AY2015/2016, Semester 1
EC4103 Sinapore Economy: Practice & Policy
This is a new core module for all economics major. It provides an overview of the Singapore economy, the international trade and financial framework that Singapore operates in, and the fiscal policies tackling the main challenges faced by Singapore. While I appreciate the intention behind this module, that is to expose undergraduates to the various aspects of policy making in Singapore, there are many things the department can improve on. First of all, I believe that the scope is too broad (5 lecturers on 5 different aspects) and thus the module is lacking in terms of depth and rigor in any and every aspect. Second, 100% CA is heavy, but to partitioned the 100% into five 20% segments with weekly submissions and presentations, it's a chore. All, yes all, of my friends think it's a pain in the ass. Most people (including myself) would prefer to focus on other modules which allow us to focus on proper research in ONE specific topic/area for the whole semester. That tastes more like research. In summary, most stuff taught are good-to-know facts, the projects are either summarizing-existing-arguments-on-the internet-to-justify-your-stand, or use-STATA-to-get-some-numbers. I don't think the department is going to remove this module any time soon, So I really hope they make fundamental changes to how the module is being organized. Finally, I honestly need to thank my group mates for their effort and accommodating with my hectic schedules.
Grading: 100% Group Project (20% for each segment).
Grade: A-
EC4303 Econometrics III
For this module, Dr. Oka placed greater emphasis on the breadth of the module, so it was covered with much less rigor than I thought. We covered OLS, MLE, Nonparametric Regressions, Quantile Regressions, Time Series (ARMA/GARCH), (Dynamic) Panel Data, LASSO, CART, Potential Outcome Framework, RDD. That amounts to one new topic/method every week. Book presentation component was quite interesting. The chapters are quite advanced for an undergraduate, so half the time we don't catch what the other groups are presenting. Fortunately, it is not tested in final exam unless it's covered in lecture notes (like Nonparametric and CART). The most memorable part was the term project, where my group took upon the challenge to do nonparametric GARCH (1-step ahead) forecasting on STI data. No amount of words can describe how much I've learn about econometrics in the process. Self-revising R to code the in-sample fitting and out-of-sample forecasting process, deciding between all the information criterion, learning about the L1 and L2 goodness-of-fit measure, and using RMSE vs Diebold-Mariano Test for forecasting superiority. It's an enjoyable process and when the final results are tabulated, there's so much pride in the work. Final exam was a little messy and I could probably do better with a clearer thought process, nevertheless, I did my best at that point of time.
Grading: 10% Tutorial Participation, 10% Presentation, 20% Assignments, 20% Group Project, 40% Final Exam.
Grade: A
EC4332 Money & Banking II
Took this module because the department DE-LISTED EC4331. Ultimate disappointment. I was looking forward to the New-Keynesian Models in EC4331. For EC4332, it's not too bad. Dr. Park is pretty chill about his midterm and final exams. The questions weren't too difficult, the course content required only minimal effort on my part, the project was not too time-consuming. Prof Bodenstein told me early in the semester that the department wants a more qualitative EC4332, and Dr. Park delivered exactly that. The intuitions are conveyed across with intuitive examples and not overly daunting. For banking, he covered the Diamond-Dybvig model and extensions to bank runs and sunspot variables, IO-style symmetric banking equilibrium (both partial and complete). He did not touch on extended topics such as lender-borrow relationship, collaterals, and shadow banking. For those who plan to take EC4332 under Dr. Huang next sem, do note that he plans to cover this (and less on monetary economics). For monetary economics, only the overlapping generation model and money-in-utility model are covered. There was also a group empirical assignment that require us to analyze Singapore's business cycles. It was a simple assignment but it's quite interesting to take theory to the data. Some of the empirical facts are tested in the final exam.
Grading: 10% Tutorial Participation, 20% Assignments, 30% Midterm Test, 40% Final Exam.
Grade: A-
EC4333 Financial Economics II
This module continues from EC3333. Only reason I took this module is to clear my specialization requirements. First half goes through interest rates, bonds, risk aversion, stochastic dominance, portfolio hedging and some extra stuff on econometrics. The second half move towards Markowitz's portfolio selection theory, stochastic calculus and risk neutral valuation. This module is not too difficult under Prof Tsui if you actually pay attention to his lectures. First half requires only geometric series and calculus. The second half it's trickier, some linear algebra knowledge can help the portfolio theory segment, while for a good understanding of stochastic calculus one would need to know some rigorous math. Fortunately, you can survive the course with a just a good understanding of Ito's lemma, Wiener process, and the lognormal property. Speaking of which, I made a mistake representing lognormal-distributed stock price in normal form. Oops!
Grading: 10% Tutorial Participation, 30% Group Project, 30% Midterm Test, 30% Final Exam.
