Data Regression Framework for Time Series Data with Extreme Events

2021 ◽  
Author(s):  
Yifan Zhang ◽  
Jiahao Li ◽  
Ablan Carlo ◽  
Alex K Manda ◽  
Scott Hamshaw ◽  
...  
Keyword(s):  
Time Series ◽  
Extreme Events ◽  
Time Series Data ◽  
Series Data ◽  
Data Regression ◽  
Regression Framework

A new approach to detect extreme events: a case study using remotely-sensed precipitation time-series data

2021 ◽  
Vol 24 ◽  
pp. 100618
Author(s):  
Philipe Riskalla Leal ◽  
Ricardo José de Paula Souza e Guimarães ◽  
Fábio Dall Cortivo ◽  
Rayana Santos Araújo Palharini ◽  
Milton Kampel
Keyword(s):  
Time Series ◽  
Extreme Events ◽  
Time Series Data ◽  
Remotely Sensed ◽  
Series Data ◽  
Precipitation Time Series ◽  
New Approach

scholarly journals Predicting Financial Extremes Based on Weighted Visual Graph of Major Stock Indices

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Dong-Rui Chen ◽  
Chuang Liu ◽  
Yi-Cheng Zhang ◽  
Zi-Ke Zhang
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Financial Market ◽  
Extreme Events ◽  
Time Series Data ◽  
Graph Algorithm ◽  
Series Data ◽  
Financial Bubbles ◽  
Stock Indices ◽  
Visual Graph

Understanding and predicting extreme turning points in the financial market, such as financial bubbles and crashes, has attracted much attention in recent years. Experimental observations of the superexponential increase of prices before crashes indicate the predictability of financial extremes. In this study, we aim to forecast extreme events in the stock market using 19-year time-series data (January 2000–December 2018) of the financial market, covering 12 kinds of worldwide stock indices. In addition, we propose an extremes indicator through the network, which is constructed from the price time series using a weighted visual graph algorithm. Experimental results on 12 stock indices show that the proposed indicators can predict financial extremes very well.

scholarly journals TINJAUAN DEFISIT FISKAL, EKSPOR, IMPOR DAN JUMLAH UMKM TERHADAP PERTUMBUHAN EKONOMI INDONESIA

2020 ◽  
Vol 5 (2) ◽  
pp. 151
Author(s):  
Erni Febrina Harahap ◽  
Luviana Luviana ◽  
Nurul Huda
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Time Series Data ◽  
Estimation Method ◽  
Secondary Data ◽  
Fixed Effect ◽  
Series Data ◽  
Important Indicator ◽  
Panel Data Regression ◽  
Data Regression

<div class="WordSection1"><p><em>Economic growth is one of most important indicator in analyze the economic development in a state. This research purpose to analyze how much the influence of fiscal deficits, export, import, and total UMKM to Indonesian economic growth. The type of data used in this research is secondary data in the form of time series data and was obtained from some government institutions. The estimation method used is panel data regression with the fixed effect approach period 2010 - 2017. From the results of this research refer that fiscal deficit, import and total UMKM have a significant to Indonesian economic growth, while export not significant to Indonesian economic growth.</em></p></div><p>Pertumbuhan ekonomi merupakan salah satu indikator yang sangat penting dalam melakukan analisis pembanguan ekonomi di suatu negara. Penelitian ini bertujuan untuk menganalisis seberapa besar pengaruh defisit fiskal, ekspor, impor, jumlah UMKM terhadap Pertumbuhan Ekonomi Indonesia. Jenis data yang digunakan dalam penelitian ini adalah data sekunder yang berupa data <em>time series</em> dan diperoleh dari beberapa lembaga pemerintah. Metode estimasi yang digunakan adalah regresi data panel dengan pendekatan <em>fixed effect </em>periode 2010 – 2017. Dari hasil penelitian menunjukkan bahwa defisit fiskal, impor dan jumlah UMKM berpengaruh signifikan terhadap Pertumbuhan Ekonomi Indonesia, sedangkan ekspor tidak berpengaruh signifikan terhadap pertumbuhan ekonomi Indonesia.</p><p><strong> </strong></p>

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHI TINGKAT BAGI HASIL DEPOSITO MUDHARABAH PADA PERBANKAN SYARIAH PERIODE 2015-2020

2021 ◽  
Vol 8 (1) ◽  
pp. 64
Author(s):  
Anisatun Muazaroh ◽  
Dina Fitrisia Septiarini
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Capital Adequacy ◽  
Rate Of Return ◽  
Series Data ◽  
Islamic Banking ◽  
Business Units ◽  
Capital Adequacy Ratio ◽  
Data Regression ◽  
Result Show

ABSTRAKPenelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi tingkat bagi hasil deposito mudharabah pada perbankan syariah periode 2015-2020. Variabel dependen dalam penelitian ini adalah tingkat bagi hasil deposito mudharabah, sedangkan variabel independen adalah Financing to Deposit Ratio, Beban Operasional terhadap Pendapatan Operasional, Capital Adequacy Ratio,  Inflasi dan BI 7-Day Rate. Populasi penelitian ini adalah industri perbankan syariah periode 2015-2020. Sampel yang digunakan adalah sampel jenuh, yakni menggunakan seluruh industri bank umum syariah dan unit usaha syariah. Penelitian ini menggunakan pendekatan kuantitatif dengan metode analisis regresi data time series. Data penelitian ini diambil dari statistik bank syariah yang bersumber dari OJK, data BI 7-Day Rate dan Inflasi bersumber dari website BI. Hasil penelitian ini menunjukkan secara parsial Inflasi dan BI 7-Day Rate yang memiliki pengaruh signifikan positif serta variabel CAR memiliki pengaruh signifikan negatif terhadap tingkat bagi hasil deposito mudharabah. Sedangkan, FDR dan BOPO tidak berpengaruh terhadap tingkat bagi hasil deposito mudharabah. Secara simultan, variabel FDR, BOPO, CAR, Inflasi dan BI 7-Day Rate memiliki pengaruh signifikan terhadap ringkat bagi hasil deposito mudharabah pada perbankan syariah di Indonesia periode 2015-2020Kata Kunci: Financial to Deposit Ratio, Beban Operasional terhadap Pendapatan Operasional, Capital Adequacy Ratio, Inflasi, BI 7-Day Rate, Tingkat Bagi Hasil Deposito. ABSTRACTThe purpose of this research is to analyze the factors that effect the rate of return mudharabah deposits on Islamic banking in Indonesia in the 2015-2020 period.  The dependent variable in this research is the rate of return mudharabah deposits, while the independent variable is Financing to Deposit Ratio, Operational Effeciency Ratio, Capital Adequacy Ratio, Inflation, and BI 7-Day Rate. The population of this research is Islamic banking industry in the 2015-2020 period. the research used saturation sampling, which used all sharia general banks and sharia business units. This research used quantitative approach by using time series data regression analysis. Sample that used in this research were taken from Islamic Bank Statistic issued by OJK, while BI Rate and Inflation taken from www.bi.go.id. The result show that Inflation and Bi 7-Day Rate has positive significant on the rate of return mudharabah deposits and variable CAR has negative significant on the rate of return mudharabah deposits. While FDR and BOPO has no effect on the rate of return mudharabah deposits. Simultaneously, variable FDR, OER, CAR, Inflation, and BI 7-Day Rate has a significant on the rate of return mudharabah deposits on Islamic banking in Indonesia 2015-2020 period.Keywords: Financing to Deposit Ratio, Operational Effeciency Ratio, Capital Adequacy Ratio , Inflation, BI 7-Day Rate, the rate of return mudharabah deposits.

Graphical Exploratory Data Analysis for Categorical Longitudinal and Time Series Data

2013 ◽  
Author(s):  
Stephen J. Tueller ◽  
Richard A. Van Dorn ◽  
Georgiy Bobashev ◽  
Barry Eggleston
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Exploratory Data

Faktor-Faktor Yang Mempengaruhi Nilai Tukar Dollar Amerika Serikat Terhadap Rupiah Tahun 2000–2013

2017 ◽  
Vol 1 (2) ◽  
pp. 177-191
Author(s):  
Rizki Rahma Kusumadewi ◽  
Wahyu Widayat
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Money Supply ◽  
Time Series Data ◽  
The United States ◽  
Economic Conditions ◽  
Series Data ◽  
Arch Model ◽  
United States Dollar ◽  
The Exchange Rate

Exchange rate is one tool to measure a country’s economic conditions. The growth of a stable currency value indicates that the country has a relatively good economic conditions or stable. This study has the purpose to analyze the factors that affect the exchange rate of the Indonesian Rupiah against the United States Dollar in the period of 2000-2013. The data used in this study is a secondary data which are time series data, made up of exports, imports, inflation, the BI rate, Gross Domestic Product (GDP), and the money supply (M1) in the quarter base, from first quarter on 2000 to fourth quarter on 2013. Regression model time series data used the ARCH-GARCH with ARCH model selection indicates that the variables that significantly influence the exchange rate are exports, inflation, the central bank rate and the money supply (M1). Whereas import and GDP did not give any influence.

An Anomaly Detection Method with Exemplar Subsequence for Time Series Data

2016 ◽  
Vol 136 (3) ◽  
pp. 363-372
Author(s):  
Takaaki Nakamura ◽  
Makoto Imamura ◽  
Masashi Tatedoko ◽  
Norio Hirai
Keyword(s):  
Time Series ◽  
Anomaly Detection ◽  
Time Series Data ◽  
Detection Method ◽  
Series Data

The Comparison of Land Subsidence between East and West Side of Bangkok, Thailand

2020 ◽  
Vol 17 (3) ◽  
pp. 1
Author(s):  
Angkana Pumpuang ◽  
Anuphao Aobpaet
Keyword(s):  
Time Series ◽  
Land Subsidence ◽  
Time Series Data ◽  
Series Data ◽  
Industrial Estates ◽  
Vertical Displacements ◽  
Land Deformation ◽  
Extensive Farming ◽  
Chao Phraya River ◽  
Set Up

The land deformation in line of sight (LOS) direction can be measured using time series InSAR. InSAR can successfully measure land subsidence based on LOS in many big cities, including the eastern and western regions of Bangkok which is separated by Chao Phraya River. There are differences in prosperity between both sides due to human activities, land use, and land cover. This study focuses on the land subsidence difference between the western and eastern regions of Bangkok and the most possible cause affecting the land subsidence rates. The Radarsat-2 single look complex (SLC) was used to set up the time series data for long term monitoring. To generate interferograms, StaMPS for Time Series InSAR processing was applied by using the PSI algorithm in DORIS software. It was found that the subsidence was more to the eastern regions of Bangkok where the vertical displacements were +0.461 millimetres and -0.919 millimetres on the western and the eastern side respectively. The districts of Nong Chok, Lat Krabang, and Khlong Samwa have the most extensive farming area in eastern Bangkok. Besides, there were also three major industrial estates located in eastern Bangkok like Lat Krabang, Anya Thani and Bang Chan Industrial Estate. By the assumption of water demand, there were forty-eight wells and three wells found in the eastern and western part respectively. The number of groundwater wells shows that eastern Bangkok has the demand for water over the west, and the pumping of groundwater is a significant factor that causes land subsidence in the area.Keywords: Subsidence, InSAR, Radarsat-2, Bangkok

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