FactSet Research Systems (FDS)
Market Price (12/24/2025): $290.41 | Market Cap: $11.0 BilSector: Financials | Industry: Financial Exchanges & Data
FactSet Research Systems (FDS)
Market Price (12/24/2025): $290.41Market Cap: $11.0 BilSector: FinancialsIndustry: Financial Exchanges & Data
Investment Highlights Why It Matters Detailed financial logic regarding cash flow yields vs trend-riding momentum.
| Attractive yieldTotal YieldTotal Yield = Earnings Yield + Dividend Yield, Earnings Yield = Net Income / Market Cap Dividend Yield = Total Dividends / Market Cap is 6.9%, FCF Yield is 5.6% | Weak multi-year price returns2Y Excs Rtn is -79%, 3Y Excs Rtn is -109% | Key risksFDS key risks include [1] a reported material weakness in its internal control over financial reporting related to IT general controls. |
| Attractive cash flow generationCFO/Rev LTMCash Flow from Operations / Revenue (Sales), Last Twelve Months (LTM) is 31%, FCF/Rev LTMFree Cash Flow / Revenue (Sales), Last Twelve Months (LTM) is 27% | ||
| Valuation becoming less expensiveP/S 6M Chg %Price/Sales change over 6 months. Declining P/S indicates valuation has become less expensive. is -36% | ||
| Low stock price volatilityVol 12M is 29% | ||
| Megatrend and thematic driversMegatrends include Fintech & Digital Payments, Cloud Computing, and Digital & Alternative Assets. Themes include Wealth Management Technology, Show more. |
| Attractive yieldTotal YieldTotal Yield = Earnings Yield + Dividend Yield, Earnings Yield = Net Income / Market Cap Dividend Yield = Total Dividends / Market Cap is 6.9%, FCF Yield is 5.6% |
| Attractive cash flow generationCFO/Rev LTMCash Flow from Operations / Revenue (Sales), Last Twelve Months (LTM) is 31%, FCF/Rev LTMFree Cash Flow / Revenue (Sales), Last Twelve Months (LTM) is 27% |
| Valuation becoming less expensiveP/S 6M Chg %Price/Sales change over 6 months. Declining P/S indicates valuation has become less expensive. is -36% |
| Low stock price volatilityVol 12M is 29% |
| Megatrend and thematic driversMegatrends include Fintech & Digital Payments, Cloud Computing, and Digital & Alternative Assets. Themes include Wealth Management Technology, Show more. |
| Weak multi-year price returns2Y Excs Rtn is -79%, 3Y Excs Rtn is -109% |
| Key risksFDS key risks include [1] a reported material weakness in its internal control over financial reporting related to IT general controls. |
Why The Stock Moved
Qualitative Assessment
AI Analysis | Feedback
I am unable to provide information on stock movements for the period between August 31, 2025, and December 24, 2025, as this time frame is in the future. My capabilities are limited to historical data up to my last training update. Show moreStock Movement Drivers
Fundamental Drivers
The 1.3% change in FDS stock from 9/23/2025 to 12/23/2025 was primarily driven by a 10.4% change in the company's Net Income Margin (%).| 9232025 | 12232025 | Change | |
|---|---|---|---|
| Stock Price ($) | 287.27 | 290.88 | 1.26% |
| Change Contribution By | LTM | LTM | |
| Total Revenues ($ Mil) | 2287.03 | 2321.75 | 1.52% |
| Net Income Margin (%) | 23.30% | 25.72% | 10.36% |
| P/E Multiple | 20.43 | 18.40 | -9.95% |
