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Streetwise Professor was founded in 2006 by Craig Pirrong, a professor of finance at the University of Houston's Bauer College of Business. Pirrong started the blog as a platform to share his insights on financial markets, commodities, and economic policy, drawing from his academic expertise and industry experience. The idea was to provide in-depth analysis of complex financial topics in a more accessible format for a broader audience. Streetwise Professor remains independently owned and operated by Pirrong. Based in Houston, Texas, Streetwise Professor primarily covers topics related to financial markets, commodities trading, energy economics, and regulatory policy. While not a traditional news outlet, the blog offers commentary and analysis on current events that impact global markets and economies. Pirrong's posts often delve into the intersection of finance, politics, and policy, providing readers with a unique perspective on how these factors influence market dynamics. One interesting fact: Despite its focus on complex financial topics, Streetwise Professor has gained a reputation for using colorful analogies and pop culture references to explain intricate market concepts. Pirrong often draws parallels between financial market behavior and themes from literature, history, and even sports, making his analysis more engaging and accessible to readers from various backgrounds.
streetwiseprof is ranked N/A among other media sources and has an average of 8,513 monthly visits according to Similar Web.
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streetwiseprof has a Bias Score of 28% Somewhat Conservative which is based on a variety of factors including its policy and politician leanings, article ratings, and the use of biased language. Its Reliability is rated as Limited, and additional analytical insights are available in the other tabs.

  • Bias Rating

    28% Somewhat Conservative

  • Policy Leanings

    12% Somewhat Conservative

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    Limited Reliability

    *Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.

  • Politician Portrayal

    49% negative

Ratings are based on recent news using data science and A.I. technology.