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  "tx_id": "tx_2e41e0af-2ae7-4d4e-b4a5-7116a1f7cf14",
  "query": "Pfizer’s 5-year stock performance and highlight the impact of COVID-19 vaccine sales",
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  "tx_id": "tx_2e41e0af-2ae7-4d4e-b4a5-7116a1f7cf14",
  "query": "Pfizer’s 5-year stock performance and highlight the impact of COVID-19 vaccine sales",
  "results": [
     {
      "title": "Pfizer shows profit growth from cost cuts and steadier COVID sales",
      "url": "https://www.reuters.com/business/healthcare-pharmaceuticals/pfizer-beats-fourth-quarter-profit-estimates-cost-cutting-efforts-2025-02-04/?utm_source=valyu.network&utm_medium=referral&utm_campaign=ai_pilot&utm_content=ai_query",
      "content": "# Pfizer shows profit growth from cost cuts and steadier COVID sales

- Pfizer's Q4 revenue beats expectations with $17.8 billion; EPS also beats

- Cost-cutting measures to save Pfizer $4.5 billion by year-end

- Analysts shift focus to Pfizer's future drug pipeline and Seagen acquisition

- COVID vaccine sales exceed expectations

- Shares gain 2.6% in early trading

Reporting by Manas Mishra and Bhanvi Satija in Bengaluru and Michael Erman in New York; Editing by Saumyadeb Chakrabarty, Nick Zieminski and Lisa Shumaker

Our Standar....",
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      "source_type": "website",
      "id": "https://www.reuters.com/business/healthcare-pharmaceuticals/pfizer-beats-fourth-quarter-profit-estimates-cost-cutting-efforts-2025-02-04/",
      "relevance_score": 0.6034099061567948
    },
    {
      "title": "Price of PFE every 1mo between 2020-05-27 00:00 and 2025-05-27 00:00",
      "url": "https://platform.valyu.network/context-enrichment/valyu/valyu-stocks-US/characteristics",
      "content": [
        {
          "datetime": "2025-05-01 04:00:00",
          "open": 24,
          "high": 24,
          "low": 22,
          "close": 24,
          "volume": 78778153
        },
        {
          "datetime": "2025-04-01 04:00:00",
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          "high": 25,
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          "volume": 78184178
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      "source": "valyu/valyu-stocks-US",
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    {
      "id": "bcc7423e-4ad5-41a5-a011-51d7cf98fd8e:PMC9832402:2",
      "title": "The influence of share buybacks on ill-health and health inequity: an exploratory analysis using a socio-ecological determinants of health lens",
      "url": "https://pubmed.ncbi.nlm.nih.gov/PMC9832402?utm_source=valyu.network&utm_medium=referral&utm_campaign=ai_pilot&utm_content=ai_query",
      "content": "### Quantitative analysis of US-listed corporations between 1982 and 2021

### An analysis of three illustrative examples: selection of corporations and methods used

We examined three illustrative examples, selected in a purposive manner, to provide further insight into the ways in which share buybacks impact on health by representing funds that have not been allocated towards meaningful investments. These three examples were chosen because we felt that, for the purposes of this exploratory study, they illustrated a range of general and sector-specific health-related consequences of large-scale share buyback programs. In addition, the three examples demonstrated how a considerable proportion of the funds used for shareholder return programs, including share buyback programs, can often be traced back to direct and indirect financial assistance from governments. This has important normative implications for regulating share buybacks, a point to which we return in the discussion section.

The three illustrative examples were:1. **i)**
   The manufacturers of the largest Coronavirus Disease 2019 (COVID-19) vaccines by revenue.
2. **ii)**
   The fossil fuel industry, focusing on the industry’s five largest corporations (excluding state-owned corporations).
3. **iii)**
   General Motors, a major US car manufacturer, focusing on its share buyback programs prior to and following the corporation’s so-called ‘Auto Bailout’ in 2009.

