Roze AI (RZAI)
Market Price (10/17/2026): $9.89 | Market Cap: $-Sector: Information Technology | Industry: Systems Software
Roze AI (RZAI)
Market Price (10/17/2026): $9.89Market Cap: $-Sector: Information TechnologyIndustry: Systems Software
Investment Highlights Why It Matters Detailed financial logic regarding cash flow yields vs trend-riding momentum.
Weak multi-year price returns2Y Excs Rtn is -89%, 3Y Excs Rtn is -133% | High stock price volatilityVol 12M is 246% Key risksRZAI key risks include [1] an uncertain U.S. Show more. |
| Weak multi-year price returns2Y Excs Rtn is -89%, 3Y Excs Rtn is -133% |
| High stock price volatilityVol 12M is 246% |
| Key risksRZAI key risks include [1] an uncertain U.S. Show more. |
Qualitative Assessment
AI Analysis | Feedback
Roze AI (RZAI) stock has lost about 55% since it went public on 9/30/2026 because of the following key factors:
1. Weak Financial Fundamentals and Business Model Concerns.
Roze AI reported a substantial 72.1% year-over-year revenue decline in fiscal year 2025, falling to approximately $2.3 million from $8.2 million in fiscal year 2024. This was accompanied by a widening net loss of $6.03 million in fiscal year 2025, compared to a $1.44 million loss in fiscal year 2024. The company also had negative operating cash flow, limited cash, and a thin balance sheet, leading to "going-concern" considerations being flagged in its filings. The company's project-based business, heavily concentrated in South Korea, was also vulnerable to macroeconomic uncertainty and a slowdown in the South Korean construction sector.
2. Direct Listing Structure and Increased Share Supply.
Roze AI's direct listing on September 30, 2026, allowed existing shareholders to sell 18.1 million shares, but the company itself did not raise any new capital, leaving it reliant on its existing, limited liquidity. Unlike traditional IPOs, direct listings lack the underwriting support that typically helps stabilize trading, which contributed to greater price volatility in the initial days. Furthermore, there is a potential for significant future dilution from 1.25 million Class C preferred shares that were sold for $10 million and are convertible into common shares at a potentially lower price. This immediate availability of shares from existing holders and the prospect of further dilution created substantial selling pressure on the stock.
Show more
Roze AI (RZAI) stock has lost about 55% since it went public on 9/30/2026 because of the following key factors:
1. Weak Financial Fundamentals and Business Model Concerns.
Roze AI reported a substantial 72.1% year-over-year revenue decline in fiscal year 2025, falling to approximately $2.3 million from $8.2 million in fiscal year 2024. This was accompanied by a widening net loss of $6.03 million in fiscal year 2025, compared to a $1.44 million loss in fiscal year 2024. The company also had negative operating cash flow, limited cash, and a thin balance sheet, leading to "going-concern" considerations being flagged in its filings. The company's project-based business, heavily concentrated in South Korea, was also vulnerable to macroeconomic uncertainty and a slowdown in the South Korean construction sector.
2. Direct Listing Structure and Increased Share Supply.
Roze AI's direct listing on September 30, 2026, allowed existing shareholders to sell 18.1 million shares, but the company itself did not raise any new capital, leaving it reliant on its existing, limited liquidity. Unlike traditional IPOs, direct listings lack the underwriting support that typically helps stabilize trading, which contributed to greater price volatility in the initial days. Furthermore, there is a potential for significant future dilution from 1.25 million Class C preferred shares that were sold for $10 million and are convertible into common shares at a potentially lower price. This immediate availability of shares from existing holders and the prospect of further dilution created substantial selling pressure on the stock.
3. Reversal of Speculative AI Enthusiasm.
The stock experienced an initial surge, reaching an intraday high of $43.49 on its direct listing day, fueled by broad investor enthusiasm for AI-themed companies. However, this speculative buying quickly reversed, leading to sharp declines. For instance, the stock dropped 24.36% on October 2, 2026, and a further 35.13% on October 5, 2026. This reversal was largely attributed to a cooling of speculative sentiment for smaller, thinly traded AI-linked names, occurring even on days when the broader market and larger technology stocks were performing positively.
