scholarly journals Multi-level cache management of quantitative trading platform

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Zou Lida ◽  
Hassan A. Alterazi ◽  
Roaya Hdeib
Keyword(s):  
User Experience ◽  
Time Series Data ◽  
Rapid Development ◽  
Research Work ◽  
Data Access ◽  
Series Data ◽  
Access Time ◽  
Management Approach ◽  
Cache Management ◽  
Multi Level

Abstract With the rapid development of quantitative trading business in the field of investment, quantitative trading platform is becoming an important tool for numerous investing users to participate in quantitative trading. In using the platform, return time of backtesting historical data is a key factor that influences user experience. In the aspect of optimising data access time, cache management is a critical link. Research work on cache management has achieved many referential results. However, quantitative trading platform has its special demands. (1) Data access of users has overlapping characteristics for time-series data. (2) This platform uses a wide variety of caching devices with heterogeneous performance. To address the above problems, a cache management approach adapting quantitative trading platform is proposed. It not only merges the overlapping data in the cache to save space but also places data into multi-level caching devices driven by user experience. Our extensive experiments demonstrate that the proposed approach could improve user experience up to >50% compared with the benchmark algorithms.

EFFECTS OF GOVERNMENT HEALTH EXPENDITURES ON THE PERFORMANCE OF HEALTH SECTOR IN NIGERIA (1979-2017). AN EMPIRICAL ANALYSIS

2020 ◽  
Vol 12 (2) ◽  
pp. 87-102
Author(s):  
Panan Danladi Gwaison ◽  
Livinus Nkuri Maimako
Keyword(s):  
Life Expectancy ◽  
Health Expenditure ◽  
Time Series Data ◽  
Rapid Development ◽  
Health Sector ◽  
Unit Root Test ◽  
Health Expenditures ◽  
Series Data ◽  
Development Indicators ◽  
Government Health

Health is a very important aspect of an individual’s wellbeing, and since individuals make a nation, therefore, healthcare expenditure could be regarded as one of the necessary conditions to achieving a sustainable long-term economic development. This study examined the effects of government health expenditures on the performance of health Sector in Nigeria. The study employed expo facto research design. The annual time series data from 1979 to 2017 was used in this study from Statistical Bulletin of the Central Bank of Nigeria and World Development Indicators, 2018. The pre estimation test like the descriptive statistics, Augmented Dickey-Fuller (ADF) unit root test Johensen cointegration test and Error correction model test. The OLS estimation technique was used to determine the coefficient of the variables and test the four hypothesis. The results indicated that government total health expenditures, capital health expenditure and recurrent health expenditures are positively related to the performance of health sector proxy by life expectancy rate and statistically insignificant. However capital health expenditure was statistically significant to life expectancy. The study recommends that more emphasis should be placed on the capital expenditures on health as this will facilitate rapid development of the sector and adequate Machinery should be put in place by all sectors of government to arrest corruption and penalize those who divert and embezzle public health fund among other recommendations were made.

scholarly journals An Empirical Analysis of Energy Consumption, FDI and High Quality Development Based on Time Series Data of Zhejiang Province

2020 ◽  
Vol 17 (9) ◽  
pp. 3321
Author(s):  
Shaolong Zeng ◽  
Yiqun Liu ◽  
Junjie Ding ◽  
Danlu Xu
Keyword(s):  
Time Series ◽  
Economic Development ◽  
Energy Consumption ◽  
Open Economy ◽  
High Speed ◽  
Time Series Data ◽  
Rapid Development ◽  
Series Data ◽  
High Quality ◽  
The Relationship

This paper aims to identify the relationship among energy consumption, FDI, and economic development in China from 1993 to 2017, taking Zhejiang as an example. FDI is the main factor of the rapid development of Zhejiang’s open economy, which promotes the development of the economy, but also leads to the growth in energy consumption. Based on the time series data of energy consumption, FDI inflow, and GDP in Zhejiang from 1993 to 2017, we choose the vector auto-regression (VAR) model and try to identify the relationship among energy consumption, FDI, and economic development. The results indicate that there is a long-run equilibrium relationship among them. The FDI inflow promotes energy consumption, and the energy consumption promotes FDI inflow in turn. FDI promotes economic growth indirectly through energy consumption. Therefore, improving the quality of FDI and energy efficiency has become an inevitable choice to achieve the transition of Zhejiang’s economy from high speed growth to high quality growth.

