Election Portfolios

Stocks

We have stopped updating stock data on the Friday before the election (2020-10-30), according to our research results in the JBF (2020) paper.

Note

This page shows the gains a potential investor would have earned by investing into our 'Political Event Portfolios' (formed using S&P500 stocks), given a correct anticipation of ... winning the US presidential election 2020. We show a performance graph starting on the day after the election (2020-11-04) and selected portfolio statistics for the percentile portfolio and the weighting method selected below. Our results are based on election association statistics that are calculated on-the-fly for the time window in the sidebar ('Calculation Date'). Therefore, it may take a couple of seconds until the output is shown.

Note

This page shows the top 10 stocks that can be associated with either the Democratic (Joe Biden) or the Republican (Donald Trump) candidate winning the US presidential election 2020. Calculations follow the methodology of Hanke, Stöckl and Weissensteiner (2020) - more details can be found in the 'Methodology'-section of this website. Our results are computed on-the-fly for the time window in the sidebar ('Calculation Date'). Therefore, it may take a couple of seconds until the output is shown. The dropdown below allows to choose the top ten Democrat/Republican stocks based on the level of significance implied by our statistical method.

Note

This page highlights how much a potential investor could have earned by investing into our 'Political Event Portfolios', given a correct anticipation of the changes in the betting odds for the Democrat/Republican candidate winning the US presidential election 2020. The graph can be seen as proof/backtest about how well our method works. For more details please refer to the 'Methodology'-section of this website. Our results are based on election association statistics that are calculated from recursively growing windows and therefore pre-computed and fixed since 2020-01-02. Changing the the time window in the sidebar ('Calculation Date') will only change the numbers and graphics provided on the right/below but not the associated statistics of every stock on each day. The dropdowns below allow to select the weighting scheme for the portfolios as well as the number of assets contained within the sorted portfolios.

Note

This page gives an indication on the stability of the association with either the Democrat or Republican party in the run-up to the US presidential election 2020, as given by Hanke, Stöckl and Weissensteiner (2020). The graphs on the right show the development of the rank within the top 5 Democrat/Republican stocks over time. Ranks get more stable due to the recursively growing estimation window and are therefore pre-computed and fixed since 2020-01-02. Changing the the time window in the sidebar ('Calculation Date') will only change the graphics provided on the right/below but not the associated statistics of every stock on each day.

Note

This page shows all the stocks within a certain industry (can be selected below) that can be associated with either the Democratic (Joe Biden) or the Republican (Donald Trump) candidate winning the US presidential election 2020. Calculations follow the methodology of Hanke, Stöckl and Weissensteiner (2020) - more details can be found in the 'Methodology'-section of this website. Our results are computed on-the-fly for the time window in the sidebar ('Calculation Date'). Therefore, it may take a couple of seconds until the output is shown. The dropdown below allows to select the industry.

Note

On this page we provide raw data (Stock Identifier (Type), Stock Name, Ticker Symbol, Industry (Thomson Reuters Business Sector), Political Event association (theta, relative to Republican Betting Odd Changes, see section 'Methodology') and the corresponding significance level) for all stocks in the S&P500 as of 2020-01-01. On the top right hand corner one can search for specific companies. On the left bottom corner the entire dataset can be downloaded.

Election Portfolios

Indices

We have stopped updating stock data on the Friday before the election (2020-10-30), according to our research results in the JBF (2020) paper.

Note

This page shows the gains a potential investor would have earned by investing into our 'Political Event Portfolios' (formed using sector indices), given a correct anticipation of ... winning the US presidential election 2020. We show a performance graph starting on the day after the election (2020-11-04) and selected portfolio statistics for the percentile portfolio and the weighting method selected below. Our results are based on election association statistics that are calculated on-the-fly for the time window in the sidebar ('Calculation Date'). Therefore, it may take a couple of seconds until the output is shown.

Note

This page shows the top 10 indices (a variety of market, industry and style indices as well as commodities and exchange rates from various providers - mainly S&P and Thomson Reuters/Refinitiv) that can be associated with either the Democratic (Joe Biden) or the Republican (Donald Trump) candidate winning the US presidential election 2020. Calculations follow the methodology of Hanke, Stöckl and Weissensteiner (2020) - more details can be found in the 'Methodology'-section of this website. Our results are computed on-the-fly for the time window in the sidebar ('Calculation Date'). Therefore, it may take a couple of seconds until the output is shown. The dropdown below allows to choose the top ten Democrat/Republican indices based on the level of significance implied by our statistical method.

Note

The results on the right/below highlight how much a potential investor could have earned by investing into a 'Political Event Portfolio' combined from all given indices, based on a correct anticipation of the changes in the betting odds for the Democrat/Republican candidate winning the US presidential election 2020. The graph can be seen as proof/backtest about how well our method works. For more details please refer to the 'Methodology'-section of this website. Our results are based on election association statistics that are calculated from recursively growing windows and therefore pre-computed and fixed since 2020-01-02. Changing the the time window in the sidebar ('Calculation Date') will only change the numbers and graphics provided on the right/below but not the associated statistics of every stock on each day. The dropdowns below allow to select the weighting scheme for the portfolios as well as the number of assets contained within the sorted portfolios.

Note

The results on the right/below give an indication on the stability of the association with either the Democrat or Republican party in the run-up to the US presidential election 2020, as given by Hanke, Stöckl and Weissensteiner (2020). The graphs on the right show the development of the rank within the top 5 Democrat/Republican indices over time. Ranks get more stable due to the recursively growing estimation window and therefore pre-computed and fixed since 2020-01-02. Changing the the time window selected in the sidebar on the left ('Calculation Date') will only change the graphics provided on the right/below but not the associated statistics of every index on each day.