Show less
Stock Movement Drivers
Fundamental Drivers
nullnull
Market Drivers
6/30/2026 to 10/16/2026| Return | Correlation | |
|---|---|---|
| RZAI | ||
| Market (SPY) | 2.2% | -44.6% |
| Sector (XLK) | -3.7% | -29.3% |
Fundamental Drivers
nullnull
Market Drivers
3/31/2026 to 10/16/2026| Return | Correlation | |
|---|---|---|
| RZAI | ||
| Market (SPY) | 17.7% | -44.6% |
| Sector (XLK) | 38.2% | -29.3% |
Fundamental Drivers
nullnull
Market Drivers
9/30/2025 to 10/16/2026| Return | Correlation | |
|---|---|---|
| RZAI | ||
| Market (SPY) | 15.5% | -44.6% |
| Sector (XLK) | 30.7% | -29.3% |
Fundamental Drivers
nullnull
Market Drivers
9/30/2023 to 10/16/2026| Return | Correlation | |
|---|---|---|
| RZAI | ||
| Market (SPY) | 84.7% | -44.6% |
| Sector (XLK) | 127.8% | -29.3% |
Price Returns Compared
| 2021 | 2022 | 2023 | 2024 | 2025 | 2026 | Total [1] | |
|---|---|---|---|---|---|---|---|
| Returns | |||||||
| RZAI Return | - | - | - | - | - | -55% | -55% |
| Peers Return | -9% | -46% | 75% | 13% | -16% | 10% | -10% |
| S&P 500 Return | 27% | -19% | 24% | 23% | 16% | 14% | 108% |
Monthly Win Rates [3] | |||||||
| RZAI Win Rate | - | - | - | - | - | 0% | |
| Peers Win Rate | 49% | 35% | 58% | 58% | 50% | 58% | |
| S&P 500 Win Rate | 75% | 42% | 67% | 75% | 67% | 50% | |
Max Drawdowns [4] | |||||||
| RZAI Max Drawdown | - | - | - | - | - | - | |
| Peers Max Drawdown | -42% | -56% | -34% | -37% | -41% | -38% | |
| S&P 500 Max Drawdown | -5% | -25% | -10% | -8% | -19% | -9% | |
[1] Cumulative total returns since the beginning of 2021
[2] Peers: GEN, S, PATH, CVLT, AI.
[3] Win Rate = % of calendar months in which monthly returns were positive
[4] Max drawdown represents maximum peak-to-trough decline within a year
[5] 2026 data is for the year up to 10/16/2026 (YTD)
How Low Can It Go
RZAI has limited trading history. Below is the Information Technology sector ETF (XLK) in its place.
| Event | XLK | S&P 500 |
|---|---|---|
| 2025 US Tariff Shock | ||
| % Loss | -25.7% | -18.8% |
| % Gain to Breakeven | 34.5% | 23.1% |
| Time to Breakeven | 65 days | 79 days |
| 2024 Yen Carry Trade Unwind | ||
| % Loss | -17.0% | -7.8% |
| % Gain to Breakeven | 20.4% | 8.5% |
| Time to Breakeven | 92 days | 18 days |
| Summer-Fall 2023 Five Percent Yield Shock | ||
| % Loss | -10.0% | -9.5% |
| % Gain to Breakeven | 11.2% | 10.5% |
| Time to Breakeven | 15 days | 24 days |
| 2022 Inflation Shock & Fed Tightening | ||
| % Loss | -33.1% | -24.5% |
| % Gain to Breakeven | 49.5% | 32.4% |
| Time to Breakeven | 246 days | 427 days |
| 2020 COVID-19 Crash | ||
| % Loss | -31.2% | -33.7% |
| % Gain to Breakeven | 45.2% | 50.9% |
| Time to Breakeven | 78 days | 140 days |
| Q4 2018 Fed Policy Error / Growth Scare | ||
| % Loss | -23.8% | -19.2% |
| % Gain to Breakeven | 31.2% | 23.8% |
| Time to Breakeven | 100 days | 105 days |
In The Past
State Street Technology Select Sector SPDR ETF's stock fell -25.7% during the 2025 US Tariff Shock. Such a loss loss requires a 34.5% gain to breakeven.
Preserve Wealth
Limiting losses and compounding gains is essential to preserving wealth.
Asset Allocation
Actively managed asset allocation strategies protect wealth. Learn more.