Impact of Fiscal Policy on Agricultural Output in Nigeria

2019 ◽  
Vol 9 (7) ◽  
pp. 1428 ◽  
Author(s):  
Adedoyin Isola LAWAL ◽  
Ernest Onyebuchi FIDELIS ◽  
Abiola Ayoopo BABAJIDE ◽  
Barnabas O. OBASAJU ◽  
Oluwatoyese OYETADE ◽  
...  
Keyword(s):  
Fiscal Policy ◽  
Agricultural Sector ◽  
Time Series Data ◽  
Negative Impact ◽  
Capital Expenditure ◽  
Research Work ◽  
Estimation Method ◽  
Series Data ◽  
Agricultural Output ◽  
The Impact

This study examines the impact of fiscal policy on agricultural output in Nigeria using the most recent official data. The metrics for fiscal policy is government capital expenditure and custom duties on fertilizer. The study used annual time series data obtained from CBN annual statistical bulletin, NCS, and FIRS which was found to be stationary at the order of I(1) and I(0). The order of unit root test led to the use of ARDL estimation method employed in the empirical analysis of this research work. The study found evidence of both short and long run relationship between the variables (VAO, GEX, IDMF, and ACGSF) using both Johansen co-integration and ARDL Bounds test. Although government expenditure (GEX) to agricultural sector was found to be statistically insignificant which recommend that government should increase agriculture capital expenditure to ensure that its contribution is significant. Consequently, custom duties on fertilizer (IDMF) was found to be negatively signed and significant indicating a negative impact on agricultural output. This demands that the policy makers should be prudent in the use of fiscal policy instrument in achieving its desired objective.

scholarly journals Standardizing Time Series Data Access across Heliophysics and Planetary Data Centers using HAPI

2020 ◽  
Author(s):  
Jon Vandegriff ◽  
Robert Weigel ◽  
Jeremy Faden ◽  
D Aaron Roberts ◽  
Todd King ◽  
...  
Keyword(s):  
Time Series ◽  
Data Centers ◽  
Time Series Data ◽  
Data Access ◽  
Series Data

scholarly journals Explainable Fraud Detection for Few Labeled Time Series Data

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Zhiwen Xiao ◽  
Jianbin Jiao
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Research Work ◽  
Fraud Detection ◽  
Predictive Performance ◽  
Multiple Instance Learning ◽  
Detection Methods ◽  
Series Data ◽  
Causal Explanations ◽  
Detection Technology

Fraud detection technology is an important method to ensure financial security. It is necessary to develop explainable fraud detection methods to express significant causality for participants in the transaction. The main contribution of our work is to propose an explainable classification method in the framework of multiple instance learning (MIL), which incorporates the AP clustering method in the self-training LSTM model to obtain a clear explanation. Based on a real-world dataset and a simulated dataset, we conducted two comparative studies to evaluate the effectiveness of the proposed method. Experimental results show that our proposed method achieves the similar predictive performance as the state-of-art method, while our method can generate clear causal explanations for a few labeled time series data. The significance of the research work is that financial institutions can use this method to efficiently identify fraudulent behaviors and easily give reasons for rejecting transactions so as to reduce fraud losses and management costs.

scholarly journals Dynamic Relationships among Crude oil price, exchange rate and BSE Sensex

2018 ◽  
Vol 13 (02) ◽  
Author(s):  
Roshan Kumar ◽  
Manisha Gupta
Keyword(s):  
Crude Oil ◽  
Stock Prices ◽  
Time Series Data ◽  
Research Work ◽  
Unit Root Test ◽  
Series Data ◽  
Causality Test ◽  
Dynamic Relationship ◽  
Crude Oil Prices ◽  
Integration Test

The study examined Dynamic relationship among crude oil prices, exchange rates and stock prices in India for the duration January 2006 to December 2016 using daily data. The research work include the testing for a unit root test in time series data, then it testing the number of co-integrating vectors in the system. In the next step we use the johansen co integration test to examine the relationship among variables. At the last Granger causality test is used to estimating the direction of causality among the variables

scholarly journals Patient Health Record Systems Scope and Functionalities: Literature Review and Future Directions (Preprint)

2017 ◽  
Author(s):  
Lina Bouayad ◽  
Anna Ialynytchev ◽  
Balaji Padmanabhan
Keyword(s):  
Health Care ◽  
Data Storage ◽  
Time Series Data ◽  
Data Access ◽  
Series Data ◽  
Health Record ◽  
Review Of The Literature ◽  
Data Types ◽  
Future Directions ◽  
Patient Health

BACKGROUND A new generation of user-centric information systems is emerging in health care as patient health record (PHR) systems. These systems create a platform supporting the new vision of health services that empowers patients and enables patient-provider communication, with the goal of improving health outcomes and reducing costs. This evolution has generated new sets of data and capabilities, providing opportunities and challenges at the user, system, and industry levels. OBJECTIVE The objective of our study was to assess PHR data types and functionalities through a review of the literature to inform the health care informatics community, and to provide recommendations for PHR design, research, and practice. METHODS We conducted a review of the literature to assess PHR data types and functionalities. We searched PubMed, Embase, and MEDLINE databases from 1966 to 2015 for studies of PHRs, resulting in 1822 articles, from which we selected a total of 106 articles for a detailed review of PHR data content. RESULTS We present several key findings related to the scope and functionalities in PHR systems. We also present a functional taxonomy and chronological analysis of PHR data types and functionalities, to improve understanding and provide insights for future directions. Functional taxonomy analysis of the extracted data revealed the presence of new PHR data sources such as tracking devices and data types such as time-series data. Chronological data analysis showed an evolution of PHR system functionalities over time, from simple data access to data modification and, more recently, automated assessment, prediction, and recommendation. CONCLUSIONS Efforts are needed to improve (1) PHR data quality through patient-centered user interface design and standardized patient-generated data guidelines, (2) data integrity through consolidation of various types and sources, (3) PHR functionality through application of new data analytics methods, and (4) metrics to evaluate clinical outcomes associated with automated PHR system use, and costs associated with PHR data storage and analytics.

