Abstract: Recognizing behavioral patterns of financial markets
is essential for traders. Japanese candlestick chart is a common tool to
visualize and analyze such patterns in an economic time series. Since
the world was introduced to Japanese candlestick charting, traders
saw how combining this tool with intelligent technical approaches
creates a powerful formula for the savvy investors.
This paper propose a generalization to box counting method of
Grassberger-Procaccia, which is based on computing the correlation
dimension of Japanese candlesticks instead commonly used 'close'
points. The results of this method applied on several foreign
exchange rates vs. IRR (Iranian Rial). Satisfactorily show lower
chaotic dimension of Japanese candlesticks series than regular
Grassberger-Procaccia method applied merely on close points of
these same candles. This means there is some valuable information
inside candlesticks.
Abstract: Daily production of information and importance of the sequence of produced data in forecasting future performance of market causes analysis of data behavior to become a problem of analyzing time series. But time series that are very complicated, usually are random and as a result their changes considered being unpredictable. While these series might be products of a deterministic dynamical and nonlinear process (chaotic) and as a result be predictable. Point of Chaotic theory view, complicated systems have only chaotically face and as a result they seem to be unregulated and random, but it is possible that they abide by a specified math formula. In this article, with regard to test of strange attractor and biggest Lyapunov exponent probability of chaos on several foreign exchange rates vs. IRR (Iranian Rial) has been investigated. Results show that data in this market have complex chaotic behavior with big degree of freedom.
Abstract: In this article, by using fuzzy AHP and TOPSIS
technique we propose a new method for project selection problem.
After reviewing four common methods of comparing alternatives
investment (net present value, rate of return, benefit cost analysis
and payback period) we use them as criteria in AHP tree. In this
methodology by utilizing improved Analytical Hierarchy Process
by Fuzzy set theory, first we try to calculate weight of each
criterion. Then by implementing TOPSIS algorithm, assessment of
projects has been done. Obtained results have been tested in a
numerical example.