  Financial forecasting is an estimation of future financial outcomes for a
company, industry, country using historical internal accounting and sales data.
We may predict the future outcome of BSE_SENSEX practically by some soft
computing techniques and can also optimized using PSO (Particle Swarm
Optimization), EA (Evolutionary Algorithm) or DEA (Differential Evolutionary
Algorithm) etc. PSO is a biologically inspired computational search &
optimization method developed in 1995 by Dr. Eberhart and Dr. Kennedy based on
the social behaviors of fish schooling or birds flocking. PSO is a promising
method to train Artificial Neural Network (ANN). It is easy to implement then
Genetic Algorithm except few parameters are adjusted. PSO is a random & pattern
search technique based on populating of particle. In PSO, the particles are
having some position and velocity in the search space. Two terms are used in
PSO one is Local Best and another one is Global Best. To optimize problems that
are like Irregular, Noisy, Change over time, Static etc. PSO uses a classic
optimization method such as Gradient Decent & Quasi-Newton Methods. The
observation and review of few related studies in the last few years, focusing
on function of PSO, modification of PSO and operation that have implemented
using PSO like function optimization, ANN Training & Fuzzy Control etc.
Differential Evolution is an efficient EA technique for optimization of
numerical problems, financial problems etc. PSO technique is introduced due to
the swarming behavior of animals which is the collective behavior of similar
size that aggregates together.
