scholarly journals How Fast Does the Clock of Finance Run?—A Time-Definition Enforcing Stationarity and Quantifying Overnight Duration

2021 ◽  
Vol 14 (8) ◽  
pp. 384
Author(s):  
Michele Caraglio ◽  
Fulvio Baldovin ◽  
Attilio L. Stella
Keyword(s):  
Stochastic Process ◽  
Time Series ◽  
Scale Invariance ◽  
The Novel ◽  
Statistical Sampling ◽  
Financial Applications ◽  
Historical Series ◽  
Simple Scaling ◽  
Definition Of ◽  
Recurrent Patterns

A definition of time based on the assumption of scale invariance may enhance and simplify the analysis of historical series with cyclically recurrent patterns and seasonalities. By enforcing simple-scaling and stationarity of the distributions of returns, we identify a successful protocol of time definition in finance, functional from tens of minutes to a few days. Within this time definition, the significant reduction of cyclostationary effects allows analyzing the structure of the stochastic process underlying the series on the basis of statistical sampling sliding along the whole time series. At the same time, the duration of periods in which markets remain inactive is properly quantified by the novel clock, and the corresponding returns (e.g., overnight or weekend) can be consistently taken into account for financial applications. The method is applied to the S&P500 index recorded at a 1 min frequency between September 1985 and June 2013.

The Limit Situation And The Narrative Of War (On The Material Of The Novel “My Lieutenant” By Daniil Granin)

2020 ◽  
Vol 6 (1) ◽  
pp. 90-104
Author(s):  
Anatoly S. Kuprin ◽  
Galina I. Danilina
Keyword(s):  
20Th Century ◽  
Scientific Work ◽  
Point Of View ◽  
Continuous Limit ◽  
The Novel ◽  
Term Limit ◽  
Abstract Author ◽  
The Third ◽  
Definition Of

The purpose of this study is the analysis of limit situation in the narrative of war. The material of the study is the novel of Daniil Granin “My Lieutenant” and related texts. In the first part of the paper, the authors explore existing approaches to the term “limit situation” and similar concepts into scientific and philosophical traditions; limits of its applicability in literary studies and its relation to the categories of “narrative instances” and “event”. Proposed a literary-theoretical definition of the limit situation, which can be used in the analysis of fiction texts. Existing approaches to the examination of the situation of war are analyzed: philosophical-existential, psychoanalytic, sociological, literary. In the second part of the paper, the authors propose their method for analyzing limit situations in texts about war, which basis on existing approaches and preserves the text-centric principle of studying the structure of the story. Two interrelated areas of research have been identified: the study of war as a continuous limit situation in the intertextual aspect (the discourse of war); the study of limit situations (death, suffering, guilt, accident) in the narrative of war as part of a specific text. In the third part of the scientific work,the analysis of war as a continuous limit situation results in the study of the concept of “limit” (border) in a fiction text. The role of “limit” (border) concept in the texts about the war is studied, the possible types of limits in the discourse of war are examined. Limit situations in the narrative of war are analyzed on the basis of the novel “My Lieutenant” by Daniil Granin. A review of journalistic and scientific works about the novel revealed both the continuity and the differences between the novel and the “lieutenant” prose of the 20th century. An analysis of the limit situations in the novel revealed their key position in the narrative. These situations are independent of the fiction time, of the fluctuation of the point of view’; the function of the abstract author is to build the narrative as a “directive” immersion of the hero and narrator in these situations.

scholarly journals Modelling spreading of an infection using time series by a novel family of models; fitting the time series of the confirmed cases of COVID-19 in China

2020 ◽  
Vol 9 (s1) ◽  
Author(s):  
Babak Jamshidi ◽  
Shahriar Jamshidi Zargaran ◽  
Mansour Rezaei
Keyword(s):  
Infectious Disease ◽  
Time Series ◽  
Communicable Disease ◽  
Time Series Models ◽  
Cumulative Number ◽  
The Novel ◽  
New Family ◽  
Two Samples ◽  
Almost All ◽  
Number Of Individuals

