QUANTAMENTALS (AC317)

Transcription

1 QUANTAMENTALS (AC317) Course duration: 54 hours lecture and class time (Over three weeks) Summer School Programme Area: Accounting LSE Teaching Department: Department of Accounting Lead Faculty: Dr Jose Carabias Palmeiro (Dept. of Accounting OLD.2.13) Pre-requisites: Introductory Accounting (including basic financial analysis) and Finance and Econometrics at undergraduate level. Previous exposure to Matlab or R programming languages would be a plus. Course Aims, Learning Outcomes and Topics Covered: This quantitative equity research course focusses on understanding the main fundamental drivers of equity prices, the role of accounting information in capturing those fundamentals and the extent to which the equity market impounds this accounting information fully into stock prices. We will adopt a rigorous, research-based, approach towards understanding the existing sources of predictability in equity markets and use the same approach to refine existing and develop new fundamental-based trading strategies. The course is highly applied and students will be using real data from financial statements and stock prices to back-test and asses the performance of trading strategies. We will cover all aspects from trading strategy design, data collection, trading strategy back-testing and implementation using computers and state-of-the-art programming languages. This course will be of particular interest to those students thinking in developing their careers in quantitative equity research teams in sell-side investment banks or buy-side quantitative asset management firms. The course will also be useful for those students thinking in conducting academic research on fundamental analysis and stock return predictability. In terms of the learning outcomes, after successful completion of the course students should be able to: i. Describe the main fundamental drivers of stock prices within a Quantamental analysis framework ii. Apply their acquired Quantamental skills to analyse existing models of stock price behaviour and implement those models iii. Criticize existing and propose new models of stock market behaviour iv. Empirically test the proposed models of stock market behaviour and interpret the results from the empirical analysis v. Design and back test new quantitative equity trading strategies vi. Evaluate the economic significance and communicate the main findings of the back tested results. Some of the topics covered include: i. Financial Statements Analysis and Valuation; ii. Econometrics for Testing Rational Expectations; iii. Trading Strategies such as Earnings Momentum, Quality, Value, etc; iv. Introduction to Programming; 1

2 v. Data Collection and Analysis. Core Textbook: (i) Penman, Stephen H, Financial Statement Analysis and Security Valuation (2012). (ii) Zacks, Leonard (ed), The Handbook of Equity Market Anomalies: Translating Market Inefficiencies into Effective Investment Strategies (2011). Teaching Arrangements: Teaching arrangements consist of both lectures and classes. Formative Assessment: Format: Valuation Quiz Date: Friday 22 nd June Feedback/results due: Monday 25 th June Summative Assessments: The precise time and location of the examinations will be circulated during the programme. Format and weighting: Mid-session examination (50%) Date: Wednesday 27 th June Results due: Monday 2 nd July 2 Format and weighting: Two hour final examination (50%) Date: Friday 6 th July Results due: Within a week of the exam Schedule of Lectures and Classes (Provisional for 2018): Morning Afternoon Week 1 Monday 18 th June Lecture 1 Class 1 Tuesday 19 th June Lecture 2 Class 2 Wednesday 20 th June Lecture 3 Class 3 Thursday 21 st June Lecture 4 Class 4 Friday 22 nd June Lecture 5 Class 5

3 Week 2 Monday 25 th June Lecture 6 Class 6 Tuesday 26 th June Lecture 7 Class 7 Wednesday 27 th June Mid-session Exam* Thursday 28 th June Lecture 8 Class 8 Friday 29 th June Lecture 9 Class 9 Week 3 Monday 2 nd July Lecture 10 Class 10 Tuesday 3 rd July Lecture 11 Class 11 Wednesday 4 th July Lecture 12 Class 12 Thursday 5 th July No Lecture No Class Friday 6 th July Final Exam* *Exams may be scheduled at any time between 9am 5pm on these days. Detailed Course Outline Lecture 1. Introduction to Financial Statements Business Activities and Financial Statements; Reformulation of Financial Statements; The Articulation of Financial Statements and the Relationships Governing Them. Penman, Stephen H., "Financial statement analysis and security valuation." (5 th Edition, 2012). Chapters 2, 8, 9, 10 and Lecture 2. Pricing Book Values Prototype valuations. The price-to-book ratio (P/B). A model for anchoring value on book value. Penman, Stephen H., "Financial statement analysis and security valuation." (5 th Edition, 2012). Chapter 5. Lecture 3. Pricing Earnings The price-to-earnings ratio (P/E). Relation between P/B and P/E. Converting analysts forecasts to a valuation. The Fed Model. Penman, Stephen H., "Financial statement analysis and security valuation." (5 th Edition, 2012). Chapter 6. Lecture 4. Financial Statement Analysis Analysis of Profitability; Analysis of Growth and Sustainable Earnings.