For the first example (COVID-19 vaccine manufacturers), we analysed financial data extracted from Compustat, as well as the annual reports....",
      "source": "valyu/valyu-pubmed",
      "length": 3929,
      "image_url": {},
      "publication_date": "2023-01-11",
      "doi": "10.1186/s12992-023-00905-0",
      "citation": "Benjamin Wood & Gary Sacks (2023). The influence of share buybacks on ill-health and health inequity: an exploratory analysis using a socio-ecological determinants of health lens.https://doi.org/10.1186/s12992-023-00905-0",
      "citation_count": 0,
      "authors": [
        "Benjamin Wood",
        "Gary Sacks"
      ],
      "references": "## References:
[65] Statista. Projected sales of select leading COVID-19 vaccines from 2020 to 2026 [22 June 2022]. Available from: [https://www.statista.com/statistics/1194747/select-leading-covid-vaccine-sales-forecast/]().
[66] Cronin B. The good times are rolling for Big Oil. 3 things to know about their surging profits: NPR; 2022 [23 June 2022]. Available from: [https://www.npr.org/2022/05/07/1097177459/big-oil-exxon-earnings-gasoline-prices-crude]().
[67] EIA. Short-term energy outlook. Washington, DC: U.S. Energy Information Administration; 2022. [22 June 2022]. Available from: [https://www.eia.gov/outlooks/steo/realprices/]().
[68] Statista. Leading oil and gas companies worldwide based on revenue as of 2022 (in billions U.S. dollars) [22 June 2022]. Available from: [https://www.statista.com/statistics/272710/top-10-oil-and-gas-companies-worldwide-based-on-revenue/]().
[69] President Barack Obama. Remarks by the President on General Motors Restructuring. Washington, DC: The White House Office of the Press Secretary; 2009. [21 June 2022]. Available from: [https://obamawhitehouse.archives.gov/the-press-office/remarks-president-general-motors-restructuring]().",
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    },
    {
      "id": "f7a547dc-e5dd-484b-a61a-03731147a089:2312.02250:4",
      "title": "Valuing Post-Revenue Biopharmaceutical Assets with Pfizer's Current Portfolio as a Case Study",
      "url": "https://arxiv.org/abs/2312.02250?utm_source=valyu.network&utm_medium=referral&utm_campaign=ai_pilot&utm_content=ai_query",
      "content": "Content: ### 5 Model validation using Pfizer sales

To validate the model, we use revenue data taken from Pfizer's financial reports from 2006 through 2022. The dataset comprises revenue data extracted from Pfizer's Financial Reports spanning from 2006 to 2019, specifically focusing on the revenues generated by several key pharmaceutical products. Additionally, information from the Annual Report on Form 10-K for the years 2020 to 2022 has been incorporated, primarily sourced from sections such as "Significant Product Revenues" and "Revenues—Selected Product Discussion." In addition, we have incorporated the patent expiration date for each asset as well as several other features including the number of phase 3 trials the asset was used as treatment for, the indication type targeted by each asset, and the total number of conditions targeted. Validation proceeds in the following two subsections as follows. First, we will hold out sales in later years and report the out-of-sample accuracy of the holdout data in terms of the MSE. Second, we will test the null hypothesis that the predictive information needed to estimate future sales is contained in the curve and that, as a result, information including number of phase 3 trials, indication type, and total number of conditions does not increase the model accuracy. Our results show that the model is accurate in terms of out-of-sample prediction accuracy and that the incorporation of the state features does not enhance prediction accuracy.

We note that in this section, we did not incorporate Cormirnaty and Paxlovid into the validation, Pfizer's two COVID-19 related assets. The sales of.....",
      "source": "valyu/valyu-arxiv",
      "length": 1003,
      "image_url": {},
      "publication_date": "2023-01-01",
      "doi": "https://doi.org/10.48550/arxiv.2312.02250",
      "citation": "Yongzhuo Chen et al. (2023). Valuing Post-Revenue Biopharmaceutical Assets with Pfizer's Current Portfolio as a Case Study.https://doi.org/10.48550/arxiv.2312.02250",
      "citation_count": 0,
      "authors": [
        "Yongzhuo Chen",
        "Yixuan Liang",
        "Yiran Liu",
        "Brian Hobbs",
        "Michael J. Kane"
      ],
      "references": "## References:
- [5] A. E. Lang, U. Patel, J. Fitzpatrick, T. Lee, M. McFarland, and C. B. Good. Association of the chantix recall with us prescribing of varenicline and other medications for nicotine dependence. JAMA Network Open, 6(2):e2254655–e2254655, 2023.",
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    },
     {
      "title": "Pfizer riding Paxlovid sales growth to better-than-expected third quarter - Washington Times",
      "url": "https://www.washingtontimes.com/news/2024/oct/29/pfizer-riding-paxlovid-sales-growth-better-than-ex/?utm_source=valyu.network&utm_medium=referral&utm_campaign=ai_pilot&utm_content=ai_query",
      "content": "- Putin's war in Ukraine