AbstractIntroductionTime series models are one of the frequently used methods to describe the pattern of spreading an epidemic.MethodsWe presented a new family of time series models able to represent the cumulative number of individuals that contracted an infectious disease from the start to the end of the first wave of spreading. This family is flexible enough to model the propagation of almost all infectious diseases. After a general discussion on competent time series to model the outbreak of a communicable disease, we introduced the new family through one of its examples.ResultsWe estimated the parameters of two samples of the novel family to model the spreading of COVID-19 in China.DiscussionOur model does not work well when the decreasing trend of the rate of growth is absent because it is the main presumption of the model. In addition, since the information on the initial days is of the utmost importance for this model, one of the challenges about this model is modifying it to get qualified to model datasets that lack the information on the first days.

scholarly journals New DTW Windows Type for Forward- and Backward-Lookingness Examination. Application for Inflation Expectation

2021 ◽  
Author(s):  
Aleksandra Rutkowska ◽  
Magdalena Szyszko
Keyword(s):  
Time Series ◽  
Information Content ◽  
Dynamic Time Warping ◽  
The Novel ◽  
Time Warping ◽  
Specific Question ◽  
Inflation Expectation ◽  
Standard Tool ◽  
Dynamic Time ◽  
Research Period

AbstractThis study provides an application of dynamic time warping algorithm with a new window constraint to assess consumer expectations’ information content regarding current and future inflation. Our study’s contribution is the novel application of DTW for testing expectations’ forward-lookingness. Additionally, we modify the algorithm to adjust it for a specific question on the information content of our data. The DTW overcomes constraints of the standard tool that examines forward-lookingness: DTW does not impose assumptions on time series properties. In empirical study we cover seven European counties and compare the DTW outcomes with the results of previous studies in these economies using a standard methodology. The research period covers 2001 to mid-2018. Application of DTW provides information on the degree of expectations’ forward-lookingness. The result, after standardization, are similar to the standard parameters of hybrid specification of expectations. Moreover, the rankings of most forward-looking consumers are replicated. Our results confirm the economic intuition, and they do not contradict previous studies.

scholarly journals Time Series Analysis of Climatic Variables in Peninsular Spain. Trends and Forecasting Models for Data between 20th and 21st Centuries

Climate ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 119
Author(s):  
Pitshu Mulomba Mukadi ◽  
Concepción González-García
Keyword(s):  
Time Series ◽  
Temperature Series ◽  
Climatic Variables ◽  
Monthly Precipitation ◽  
Agricultural Crops ◽  
Arima Models ◽  
Cover Time ◽  
Pests And Diseases ◽  
Historical Series ◽  
Preliminary Phase

Time series of mean monthly temperature and total monthly precipitation are two of the climatic variables most easily obtained from weather station records. There are many studies analyzing historical series of these variables, particularly in the Spanish territory. In this study, the series of these two variables in 47 stations of the provincial capitals of mainland Spain were analyzed. The series cover time periods from the 1940s to 2013; the studies reviewed in mainland Spain go up to 2008. ARIMA models were used to represent their variation. In the preliminary phase of description and identification of the model, a study to detect possible trends in the series was carried out in an isolated manner. Significant trends were found in 15 of the temperature series, and there were trends in precipitation in only five of them. The results obtained for the trends are discussed with reference to those of other, more detailed studies in the different regions, confirming whether the same trend was maintained over time. With the ARIMA models obtained, 12-month predictions were made by measuring errors with the observed data. More than 50% of the series of both were modeled. Predictions with these models could be useful in different aspects of seasonal job planning, such as wildfires, pests and diseases, and agricultural crops.

IDENTIFYING DISTINCT STOCHASTIC DYNAMICS FROM CHAOS: A STUDY ON MULTIMODAL NEURAL FIRING PATTERNS

2009 ◽  
Vol 19 (02) ◽  
pp. 453-485 ◽  
Author(s):  
MINGHAO YANG ◽  
ZHIQIANG LIU ◽  
LI LI ◽  
YULIN XU ◽  
HONGJV LIU ◽  
...  
Keyword(s):  
Time Series ◽  
Limit Cycle ◽  
Stochastic Dynamics ◽  
Nonlinear Time Series ◽  
Special Importance ◽  
Neuronal System ◽  
Neural Firing ◽  
Firing Patterns ◽  
Theoretical Simulation ◽  
Definition Of

