SEARCH · Searcharxiv

Results for “q-fin.GN”

Search indexed arXiv papers on artificial intelligence, large language models, computer vision and robotics. Read source abstracts and follow links to arXiv.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15Linked to original sources

arXiv2011

Knowledge Dispersion Index for Measuring Intellectual Capital

In this paper we propose a novel index to quantify and measure the flow of information on macro and micro scales. We discuss the implications of this index for knowledge management fields and also as intellectual capital that can thus be utilized by entrepreneurs. We explore different function and human oriented metrics that can be used at micro-scales to process the flow of information. We present a table of about 23 metrics, such as change in IT inventory and percentage of employees with advanced degrees, that can be used at micro scales to wholly quantify knowledge dispersion as intellectual capital. At macro scales we split the economy in an industrial and consumer sector where the flow of information in each determines how fast an economy is going to grow and how overall an economy will perform given the aggregate demand. Lastly, we propose a model for knowledge dispersion based on graph theory and show how corrections in the flow become self-evident. Through the principals of flow conservation and capacity constrains we also speculate how this flow might seeks some equilibrium and exhibit self-correction codes. This proposed model allows us to account for perturbations in form of local noise, evolution of networks, provide robustness against local damage from lower nodes, and help determine the underlying classification into network super-families.

cs.SI↗

arXiv2011

Learning, investments and derivatives

The recent crisis and the following flight to simplicity put most derivative businesses around the world under considerable pressure. We argue that the traditional modeling techniques must be extended to include product design. We propose a quantitative framework for creating products which meet the challenge of being optimal from the investors point of view while remaining relatively simple and transparent.

q-fin.GN↗

arXiv2011

A model of coopetitive game and the Greek crisis

In the present work we propose an original analytical model of coopetitive game. We try to apply this analytical model of coopetition - based on game theory and conceived at a macro level - to the Greek crisis, suggesting feasible solutions in a cooperative perspective for the divergent interests which drive the economic policies in the euro area.

math.OC↗

arXiv2011

Chaos structures. Multicurrency adviser on the basis of NSW model and social-financial nets

Algorithm of multicurrency trading at the market of Forex is realized on the basis of nonlinear stochastic wavelets. The distinctive feature of the algorithm is the possibility of weakly- and strongly connected horizontal self-assemblies, as well as use of nested structures. On-line trading with eight currency couples has shown high effectiveness and stability of the algorithm. It is discussed the problem of possibility of excess profit earning in electronic markets via development of social-financial nets based on synchronization of work of individual traders by means of proposed algorithm.

q-fin.GN↗

arXiv2011

Revenue diversification in emerging market banks: implications for financial performance

Shaped by structural forces of change, banking in emerging markets has recently experienced a decline in its traditional activities, leading banks to diversify into new business strategies. This paper examines whether the observed shift into non-interest based activities improves financial performance. Using a sample of 714 banks across 14 East-Asian and Latin-American countries over the post 1997-crisis changing structure, we find that diversification gains are more than offset by the cost of increased exposure to the non-interest income, specifically by the trading income volatility. But this diversification performance's effect is found to be no linear with risk, and significantly not uniform among banks and across business lines. An implication of these findings is that banking institutions can reap diversification benefits as long as they well-studied it depending on their specific characteristics, competences and risk levels, and as they choose the right niche.

q-fin.GN↗

arXiv2011

Role of Diversification Risk in Financial Bubbles

We present an extension of the Johansen-Ledoit-Sornette (JLS) model to include an additional pricing factor called the "Zipf factor", which describes the diversification risk of the stock market portfolio. Keeping all the dynamical characteristics of a bubble described in the JLS model, the new model provides additional information about the concentration of stock gains over time. This allows us to understand better the risk diversification and to explain the investors' behavior during the bubble generation. We apply this new model to two famous Chinese stock bubbles, from August 2006 to October 2007 (bubble 1) and from October 2008 to August 2009 (bubble 2). The Zipf factor is found highly significant for bubble 1, corresponding to the fact that valuation gains were more concentrated on the large firms of the Shanghai index. It is likely that the widespread acknowledgement of the 80-20 rule in the Chinese media and discussion forums led many investors to discount the risk of a lack of diversification, therefore enhancing the role of the Zipf factor. For bubble 2, the Zipf factor is found marginally relevant, suggesting a larger weight of market gains on small firms. We interpret this result as the consequence of the response of the Chinese economy to the very large stimulus provided by the Chinese government in the aftermath of the 2008 financial crisis.

q-fin.GN↗

arXiv2011

Finance Without Probabilistic Prior Assumptions

We develop the fundamental theorem of asset pricing in a probability-free infinite-dimensional setup. We replace the usual assumption of a prior probability by a certain continuity property in the state variable. Probabilities enter then endogenously as full support martingale measures (instead of equivalent martingale measures). A variant of the Harrison-Kreps-Theorem on viability and no arbitrage is shown. Finally, we show how to embed the superhedging problem in a classical infinite-dimensional linear programming problem.

