By comparing a company’s stock price to its intrinsic value, equity research analysts can determine whether it is undervalued or overvalued. Once all of this research and analysis is complete, equity research analysts must write reports and make client recommendations. These reports typically include detailed information about the analyzed company or industry and the analyst’s recommendations for buying, holding, or selling the stock. Their responsibilities include conducting industry research, assessing company financial statements, conducting valuation analyses, and making client recommendations. By providing investors with valuable insights and information, equity research analysts help them make informed investment decisions. Understanding and projecting financial statements is a cornerstone of financial modeling, serving as the bedrock upon which all further analysis is built.

Discounted Cash Flow (DCF) Model

Equity research involves conducting, analyzing and disseminating research about stocks and different companies, improving the investment decision-making process. On the other hand, financial modeling involves the development of a representation of relationship between financial variables, and being used for forecasting, budgeting and evaluation of financial outcomes. In conclusion, Equity research and financial modeling are two essential elements of both the primary and secondary markets in investment banking. It is used in both markets to make informed decisions, accurately price securities, and project/analyze potential returns of the stock. An equity research career provides a range of benefits, particularly within top-tier firms.

Emergence of Alternative Data

It’s not just about crunching numbers; it’s about understanding the story behind the figures and providing a comprehensive view of a company’s potential. For equity research analysts, mastering financial modeling is not just a skill—it’s an art that, when perfected, can provide a competitive edge in the market. Financial analysis is critical to the equity research report, providing insight into the company’s financial health and performance. This section should include a detailed analysis of the company’s income statement, balance sheet, and cash flow statement. The analyst should also compare the company’s financial performance to its peers and industry benchmarks.

3 Model interpretation and feature importance analysis results

• It’s a blend of art and science, requiring both creative thinking and rigorous analysis.
• The primary components of equity research are fundamental analysis and financial modeling.
• Analysts are usually divided into industry sectors to cover similar companies within an industry.
• The higher the value, the more important the principal component is to the model’s prediction.

This data provides a rich empirical foundation for the study and supports the development and validation of various financial forecasting models. The combination of big data and machine learning technologies offers new solutions to address these challenges. Big data technology efficiently processes large volumes of diverse data, enabling the identification of complex patterns in financial data and providing more precise support for decision-making (1). Machine learning algorithms, such as regression analysis, classification models, and time series analysis, have shown great potential in the field of financial forecasting (2). Research shows that machine learning methods can analyze historical financial data in depth, predict future financial conditions, and even provide early warnings for potential risks (3, 4).

Forecasting

• While reading equity research reports can help with this process, acquiring these skills is often accomplished through the learn-by-doing method.
• Students who don’t have a background in accounting or finance will be sent a short guide on terminology before class starts.
• The volume and complexity of its financial data have been substantial, and the traditional financial management system has shown significant limitations in real-time data analysis and forecasting.
• It should also include information on the industry in which the company operates, such as market trends and competitive landscape.

Strong modeling skills allow analysts to quickly adjust assumptions and defend their investment thesis when challenged by portfolio managers. After completing data preprocessing and cleaning, this study applied Principal Component Analysis (PCA) to 54 key financial indicators for dimensionality reduction and feature extraction. PCA effectively compressed the original 54 financial indicators into 15 principal components, which together explain about 90% of the total variance in the data.

Step 1: Selection of Companies

For individuals who need to balance their study of financial modeling with other commitments such as full-time work or travel, self-paced coursework is for you. Unlike in-person and live online study, on-demand financial modeling classes are pre-recorded. Although it may be tricky to master complex financial modeling concepts like nested functions or VLOOKUP, self-paced courses are a good option for beginners looking to get started with financial modeling.

They develop driver-based models linking operational metrics like headcount, sales volume, or production capacity to financial outcomes. These models help identify areas for improvement and determine available resources for new initiatives. Beyond LBOs, private equity firms build DCF models to assess intrinsic value and merger models to evaluate add-on acquisitions for portfolio companies. These financial models help identify value creation opportunities through operational improvements, strategic acquisitions, or financial engineering. The input layer receives the financial data, which has been processed by PCA for dimensionality reduction.

For example, a company like Blockbuster once had a strong economic moat due to its dominant position in the video rental industry. However, the rise of streaming services like Netflix eventually caused Blockbuster to go bankrupt. Crowdsourced equity research platforms, where independent analysts and investors share their research and opinions, are gaining popularity.

The Future of Financial Modeling in Equity Research

After constructing and validating the CNN-LSTM hybrid model, it is essential to understand the decision-making process of the model and the impact of each feature on the prediction results. Global feature importance analysis not only enhances the transparency and trustworthiness of the model but also provides valuable financial decision-making insights for corporate management. The CNN-LSTM hybrid model shows reasonable scalability for financial datasets of the size used in our study. For our implementation using 54,389 observations with 54 features across 60 time steps, the model training took approximately 18 h on a workstation with an NVIDIA RTX 3090 GPU with 24GB memory. This training time included basic hyperparameter tuning but would increase substantially for more extensive tuning processes. For inference, the model processes new data in approximately 150–200 ms per sample, which is adequate for daily financial forecasting applications though not suitable for high-frequency trading scenarios.

After the analysis and research is thoroughly conducted, equity research analysts put forth their observations in the form of equity research reports. As a Portfolio Manager, you would use the insights from equity research to make investment decisions for a fund or portfolio. This role requires a deep understanding of financial markets, risk management, and asset allocation strategies. The process of modeling and underwriting is an integral part of equity research and financial modeling. Equity analysts use modeling techniques to identify the potential for returns in a particular security, portfolio or company, and then use those insights to determine what the fair value of the security should be.

Although it takes time and requires developing a solid investment strategy and acquiring financial literacy, it’s not considered as difficult a skill to acquire as financial modeling. If you’re new to investing and want to learn how to get started, Noble Desktop’s free online class, Stock Market Investing Fundamentals, is a great way to master investment basics. This hour-long course covers topics like the risk-reward principle, capital gains tax, and some basics of valuation. Equity research employs various methodologies to evaluate companies’ financial health and growth potential, generating accurate and actionable reports.

1 Data source and description

It includes the presentation of the equity research financial modeling Principal Component Analysis (PCA) results, analyzing the explanatory power of each principal component on the financial indicators and their economic significance. Additionally, the performance of the CNN-LSTM hybrid model will be evaluated and compared with traditional methods. Furthermore, the SHAP method will be applied to analyze feature importance and explain the model’s decision-making process.