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  • Seeking alpha in US senators’ stock transactions

    Seeking alpha in US senators’ stock transactions

    To analyze the relationship between information asymmetry and the returns generated when U.S. senators use political information to trade stocks, this review examines the study titled “A Dilemma of Self-interest vs Ethical Responsibilities in Political Insider Trading” by Jan Hanousek et al., published in the Journal of Business Ethics in October 2022. The study empirically investigates whether senators’ stock trades contradict social contract theory and explores the informational value of their transactions.

    Methodology

    This study is based on a dataset of 8,064 securities transactions, including 7,092 stock trades disclosed by U.S. senators under the STOCK Act between 2012 and 2019. To measure the information asymmetry associated with senators’ transactions, the study employs Abnormal Idiosyncratic Volatility (AIV), a metric that captures changes in stock volatility during specific events and is particularly suited for evaluating the likelihood of trades based on insider information.

    Key Points of Methodology

    • Abnormal Idiosyncratic Volatility (AIV): This measures the level of information asymmetry by analyzing volatility changes around trading days compared to normal periods.

    • Event Window: A 5-day event window (2 days before and after the trade day, including the trade day) was used to calculate abnormal volatility and compare it with other periods.

    • Focus: The study sought to determine whether senators’ trades generated higher AIV than major corporate events like quarterly earnings announcements or mergers and acquisitions (M&A), linking political insider information to stock returns.

     

    AIV Calculation

    1. Transaction Volatility (IVATT): Daily volatility during the 5-day event window was measured, excluding market-wide factors.

    2. Non-Transaction Volatility (IVNAT): Volatility during other periods of the year was calculated similarly.

    3. AIV: The difference between IVATT and IVNAT. A higher AIV indicates a greater likelihood that specific information influenced the stock on the transaction day.

     

    The study confirmed that senators’ stock trades are associated with significant abnormal returns. Specifically:

    • Stocks traded by senators recorded an average excess return of 4.9% over three months after the transaction date.

    • As shown in the data, senators’ trades consistently outperformed the market over holding periods of 1 week, 2 weeks, 1 month, 2 months, and 3 months.

     

    In terms of information asymmetry, senators’ trades recorded an average Abnormal Idiosyncratic Volatility (AIV) of 3.6%, which is three times higher than the 1.1% AIV observed during major corporate earnings announcements. This indicates that senators’ stock transactions are accompanied by significant information asymmetry.

    Such asymmetry suggests that the political information held by senators carries substantial value in the stock market and demonstrates that senators participate in market transactions from a privileged position of informational advantage over other investors.

    Conclusion

    This study confirms that senators’ stock trades induce information asymmetry and exhibit a strong correlation with stock price volatility. Specifically, the timing of their transactions aligns with heightened AIV, indicating that the information senators use is indeed reflected in stock prices.

    The existence of information asymmetry between U.S. politicians and the general public, coupled with the fact that senators achieve market-beating returns by holding stocks for three months after their purchases, suggests that trading based on senators’ political information could hold value as an investment strategy.

  • How are stock purchase disclosures by politicians related to stock prices?

    How are stock purchase disclosures by politicians related to stock prices?

    To explore the relationship between U.S. politicians’ stock purchase disclosures and stock returns, I reviewed the article titled “Perceptions of Political Self-Dealing? An Empirical Investigation of Market Returns Surrounding the Disclosure of Politician Stock Purchases,” published in the Strategic Management Journal in October 2022.

    Hypotheses and Methodology

    Hypothesis 1: The disclosure of stock purchases by senators will trigger a positive market reaction for the respective company’s stock.

    Hypothesis 2: If a senator serves on a committee that oversees a specific company, the market reaction will be stronger.

    Hypothesis 3a, 3b, 3c: When the company has lobbied on the senator’s legislation, testified in a committee where the senator serves, or has connections with the senator through campaign contributions, the market reaction to the senator’s stock purchase disclosure will be amplified.

    Methodology

    • Event Study and Cumulative Abnormal Return (CAR) Calculation: To measure the abnormal returns before and after the disclosure of senators’ stock purchases, they used the Fama-French 4-factor model to calculate CAR. They analyzed stock price changes across various event windows (e.g., disclosure day and the following day (0, +1), etc.).

    • Cross-Sectional Regression Analysis: To examine the impact of variables such as committee membership, lobbying activities, and campaign contributions on market reactions, they conducted an OLS regression analysis.