Note

The results on the right/below show all the stocks within a certain category (can be selected below) that can be associated with either the Democratic (Joe Biden) or the Republican (Donald Trump) candidate winning the US presidential election 2020. Calculations follow the methodology of Hanke, Stöckl and Weissensteiner (2020) - more details can be found in the 'Methodology'-section of this website. Our results are computed on-the-fly for the time window selected in the sidebar on the left ('Calculation Date'). Therefore, it may take a couple of seconds until the output is shown. The dropdown below allows to select the industry.

Note

On the right/below, we show raw data (Index Name, Index Category, Political Event association (theta, relative to Republican Betting Odd Changes, see section 'Methodology') and the corresponding significance level) for all indices in our database. On the top right hand corner one can search for specific companies. On the left bottom corner the entire dataset can be downloaded.

Election Portfolios

Funds

We have stopped updating stock data on the Friday before the election (2020-10-30), according to our research results in the JBF (2020) paper.

Note

This page shows the gains a potential investor would have earned by investing into our 'Political Event Portfolios' (formed using US equity funds), given a correct anticipation of ... winning the US presidential election 2020. We show a performance graph starting on the day after the election (2020-11-04) and selected portfolio statistics for the percentile portfolio and the weighting method selected below. Our results are based on election association statistics that are calculated on-the-fly for the time window in the sidebar ('Calculation Date'). Therefore, it may take a couple of seconds until the output is shown.

Note

This page shows the top 10 investment funds (US equity based on Lipper classification) that can be associated with either the Democratic (Joe Biden) or the Republican (Donald Trump) candidate winning the US presidential election 2020. Calculations follow the methodology of Hanke, Stöckl and Weissensteiner (2020) - more details can be found in the 'Methodology'-section of this website. Our results are computed on-the-fly for the time window selected in the sidebar on the left ('Calculation Date'). Therefore, it may take a couple of seconds until the output is shown. The dropdown below allows to choose the top ten Democrat/Republican funds based on the level of significance implied by our statistical method.

Note

Tis page highlights how much a potential investor could have earned by investing into a 'Political Event Portfolio' combined from all given funds, based on a correct anticipation of the changes in the betting odds for the Democrat/Republican candidate winning the US presidential election 2020. The graph can be seen as proof/backtest about how well our method works. For more details please refer to the 'Methodology'-section of this website. Our results are based on election association statistics that are calculated from recursively growing windows and therefore pre-computed and fixed since 2020-01-02. Changing the the time window selected in the sidebar on the left ('Calculation Date') will only change the numbers and graphics provided on the right/below but not the associated statistics of every stock on each day. The dropdowns below allow to select the weighting scheme for the portfolios as well as the number of assets contained within the sorted portfolios.

Note

Here we give an indication on the stability of the association with either the Democrat or Republican party in the run-up to the US presidential election 2020, as given by Hanke, Stöckl and Weissensteiner (2020). The graphs on the right show the development of the rank within the top 5 Democrat/Republican funds over time. Ranks get more stable due to the recursively growing estimation window and therefore pre-computed and fixed since 2020-01-02. Changing the the time window selected in the sidebar on the left ('Calculation Date') will only change the graphics provided on the right/below but not the associated statistics of every index on each day.

Note

On this page we show raw data (Lipper Code, Fund Name, ISIN, Political Event association (theta, relative to Republican Betting Odd Changes, see section 'Methodology') and the corresponding significance level) for all funds in our database. On the top right hand corner one can search for specific companies. On the left bottom corner the entire dataset can be downloaded.

Election Portfolios

About us

Michael Hanke

Prof. Dr. Michael Hanke received his doctoral degree and habilitation from WU (Vienna), and is a Certified Financial Risk Manager (FRM). His research interests are in quantitative finance, exchange rates, stochastic optimization, scenario generation, and pension finance. He has published in leading finance, economics and operations research journals. He is chairman of the board of a pension fund and a board member of two fund management companies.

Sebastian Stöckl

Dr. Sebastian Stöckl is an Assistant Professor at the Chair in Finance at the University of Liechtenstein. He received his Ph.D. in Economics from the University of Innsbruck and is also the holder of two graduate degrees in Business Administration and Technical Mathematics, both also from the University of Innsbruck. His research interest covers all areas of uncertainty, e.g. (i) parameter uncertainty, (ii) financial uncertainty, (iii) macroeconomic uncertainty (also check the corresponding shiny app ) and (iv) political uncertainty and he has published several papers on these topics in Finance and Economics Journals.

Alex Weissensteiner

Prof. Alex Weissensteiner is Professor for Quantitative Finance at the Faculty of Economics and Management at the Free University of Bozen-Bolzano. He holds a Ph.D. from the Leopold-Franzens University Innsbruck, and he was Professor for Financial Engineering at the Technical University of Denmark (2013-2014). At the Free University of Bozen-Bolzano, he was Coordinator of the Quality Committee (2016-2020), Vice-Dean Teaching (2018-2020) and Program Director of the BSc 'Economics and Management' (2015-2020). He is teaching courses as Mathematical Finance, Financial Risk Management and Quantitative Finance. His research interests are in the fields of asset allocation, theoretical and empirical asset pricing. He published in leading outlets as, e.g., the Journal of Financial and Quantitative Analysis, the Journal of Financial Markets and the Journal of Banking and Finance.