| Shares Outstanding (Mil) | 37.91 | 37.77 | 0.37% |
| Cumulative Contribution | 1.26% |
Market Drivers
9/23/2025 to 12/23/2025| Return | Correlation | |
|---|---|---|
| FDS | 1.3% | |
| Market (SPY) | 3.7% | 3.2% |
| Sector (XLF) | 3.1% | 34.8% |
Fundamental Drivers
The -33.1% change in FDS stock from 6/24/2025 to 12/23/2025 was primarily driven by a -39.6% change in the company's P/E Multiple.| 6242025 | 12232025 | Change | |
|---|---|---|---|
| Stock Price ($) | 434.59 | 290.88 | -33.07% |
| Change Contribution By | LTM | LTM | |
| Total Revenues ($ Mil) | 2254.22 | 2321.75 | 3.00% |
| Net Income Margin (%) | 24.07% | 25.72% | 6.85% |
| P/E Multiple | 30.45 | 18.40 | -39.58% |
| Shares Outstanding (Mil) | 38.02 | 37.77 | 0.65% |
| Cumulative Contribution | -33.07% |
Market Drivers
6/24/2025 to 12/23/2025| Return | Correlation | |
|---|---|---|
| FDS | -33.1% | |
| Market (SPY) | 13.7% | 7.1% |
| Sector (XLF) | 7.8% | 30.0% |
Fundamental Drivers
The -39.9% change in FDS stock from 12/23/2024 to 12/23/2025 was primarily driven by a -46.3% change in the company's P/E Multiple.| 12232024 | 12232025 | Change | |
|---|---|---|---|
| Stock Price ($) | 483.72 | 290.88 | -39.87% |
| Change Contribution By | LTM | LTM | |
| Total Revenues ($ Mil) | 2203.06 | 2321.75 | 5.39% |
| Net Income Margin (%) | 24.38% | 25.72% | 5.47% |
| P/E Multiple | 34.25 | 18.40 | -46.27% |
| Shares Outstanding (Mil) | 38.03 | 37.77 | 0.69% |
| Cumulative Contribution | -39.87% |
Market Drivers
12/23/2024 to 12/23/2025| Return | Correlation | |
|---|---|---|
| FDS | -39.9% | |
| Market (SPY) | 16.7% | 36.6% |
| Sector (XLF) | 15.7% | 48.4% |
Fundamental Drivers
The -24.7% change in FDS stock from 12/24/2022 to 12/23/2025 was primarily driven by a -50.6% change in the company's P/E Multiple.| 12242022 | 12232025 | Change | |
|---|---|---|---|
| Stock Price ($) | 386.30 | 290.88 | -24.70% |
| Change Contribution By | LTM | LTM | |
| Total Revenues ($ Mil) | 1843.89 | 2321.75 | 25.92% |
| Net Income Margin (%) | 21.53% | 25.72% | 19.46% |
| P/E Multiple | 37.28 | 18.40 | -50.65% |
| Shares Outstanding (Mil) | 38.31 | 37.77 | 1.41% |
| Cumulative Contribution | -24.72% |
Market Drivers
12/24/2023 to 12/23/2025| Return | Correlation | |
|---|---|---|
| FDS | -36.7% | |
| Market (SPY) | 48.4% | 37.2% |
| Sector (XLF) | 52.3% | 45.7% |
Price Returns Compared
| 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | Total [1] | |
|---|---|---|---|---|---|---|---|
| Returns | |||||||
| FDS Return | 25% | 47% | -17% | 20% | 2% | -39% | 15% |
| Peers Return | 38% | 43% | -24% | 32% | 15% | -8% | 110% |
| S&P 500 Return | 16% | 27% | -19% | 24% | 23% | 17% | 114% |
Monthly Win Rates [3] | |||||||
| FDS Win Rate | 58% | 83% | 50% | 67% | 42% | 25% | |
| Peers Win Rate | 63% | 63% | 37% | 60% | 53% | 50% | |
| S&P 500 Win Rate | 58% | 75% | 42% | 67% | 75% | 73% | |
Max Drawdowns [4] | |||||||
| FDS Max Drawdown | -24% | -11% | -28% | -4% | -17% | -47% | |
| Peers Max Drawdown | -26% | -8% | -35% | -5% | -8% | -20% | |
| S&P 500 Max Drawdown | -31% | -1% | -25% | -1% | -2% | -15% | |
[1] Cumulative total returns since the beginning of 2020
[2] Peers: SPGI, MCO, MSCI, MORN, TRI. See FDS Returns vs. Peers.
