Implementacija trgovalne strategije za zajem dividend

MOHORIČ, ANDREJ (author), Lavbič, Dejan (mentor)

V diplomski nalogi smo raziskovali področje trgovanja s strategijo za zajem dividend. Razvita je bila tudi informacijska rešitev, kjer so prikazani rezultati analize za več kot 3000 ameriških podjetij. V analizi smo zajeli podatke od leta 2010 do leta 2021. Spletna aplikacija uporabniku svetuje, katera podjetja so primerna za izvedbo strategije za zajem dividend in prikaže kdaj približno, glede na zgodovinske podatke, bo določeno podjetje ponovno izdalo dividende. Podatke delnic smo analizirali z orodjem Jupyter Notebook, za prikaz analiziranih podatkov pa smo uporabili spletno platformo Anvil. Pri analizi podatkov v Jupyter Notebooku smo podatke shranili v platformi Clever Cloud, ki omogoča rabo lastne podatkovne baze MySql. Strategijo za zajem dividend smo glede na analizo podjetij simulirali od leta 2010 do 2021, kjer smo kupovali delnice podjetij, ki so imela v zgodovini najboljše rezultate. Rezultate smo primerjalli s kriptovaluto Bitcoin, indeksom S\&P 500 in delnicami podjetij Amazon in Google. To smo naredili s kazalci Sharp Ratio, Sortino Ratio, največji padec in Calmar Ratio. Kazalci ovrednotenja strategije, glede na druge finančnimi inštrumenti, jasno kažejo, da je strategija dosegla povprečne rezultate, saj pri nobenem kazalcu ni dosegla najboljših rezultatov in prav tako ne najslabših. Rezultate smo s pomočjo knjižnic Python tudi grafično prikazali.

• Language: Slovenian
• Keywords: Strategija za zajem dividend, trgovanje, dividende, analiza, Jupyter Notebook, Anvil, Clever Cloud, MySql
• Work type: Bachelor thesis/paper
• Typology: 2.11 - Undergraduate Thesis
• Organization: FRI - Faculty of Computer and Information Science
• Year: 2021
• PID: 20.500.12556/RUL-128913
• COBISS.SI-ID: 75072771
• Publication date in RUL: 16.08.2021

Secondary language

• Language: English
• Title: Implementation of dividend capture strategy

Abstract

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.

• Keywords: Dividend capture strategy, trading, dividends, analysis, Jupyter Notebook, Anvil, Clever Cloud, MySql