Data Processing

Financial Data Knowledge and Processing

1. Harvard Online Courses, Data Science: Machine Learning

2. Harvard Online Courses, Data Science: Probability

3. Harvard Online Courses, Data Science: Linear Regression

4. Harvard Online Courses, Data Science: R Basics

5. Harvard Online Courses, Data Science Visualization

6. Harvard Online Courses, Intro to Data Science with Python

7. Harvard Online Courses, Data Science Capstone

8. Stanford Online Courses, R Programming Fundamentals 

9. Stanford Online Courses, Statistical Learning with Python

10. Stanford Online Courses, Mining Massive Data Sets

11. Stanford Online Courses, Statistical Learning with R

12. Stanford Online Courses, Databases: Relational and SQL

13. Stanford Online Courses, Databases: Semistructured Data

14. Stanford Online Courses, Databases: Advanced Topics in SQL

15. Ozenbas, Deniz et al. "Liquidity and the Impact of Information Shocks." Liquidity Markets and Trading in Action: An Interdisciplinary Perspective, edited by Deniz Ozenbas, Michael S. Pagano, Robert A. Schwartz, and Bruce W. Weber, Springer, 2022, pp. 51–69, https://link.springer.com/book/10.1007/978-3-030-74817-3

16. Sanger, William, and Thierry Warin. "High Frequency and Unstructured Data in Finance: An Exploratory Study of Twitter. Journal of Global Research in Computer Science, vol. 7, no. 4, April 2016, pp. 6–16, https://www.rroij.com/open-access/high-frequency-and-unstructured-data-in-finance-an-exploratory-study-oftwitter-.pdf

17. Cheng, Peng et al. "Massive Data Analytics for Macroeconomic Nowcasting." Data Science for Economics and Finance, edited by Sergio Consoli, Diego Reforgiato Recupero, and Michaela Saisana, Springer, 2021, pp. 145–167, https://link.springer.com/chapter/10.1007/978-3-030-66891-4_7.

18. Ghirelli, Corinna et al. "New Data Sources for Central Banks." Data Science for Economics and Finance, edited by Sergio Consoli, Diego Reforgiato Recupero, and Michaela Saisana, Springer, 2021, pp. 169–194, https://link.springer.com/chapter/10.1007/978-3-030-66891-4_8.

19. Akansu, Ali. "The Flash Crash: A Review."Journal of Capital Market Studies, vol. 1, no. 1, 2017, pp. 89–100, https://www.emerald.com/insight/content/doi/10.1108/JCMS-10-2017-001/full/html

20. Ishwarappa, and J. Anuradha. “A Brief Introduction on Big Data 5Vs Characteristics and Hadoop Technology.” Procedia Computer Science, vol. 48, 2015, pp. 319–24. Crossref, https://doi.org/10.1016/j.procs.2015.04.188

21. Bionic Turtle. "FRM: Why We Use Log Returns in Finance." YouTube, 3 Feb. 2009, https://www.youtube.com/watch?v=PtoUlt3V0CI.

22. Damodaran, Aswath. "Corporate Finance B40.2302 Lecture Notes: Packet 1." http://people.stern.nyu.edu/adamodar/pdfiles/cfovhds/cfpacket1spr19.pdf

23. "Measures of Spread: Range, Variance & Standard Deviation." Khan Academy. https://www.khanacademy.org/math/statistics-probability/summarizing-quantitative-data/variance-standard-deviation-population/v/range-variance-and-standard-deviation-as-measures-of-dispersion

24. Bionic Turtle. "Three Approaches to Value at Risk (VaR) and Volatility (FRM T4-1)." YouTube, 14 Nov. 2018, https://www.youtube.com/watch?v=qzOWm7PurHE.

25. Downey, Allen B. Think Stats: Exploratory Data Analysis in Python. Version 2.2, Green Tea Press, Needham, MA. https://greenteapress.com/thinkstats2/thinkstats2.pdf

26. Damodaran, Aswath. "January 2019 Data Update 4: The Many Faces of Risk!" YouTube, 21 Jan. 2019, https://www.youtube.com/watch?v=nI_vtGf5_Jc.

