CHEONG Siew Ann

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11 to 20 of 88 Results

Hidden-State Modelling of a Cross-section of Geoelectric Time Series Data Can Provide Reliable Intermediate-term Probabilistic Earthquake Forecasting in Taiwan Jun 1, 2021 Cheong, Siew Ann, 2021, "Hidden-State Modelling of a Cross-section of Geoelectric Time Series Data Can Provide Reliable Intermediate-term Probabilistic Earthquake Forecasting in Taiwan", https://doi.org/10.21979/N9/JSUTCD, DR-NTU (Data), V1 (C, V, S, K) index time series data generated using 0.5-Hz GEMS time series data from Taiwan. In this data set, C is a modified autocorrelation function, V is the variance, S the skewness, and K the kurtosis of the GEMS geo-electric field time series.
Using Topological Data Analysis (TDA) and Persistent Homology to Analyse the Stock Markets in Singapore and Taiwan Feb 21, 2021 Cheong, Siew Ann, 2021, "Using Topological Data Analysis (TDA) and Persistent Homology to Analyse the Stock Markets in Singapore and Taiwan", https://doi.org/10.21979/N9/8XMZGF, DR-NTU (Data), V1 Data sets and Python scripts for paper published by T.-W. Yen and S. A. Cheong in Frontiers in Physics for a special issue "From Physics to Econophysics back to Physics: Methods and Insights".
Cross sections of 8 to 9 mixed assets after hypothesis testing Dec 14, 2020 - Identifying Actionable Serial Correlations in Financial Markets Cheong, Siew Ann, 2020, "Cross sections of 8 to 9 mixed assets after hypothesis testing", https://doi.org/10.21979/N9/FR745X, DR-NTU (Data), V1 Set 1 = (A) gold, (B) silver, (C) palladium, (D) S\&P 500, (E) Hang Seng, (F) platinum, (G) Dow Jones, (H) Nikkei, and (I) NASDAQ, prices between Apr 2, 1990 and Jan 28, 2018. Set 2 = (A) 5-year US bond, (B) 10-year US bond, (C) 2-year US bond, (D) 6-month US bond, (E) wheat, (F)...
Second cross section of 10 DJI component stocks: intermediate files for hypothesis testing Dec 14, 2020 - Identifying Actionable Serial Correlations in Financial Markets Cheong, Siew Ann, 2020, "Second cross section of 10 DJI component stocks: intermediate files for hypothesis testing", https://doi.org/10.21979/N9/FDIDAM, DR-NTU (Data), V1 Python npy files
Cross section of 5 DJI component stocks Dec 14, 2020 - Identifying Actionable Serial Correlations in Financial Markets Cheong, Siew Ann, 2020, "Cross section of 5 DJI component stocks", https://doi.org/10.21979/N9/KGGAMP, DR-NTU (Data), V1 ['A', 'B', 'C', 'D', 'E', 'STC', 'STC5', 'TC5', 'fTC5', 'fTC5null', 'lmax', 'lmin', 'nSTCempty', 'setTC5', 'sigseqp001', 'sigseqp005', 'sigseqp005n5']
First cross section of 10 DJI component stocks: Intermediate data files for hypothesis testing Dec 14, 2020 - Identifying Actionable Serial Correlations in Financial Markets Cheong, Siew Ann, 2020, "First cross section of 10 DJI component stocks: Intermediate data files for hypothesis testing", https://doi.org/10.21979/N9/JCIKFR, DR-NTU (Data), V1 To be used for Python script for hypothesis testing.
First cross section of 10 DJI component stocks Dec 14, 2020 - Identifying Actionable Serial Correlations in Financial Markets Cheong, Siew Ann, 2020, "First cross section of 10 DJI component stocks", https://doi.org/10.21979/N9/GHMOKN, DR-NTU (Data), V1 X1 = GE, X2 = CSCO, X3 = HD, X4 = JPM, X5 = MMM, X6 = MRK, X7 = UTX, X8 = BA, X9 = VZ, X10 = XOM
Identifying Actionable Serial Correlations in Financial Markets(Nanyang Technological University) Dec 14, 2020 Intermediate Python NumPy npy files for manuscript submitted to Frontiers in Applied Mathematics and Statistics.
COVID-19 Statistics in China Oct 1, 2020 Cheong, Siew Ann; Liu, Wenyuan; Yen, Tsung-Wen Peter, 2020, "COVID-19 Statistics in China", https://doi.org/10.21979/N9/A2XWCW, DR-NTU (Data), V1, UNF:6:Q5f5mkGTX4bTDGqjjghVDA== [fileUNF] A data set on COVID-19 pandemic in China, which covers daily statistics of confirmed cases (new and cumulative), recoveries (new and cumulative) and deaths (new and cumulative) at city/county level. All data are extracted from Chinese government reports.
Zip's Law Null Model Samples for Reuters News Corpus Jul 21, 2020 - Reuters News Corpus Cheong, Siew Ann, 2020, "Zip's Law Null Model Samples for Reuters News Corpus", https://doi.org/10.21979/N9/EC76OJ, DR-NTU (Data), V1 npy files containing Zipf's Law null model samples for Reuters news corpus.

