Hartmann’s Question of “Being as Being” and M. Heidegger’s Question of “The Meaning of Being”: Two Views over Ontology

The article addresses two versions of returning to ontology and two views on the nature of ontology. The aim of the article is to reveal the way two 20th century philosophers—Nicolai Hartmann and Martin Heidegger—saw the meaning and purpose of ontology, as well as the answer to the question as to why each of them thought that the other’s ontological approach was fundamentally flawed. My investigation is based on Hartmann’s book Ontology: Laying the Foundations and Heidegger’s book Being and Time. Hartmann’s option of returning to ontology implies the question about being as being. It is impossible to reduce being as being (being as such) to being in some definite, limited sense. Thus, being as being possesses absolute universality and cannot be defined, albeit one can distinguish some structure in it. Not only being is always both being-there (Dasein) and being-so (Sosein), but being is also always either real or ideal. Hartmann is certain that the restriction of being as being to being in some definite sense and the miscomprehension of that four-component system leads up to various errors. According to Hartmann, Heidegger misses the ontological question because he puts the question on being as it is given instead of that on being as it is in itself. According to Heidegger, Hartmann misses the ontological question because he stays on the grounds of the unrestricted speculations instead of understanding being and its meaning by means of being itself. The question arises as to who of them is right. As a matter of fact, there are no arguments that both philosophers would deem acceptable. Each of them is deaf to the opponent’s opinion. In addition, we are not obligated to accept neither Heidegger nor Hartman’s opinion because there are certainly more than just two views on ontology

Predictable markets? A news-driven model of the stock market

We attempt to explain stock market dynamics in terms of the interaction among three variables: market price, investor opinion and information flow. We propose a framework for such interaction and apply it to build a model of stock market dynamics which we study both empirically and theoretically. We demonstrate that this model replicates observed market behavior on all relevant timescales (from days to years) reasonably well. Using the model, we obtain and discuss a number of results that pose implications for current market theory and offer potential practical applications.Comment: This is the version accepted for publication in a new journal Algorithmic Finance (http://algorithmicfinance.org). A draft was posted here on 29 Apri

DSG: An End-to-End Document Structure Generator

Information in industry, research, and the public sector is widely stored as rendered documents (e.g., PDF files, scans). Hence, to enable downstream tasks, systems are needed that map rendered documents onto a structured hierarchical format. However, existing systems for this task are limited by heuristics and are not end-to-end trainable. In this work, we introduce the Document Structure Generator (DSG), a novel system for document parsing that is fully end-to-end trainable. DSG combines a deep neural network for parsing (i) entities in documents (e.g., figures, text blocks, headers, etc.) and (ii) relations that capture the sequence and nested structure between entities. Unlike existing systems that rely on heuristics, our DSG is trained end-to-end, making it effective and flexible for real-world applications. We further contribute a new, large-scale dataset called E-Periodica comprising real-world magazines with complex document structures for evaluation. Our results demonstrate that our DSG outperforms commercial OCR tools and, on top of that, achieves state-of-the-art performance. To the best of our knowledge, our DSG system is the first end-to-end trainable system for hierarchical document parsing.Comment: Accepted at ICDM 202

Forecasting stock market returns over multiple time horizons

In this paper we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we introduce investors with different investment horizons into the news-driven, analytic, agent-based market model developed in Gusev et al. (2015). This heterogeneous framework enables us to capture dynamics at multiple timescales, expanding the model's applications and improving precision. We study the heterogeneous model theoretically and empirically to highlight essential mechanisms underlying certain market behaviors, such as transitions between bull- and bear markets and the self-similar behavior of price changes. Most importantly, we apply this model to show that the stock market is nearly efficient on intraday timescales, adjusting quickly to incoming news, but becomes inefficient on longer timescales, where news may have a long-lasting nonlinear impact on dynamics, attributable to a feedback mechanism acting over these horizons. Then, using the model, we design algorithmic strategies that utilize news flow, quantified and measured, as the only input to trade on market return forecasts over multiple horizons, from days to months. The backtested results suggest that the return is predictable to the extent that successful trading strategies can be constructed to harness this predictability.Comment: This is the version accepted for publication in a journal Quantitative Finance. A draft was posted here on 18 August 2015. 50 page

Experience in the surgical management of children with complicated crohn's disease

Objective: To present experience in pre-surgical diagnosis, selection of surgical tactics and volume of intervention in different variants of gastrointestinal tract lesions and disease activity. Materials and methods: We undertook cross-sectional, retrospective-prospective study of 64 children who underwent surgery due to complicated CD. We analyzed CD activity via PCDAI, medications used, inflammation localization, and changes in mass-growth parameters at pre-surgery stage. Results: Three patients from the group of 44 children with two-stage surgical treatment later showed inefficacy of GEBD in post-operative period. The disease progression was revealed and, therefore, subtotal colectomy was required. Three children had secondary adhesion of surgical wounds by means of active immunosuppressive therapy at preoperative period, and five patients developed suture sinuses at post-operative period. Early adhesive intestinal obstruction was revealed in 3 (4.7%) cases, and they required re-surgery. Conclusions: Personalized approach to the surgical treatment of children with complicated CD has shown its efficacy due to the small percentage of postoperative complications with re-surgery. There was significant improvement in mass-growth parameters, recovery of albumin levels, and anemia decrease in 96.9% of cases in the long-term postoperative period (6 months or more)