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  • MSGM Stock Surge: Analyzing the 145.54% Increase in Motorsport Games’ Stock Price

    MSGM Stock Surge: Analyzing the 145.54% Increase in Motorsport Games' Stock Price
    MSGM Stock Analysis Concept

    Analyzing the Massive Surge in Motorsport Games’ (MSGM) Stock Price

    Motorsport Games Inc. (NASDAQ: MSGM) has recently caught the attention of investors with a remarkable surge in its stock price, skyrocketing by 145.54% to a current price of $2.75. This unexpected rise, accompanied by an increase in trading volume to 35,902,054, warrants a detailed examination of the factors contributing to this surge, the possible institutional trading patterns, and the inherently associated investment risks.

    MSGM Stock Price and Volume Trends
    MSGM Stock Price and Volume Changes – Last 3 Months

    Understanding Motorsport Games and Its Industry Position

    Motorsport Games Inc., a prominent racing game developer and publisher, has built its reputation on developing and publishing authentic simulation racing titles, including the well-regarded Le Mans Ultimate. Additionally, the company has expanded into the esports ecosystem with platforms such as rFactor 2 and KartKraft, bolstering its offering for a competitive advantage in the rapidly growing virtual racing industry. The company’s recent release of Le Mans Ultimate in Early Access demonstrates its ongoing commitment to delivering high-quality gaming experiences.

    Compliance with Nasdaq and Strategic Investments: Catalysts for the Surge

    One of the pivotal announcements that likely sparked investor interest in MSGM’s stock is the company’s recent announcement of regaining compliance with Nasdaq’s stockholders’ equity requirement, as noted on Globe Newswire on April 17, 2025. CEO Stephen Hood’s statement on the momentum gained through compliance, coupled with strategic investments, has reinforced investor confidence.

    Particularly noteworthy is the $2.5 million strategic investment led by virtual reality leader Pimax. This move not only strengthens the company’s financial position but also provides resources to accelerate product development, a critical factor in its compliance regain.

    In-Depth Analysis of Institutional Trading Patterns

    While there isn’t explicit insider trading or significant stock buyback activity on record affecting the stock’s movement, the surge in MSGM stock raises questions about potential institutional trading patterns. The large trading volume of over 35 million shares suggests strong institutional interest. These patterns often indicate a strategic position by hedge funds or investment firms anticipating future earnings growth driven by recent regulatory compliance and technological advancements in the racing game sector.

    Investment Risks and Considerations

    Despite the positive catalysts, investors should tread cautiously. The gaming industry, especially niche sectors like racing simulations, carries inherent volatility risks. The success of MSGM’s future products and esports expansions depends heavily on consumer acceptance and technology integration, particularly in collaborations like those with Pimax.

    Also, forward-looking statements from the company highlight expectations that may not materialize if market conditions change. Retail investors should be aware that current market sentiment may shift, and a high degree of volatility in the stock price is expected in the short term.

    Conclusion: A Balanced Outlook

    In summary, Motorsport Games’ (MSGM) stock surge reflects a confluence of strategic business maneuvers, compliance achievements, and potential institutional positioning. However, retail investors should evaluate the presented opportunities against possible economic shifts and industry-specific challenges. The exciting developments at MSGM underscore the importance of strategic investments, forward-thinking management initiatives, and risk-adjusted investment strategies.

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  • [v2.3.0] API Release Note

    New API Releases

    Insider Transaction News API

    An API has been launched that allows you to retrieve news content based on data analyzed from insider transactions.

    Stock Market Transfer API

    An API has been released to check information about the pre-listing market.

    Company Subsidiary Info API

    An API has been launched to retrieve information about subsidiaries of listed companies.

    API Changes

    New items have been added to the Close Price Data API.

    [Changed Items]

  • [03/26/25] New Update: Launch of the U.S. Politician Transaction Widget & More

    [03/26/25] New Update: Launch of the U.S. Politician Transaction Widget & More

    [WG] Want to Follow Nancy Pelosi’s Trades? The U.S. Politician Trading Widget v1.0.0 is Here!

    They say politics is just a side hustle—how about following Nancy Pelosi’s trades?

    Now, you can easily track stock transactions made by U.S. politicians and analyze trades related to the committees they belong to.