[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] 2025 data is for the year up to 12/23/2025 (YTD)
How Low Can It Go
| Event | FDS | S&P 500 |
|---|---|---|
| 2022 Inflation Shock | ||
| % Loss | -28.7% | -25.4% |
| % Gain to Breakeven | 40.2% | 34.1% |
| Time to Breakeven | 881 days | 464 days |
| 2020 Covid Pandemic | ||
| % Loss | -33.7% | -33.9% |
| % Gain to Breakeven | 50.9% | 51.3% |
| Time to Breakeven | 72 days | 148 days |
| 2018 Correction | ||
| % Loss | -22.4% | -19.8% |
| % Gain to Breakeven | 28.9% | 24.7% |
| Time to Breakeven | 133 days | 120 days |
| 2008 Global Financial Crisis | ||
| % Loss | -54.9% | -56.8% |
| % Gain to Breakeven | 121.6% | 131.3% |
| Time to Breakeven | 361 days | 1,480 days |
Compare to CBOE, TW, MKTX, DFIN, SPGI
In The Past
FactSet Research Systems's stock fell -28.7% during the 2022 Inflation Shock from a high on 12/29/2021. A -28.7% loss requires a 40.2% gain to breakeven.
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AI Analysis | Feedback
Here are 1-3 brief analogies for FactSet Research Systems (FDS):
- The Bloomberg Terminal for financial research and analytics.
- Salesforce for investment firms, providing essential financial data and analytical software.
AI Analysis | Feedback
- FactSet Workstation: An integrated software platform providing financial professionals with access to comprehensive data, analytics, and reporting tools.
- Financial Data Feeds & APIs: Direct delivery of vast datasets, including company fundamentals, market prices, estimates, and alternative data, for integration into client systems.
- Portfolio & Risk Analytics: Specialized tools for investment professionals to measure performance, analyze risk, optimize portfolios, and conduct attribution.
- Wealth Management Platform: Tailored solutions for wealth advisors, offering tools for client engagement, portfolio modeling, and reporting.
- Research Management Solutions: Tools designed to help investment firms streamline their research workflows, foster collaboration, and manage compliance.
AI Analysis | Feedback
Major Customers of FactSet Research Systems (FDS)
FactSet Research Systems (FDS) primarily sells its integrated financial information, analytical applications, and industry-leading services to other companies, making it a business-to-business (B2B) provider.
Due to the confidential nature of client relationships and the vast number of institutional customers FactSet serves globally (tens of thousands of financial professionals across thousands of firms), specific names of its individual major customer companies are not publicly disclosed. Instead, FactSet serves a broad range of firms within the global financial industry. Its primary customer categories include:
- Investment Management Firms (Buy-Side): This is FactSet's largest client segment. It encompasses a wide array of institutions such as asset managers, mutual funds, hedge funds, private equity firms, pension funds, and wealth management firms. These clients utilize FactSet for comprehensive portfolio analysis, investment research, risk management, and trading workflows.
- Investment Banking and Brokerage Firms (Sell-Side): This category includes investment banks, broker-dealers, and their research departments. They leverage FactSet for activities such as M&A advisory, equity research, debt capital markets, and sales & trading.
- Corporations and Private Equity Firms: FactSet serves corporate finance departments, investor relations teams, and private equity firms for strategic planning, competitive analysis, and due diligence processes.
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Amazon.com, Inc. (AMZN)
S&P Global Inc. (SPGI)
Moody's Corporation (MCO)
MSCI Inc. (MSCI)
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```htmlPhil Snow – Chief Executive Officer
Phil Snow joined FactSet in 2000, serving as President from 2014 to 2016 before being appointed Chief Executive Officer in 2017. Prior to his CEO role, he held various positions including Senior Vice President, Director of Americas Sales, and Regional Sales Manager. He holds an MBA from Columbia Business School and a B.A. in History from Bowdoin College. No information is readily available regarding him founding or managing other companies, selling companies to an acquirer, or managing companies backed by private equity firms.
Kristin Snow – Chief Financial Officer
Kristin Snow has been with FactSet since 1998 and was appointed Chief Financial Officer in 2023. Before her current role, she served as Senior Vice President, Chief Accounting Officer, and Global Controller. She is a Certified Public Accountant and earned her B.S. in Accounting from the University of Massachusetts, Amherst. No information is readily available regarding her founding or managing other companies, selling companies to an acquirer, or managing companies backed by private equity firms.