Some chaotic and a series of stochastic neural firings are multimodal. Stochastic multimodal firing patterns are of special importance because they indicate a possible utility of noise. A number of previous studies confused the dynamics of chaotic and stochastic multimodal firing patterns. The confusion resulted partly from inappropriate interpretations of estimations of nonlinear time series measures. With deliberately chosen examples the present paper introduces strategies and methods of identification of stochastic firing patterns from chaotic ones. Aided by theoretical simulation we show that the stochastic multimodal firing patterns result from the effects of noise on neuronal systems near to a bifurcation between two simpler attractors, such as a point attractor and a limit cycle attractor or two limit cycle attractors. In contrast, the multimodal chaotic firing trains are generated by the dynamics of a specific strange attractor. Three systems were carefully chosen to elucidate these two mechanisms. An experimental neural pacemaker model and the Chay mathematical model were used to show the stochastic dynamics, while the deterministic Wang model was used to show the deterministic dynamics. The usage and interpretation of nonlinear time series measures were systematically tested by applying them to firing trains generated by the three systems. We successfully identified the distinct differences between stochastic and chaotic multimodal firing patterns and showed the dynamics underlying two categories of stochastic firing patterns. The first category results from the effects of noise on the neuronal system near a Hopf bifurcation. The second category results from the effects of noise on the period-adding bifurcation between two limit cycles. Although direct application of nonlinear measures to interspike interval series of these firing trains misleadingly implies chaotic properties, definition of eigen events based on more appropriate judgments of the underlying dynamics leads to accurate identifications of the stochastic properties.

Efficient Time Series Clustering and Its Application to Social Network Mining

2014 ◽  
Vol 23 (2) ◽  
pp. 213-229 ◽  
Author(s):  
Cangqi Zhou ◽  
Qianchuan Zhao
Keyword(s):  
Time Series ◽  
Social Network ◽  
Information Diffusion ◽  
Time Series Data ◽  
Online Social Network ◽  
Dissimilarity Measure ◽  
Series Data ◽  
Formation Mechanisms ◽  
Network Analyses ◽  
Definition Of

AbstractMining time series data is of great significance in various areas. To efficiently find representative patterns in these data, this article focuses on the definition of a valid dissimilarity measure and the acceleration of partitioning clustering, a common group of techniques used to discover typical shapes of time series. Dissimilarity measure is a crucial component in clustering. It is required, by some particular applications, to be invariant to specific transformations. The rationale for using the angle between two time series to define a dissimilarity is analyzed. Moreover, our proposed measure satisfies the triangle inequality with specific restrictions. This property can be employed to accelerate clustering. An integrated algorithm is proposed. The experiments show that angle-based dissimilarity captures the essence of time series patterns that are invariant to amplitude scaling. In addition, the accelerated algorithm outperforms the standard one as redundancies are pruned. Our approach has been applied to discover typical patterns of information diffusion in an online social network. Analyses revealed the formation mechanisms of different patterns.

Antisemitic or Bordering on Antisemitic? Grey Areas in Romanian Fake News Discourses in the Wake of the Covid-19 Pandemic

Transilvania ◽  
2021 ◽  
pp. 121-127
Author(s):  
Anca-Simina Martin
Keyword(s):  
Influenza Pandemic ◽  
The Novel ◽  
Fake News ◽  
Jewish Communities ◽  
Elie Wiesel ◽  
Working Definition ◽  
The Holocaust ◽  
The Us ◽  
Definition Of ◽  
Novel Coronavirus

Jews as a collective have long served as scapegoats for epidemics and pandemics, such as the Bubonic Plague and, according to some scholars, the 1918–1920 influenza pandemic. This practice reemerged in the early days of the Covid-19 pandemic, when more and more fake news outlets in the US and Europe started publishing articles on a perceived linkage between Jewish communities and the novel coronavirus. What this article aims to achieve is to facilitate a dialogue between the observations on the phenomenon made by the Elie Wiesel National Institute for the Study of the Holocaust in Romania and the latest related EU reports, with a view to charting its beginnings in Romania in relation to other European countries and in an attempt to see whether Romania, like France and Germany, has witnessed the emergence of “grey area” discourses which are not fully covered by International Holocaust Remembrance Alliance working definition of antisemitism.

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