- Business & Economy

- Media Spotlight

- Waste, Fraud & Abuse

- Inside the Ring

- Just the Headlines

- Photo Galleries

- 40 years of The Washington Times

- Policy Corrections Threat Status Energy & Environment Banking & Finance Health Care Reform Second Amendment Immigration Reform Homeland & Cybersecurity Aerospace & Defense Taxes & Budget Law Enforcement & Intelligence Transportation & Infrastructure

- Energy & Environment

- Banking & Finance

- Health Care Reform

- Second Amendment

- Immigration Reform

- Homeland & Cybersecurity

- Aerospace & Defense

- Law Enforcement & Intelligence

- Transportation & Infrastructure

- Commentary Commentary Main Corrections Editorials Letters Charles Hurt Cheryl K. Chumley Kelly Sadler Jed Babbin Tom Basile Tim Constantine Joseph Curl Joseph R. DeTrani Don Feder Billy Hallowell Daniel N. Hoffman David Keene Robert Knight Gene Marks Clifford D. May Michael McKenna Stephen Moore Tim Murtaugh Peter Navarro Everett Piper Cal Thomas Scott Walker Miles Yu Black Voices Books Cartoons To the Republic

- Commentary Main

- Cheryl K. Chumley

- Tim Constantine

- Joseph R. DeTrani

- Billy Hallowell

- Daniel N. Hoffman

- Clifford D. May

- Michael McKenna

- To the Republic

- Sports Sports Main Corrections Washington Commanders Football Baseball Basketball NCAA Thom Loverro Tennis Golf Hockey Soccer Horse Racing NASCAR & Racing District of Sports Podcast Sports Photos

- Washington Commanders

- NASCAR & Racing

- District of Sports Podcast

- Sponsored Corrections Higher Ed Harassment Health Care on the Hill Invest in Portugal Health Care 2022 Africa FDI Edition Immigration 2022 Invest in Ireland ESG Investments U.S. & South Korea Alliance 146 Heroes Invest in Malta Victorious Family Energy 2024 Transportation 2024 National Clean Energy Week Invest in Greece 2025 Free Iran 2025 Infrastructure 2025 Renewing American Energy Dominance Investing in American Health

-....",
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      "data_type": "unstructured",
      "source_type": "website",
      "id": "https://www.washingtontimes.com/news/2024/oct/29/pfizer-riding-paxlovid-sales-growth-better-than-ex/",
      "relevance_score": 0.52078125
    },
    {
      "id": "92ce7e3f-cb88-4d03-a3b2-8da7afc43a36:2401.05414:10",
      "title": "On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors",
      "url": "https://arxiv.org/abs/2401.05414?utm_source=valyu.network&utm_medium=referral&utm_campaign=ai_pilot&utm_content=ai_query",
      "content": "Content: ## 5 Experiments

In this section, we apply our proposed method to Sp100 stock price dataset and see how well we can address the three issues, i.e., time resolution, non-stationarity, and latent variables.

For the first issue, throughout the experiments we use the log daily/hourly return data, which can be written as the sum of the log minute return. Therefore, suppose the causal effects among stocks can be approximated as linear and happen instantaneously, according to Section 2, those instantaneous causal relations can still be recovered from the aggregated sum data. This can be verified by the reasonable results shown below. For the rest of this section, we focus on dealing with nonstationary relations and latent variables.



# 5.1 Results on Constraint-based causal Discovery from heterogeneous/NOnstationary Data (CD-NOD)

The scatter plot in  Figure 1 highlights the potential for significant shifts in causal relationships among stocks during the Covid-19 pandemic. To further investigate this and explore what information can obtained in a nonstationary market context, in this subsection we focus on ten representative stocks from the SP100. These stocks are across various sectors that might be influenced by the pandemic:

- Pharmaceuticals: Pfizer (PFE) and Merck (MRK). These companies are directly involved in the development and distribution of Covid-19 treatments and vaccines.
- Entertainment and Streaming: Netflix (NFLX), Disney (DIS). The stay-at-home policies and social distancing measures increased demand for home entertainment.
- Travel and Hospitality: Boeing (BA), Booking Holdings (BKNG). Disney (DIS) may also be counted here as for their resorts. These companies experienced significant downturns due to travel restrictions and reduced consumer travel interest.
- Consumer Services and Retail: Walmart (WMT), Visa (V). These companies represent......",
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      },
      "publication_date": "2024-01-01",
      "doi": "https://doi.org/10.48550/arxiv.2401.05414",
      "citation": "Xinshuai Dong et al. (2024). On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors.https://doi.org/10.48550/arxiv.2401.05414",
      "citation_count": 0,
      "authors": [
        "Xinshuai Dong",
        "Haoyue Dai",
        "Yewen Fan",
        "Songyao Jin",
        "Sathyamoorthy Rajendran",
        "Kun Zhang"
      ],
      "references": "",
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        {
      "title": "Pfizer eyes 2025 revenue growth despite post-COVID challenges, activist pressure",
      "url": "https://www.mmm-online.com/news/pfizer-eyes-2025-revenue-growth/?utm_source=valyu.network&utm_medium=referral&utm_campaign=ai_pilot&utm_content=ai_query",
      "content": "##### HAYMARKET MARKETING COMMUNICATIONS:

- News Agencies Five Things to Know Data/Analytics Campaigns Pharma Podcasts Policy Media Technology People Moves The Wire

- Five Things to Know

- In-Depth MM+M Best Places to Work 2024 Career and Salary Survey 2024 Healthcare Marketers Trend Report

- MM+M Best Places to Work 2024

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# Pfizer eyes 2025 revenue growth despite post-COVID challenges, activist pressure

Pfizer said it had achieved $4 billion in net cost savings through 2024 and that it expects full-year 2025 revenue to range between $61 to $64 billion.....",
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    {
      "title": "Pfizer Inc. (PFE) Stock Price, News, Quote & History - Yahoo Finance",
      "url": "https://finance.yahoo.com/quote/PFE/?utm_source=valyu.network&utm_medium=referral&utm_campaign=ai_pilot&utm_content=ai_query",
      "content": "Yahoo is part of the Yahoo family of brandsThe sites and apps that we own and operate, including Yahoo, AOL, Engadget, Rivals, In The Know and Makers.Yahoo family of brands.

- provide our sites and apps to you

- authenticate users, apply security measures, and prevent spam and abuse, and

- MeasurementWe count the number of visitors to our pages, the type of device they use (iOS or Android), the browser they use and the duration of their visit to our websites and apps. This data is collected in aggregate and is not tied to specific users.measure your use of our sites and apps

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      "description": "Find the latest Pfizer Inc. (PFE) stock quote, history, news and other vital information to help you with your stock trading and investing.",
      "source": "web",
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    {
      "id": "ef6606ae-0ed5-438b-a014-ea5c2a0db85f:2401.05414:3",
      "title": "On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors",
      "url": "https://arxiv.org/abs/2401.05414?utm_source=valyu.network&utm_medium=referral&utm_campaign=ai_pilot&utm_content=ai_query",
      "content": "Content: #### 3.2 From Causal Discovery Perspective

#### 3.1 From the Financial Perspective

It is well-known that financial markets has a non-stationary nature. For instance, substantial evidence suggests regime shifts in the crude oil market, as highlighted by (Vo, 2009). Financial market time series data are prone to undergo unpredictable changes, which is known as concept drift (Lu et al., 2018; Žliobait˙e et al., 2016; Gama et al., 2014).

Concept drift is a phenomenon where the distribution of streaming data undergoes possibly unpredictable changes over time, as described in (Lu et al., 2018). In formal terms, when the feature vector is represented by x and the label by y, concept drift is characterized by the time-dependent alteration in the joint distribution of p(x, y), as detailed in (Lu et al., 2014).

Example 1 Figures 1 demonstrates the evolving correlation between the stock price daily log return time series of Pfizer Inc. (PFE) and The Boeing Company (BA) from 2019 to 2023. This relationship has experienced significant shifts, particularly during the pre- and post-COVID periods. In 2019, a time of economic expansion, both PFE and BA exhibited an upward trend in stock prices. The correlation observed in this era could be influenced by broader economic factors (confounders). The correlation is relatively weak in this period. The onset of COVID-19 in early 2020 saw a sharp decline in both BA's and PFE's stock prices. However, in late 2020, both stocks generally increased, displaying a notably stronger correlation (also demonstrated by the correlation between the log daily returns in 2020). This change is possibly linked to Pfizer's vaccine development positively impacting travel confidence, thereby affecting the aviation sector. After 2021, this correlation moderated, aligning with the evolving COVID-19 situation. By 2023, as COVID-19 concerns eased, the correlation between PFE and BA stock prices significantly weakened.