Sophie Adams – Chief Content Officer
Sophie Adams serves as FactSet's Chief Content Officer.
Linda H. Smith – Chief Product Officer
Linda H. Smith is the Chief Product Officer at FactSet.
Serban Ursachi – Chief Technology Officer
Serban Ursachi holds the position of Chief Technology Officer at FactSet.
AI Analysis | Feedback
The key risks to FactSet Research Systems (FDS) include:
- Material Weakness in Internal Control Over Financial Reporting: FactSet has reported a material weakness in its internal control over financial reporting, specifically related to IT general controls. This issue, if not adequately addressed, could undermine investor confidence and potentially lead to financial misstatements. The company has acknowledged this weakness, and its independent registered public accounting firm has issued an adverse opinion, highlighting the urgency for remediation.
- Dependence on the Financial Services Industry and Economic Conditions: FactSet's client base is heavily concentrated within the financial services industry. This concentration makes the company susceptible to industry-specific risks, such as economic downturns, changes in regulations, or shifts in investment strategies (e.g., the shift from active to passive investing). Such factors could directly impact client spending and, consequently, FactSet's revenue streams and profitability.
- Cybersecurity, Technology, and Data Security Risks: FactSet faces significant risks from potential cyber-attacks, unauthorized access to confidential data, and failures in its cybersecurity systems. The company's reliance on third-party service providers and its increasing use of mobile and cloud technologies, along with the expansion of AI technologies, further amplify these risks, potentially leading to business disruption, compliance issues, or reputational damage.
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The emergence of specialized FinTech startups leveraging advanced Artificial Intelligence (AI) and Machine Learning (ML) models, particularly Large Language Models (LLMs), to provide highly efficient and automated financial research and analytical tools. These solutions excel at processing vast amounts of unstructured data (e.g., earnings call transcripts, news, regulatory filings) to deliver rapid insights and summaries, directly challenging FactSet's traditional research workflows and the value proposition of its integrated platform. Companies like AlphaSense illustrate this trend, attracting users with best-of-breed capabilities for specific analytical needs.AI Analysis | Feedback
The addressable markets for FactSet Research Systems' main products and services are primarily within the global financial data and analytics sector, as well as specific segments like investment management software and wealth management technology.- The global financial data and analytics market size was valued at USD 283.4 billion in 2022 and is projected to reach USD 735.2 billion by 2032.
- The global investment management software market size was valued at USD 5.76 billion in 2022 and is projected to reach USD 14.88 billion by 2032.
- The global wealth management software market size was USD 4.8 billion in 2023 and is projected to reach USD 16.5 billion by 2032.
AI Analysis | Feedback
FactSet Research Systems (FDS) is expected to drive future revenue growth over the next 2-3 years through several key initiatives and market trends:
- Expansion in the Wealth Management Segment: FactSet continues to focus on expanding its presence in the wealth management sector. The company aims to achieve this by offering specialized solutions that cater to the unique needs of wealth managers, including enhanced portfolio analytics, reporting, and client engagement tools. This strategic focus is expected to capture a larger share of this growing market segment.
- Growth in Content and Technology Solutions (CTS): FactSet's Content and Technology Solutions segment is anticipated to be a significant driver of revenue. This includes leveraging its robust data feeds, analytics, and technology platforms to attract new clients and deepen relationships with existing ones. Ongoing investments in data enrichment and technological advancements within CTS are designed to enhance its value proposition and drive adoption.
- Strategic Pricing and Value Realization: The company is expected to continue optimizing its pricing strategies to reflect the increasing value and breadth of its offerings. This includes potential for modest price increases where justified by product enhancements, increased functionality, and superior client service, thereby contributing to organic revenue growth.
- Increased Adoption of Open-Platform Solutions: FactSet's commitment to an open platform strategy, allowing for greater integration and customization, is likely to attract a broader range of financial professionals. By providing flexible and interconnected solutions, FactSet can enhance user stickiness and drive further consumption of its services across various workflows, leading to increased subscription revenue.