27. Downey, Allen B. Think Stats: Exploratory Data Analysis in Python. Version 2.2, Green Tea Press, Needham, MA. https://greenteapress.com/thinkstats2/thinkstats2.pdf

28. Khan Academy. "Exchange Traded Funds (ETFs) | Finance and Capital Markets | Khan Academy." YouTube, 18 April 2011, https://www.youtube.com/watch?v=SFdsY9Rdh6w.

29. DataCamp. "Python Tutorial: Correlation of Two Time Series." YouTube, 1 March 2020, https://www.youtube.com/watch?v=XVV6IVPUlKU.

30. Sargent, Thomas J., and John Stachurski. Python Programming for Economics and Finance. QuantEcon. https://python-programming.quantecon.org/functions.html.

31. Sargent, Thomas J., and John Stachurski. Python Programming for Economics and Finance. QuantEcon. https://python-programming.quantecon.org/python_essentials.html.

32. Sargent, Thomas J., and John Stachurski. Python Programming for Economics and Finance. QuantEcon. https://python-programming.quantecon.org/matplotlib.html.

33. Sargent, Thomas J., and John Stachurski. Python Programming for Economics and Finance. QuantEcon. https://python-programming.quantecon.org/pandas.html.

34. Sargent, Thomas J., and John Stachurski. Python Programming for Economics and Finance. QuantEcon. https://python-programming.quantecon.org/numpy.html.

35. Jena, Sangram Keshari et al. "Put–Call Ratio Volume vs. Open Interest in Predicting Market Return." Economies, vol. 7, no. 1, 2019, pp. 1–10, https://www.mdpi.com/2227-7099/7/1/24.

36. The pandas development team. pandas documentation. Version 1.4.2. https://pandas.pydata.org/docs/reference/

37. Sullivan, Eric. "Numerical Methods: An Inquiry-Based Approach in Python." GitHub.
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38. Python Software Foundation. Python 3.10.4 Documentation. https://docs.python.org/3/tutorial/controlflow.html.

39. Sargent, Thomas J., and John Stachurski. Python Programming for Economics and Finance. QuantEcon. https://python-programming.quantecon.org/python_essentials.html#id7

40. Sargent, Thomas J., and John Stachurski. Python Programming for Economics and Finance. QuantEcon. https://python-programming.quantecon.org/matplotlib.html

41. The pandas development team. pandas documentation. Version 1.4.2. https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.apply.html

42. Coleman, Chase et al. "GroupBy." QuantEcon Data Science. https://datascience.quantecon.org/pandas/groupby.html.

43. jakevdp. "PythonDataScienceHandbook." GitHub. https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.00-Introduction-To-Matplotlib.ipynb.

44. jakevdp. "PythonDataScienceHandbook." GitHub. https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.01-Simple-Line-Plots.ipynb.

45. jakevdp. "PythonDataScienceHandbook." GitHub. https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.02-Simple-Scatter-Plots.ipynb.

46. jakevdp. "PythonDataScienceHandbook." GitHub. https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.06-Customizing-Legends.ipynb.

47. jakevdp. "PythonDataScienceHandbook." GitHub. https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.08-Multiple-Subplots.ipynb.

48. jakevdp. "PythonDataScienceHandbook." GitHub. https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.09-Text-and-Annotation.ipynb.

49. 8. jakevdp. "PythonDataScienceHandbook." GitHub. https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.10-Customizing-Ticks.ipynb.

50. DocNow. "twarc." GitHub. https://github.com/DocNow/twarc/blob/4bff06bb8f2e279ea0a2064d6bfaec3c9b4b3aff/docs/api/library.md

51. twarc2 (en). twarc project. https://twarc-project.readthedocs.io/en/latest/twarc2_en_us/

52. Bailey, Mark M. "NRCLex 3.0.0." Python Software Foundation. https://pypi.org/project/NRCLex/

53. twitterdev. getting-started-with-the-twitter-api-v2-for-academic-research. GitHub.https://github.com/twitterdev/getting-started-with-the-twitter-api-v2-for-academic-research

54. Daityari, Shaumik. "How to Perform Sentiment Analysis in Python 3 Using the Natural Language Toolkit." Digital Ocean, 26 September 2019. https://www.digitalocean.com/community/tutorials/how-to-perform-sentiment-analysis-in-python-3-using-the-natural-language-toolkit-nltk

55. Wazeed17. "JavaScript JSON." GeeksforGeeks. https://www.geeksforgeeks.org/javascript-json/

56. vivekkothari. "Jason | Data Types" GeeksforGeeks. https://www.geeksforgeeks.org/json-data-types/

57. GeeksforGeeks. "Python JSON." https://www.geeksforgeeks.org/python-json/?ref=lbp

58. kartikeya shukla 1. "Working with JSON Data in Python." GeeksforGeeks. https://www.geeksforgeeks.org/working-with-json-data-in-python/?ref=lbp.

