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Trailing twelve months

Trailing twelve months (TTM), also known as last twelve months (LTM), is a financial metric that measures a company's performance using data from the most recent 12 consecutive months, providing a current and rolling view of key indicators such as , , and other operational figures without being constrained by fiscal year-end boundaries. This approach contrasts with annual reporting by incorporating the latest quarterly data to reflect up-to-date financial health, helping to smooth out seasonal fluctuations and offer a more accurate snapshot for analysis. TTM is widely used in , valuation, and investment decisions, such as calculating ratios like price-to-earnings (P/E) or (EPS), where it divides the current by the TTM EPS to assess relative value. To calculate TTM figures, analysts typically sum the data from the four most recent quarters reported in filings like 10-Q and 10-K forms; for example, TTM is derived by adding the latest to the current year-to-date (YTD) data and subtracting the prior year's corresponding YTD data. A practical illustration is Alphabet Inc.'s TTM as of Q3 2025 (ended September 30, 2025), calculated as $350,018 million (FY 2024) plus $288,900 million (Q1–Q3 2025 YTD) minus $253,000 million (Q1–Q3 2024 YTD), resulting in $385,918 million. In applications beyond , TTM extends to sectors like commercial for evaluating property performance over the prior 12 months of operations, and in portfolio management for yields based on the weighted average of dividends or over that period. Its flexibility makes it essential for , where it enables timely comparisons of target companies' metrics against peers or historical benchmarks.

Definition and Fundamentals

Core Concept

The trailing twelve months (TTM), also known as the trailing 12 months, refers to the most recent 12 consecutive months of a company's financial , typically ending on the current date or the latest reporting period. This rolling period provides an up-to-date snapshot of performance metrics, avoiding the limitations of static annual reports that may include outdated information. The primary purpose of TTM is to offer a smoothed and current view of a company's ongoing financial health, particularly beneficial for businesses with seasonal fluctuations, as it mitigates distortions from fixed calendar or fiscal year boundaries. By aggregating data over this dynamic window, TTM captures trends in , expenses, and profitability without being skewed by quarterly variations or end-of-year anomalies. In practice, TTM aggregates key financial metrics by summing relevant figures—such as or —from the past four quarters or equivalent monthly data. Common TTM metrics include TTM , which measures total income over the period; TTM (), reflecting diluted profits per outstanding share; and TTM , indicating overall profitability after expenses. These metrics enable analysts to assess normalized performance for informed decision-making in financial reporting and valuation.

Historical Context

The concept of the trailing twelve months (TTM) emerged in the mid-20th century as financial reporting practices evolved to meet demands for more timely and granular disclosures in the United States, following the enactment of key securities laws in the 1930s. The Securities Act of 1933 and the Securities Exchange Act of 1934 established the Securities and Exchange Commission (SEC) and required periodic financial reporting to protect investors after the 1929 stock market crash, initially emphasizing annual reports but setting the stage for enhanced frequency. Quarterly reporting was experimented with in the 1940s for select financial items, but it was not standardized until the SEC mandated full quarterly filings (Form 10-Q) for all public companies in 1970, providing the quarterly data essential for compiling TTM figures and enabling a rolling view of the most recent 12 months' performance. TTM is used as a non-GAAP supplement to official filings under Generally Accepted Accounting Principles (), with its role amplified in enhancing transparency following the Sarbanes-Oxley Act of 2002. Enacted in the wake of corporate scandals like , the Sarbanes-Oxley Act (SOX) strengthened internal controls and disclosure requirements, underscoring the value of current-period metrics like TTM for investor confidence without altering core GAAP structures. Internationally, TTM has supported harmonization under (IFRS) by facilitating comparisons across entities with divergent fiscal year-ends, allowing consistent 12-month performance assessments in a global context. As of 2025, ongoing discussions within the regarding a potential shift from quarterly to semi-annual reporting for public companies could impact the frequency of data available for TTM calculations. In September 2025, the announced plans to propose rule changes allowing companies to opt for semi-annual comprehensive interim reports, following petitions and directives aimed at reducing reporting burdens while maintaining . These proposals, if adopted, may necessitate adjustments in how TTM metrics are derived, potentially relying more on annual filings supplemented by voluntary disclosures.