- International Market Penetration: While not explicitly detailed in every recent report, FactSet has historically pursued opportunities in international markets. Continued efforts to expand its client base and deepen its market penetration in key regions outside of its core markets, through localized solutions and increased sales presence, represent a potential avenue for future revenue growth.
AI Analysis | Feedback
Share Repurchases
- FactSet's Board of Directors authorized an additional $300 million for its share repurchase program in June 2024, bringing the total authorized amount to $600 million.
- During fiscal year 2023, FactSet repurchased approximately $300 million of its common stock.
- In fiscal year 2022, FactSet repurchased $268.4 million of its common stock.
Outbound Investments
- FactSet completed the acquisition of CUSIP Global Services (CGS) from S&P Global for approximately $1.925 billion in March 2022.
- FactSet acquired Cobalt Software, a private markets data and software provider, in March 2021.
Capital Expenditures
- Capital expenditures were $55.4 million in fiscal year 2023.
- Capital expenditures were $60.2 million in fiscal year 2022.
- The primary focus of capital expenditures generally relates to investments in technology infrastructure, data center improvements, and office facilities.
Latest Trefis Analyses
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|---|---|
| ARTICLES |
Trade Ideas
Select ideas related to FDS. For more, see Trefis Trade Ideas.
| Date | Ticker | Company | Category | Trade Strategy | 6M Fwd Rtn | 12M Fwd Rtn | 12M Max DD |
|---|---|---|---|---|---|---|---|
| 11212025 | WU | Western Union | Dip Buy | DB | FCFY OPMDip Buy with High FCF Yield and High MarginBuying dips for companies with high FCF yield and meaningfully high operating margin | 12.4% | 12.4% | -0.4% |
| 11212025 | COIN | Coinbase Global | Monopoly | MY | Getting CheaperMonopoly-Like with P/S DeclineLarge cap with monopoly-like margins or cash flow generation and getting cheaper based on P/S multiple | 0.8% | 0.8% | -0.5% |
| 11142025 | PYPL | PayPal | Dip Buy | DB | FCFY OPMDip Buy with High FCF Yield and High MarginBuying dips for companies with high FCF yield and meaningfully high operating margin | -5.4% | -5.4% | -7.5% |
| 11142025 | V | Visa | Monopoly | MY | Getting CheaperMonopoly-Like with P/S DeclineLarge cap with monopoly-like margins or cash flow generation and getting cheaper based on P/S multiple | 7.1% | 7.1% | -2.7% |
| 11072025 | WD | Walker & Dunlop | Dip Buy | DB | P/E OPMDip Buy with Low PE and High MarginBuying dips for companies with tame PE and meaningfully high operating margin | -11.5% | -11.5% | -12.1% |
| 09262025 | FDS | FactSet Research Systems | Dip Buy | DB | P/E OPMDip Buy with Low PE and High MarginBuying dips for companies with tame PE and meaningfully high operating margin | 0.8% | 0.8% | -12.5% |
Research & Analysis
Invest in Strategies