q-fin.GN↗

arXiv2013

Path properties and regularity of affine processes on general state spaces

We provide a new proof for regularity of affine processes on general state spaces by methods from the theory of Markovian semimartingales. On the way to this result we also show that the definition of an affine process, namely as stochastically continuous time-homogeneous Markov process with exponential affine Fourier-Laplace transform, already implies the existence of a càdlàg version. This was one of the last open issues in the fundaments of affine processes.

math.PR↗

arXiv2011

Keynesian Economics After All

It is demonstrated that the US economy has on the long-term in reality been governed by the Keynesian approach to economics independent of the current official economical policy. This is done by calculating the two-point correlation function between the fluctuations of the DJIA and the US public debt. We find that the origin of this condition is mainly related to the wars that the USA has fought during the time period investigated. Wars mean a large influx of public money into the economy, thus as a consequence creating a significant economical upturn in the DJIA. A reason for this straight-cut result of our analysis, is that very few wars have been fought on US-territory and those that have, were in the 18th century, when the partial destruction of cities, factories, railways and so on, was more limited and with less effect on the over-all economy.

q-fin.GN↗

arXiv2011

On the Representation of General Interest Rate Models as Square Integrable Wiener Functionals

In the setting proposed by Hughston & Rafailidis (2005) we consider general interest rate models in the case of a Brownian market information filtration $(\mathcal{F}_t)_{t\geq0}$. Let $X$ be a square-integrable $\mathcal{F}_\infty$-measurable random variable, and assume the non-degeneracy condition that for all $t<\infty$ the random variable $X$ is not $\mathcal{F}_t$-measurable. Let ${σ_t}$ denote the integrand appearing in the representation of $X$ as a stochastic integral, write $π_t$ for the conditional variance of $X$ at time $t$, and set $r_t = σ^2_t / π_t$. Then $π_t$ is a potential, and as such can act as a model for a pricing kernel (or state price density), where $r_t$ is the associated interest rate. Under the stated assumptions, we prove the following: (a) that the money market account process defined by $B_t = \exp (\int_0^t r_s \,ds)$ is finite almost surely at all finite times; and (b) that the product of the money-market account and the pricing kernel is a local martingale, and is a martingale provided a certain integrability condition is satisfied. The fact that a martingale is thus obtained shows that from any non-degenerate element of Wiener space satisfying the integrability condition we can construct an associated interest-rate model. The model thereby constructed is valid over an infinite time horizon, with strictly positive interest, and satisfies the relevant intertemporal relations associated with the absence of arbitrage. The results thus stated pave the way for the use of Wiener chaos methods in interest rate modelling, since any such square-integrable Wiener functional admits a chaos expansion, the individual terms of which can be regarded as parametric degrees of freedom in the associated interest rate model to be fixed by calibration to appropriately liquid sectors of the interest rate derivatives markets.

q-fin.GN↗

arXiv2011

Econophysics: Bridges over a Turbulent Current

In this editorial guide for the special issue on econophysics, we give a unique review of this young but quickly growing discipline. A suggestive taxonomy of the development is proposed by making a distinction between classical econophysics and modern econophysics. For each of these two stages of development, we identify the key economic issues whose formulations and/or treatments have been affected by physics or physicists, which includes value, business fluctuations, economic growth, economic and financial time series, the distribution of economic entities, interactions of economic agents, and economic and social networks. The recent advancements in these issues of modern econophysics are demonstrated by nine articles selected from the papers presented at the Econophysics Colloquium 2010 held at Academia Sinica in Taipei.

q-fin.GN↗

arXiv2011

Recurrence Quantification Analysis of Financial Market Crashes and Crises

Financial markets are systems with the complex behavior, that can be hardly analyzed by means of linear methods. Recurrence Quantification Analysis (RQA) is a nonlinear methodology, which is able to work with the nonstationary and short data series. Thus, we apply RQA for the studying of the critical events on financial markets. For the present research, stock crashes of DJI 1929; DJI, NYSE and S&P500 1987; NASDAQ 2000; HSI 1994, 1997 and Spanish 1992, Portuguese 1992, British 1992, German 1992, Italian 1992, Mexican 1994, Brazilian 1999, Indonesian 1997, Thai 1997, Malaysian 1997, Philippine 1997, Russian 1998, Turkish 2001, Argentine 2002 currency devaluations were taken. The recent world financial crisis of 2007-2010 was considered as well. The possibility of LAM measure to serve as a tool for the revealing, monitoring, analysing and precursoring of financial bubbles, crises and crashes was asserted.