    • Information Asymmetry Check: To ensure that no information was leaked prior to the disclosure, they reviewed media coverage and conducted an additional event study for the actual purchase date.

    Between 2012 and 2020, 2,234 instances of senators’ stock purchases were used as the sample for Hypothesis 1, and 2,066 instances were used as the sample for the other four hypotheses.

    The above table shows the cumulative average abnormal returns (CAAR) analysis results for the impact of senators’ stock purchase disclosures on stock prices.

    Both the equally-weighted index (where equal weights are given to each event) and the value-weighted index (considering each stock’s market capitalization) recorded positive CAAR across all four event windows. The standardized cross-sectional test and the generalized sign Z values also show statistically significant p-values, supporting Hypothesis 1 that the market reacts positively for a certain period after a senator’s purchase disclosure.

    Table 2 reveals daily abnormal returns, capturing the stock price reaction before and after the senator’s stock purchase disclosures.

    On the disclosure day, the equally-weighted and value-weighted abnormal returns were 0.09% and 0.11%, respectively, both statistically significant. Conversely, before the disclosure, abnormal returns were either negative (D-3, D-2) or positive but not statistically significant (D-1, p>0.1). Thus, Table 2 provides evidence for Hypothesis 1, showing a positive market reaction on the disclosure day and the days following it.

    Finally, Table 3 uses cross-sectional analysis to examine the factors influencing abnormal returns following senators’ stock purchase disclosures.

    This analysis uses Ordinary Least Squares (OLS) regression to understand how various factors affect stock prices when senators’ stock purchases are disclosed. Each coefficient in the table indicates the effect of independent variables on CAAR.

    • Senator jurisdiction * lobbying the senator: When senators have lobbied for legislation benefiting a specific company, it has a significant positive impact on abnormal returns (coefficient 0.39, p = 0.02), supporting Hypothesis 3a.

    • Senator committee jurisdiction: When a senator serves on a committee overseeing the company’s industry, abnormal returns increase significantly (coefficient 0.57, p = 0.01), supporting Hypothesis 2.

    • Senator jurisdiction * campaign contributions: When companies make campaign contributions to senators, abnormal returns increase (coefficient 0.15, p = 0.02), indicating that campaign contributions may signal a positive relationship between the senator and the company, supporting Hypothesis 3c.

    • Senator jurisdiction * congressional testimony: The coefficient for this variable is -0.36, but the p-value is 0.35, which is not statistically significant. Therefore, Hypothesis 3b is rejected.

    Summary

    In summary, this study identifies short-term profit opportunities following senators’ stock purchase disclosures. Additionally, analyzing the historical or current relationships between senators and companies, such as committee memberships or lobbying connections, may also reveal opportunities for abnormal returns.

    Explore opportunities for generating abnormal returns by leveraging Waiker’s politician trading data.

  • [02/03/25] Updates including the launch of News Widget

    Hello, this is the Waiker team with our first release of 2025.

    [WG] Advanced Reuters News Widget v1.0.0 Launched

    A new widget is now available, making it quick and easy for anyone to consume Reuters news on mobile devices.

    🔍 ‘Stock Search’ to Find Only the News You Care About

    Search by company name or ticker to view news related to specific stocks. You can now access news on U.S. small and mid-cap stocks that were previously hard to find.

    🚀 Real-Time Advanced Reuters ‘News List’

    Access high-quality Reuters news in real time. We’ve resolved the issue of duplicate listings caused by updates or revisions to the same news article. If an article has already been published, it will now be grouped with the most recent updates for a cleaner, more organized feed.

    🎫 ‘AI Tagging’ That Pinpoints Only the Most Relevant Stocks

    No more sifting through full articles to identify related stocks or dealing with irrelevant tags causing confusion. With Waiker’s AI tagging technology, we highlight only the stocks that are truly relevant to the news, providing a clearer and more efficient experience.

    Get Straight to the Point with ‘AI News Summary’

    Whether it’s complex data, detailed reports, or lengthy interviews, you can grasp the key points without reading the entire text. Waiker’s AI-powered news summaries highlight the essentials, saving you time while keeping you informed.

    💬 Reuters News at Your Fingertips: ‘AI-Translated News & Original Text’

    No more awkward translations with generic tools. Now, experience seamless, market-specialized translations powered by Waiker’s AI technology. Enjoy Reuters news in natural Korean, with the option to view the original text anytime.

