Searcharxiv⌕ Search

arXiv subjects

Zoran Utkovski

Publications and source records attributed to Zoran Utkovski.

35 records · Page 2Linked to original sources

Option Pricing with Heavy-Tailed Distributions of Logarithmic Returns

A growing body of literature suggests that heavy tailed distributions represent an adequate model for the observations of log returns of stocks. Motivated by these findings, here we develop a discrete time framework for pricing of European options. Probability density functions of log returns for different periods are conveniently taken to be convolutions of the Student's t-distribution with three degrees of freedom. The supports of these distributions are truncated in order to obtain finite values for the options. Within this framework, options with different strikes and maturities for one stock rely on a single parameter -- the standard deviation of the Student's t-distribution for unit period. We provide a study which shows that the distribution support width has weak influence on the option prices for certain range of values of the width. It is furthermore shown that such family of truncated distributions approximately satisfies the no-arbitrage principle and the put-call parity. The relevance of the pricing procedure is empirically verified by obtaining remarkably good match of the numerically computed values by our scheme to real market data.

q-fin.PR↗

Correlation Patterns in Foreign Exchange Markets

The value of an asset in a financial market is given in terms of another asset known as numeraire. The dynamics of the value is non-stationary and hence, to quantify the relationships between different assets, one requires convenient measures such as the means and covariances of the respective log returns. Here, we develop transformation equations for these means and covariances when one changes the numeraire. The results are verified by a thorough empirical analysis capturing the dynamics of numerous assets in a foreign exchange market. We show that the partial correlations between pairs of assets are invariant under the change of the numeraire. This observable quantifies the relationship between two assets, while the influence of the rest is removed. As such the partial correlations uncover intriguing observations which may not be easily noticed in the ordinary correlation analysis.

q-fin.ST↗

Cooperation dynamics of generalized reciprocity in state-based social dilemmas

We introduce a framework for studying social dilemmas in networked societies where individuals follow a simple state-based behavioral mechanism based on generalized reciprocity, which is rooted in the principle "help anyone if helped by someone". Within this general framework, which applies to a wide range of social dilemmas including, among others, public goods, donation and snowdrift games, we study the cooperation dynamics on a variety of complex network examples. By interpreting the studied model through the lenses of nonlinear dynamical systems, we show that cooperation through generalized reciprocity always emerges as the unique attractor in which the overall level of cooperation is maximized, while simultaneously exploitation of the participating individuals is prevented. The analysis elucidates the role of the network structure, here captured by a local centrality measure which uniquely quantifies the propensity of the network structure to cooperation, by dictating the degree of cooperation displayed both at microscopic and macroscopic level. We demonstrate the applicability of the analysis on a practical example by considering an interaction structure that couples a donation process with a public goods game.

q-bio.PE↗

Economic Complexity Unfolded: Interpretable Model for the Productive Structure of Economies

Economic complexity reflects the amount of knowledge that is embedded in the productive structure of an economy. It resides on the premise of hidden capabilities - fundamental endowments underlying the productive structure. In general, measuring the capabilities behind economic complexity directly is difficult, and indirect measures have been suggested which exploit the fact that the presence of the capabilities is expressed in a country's mix of products. We complement these studies by introducing a probabilistic framework which leverages Bayesian non-parametric techniques to extract the dominant features behind the comparative advantage in exported products. Based on economic evidence and trade data, we place a restricted Indian Buffet Process on the distribution of countries' capability endowment, appealing to a culinary metaphor to model the process of capability acquisition. The approach comes with a unique level of interpretability, as it produces a concise and economically plausible description of the instantiated capabilities.

econ.EM↗

Sparse Three-parameter Restricted Indian Buffet Process for Understanding International Trade

This paper presents a Bayesian nonparametric latent feature model specially suitable for exploratory analysis of high-dimensional count data. We perform a non-negative doubly sparse matrix factorization that has two main advantages: not only we are able to better approximate the row input distributions, but the inferred topics are also easier to interpret. By combining the three-parameter and restricted Indian buffet processes into a single prior, we increase the model flexibility, allowing for a full spectrum of sparse solutions in the latent space. We demonstrate the usefulness of our approach in the analysis of countries' economic structure. Compared to other approaches, empirical results show our model's ability to give easy-to-interpret information and better capture the underlying sparsity structure of data.

cs.LG↗

Multiplex Network Structure Enhances the Role of Generalized Reciprocity in Promoting Cooperation

In multi-agent systems, cooperative behavior is largely determined by the network structure which dictates the interactions among neighboring agents. These interactions often exhibit multidimensional features, either as relationships of different types or temporal dynamics, both of which may be modeled as a "multiplex" network. Against this background, here we advance the research on cooperation models inspired by generalized reciprocity, a simple pay-it-forward behavioral mechanism, by considering a multidimensional networked society. Our results reveal that a multiplex network structure can act as an enhancer of the role of generalized reciprocity in promoting cooperation by acting as a latent support, even when the parameters in some of the separate network dimensions suggest otherwise (i.e. favor defection). As a result, generalized reciprocity forces the cooperative contributions of the individual agents to concentrate in the dimension which is most favorable for the existence of cooperation.

