MEAFA workshop on Quantitative Analysis using Stata, 11 - 15 Feb 2013

Announcements

11 Feb 2013: Survey Design and Analysis Services LP, the official distributor of Stata products in Australia and New Zealand, offers 20% off new single-user Stata licenses and up to 20% off Stata Press books for the participants of this course. For questions about this discount contact Survey Design and Analysis Services: phone (03)9878 7373 or email sales@survey-design.com.au

11 Dec 2012: The workshop is now open for reservations. Places are limited and are reserved on a first-come first-served basis following the completion of the online Reservation Form.

Brief workshop description

You may attend any one day or any combination of the following days:

Day 1 (Monday, 11 February 2013): Working efficiently with Stata and data management by Demetris Christodoulou, MEAFA General Convenor

This day assumes no previous knowledge of Stata 12. It demonstrates ways to work efficiently with the software with a focus on reproduction and validation. It shows how to personalise the working environment, handle different data structures and analyse various types of variables efficiently. Logs, output management and basic tables will also be discussed. This day is of interest to those who are new to Stata or have limited experience with Stata 12.

Day 2 (Tuesday, 12 February 2013): Programming by Demetris Christodoulou, MEAFA General Convenor

This day assumes working knowledge of Stata but no knowledge of programming with Stata or any other software. By the end of this day you will be able to produce efficient, tractable and automated routines for data management, statistical analysis, econometric estimation, creation of tables and more. This day is appropriate to those who wish to attain a deeper knowledge of Stata and achieve the aforementioned attributes in their work. If you have no or limited experience with Stata 12 then you are advised to attend Day 1 first.

Day 3 (Wednesday, 13 February 2013): Time-series analysis and forecasting by Richard Gerlach, MEAFA Quant Analysis Convenor

This day assumes working knowledge of Stata and basic knowledge of statistics and econometrics, but assumes zero knowledge of time-series analysis. This is an application-driven day that details the advantages and limitations of univariate time series analysis and how it leads to forecasting. This day is of interest to those who wish to learn how to model and analyse univariate time series structures using Stata. Detailed notes on theory will be provided as background reading. If you have no or limited experience with Stata 12 then you are advised to attend Day 1 first.

Day 4 (Thursday, 14 February 2013): Monte Carlo simulation by Demetris Christodoulou, MEAFA General Convenor

This day assumes good knowledge of Stata and reasonable knowledge of statistics. Monte Carlo (MC) simulation describes the process of generating repeated random sampling for imitating real situations through the use of reasonable probabilistic assumptions. MC simulation is most appropriate for evaluating complex deterministic formulations that are characterised by significant uncertainty. The principles of MC simulation will be demonstrated through a wide variety of applications from statistics, econometrics, business, health and other areas. If you have no experience with Stata 12 then you are advised to attend Day 1. A number of programming tools will be used so you may also wish to attend Day 2.

Day 5 (Friday, 15 February 2013): Event study methodology by Demetris Christodoulou, MEAFA General Convenor

This day assumes financial background, good knowledge of Stata and reasonable knowledge of statistics and econometrics. Event studies examine the market reaction in response to new value-relevant information. Event studies can be used to examine the market valuation of security-specific events such as earnings upgrades or equity transactions, as well as economy-wide events such as industry subsidies, election results or natural disasters. This day will demonstrate ways to model and analyse event studies, visualise market reaction and measure abnormal returns of a security or a pool or securities. If you have no experience with Stata 12 then you are advised to attend both Days 1 and 2 first (programming tools will be used extensively).

Enrollment and Fees

You may attend any one day or any combination of days. The cost for attending is $600 per day.

Fees include extensive course material, do-files and data sets, use of computing facilities, temporary use of Stata 12 licenses and full catering. Numbers are limited and places are reserved on a first-come first-served basis following the completion of the online Reservation Form. Successful attendees will be notified shortly after reservation and invoices will be issued accordingly. Due to the limited places, MEAFA maintains a no refund policy following payment. For more information on enrollment and fees contact business.meafa@sydney.edu.au.

N.B. Proceedings from the workshop go to funding MEAFA PhD scholarships.

Discounts

You may qualify for one of the following discounts:

  • 30% discount for a restricted number of non-employed full-time PhD students.
  • 15% discount for additional attendees from the same business organisation, governmental department or academic unit.

Venue and computing facilities

The workshop will take place at the computer labs of The University of Sydney Business School, ground level of Building H69, cnr Codrington & Rose streets (see interactive map).

PCs and Stata 12 licenses for Microsoft Windows will be provided onsite. You can also install a temporary one-month Stata 12 license on your own laptop and work from there but to do that make sure to arrive early to install the license.