Grade: A
EC5104R Mathematical Economics
THIS IS ONE CRAZY MODULE. NUFF SAID. LOL. Okay I'll elaborate. Tthe only thing that might help is a good real analysis background. MA2108, MA3110, MA3209, MA4211, MA4266. Maybe EC3314 under Prof Quah. Main properties of functions and correspondences covered are continuity, convexity, completeness and compactness. The major results proved in class include Mean Value Theorem, Intermediate Value Theorem, Extreme Value Theorem, Maximum Theorem, Fixed Point Theorems, Benveniste-Scheinkman Theorem, Inverse Function Theorem, and Implicit Function Theorem. Building on these theorems, we derive the conditions in which optimal solutions exist and how these solutions can be computed using the Lagrangian method and Karush-Kuhn-Tucker conditions for static problems, and the equivalence between the unique, optimal solution of the Bellman Equation and the solution to the Sequence Problem in dynamic programming. In summary, HARD, VERY HARD. Not even exaggerating. It doesn't help that Prof Takahashi marks in an all-or-nothing manner. Either you get full credit worth 10% of the overall marks, or nothing at all. So one small mistake can cost you a bomb because this module is non-bell-curved so each % is too damn precious. It's the one module where studying very, very hard doesn't guarantee any result (I spent 60% of my sem studying for this), but not studying guarantees failure. I knew I didn't do well but I was expecting at least a B, I hope it doesn't affect graduate admission that much :(
Grading: 20% Assignments, 40% Midterm Test, 40% Final Exam.
Grade: B-
EC5332R Money & Banking
I audited this module under the permission of Prof. Bodenstein. However, I've only managed to attend two seminars as it clashes with MA3209 lectures (or when lunch takes precedence lol). The course follows the same textbook as the banking part of EC4332, and also covers the extended topics with greater detail. I must say that I did learn a lot more about banking in this class, albeit my lack of attendance. It appears that this module overlaps almost entirely with Dr. Huang's EC4332 syllabus next semester.
Grading: 40% Presentations, 20% Assignments, 40% Group Project.
Grade: N/A
MA3209 Mathematical Analysis III
This module generalizes the theorems in MA2108 and MA3110 to metric spaces, in particular, the Euclidean n-spaces, bounded and/or continuous function spaces. Concepts of open and closed sets are studied in detail. Continuity concept is generalized to metric spaces. Together with completeness, connectedness, and compactness properties of metric subspaces, these topics dominated the first half of the course. The second half focused on differentiability of multivariate functions, which is a rigorous synthesis of MA1104 and MA3110. Inverse Function Theorem, Implicit Function Theorem, and the Lagrangian Theorem are the main results of this segment of the course. In summary, generalizing MA2108/MA3110 from 2D to nD. Damn, I was invoking the Implicit Function Theorem in the final exam, but I wrote "by Inverse Function Theorem". Apparently I wasn't penalized (too heavily) for that since I expected a B+. I think I'll do some topology next sem since I don't need to S/U this.
Grading: 10% Assignments, 40% Midterm Test, 50% Final Exam.
Grade: B+
MA4269 Mathematical Finance II
Ahh this module was fun but I kinda screwed the midterm (it's only 20% though). This module covers a wide range of options: European, American, Asian, Barrier, Lookback, Exchange. Wow. It's really interesting to learn beyond the vanilla options and discrete-time n-step binomial pricing in MA3269. The course content focus on continuous-time finance, with the martingale approach being the main risk-neutral valuation method. PDE formulation governing the asset value is also a huge topic, but we are not required to solve the PDEs. However, to use the martingale pricing approach, the Martingale Representation Theorem, Radon-Nikodyn Theorem, and Girsanov Theorem are indispensable. So, we have to learn some basic concepts regarding probability measures and how to transform between different numeraires. Well, actually, just between money and stock numeraires. It's a very good introduction to exotic options, and you'd see why quantitative finance/financial engineering positions are filled with mathematicians, physicists and engineers instead of business school graduates. Like all math modules, final was a race against time. Didn't manage to do one full question for this paper but I doubt many finished the paper anyway.
Grading: 20% Assignments, 20% Midterm Test, 60% Final Exam.
Grade: B+
Ending Note
SAP is 4.30, which is well within my expectation of 4.26-4.36. Honestly, 33MC was much heavier than expected but it was still manageable with some sacrifice (like not choreoing for DP, having minimal social life, zero games, think only math and econs). CAP finally breached the barrier to 4.01 after working my ass off for 5 semesters. On the dark side (SORRY I JUST WATCHED STAR WARS), when I checked my results my eyes instinctively went for EC5104R and was rather disappointed. I was hoping for a miracle (getting a B+ or better) for it because it is one of the signaling module for graduate admissions (since it's a graduate module). OH WELL.
