英文标题：
《Mergers and acquisitions transactions strategies in diffusion - type
financial systems in highly volatile global capital markets with
nonlinearities》
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作者：
Dimitri O. Ledenyov and Viktor O. Ledenyov
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最新提交年份：
2015
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英文摘要：
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.
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中文摘要：
并购交易代表了企业转型交易中一系列独特的业务优化机会，这些交易通常具有高风险的特点。通过考虑投资规模、购买价格、交易方向、交易类型，并使用现代可比交易分析和金融领域扩散型金融系统中的商业估值技术，可以成功实施并购交易。我们使用嵌入式优化近实时人工智能算法开发了MicroMA软件程序，利用相关公司的财务绩效特征，创建成功的良性M和A策略，并估计M和交易完成成功的概率。我们认为，M和A交易数在一定时间段内的波动依赖性是准周期的。我们认为有很多因素可以在时域内产生M和交易数的准周期振荡，例如：股市泡沫效应。我们在Matlab中研究了M和A数准周期振荡的非线性，包括理想、线性、二次和指数依赖性。我们发现，M和a时间序列中的随机数之和的平均值代表了一个具有准周期系统振荡的时间序列，可以用多项式数很好地近似。我们认为，在并购和交易实施过程中，公司吸收新获得的知识并创建新的创新知识库的能力是并购和交易成功的关键先决条件，就像在瑞士一样。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：General Finance 一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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