    [See Advanced Reuters News Widget]

    [BDR] Major API Updates

    New large-scale data APIs have been updated, including insider trading, active institutional investor transactions, and financial statements.

    🤵‍♂️ Updated ‘Insider Trading API’ with Group Transactions

    Now you can access a Group Transaction API that aggregates insider trades within a specific period from multiple insiders of a company. We’ve also made other insider trading APIs easier to use.

    🏢 Want to Follow the Masters of Investment? ‘Active Institutional Investor Trading API’

    If you’ve ever wanted to know where Warren Buffett is investing, this is for you! We’ve categorized data on trades made by major institutions. Who are the investment masters outperforming the market?

    📊 The Basics of Basics: ‘Financial Statements API’

    How’s the outlook for the company you’re thinking of investing in? Use the financial statements API to spot undervalued companies or those with poor financial health to guide your investment decisions.

    [See API Guide]

    [WG] Insider Transaction Widget v4.2.0 Update

    The major insider transaction widget has been renewed! Experience improved usability and new features, including continuous trades, trades by key positions, and sector-wise insider trading fluctuations.

    ⛓️ Continuous Trades

    You can now view consecutive trades made by the same insider for a single stock, bundled together for better insight.

    🎓 Trades by Key Positions

    See the trades made by insiders in key positions, including C-Level executives, major shareholders, and board members.

    🎉 Sector-wise Insider Transaction Changes

    Track the changes in insider trades across 13 different sectors on a weekly basis. You can also see which sectors have had new trades this week.

    [See Insider Transaction Widget]

    Purchase Waiker products online!

    🔐 Simple and Fast Signup

    Sign up for Waiker quickly without any complicated procedures, using just your email address. Whether you’re an individual user or a corporate customer, getting started is easy!

    You can now sign up and make payments on Waiker easily and conveniently in one place!

    💳 Transparent and Convenient Payment

    You can check various plans on the pricing page and make an immediate purchase of your desired product. With the newly launched personal plans, individual investors and general users can easily access Waiker’s diverse data. After payment, you’ll instantly have access to real-time data and a variety of services.

    Sign up now and experience Waiker’s powerful data services!

    [Sign up and start free trial]

  • Insider Buy/Sell Ratio and Market Trends

    Insider Buy/Sell Ratio and Market Trends

    Understanding market trends goes beyond price charts and economic indicators—sometimes, the most revealing signals come from within companies themselves. Insider trading data offers a unique lens into how corporate leaders view their own businesses, especially during times of market turbulence. In this article, we explore the relationship between the Insider Buy/Sell Ratio and the performance of the S&P 500 ETF (SPY), uncovering how insider behavior can serve as a powerful indicator of market sentiment and potential turning points.

     

    The chart above showcases a comparative analysis of the Insider Buy/Sell Ratio and the performance of the S&P 500 ETF (SPY) over time.

    Understanding the Buy/Sell Ratio

    The Buy/Sell Ratio is calculated as follows.

    1. Identify the number of stocks with positive insider net purchases (where net buy volume > 0) and compare it to the number of stocks with negative net purchases (where net buy volume < 0).

    2. Divide the former by the latter and subtract 1, creating an indicator that captures insider trading behavior within the market.

    This ratio is visualized as a time series on the primary y-axis (left), with markers and lines representing its trend.

    Description

    The chart clearly highlights key moments when the Buy/Sell Ratio spikes, coinciding with significant downturns in the broader stock market, as indicated by the S&P 500 ETF (SPY), plotted on the secondary y-axis (right).

    During periods of substantial market decline, insiders appear to increase their buying activity relative to selling. This behavior likely reflects their confidence in the long-term value of their companies, suggesting that insiders perceive these periods as opportunities to accumulate shares at discounted prices.

    Key Insights

    1. Market Declines Trigger Insider Activity: Noticeable spikes in the Buy/Sell Ratio occur during major market sell-offs, such as the financial crisis of 2008, the COVID-19 crash in early 2020, and other correction phases. These spikes suggest that insiders may act contrarian to the broader market sentiment, buying heavily when prices drop.

     

    2. Buy/Sell Ratio as a Contrarian Indicator: The trend indicates that the Buy/Sell Ratio could serve as a contrarian signal, potentially identifying periods of market pessimism where insiders foresee recovery or undervaluation.