RZAI has limited trading history. Below is the Information Technology sector ETF (XLK) in its place.
| Event | XLK | S&P 500 |
|---|---|---|
| 2025 US Tariff Shock | ||
| % Loss | -25.7% | -18.8% |
| % Gain to Breakeven | 34.5% | 23.1% |
| Time to Breakeven | 65 days | 79 days |
| 2022 Inflation Shock & Fed Tightening | ||
| % Loss | -33.1% | -24.5% |
| % Gain to Breakeven | 49.5% | 32.4% |
| Time to Breakeven | 246 days | 427 days |
| 2020 COVID-19 Crash | ||
| % Loss | -31.2% | -33.7% |
| % Gain to Breakeven | 45.2% | 50.9% |
| Time to Breakeven | 78 days | 140 days |
| Q4 2018 Fed Policy Error / Growth Scare | ||
| % Loss | -23.8% | -19.2% |
| % Gain to Breakeven | 31.2% | 23.8% |
| Time to Breakeven | 100 days | 105 days |
| 2008-2009 Global Financial Crisis | ||
| % Loss | -51.5% | -53.4% |
| % Gain to Breakeven | 106.2% | 114.4% |
| Time to Breakeven | 797 days | 1085 days |
In The Past
State Street Technology Select Sector SPDR ETF's stock fell -25.7% during the 2025 US Tariff Shock. Such a loss loss requires a 34.5% gain to breakeven.
Preserve Wealth
Limiting losses and compounding gains is essential to preserving wealth.
Asset Allocation
Actively managed asset allocation strategies protect wealth. Learn more.
About Roze AI (RZAI)
Roze AI (RZAI) is a Canadian holding company with its primary operations in South Korea, specializing in advanced disaster prevention technology. The company's core product is the Disaster AI Platform (DAP), an innovative digital twin AI wireless fire system. This platform utilizes wireless sensing and monitoring data collection devices combined with AI data analysis and simulation to provide early detection, prevention, suppression, and alert transmission for fire incidents.
The DAP system has a proven track record, having been successfully installed and verified through long-term testing at major government facilities, military bases, government-designated production facilities, and power plants in Korea. Looking ahead, Roze AI is strategically developing a proprietary System on Chip (SoC) for real-time disaster information processing, which will incorporate energy harvesting technology for semi-permanent power. This SoC, developed through a fabless model, will not only enhance the DAP system but also be offered as a standalone product, targeting a broader global market for disaster early warning systems, integrated disaster management platforms, and related solutions.
Roze AI holds comprehensive patents for its vertically integrated AI wireless fire detection and prevention system across the US, Korea, and other countries. For future growth, the company has entered into a memorandum of understanding with PDI Global LLC to explore supplying its fire prevention and disaster safety solutions to U.S. real estate development projects, representing a potential new market expansion opportunity, with initial participation expected no earlier than the second half of 2026.
AI Analysis | Feedback
Analogy 1: Think of Roze AI as the 'Palantir for fire safety,' using advanced AI and digital twin technology to predict and prevent disasters in critical facilities.
Analogy 2: They're like a future Qualcomm or NVIDIA, but specializing in designing AI System-on-Chips (SoCs) exclusively for real-time disaster prevention systems.
AI Analysis | Feedback
- DAP (Disaster AI Platform): An AI-driven digital twin wireless fire system designed for the early detection, prevention, suppression, and alert transmission of fire incidents.
- Disaster Prevention SoC (System on Chip): A planned, fabless-designed chip for real-time processing and transmission of fire and disaster information, intended for integration into their DAP system and sale as a standalone product.
AI Analysis | Feedback
Roze AI Major Customers
Roze AI (RZAI) primarily sells its Disaster AI Platform (DAP) and related solutions to other companies and governmental entities rather than individuals. Based on the provided background information, specific names of these customer companies are not disclosed, but the major customer categories are:
- Government facilities and military bases in Korea.
- Government-designated production facilities in Korea.
- Power plants in Korea.
The company also has a memorandum of understanding with PDI Global LLC (a private entity, no symbol provided) for potential future collaboration on U.S. real estate development projects, but no business operations or material revenues are expected from this arrangement within the next 12 months, and it is not considered a current major customer.
Furthermore, Roze AI plans to develop and release an SoC (System on Chip) as a separate product for various disaster prevention solution markets, targeting major players such as Honeywell (HON), Siemens (SIE.DE, but primarily referred to as Siemens AG), Motorola Solutions (MSI), NEC (6701.T), and ABS Group. However, these are future target customers for the SoC product, not current major customers for their existing DAP platform.
AI Analysis | Feedback
AI Analysis | Feedback
Young Jin Cho, Chief Executive Officer and Director
Young Jin Cho is a semiconductor and IT veteran with over 30 years of experience in the US and Korea. He founded Roze AI Korea in 2015 and has led the company's AI/IoT product development, holding multiple national innovation recognitions. On December 19, 2024, he acquired Rozeta Vina Ltd., Roze AI's former Vietnam subsidiary.
