AMIS 2020 :: Structured abstract

AMIS 2020 Conference Structured Abstracts: Written Abstracts as a 'mini pitch'

Structured Abstract Design: AMIS 2020 submitters are invited to prepare a written 'mini-pitch' of their research paper by using the 6 core elements of Faff’s (2016) template tool, with a maximum total of 250 words. These abstracts will appear in the AMIS conference booklet.

Idea?	Identify the 'core' idea that drives the intellectual content of this research topic. If appropriate: articulate the central hypothesis/prediction/proposition identify the key dependent ('explained') variable and the key test/independent ('explanatory') variable(s).
Data?	Make a brief statement about the data/sampling used in the study. For example: What data are used? e.g. country/setting; Unit of analysis? sample period; sampling interval? Type of data: firm specific vs. industry vs. macro vs. …? What is the sample size? Cross-sectionally? Time-series/longitudinal? Is it a panel dataset? Data Sources? Are the data commercially available? Any hand-collecting required? Are the data created based on authors own survey instrument? Or by interviews? Are there any problems with missing data/observations? Other data obstacles?
Tools?	State the basic empirical framework and research design. Is it a regression model approach? Survey instrument design? Interview design?
What's New?	What is really new about your study? Briefly state (up to) three key findings of the study.
So What?	Why is it important to know the answer? How will major decisions/behaviour/activity etc be influenced by the outcome of this research? What is the economic significance of the findings?
Contribution?	What is the primary essence of the contribution to the relevant research literature?

EXAMPLE of Written Abstract

Do Stock Markets Catch the Flu?

Presenting Author: McTier, B., Washington State University

Idea: To examine the impacts of influenza on the NYSE using different stock market performance measures.

Data: Time Series for national effects and Panel data for international flu effects Data Frequency: Weekly; Country: US. Sources: Publicly available e.g. Centers for Disease Control and Prevention (CDC), Google Flu Trends, TAQ data. Variables: Stock returns, Bid-ask spreads, Market Volume, New York flu cases, US flu cases, Global flue cases, Volatility, SAD onset and Dummy variables of Cloud cover.

Tools: Regression Analysis (Index Portfolio regression and Panel regression). Software: Being regression analysis, software like SPSS, EVIEWS, STATA are capable of estimating the model.

What’s new: Three key findings: (1) Influenza negatively affects the NYSE in terms of Dollar volume, number of trades, turnover. (2) Increase in flu incidence is related to the lower volatility but high Bid-Ask spreads due to less information production. (3) Volume and volatility effects are more closely tied to New York flu incidence (local), with bid-ask spreads and returns more strongly associated with the US (national) flu incidence whereas for international markets flu is negatively related to trading activity and returns.

So what: Investors are able to predict the stock market performance w.r.t incidence of influenza both nationally or internationally. The inclusion of cloud-cover in the model also enables investors to predict the performance of the markets.

Contribution: Providing a mechanism to capture the effects of influenza incidence (local, national and international) on the stock market using different measures of performance.

You can also download the above information in the document here

The following important dates also have to be taken into account:

• Sunday, July 26, 2020 - Extended deadline for the submission of full papers
• Sunday, August 16, 2020 - Deadline for the notification of full paper acceptance
• Sunday, September 20, 2020 - Deadline for registration