This is a new core module for all economics major. It provides an overview of the Singapore economy, the international trade and financial framework that Singapore operates in, and the fiscal policies tackling the main challenges faced by Singapore. While I appreciate the intention behind this module, that is to expose undergraduates to the various aspects of policy making in Singapore, there are many things the department can improve on. First of all, I believe that the scope is too broad (5 lecturers on 5 different aspects) and thus the module is lacking in terms of depth and rigor in any and every aspect. Second, 100% CA is heavy, but to partitioned the 100% into five 20% segments with weekly submissions and presentations, it's a chore. All, yes all, of my friends think it's a pain in the ass. Most people (including myself) would prefer to focus on other modules which allow us to focus on proper research in ONE specific topic/area for the whole semester. That tastes more like research. In summary, most stuff taught are good-to-know facts, the projects are either summarizing-existing-arguments-on-the internet-to-justify-your-stand, or use-STATA-to-get-some-numbers. I don't think the department is going to remove this module any time soon, So I really hope they make fundamental changes to how the module is being organized. Finally, I honestly need to thank my group mates for their effort and accommodating with my hectic schedules.
Grading: 100% Group Project (20% for each segment).
Grade: A-
EC4303 Econometrics III
For this module, Dr. Oka placed greater emphasis on the breadth of the module, so it was covered with much less rigor than I thought. We covered OLS, MLE, Nonparametric Regressions, Quantile Regressions, Time Series (ARMA/GARCH), (Dynamic) Panel Data, LASSO, CART, Potential Outcome Framework, RDD. That amounts to one new topic/method every week. Book presentation component was quite interesting. The chapters are quite advanced for an undergraduate, so half the time we don't catch what the other groups are presenting. Fortunately, it is not tested in final exam unless it's covered in lecture notes (like Nonparametric and CART). The most memorable part was the term project, where my group took upon the challenge to do nonparametric GARCH (1-step ahead) forecasting on STI data. No amount of words can describe how much I've learn about econometrics in the process. Self-revising R to code the in-sample fitting and out-of-sample forecasting process, deciding between all the information criterion, learning about the L1 and L2 goodness-of-fit measure, and using RMSE vs Diebold-Mariano Test for forecasting superiority. It's an enjoyable process and when the final results are tabulated, there's so much pride in the work. Final exam was a little messy and I could probably do better with a clearer thought process, nevertheless, I did my best at that point of time.
Grading: 10% Tutorial Participation, 10% Presentation, 20% Assignments, 20% Group Project, 40% Final Exam.
Grade: A
EC4332 Money & Banking II
Took this module because the department DE-LISTED EC4331. Ultimate disappointment. I was looking forward to the New-Keynesian Models in EC4331. For EC4332, it's not too bad. Dr. Park is pretty chill about his midterm and final exams. The questions weren't too difficult, the course content required only minimal effort on my part, the project was not too time-consuming. Prof Bodenstein told me early in the semester that the department wants a more qualitative EC4332, and Dr. Park delivered exactly that. The intuitions are conveyed across with intuitive examples and not overly daunting. For banking, he covered the Diamond-Dybvig model and extensions to bank runs and sunspot variables, IO-style symmetric banking equilibrium (both partial and complete). He did not touch on extended topics such as lender-borrow relationship, collaterals, and shadow banking. For those who plan to take EC4332 under Dr. Huang next sem, do note that he plans to cover this (and less on monetary economics). For monetary economics, only the overlapping generation model and money-in-utility model are covered. There was also a group empirical assignment that require us to analyze Singapore's business cycles. It was a simple assignment but it's quite interesting to take theory to the data. Some of the empirical facts are tested in the final exam.
Grading: 10% Tutorial Participation, 20% Assignments, 30% Midterm Test, 40% Final Exam.
Grade: A-
EC4333 Financial Economics II
This module continues from EC3333. Only reason I took this module is to clear my specialization requirements. First half goes through interest rates, bonds, risk aversion, stochastic dominance, portfolio hedging and some extra stuff on econometrics. The second half move towards Markowitz's portfolio selection theory, stochastic calculus and risk neutral valuation. This module is not too difficult under Prof Tsui if you actually pay attention to his lectures. First half requires only geometric series and calculus. The second half it's trickier, some linear algebra knowledge can help the portfolio theory segment, while for a good understanding of stochastic calculus one would need to know some rigorous math. Fortunately, you can survive the course with a just a good understanding of Ito's lemma, Wiener process, and the lognormal property. Speaking of which, I made a mistake representing lognormal-distributed stock price in normal form. Oops!
Grading: 10% Tutorial Participation, 30% Group Project, 30% Midterm Test, 30% Final Exam.
