Transformations  in
Business & Economics

INVESTIGATION OF ALGORITHMIC TRADING MODELS FOR SHARES OF THE DRUG MANUFACTURING INDUSTRY
Nijole Maknickiene, Raimonda Martinkute-Kauliene, Viktorija Stasytyte

ABSTRACT: Algorithmic trading models are now widely used in investment decision-making. By grounding these models in scientific knowledge, investors can obtain efficient results in financial markets. During the COVID-19 outbreak, the drug manufacturing industry has received substantial attention from investors. The purpose of our research is to form an investment portfolio using an algorithmic trading model in the drug manufacturing industry. The model covers the entire process of portfolio formation: market analysis, selection of industry, selection of particular stocks, data mining, forecasting and investment decision-making. Three portfolios - maximum return, minimum risk and maximum Sharpe ratio - are constructed and compared across two periods. Portfolios formed using deep learning forecasting outperformed the index in more cases than did portfolios created using the Monte Carlo simulation. Portfolio formation using algorithmic trading models is suitable for individual investors, can be easily automated using the computer application and can not only be applied to one industry but diversified across various sectors.

KEYWORDS:  investment portfolio, algorithmic trading model, deep learning forecasting, drug manufacturing industry.

JEL classification:  C6, G1.