|Venue:||University of Sydney
|Dates:||February 11–15, 2013|
You may attend any one or any combination of the following days:
Monday, February 11:
Working efficiently with Stata and data management by Demetris Christodoulou, MEAFA General Convener
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 personalize the working environment, handle different data structures, and analyze 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.
Tuesday, February 12:
Programming by Demetris Christodoulou, MEAFA General Convener
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.
Wednesday, February 13:
Time-series analysis and forecasting by Richard Gerlach, MEAFA Quant Analysis Convener
This day assumes working knowledge of Stata and basic knowledge of statistics and econometrics but assumes no 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 analyze 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.
Thursday, February 14:
Monte Carlo simulation by Richard Gerlach, MEAFA Quant Analysis Convener, and Demetris Christodoulou, MEAFA General Convener
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 characterized by significant uncertainty. The principles of MC simulation will be demonstrated through a wide variety of applications from statistics, econo metrics, 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.
Friday, February 15:
Event study methodology by Demetris Christodoulou, MEAFA General Convener
This day assumes a 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 analyze event studies, visualize market reaction, and measure abnormal returns of a security or a pool of securities. If you have no experience with Stata 12, then you are advised to attend both Day 1 and Day 2 first (programming tools will be used extensively).
For more information, including a detailed program, or to register, visit sydney.edu.au/business/research/meafa/activities/pdworkshop/2013.