     

    Implications

    This analysis underscores the potential predictive value of insider trading data. By tracking insider sentiment, market participants can gain insights into periods of heightened conviction among company insiders, particularly during market stress.

    The synchronization of these two metrics provides a fascinating perspective on market dynamics and insider confidence, offering a valuable tool for traders, investors, and researchers seeking to understand market cycles.

  • How Can U.S. Politician Trading Data Be Used for Investment?

    How Can U.S. Politician Trading Data Be Used for Investment?

    1. Why is U.S. Politician Trading Data Important?

    The stock trades of U.S. politicians hold particularly significant information for investors. U.S. politicians have the authority to propose or pass bills that directly impact the economy and industries. When politicians buy or sell large amounts of a specific company’s stock, it can hint at the government’s future policy direction for that company or industry. For example, if a politician who supports electric vehicles or renewable energy purchases stocks in that sector, it may indicate potential future policy support for these areas.

    2. Collection and Verification of Politician Trading Data

    Politician trading data is collected through various channels, and it’s crucial to verify this data and make it reliable. In the U.S., major asset movements by politicians are reported by regulatory agencies such as the SEC (Securities and Exchange Commission). Our company utilizes a strong QC system to collect and verify data from multiple sources, thereby enhancing data integrity and providing investors with highly reliable information.

    3. AI-Based Error Detection and Pattern Analysis

    Politician trading data involves various variables, and precise data analysis is essential for providing investment insights. Our AI-based error detection system automatically detects abnormal or unusual patterns in politicians’ stock trading records. For example, if a certain politician buys a large volume of stocks in a related industry right before proposing a bill, our AI quickly identifies this and can alert investors. This analysis helps in understanding the correlation between politicians’ actions and policy changes.

    4. Investment Strategies Utilizing Politician Trading Data

    Using U.S. politician trading data, investors can gain clearer insights into the future direction of industries and potential policy changes. For example, if key politicians sell healthcare company stocks while a healthcare reform bill is under discussion in Congress, this might signal that the bill may not pass or could negatively impact the industry. Conversely, if politicians are buying stocks in construction or materials-related companies while an infrastructure-related bill is being discussed, it could indicate stronger policy support for that industry.

    5. Real-World Examples Demonstrating the Importance of Politician Trading Data

    5-a. Nancy Pelosi’s Stock Trades

    Nancy Pelosi, the former Speaker of the U.S. House of Representatives, has long been under scrutiny for her stock trades. In 2021, her husband, Paul Pelosi, made significant profits by trading tech stocks such as Apple and Tesla. At that time, Speaker Pelosi was in a position to influence important legislation involving these companies, raising suspicions around these trades. This incident intensified debates over the potential for politicians to exploit insider information. [Source: Forbes, 2021]

    5-b. The Stock Sale Incident of Richard Burr

    In February 2020, U.S. Senator Richard Burr sold a significant portion of his stock portfolio just before the COVID-19 pandemic began to spread in earnest. He made this decision after receiving a confidential briefing on the economic impacts of the pandemic. After the stock market plunged, Burr’s trades were investigated for insider trading, although no charges were filed. [Source: NPR, 2020]

    5-c. Dick Cheney’s Halliburton Stock Trades

    Former Vice President Dick Cheney faced significant criticism over his stock trades involving Halliburton in the early 2000s, especially concerning the U.S. involvement in the Iraq War. Cheney had served as CEO of Halliburton prior to his vice presidency, and as Vice President, he played a role in securing Iraq War contracts for the company. His stock ownership led to public skepticism over political and ethical issues surrounding his investments. [Source: Time Magazine, 2003]

    6. Investment Insights Through Politician Trading Data

    Politicians’ stock trades provide vital clues to market trends. Politicians often have access to internal policy information, making their trading activities a potentially meaningful signal for the stock market. By leveraging U.S. politician trading data, our investment analysis system connects political movements with resulting market changes, offering timely and practical insights for investors.

    Conclusion: Using Politician Trading Data for Future-Focused Investment Strategies

    U.S. politician trading data offers investors unique and valuable insights. By analyzing this data, investors can understand the correlation between political decisions and industry trends and prepare for future market shifts. With data-driven analysis, investors gain an informational advantage, allowing for more strategic understanding and responses to market movements.

    References

    Summary

    This blog post now includes three different cases: Nancy Pelosi’s stock trading, Richard Burr’s COVID-19-related trades, and Dick Cheney’s Halliburton transactions. These cases demonstrate how politician trading activities have stirred controversy across various contexts, highlighting the significance of such trading as signals for investors.