Of course, it's worth noting that pairwise relationships don't always reflect true causality (may be subject to confounders), which is typically captured by conditional relationships. PFE(ADF=-7.63: 96-th/99) vs BA(ADF=-11.00: 54-th/99)



# Therefore, the explanations provided above serve more for intuitive understanding than accurate discovery. For a more systematic investigation of this example, please refer to Section 5.

To handle concept drift, prior works usually rely on the assumption that the latest data contains more useful information. Researchers have proposed to use retraining based methods (Bach and Maloof, 2008), ensemble based methods (Gomes et al., 2017), incremental adaptation based methods (Domingos and Hulten, 2000) to tackle concept drift for the general time series tasks. In recent developments, new approaches have been introduced specifically for financial applications. Li et al. (2022) suggests initially training a model to predict future data distributions. This model is then used to create training examples that mirror the anticipated future data, which are subsequently utilized to train machine learning models. On the other hand, Riva et al. (2022) advocates for treating the trading task as a non-stationary reinforcement learning problem and selects the most effective strategy from a set of reinforcement learning models.

",
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      "publication_date": "2024-01-01",
      "doi": "https://doi.org/10.48550/arxiv.2401.05414",
      "citation": "Xinshuai Dong et al. (2024). On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors.https://doi.org/10.48550/arxiv.2401.05414",
      "citation_count": 0,
      "authors": [
        "Xinshuai Dong",
        "Haoyue Dai",
        "Yewen Fan",
        "Songyao Jin",
        "Sathyamoorthy Rajendran",
        "Kun Zhang"
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    {
      "title": "The Strategic Repositioning Driving Pfizer's Growth Story",
      "url": "https://www.mitrade.com/insights/news/live-news/article-8-745471-20250408?utm_source=valyu.network&utm_medium=referral&utm_campaign=ai_pilot&utm_content=ai_query",
      "content": "- English(Australia)

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# The Strategic Repositioning Driving Pfizer's Growth Story

- Pfizer’s non-COVID portfolio grew 12% in 2024, led by a 65% surge in Vyndaqel sales and 26% oncology revenue growth.

- Comirnaty revenue collapsed 52%, while Paxlovid sales normalized, forcing Pfizer to accelerate its specialty and oncology pivot.

- Seagen’s $3.4B contribution bolstered oncology expansion, but $2.9B in Q4 impairments reflect pipeline volatility.

- Cost-cutting efforts saved $4.5B, yet Seagen integration and high R&D ($10.8B) demand disciplined execution.

- Health Care > Pharmaceuticals

TradingKey - After a generation-defining bonanza of COVID-19 vaccines and antiviral therapeutics, Pfizer reaches a crossroads. The pandemic-era goliath of biopharma, whose reach was once celebrated as well as its blockbuster franchise, is today reshaping its anchor as pandemic-driven revenue evaporates. Despite a spectacular collapse in Comirnaty sales and whipsawing fluctuations from Paxlovid's reco...",
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    {
      "id": "55bf7134-83c0-4d04-8657-1979536857f8:PMC11347277:4",
      "title": "Examining media’s coverage of COVID-19 vaccines and social media sentiments on vaccine manufacturers’ stock prices",
      "url": "https://pubmed.ncbi.nlm.nih.gov/PMC11347277?utm_source=valyu.network&utm_medium=referral&utm_campaign=ai_pilot&utm_content=ai_query",
      "content": "## Results

To address RQ1 which aimed to uncover the key topics on COVID-19 as featured in the media, topic modelling was run with results reported in Table 3 and topic prevalence in Figures 2 – 4 . A total of 10 topics were generated encompassing topics relating to (1) late-stage vaccine trials, (2) vaccine mechanism, (3) politicisation of vaccines, (4) disruptions in vaccine delivery, (5) stock market discussions, (6) vaccine delivery supply chain, (7) vaccines for children, (8) blood clots, (9) peak of COVID-19 waves and (10) boosters for COVID-19 variants. Examining the topic prevalence graphs, the results showed that topics varied in prevalence at different stages of the pandemic. For each plot, the 95% confidence interval is given by dotted lines.





Topics that were more prevalent in 2020 include those relating to vaccine trials, vaccine mechanism, politicisation of vaccination as well as stock market discussions. Following which, topics relating to vaccine delivery disruptions and the supply chain, as well as booster shots and blood clots ......",
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      "citation": "Shun Yao Bai & Edmund W. J. Lee (2024). Examining media’s coverage of COVID-19 vaccines and social media sentiments on vaccine manufacturers’ stock prices.https://doi.org/10.3389/fpubh.2024.1411345",
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