    • Top-performing stocks held by politicians

    • Stocks politicians are paying attention to

    • Stocks related to sectors overseen by political committees

    • Latest transactions of key politicians

    Check out Politician Transaction Widget →

    [Data Labs] Insider Transaction News Goes Live—And Stock Prices Follow!

    Does insider transaction news actually impact investment decisions?

    Now, you can check how much stock prices have risen after news about insider transactions is published.

    To support better investment decisions, we now provide recent stock prices, average insider purchase prices, and transaction amounts directly within the insider trading news section. Our goal is to enhance the feature so that you can invest using just the news alone.

    Explore Insider Transaction News →

    [Data QC] Corrected Disclosure Data Now Available with Waiker’s Data QC System

    Because disclosure data is manually entered, errors occur countless times daily. While some are corrected through revised disclosures, many remain uncorrected, making it difficult to ensure data integrity using raw parsed data alone.

    To address this issue, Waiker has been providing error codes for detected disclosure errors. With this update, we now provide not only error codes but also corrected values, affected fields, and detailed error messages!

    • AS-IS: Disclosure Error Detection → Provides an Error Code
    • TO-BE : Disclosure Error Detection → Provides an Error Code → Provides Corrected Values

    While many stock data providers display disclosure data as-is despite potential errors, Waiker goes further by offering detailed error information and corrected values, ensuring higher data reliability.

    Check out the Developer Center →

    [BDR] New Data Additions

    This update also brings new datasets to BDR:

    • Insider Transaction News API: Get updates on companies involved in insider transactions.

    • Subsidiary API: Retrieve information on a company’s subsidiaries.

    • Market Relisting API: Identify stocks that have changed their listing market.

    Access the API Guide →

    Preview Data in API Viewer →

  • [02/26/25] Updates including the launch of Insider Transaction News

    [02/26/25] Updates including the launch of Insider Transaction News

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

    [Data Lab] Want to Uncover the Meaning Behind Hidden Trades? ‘Insider Transaction News’ Launched

    We received feedback from users who were curious about whether insider trades held any significant meaning and what the recent trends among insiders were.

    Reading through all the news articles to find reasons behind these trades can be time-consuming. To help with this, Waiker uses AI technology to gather and analyze essential information related to trades and summarize it into concise articles.

    Insider Transaction News will provide compact insights from insider trading data, recent trends, and AI expert analyses.

    View Insider Transaction News →

    [Data Lab] The Secret of Top Investors: ‘Insider Transaction Screener’ Launched

    Discover insights from real-time insider transaction data using the Insider Transaction Screener.

    You can search by ticker, stock, insider name, and more, along with filters suggested by Waiker’s expertise. This tool is designed to help uncover valuable data-driven insights. A 7-day free trial is available now, so try it out today.

    Explore Insider Transaction Screener →

    Other Updates

    [Data Lab] Explore AI-Powered Services in the Market Data Lab

    Try out various features and datasets, including Waiker News, Waiker AI vs. LLM Comparison Service, and the Insider Transaction Screener.

    If you find Waiker’s experiments interesting, sign up to receive notifications for upcoming experiments.

    Go to Data Lab →

    [BDR] New Datasets Released in This Update

    • A new API for checking the composition of passive fund holdings has been added to BDR.

    • A new API allows you to view monthly insider buy/sell ratios.

    • View API Guide →

    • Preview Data in API Viewer →

    [Homepage] Now You Can Chat with Us in Real Time

    Click the chat button in the lower right corner of the homepage for quick and easy support.

    The Waiker team will assist you as quickly as possible with service usage, product purchases, and other inquiries.

    Contact Us →

    [Homepage] Check Release Notes in the Developer Center

    A new Release Note page has been added to let you easily track new features, improvements, and important announcements all in one place.

    View Release Notes →

  • [v2.2.0] API updates

    New API Release

    Monthly Insider Buy/Sell Ratio API
    A new API has been released that provides the monthly buy/sell ratio based on insider trading activities.

    Passive Fund Constituents API
    This API allows users to view the holdings of institutional investors’ passive funds.

