RMSC4003 (2020 Fall)
RMSC4003 (2020 Fall)
Embedded Files
Statistical Modelling in Financial Markets
Statistical Modelling in Financial Markets
Tutorial Time: (Sep - Dec 2020)
Tue: 17:30pm - 18:15pm
Thu: 13:30pm - 14:15pm
Login Details
Meeting ID: 923 2524 7296
Password: See Blackboard
Tutorial Notes
Tutorial Notes
Tutorial 1 (22/9, 24/9): (Notes) r4003_t1.pdf; (R code) r4003_t1.R ; (Data) 0282.HK.csv
Tutorial 2 (29/9, 1/10): (Notes) r4003_t2.pdf; (Notes with answers) r4003_t2_sol.pdf
Tutorial 3 (6/10, 8/10): (Notes) r4003_t3.pdf; (Notes with answers) r4003_t3_sol.pdf
R example on efficient frontier (To be discussed in Tutorial 4): r4003_t3_example.html
Tutorial 4 (13/10, 15/10): (Notes) r4003_t4.pdf; (Notes with answers) r4003_t4_sol.pdf
Tutorial 5 (20/10, 22/10): (Notes) r4003_t5.pdf; (Notes with answers) r4003_t5_sol.pdf
Tutorial 6 (27/10, 29/10): (Notes) r4003_t6.pdf; (Notes with answers) r4003_t6_sol.pdf
Tutorial 7 (3/11, 5/11): (Notes) r4003_t7.pdf; (Notes with answers) r4003_t7_sol.pdf; (Handwritten) r4003_t7_hand.pdf
Tutorial 8 (17/11, 19/11): (Notes) r4003_t8.pdf; (Notes with answers) r4003_t8_sol.pdf
Tutorial 9 (24/11, 26/11): (Notes) r4003_t9.pdf; (Notes with answers) r4003_t9_sol.pdf
Tutorial 10 (1/12, 3/12): (Notes) r4003_t10.pdf; (Notes with answers) r4003_t10_sol.pdf
Tutorial 11 (No tutorial): (Notes) r4003_t11.pdf; (Notes with answers) r4003_t11_sol.pdf
Others:
Others:
Assignment 1 Hints: r4003_a1_hints.pdf
Assignment 3 Hints: r4003_a3_hints.pdf
Market News:
Market News:
Background knowledge:
Background knowledge:
Finding inverse with Gaussian Elimination. video
Optional materials that might be helpful to you:
Optional materials that might be helpful to you:
Financial Markets by Robert Shiller: https://www.coursera.org/learn/financial-markets-global
*Robert Shiller is a favourite finance professor of mine.
VBA course on udemy: https://www.udemy.com/course/ultimate-excel-programmer/
Introduction to Statistical Learning with Application in R (A book with video lectures by two Stanford Professors). https://www.dataschool.io/15-hours-of-expert-machine-learning-videos/
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