q-bio.PE↗

Promoting cooperation by preventing exploitation: The role of network structure

A growing body of empirical evidence indicates that social and cooperative behavior can be affected by cognitive and neurological factors, suggesting the existence of state-based decision-making mechanisms that may have emerged by evolution. Motivated by these observations, we propose a simple mechanism of anonymous network interactions identified as a form of generalized reciprocity - a concept organized around the premise "help anyone if helped by someone", and study its dynamics on random graphs. In the presence of such mechanism, the evolution of cooperation is related to the dynamics of the levels of investments (i.e. probabilities of cooperation) of the individual nodes engaging in interactions. We demonstrate that the propensity for cooperation is determined by a network centrality measure here referred to as neighborhood importance index and discuss relevant implications to natural and artificial systems. To address the robustness of the state-based strategies to an invasion of defectors, we additionally provide an analysis which redefines the results for the case when a fraction of the nodes behave as unconditional defectors.

q-bio.PE↗

Performance Limits of Energy Detection Systems with Massive Receiver Arrays

Energy detection (ED) is an attractive technique for symbol detection at receivers equipped with a large number of antennas, for example in millimeter wave communication systems. This paper investigates the performance bounds of ED with pulse amplitude modulation (PAM) in large antenna arrays under single stream transmission and fast fading assumptions. The analysis leverages information-theoretic tools and semi-numerical approach to provide bounds on the information rate, which are shown to be tight in the low and high signal-to-noise ratio (SNR) regimes, respectively. For a fixed constellation size, the impact of the number of antennas and SNR on the achievable information rate is investigated. Based on the results, heuristics are provided for the choice of the cardinality of the adaptive modulation scheme as a function of the SNR and the number of antennas.

cs.IT↗

Random Access in C-RAN for User Activity Detection with Limited-Capacity Fronthaul

Cloud-Radio Access Network (C-RAN) is characterized by a hierarchical structure in which the baseband processing functionalities of remote radio heads (RRHs) are implemented by means of cloud computing at a Central Unit (CU). A key limitation of C-RANs is given by the capacity constraints of the fronthaul links connecting RRHs to the CU. In this letter, the impact of this architectural constraint is investigated for the fundamental functions of random access and active User Equipment (UE) identification in the presence of a potentially massive number of UEs. In particular, the standard C-RAN approach based on quantize-and-forward and centralized detection is compared to a scheme based on an alternative CU-RRH functional split that enables local detection. Both techniques leverage Bayesian sparse detection. Numerical results illustrate the relative merits of the two schemes as a function of the system parameters.

cs.IT↗

The Impact of Services on Economic Complexity: Service Sophistication as Route for Economic Growth

Economic complexity reflects the amount of knowledge that is embedded in the productive structure of an economy. By combining tools from network science and econometrics, a robust and stable relationship between a country's productive structure and its economic growth has been established. Here we report that not only goods but also services are important for predicting the rate at which countries will grow. By adopting a terminology which classifies manufactured goods and delivered services as products, we investigate the influence of services on the country's productive structure. In particular, we provide evidence that complexity indices for services are in general higher than those for goods, which is reflected in a general tendency to rank countries with developed service sector higher than countries with economy centred on manufacturing of goods. By focusing on country dynamics based on experimental data, we investigate the impact of services on the economic complexity of countries measured in the product space (consisting of both goods and services). Importantly, we show that diversification of service exports and its sophistication can provide an additional route for economic growth in both developing and developed countries.

econ.GN↗

Finite-SNR Bounds on the Sum-Rate Capacity of Rayleigh Block-Fading Multiple-Access Channels with no a Priori CSI

We provide nonasymptotic upper and lower bounds on the sum-rate capacity of Rayleigh block-fading multiple-access channels for the setup where a priori channel state information is not available. The upper bound relies on a dual formula for channel capacity and on the assumption that the users can cooperate perfectly. The lower bound is derived assuming a noncooperative scenario, where each user employs unitary space-time modulation (independently from the other users). Numerical results show that the gap between the upper and the lower bound is small already at moderate SNR values. This suggests that the sum-rate capacity gains obtainable through user cooperation are minimal.

cs.IT↗

Random Access Protocols with Collision Resolution in a Noncoherent Setting

Wireless systems are increasingly used for Machine-Type Communication (MTC), where the users sporadically send very short messages. In such a setting, the overhead imposed by channel estimation is substantial, thereby demanding noncoherent communication. In this paper we consider a noncoherent setup in which users randomly access the medium to send short messages to a common receiver. We propose a transmission scheme based on Gabor frames, where each user has a dedicated codebook of M possible codewords, while the codebook simultaneously serves as an ID for the user. The scheme is used as a basis for a simple protocol for collision resolution.

cs.IT↗

On Energy-efficiency in Wireless Networks: A Game-theoretic Approach to Cooperation Inspired by Evolutionary Biology