    Institutional Investor API Updates

    Name Change:

    Previous: Active Institutional Investor → Now: Institutional Investor

    Endpoint Changes:

    • Base address for institutional investors:
      • Previous: /v1/basic/active-transaction → Now: /v1/basic/institution-transaction
    • 1-Year Profit Rank:
      • Previous: /investor/list → Now: /year-profit-rank
    • Holding Stocks Rank:
      • Previous: /most-held → Now: /most-held-rank
    • Portfolio Weight:
      • Previous: /guru/most-held → Now: /most-held-weight
    • Recent Quarterly Transactions:
      • Previous: /guru/recent-quarter-picks → Now: /recent-quarter
    • MDD:
      • Previous: /guru/mdd → Now: /mdd
    • Stocks Below Average Institutional Price:
      • Previous: /cheaper-than-institution → Now: /cheaper-than-average-price

    Deprecated API:

    The “Key Insider Transactions Briefing” API has been deprecated.

  • How to Utilize Passive Fund Holdings Data?

    Today, we would like to introduce our newly released Passive Fund or ETF (Exchange-Traded Fund) holdings data and discuss how to use this data effectively.

    What is Passive Investing?

    Photo by Precondo CA on Unsplash

    First, passive investing is an investment strategy that seeks to track the performance of a specific index or benchmark. Unlike actively managed funds, passive funds don’t involve portfolio managers actively selecting stocks or timing the market. Instead, they simply reflect the market index.

    Commonly known ETF products fall under passive investing and are typically associated with lower management fees and the potential for stable, long-term returns.

    1. Cost Efficiency: Passive funds generally have lower management fees compared to active funds, positively impacting investors’ long-term returns.

    2. Transparency: Since these funds track the the entire market or a specific index, the composition of the investment portfolio is clear and transparent.

    3. Diversification: Investing in a wide range of assets allows effective risk diversification across different stocks or industries.

    Market Shift: From Active Funds to Passive Funds

    Recent Passive Fund Trends

    Traditionally, fund managers have preferred active investment strategies. However, as the graph above shows, passive fund growth has surged in recent years.

    ETFs, in particular, offer investors convenient access to various asset classes, attracting both individual and institutional investors.

    Even in Korea, retail investors investing in U.S. markets have become familiar with tickers like SPY and QQQ, reflecting the growing popularity of passive investing.

    How to Use ‘Passive Fund Holdings’ Data?

    Example: Passive Funds Tracking the S&P 500

    The first way to utilize Waiker’s Passive Fund Holdings Data is by easily identifying ETFs and index funds that track a specific index.

    The image above shows search results for passive funds that track the S&P 500 or its derivatives. With Waiker’s data, you can easily view a list of passive funds following the index and gain quick insights into their size (assets, liabilities, etc.).

    Second Use Case: Identifying Tracking Errors

    Waiker’s data also provides the fund’s Net Asset Value (NAV), making it easier to calculate tracking errors. This allows you to conveniently apply trading strategies based on the difference between market prices and NAV.

    Tracking error is a crucial metric that shows how faithfully a fund replicates its target index. A lower tracking error means the fund reflects the index more accurately, which enhances investor confidence.

    Third Use Case: Utilizing Rebalancing Dates

    Index providers recalculate and manage the composition of the index on predetermined dates, such as quarterly or semi-annually.

    Inclusions and exclusions of specific stocks in an index can be interpreted as major positive or negative signals, making it important for investors to monitor these changes and dates carefully.

    The following example shows the holdings of a specific ETF. As of May 31, 2023, ProShares UltraPro QQQ held 1,249,343 shares of Tesla.

    ETF Holdings Data

    While passive funds primarily track specific indices, the composition and weighting of holdings can vary by fund.

    For instance, while the S&P 500 consists of 503 stocks, an actual fund might only hold 501 stocks. Therefore, understanding how many funds hold specific stocks, and to what extent, can help estimate potential buying or selling volumes on rebalancing dates.

    Passive Investing: Beyond Market Average Returns

    While passive investing is generally a strategy aimed at achieving market-average returns, passive fund data has evolved beyond that purpose.

    By applying precise data analysis, investors can optimize quantitative investment strategies using ETFs.

    In this article, we briefly introduced several strategies:

    1. Listing passive funds that track specific indices

    2. Optimizing ETF selection using tracking error analysis

    3. Developing precise investment strategies based on rebalancing timing

    How are you using ETF data? If you have your own passive investment strategies, feel free to share them!

    John C. Bogle:

    “Don’t look for the needle in the haystack. Just buy the haystack!”

