Hidden forces and fluctuations from moving averages: A test study

Alfi, V.; Coccetti, F.; Marotta, M.; Pietronero, L.; Takayasu, Misako

doi:10.1016/j.physa.2006.04.113

Cited by 24 publications

(20 citation statements)

References 6 publications

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“…The factor M − 1 in the denominator of the force term makes the potential independent of the particular choice of the moving average [17]. This equation has been used in previous papers to analyze real data [17,19,20]. The conclusion is that is indeed possible to observe this kind of forces also in real stock-prices.…”

Section: Definition Of a Minimal Abm With Fundamentalists And Chartistsmentioning

confidence: 95%

“…In our model we can overcome this complication by simplifying the chartists' behavior. In fact, the description of chartists is in term of the recently introduced potential method [17,18,19,20]. Chartist agents detect a trend by looking at the distance between the price and its smoothed profile which in our case is the moving average computed on the previous M time steps.…”

Section: Definition Of a Minimal Abm With Fundamentalists And Chartistsmentioning

confidence: 99%

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Minimal agent based model for financial markets I

et al. 2009

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We introduce a minimal Agent Based Model for financial markets to understand the nature and Self-Organization of the Stylized Facts. The model is minimal in the sense that we try to identify the essential ingredients to reproduce the main most important deviations of price time series from a Random Walk behavior. We focus on four essential ingredients: fundamentalist agents which tend to stabilize the market; chartist agents which induce destabilization; analysis of price behavior for the two strategies; herding behavior which governs the possibility of changing strategy. Bubbles and crashes correspond to situations dominated by chartists, while fundamentalists provide a long time stability (on average). The Stylized Facts are shown to correspond to an intermittent behavior which occurs only for a finite value of the number of agents N . Therefore they correspond to finite size effect which, however, can occur at different time scales. We propose a new mechanism for the Self-Organization of this state which is linked to the existence of a threshold for the agents to be active or not active. The feedback between price fluctuations and number of active agents represent a crucial element for this state of SelfOrganized-Intermittency. The model can be easily generalized to consider more realistic variants.

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Section: Definition Of a Minimal Abm With Fundamentalists And Chartistsmentioning

confidence: 95%

Section: Definition Of a Minimal Abm With Fundamentalists And Chartistsmentioning

confidence: 99%

Minimal agent based model for financial markets I

et al. 2009

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“…Note that previous studies have shown that several features of empirical market dynamics are determined by an effective potential defined in terms of the long-term moving average of price [22]. Given the price information, an agent i decides to trade at time t according to the probability…”

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confidence: 99%

Emergence of universal scaling in financial markets from mean-field dynamics

Vikram

Sinha

2011

Phys. Rev. E

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Collective phenomena with universal properties have been observed in many complex systems with a large number of components. Here we present a microscopic model of the emergence of scaling behavior in such systems, where the interaction dynamics between individual components is mediated by a global variable making the mean-field description exact. Using the example of financial markets, we show that asset price can be such a global variable with the critical role of coordinating the actions of agents who are otherwise independent. The resulting model accurately reproduces empirical properties such as the universal scaling of the price fluctuation and volume distributions, long-range correlations in volatility and multiscaling.PACS numbers: 89.75. Da,89.65.Gh,05.65.+b,05.40.Fb Universal scaling behaviour is an emergent property of many complex systems [1]. In such systems, the interactions between a large number of individual components yields macro-scale collective behavior with features that are almost invariant across different spatial and temporal scales [2]. A financial market provides a general and useful paradigm of such a system, since it involves a large number of agents whose actions are subject to internal and external influences, such as information about the state of the market as provided by market indices [3]. Despite this complexity, the availability of a large volume of high-quality data for analysis has enabled the identification of well characterized statistical properties [4,5]. These properties, including the fat-tailed distribution of relative price changes [6,7] and intermittent bursts of large fluctuations that characterize volatility clustering [8], appear to be universal: they are invariant across different markets, types of assets traded and periods of observation [9]. More generally, the question of how universal features emerge from collective behavior in systems with many components is not restricted to the purely economic domain. Thus, new approaches to understanding the behavior of financial markets may contribute to the understanding of the physics of nonequilibrium steady states in general.Mainstream economic theories for price fluctuations of financial assets typically assume the efficient market hypothesis [10]. According to this, price variations reflect changes in the fundamental (or "true") value of the assets. However, detailed analysis of data from actual markets show that much of the observed price variation cannot be explained solely in terms of changes in economic fundamentals [11]. The absence of a strong correlation between large market fluctuations and purely economic factors leaves unresolved the question of why markets are so volatile. As the dynamics of markets are a result of the collective behavior of many interacting constituents, models based on statistical physics have been proposed to explain the observed universal behavior [12][13][14][15]. Most such models consider explicit interactions between agents to reproduce a very limited set of the universal emp...

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“…In recent papers [3,4] has been introduced the idea the the stock-price dynamics can be influenced by a moving average of the price itself in the previous time steps. Hence, at every time step t, one can introduce a moving average of the previous M time steps: average defined as the average over the previous 50 points.…”

Section: The Effective Potential Modelmentioning

confidence: 99%

Detecting the traders’ strategies in minority–majority games and real stock-prices

Alfi

Martino

Pietronero

et al. 2007

Physica A: Statistical Mechanics and its Applications

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Price dynamics is analyzed in terms of a model which includes the possibility of effective forces due to trend followers or trend adverse strategies. The method is tested on the data of a minoritymajority model and indeed it is capable of reconstructing the prevailing traders' strategies in a given time interval. Then we also analyze real (NYSE) stock-prices dynamics and it is possible to derive an indication for the the "sentiment" of the market for time intervals of at least one day. 89.65+Gh,

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Hidden forces and fluctuations from moving averages: A test study

Cited by 24 publications

References 6 publications

Minimal agent based model for financial markets I

Minimal agent based model for financial markets I

Emergence of universal scaling in financial markets from mean-field dynamics

Detecting the traders’ strategies in minority–majority games and real stock-prices

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