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Leading one's life as a person is an essential feature of our human existence which is constitutively characterized by finiteness, sociality and vulnerability. Within the framework of a pragmatistic anthropology central features of our being persons (i.e. personal identity, self-consciousness, freedom, autonomy and responsibility) are made explicit in this study. The such unfolded conception is anthropological in the sense of being restricted to the human life-form. The explication is pragmatistic in a double sense: Firstly, action is taken as a complex and not reducible basic feature; secondly, the study is committed to the pragmatistic model of justification. Leading one's life as a human person, this is the study's central thesis, is realized in constellations of recognition (intersubjective or institutionally framed). These can be made explicit as basic grammar of our evaluative Praxis within an ascriptivist framework.

Data Science is a bridge discipline connecting fundamental science, applied disciplines, and the arts. The demand for novel data science methods is well established. However, there is much less agreement on the core aspects of representation, modeling, and analytics that involve huge and heterogeneous datasets. The scientific community needs to build consensus about data science education and training curricula, including the necessary entry matriculation prerequisites and the expected learning competency outcomes needed to tackle complex big data challenges. To meet the rapidly increasing demand for effective evidence-based practice and data analytic methods, research teams, funding agencies, academic institutions, politicians, and industry leaders should embrace innovation, promote high-risk projects, join forces to expand the technological capacity, and enhance the workforce skills.

Qualitative researchers commonly perceive that positivist hard-science researchers and policies of governments deprecate qualitative methods and approaches. Curiously though, we could not see anyone asking quantitative researchers 'What do you think about qualitative approaches and methods?' We did this in interviews with 17 assumed quantitative researchers in the fields of advanced materials construction, civil engineering, transport modelling, computer science, and geotechnics. Surprisingly, these researchers rarely described themselves as purely quantitative, and were rarely against the five qualitative methods discussed. Moreover, many actually used qualitative methods, often in ways we had not anticipated. Drawing on a Bakhtinian grounded framework, we present our analysis as a performed ethnographic dialogue between data extracts and research literature. We present evidence that the alleged qualitative-quantitative divide does not apply here, and suggest dialogic ways to see teach "qualitative" and "quantitative" and some associated terms.

Alan Greenspan's paper (March 2010) presents his retrospective view of the crisis. His theme has several parts. First, the housing price bubble, its subsequent collapse and the financial crisis were not predicted either by the market, the FED, the IMF or the regulators in the years leading to the current crisis. Second, financial intermediation tried to function on too thin layer of capital - high leverage - owing to a misreading of the degree of risk embodied in ever more complex financial products and markets. Third, the breakdown was unpredictable and inevitable, given the 'excessive' leverage - or low capital - of the financial intermediaries. The proposed legislation for the 'reform' of the financial system requires that the FED "identify, measure, manage and mitigate risks to the financial stability of the United States". The focus is upon capital requirements or debt ratios. The 'Quants' ignored systemic risk and just focused upon risk transfer in very liquid markets. The FED, IMF, Treasury and the 'Quants'/market lacked the appropriate tools of analysis to answer the following questions: what is an optimal leverage or capital requirement that balances the expected growth against risk? What are theoretically founded early warning signals of a crisis? The author explains why the application of stochastic optimal control (SOC)/dynamic risk management is an effective approach to determine the optimal degree of leverage, the optimum and excessive risk and the probability of a debt crisis. The theoretically derived early warning signal of a crisis is the excess debt ratio, equal to the difference between the actual and optimal ratio. The excess debt starting from 2004-05 indicated that a crisis was most likely. This SOC analysis should be used by those charged with surveillance of financial markets.

This book is a quantitative quide to barrier options in FX environments. Barrier options are a class of highly path-dependent exotic options which present particular challenges to practitioners in all areas of the financial industry. They are traded in large volumes as stand-alone contracts in the FX options market, and are second only to vanilla options, representing a huge portion of this trillion dollar market. Structured products in FX commonly include barrier features, and in order to analyse the effect these features have on the overall structured product, it is important first to understand how individual barrier options work. This book takes a quantitative approach to barrier options in FX environments. Its primary perspectives are those of quantitative analysts, both in the front office and in control functions. It will derive, demonstrate and analyse a wide range of models, modelling techniques and numerical algorithms that can be used for constructing valuation and risk-management models across a range of scenarios. Coverage will include

Innovative insights on creating models that will help you become a disciplined intelligent investorThe pioneer of value investing, Benjamin Graham, believed in a philosophy that continues to be followed by some of today's most successful investors, such as Warren Buffett. Part of this philosophy includes adhering to your stock selection process come "hell or high water" which, in his view, was one of the most important aspects of investing. So, if a quant designs and implements mathematical models for predicting stock or market movements, what better way to remain objective, then to invest usin.