Gathering data for equity research reports is time consuming and resource draining. Fortunately, the right tools can help organize and speed up the process so tedious research and data entry tasks are streamlined. Data extraction software gets the data you need in a structured format to quickly synthesize the information into usable equity reports. This speeds up the decision-making process on investments and reduces human error and fatigue. Here’s how you can leverage data extraction in equity research.
Extract Business Details
Equity researchers often want to gather non-traditional data for their financial forecasts, evaluations, and financial projections. That type of data may not be complicated to find, but manually gathering it from multiple websites takes precious time away from the crucial process of analyzing and interpreting the findings. In addition, the fatigue of pulling the information together increases human error and creates duplicate and unnecessary entries.
Instead of relying on manual data entry, researchers can use data import tools and spend more time organizing and interpreting the data. Data extraction ultimately saves time so equity researchers can move on to more crucial tasks.
Evaluating the financials of a startup requires compiling research from multiple sources and digging into sites (like Angel List and TechCrunch) to find funding information. The process may look similar to that of compiling basic business details, but it also requires a volume of data, including any publicly-disclosed financial statements. Combing through multiple websites and online databases by hand can be difficult to manage and isn’t always reliable. For example, sifting through hundreds of websites could yield outdated information and create the need to cross-reference all collected data.
Meanwhile, data collection tools can parse through the information for you, and even find the latest updated data. This allows equity researchers to quickly pull the relevant information together to evaluate the necessary financials to determine if investing or trading with a startup is the right move.
When an equity researcher works with an investor, they want to evaluate the long-term value and possible return on investment of a company. This process includes multiple steps and moving parts, including researching individual companies and evaluating investments in the marketplace.
Instead of sampling hundreds to thousands of pieces of data and looking for patterns to determine the company’s value, data extraction tools can pull all of the information together for a more streamlined and usable analysis in a fraction of the time that hand-compiling data takes. Investors can then use these highly-organized and accessible reports to speed up the decision-making process.
The ratio analysis evaluates a company’s operating and financial performance, including its profitability. Equity researchers may be tasked with pulling data on several years’ worth of balance sheets and comparing the trends against other companies. Equity researchers also compare the firm’s ratios against existing industry data to see how the company is doing in the marketplace.
This type of data collection can be difficult to do and track to get the latest and most comprehensive view of a company’s financial performance. Data extraction and collection tools can help automate that process so equity researchers, investors, and related teams can focus on their investment decisions.
Equity researchers look at the growth of a company or sector and its profitability to help analysts and investors put together valuation models. Equity researchers also rely on multiple quarterly earnings reports to help forecast how a company or investment will perform over a 12-month period.
But those projections also shift as more data becomes available. That’s why it’s important to leverage scheduled data updates to keep up with the latest data so projects are as up-to-date as possible. This can help determine sound investment decisions. Otherwise, equity researchers may end up with multiple pieces of outdated information that impact the analytics and reports before the team can thoroughly study the valuation models.
Competitive analysis can apply to numerous industries, including equity research and investments. The idea behind this method is to figure out how companies in your sector stack up against each other, or your own company. Whether you’re looking at how financial performance or how their products and services differ, collecting competitive analysis data can fuel your analysis.
Data extraction tools come into play with competitive analysis when multiple pieces of data and information need to be quickly collected, organized, updated, and compiled. Use data import tools to collect information on everything from how stocks are performing, to the funding of different businesses and profits.
Financial Statement Analysis
Collecting, analyzing, and organizing information for hundreds of financial statements results in an incredible amount of data. Without the right data and information to complete financial statements, it’s difficult for companies to interpret where their break-even point is, and their margin of safety in areas like their marketing spend vs. their sales. Equity researchers may also be tasked with figuring out the return on net assets and the gross profit ratio.
When it comes to stocks and bonds, today’s research often revolves around what Wall Street reports on big cap, liquid stocks. But there are plenty of publicly-traded stocks that aren’t always reported. Research firms need more information on these gaps, and equity researchers are tasked with pulling together the information on less-mainstream stocks that may still be worthwhile.
The data extraction process can help quickly get data on stocks and bonds, then compare the data against what Wall Street is already reporting on, and compile the data into equity reports.
Private Portfolio Research
As equity research faces unbundling under the European regulation Markets in Financial Instruments Directive II (MiFID II), banking clients are tasked with separating money spent on research from what they spent on executing trades. That’s good news in terms of staying transparent, but it also means that paying for quality equity research is crucial. That puts added pressure on equity researchers and trading teams to quickly identify changes in investments and adjust client portfolios.
An integral part of that research is to automatically require new stock and investment data, changes in acquisitions, and any relevant information that could change the profitability of investments. Without data extraction tools, it’s difficult to stay on top of hundreds to thousands of investments and make immediate recommendations and portfolio changes to protect a client’s financial interests.
At the end of the day, an equity researcher’s job is about reliability, efficiency and the ability to quickly digest and make sense of emerging data. Their role is an integral part of keeping the financial industry as transparent as possible and making sure all information is presented in a clear and usable manner.
Using web data can help equity researchers get and analyze non-traditional research as well as traditional data such as income statements, balance sheets, and statements of cash flow. There’s no limit to how data extraction can be used for collecting online equity research.
Let Import.io help you get data for research.