    Posted by @Ava, @Jake, @Ethan, @Noah

  • How can insider transaction be utilized?

    How can insider transaction be utilized?

    Who is an insider?

    An insider typically refers to company executives and board members. In the United States and Canada, shareholders owning over 10% of voting shares also qualify as insiders, including venture capital firms and investment companies like Berkshire Hathaway. Insider trading encompasses these insiders’ stock buying and selling activities.

    Following Insider Buying

    Insider buying signals confidence, as insiders typically don’t purchase shares when expecting price declines. When multiple insiders buy company stock, it warrants attention.

    Following Insider Selling

    Insider selling patterns can provide valuable trading insights. Studies show that clustered transactions often yield reliable trading signals.

    Key Insider Trading Patterns to Watch

    1. Insider buying carries more weight than selling, as buying typically indicates profit expectation while selling can occur for various reasons.

    Example: [Insider Buying] SNDA / Sonida Senior Living, Inc.
    Sam Levinson purchased approximately 1.05 million shares on February 1, 2024. Following investment funding news, the stock price rose significantly during February-March.

    2. Executive transactions hold greater significance due to their access to critical information.

    3. Small company insider trading often provides more profitable signals due to limited public information.

    4. Clustered transactions offer more reliable signals than individual trades.

    Example: [Cluster Selling] AMR / Alpha Metallurgical Resources Inc.
    Clustered insider selling occurred from late February to early March 2024. Following executive changes and the selling pattern, the stock price declined significantly.

    How to Find Insider Trading Information

    While Form 4 filings can be monitored on the SEC website, this process can be time-consuming. Waiker’s insider trading data API or widget offers a more efficient tracking solution.

  • Waiker Awarded the 2024 CES Innovation Award in Artificial Intelligence

    Waiker, a global stock market data tech company, has been recognized with the 2024 CES Innovation Award in the Artificial Intelligence category. Among 25 global awardees at CES, Waiker stands as the only data company, earning international acclaim for revolutionizing the stock market data industry through its technological innovations.

    Through partnerships with LSEG Refinitiv, KOSCOM, and stock exchanges like NASDAQ, Waiker has developed groundbreaking stock market data products. The company’s technology successfully transforms complex market data into meaningful datasets that demonstrate high correlation with stock prices, overcoming previous limitations in speed and accuracy.

    Global securities firms and asset management companies are increasingly implementing Waiker’s technology-based stock market data products in their digital services, signaling a shift toward data-driven innovation in the financial investment industry.

  • Shinhan Securities Partners with Waiker for Cloud-based Open Platform

    Shinhan Securities Partners with Waiker for Cloud-based Open Platform

    Shinhan Securities has announced a Memorandum of Understanding with Waiker, an AI global stock market startup, to develop a cloud-based open platform. Shinhan Securities, a subsidiary of the Shinhan Financial Group and a cornerstone of South Korea’s financial industry since the 1960s, provides comprehensive financial services including securities brokerage, investment banking, and asset management.

    Waiker specializes in AI-powered global stock market database creation and utilization. The startup has secured an exclusive service contract with the London Stock Exchange Group (LSEG) for AI data services and supplies AI-powered US stock market analysis content to KBS using their specialized Large Language Model (sLLM).

    As Shinhan Investment Securities prepares to launch its open platform, the partnership with Waiker aims to establish a technological roadmap with clearly defined stages for mutual growth and success in the global market.

    Waiker CEO Elvin Hwang commented, “From our initial efforts collecting global stock market data, we identified areas where infrastructure for the stock market is underdeveloped in certain regions. Partnering with Shinhan Securities on the enhancement of global stock market infrastructure initiative through their open platform presented an attractive opportunity for Waiker.”

    Hyeong-sook Jeon, Shinhan Securities’ ICT Group head, stated, “Distinct from entities solely fixated on AI or data collection, Waiker’s prowess lies in swiftly and adeptly converting unstructured stock market data into AI-driven databases within a hybrid cloud environment. Making the company to become an apt prime partner for our open platform.”

    While tech giants like Amazon and Google have mainstreamed data and IT infrastructure integration in consumer goods and media, the financial sector has remained conservative in adopting modern technology. Shinhan Securities aims to address this gap by leveraging both companies’ technological competencies to establish solutions that will revitalize global stock trading and data infrastructure.