59. soumya 08. "Read, Write and Parse JSON Using Python." GeeksforGeeks. https://www.geeksforgeeks.org/read-write-and-parse-json-using-python/?ref=lbp.

60. aman neekhara. "Append to JSON File Using Python." GeeksforGeeks. https://www.geeksforgeeks.org/append-to-json-file-using-python/?ref=lbp.

61. kumar_satyam. "Serializing JSON Data in Python." GeeksforGeeks. https://www.geeksforgeeks.org/serializing-json-data-in-python/?ref=lbp

62. romy421kumari. "Deserialize JSON to Object in Python." GeeksforGeeks. https://www.geeksforgeeks.org/deserialize-json-to-object-in-python/?ref=lbp

63. rakshitarora. "json.load() in Python." GeeksforGeeks. https://www.geeksforgeeks.org/json-load-in-python/

64. manandeep1610. "json.loads() in Python." GeeksforGeeks. https://www.geeksforgeeks.org/json-loads-in-python/

65. sathvik chiramana. "json.dumps() in Python." GeeksforGeeks. https://www.geeksforgeeks.org/json-dumps-in-python/

66. erakshaya485. "json.dump() in Python." GeeksforGeeks. https://www.geeksforgeeks.org/json-dump-in-python/

67. Kashnitsky, Yury. "Topic 9. Part 1. Time Series Analysis in Python." Kaggle. https://www.kaggle.com/kashnitsky/topic-9-part-1-time-series-analysis-in-python.

68. Rooney. "Correlation: Pearson, Spearman, and Kendall." Kaggle. https://www.kaggle.com/kiyoung1027/correlation-pearson-spearman-and-kendall/report.

69. The Pennsylvania State University. "STAT 501: Regression Methods. 14.5.2 - Exponential Smoothing." PennState Eberly College of Science. https://online.stat.psu.edu/stat501/node/1001.

70. Technical Analysis. https://github.com/shshankar1/ebooks/blob/master/Technical_Analysis.pdf.

71. w3resource. "Python: enumerate() function." https://www.w3resource.com/python/built-in-function/enumerate.php.

72. ForexBoat. "Parabolic SAR Indicator Formula and Strategy." YouTube, 4 Oct. 2017, https://www.youtube.com/watch?v=kFTcvDsU1ik.

73. eVidhya. "ADX MACD Parabolic SAR Strategy | Forex Strategies." YouTube, 4 Oct. 2019, https://www.youtube.com/watch?v=hCo9ax0W2Bw.

74. ForexBoat. "Stochastic Oscillator Settings and Trading Strategy in Forex." YouTube, 21 Sept. 2017, https://www.youtube.com/watch?v=bb9ms3fUK7k.

75. Stas Serfes. "How to Use the RSI Indicator on ThinkOrSwim (Relative Strength Index)." YouTube, 27 March 2019, https://www.youtube.com/watch?v=01spTWPsRNY

76. bukosabino. "ta." GitHub. https://github.com/bukosabino/ta

77. Ma, Lijuan et al. "Fundamental Analysis in China: An Empirical Study of the Relationship between Financial Ratios and Stock Prices." Theoretical Economics Letters, vol. 8, no. 15, 2018, pp. 1–27, https://www.scirp.org/html/8-1501685_88850.htm

78. Edspresso. "What is the urllib module in Python 3?" Educative. https://www.educative.io/edpresso/what-is-the-urllib-module-in-python-3.