Wealth Management
Peer Comparisons for FactSet Research Systems
| Peers to compare with: |
Financials
| Median | |
|---|---|
| Name | |
| Mkt Price | 403.13 |
| Mkt Cap | 52.1 |
| Rev LTM | 5,216 |
| Op Inc LTM | 1,892 |
| FCF LTM | 1,605 |
| FCF 3Y Avg | 1,571 |
| CFO LTM | 1,988 |
| CFO 3Y Avg | 1,918 |
Growth & Margins
| Median | |
|---|---|
| Name | |
| Rev Chg LTM | 8.3% |
| Rev Chg 3Y Avg | 9.3% |
| Rev Chg Q | 8.6% |
| QoQ Delta Rev Chg LTM | 2.1% |
| Op Mgn LTM | 36.2% |
| Op Mgn 3Y Avg | 33.8% |
| QoQ Delta Op Mgn LTM | 1.1% |
| CFO/Rev LTM | 34.8% |
| CFO/Rev 3Y Avg | 34.7% |
| FCF/Rev LTM | 29.3% |
| FCF/Rev 3Y Avg | 29.9% |
Valuation
| Median | |
|---|---|
| Name | |
| Mkt Cap | 52.1 |
| P/S | 9.4 |
| P/EBIT | 25.6 |
| P/E | 35.2 |
| P/CFO | 26.3 |
| Total Yield | 4.3% |
| Dividend Yield | 1.0% |
| FCF Yield 3Y Avg | 2.9% |
| D/E | 0.1 |
| Net D/E | 0.1 |
Returns
| Median | |
|---|---|
| Name | |
| 1M Rtn | 4.4% |
| 3M Rtn | 1.9% |
| 6M Rtn | -14.4% |
| 12M Rtn | -10.0% |
| 3Y Rtn | 26.1% |
| 1M Excs Rtn | -0.2% |
| 3M Excs Rtn | -1.6% |
| 6M Excs Rtn | -27.7% |
| 12M Excs Rtn | -27.3% |
| 3Y Excs Rtn | -54.5% |
Comparison Analyses
Price Behavior
| Market Price | $290.88 | |
| Market Cap ($ Bil) | 11.0 | |
| First Trading Date | 06/28/1996 | |
| Distance from 52W High | -40.1% | |
| 50 Days | 200 Days | |
| DMA Price | $278.76 | $371.04 |
| DMA Trend | down | down |
| Distance from DMA | 4.3% | -21.6% |
| 3M | 1YR | |
| Volatility | 33.2% | 28.6% |
| Downside Capture | 10.79 | 71.28 |
| Upside Capture | 14.79 | 10.44 |
| Correlation (SPY) | 4.6% | 36.4% |
| 1M | 2M | 3M | 6M | 1Y | 3Y | |
|---|---|---|---|---|---|---|
| Beta | -0.13 | 0.11 | 0.10 | 0.33 | 0.56 | 0.67 |
| Up Beta | -0.28 | 1.41 | 1.81 | 1.41 | 0.72 | 0.81 |
| Down Beta | -2.29 | -0.39 | -0.64 | -0.25 | 0.54 | 0.64 |
| Up Capture | 44% | -17% | -76% | -41% | 3% | 15% |
| Bmk +ve Days | 12 | 25 | 38 | 73 | 141 | 426 |
| Stock +ve Days | 9 | 21 | 29 | 56 | 111 | 390 |
| Down Capture | 9% | 6% | 68% | 103% | 79% | 91% |
| Bmk -ve Days | 7 | 16 | 24 | 52 | 107 | 323 |
| Stock -ve Days | 10 | 20 | 33 | 69 | 137 | 360 |
[1] Upside and downside betas calculated using positive and negative benchmark daily returns respectively
Based On 1-Year Data
| Comparison of FDS With Other Asset Classes (Last 1Y) | |||||||
|---|---|---|---|---|---|---|---|
| FDS | Sector ETF | Equity | Gold | Commodities | Real Estate | Bitcoin | |
| Annualized Return | -37.8% | 18.1% | 18.8% | 72.9% | 9.0% | 3.7% | -11.4% |
| Annualized Volatility | 28.7% | 19.0% | 19.5% | 19.2% | 15.3% | 17.2% | 35.0% |
| Sharpe Ratio | -1.65 | 0.74 | 0.76 | 2.72 | 0.36 | 0.05 | -0.14 |
| Correlation With Other Assets | 47.7% | 36.0% | 0.5% | 9.4% | 45.0% | 13.3% | |
ETFs used for asset classes: Sector ETF = XLF, Equity = SPY, Gold = GLD, Commodities = DBC, Real Estate = VNQ, and Bitcoin = BTCUSD
Smart multi-asset allocation framework can stack odds in your favor. Learn How
