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Methodological and Empirical Advances in Financial Analysis (MEAFA) Workshop on Quantitative Analysis Using Stata

Venue: University of Sydney
Sydney, Australia
Dates: June 24–28, 2013

MEAFA designs and provides advanced quantitative research training to academia, industry, and government. MEAFA’s professional development workshops in quantitative analysis keep members updated with the latest develoment in quantitative analysis. Their workshops are widely recognized by industry, government, and academia for their state-of- the-art content. To date, more than 430 participants have attended MEAFA’s workshops.

Topics includes Structurual equation modeling, Working efficiently with Stata, Management of raw data, and Data visualization. You may attend any one or any combination of the following days. Days 4–5 on SEM are packaged together.

Monday, June 24:

Working efficiently with Stata by Demetris Christodoulou, MEAFA General Convener

This day assumes no previous knowledge of Stata 12. It describes the environment of Stata and covers the core syntactic features and demonstrates ways of working efficiently with Stata, including the use of logs and do-files. It presents the programming principles and tools for constructing code that is automated, reproducible, tractable, and verifiable. It demonstrates the access to saved results and the use of macros, loops, and conditional statements. The day will benefit those who are new to Stata or have limited experience with Stata 12. It will also benefit more experienced users who wish to attain a more structural understanding of Stata from first principles. The material has been revamped from previous years.

Tuesday, June 25:

Management of raw data by Demetris Christodoulou, MEAFA General Convener

This day assumes a working knowledge of Stata and basic programming skills. If you have no or limited experience with Stata 12, then you are strongly advised to attend Day 1 first. The day shows how to import and export different data formats. It demonstrates the management of various types of data, including numerical variables, string variables, and date and time variables, and the implications of missing values. It explores key data structures, including cross-sectional, time-series, and panel data in long and wide formats. It covers the management of data attributes, the organization of data and the critical importance of metadata and demonstrates strategies for working efficiently with very large datasets. Dataset organization, archiving, combinations, and transformations will also be discussed.

Wednesday, June 26:

Data visualization by Demetris Christodoulou, MEAFA General Convener

This day assumes a working knowledge of Stata but no knowledge of data visualization with Stata or any other software. The day provides an in-depth analysis of Stata's graphing logic and shows how to make sense of its vast graph syntax. Graphing examples will be demonstrated for a variety of data structures, using real data or simulated data. Demonstrations will include the contrast of theoretical with empirical probability densities, y-x relationships, parametric and nonparametric fits, advanced bar charts and box plots, and more. By the end of this day, you should be able to produce informative, robust, flexible, and beautiful graphs using reproducible and adaptable routines. If you have no or limited experience with Stata, then you are strongly advised to attend Day 1 first. Data management elements from Day 2 will also be used. The material has been revamped from previous years.

Thursday–Friday, June 27–28:

Structural equation modeling (SEM) by Kristin MacDonald, Senior Statistician, StataCorp

These two days assume a working experience with Stata and reasonable knowledge of statistics. Structural equation modeling (SEM) is a statistical methodology for formulating and estimating causal relationships of all sorts. SEM is an alternative way of thinking, formulating, and estimating simple and complex cause-and-effect models, from simple linear regressions and instrumental variable models to measurement models, systems of simultaneous equations, confirmatory factor analysis, correlated uniqueness models, latent growth models, and much more. SEM will be demonstrated using a variety of applications across disciplines. If you have no or little experience with Stata 12, then you are advised to attend at least Day 1. See the StataCorp website for a detailed description of SEM, an application, and the complete list of SEM capabilities.

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