79. Pulkit_Singh. "Python Urllib Module." GeeksforGeeks.https://www.geeksforgeeks.org/python-urllib-module/.

80. Avasthi, Manika. Foundations of Business. 2020. https://pressbooks.rampages.us/businessfoundation/chapter/12-8/.

81. JerBouma. "FundamentalAnalysis." GitHub. https://github.com/JerBouma/FundamentalAnalysis

82. Zhao, Yilin. "Research on the GameStop Stock Prices Surge during Covid-19 under the Perspective of Individual Investors." Advances in Economics, Business and Management Research, Proceedings of the 2021 3rd International Conference on Economic Management and Cultural Industry, December 2021. https://www.atlantis-press.com/proceedings/icemci-21/125966071.

83. Hott, Christian. "Leverage and Risk Taking under Moral Hazard." Journal of Financial Services Research, vol. 61, 2022, pp. 167–185, https://link.springer.com/article/10.1007/s10693-021-00359-8.

84. Wujek, Joseph H. "Challenger O-Ring Data Analysis." Online Ethics Center for Engineering and Science, 1995, https://onlineethics.org/cases/numerical-design-problems-ethical-content/challenger-o-ring-data-analysis.

85. CBS News. "Stock Trade Typo Costs Firm $225M." 9 December 2005. https://www.cbsnews.com/news/stock-trade-typo-costs-firm-225m/.

86. Gerber, James. A Great Deal of Ruin: Financial Crises Since 1929. Cambridge University Press, 2019.

87. Hott, Christian. "Leverage and Risk Taking under Moral Hazard." Journal of Financial Services Research, vol. 61, 2022, pp. 167–185, https://link.springer.com/article/10.1007/s10693-021-00359-8.

88. Lo, Andrew. Adaptive Market Hypothesis. Princeton University Press, 2017.

89. SAS. "SAS Acquires Kamakura to Propel Risk Technology Innovation as Financial Sector Braces for Volatility." 27 June 2022. https://www.sas.com/en_us/news/press-releases/2022/june/sas-acquires-kamakura-corp.html.

90. Wilmott. Financial Modelers’ Manifesto, 2009. https://wilmott.com/financial-modelers-manifesto/.

91. Wujek, Joseph H. "Challenger O-Ring Data Analysis." Online Ethics Center for Engineering and Science, 1995, https://onlineethics.org/cases/numerical-design-problems-ethical-content/challenger-o-ring-data-analysis.

92. Zhao, Yilin. "Research on the GameStop Stock Prices Surge during Covid-19 under the Perspective of Individual Investors." Advances in Economics, Business and Management Research, Proceedings of the 2021 3rd International Conference on Economic Management and Cultural Industry, December 2021. https://www.atlantis-press.com/proceedings/icemci-21/125966071.

93. Alma Mater Studiorum. Information Literacy Tutorial. 2018. https://sba.unibo.it/en/services/training/tutorial-di-information-literacy-1.

94. Ismail, W. Omar Ali Saifuddin Wan, et al. "The Essential of Engineering Education Involving Critical Thinking and Problems Solving Skills among Mechanical Engineer Employees." IOP Conference Series: Materials Science Engineering, vol. 697, 2019, https://iopscience.iop.org/article/10.1088/1757-899X/697/1/012017.

95. Hattingh, Marié, et al. "The Use of Critical Thinking to Identify Fake News: A Systematic Literature Review." Responsible Design, Implementation and Use of Information and Communication Technology, 2020, pp. 235–246, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7134234/.

96. Alma Mater Studiorum. Information Literacy Tutorial. 2018. https://sba.unibo.it/en/services/training/tutorial-di-information-literacy-1.

97. Hattingh, Marié, et al. "The Use of Critical Thinking to Identify Fake News: A Systematic Literature Review." Responsible Design, Implementation and Use of Information and Communication Technology, 2020, pp. 235–246, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7134234/.

98. Ismail, W. Omar Ali Saifuddin Wan, et al. "The Essential of Engineering Education Involving Critical Thinking and Problems Solving Skills among Mechanical Engineer Employees." IOP Conference Series: Materials Science Engineering, vol. 697, 2019, https://iopscience.iop.org/article/10.1088/1757-899X/697/1/012017.

99. Grammatikos, Theoharry, and Nikolaos I. Papanikolaou. "Applying Benford's Law to Detect Accounting Data Manipulation in the Banking Industry." Journal of Financial Services Research, vol. 59, 2021, pp. 115-142, https://link.springer.com/article/10.1007/s10693-020-00334-9.