Grade: A
EC5104R Mathematical Economics
THIS IS ONE CRAZY MODULE. NUFF SAID. LOL. Okay I'll elaborate. Tthe only thing that might help is a good real analysis background. MA2108, MA3110, MA3209, MA4211, MA4266. Maybe EC3314 under Prof Quah. Main properties of functions and correspondences covered are continuity, convexity, completeness and compactness. The major results proved in class include Mean Value Theorem, Intermediate Value Theorem, Extreme Value Theorem, Maximum Theorem, Fixed Point Theorems, Benveniste-Scheinkman Theorem, Inverse Function Theorem, and Implicit Function Theorem. Building on these theorems, we derive the conditions in which optimal solutions exist and how these solutions can be computed using the Lagrangian method and Karush-Kuhn-Tucker conditions for static problems, and the equivalence between the unique, optimal solution of the Bellman Equation and the solution to the Sequence Problem in dynamic programming. In summary, HARD, VERY HARD. Not even exaggerating. It doesn't help that Prof Takahashi marks in an all-or-nothing manner. Either you get full credit worth 10% of the overall marks, or nothing at all. So one small mistake can cost you a bomb because this module is non-bell-curved so each % is too damn precious. It's the one module where studying very, very hard doesn't guarantee any result (I spent 60% of my sem studying for this), but not studying guarantees failure. I knew I didn't do well but I was expecting at least a B, I hope it doesn't affect graduate admission that much :(
Grading: 20% Assignments, 40% Midterm Test, 40% Final Exam.
Grade: B-
EC5332R Money & Banking
I audited this module under the permission of Prof. Bodenstein. However, I've only managed to attend two seminars as it clashes with MA3209 lectures (or when lunch takes precedence lol). The course follows the same textbook as the banking part of EC4332, and also covers the extended topics with greater detail. I must say that I did learn a lot more about banking in this class, albeit my lack of attendance. It appears that this module overlaps almost entirely with Dr. Huang's EC4332 syllabus next semester.
Grading: 40% Presentations, 20% Assignments, 40% Group Project.
Grade: N/A
MA3209 Mathematical Analysis III
This module generalizes the theorems in MA2108 and MA3110 to metric spaces, in particular, the Euclidean n-spaces, bounded and/or continuous function spaces. Concepts of open and closed sets are studied in detail. Continuity concept is generalized to metric spaces. Together with completeness, connectedness, and compactness properties of metric subspaces, these topics dominated the first half of the course. The second half focused on differentiability of multivariate functions, which is a rigorous synthesis of MA1104 and MA3110. Inverse Function Theorem, Implicit Function Theorem, and the Lagrangian Theorem are the main results of this segment of the course. In summary, generalizing MA2108/MA3110 from 2D to nD. Damn, I was invoking the Implicit Function Theorem in the final exam, but I wrote "by Inverse Function Theorem". Apparently I wasn't penalized (too heavily) for that since I expected a B+. I think I'll do some topology next sem since I don't need to S/U this.
Grading: 10% Assignments, 40% Midterm Test, 50% Final Exam.
Grade: B+
MA4269 Mathematical Finance II
Ahh this module was fun but I kinda screwed the midterm (it's only 20% though). This module covers a wide range of options: European, American, Asian, Barrier, Lookback, Exchange. Wow. It's really interesting to learn beyond the vanilla options and discrete-time n-step binomial pricing in MA3269. The course content focus on continuous-time finance, with the martingale approach being the main risk-neutral valuation method. PDE formulation governing the asset value is also a huge topic, but we are not required to solve the PDEs. However, to use the martingale pricing approach, the Martingale Representation Theorem, Radon-Nikodyn Theorem, and Girsanov Theorem are indispensable. So, we have to learn some basic concepts regarding probability measures and how to transform between different numeraires. Well, actually, just between money and stock numeraires. It's a very good introduction to exotic options, and you'd see why quantitative finance/financial engineering positions are filled with mathematicians, physicists and engineers instead of business school graduates. Like all math modules, final was a race against time. Didn't manage to do one full question for this paper but I doubt many finished the paper anyway.
Grading: 20% Assignments, 20% Midterm Test, 60% Final Exam.
Grade: B+
Ending Note
SAP is 4.30, which is well within my expectation of 4.26-4.36. Honestly, 33MC was much heavier than expected but it was still manageable with some sacrifice (like not choreoing for DP, having minimal social life, zero games, think only math and econs). CAP finally breached the barrier to 4.01 after working my ass off for 5 semesters. On the dark side (SORRY I JUST WATCHED STAR WARS), when I checked my results my eyes instinctively went for EC5104R and was rather disappointed. I was hoping for a miracle (getting a B+ or better) for it because it is one of the signaling module for graduate admissions (since it's a graduate module). OH WELL.