nlin.CD↗

arXiv2011

Detection of Crashes and Rebounds in Major Equity Markets

Financial markets are well known for their dramatic dynamics and consequences that affect much of the world's population. Consequently, much research has aimed at understanding, identifying and forecasting crashes and rebounds in financial markets. The Johansen-Ledoit-Sornette (JLS) model provides an operational framework to understand and diagnose financial bubbles from rational expectations and was recently extended to negative bubbles and rebounds. Using the JLS model, we develop an alarm index based on an advanced pattern recognition method with the aim of detecting bubbles and performing forecasts of market crashes and rebounds. Testing our methodology on 10 major global equity markets, we show quantitatively that our developed alarm performs much better than chance in forecasting market crashes and rebounds. We use the derived signal to develop elementary trading strategies that produce statistically better performances than a simple buy and hold strategy.

q-fin.GN↗

arXiv2011

Second-Order, Dissipative Tâtonnement: Economic Interpretation and 2-Point Limit Cycles

This paper proposes an alternative to the classical price-adjustment mechanism (called "tâtonnement" after Walras) that is second-order in time. The proposed mechanism, an analogue to the damped harmonic oscillator, provides a dynamic equilibration process that depends only on local information. We show how such a process can result from simple behavioural rules. The discrete-time form of the model can result in two-step limit cycles, but as the distance covered by the cycle depends on the size of the damping, the proposed mechanism can lead to both highly unstable and relatively stable behaviour, as observed in real economies.

q-fin.GN↗

arXiv2011

How much multifractality is included in monofractal signals?

We investigate the presence of residual multifractal background for monofractal signals which appears due to the finite length of the signals and (or) due to the long memory the signals reveal. This phenomenon is investigated numerically within the multifractal detrended fluctuation analysis (MF-DFA) for artificially generated time series. Next, the analytical formulas enabling to describe the multifractal content in such signals are provided. Final results are shown in the frequently used generalized Hurst exponent h(q) multifractal scenario and are presented as a function of time series length L and the autocorrelation exponent value γ. The multifractal spectrum (α, f (α)) approach is also discussed. The obtained results may be significant in any practical application of multifractality, including financial data analysis, because the "true" multifractal effect should be clearly separated from the so called "multifractal noise". Examples from finance in this context are given. The provided formulas may help to decide whether we do deal with the signal of real multifractal origin or not.

physics.data-an↗

arXiv2011

Collective behavior in financial market

Financial market is an example of complex system, which is characterized by a highly intricate organization and the emergence of collective behavior. In this paper, we quantify this emergent dynamics in the financial market by using concepts of network synchronization. We consider networks constructed by the correlation matrix of asset returns and study the time evolution of the phase coherence among stock prices. It is verified that during financial crisis a synchronous state emerges in the system, defining the market's direction. Furthermore, the paper proposes a statistical regression model able to identify the topological features that mostly influence such an emergence. The coefficients of the proposed model indicate that the average shortest path length is the measurement most related to network synchronization. Therefore, during economic crisis, the stock prices present a similar evolution, which tends to shorten the distances between stocks, indication a collective dynamics.

q-fin.GN↗

arXiv2011

Heterogeneity, correlations and financial contagion

We consider a model of contagion in financial networks recently introduced in the literature, and we characterize the effect of a few features empirically observed in real networks on the stability of the system. Notably, we consider the effect of heterogeneous degree distributions, heterogeneous balance sheet size and degree correlations between banks. We study the probability of contagion conditional on the failure of a random bank, the most connected bank and the biggest bank, and we consider the effect of targeted policies aimed at increasing the capital requirements of a few banks with high connectivity or big balance sheets. Networks with heterogeneous degree distributions are shown to be more resilient to contagion triggered by the failure of a random bank, but more fragile with respect to contagion triggered by the failure of highly connected nodes. A power law distribution of balance sheet size is shown to induce an inefficient diversification that makes the system more prone to contagion events. A targeted policy aimed at reinforcing the stability of the biggest banks is shown to improve the stability of the system in the regime of high average degree. Finally, disassortative mixing, such as that observed in real banking networks, is shown to enhance the stability of the system.

q-fin.GN↗

arXiv2011

Escalation, timing and severity of insurgent and terrorist events: Toward a unified theory of future threats

I present a unified discussion of several recently published results concerning the escalation, timing and severity of violent events in human conflicts and global terrorism, and set them in the wider context of real-world and cyber-based collective violence and illicit activity. I point out how the borders distinguishing between such activities are becoming increasingly blurred in practice -- from insurgency, terrorism, criminal gangs and cyberwars, through to the 2011 Arab Spring uprisings and London riots. I review the robust empirical patterns that have been found, and summarize a minimal mechanistic model which can explain these patterns. I also explain why this mechanistic approach, which is inspired by non-equilibrium statistical physics, fits naturally within the framework of recent ideas within the social science literature concerning analytical sociology. In passing, I flag the fundamental flaws in each of the recent critiques which have surfaced concerning the robustness of these results and the realism of the underlying model mechanisms.

physics.soc-ph↗