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11 to 20 of 80 Results
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
COVID-19 Statistics in China
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.
Bigram-Based Comparison of Keywords From Different Methods for Reuters News Corpus
Jul 21, 2020 - Reuters News Corpus
Cheong, Siew Ann, 2020, "Bigram-Based Comparison of Keywords From Different Methods for Reuters News Corpus", https://doi.org/10.21979/N9/YMVWYW, DR-NTU (Data), V1
npy files containing the number of matching bigrams as a function of list length for different pairs of methods applied to the Reuters news corpus.
Word-Based Comparison of Keywords From Different Methods for Reuters News Corpus
Jul 21, 2020 - Reuters News Corpus
Cheong, Siew Ann, 2020, "Word-Based Comparison of Keywords From Different Methods for Reuters News Corpus", https://doi.org/10.21979/N9/1YOH1P, DR-NTU (Data), V1
npy files containing the number of matching words as a function of list length for different pairs of methods applied to the Reuters news corpus.
Log Rank Movements
Jul 21, 2020 - Reuters News Corpus
Cheong, Siew Ann, 2020, "Log Rank Movements", https://doi.org/10.21979/N9/S6XPII, DR-NTU (Data), V1
npy files for the log rank movements for words and bigrams of Reuters news corpus.
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