Methodology

Support and Resistance’s Evolving Definition

VecViz provides “Support and Resistance Based Investment Analytics”. Support and Resistance are long standing, popular concepts in technical analysis. However, the definition of neither “Support” nor “Resistance” has ever been well settled, let alone the methodology for identifying and measuring it.  In the table below we summarize four papers from academia that focus on Support […]

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Mitigating Common Mean Variance Optimization Process Challenges

Mean Variance Optimization is primarily the concern of institutional investors and quants, but this blog can still be of interest to individual investors who actively consider their personal asset allocation. With month end, quarter end, and fiscal year end approaching, many institutional investment teams are in the late innings of portfolio strategy and asset allocation

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Comparing VecViz’s V-Score to a Chart Image Recognition Based model recently Featured in the Journal of Finance

When a recent contact forwarded “(Re-)Imag(in)ing Price Trends” to me this spring, I was greatly heartened. I knew my undertaking in developing VecViz’s Vector Model and V-Score – distilling predictive performance insights from price history charts, was ambitious. I believed that I had done so, but convincing others that it was even theoretically possible was

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An LLM’s Comparison of VecViz to Established Vol Models

Comparison can aid definition. In other blog posts we have discussed the approach of VecViz and its Vector Model to price probability. Here we seek to further illuminate that approach through qualitative comparison to a few well-established volatility model archetypes that enjoy significant institutional money manager use. Specifically, we seek to compare the Vector Model

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Realistic Vol Estimates through Support, Resistance and Machine Learning

“Sigma” vol is familiar and easy but has important flaws. “Sigma” type volatility metrics that rely on assumptions of normally, independent, identically distributed returns have many shortcomings when applied to financial markets, including: More realistic, established vol models are challenging to implement. Sigma’s shortcomings have for decades motivated the creation of many flavors of “local

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“Vector Strength” quantifies support and resistance

Vector Set Strength decreases with distance and time Like the wake behind a speedboat, Vector Set Strength generally dissipates with distance and time from the model date price. Therefore, Vector Sets anchored by recent tops and bottoms have greater strength than those formed from tops and bottoms that occurred in the distant past. Likewise, Vector

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“Let me warn you…” of the limitations of VecViz’s Analytics.

“Let me warn you, Icarus, to take the middle way, in case the moisture weighs down your wings, if you fly too low, or if you go too high, the sun scorches them. Travel between the extremes.” Ovid, Metamorpheses Similar to Daedelus’ warning to Icarus regarding his wings, VecViz advises you use the Vector Model

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