Data mining model for multimedia financial time series using information entropy

2020 ◽  
Vol 39 (4) ◽  
pp. 5339-5345
Author(s):  
Han He ◽  
Yuanyuan Hong ◽  
Weiwei Liu ◽  
Sung-A Kim
Keyword(s):  
Data Mining ◽  
Time Series ◽  
Time Series Data ◽  
Financial Time Series ◽  
Rapid Development ◽  
Development Trend ◽  
Series Data ◽  
Transaction Data ◽  
Relationship Analysis ◽  
Financial Time

At present, KDD research covers many aspects, and has achieved good results in the discovery of time series rules, association rules, classification rules and clustering rules. KDD has also been widely used in practical work such as OLAP and DW. Also, with the rapid development of network technology, KDD research based on WEB has been paid more and more attention. The main research content of this paper is to analyze and mine the time series data, obtain the inherent regularity, and use it in the application of financial time series transactions. In the financial field, there is a lot of data. Because of the huge amount of data, it is difficult for traditional processing methods to find the knowledge contained in it. New knowledge and new technology are urgently needed to solve this problem. The application of KDD technology in the financial field mainly focuses on customer relationship analysis and management, and the mining of transaction data is rare. The actual work requires a tool to analyze the transaction data and find its inherent regularity, to judge the nature and development trend of the transaction. Therefore, this paper studies the application of KDD in financial time series data mining, explores an appropriate pattern mining method, and designs an experimental system which includes mining trading patterns, analyzing the nature of transactions and predicting the development trend of transactions, to promote the application of KDD in the financial field.

Accessing environmental time series data in R from Sensor Observation Services with ease

2020 ◽  
Author(s):  
Daniel Nüst ◽  
Eike H. Jürrens ◽  
Benedikt Gräler ◽  
Simon Jirka
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Data Access ◽  
R Package ◽  
Series Data ◽  
Observation Data ◽  
Software Environment ◽  
Technical Standards ◽  
Seamless Integration ◽  
Environmental Time Series

<p>Time series data of in-situ measurements is the key to many environmental studies. The first challenge in any analysis typically arises when the data needs to be imported into the analysis framework. Standardisation is one way to lower this burden. Unfortunately, relevant interoperability standards might be challenging for non-IT experts as long as they are not dealt with behind the scenes of a client application. One standard to provide access to environmental time series data is the Sensor Observation Service (SOS, ) specification published by the Open Geospatial Consortium (OGC). SOS instances are currently used in a broad range of applications such as hydrology, air quality monitoring, and ocean sciences. Data sets provided via an SOS interface can be found around the globe from Europe to New Zealand.</p><p>The R package sos4R (Nüst et al., 2011) is an extension package for the R environment for statistical computing and visualization (), which has been demonstrated a a powerful tools for conducting and communicating geospatial research (cf. Pebesma et al., 2012; ). sos4R comprises a client that can connect to an SOS server. The user can use it to query data from SOS instances using simple R function calls. It provides a convenience layer for R users to integrate observation data from data access servers compliant with the SOS standard without any knowledge about the underlying technical standards. To further improve the usability for non-SOS experts, a recent update to sos4R includes a set of wrapper functions, which remove complexity and technical language specific to OGC specifications. This update also features specific consideration of the OGC SOS 2.0 Hydrology Profile and thereby opens up a new scientific domain.</p><p>In our presentation we illustrate use cases and examples building upon sos4R easing the access of time series data in an R and Shiny () context. We demonstrate how the abstraction provided in the client library makes sensor observation data for accessible and further show how sos4R allows the seamless integration of distributed observations data, i.e., across organisational boundaries, into transparent and reproducible data analysis workflows.</p><p><strong>References</strong></p><p>Nüst D., Stasch C., Pebesma E. (2011) Connecting R to the Sensor Web. In: Geertman S., Reinhardt W., Toppen F. (eds) Advancing Geoinformation Science for a Changing World. Lecture Notes in Geoinformation and Cartography, Springer. </p><p>Pebesma, E., Nüst, D., & Bivand, R. (2012). The R software environment in reproducible geoscientific research. Eos, Transactions American Geophysical Union, 93(16), 163–163. </p>

Sign in / Sign up

Export Citation Format

Share Document