Review of the Mayorov Alexey master thesis: 
“Research of indicative analysis and supervised machine 
learning methods for predicting stock quotes “.

In the thesis, different method for forecasting and prediction stock quotes are considered. The problem is relevant due to the fact that at all times a person strives to get maximum profit at minimum cost. So, it is with the stock price: how to predict the price in order to invest money on time or vice versa to sell. In many works, one can find the opinion that modeling and forecasting stock prices is a complex process and often not very rewarding. Sometime modeling gives us the prediction probability 0.5, like in tossing coin. But now, with the growth of computing power and the emergence of new forecasting algorithms using machine learning methods, there is hope for the possibility of obtaining a good forecast.
In the paper, the most popular technical analysis metrics were studied.  Intel and HP shares () are chosen for research. The data is taken from Yahoo Finance via yfinance python package. Regression, classification, and machine learning methods for predicting stock quotes were explored. Data were prepared for each of the methods. Machine learning and traditional technical analysis algorithms for predicting the price of stock quotes were implemented, and their performance was compared. 
Regression algorithms, classification algorithms (k-nearest neighbor, decision tree, Naive Bayes), machine learning methods (the LSTM algorithm using thinning and without thinning) are considered and applied. After that all the quality of the models is checked and the best one is selected, using MSE and MAE.
In the process of studying and writing the final qualifying work, Alexey Mayorov's showed high diligence. It is worth noting the high degree of independence of Alexey's research.
The research topic is relevant and important, the structure and content of the dissertation correspond to the stated topic. The work is accompanied by tables and graphs of constructed models in Python, and forecasts, which confirms the master's qualification in the application of modern methods of data analysis and possession of computer technology.

The results of the work meet the requirements for the master's final qualifying work, and Alexey Mayorov's work can be evaluated with an excellent grade.
 
Scientific supervisor, 
Associated Professor, 
Yaroslavna Pankratova