Analytics for Capital Market Trading and Investment (BT4013), NUS, Jan-May 2019

• He is very responsible.
• Well scheduled lecture and good sense of responsibility
• Great teacher
• great teacher
• He is very professional and enthusiastic in teaching.
• Patient and helpdul educator
• Nice to student
• Passionate towards teaching and goes the extra mile to check that we are okay with the pace of the lesson + constantly asking us for feedback
• One of the most rewarding module in my course
• he is an effective lecturer that teaches well
• He is well prepared and knowledgable.
• He is enthusiastic when teaching.
• ok
• accepting teacher that encourages class participation and helps students in need
• Responsible, effective, approachable
• Good knowledge on the topics.
• Very motivated teacher that is very knowledgeable and clear on what he is teaching.
• Humorous, knowledgeable, plans the lessons well
• Patient and willing to repeat and explain concepts that are unclear to students
• Very clear explanation for concept, well planned slides
• Clear and goes through the entire rationale and idea on how each algo works
• Very proficient in knowledge and teaches very well.
• Very comprehensive and tries to ensure that the weaker students are accounted for
• Good technical knowledge, engaging in class
• Highly engaging and relevant. Examples used in class generally relevant to real world.
• very engaging lecture
• Very clear in teaching, breaks down the concepts and formulas so that it is easy to understand
• Knows his content well and puts in effort to make sure we all do too.
• knowledge
• Approachable
• Speak more clearly and slow down the pace.
• motivation
• N.A.
• less futures for the projects
• I believe that the workload for this module is very heavy. Too many homework to submit. I believe that the workload for this module could be lighter.
• Give less homework
• less quiz
• Lesser content or workload. The module is too heavy.
• Given that our math background may not be as strong as what he expects, the department could introduce rigorous statistics modules to help facilitate the transition to said module. I do believe the cohort needs a stronger statistical background anyways.
• Balance module workload, higher weightage components and less grade components.
• there can be too much new content in one lesson sometimes, which makes it difficult to absorb everything at once
• Do not leave blanks in notes
• Would like to see a bit more hands-on in coding the algorithms out for backtesting properly etc. Quiz right at 9am is also quite brutal.
• using piazza is a stupid idea
• don't try to rush your content
• It would be great if Stanley can balance the workload of each homework.
• don't speak too fast; dont rush through the materials
• Good and passionate teacher
• Well structured content
• great
• Enthusiastic and professional in teaching.
• Patient to answer qns
• Patient and effective lecturer
• I like his sense of humor
• Enthusiastic
• Clear and goes through the entire rationale and idea on how each algo works
• One of the most engaging professors I've encountered.
• Very technical, great understanding of subject matter.
• Approachable
• Patient and willing to help
• Clear explanation
• Comprehensive materials
• Clear and easy to understand
• He is knowledgeable and patient.
• Get a better TA
• Lectures may be a little fast at times without any opportunities to catch up.
• Work on balancing the workload of the module. Module workload is very high with numerous components that weigh little. Perhaps the project can take up a higher proportion of marks and reduce the number of homeworks.
• Be more clear
• Less homework
• Provide more comprehensive notes
• N.a
• Reduce/spread out workload
• Speak more clearly and slow down the pace
• too difficult i not good in math
• Too much theory on the math too little application
• Dry at times
• More time can be spent on teaching the difficult concepts that are introduced towards the end of the module
• Too much homework disrupted the revision schedule
• The project
• Too much math.
• Too many assignments.
• The assignments are not spread out properly (too much at the last part)
• Too content heavy
• Workload may be slightly heavier than expected
• Too many assignments coupled with project and midterms. Possibly reduce the workload and focus on less content.
• too heavy
• too much unnecessary details
• too much homework
• piazza is hell
• u can't apply what u learn in project
• mathematically heavy
• Exposes us to time-series modeling
• i get to participate in a soft-quant competition
• it telling me that quant trading is difficult
• All concepts are explained clearly and concisely.
• the industry talks
• It is a difficult module, very content heavy and intensive in terms of cumulative assessments. I feel as if every 1% of the grade is hard earned! Nonetheless, it has provided me with a lot of working knowledge that I really appreciate.
• Rigorous, actually feel like I am learning useful things
• Well planned module that teaches important time series concepts
• Well planned, useful content
• Lots of hands-on about how to analyse time series data (work with real world data too).
• Good real world application
• Interesting things covered, and application is possible in projects and assignments.
• Goes into the technical aspect of time series analysis, very statistically and linked mathematical intuition with real-world application
• Good learning curve, very comprehensive in coverage.
• Something new, first time learning time-series analysis. Well paced.
• Good combination of theory and practices
• I can explore real data.