exponent values α>2, which are outside the Levy-stable regime 0<α<2. To test the universality of this relationship in ‘time duration,’ we isolate the time duration between rate of change for the period Jan 2000-Oct 2010 for the 23 largest stocks of the Bucharest Stock Exchange which has the highest volume of trade in Romania. We find that D(g) decays as an exponential function D(g)~exp(-βg) with a characteristic decay scales β=2.45±0.045. Thus we conclude that time duration in Romanian stock market may belong to a universality class that is witnessed in equity prices around the world.

Time Duration Decay

Nature and markets are replete with examples of three systems. However, little has been written about these recurring cases of three systems. This is a compilation of various examples of such systems and how human psychology relates to three systems better than other systems. Leonhard Euler discussed the three body problem in 1760. Is it just a coincidence or are three systems related to a key mathematical proportion?

The Three Systems

This paper applies performance cycles to the top 100 stocks of Toronto Stock Exchange.

This is the PREZI presentation Mukul Pal presented in Toronto on 20 Oct 2011 at the Canadian Society of Technical Analyst annual event.

Time is a snowflake

In their 1985 paper ‘Does the stock market overeact?’, DeBondt and Thaler explained the idea of mean reversion and how it leads to the Loser’s portfolio of 3 years outperforming the Winner’s portfolio of the same time. Based on mean reversion, this paper illustrates a new stock selection and trend determining approach. The paper uses an innovative approach to convert price performance data into non price ranking data, which is positively tested for mean reversion and stationarity.

Mean Reversion Indicator

Time Fractals Video at TEDx