The following guest article was submitted by Mikheil Shengelia, Research Analyst at Eagle Alpha, an alternative data aggregation platform providing supporting advisory services for data buyers and vendors.
Alternative Data Meets Event Risk
Event risk refers to any future event, press releases, corporate announcements as well as potentially unforeseen occurrences, like M&A, that could materially affect the value of a company or investment. These events can range from share buybacks or corporate reorganizations to major strategic shifts such as mergers, acquisitions, or leveraged buyouts.
Scheduled corporate events like quarterly earnings, product announcements, FDA approvals, and many more such events, are very important for investors to monitor. Each of these scenarios can have a significant impact on stock prices — sometimes driving them higher due to perceived growth potential, or lower if investors anticipate financial strain or operational disruption.
Businesses also face risks arising from operational and external shocks. For instance, a company might be forced to recall a flagship product due to safety concerns, face legal allegations or regulatory investigations, or experience sudden changes in macroeconomic conditions that sharply increase the cost of essential inputs or end demand. In some cases, new or additional debt taken on to finance acquisitions or restructuring may come with higher interest rates, placing strain on cash flows and debt repayment capacity.
In today’s data-driven world, identifying and interpreting such events in real time has become critical. The exponential growth of digital information (ranging from news articles and press releases to social media commentary) has created both opportunities and challenges for investors, analysts, and corporations.
Click here to download Eagle Alpha’s Annual Alternative Data Report.
Experienced asset managers have long recognized the importance of timing and foresight in financial markets. For decades, economic calendars have been a cornerstone of strategic planning — helping investors anticipate key macroeconomic indicators, earnings releases, and corporate announcements that could influence asset prices.
The origins of structured event disclosure can be traced back to the Securities Exchange Act of 1934, a landmark piece of legislation that established the foundation for modern financial transparency. This act required publicly listed companies to provide timely and periodic updates — most notably through annual 10-K and quarterly 10-Q filings — to ensure that investors had access to consistent and reliable information for decision-making.
Events data can be broken down into two sub-categories:
- Calendar events. These are scheduled and predictable events, often known in advance, that are formally communicated by companies or regulatory bodies. Examples include earnings release dates, dividend payment dates, IPO effective dates, share repurchase announcements, stock split effective dates, FDA approvals, product launch timelines, and guidance updates. These events form the structured backbone of most economic and corporate calendars and are essential for planning and forecasting.
- Significant events. These refer to unscheduled or unexpected developments that typically cause material price dislocations or volatility spikes—commonly known as gap risks. Such events may include mergers and acquisitions, leadership changes (e.g., CEO or CFO departures), recapitalizations, regulatory actions, sanctions, bankruptcy filings, activist campaigns, or credit downgrades.
Event-driven strategies seek to exploit market inefficiencies created by corporate or macroeconomic events, both scheduled and unexpected. Key approaches include merger arbitrage, where investors profit from the spread between a target’s trading price and an acquisition offer; activism, which targets companies facing strategic or governance pressure; distressed investing, focused on securities of financially troubled firms trading at deep discounts; and special situations, such as spinoffs, asset sales, litigation, or regulatory shifts.
The purpose of event detection goes well beyond simply categorizing or summarizing news. It forms the foundation for higher-level algorithmic processes, including risk management, predictive modeling, and the design of automated trading strategies. Sophisticated event detection frameworks can help market participants anticipate reactions, model contagion effects, and gain early insights into emerging risks.
Many data vendors active in this field also integrate sentiment analysis to enhance their insights, assessing not only the factual content of an event but also the tone and market perception surrounding it. By combining event detection with sentiment scoring, investors can better understand both the what and the how of market reactions which could lead to more informed, data-driven trading decisions.
Academic Research
Academic research has long shown that corporate and calendar events have a meaningful impact on asset prices. Early work by Beaver (1968) found that earnings announcements lead to sharp increases in trading volume and return volatility, a pattern reinforced by later studies documenting persistent price effects around scheduled events. Research by Lamont and Frazzini (2007) highlighted a long-term “earnings announcement premium,” with stocks tending to rise around earnings dates.
Event studies also show strong reactions to corporate actions. Ikenberry, Lakonishok, and Vermaelen (1995) found significant abnormal returns following share repurchase announcements, particularly for undervalued firms. In mergers and acquisitions, Hackbarth and Morellec (2006) showed that announcement gains accrue primarily to target firms, with limited impact on acquirers.
More recent research has expanded into ESG and regulatory events. Studies suggest that changes in ESG scores can affect downside and systemic risk, while the ECB analysis of euro area banks found modest but positive share price reactions to buyback announcements, especially for banks trading below book value.
Figure 1: Distribution of Abnormal Returns and Implied Volatility on Trading Days With and Without Share Buyback Executions (Source: ECB)
Applications
In a recent webinar hosted by Eagle Alpha, they invited EventVestor who focuses on transforming corporate and investor events into structured, forward-looking intelligence that investors can systematically analyze and act on.
A central use case is EventVestor’s detailed tracking of earnings dates, including the distinction between estimated and confirmed announcements. Changes in confirmation timing (e.g., delays, early confirmations, or repeated revisions) can act as subtle but meaningful signals of management confidence, operational uncertainty, or shifting disclosure strategy.
Figure 2: Comprehensive Corporate Events Data (Source: EventVestor)
Beyond earnings, EventVestor provides broad coverage of corporate and investor-facing events, including investor days, broker-hosted conferences, analyst meetings, guidance updates, M&A announcements, shareholder actions, and executive or board changes. These events are timestamped, normalized, and categorized, making them suitable for both discretionary monitoring and quantitative backtesting. This structure enables analysts to move beyond narrative interpretation toward repeatable signal generation.
EventVestor also captures executive visibility and participation data, tracking which C-suite leaders appear at conferences, industry events, or in financial media. Patterns in executive engagement such as increased CEO visibility ahead of major announcements can offer insight into management intent and communication strategy. When combined with other corporate events, this data helps contextualize why and when management chooses to engage the market.
Eagle Alpha’s Annual Alternative Data Report highlights the major trends shaping the industry, from evolving data sourcing strategies and increased AI adoption to new legal, privacy, and governance requirements. The report combines expert perspectives on macro and market dynamics with real-world case studies showing how alternative data is applied by the practitioners. Download it here.