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Inga Ivanova

Publications and source records attributed to Inga Ivanova.

14 recordsLinked to original sources

Mechanisms of information communication and market price movements. The case of SP 500 market

In this paper we analyze how market prices change in response to information processing among the market participants and how non-linear information dynamics drive market price movement. We analyze historical data of the SP 500 market for the period 1950 -2025 using the logistic Continuous Wavelet Transformation method. This approach allows us to identify various patterns in market dynamics. These patterns are conceptualized using a new theory of reflexive communication of information in a market consisting of heterogeneous agents who assign meaning to information from different perspectives. This allows us to describe market dynamics and make forecasts of its development using the most general mechanisms of information circulation within the content-free approach.

q-fin.ST

Towards the Structure and Mechanisms of Complex Systems, the Approach of the Quantitative Theory of Meaning

We study analysis of complex systems using a Quantitative Theory of Meaning developed as an extention of Shannon's Communication Theory. The approach consideres complexity not in terms of the manifestation of its effects which are manifestation of the dynamics of the system, but in terms of primary causes and taking into account the topology of the system. Here, the dynamics of the system are provided by reflexive communication between heterogenious agents that make up the system. Unlike Shannon's Communication Theory the Theory of Meaning imposes restrictions on the complex systems being analyzed. Non-linearity and specific dynamics of the system arise as a consequence of the topology of the system. This topology also suggests a method for analyzing complex systems, the logistic Continuous Wavelet Transform (CWT). The paper also lays the foundation for future research in various fields studying complex systems of interacting geterogeneous agents, which may form a new paradigm for better understanding the structure, mechanisms, and dynamics of complex systems.

cs.CY

Quantitative Theory of Meaning. Application to Financial Markets. EUR/USD case study

The paper focuses on the link between information, investors' expectations and market price movement. EUR/USD market is examined from communication-theoretical perspective on the dynamics of information and meaning. We build upon the quantitative theory of meaning as a complement to the quantitative theory of information. Different groups of investors entertain different criteria to process information, so that the same information can be supplied with different meanings. Meanings shape investors' expectations which are revealed in market asset price movement. This dynamics can be captured by non-linear evolutionary equation. We use a computationally efficient technique of logistic Continuous Wavelet Transformation (CWT) to analyze EUR/USD market. The results reveal the latent EUR/USD trend structure which coincides with the model predicted time series indicating that proposed model can adequately describe some patterns of investors' behavior. Proposed methodology can be used to better understand and forecast future market assets' price movement.

cs.CY

Triple Helix synergy and patent dynamics. Cross country compartison

We use a computationally efficient technique of Logistic Continuous Wavelet transform (CWT) to analyze patent data for Switzerland, Germany, USA, and Brszil for the period 1980-2000. We found that patent growth dynamics follows the dynamics of innovation system synergy in the framework of Triple Helix model of innovations where observed non-linear actors' interactions are provided by biased information exchange between heterogenious actors. Suggested approach reveals the latent trend structure in patent and innovation dynamics and may help policymakers identify the potential drivers of patent and innovation activity and form informed policy for boosting innovation development. The paper also privides a foundation for future research in differnt fields studying complex systems of interacting heterogenious agents.

physics.soc-ph

communication of information in systems of heterogenious agents and systems' dynamics

Communication of information in complex systems can be considered as major driver of systems evolution. What matters is not the communicated information by itself but rather the meaning that is supplied to the information. However informational exchange in a system of heterogenious agents, which code and decode information with different meaning processing structures, is more complex than simple input-output model. The structural difference of coding and decoding algorithms in a system of three or more groups of agents, entertaining different sets of communication codes,provide a source of additional options which has an impact on system's dynamics. The mechanisms of meaning and information processing can be evaluated analytically ion a model framework. The results show that model predictions acccurately fit empirically observed data in systems of different origions.

cs.CY

Evolutionary Dynamics of Investors Expectations and Market Price Movement

The paper presents a step forward into the development of the theory of meaning. Stock and financial markets are examined from communication-theoretical perspective on the dynamics of information and meaning. This study focuses on the link between the dynamics of investors' expectations and market price movement. The model for market asset price dynamiscs, based on non-linear evolutionary equation linking investors' expectations and market asset price movement, is provided. Model predictions are tested on various FX, energy, food, and indices markets along different time frames. The results suggest that model predicted time series is co-integrated with asset time series which implies that the prop[osed model can be used to forecast future price movement.