Timetable

All days have the same schedule (catering provided throughout the day):

  • 08:40-09:00 - Welcome tea and coffee
    09:00-10:30 - Session 1
  • 10:30-10:45 - Morning break
    10:45-12:15 - Session 2
  • 12:15-13:15 - Lunch
    13:15-14:45 - Session 3
  • 14:45-15:00 - Afternoon break
    15:00-16:30 - Session 4
  • 16:30-17:00 - Buffer-time and user-specific questions

The computer labs will be accessible from 8am to 6pm every day.

Detailed Programme

Day 1 (Monday, 11 February 2013): Working efficiently with Stata 12 and Data Management

Session 1: The Stata environment
The Stata environment; configuration; special features; updates; personalised system; obtain help and perform search; language and Stata syntax; working with do-files.
Session 2: Data management fundamentals
Data formats; import and export delimited data; manually input data; data management; variable attributes; reviewing and documenting the dataset; metadata; formatting; storage precision.
Session 3: Variable types
Categorical vs. continuous data; numerical, string and date/time variables; missing data; dummy variables; special purpose variables.
Session 4: Output management and special features
Logs; tables; export output; statistical and estimation commands; prefixes; suffixes; dataset combinations including append and merge.

Day 2 (Tuesday, 12 February 2013): Programming

Session 1: Programming fundamentals
Properly structured do-files; comments; -do- vs. -run-; -quietly- vs. -noisily-; -preserve- and -restore-; accessing Stata parameters and Stata constants; self-contained do-files.
Session 2: Macros
Macro types; macro operations; counters; compound punctuation; macro expansion; macro evaluation; formatting macro output; nested macros.
Session 3: Special features of macros and loops
Incrementing/decrementing macros; combining incrementation with evaluation; preventing macro expansion; foreach loop; forvalues loop; nested loops; the -if- programming command.
Session 4: Automating routines
Capturing saved results; macro evaluation with saved results; scalars and precision; creating tables using stored results; the commands -file- and -postfile-; user-written tables; explicit subscripting.

Day 3 (Wednesday, 13 February 2013): Time-series analysis and forecasting

Session 1: Introduction to forecasting and time series
Why forecast?; Stata time series structure; describing, graphing time series; smoothing and time series components; data transformations; exponential smoothing and forecasting; forecast accuracy; stationarity; auto-correlation and ACF plots.
Session 2: Time series modelling and forecasting
The autoregressive process (AR); the moving average process (MA); ARMA processes; time series regression; Holt-Winters for trends; seasonal Holt-Winters.
Session 3: Integrated and seasonal Box-Jenkins models
Trends and integration; ARIMA processes; detecting trends and/or mean non-stationarity; ARIMA model forecast behaviour; Seasonal ARIMA models; pure additive and factored models; models for outliers, level shifts and other interventions.
Session 4: Time series regression and volatility modelling
Advanced time series regression; distributed lag models; conditional heteroskedasticity (CH); ARCH and Generalised ARCH processes (GARCH); Value-at-Risk.

Day 4 (Thursday, 14 February 2013): Monte Carlo (MC) simulation

Session 1: MC Simulation fundamentals
What is MC simulation; Stata set-up parameters; initialisation seed; the Uniform distribution; first principle distributions (Triangular, Bernouli, Binomial, Normal); stable distributions; the command -simulate-.
Session 2: Evaluation
The Law of Large Numbers; the Central Limit Theorem; improving accuracy and convergence; the costs and benefits of increasing the number of repetitions; variance reduction techniques; computing integrals.
Session 3: Distributions
Distribution types; deterministic and stochastic input; historical vs. theory input; distribution families; multivariate distributions; correlated structures.
Session 4: Applications
Simulating regression misspecifications (endogeneity, omitted variables, non-Normal errors, outliers etc); simulating the size and power of tests; time series simulation; panel data simulation.

Day 5 (Friday, 15 February 2013): Event study methodology

Session 1: Event study fundamentals
Market efficiency; data requirements; security-specific event studies; group event studies; event study timeline; event window specification; estimation window specification.
Session 2: Empirical considerations
Event contamination; shifting event dates; merging data sources; thin trading; standardization and validation of event timelines; visualisation of price movement; calculation of observed returns.
Session 3: Abnormal returns
Constant mean return; market-adjusted return; matching return; market model; CAPM model; analysis of estimated parameters; multi-factor models; analysis of IID abnormal returns; cumulative abnormal returns; buy-and hold abnormal returns.
Session 4: Analysis of non-IID abnormal returns
Non-identical distribution; non-independent distribution; event-induced variance; generalised sign test; rank test; additional analysis.

N.B. The precise content is subject to fine-tuning.

Reservation Form

Numbers are limited and places are reserved on a first-come first-served basis following the completion of the Reservation Form.