In our bachelor degree, we researched the field of trading with a dividend capture strategy. An information solution was also developed, showing the results of the analysis for more than 3,000 American companies. The analysis covered data from 2010 to 2021. The web application advises the user which companies are suitable for performing a dividend capture strategy and it shows when approximately, according to historical data, a particular company will declare its dividends again.
We analyzed the stock data in the Jupyter Notebook tool, and used the Anvil online platform to display the analyzed data. When analyzing the data in the Jupyter Notebook, we stored the data in the Clever Cloud platform, which allowed us to use the MySql database. Based on the analysis of the companies, we simulated the strategy for capturing dividends from 2010 to 2021, where we only bought shares of companies that had the best results in history. We compared the results to the cryptocurrency Bitcoin, the S\&P 500 index, and shares of Amazon and Google. We evaluate strategy with the Sharp Ratio, Sortino Ratio, Maximum Withdrawal and Calmar Ratio pointers. Evaluation indicators show that the strategy is more effective than other financial instruments. We also graphically displayed the results using Python libraries.
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