We develop a game-theoretic framework to investigate the effect of cooperation on the energy efficiency in wireless networks. We address two examples of network architectures, resembling ad-hoc network and network with central infrastructure node. Most present approaches address the issue of energy efficiency in communication networks by using complex algorithms to enforce cooperation in the network, followed by extensive signal processing at the network nodes. Instead, we address cooperative communication scenarios which are governed by simple, evolutionary-like, local rules, and do not require strategic complexity of the network nodes. The approach is motivated by recent results in evolutionary biology which suggest that cooperation can emerge in Nature by evolution, i. e. can be favoured by natural selection, if certain mechanism is at work. As result, we are able to show by experiments that cooperative behavior can indeed emerge and persist in wireless networks, even if the behavior of the individual nodes is driven by selfish decision making. The results from this work indicate that uncomplicated local rules, followed by simple fitness evaluation, can promote cooperation and generate network behavior which yields global energy efficiency in certain wireless networks.

cs.NI↗

Energy-efficiency in Decentralized Wireless Networks: A Game-theoretic Approach inspired by Evolutionary Biology

Energy efficiency is gaining importance in wireless communication networks which have nodes with limited energy supply and signal processing capabilities. We present a numerical study of cooperative communication scenarios based on simple local rules. This is in contrast to most of the approaches in the literature which enforce cooperation by using complex algorithms and require strategic complexity of the network nodes. The approach is motivated by recent results in evolutionary biology which suggest that, if certain mechanism is at work, cooperation can be favoured by natural selection, i. e. even selfish actions of the individual nodes can lead to emergence of cooperative behaviour in the network. The results of the simulations in the context of wireless communication networks verify these observations and indicate that uncomplicated local rules, followed by simple fitness evaluation, can generate network behaviour which yields global energy efficiency.

cs.NI↗

Protocol Coding through Reordering of User Resources: Applications and Capacity Results

While there are continuous efforts to introduce new communication systems and standards, it is legitimate to ask the question: how can one send additional bits by minimally changing the systems that are already operating? This is of a significant practical interest, since it has a potential to generate additional value of the systems through, for example, introduction of new devices and only a software update of the access points or base stations, without incurring additional cost for infrastructure hardware installation. The place to look for such an opportunity is the communication protocol and we use the term *protocol coding* to refer to strategies for sending information by using the degrees of freedom available when one needs to decide the actions taken by a particular communication protocol. In this paper we consider protocol coding that gives a rise to *secondary communication channels*, defined by combinatorial ordering of the user resources (packets, channels) in a primary (legacy) communication system. We introduce communication models that enable us to compute the capacity of such secondary channels under suitable restrictions imposed by the primary systems. We first show the relation to the capacity of channels with causal channel state information at the transmitter (CSIT), originally considered by Shannon. By using the specific communication setup, we develop an alternative framework for achieving the capacity and we discuss coding strategies that need to be used over the secondary channels. We also discuss some practical features of the secondary channels and their applications that add value to the existing wireless systems.

cs.IT↗

Protocol Coding through Reordering of User Resources, Part I: Capacity Results

The vast existing wireless infrastructure features a variety of systems and standards. It is of significant practical value to introduce new features and devices without changing the physical layer/hardware infrastructure, but upgrade it only in software. A way to achieve it is to apply protocol coding: encode information in the actions taken by a certain (existing) communication protocol. In this work we investigate strategies for protocol coding via combinatorial ordering of the labelled user resources (packets, channels) in an existing, primary system. Such a protocol coding introduces a new secondary communication channel in the existing system, which has been considered in the prior work exclusively in a steganographic context. Instead, we focus on the use of secondary channel for reliable communication with newly introduced secondary devices, that are low-complexity versions of the primary devices, capable only to decode the robustly encoded header information in the primary signals. We introduce a suitable communication model, capable to capture the constraints that the primary system operation puts on protocol coding. We have derived the capacity of the secondary channel under arbitrary error models. The insights from the information-theoretic analysis are used in Part II of this work to design practical error-correcting mechanisms for secondary channels with protocol coding.

cs.IT↗

Protocol Coding through Reordering of User Resources, Part II: Practical Coding Strategies

We use the term protocol coding to denote the communication strategies in which information is encoded through the actions taken by a certain communication protocol. In this work we investigate strategies for protocol coding via combinatorial ordering of the labelled user resources (packets, channels) in an existing, primary system. This introduces a new, secondary communication channel in the existing system, which has been considered in the prior work exclusively in a steganographic context. Instead, we focus on the use of secondary channel for reliable communication with newly introduced secondary devices, that are low-complexity versions of the primary devices, capable only to decode the robustly encoded header information in the primary signals. In Part I of the work we have characterized the capacity of the secondary channel through information-theoretic analysis. In this paper we consider practical strategies for protocol coding inspired by the information-theoretic analysis. It turns out that the insights from Part I are instrumental for devising superior design of error-control codes. This is demonstrated by comparing the error performance to the "na"ıve" strategy which is presumably available without carrying out the analysis in Part I. These results are clearly outlining both the conceptual novelty behind the discussed concept of secondary channel as well as its practical applicability.

cs.IT↗