Seon Ho Lee, Chief Financial Officer
Seon Ho Lee previously served as a finance lead at a KOSDAQ-listed company and possesses experience in public listings, capital markets, and corporate finance.
Seog Hun Cho, Chief Operating Officer and Director
Seog Hun Cho is responsible for leading operations, sales, and government programs, bringing a background in large-scale deployments and procurement approvals within Korea.
O Jang Jeong, Chief Technology Officer – R&D Strategy (Roze AI Korea)
O Jang Jeong has over 30 years of experience in firmware and systems engineering and leads the R&D of the Disaster AI Platform (DAP) and embedded software for wireless fire detection at Roze AI Korea.
Seung Ju Lee, Chief Technology Officer – DAP (Roze AI Korea)
Seung Ju Lee is an expert in RF/wireless and firmware, and a key contributor to the stability of AIoT products and communication within Roze AI Korea.
AI Analysis | Feedback
-
High Uncertainty of U.S. Market Entry and Revenue Generation: Roze AI's planned expansion into the U.S. market relies on a memorandum of understanding with PDI Global LLC to establish a joint venture. However, the company explicitly states that "no definitive agreements are in place, no committed funding obligations, and no material revenues expected to be generated from this arrangement within the next 12 months." Furthermore, any initial participation is not expected earlier than the second half of 2026. This indicates a significant risk that the anticipated U.S. market entry and associated revenue contributions may be delayed, reduced, or may not materialize as currently envisioned.
-
Intense Competition in the Broader Disaster Prevention Solution Market: Roze AI plans to develop and release its SoC (System on Chip) as a separate product to supply various disaster prevention solution markets, including disaster early warning systems, integrated disaster management platforms, and disaster risk assessment services. This strategy places them in direct competition with established major players such as Honeywell, Siemens, Motorola Solutions, NEC, and ABS Group. Successfully penetrating and gaining market share against such entrenched and well-resourced competitors presents a significant business challenge.
-
Reliance on Third-Party Foundries in a Fabless Semiconductor Model: Roze AI operates on a fabless model for its SoC development, meaning it will outsource all processes, including wafer production, packaging, and testing, to specialized foundries. While this approach avoids the immense capital expenditure of owning manufacturing facilities, it introduces dependency on third-party companies. This reliance carries risks related to supply chain disruptions, manufacturing delays, quality control issues from external partners, and potential intellectual property protection challenges, which could impact the timely and cost-effective production of their SoC.
AI Analysis | Feedback
AI Analysis | Feedback
Addressable Markets for Roze AI (RZAI)
Roze AI (RZAI) operates in the disaster prevention technology sector, primarily with its Disaster AI Platform (DAP), an AI wireless fire system leveraging digital twin technology, and a planned System on Chip (SoC) for various disaster prevention solutions.
Disaster AI Platform (DAP) - Digital Twin AI Wireless Fire System
- Global Fire Protection System Market: This market was valued at approximately USD 101.46 billion in 2026 and is projected to reach USD 182.20 billion by 2035, growing at a compound annual growth rate (CAGR) of 6.73%. Other estimates place the global market at USD 101.2 billion in 2026, growing to USD 156.2 billion by 2033 with a CAGR of 6.4%. The enhanced fire protection systems market specifically is projected to grow from USD 85.06 billion in 2025 to USD 118.14 billion by 2030, at a CAGR of 6.8%.
- South Korea Fire Protection System Market: This market was valued at approximately USD 5,771.3 million in 2025 and is projected to reach USD 9,276.3 million by 2030, exhibiting a CAGR of 10.0%. More specifically for smart fire safety solutions in South Korea, the market is estimated at USD 1.5 billion by 2027. The South Korea enhanced fire protection systems market was valued at USD 94.3 million in 2026 and is projected to reach USD 141.2 million by 2033, with a CAGR of 5.98% from 2027 to 2033.
- Global Building Digital Twin Market: This market, which includes fire safety and emergency simulation applications, was valued at USD 4.19 billion in 2025 and is projected to grow to USD 44.70 billion by 2035, with an exceptional CAGR of 26.95%.
- Global Fire Protection Internet of Things (IoT) Market: This market increased from USD 1.58 billion in 2025 to USD 1.68 billion in 2026 and is projected to reach USD 2.56 billion by 2032, with a CAGR of 7.16%.