  • Cluster Trading Analysis on Insider Transactions

    What is Cluster Trading?

    Cluster trading refers to the scenario where insiders of a company engage in similar transactions (buying or selling) within a specific period. When insiders, who have deeper knowledge of a company’s internal matters, engage in such actions, their trading behavior can provide useful insights into the company’s future prospects, potentially influencing stock prices. Furthermore, if multiple insiders simultaneously engage in transactions in the same direction, it can increase the reliability of the information from those insider trades.

    This hypothesis was empirically tested using insider trading data from Waiker.

    Analytical Method

    1. Definition of Cluster Trading:
      • A cluster trade is defined when at least 4 insiders trade in the same direction (buying or selling) within 30 days of the initial insider trade date.
    2. Performance Measurement:
      • The performance of stock price is tracked for up to 60 trading days following the initial insider trade date to calculate cumulative returns.
    3. Cluster vs Non-Cluster:
      • Cluster trades are compared with non-cluster trades (defined as insider trades that do not meet the 4 insiders threshold).
      • Average cumulative returns for both cluster and non-cluster trades are calculated for comparison.
    4. Comparison of Results:
      • The performance of cluster trades is compared with non-cluster trades over various timeframes (20, 40, 60 trading days) to analyze the potential benefit of cluster trading.

    Results of the Analysis

    • Cluster Trading Outperforms Non-Cluster Trading:
      • Non-cluster trades exhibit lower returns compared to cluster trades at 20, 40, and 60 trading day intervals (as seen in the blue-highlighted cells in the table below).
      • Annualized Returns:
        • At the 20 trading-day mark, cluster trading yields 11.31% higher returns than non-cluster trading.
        • At the 40 trading-day mark, cluster trading outperforms by 14.53%.
        • At the 60 trading-day mark, cluster trades result in 9.05% higher returns.
    • Cluster Trades Show Consistent Performance Over Time:
      • Cluster trades demonstrate a steady performance over time, while non-cluster trades do not show similar long-term results.
    • Optimal Holding Period:
      • The best performance for cluster trades occurs with a 20 trading-day holding period, which indicates that the value of the insider information from cluster trading diminishes over time.

    Key Findings

    • Cluster Trading Signals:
      • When 4 or more insiders engage in buying transactions within the past month and there are no selling trades, the likelihood of a positive performance is high.
    • Cluster Trading Stability:
      • Cluster trades tend to provide more stable and consistent returns than non-cluster trades.

    Performance Summary:

    Cluster PeriodNumber of InsidersSample SizeBuy/Sell20-Day Avg. Return (Annualized)40-Day Avg. Return (Annualized)60-Day Avg. Return (Annualized)
    Cluster Trading4 Insiders32,524Buy2.49% (34.4%)3.74% (24.65%)4.34% (18.52%)
    Non-Cluster–68,429Buy1.75% (23.09%)1.62% (10.12%)2.29% (9.47%)

    Note: The table presents both the cumulative returns and their annualized values for comparison.

    Time-series Changes in Average Return

    Conclusion

    • Cluster Trading’s Advantage:
      • Insider transactions that occur in clusters (with 4 or more insiders trading in the same direction) significantly outperform non-cluster trades in terms of return.
      • Cluster trading tends to provide more consistent and stable returns, especially when compared to non-cluster trades.
      • Optimal Holding Period: The ideal holding period for cluster trades is 20 trading days, beyond which the value of the insider information tends to decrease.
    • Insights for Investors:
      • Cluster trades offer a strong signal for investors looking for stable returns and insider-driven insights into stock price movements.
    • Data Availability:
      • Detailed cluster trading data is provided by Weikher’s Insider Trading Database, allowing investors to access valuable insights on insider trading patterns and trends.

  • Hana Securities Co.,Ltd secures new content with ‘AI Insider Signal’

    Hana Securities is committed to leveraging artificial intelligence (AI) technology and global financial data to offer investors more precise and reliable insights. In collaboration with Waiker, Hana Securities has newly launched the ‘AI Insider Signal’ service within its mobile trading system, OneQ Pro. This service visualizes stock trading data of key corporate insiders, helping investors better understand insider trading trends.