  • KBS and Waiker Pioneer Live Broadcast on US Stock Analysis based on AI LLM

    KBS and Waiker Pioneer Live Broadcast on US Stock Analysis based on AI LLM

    KBS (Korean National Broadcasting) has been utilizing Waiker’s AI content and technology since June 1. Through ‘Market Now’, a news corner of Newsline W, KBS has been live broadcasting U.S. stock news using Waiker’s technology. Aimed at assisting Korean investors in U.S. stocks, Market Now has reached a maximum daily viewership of 700,000.

    Waiker, a leader in AI natural language processing technology specialized in stock market data, has secured numerous domestic and international clients through successful projects. Their sLLM (Specialized Large Language Model) swiftly analyzes unstructured information related to the global stock market, converting it into a database and generating content according to customer needs. Years of sustained taxonomy and semantic DB construction have established their unique position in mining quality data and utilizing text-generative AI technology.

    KBS has validated Waiker’s solution for broadcasting real-time U.S. stock market events, economic indicators, indices, trading volume trends, and quotes. The broadcast covers insider trading information, earnings announcements, major contracts, management matters, and IB investment opinions.

    Korean investors, who maintain an annual net purchase of approximately $4.6 billion in U.S. stocks, face challenges in accessing information due to language and time barriers. KBS implemented Waiker’s solution to help viewers find meaningful information amid the data flood.

    The U.S. stock market is renowned for its market-friendly policies, capital raising capabilities, and liquidity, along with the industrial competitiveness and growth momentum of listed companies. This has attracted worldwide investors from Europe, China, and Japan. While Korea’s KOSPI has risen by an annual average of about 0.8% since early 2012, the S&P500 has averaged about 17% growth. U.S. stocks, being dollar-denominated, can provide a hedge effect when risk asset values decline.

    ‘Market Now’ broadcasts on KBS 1TV at 10:55 PM on Mondays and 10:50 PM Tuesday through Friday on NewslineW, offering viewers insights into U.S. economic and industrial trends.

  • Waiker develops AI technology specialized in stock market data and partners with LSEG for global data business

    Waiker develops AI technology specialized in stock market data and partners with LSEG for global data business

    Waiker announced on October 4th that it has entered into an exclusive Proof of Concept (PoC) contract with the London Stock Exchange Group (LSEG) to provide AI data services based on Large Language Model (LLM) to global investment banks, including Citi, HSBC, and Nomura. Starting from the fourth quarter, Waiker’s data services will be gradually supplied to LSEG’s global clients through the PoC contract.

    Founded in 2020, Waiker has developed AI NLP (natural language processing) models specialized in stock market data that accurately and swiftly convert target data from global companies’ various disclosures, investor relations, and news articles into its databases. Previously, Waiker entered into a Memorandum of Understanding (MoU) with Refinitiv, the world’s second-largest stock market data production and distribution company, now a subsidiary of LSEG. The startup has undergone technological verification for 15 months to validate its AI data extraction, accuracy, speed, and performance.

    Waiker CEO Elvin Hwang stated, “The contract signed with LSEG stipulates that target data from disclosures, news, and reports within the digital environment will be processed with AI and conveniently provided according to the demands of potential clients, including securities firms and asset management companies.” He added, “LSEG currently has over 40,000 clients, which implies that the product supply will be targeted towards these clients.”

    Over years of extensive R&D on NLP, Waiker has gained recognition for its potential within specialized fields compared to general-purpose LLMs. Company disclosures including business contracts, management decisions, M&A, and changes in beneficial ownership are unstructured, typically centering on text and including numbers and facts, thereby causing irregularities and ambiguities. Compared to data stored in database cell formats or annotated data within documents, it is nearly impossible to analyze and collect this information in one’s database through simple crawling or scraping.

    Therefore, the added value of such data is significant when utilized by securities and asset management industries, resulting in annual cost expenditures of hundreds of thousands of dollars per corporate client. Waiker AI will provide data according to client demand, automatically analyzing and datafying unstructured information into various languages including English and Korean, via over 7B training data.

    Waiker anticipates that the PoC and joint business contract will serve as a catalyst for its global revenue growth. The collaboration between LSEG and Waiker’s specialized Large Language Model (sLLM), which can datafy unstructured information of listed companies in major stock markets including the United States, India, Japan, China, and South Korea, is expected to establish global presence and serve as an opportunity to enhance mutual benefits for both companies.