SoC (System on Chip) for Disaster Prevention Solutions
- Global AI in Disaster Response and Emergency Management Market: This market reached approximately USD 152.95 billion in 2025 and is expected to grow to USD 224.73 billion in 2030, at a CAGR of 7.7%. Another report values this market at USD 5.6 billion in 2026, projected to grow to USD 20 billion by 2033, registering a CAGR of 20%.
- Global Disaster Preparedness Systems Market: This market was valued at USD 212.39 billion in 2025 and is projected to grow from USD 230.73 billion in 2026 to USD 447.59 billion by 2034, exhibiting a CAGR of 8.64%. Another source estimates the market size at USD 206.35 billion in 2025, predicted to increase from USD 223.68 billion in 2026 to approximately USD 457.78 billion by 2035, expanding at a CAGR of 8.29%.
- Global Disaster Management Market: This market was valued at USD 142.6 billion in 2025 and is expected to reach USD 298.4 billion by 2034, expanding at a CAGR of 8.6%.
- Global Artificial Intelligence in Disaster Risk Market: This market was valued at USD 479.5 billion in 2023 and is predicted to reach USD 2,150.1 billion by 2031, with a 21.3% CAGR.
- South Korea Artificial Intelligence Market: The broader AI market in South Korea, which would encompass the AI capabilities of the SoC, was valued at USD 3.9 billion in 2025 and is projected to reach USD 32.4 billion by 2034, exhibiting a CAGR of 26.33% from 2026 to 2034. Additionally, South Korea plans to invest approximately USD 692 million (940 billion won) in 50 AI-related disaster and safety projects through 2030.
- Global Earthquake Early Warning Systems Market: As a specific segment of disaster prevention, this market was valued at USD 1.55 billion in 2023 and is anticipated to grow at a CAGR of over 5% between 2024 and 2032. It is estimated to reach USD 2.49 billion by 2034, growing at a CAGR of 6.1%.
AI Analysis | Feedback
Here are three expected drivers of future revenue growth for Roze AI (RZAI) over the next 2-3 years:
- Expansion into the U.S. Real Estate Development Market: Roze AI anticipates revenue growth through its memorandum of understanding to establish a joint venture with PDI Global LLC. This collaboration aims to participate in U.S.-based real estate development projects by supplying Roze AI’s fire prevention and disaster safety solutions. The company expects to contribute its technology, products, and services to applicable projects and share in project-level revenues.
- Commercialization of the Disaster Prevention System on Chip (SoC): Roze AI plans to develop an SoC that can transmit, receive, and process fire and disaster information in real time. This SoC will be released as a separate product, targeting various disaster prevention solution markets such as disaster early warning systems, integrated disaster management platforms, and disaster data analysis solutions, offering a new revenue stream beyond its integrated DAP system. The SoC will also enhance its existing Disaster AI Platform (DAP) system.
- Increased Adoption and Deployment of the Disaster AI Platform (DAP): Continued growth is expected from the further installation and operation of Roze AI's core Disaster AI Platform (DAP). The platform, a digital twin AI wireless fire system, has been successfully installed and operated at major government facilities, military bases, government-designated production facilities, and power plants in Korea, and has been certified for its stability and disaster prevention functionality, indicating potential for broader deployment in existing and new markets.
AI Analysis | Feedback
Research & Analysis
Invest in Strategies
Wealth Management
Peer Comparisons
| Peers to compare with: |
Financials
| Median | |