     

    Waiker, a partner of LSEG (London Stock Exchange Group), specializes in AI-driven stock market data analysis and widget services. With its proprietary data verification system, Waiker analyzes insider trading information in real time using both domestic and international disclosure data. The ‘AI Insider Signal’ service provides not only key insiders’ stock transactions but also unique investment insights, such as consecutive trades, group transactions, and outperformance compared to AI-based indices. The data is visualized to enhance user experience, making it more accessible and intuitive for investors.

     

    Through this collaboration, Hana Securities has expanded its AI-powered financial data offerings. The company stated, “We will continue to strengthen our AI capabilities to develop specialized financial market content that differentiates us in the industry.”

  • Shinhan Securities Co.,Ltd. provides international news through Waiker.

    Shinhan Securities’ adoption of overseas news is a prime example of how AI technology can create tangible value in the financial industry. By utilizing Waiker’s AI technology, which offers innovative financial data solutions, Shinhan Securities has successfully implemented a service that translates and summarizes overseas stock news on their mobile trading system (MTS), Shinhan SOL.

     

    The overseas stock news service is based on Reuters news provided by global financial data company LSEG (formerly Refinitiv). Waiker translates and summarizes these news articles in real-time using AI algorithms, helping investors quickly and efficiently grasp information about U.S.-listed stocks. The service is delivered alongside the original English text to enhance the reliability of the information and support investors in making more accurate decisions. Waiker’s AI technology goes beyond simple translation and summarization; it combines natural language processing (NLP) and data analytics to systematically organize and process vast amounts of financial data. This allows Shinhan Securities to offer a differentiated investment experience to clients, successfully enhancing their competitiveness in overseas stock investments.

     

    Jeon Hyung-sook, Head of the Platform Group at Shinhan Securities, said, “Through AI-based overseas news provision and ‘similar businesses’ information services, we are now able to deliver both domestic and international investment information to clients quickly and easily. We will continue to leverage AI technology to provide even more valuable information to our clients in the future.”

     

    Shinhan Securities’ implementation of overseas news is a prime example of how AI technology can create practical value in the financial industry.

  • The Value of U.S. House Representatives’ Stock Transaction Data

    The Value of U.S. House Representatives’ Stock Transaction Data

    Backtesting the stock trading data of U.S. House members from Waiker’s politician transaction dataset revealed that many U.S. politicians achieved market-beating returns in 2023. The dataset allows for the examination of returns by individual politicians and their affiliated parties. The results suggest that certain politicians may have benefited from an informational advantage inaccessible to the general public. Below are some particularly noteworthy statistics:

    1. Key Returns and Performance

    The top 5 House members by stock trading returns in 2023 are as follows:

    • Democratic Rep. Brian Higgins: 238.9%

    • Republican Rep. Mark Green: 122.2%

    • Republican Rep. Garret Graves: 107.6%

    • Republican Rep. David Rouzer: 105.6%

    • Democratic Rep. Seth Moulton: 80%

    Additionally House Speaker Nancy Pelosi recorded a return of 65.5%, ranking among the higher-performing members.

    Given that the S&P 500 Index recorded an annual return of 23.8% in 2023, these results indicate substantial outperformance. Notably, Democratic Rep. Brian Higgins achieved a remarkable return of 238.9%, a performance level far beyond what most average investors could expect.

     

     

    From a party perspective:

    • Democratic House members recorded an average return of approximately 33.0%,

    • Republican House members achieved an average return of 19.0%.

    The higher returns of the ruling Democratic Party members are analyzed as a result of the government promoting policies to support sustainable technological innovation. Democratic lawmakers tend to focus their investments in sectors such as artificial intelligence (AI), cloud computing, and renewable energy technologies.

    The report shows that lawmakers have a tendency to concentrate their investments in specific industries. Notably, the technology and energy industries were the sectors that garnered the most interest among politicians throughout 2023, reflecting the policy differences and interests of each party in their trading tendencies.

    Conclusion

    Politician transaction data is not merely intriguing but serves as a valuable tool for investors to develop actionable strategies. Politicians are often directly or indirectly exposed to critical information related to economic policies, legislative changes, and industry regulations. Analyzing trading patterns based on this information offers practical insights for predicting market trends.

    By studying the industries that politicians frequently trade in or the timing of their concentrated transactions, investors can better anticipate which sectors might experience future growth. Actively analyzing such data can enhance investors’ ability to predict significant market changes and adapt their strategies accordingly.