q-fin.ST

Toward a Calculus of Redundancy: The feedback arrow of expectations in knowledge-based systems

This paper considers the relationships among meaning generation, selection, and the dynamics of discourse from a variety of perspectives ranging from information theory and biology to sociology. Following Husserl's idea of a horizon of meaning in intersubjective communication, we propose a way in which, using Shannon's equations, the generation and selection of meanings from a horizon of possibilities can be considered probabilistically. The information-theoretical dynamics we articulate considers a process of meaning generation within cultural evolution: information is imbued with meaning, and through this process, the number of options for the selection of meaning in discourse proliferates. The redundancy of possible meanings contributes to a codification of expectations within the discourse. Unlike hard-wired DNA, the codes of non-biological systems can co-evolve with the variations. Spanning horizons of meaning, the codes structure the communications as selection environments that shape discourses. Discursive knowledge can be considered as meta-coded communication which enables us to translate among differently coded communications. The dynamics of discursive knowledge production can thus infuse the historical dynamics with a cultural evolution by adding options, that is, by increasing redundancy. A calculus of redundancy is presented as an indicator whereby these dynamics of discourse and meaning may be explored empirically.

cs.DL

"Open Innovation" and "Triple Helix" Models of Innovation: Can Synergy in Innovation Systems Be Measured?

The model of "Open Innovations" (OI) can be compared with the "Triple Helix of University-Industry-Government Relations" (TH) as attempts to find surplus value in bringing industrial innovation closer to public R&D. Whereas the firm is central in the model of OI, the TH adds multi-centeredness: in addition to firms, universities and (e.g., regional) governments can take leading roles in innovation eco-systems. In addition to the (transversal) technology transfer at each moment of time, one can focus on the dynamics in the feedback loops. Under specifiable conditions, feedback loops can be turned into feedforward ones that drive innovation eco-systems towards self-organization and the auto-catalytic generation of new options. The generation of options can be more important than historical realizations ("best practices") for the longer-term viability of knowledge-based innovation systems. A system without sufficient options, for example, is locked-in. The generation of redundancy -- the Triple Helix indicator -- can be used as a measure of unrealized but technologically feasible options given a historical configuration. Different coordination mechanisms (markets, policies, knowledge) provide different perspectives on the same information and thus generate redundancy. Increased redundancy not only stimulates innovation in an eco-system by reducing the prevailing uncertainty; it also enhances the synergy in and innovativeness of an innovation system.

cs.CY

What is the effect of synergy in international collaboration on regional economies?

We analyze the effects of relative increments of mutual information among the geographical, technological, and organizational distributions of firms on the relative augmentation of regional summary turnover in terms of synergies. How do increases in synergy in international cooperation affect regional turnover? The methodological contribution of this study is that we translate the synergy (abstractly measured in bits of information) into more familiar economic terms, such as turnover for the special case of domestic-foreign collaborations. The analysis is based on Norwegian data, as Norway is a small country with an open and export-oriented economy. Data for Norway is publicly available in great detail.

cs.CY

The Self-Organization of Meaning and the Reflexive Communication of Information

Following a suggestion of Warren Weaver, we extend the Shannon model of communication piecemeal into a complex systems model in which communication is differentiated both vertically and horizontally. This model enables us to bridge the divide between Niklas Luhmann's theory of the self-organization of meaning in communications and empirical research using information theory. First, we distinguish between communication relations and correlations among patterns of relations. The correlations span a vector space in which relations are positioned and can be provided with meaning. Second, positions provide reflexive perspectives. Whereas the different meanings are integrated locally, each instantiation opens global perspectives--"horizons of meaning"--along eigenvectors of the communication matrix. These next-order codifications of meaning can be expected to generate redundancies when interacting in instantiations. Increases in redundancy indicate new options and can be measured as local reduction of prevailing uncertainty (in bits). The systemic generation of new options can be considered as a hallmark of the knowledge-based economy.

cs.IT

Economic and Technological Complexity: A Model Study of Indicators of Knowledge-based Innovation Systems

