OaR Performance Report Summary: 2/01/2025

VecViz’s analytic performance reports document the behavior and performance of our analytics. This post focuses on the “VecViz Opportunity At Risk (OaR) Performance Report” as of February 1, 2025, Here we will summarizes the key findings, and explain how to use the report to investigate the performance of specific tickers. You can find this report on the “Reports” section of the VecViz website, along with updated reports over time.

OaR is the maximum amount of gain you could lose out on as of the end of a specified time horizon, at a specified level of probability, by being uninvested. OaR is likely of interest to return seeking / risk tolerant investors, as a tool to help them imagine their upside. OaR should be of interest to risk adverse investors, and especially short sellers. OaR is also relevant to investors in the options market, although less so than our Option Fair Value Estimates and their associated Performance Report.

Performance Metrics Utilized in the OaR Report

The OaR Performance Report compares the behavior and performance of 95% and 99% OaR calculated by VecViz’s Vector Model to the same as calculated by VecViz’s implementation of the Sigma Model. The primary performance metric is the Breakage Rate, and the secondary metric is the Return on Long OaR Based Capital (ROLOBC).¹

OaR Breakage Rate

OaR breakage occurs when actual gains exceed the OaR estimate. The primary goal of an OaR estimate is a breakage rate consistent with stated intentions: 5% for 95% OaR and 1% for 99% OaR. Ideally, breakage would be randomly distributed across model dates and tickers., and so we also evaluate the consistency of the breakage rate accordingly.

ROLOBC

For a given average breakage rate, an OaR estimate that is less aggressive for tickers with below-average returns and more aggressive for tickers with above-average returns is preferable. Such an estimate would yield attractive ROLOBC (see our FAQ or the report introduction for a definition). Maximizing ROLOBC is an important, though secondary, criterion for evaluating OaR performance.

The OaR report considers the “alpha” and “beta” of Vector Model OaR relative to Sigma’s OaR² a couple different ways, detailed in the tables below, to help determine whether differentials in ROLOBC performance are due to OaR differentials across tickers or relative changes in OaR over time.

95% & 99% OaR Summary Tables

We summarize how well the Vector Model fits these criteria relative to Sigma in the table below, for each of the six time horizons (denominated in trading days, where 21d ~= 1 month, 252d ~= 1 year).  Where the Vector Model better fits the criteria we enter a “V”, and where Sigma is superior, we enter an “S”.  For sake of brevity, we present here results only for the entire out of sample performance record (“ALL TMD” = all ticker model dates, but the complete report also specifically addresses the trailing 1 year, 3 month, and 1 month time lookback windows.

95% OaR, ALL TMD (all ticker – model dates and associated forward horizon performance to the extent passage of time allows from 1/31/2022 – 1/30/2025)	1d	10d	21d	63d	126d	252d	1d V / S	252d V /S	page(s)
Average OaR Estimated Gain Aggressiveness	V	V	V	V	V	V	6.6 / 4.0	106.7 / 63.7	15
Average Breakage Proximity to 5.00%	V	S	S	V	V	V	4.32 / 4.05	5.15 / 11.12	26
Breakage Consistency Across Model Dates	V	V	V	V	V	V	na	na	35, 37, 39, 41, 43, 45
Breakage Consistency Across Tickers	S	S	S	V	V	V	na	na	47-52
Average ROLOBC	V	V	V	V	V	V	0.05 / 0.04	24.44 / 15.08	27
VM ROLOBC Alpha Across All TMD’S	0.00	0.08	0.15	0.46	0.95	3.03	na	na	27
Average VM ROLOBC Alpha By Ticker, Across All Model Dates	0.00	0.05	0.01	-0.12	-1.22	-1.72	na	na	27

