How to leverage alternative data in asset management
Whether you are managing a hedge fund trying to find innovative sources of alpha or are an analyst looking to future proof your company’s financial investments, as big data continues to disrupt the investment research landscape, getting on top of these alternative datasets as early as possible is the key to capturing the immense alpha left in this data.
In our blog post, we will show you what alternative data is and how harnessing the power of web extracted alternative data can give insights that keep you two steps ahead of the market.
What is alternative data?
Alternative data in finance is the data that has been used to gain insights in order to make better investment decisions. This data is published by sources other than the company itself. Web data is the biggest source of alternative data, helping investment managers by informing them about new and hot market opportunities, and arming them with the insight needed to act quickly and develop positions carefully. Data collection is usually through traditional data sources like press releases, product releases, and financial statements as well as other activities like social media and hiring.
How can alternative data for finance help you?
When it comes to extracting high-quality data from the web, there’s virtually no limit to the type and quantity of data available. Our blog post takes you through a few typical data types and how it can help with asset management decisions.
Type 1: Product data
Product data is one of the most complex but important sources of data that provide critical insights into the performance of a product or a brand. Amazon, Walmart, Target, eBay, etc are great examples of websites that provide thousands of data points to reveal company and category performance.
How is product data useful?
- A product’s rank on an online retailer's bestseller list can indicate strong performance, while poor ranking and a discount history revealing early price reductions can expose inventory troubles and margin reductions.
- Advertising data can provide a unique insight into the corporate spend behind product launch and anticipate revenue changes or slow-moving inventory, along with measurements for product traction and adoption.
- YoY share trends from online retailers are powerful predictive indicators of revenue momentum and stock performance.
All this data offers lucrative opportunities for investors when determining market orders and positions.
Type 2: SEC filing data
Taking a dive into the lengthy and often nebulous pages of a company’s SEC filings can lead to amazing investment insights. It arms investors with high-quality and reliable information, which is why the demand for web scraped SEC filing data is surging.
SEC filings have an immediate impact on stock performance. Markets are highly responsive to filings, whose submission has a direct relationship to increased trade volume. Scraping SEC filings, 10-Ks and 10-Qs produce enormous datasets, revealing non-trivial patterns in huge aggregations of data. Investors can use this information to identify rare opportunities for alpha as well as high performing outliers.
Type 3: Product reviews
Investment managers want first-hand information on the product information and its current performance so that they can accurately predict the stock performance. While the companies quarterly earnings can provide such insights, it may be too late to make profitable decisions.
Scraping product reviews can allow investors to proactively gather information on a product life cycle and make more up to date assumptions about company earnings. After all, what’s one of the first metrics many of us look to when deciding on a product? The reviews.
Utilizing scraped product reviews to evaluate how a company or product is trending in the category and against its competition helps hone the perception of risk in the investment decision-making process. Negative consumer reviews can increase stock volatility and pose a serious risk to shareholder value. By extracting product reviews historically and in real-time, smarter and more timely analyses (or corrective actions) can be performed.
Type 4: Company news
Where can we get information straight from the horse’s mouth? A company’s website and its communications are a good place to start. Scraping data from the web may include analyzing company web traffic, announcements, and hiring activity with the aim of accessing otherwise exclusive insights.
The following are key pieces of data to monitor:
- Press releases
- Company web traffic
- Hiring activity (via the company website and employment websites)
- Product announcements
- Social media activities
These data give a full picture of a company’s inside track generating extremely useful insights on the company’s trajectories; saving companies from making serious investment blunders.
Type 5: Sentiment analysis
The rise of social media platforms like Facebook and Twitter has led to a flood of public sentiment. Public sentiment on social media gives insight into both the public at large and also any given subset we might want to glean more information about.
Tweets have incredible predictive value. Companies announce developments on social media channels like Twitter, Instagram, and Facebook, and sometimes breaking news hits the social media channels before any other traditional mediums. Company popularity and reputation can be monitored carefully and tracked against competitors.
With an opportunistic mindset and consistent dataset, investors can track and analyze the changes in a company’s internal framework to make financial decisions.
Harnessing the power of quality alternative data will be a decisive advantage in your search for alpha. More data and better data means your investment decision-making process produces more value, more consistently.
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