Based On 5-Year Data
| Comparison of FDS With Other Asset Classes (Last 5Y) | |||||||
|---|---|---|---|---|---|---|---|
| FDS | Sector ETF | Equity | Gold | Commodities | Real Estate | Bitcoin | |
| Annualized Return | -2.6% | 16.2% | 14.8% | 18.9% | 11.8% | 4.7% | 35.5% |
| Annualized Volatility | 24.5% | 18.9% | 17.1% | 15.5% | 18.7% | 18.9% | 48.9% |
| Sharpe Ratio | -0.12 | 0.71 | 0.70 | 0.98 | 0.51 | 0.16 | 0.62 |
| Correlation With Other Assets | 44.4% | 49.5% | 5.1% | 7.0% | 47.9% | 17.3% | |
ETFs used for asset classes: Sector ETF = XLF, Equity = SPY, Gold = GLD, Commodities = DBC, Real Estate = VNQ, and Bitcoin = BTCUSD
Smart multi-asset allocation framework can stack odds in your favor. Learn How
Based On 10-Year Data
| Comparison of FDS With Other Asset Classes (Last 10Y) | |||||||
|---|---|---|---|---|---|---|---|
| FDS | Sector ETF | Equity | Gold | Commodities | Real Estate | Bitcoin | |
| Annualized Return | 7.1% | 13.1% | 14.8% | 15.1% | 6.8% | 5.4% | 69.1% |
| Annualized Volatility | 26.0% | 22.3% | 18.0% | 14.8% | 17.6% | 20.8% | 55.8% |
| Sharpe Ratio | 0.29 | 0.55 | 0.71 | 0.85 | 0.31 | 0.23 | 0.90 |
| Correlation With Other Assets | 55.4% | 61.0% | 3.1% | 17.6% | 52.3% | 15.8% | |
ETFs used for asset classes: Sector ETF = XLF, Equity = SPY, Gold = GLD, Commodities = DBC, Real Estate = VNQ, and Bitcoin = BTCUSD
Smart multi-asset allocation framework can stack odds in your favor. Learn How
Returns Analyses
Earnings Returns History
Expand for More| Forward Returns | |||
|---|---|---|---|
| Earnings Date | 1D Returns | 5D Returns | 21D Returns |
| 12/18/2025 | -7.7% | ||
| 9/18/2025 | -4.0% | -5.8% | -4.8% |
| 6/23/2025 | 3.5% | 4.5% | -1.4% |
| 3/20/2025 | 0.4% | 4.2% | -4.2% |
| 12/19/2024 | 3.5% | 3.9% | -1.8% |
| 9/19/2024 | 5.1% | 2.5% | 5.7% |
| 6/21/2024 | 3.8% | 1.6% | 5.1% |
| 3/21/2024 | -7.6% | -8.3% | -11.0% |
| ... | |||
| SUMMARY STATS | |||
| # Positive | 12 | 15 | 14 |
| # Negative | 12 | 9 | 10 |
| Median Positive | 3.6% | 3.6% | 3.5% |
| Median Negative | -4.3% | -5.8% | -4.8% |
| Max Positive | 15.1% | 12.3% | 17.9% |
| Max Negative | -8.3% | -8.7% | -11.0% |
SEC Filings
Expand for More| Report Date | Filing Date | Filing |
|---|---|---|
| 8312025 | 10222025 | 10-K 8/31/2025 |
| 5312025 | 7032025 | 10-Q 5/31/2025 |
| 2282025 | 4042025 | 10-Q 2/28/2025 |
| 11302024 | 1082025 | 10-Q 11/30/2024 |
| 8312024 | 10292024 | 10-K 8/31/2024 |
| 5312024 | 7032024 | 10-Q 5/31/2024 |
| 2292024 | 4032024 | 10-Q 2/29/2024 |
| 11302023 | 1052024 | 10-Q 11/30/2023 |
| 8312023 | 10272023 | 10-K 8/31/2023 |
| 5312023 | 7032023 | 10-Q 5/31/2023 |
| 2282023 | 4032023 | 10-Q 2/28/2023 |
| 11302022 | 1052023 | 10-Q 11/30/2022 |
| 8312022 | 10212022 | 10-K 8/31/2022 |
| 5312022 | 7012022 | 10-Q 5/31/2022 |
| 2282022 | 4042022 | 10-Q 2/28/2022 |
| 11302021 | 1032022 | 10-Q 11/30/2021 |
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.