The Economic Complexity Index (ECI; Hidalgo & Hausmann, 2009) measures the complexity of national economies in terms of product groups. Analogously to ECI, a Patent Complexity Index (PatCI) can be developed on the basis of a matrix of nations versus patent classes. Using linear algebra, the three dimensions: countries, product groups, and patent classes can be combined into a measure of "Triple Helix" complexity (THCI) including the trilateral interaction terms between knowledge production, wealth generation, and (national) control. THCI can be expected to capture the extent of systems integration between the global dynamics of markets (ECI) and technologies (PatCI) in each national system of innovation. We measure ECI, PatCI, and THCI during the period 2000-2014 for the 34 OECD member states, the BRICS countries, and a group of emerging and affiliated economies (Argentina, Hong Kong, Indonesia, Malaysia, Romania, and Singapore). The three complexity indicators are correlated between themselves; but the correlations with GDP per capita are virtually absent. Of the world's major economies, Japan scores highest on all three indicators, while China has been increasingly successful in combining economic and technological complexity. We could not reproduce the correlation between ECI and average income that has been central to the argument about the fruitfulness of the economic complexity approach.

econ.GN

Knowledge-generating Efficiency in Innovation Systems: The relation between structural and temporal effects

Using time series of US patents per million inhabitants, knowledge-generating cycles can be distinguished. These cycles partly coincide with Kondratieff long waves. The changes in the slopes between them indicate discontinuities in the knowledge-generating paradigms. The knowledge-generating paradigms can be modeled in terms of interacting dimensions (for example, in university-industry-government relations) that set limits to the maximal efficiency of innovation systems. The maximum values of the parameters in the model are of the same order as the regression coefficients of the empirical waves. The mechanism of the increase in the dimensionality is specified as self-organization which leads to the breaking of existing relations into the more diversified structure of a fractal-like network. This breaking can be modeled in analogy to 2D and 3D (Koch) snowflakes. The boost of knowledge generation leads to newly emerging technologies that can be expected to be more diversified and show shorter life cycles than before. Time spans of the knowledge-generating cycles can also be analyzed in terms of Fibonacci numbers. This perspective allows for forecasting expected dates of future possible paradigm changes. In terms of policy implications, this suggests a shift in focus from the manufacturing technologies to developing new organizational technologies and formats of human interactions

cs.CY

Synergy cycles in the Norwegian innovation system: The relation between synergy and cycle values

The knowledge base of an economy measured in terms of Triple Helix relations can be analyzed in terms of mutual information among geographical, sectorial, and size distributions of firms as dimensions of the probabilistic entropy. The resulting synergy values of a TH system provide static snapshots. In this study, we add the time dimension and analyze the synergy dynamics using the Norwegian innovation system as an example. The synergy among the three dimensions can be mapped as a set of partial time series and spectrally analyzed. The results suggest that the synergy at the level of both the country and its 19 counties shoe non-chaotic oscillatory behavior and resonates in a set of natural frequencies. That is, synergy surges and drops are non-random and can be analyzed and predicted. There is a proportional dependence between the amplitudes of oscillations and synergy values and an inverse proportional dependence between the oscillation frequencies' relative inputs and synergy values. This analysis of the data informs us that one can expect frequency-related synergy-volatility growth in relation to the synergy value and a shift in the synergy volatility towards the long-term fluctuations with the synergy growth.

cs.CY

Redundancy Generation in University-Industry-Government Relations: The Triple Helix Modeled, Measured, and Simulated

A Triple Helix (TH) of bi- and trilateral relations among universities, industries, and governments can be considered as an ecosystem in which uncertainty can be reduced auto-catalytically. The correlations among the distributions of relations span a vector space in which two vectors (P and Q) represent "sending" and "receiving," respectively. These vectors can also be understood in terms of the generation versus reduction of uncertainty in the communication field that results from interactions among the three (bi-lateral) communication channels. We specify a set of Lotka-Volterra equations between the vectors that can be solved. Redundancy generation can then be simulated and the results can be decomposed in terms of the TH components. Among other things, we show that the strength and frequency of the relations are independent parameters. Different components in terms of frequencies in triple-helix systems can also be distinguished and interpreted using Fourier analysis of the empirical time-series. The case of co-authorship relations in Japan is analyzed as an empirical example; but "triple contingencies" in an ecosystem of relations can also be considered more generally as a model for redundancy generation by providing meaning to the (Shannon-type) information in inter-human communications.

cs.CY