4 Penman, Stephen H., "Financial statement analysis and security valuation." (5 th Edition, 2012). Chapters 12 and 13. Lecture 5. Statistical Tools Basic Regression Analysis; Regression Analysis and Forecasting; Regression Analysis diagnostics. Lecture 6. Tests of Market Efficiency Tests of Market Efficiency; Forecasting as the Key Principle in Fundamental Analysis; The role of Earnings Announcements to Understand How the Market Process Information; The Importance of an Alternative Hypothesis for Market Expectations about Firm Fundamentals; Introduction to Matlab. Mishkin, F. S. A rational expectations approach to macroeconometrics: testing policy ineffectiveness and efficient-markets models. University of Chicago Press (2007). Chapter 3. Lecture 7. Implementation Trading Strategies From Signal Extraction to Portfolio Construction and Strategy Returns; Portfolio Turnover; Trading Costs; Data Traps in Backtesting; Implementation of Trading Strategies using Matlab. Strategies (2011). Chapter 11. Lecture 8. Earnings Momentum Time-series Properties of Quarterly Earnings; Naïve Market Earnings Expectations About the Time-series Properties of Quarterly Earnings; Standardized Unexpected Earnings and Future Stock Returns; Delayed response to information or risk? Strategies (2011). Chapter 4. Bernard, Victor L., and Jacob K. Thomas. "Evidence that stock prices do not fully reflect the implications of current earnings for future earnings." Journal of Accounting and Economics 13, no. 4 (1990): Lecture 9. Accrual Anomaly (Quality Investing) Earnings components: accruals and cash-flows; Differential time-series properties of accruals and cash-flows; Naïve market earnings expectations about the time-series properties of accruals and cash-flows; Accruals and future stock returns; Earnings fixation or risk? Strategies (2011). Chapter 2. Sloan, Richard G. "Do stock prices fully reflect information in accruals and cash flows about future earnings?" The Accounting Review (1996): Lecture 10. Contrarian Investment and Naïve Extrapolation of Long-term Earnings Growth

5 Analysts Long-term Earnings Long-term Growth Forecasts; Investors Naive Reliance on Analysts Long-term Earnings Growth Forecasts; Long-term Earnings Growth Forecasts and Future Stock Returns; Returns to buying stocks with low prices relative to earnings, cash-flows or book-values. Dechow, Patricia M., and Richard G. Sloan. "Returns to contrarian investment strategies: Tests of naive expectations hypotheses." Journal of Financial Economics 43, no. 1 (1997): Lecture 11. Enhancing the Returns of Existing Trading Strategies: The Role of Fundamental Analysis Separating Winners from Losers among High Book-to-Market Stocks: the F-score; Separating Winners from Losers among Low Book-to-Market Stocks: the G-score; Piotroski, Joseph D. "Value investing: The use of historical financial statement information to separate winners from losers." Journal of Accounting Research (2000): Mohanram, Partha S. "Separating Winners from Losers among Low Book-to-Market Stocks using Financial Statement Analysis." Review of Accounting Studies 10, no. 2-3 (2005): Lecture 12. Extensions Combining Earnings Momentum and Accrual Anomaly; Revenue Surprises; Analysts Recommendations; Twitter and Earnings Announcement Returns; Macroeconomic News and Earnings Momentum; Frontiers in Quantitative Investment. Richardson, Scott, İrem Tuna, and Peter Wysocki. "Accounting anomalies and fundamental analysis: A review of recent research advances." Journal of Accounting and Economics 50, no. 2 (2010): Credit Transfer: If you are hoping to earn credit by taking this course, it is advisable that you confirm it is eligible for credit transfer well in advance of the start date. Please discuss this directly with your home institution or Study Abroad Advisor. As a guide, our LSE Summer School courses are typically eligible for three or four credits within the US system and 7.5 ECTS in Europe. Different institutions and countries can, and will, vary. You will receive a digital transcript and a printed certificate following your successful completion of the course in order to make arrangements for transfer of credit. If you have any queries, please direct them to summer.school@lse.ac.uk