About
Market analysis at Bayesian Edge focuses on the intersection of data science and research into the fundamental narratives that drive markets. We are strongly influenced by Bayesian inference. Our models and quantitative research emphasize time-varying parameters, because financial market participants value recent data more highly than older data or information. We apply many of the concepts from physics, including phase transitions for analyzing major shocks that take an economy far from equilibrium, complex systems analysis with behavioral feedback, and respect for the "arrow of time" that limits the ability to return to old ("normal") equilibrium. We avoid a dependence on bell-shaped probability curves or Gaussian assumptions, allowing for highly skewed or even bi-modal distributions to better capture tail risk in financial markets. We pay special attention to developments that matter for context, such as demographics, geopolitics, climate, etc. We use mathematics to enforce our logic, yet we insist that our concepts be explained in an intuitive manner.
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Commentary includes short narratives on key topics impacting global markets.
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Fed policy shifts
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Geopolitical risks
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Artificial Intelligence, jobs, and economic growth
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Mag-7 and AI market impacts
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Tariffs and their responses (in the land of eye for an eye, there are many blind people)
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Risk Management challenges from tail risk and lack of correlation stability
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Information from options strikes, volumes, and open interest for estimating market risk
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Evolution of Prediction Markets
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Research Projects describe a few of the Bayesian-Inspired data science projects currently in progress.
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Pattern shift recognition with Time-Varying Parameters
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Factor and momentum models for commodity trading
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Distribution independent risk-return probability analysis (bell-shaped curves not required)
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Changing dynamics of Federal Reserve Forward Guidance and federal funds futures markets
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Research Archives includes links to a selection of previously published academic and business press research.
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Physics of Phase Transitions applied to the Pandemic of 2020
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Tariffs are American as Apple Pie
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Bayesian-inspired asset allocation research
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Challenges with back-testing, simulations (models work until they don't, understand why)
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Liberal arts and management science
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Consulting Services describes the various opportunities for working with Blu Putnam.
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Regular market commentary
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Research white papers
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Webinars, conference or event presentations
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Internal data analysis for sales and marketing (not limited to finance industry)
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Strategic planning (not limited to finance industry)
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Independent board member or advisor (not limited to finance industry)
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Biography provides a brief summary of Blu Putnam's career and a link to the long-form version of his resume.