  The M and A transactions represent a wide range of unique business
optimization opportunities in the corporate transformation deals, which are
usually characterized by the high level of total risk. The M and A transactions
can be successfully implemented by taking to an account the size of
investments, purchase price, direction of transaction, type of transaction, and
using the modern comparable transactions analysis and the business valuation
techniques in the diffusion type financial systems in the finances. We
developed the MicroMA software program with the embedded optimized
near-real-time artificial intelligence algorithm to create the winning virtuous
M and A strategies, using the financial performance characteristics of the
involved firms, and to estimate the probability of the M and A transaction
completion success. We believe that the fluctuating dependence of M and A
transactions number over the certain time period is quasi periodic. We think
that there are many factors, which can generate the quasi periodic oscillations
of the M and A transactions number in the time domain, for example: the stock
market bubble effects. We performed the research of the nonlinearities in the M
and A transactions number quasi-periodic oscillations in Matlab, including the
ideal, linear, quadratic, and exponential dependences. We discovered that the
average of a sum of random numbers in the M and A transactions time series
represents a time series with the quasi periodic systematic oscillations, which
can be finely approximated by the polynomial numbers. We think that, in the
course of the M and A transaction implementation, the ability by the companies
to absorb the newly acquired knowledge and to create the new innovative
knowledge bases, is a key predeterminant of the M and A deal completion success
as in Switzerland.