99% OaR, ALL TMD (all ticker – model dates and associated forward horizon performance to the extent passage of time allows from 1/31/2022 – 1/30/2025)	1d	10d	21d	63d	126d	252d	1d V / S	252d V /S	page(s)
Average OaR Estimated Gain Aggressiveness	V	V	V	V	V	V	12.6 / 5.7	167.6 / 90.0	110
Average Breakage Proximity to 1.00%	V	V	V	V	V	V	1.11 / 1.37	2.11 / 4.87	121
Breakage Consistency Across Model Dates	V	V	V	V	V	V	na	na	129, 131, 133, 135, 137, 139
Breakage Consistency Across Tickers	S	S	S	V	V	V	na	na	141-146
Average ROLOBC	V	V	V	V	V	V	0.07 / 0.04	24.71 / 15.05	122
VM ROLOBC Alpha Across All TMD’S	0.00	0.03	0.14	0.32	0.53	1.51	na	na	122
Average VM ROLOBC Alpha By Ticker, Across All Model Dates	0.00	-0.02	0.02	-0.34	-1.00	-0.66	na	na	122

Summary Conclusions:

Over the period studied, which includes both the bear market of 2022 and the bull market that followed up through most of January 2025, both 95% and 99% Vector Model OaR levels:

1. were typically more aggressive than Sigma OaR;
2. had breakage rates closer to target for nearly every horizon;
3. exhibited breakage rate consistency across tickers inferior to Sigma for shorter horizons, but superior for longer horizons;
4. exhibited greater breakage rate consistency across model dates than Sigma for all horizons;
5. had higher ROLOBC than Sigma for every horizon;
6. had positive ROLOBC alpha across tickers and model dates for every horizon beyond 1d. This was driven primarily by alpha across tickers, particulalry for longer term horizons.

These strong results for the Vector Model relative to Sigma are fairly consistent across the trailing 365d, 90d, or 30d windows, They are not significantly changed when any of the seven major ticker groupings we identified were excluded from the analysis, including Cryto & Meme related stocks, regional banks that ultimately failed, the Mag7, the semiconductors, the small caps, and debt oriented ETF’s and closed end funds. See the report’s Appendix for associated detail.

For further ticker level inquiry visit the Dashboards page. There you can:

1. see OaR estimates as of yesterday’s close overlaid upon VecViz’s Vector Strength Histogram and detailed in a table. VaR estimates are presented alongside these OaR estimates, and may also be of interest;
2. view a chart of 95 and 99% OaR for the Vector Model and Sigma for the entire out of sample period, for each of the 6 time horizons;
3. view a table that provides the 95% and 99% OaR breakage and ROOBC³ for any ticker (or group of tickers) for an evenly spaced sampling of 20 model dates across the entire out of sample back testing / live daily production period;
4. see how OaR has varied with the issuer’s V-Score over those same 20 evenly spaced model dates spanning the entire out of sample back testing/ live daily production period.

Note that the dashboards are best viewed on a desktop or laptop, that there are 8 of them, they load progressively as you scroll down, with a few of them taking 15-30 seconds to initially load. After the initial load they load much quicker as you toggle between tickers, horizons, etc.

Appendix: Ticker Level OaR & ROLOBC Performance Report Inquiry

When we press “Ctrl-F” on the VaR report pdf file and enter “NVDA”, for example we learn that it appears 171 times in the document. Clicking through the search results we learn that NVDA was (for most horizons and lookback windows unless otherwise noted) a

• “Top 30” ticker with regard to: OaR Breakage for Sigma, OaR Breakage for Vector Model for longer horizons only, ROLOBC for Vector Model and Sigma, Vector Model vs Sigma OaR and ROLOBC differentials;
• “Bottom 30” ticker with regard to: ROLOBC for the prior 30d window for Vector Model and Sigma, Vector Model vs Sigma OaR Breakage differentials, and Vector Model vs Sigma ROLOBC differentials for the prior 30d lookback window.

1. See our FAQ page for definitions of the Vector Model, Sigma, OaR, ROLOBC, and many other terms. ↩︎
2. We ascribe underlying ticker-model date forward horizon price returns to Sigma, so the Alpha and Beta can also be said to be relative to the underlyting ticker model date forward horizon price returns as well. ↩︎
3. A predecessor metric to ROLOBC is ROOBC, which is essentially ROVBC for short sellers. ROOBC is positive when the underlying ticker price declines, and vice versa. Higher ROOBC is preferable to lower ROOBC. In retrospect we realize that ROLOBC is of interest to a broader audience and we will be endeavoring to replace ROOBC with ROLOBC within our dashboards in the weeks ahead. ↩︎