


Innovation Beta launched in 2018 to develop algorithms that identify investor conviction, which is crucial for achieving investment outperformance. Many academic studies highlight that the best ideas or strong conviction can lead to better investment results. Our journey began by applying machine learning techniques to investigate trading
Innovation Beta launched in 2018 to develop algorithms that identify investor conviction, which is crucial for achieving investment outperformance. Many academic studies highlight that the best ideas or strong conviction can lead to better investment results. Our journey began by applying machine learning techniques to investigate trading behaviors that might indicate a strong conviction. We explored numerous factors: Were the largest positions in a portfolio indicative? Did the most recent buys play a role? Was there an industry concentration or a high active share? The possibilities were extensive, and we meticulously analyzed the data to find answers. Ultimately, we discovered a measurement that effectively captured the essence of conviction, signaling opportunities to overweight certain stocks. Conversely, low conviction scores indicated stocks to avoid. Initially, our plan was to create a conviction-themed suite of indices and ETFs; however, the market demand for smart beta products from a smaller firm like ours wasn't sufficient. Instead, we found success with our highly searchable database, which provides valuable data for quants, financial executives, public and investor relations professionals, and journalists. Stay tuned as we prepare to reintroduce the Conviction signals for your review.
Welcome. @PortfolioStory is my place to share interesting tales about stocks and investing, utilizing genuine trades from experienced investors. Just like fingerprints at a crime scene, stock trading and portfolio construction reveal an investor’s thinking in a rapidly changing world. While no investor possesses the perfect crystal ball,
Welcome. @PortfolioStory is my place to share interesting tales about stocks and investing, utilizing genuine trades from experienced investors. Just like fingerprints at a crime scene, stock trading and portfolio construction reveal an investor’s thinking in a rapidly changing world. While no investor possesses the perfect crystal ball, changes in stock ownership can provide clues about future trends, contributing to potential investment outperformance. This is not investment advice, but readers may discover valuable insights into trading behaviors, as we believe that 'Every Portfolio Tells A Story.' Our most recent content can be found on X and LinkedIn before this site. Follow on X (Twitter) @PortfolioStory https://x.com/PortfolioStory LinkedIn: https://www.linkedin.com/in/tsgalbraith/ After years of working with institutional clients, we are now making our database more broadly available, incorporating machine learning techniques to enhance our offerings. Please give us some time to improve this page!
In 2020, the SEC proposed changing the reporting limit for investment advisors from $100 million to $3.5 billion, a change that would have removed over 4,000 advisors from the quarterly reporting requirement that has been in place for more than 40 years. This potential shift sparked concerns among investors who need more transparency, not
In 2020, the SEC proposed changing the reporting limit for investment advisors from $100 million to $3.5 billion, a change that would have removed over 4,000 advisors from the quarterly reporting requirement that has been in place for more than 40 years. This potential shift sparked concerns among investors who need more transparency, not less, especially regarding investment outperformance. Ultimately, the SEC decided not to move forward with the proposed change, but the uproar surrounding it underscored the importance of using data, including advanced machine learning techniques, to analyze trading behaviors and make informed decisions. Our letter to the SEC is available in the Download section.
"In the Balance" Excel notebook - Buyers and Sellers in Q1 2025 filtered by assets ranging from $400 million to $10 billion, and positions between 25 and 99. This data allows for insights into trading behaviors and highlights investment outperformance. Additionally, it includes the top 20 New Positions for the past 40 quarters, utilizing machine learning techniques to analyze trends.