100. Chang, Kuo-Chung. "The Effect of Data Theft on a Firm's Short-Term and Long-Term Market Value." Mathematics, vol. 8, no. 5, 2020, https://www.mdpi.com/2227-7390/8/5/808/htm.

101. Liu, Grace. "Data Quality Problems Troubling Business and Financial Researchers: A Literature Review and Synthetic Analysis." Journal of Business & Finance Librarianship, 2020, https://digitalcommons.wcupa.edu/lib_facpub/13/.

102. Arliss, Will. "Probability of the Challenger Disaster." Medium, 9 October 2020, https://towardsdatascience.com/probability-of-the-challenger-disaster-c2a17b7984cc.

103. Barret, Brian. "An Artist Used 99 Phones to Fake a Google Maps Traffic Jam." Wired, 3 Feb. 2020, https://www.wired.com/story/99-phones-fake-google-maps-traffic-jam/.

104. Butler, Oobah. "I Made My Shed the Top Rated Restaurant On TripAdvisor." Vice, 6 December 2017, https://www.vice.com/en/article/434gqw/i-made-my-shed-the-top-rated-restaurant-on-tripadvisor.

105. Chang, Kuo-Chung, et al. "The Effect of Data Theft on a Firm’s Short-Term and Long-Term Market Value." Mathematics, vol. 8, no. 5, 2020, https://www.mdpi.com/2227-7390/8/5/808/htm.

106. D'Acunto, Francesco, and Alberto Rossi. "Robo-advice: An Effective Tool to Reduce Inequalities?" Brookings, 5 Oct. 2022, https://www.brookings.edu/research/robo-advice-an-effective-tool-to-reduce-inequalities/.

107. Grammatikos, Theoharry, and Nikolaos I. Papanikolaou. "Applying Benford’s Law to Detect Accounting Data Manipulation in the Banking Industry." Journal of Financial Services Research, vol. 59, 2021, pp. 115–142, https://link.springer.com/article/10.1007/s10693-020-00334-9.

108. Horn, Sebastian, et al. "Systematic Underreporting of Public Debt Statistics: 50 Years of Evidence and Recent Progress." World Bank Blogs, 3 March 2022, https://blogs.worldbank.org/developmenttalk/systematic-underreporting-public-debt-statistics-50-years-evidence-and-recent.

109. Klosowski, Thorin. "The State of Consumer Data Privacy Laws in the US (And Why It Matters)." The New York Times, 6 Sept. 2021, https://www.nytimes.com/wirecutter/blog/state-of-privacy-laws-in-us/.

110. Le Marois, Oliver, and Douady, Raphael. "Return Smoothing Practices." The Hedge Fund Journal, 2007, https://thehedgefundjournal.com/return-smoothing-practices/.

111. Levitt, Steven D., and Stephen J. Dubner. _Freakonomics: A Rogue Economist Explores the Hidden Side of Everything. _William Morrow, 2005.

112. Liu, Grace. "Data Quality Problems Troubling Business and Financial Researchers: A Literature Review and Synthetic Analysis." Journal of Business & Finance Librarianship, November 2020, https://digitalcommons.wcupa.edu/lib_facpub/13/.

113. U.S. Securities and Exchange Commission. "SEC Charges Investment Adviser with Failing to Disclose Conflicts Arising from Mutual Fund and Account Recommendations." March 2022, https://www.sec.gov/litigation/litreleases/2022/lr25340.htm.

114. U.S. Securities and Exchange Commission. "SEC Charges Father-and-Son Hedge Fund Managers Who Agree to Pay $4.8 Million to Settle Fraud Case." 2012, https://www.sec.gov/news/press-release/2012-2012-71htm.

115. U.S. Securities and Exchange Commission. "SEC Charges Hertz with Inaccurate Financial Reporting and Other Failures. 1 Feb. 2019, https://www.sec.gov/enforce/33-10601-s.

116. U.S. Securities and Exchange Commission. "SEC Charges Two Robo-Advisers With False Disclosures." 2018, https://www.sec.gov/news/press-release/2018-300.

117. Data Cleaning Example - Loan Data, https://winder.ai/data-cleaning-example-loan-data/ 

118. Web Scarping for Economist, Javad Shamsi (LSE PhD Candidate), https://github.com/mjavadshamsi/web-scraping-economists/