Hidden-State Modelling of a Cross-section of Geoelectric Time Series Data Can Provide Reliable Intermediate-term Probabilistic Earthquake Forecasting in Taiwan

Jun 1, 2021

Cheong, Siew Ann, 2021, "Hidden-State Modelling of a Cross-section of Geoelectric Time Series Data Can Provide Reliable Intermediate-term Probabilistic Earthquake Forecasting in Taiwan", https://doi.org/10.21979/N9/JSUTCD, DR-NTU (Data), V1

(C, V, S, K) index time series data generated using 0.5-Hz GEMS time series data from Taiwan. In this data set, C is a modified autocorrelation function, V is the variance, S the skewness, and K the kurtosis of the GEMS geo-electric field time series.

Using Topological Data Analysis (TDA) and Persistent Homology to Analyse the Stock Markets in Singapore and Taiwan

Feb 21, 2021

Cheong, Siew Ann, 2021, "Using Topological Data Analysis (TDA) and Persistent Homology to Analyse the Stock Markets in Singapore and Taiwan", https://doi.org/10.21979/N9/8XMZGF, DR-NTU (Data), V1

Data sets and Python scripts for paper published by T.-W. Yen and S. A. Cheong in Frontiers in Physics for a special issue "From Physics to Econophysics back to Physics: Methods and Insights".

Cross sections of 8 to 9 mixed assets after hypothesis testing

Dec 14, 2020 - Identifying Actionable Serial Correlations in Financial Markets

Cheong, Siew Ann, 2020, "Cross sections of 8 to 9 mixed assets after hypothesis testing", https://doi.org/10.21979/N9/FR745X, DR-NTU (Data), V1

Set 1 = (A) gold, (B) silver, (C) palladium, (D) S\&P 500, (E) Hang Seng, (F) platinum, (G) Dow Jones, (H) Nikkei, and (I) NASDAQ, prices between Apr 2, 1990 and Jan 28, 2018. Set 2 = (A) 5-year US bond, (B) 10-year US bond, (C) 2-year US bond, (D) 6-month US bond, (E) wheat, (F)...

Second cross section of 10 DJI component stocks: intermediate files for hypothesis testing

Dec 14, 2020 - Identifying Actionable Serial Correlations in Financial Markets

Cheong, Siew Ann, 2020, "Second cross section of 10 DJI component stocks: intermediate files for hypothesis testing", https://doi.org/10.21979/N9/FDIDAM, DR-NTU (Data), V1

Python npy files

Cross section of 5 DJI component stocks

Dec 14, 2020 - Identifying Actionable Serial Correlations in Financial Markets

Cheong, Siew Ann, 2020, "Cross section of 5 DJI component stocks", https://doi.org/10.21979/N9/KGGAMP, DR-NTU (Data), V1

['A', 'B', 'C', 'D', 'E', 'STC', 'STC5', 'TC5', 'fTC5', 'fTC5null', 'lmax', 'lmin', 'nSTCempty', 'setTC5', 'sigseqp001', 'sigseqp005', 'sigseqp005n5']

First cross section of 10 DJI component stocks: Intermediate data files for hypothesis testing

Dec 14, 2020 - Identifying Actionable Serial Correlations in Financial Markets

Cheong, Siew Ann, 2020, "First cross section of 10 DJI component stocks: Intermediate data files for hypothesis testing", https://doi.org/10.21979/N9/JCIKFR, DR-NTU (Data), V1

To be used for Python script for hypothesis testing.

First cross section of 10 DJI component stocks

Dec 14, 2020 - Identifying Actionable Serial Correlations in Financial Markets

Cheong, Siew Ann, 2020, "First cross section of 10 DJI component stocks", https://doi.org/10.21979/N9/GHMOKN, DR-NTU (Data), V1

X1 = GE, X2 = CSCO, X3 = HD, X4 = JPM, X5 = MMM, X6 = MRK, X7 = UTX, X8 = BA, X9 = VZ, X10 = XOM

Identifying Actionable Serial Correlations in Financial Markets(Nanyang Technological University)

Dec 14, 2020

Intermediate Python NumPy npy files for manuscript submitted to Frontiers in Applied Mathematics and Statistics.

COVID-19 Statistics in China

Oct 1, 2020

Cheong, Siew Ann; Liu, Wenyuan; Yen, Tsung-Wen Peter, 2020, "COVID-19 Statistics in China", https://doi.org/10.21979/N9/A2XWCW, DR-NTU (Data), V1, UNF:6:Q5f5mkGTX4bTDGqjjghVDA== [fileUNF]

A data set on COVID-19 pandemic in China, which covers daily statistics of confirmed cases (new and cumulative), recoveries (new and cumulative) and deaths (new and cumulative) at city/county level. All data are extracted from Chinese government reports.

Zip's Law Null Model Samples for Reuters News Corpus

Jul 21, 2020 - Reuters News Corpus

Cheong, Siew Ann, 2020, "Zip's Law Null Model Samples for Reuters News Corpus", https://doi.org/10.21979/N9/EC76OJ, DR-NTU (Data), V1

npy files containing Zipf's Law null model samples for Reuters news corpus.

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