|---|---|
| Name | |
| Mkt Price | 17.18 |
| Mkt Cap | 6.7 |
| Rev LTM | 1,216 |
| Op Inc LTM | 109 |
| FCF LTM | 258 |
| FCF 3Y Avg | 218 |
| CFO LTM | 265 |
| CFO 3Y Avg | 223 |
Growth & Margins
| Median | |
|---|---|
| Name | |
| Rev Chg LTM | 15.5% |
| Rev Chg 3Y Avg | 14.5% |
| Rev Chg Q | 11.4% |
| QoQ Delta Rev Chg LTM | 2.7% |
| Op Inc Chg LTM | 20.5% |
| Op Inc Chg 3Y Avg | 18.5% |
| Op Mgn LTM | 8.9% |
| Op Mgn 3Y Avg | -2.7% |
| QoQ Delta Op Mgn LTM | 0.0% |
| CFO/Rev LTM | 21.7% |
| CFO/Rev 3Y Avg | 21.5% |
| FCF/Rev LTM | 21.1% |
| FCF/Rev 3Y Avg | 21.0% |
Price Behavior
| Market Price | $9.82 | |
| Distance from 52W High | -62.7% | |
| 50 Days | 200 Days | |
| DMA Price | ||
| DMA Trend | ||
| Distance from DMA | ||
| 3M | 1YR | |
| Volatility | 246.0% | 246.0% |
| Downside Capture | ||
| Upside Capture | ||
| Correlation (S&P 500) |
| 1M | 2M | 3M | 6M | 1Y | 3Y | |
|---|---|---|---|---|---|---|
| Beta | ||||||
| Up Beta | � | � | � | � | � | � |
| Down Beta | � | � | � | � | � | � |
| Up Capture | 0% | 0% | 0% | 0% | 0% | 0% |
| Bmk +ve Days | 6 | 16 | 27 | 66 | 132 | 424 |
| Stock +ve Days | ||||||
| Down Capture | -0% | -0% | -0% | -0% | -0% | -0% |
| Bmk -ve Days | 16 | 26 | 37 | 60 | 120 | 328 |
| Stock -ve Days |
[1] Upside and downside betas calculated using positive and negative benchmark daily returns respectively
Based On 1-Year Data
| Annualized Return | Annualized Volatility | Sharpe Ratio | Correlation with RZAI | |
|---|---|---|---|---|
| RZAI | -55.3% | 246.0% | -5.38 | - |
| Sector ETF (XLK) | 29.7% | 26.4% | 0.95 | -29.3% |
| Equity (SPY) | 15.8% | 12.7% | 0.86 | -44.6% |
| Gold (GLD) | -1.4% | 29.4% | -0.05 | 23.5% |
| Commodities (DBC) | 50.4% | 20.7% | 1.86 | 72.3% |
| Real Estate (VNQ) | 4.8% | 13.7% | 0.09 | 3.5% |
| Bitcoin (BTCUSD) | -25.9% | 43.6% | -0.57 | -7.7% |
Smart multi-asset allocation framework can stack odds in your favor. Learn How
Based On 5-Year Data
| Annualized Return | Annualized Volatility | Sharpe Ratio | Correlation with RZAI | |
|---|---|---|---|---|
| RZAI | -14.8% | 246.0% | -5.38 | - |
| Sector ETF (XLK) | 20.2% | 26.0% | 0.69 | -29.3% |
| Equity (SPY) | 13.2% | 17.1% | 0.59 | -44.6% |
| Gold (GLD) | 18.4% | 18.9% | 0.79 | 23.5% |
| Commodities (DBC) | 9.6% | 19.5% | 0.37 | 72.3% |
| Real Estate (VNQ) | 1.6% | 18.8% | -0.02 | 3.5% |
| Bitcoin (BTCUSD) | 8.8% | 51.8% | 0.35 | -7.7% |
Smart multi-asset allocation framework can stack odds in your favor. Learn How
Based On 10-Year Data
| Annualized Return | Annualized Volatility | Sharpe Ratio | Correlation with RZAI | |
|---|---|---|---|---|
| RZAI | -7.7% | 246.0% | -5.38 | - |
| Sector ETF (XLK) | 23.9% | 25.0% | 0.86 | -29.3% |
| Equity (SPY) | 15.2% | 17.9% | 0.72 | -44.6% |
| Gold (GLD) | 12.3% | 16.4% | 0.61 | 23.5% |
| Commodities (DBC) | 8.1% | 18.1% | 0.36 | 72.3% |
| Real Estate (VNQ) | 5.2% | 20.7% | 0.21 | 3.5% |
| Bitcoin (BTCUSD) | 63.2% | 66.2% | 1.03 | -7.7% |
Smart multi-asset allocation framework can stack odds in your favor. Learn How
SEC Filings
Expand for More| Report Date | Filing Date | Filing |
|---|---|---|
| 12/31/2024 | 03/09/2026 | DRS/A |
| Report Date | Filing Date | Filing |
|---|---|---|
| 12/31/2024 | 03/09/2026 | DRS/A |
Industry Resources
| Information Technology Resources |
| TechCrunch |
| Wired |
| CIO |
| MIT Technology Review |
| Gartner Insights |
| Ars Technica |
| Systems Software Resources |
| CNET |
| ZDNet |
| Gartner |
| Software Development Times |
External Quote Links
| Y Finance | Barrons |
| TradingView | Morningstar |
| SeekingAlpha | ValueLine |
| Motley Fool | Robinhood |
| CNBC | Etrade |
| MarketWatch | Unusual Whales |
| YCharts | Perplexity Finance |
| FinViz |
Prefer one of these to Trefis? Tell us why.