Fundamental Analysis

Contrasting the efficiency of stock price prediction models using various types of LSTM models aided with sentiment analysis ArXiv ID: 2307.07868 “View on arXiv” Authors: Unknown Abstract Our research aims to find the best model that uses companies projections and sector performances and how the given company fares accordingly to correctly predict equity share prices for both short and long term goals. Keywords: Equity prediction, Sector performance, Fundamental analysis, Projection modeling, Equities ...

Higher-order Graph Attention Network for Stock Selection with Joint Analysis ArXiv ID: 2306.15526 “View on arXiv” Authors: Unknown Abstract Stock selection is important for investors to construct profitable portfolios. Graph neural networks (GNNs) are increasingly attracting researchers for stock prediction due to their strong ability of relation modelling and generalisation. However, the existing GNN methods only focus on simple pairwise stock relation and do not capture complex higher-order structures modelling relations more than two nodes. In addition, they only consider factors of technical analysis and overlook factors of fundamental analysis that can affect the stock trend significantly. Motivated by them, we propose higher-order graph attention network with joint analysis (H-GAT). H-GAT is able to capture higher-order structures and jointly incorporate factors of fundamental analysis with factors of technical analysis. Specifically, the sequential layer of H-GAT take both types of factors as the input of a long-short term memory model. The relation embedding layer of H-GAT constructs a higher-order graph and learn node embedding with GAT. We then predict the ranks of stock return. Extensive experiments demonstrate the superiority of our H-GAT method on the profitability test and Sharp ratio over both NSDAQ and NYSE datasets ...

Financial Analysis of Tesla ArXiv ID: ssrn-3896901 “View on arXiv” Authors: Unknown Abstract This study has done based on the financial analysis of Tesla, inc. to understand its financial position throughout the year 2017 to 2020. The fundamental purpos Keywords: Financial analysis, Tesla, Financial position, Fundamental analysis, Valuation Complexity vs Empirical Score Math Complexity: 1.0/10 Empirical Rigor: 3.0/10 Quadrant: Street Traders Why: The paper employs basic financial ratios (e.g., current ratio, ROE) with no advanced mathematical derivations, but it uses real historical financial data from Yahoo Finance to compute metrics, making it more data-driven than theoretical. flowchart TD A["Research Goal<br>Assess Tesla's Financial Position<br>2017-2020"] --> B["Methodology<br>Fundamental Analysis"] B --> C["Data Sources<br>Annual Financial Statements"] C --> D["Computation<br>Ratios & Valuation Metrics"] D --> E["Key Findings<br>Growth Trajectory & Profitability"]

Theoretical Review of the Role of Financial Ratios ArXiv ID: ssrn-3472673 “View on arXiv” Authors: Unknown Abstract Purpose – Financial ratios are an instrumental tool in the world of finance and hence comprehensive knowledge of its various aspects is mandated for its user. T Keywords: Financial Ratios, Fundamental Analysis, Credit Risk, Financial Statement Analysis, Solvency, Fixed Income Complexity vs Empirical Score Math Complexity: 2.0/10 Empirical Rigor: 1.0/10 Quadrant: Philosophers Why: The paper is a qualitative literature review that discusses historical concepts and applications of financial ratios without presenting novel mathematical derivations, statistical models, or backtesting results. flowchart TD A["Research Goal:<br>Review Financial Ratios' Theoretical Role"] --> B["Key Methodology:<br>Theoretical Review & Analysis"] B --> C["Data/Inputs:<br>Finance Literature & Financial Statements"] C --> D["Computational Processes:<br>Ratio Calculation & Fundamental Analysis"] D --> E["Key Outcomes:<br>Credit Risk, Solvency & Fixed Income Assessment"]