Posted this video on X/Twitter under @vecvizanalytics pre-market on the morning of 5/19/25 with the comment $TLT as of the 5/16/25 close, reviewed using systematic channel analysis, machine learning, and narrative in vide below. Pre-market on 5/19 TLT is at the 0.382 level of Nov2019/ Dec2023/Jan2025 anchored vs10. #stocks #analytics #quantfinance #charts We intend to […]
TLT as of 5/16/25, followed by methodology Explanations Read More »
Posted this video on X/Twitter under @vecvizanalytics on the morning of 5/16/25 with the comment “Do you agree that 593 is likely tough resistance?”. We intend to post case studies on X/Twitter first, to establish a “time-stamp”, then add the content here. If you are interested in methodological linkages to established quant finance principles, a
SPY at the 5/15/25 close, Followed by methodology Explanations Read More »
Posted this video on X/Twitter under @vecvizanalytics pre-market on the morning of 5/15/25 with the comment “$UNH chart looks like TDG circa March 2020 as per Vector Model chart shape metrics. That would be a good thing bulls over 3m-6m. Conversely, if UNH has truly “leveled down”, we show the case for settling in at
UNH at the 5/14/25 close, followed by methodology Explanations Read More »
Posted this video on X/Twitter under @vecvizanalytics on the afternoon of 5/13/25 with the comment “$NVDA strong today. Video below explores the near /intermediate term upside. Shows potential gap in resistance between $135 and $141, but Vector Model indicates absent an unusual bullish lift or catalyst getting past $143 probably takes a month.” We intend to
NVDA as of 5/12/25 close, followed by methodology Explanations Read More »
In this post we use VecViz’s dashboards to examine the strongest Vector Sets for SPY anchored to tops or bottoms occurring in the pre-Covid period of Trump’s first term to see what insights they offer at this moment. Vector Set vs2: Anchored by 2016-2018 Turning Points As of yesterday’s close (April 2, 2025), the second
SPY and the 2025 Tariffs from a Vector Perspective Read More »
We are experts in neither Nvidia (NVDA) nor DeepSeek. We are neither endorsing nor seeking to refute the headline above, but given headlines such as this we seek in this post to demonstrate how to use VecViz’s dashboards to explore DeepSeek’s potential impact on the price of NVDA, and then how to layer in the
NVDA / Deepseek VecViz Dashboard Use Case Example Read More »
VST (Vistra) has been a top performer this year, and is up ~6% today (as of 2:30pm) in the context of a modestly lower S&P 500. Though we lack VecEvents for Vistra we use the V-Score closest comparables and Vector Strength Histogram to seek some cognition of risk and opportunity, or at least questions to
“High Flyer” Case Study: VST on 9/25/24 Read More »
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
Mitigating Common Mean Variance Optimization Process Challenges Read More »
In this case study we illustrate how the VecViz’s Dashboards, can improve understanding of and provide fertile material for dialogue related to a price forecast by (1) placing the forecast in the context of the strongest historical price channel trajectories (i.e., Vector Sets) supporting it, (2) providing related probability estimates, and (3) allowing for efficient
Analyst Price Forecast Evaluation Case Study: Gold as of 9/13/2024 Read More »
With “#stockmarketcrash” trending on Twitter / X pre-market yesterday morning, and as a counterpart to “SPY 572… 22 points (and a paradigm shift?) away“, in which we explored the SPY’s upside prospects, here we use the VecViz Dashboard platform to explore the downside prospects of the SPY. We consider the 1 month forward time horizon
SPY as of 9/9/2024: Downside Cognition Case Study Read More »