Calculation Methods

Step-by-Step Computation

The trailing twelve months (TTM) is computed by aggregating financial data from the most recent 12-month period, typically using quarterly reports to ensure a rolling view of performance. For standard quarterly reporting companies, the core sums the figures from the four latest quarters. For instance, TTM is calculated as: \text{TTM Revenue} = Q_n + Q_{n-1} + Q_{n-2} + Q_{n-3} where Q_n represents the from the most recent quarter, and Q_{n-3} is the oldest included quarter. This approach applies similarly to other items like or EBITDA, providing a snapshot that aligns with the end of the latest reporting period. To compute TTM step by step:
  1. Identify the reporting date, which is typically the end of the most recent quarter (e.g., for ).
  2. Retrieve the relevant financial figures from the company's quarterly filings (10-Q) for the current and prior three quarters.
  3. Sum these values directly, ensuring consistency in accounting standards (e.g., ) across periods to avoid distortions.
If the reporting date falls mid-quarter or outside standard fiscal alignments, the calculation adjusts by incorporating year-to-date (YTD) data from the latest partial period. The becomes: \text{TTM Metric} = \text{Last Full Fiscal Year} + \text{Current YTD} - \text{Prior Year YTD (Same Period)} This method, often referred to as the last twelve months (LTM) variant, prorates the partial quarter by using actual reported YTD figures rather than estimates, ensuring the total covers exactly 12 months. For example, if calculating as of May 2024 with Q1 fully reported but partial Q2 data available, add the full prior fiscal year, include Q1 2024 plus the partial Q2, and subtract the equivalent period from the prior year. When a new quarter is released, the TTM rolls forward by subtracting the value from the dropped (oldest) quarter and adding the new quarter's value to maintain the 12-month window. The update formula is: \text{New TTM} = \text{Old TTM} - Q_{n-3} + Q_{n+1} where Q_{n-3} is the quarter now falling outside the trailing period. This rolling mechanism automates continuity without recalculating from scratch each time. In cases where quarterly reports are unavailable or monthly data is more accessible (e.g., for private companies or ), TTM can be derived by summing the most recent 12 months of monthly figures. Prorating partial quarters involves apportioning based on elapsed days or months—for instance, if only two months of a quarter are available, multiply the partial figure by 1.5 to estimate the full quarter before inclusion. For earnings per share (EPS), TTM adjusts the standard EPS formula to the trailing period: \text{TTM EPS} = \frac{\text{Net Income over Last 12 Months}}{\text{Weighted Average Shares Outstanding over the Same Period}} Net income is summed from the four quarters (or adjusted via the YTD method), and the denominator uses the weighted average shares to account for any issuances or buybacks during the period, ensuring per-share accuracy. This yields a diluted or basic TTM EPS depending on whether potential share dilution is factored in.

Data Requirements and Adjustments

To compute trailing twelve months (TTM) metrics accurately, analysts rely on primary data sources that provide standardized, audited financial information. , quarterly reports filed on with the Securities and Exchange Commission (SEC) via the database serve as the core input, offering detailed income statements, balance sheets, and cash flow data for each of the most recent four fiscal quarters. Annual reports on provide baseline annual figures and contextual notes that help validate quarterly data, particularly for the earliest quarter in the TTM period. Additionally, earnings releases from company (IR) websites and aggregated databases such as supply preliminary or summarized quarterly results, enabling quicker TTM approximations before full 10-Q filings are available. Adjustments to are essential to isolate recurring operational and avoid distortions in TTM calculations. Non-recurring items, such as gains or losses from asset sales, charges, or litigation settlements, must be excluded to derive an adjusted TTM metric that reflects sustainable earnings; for instance, one-time asset sale proceeds are subtracted from the relevant quarter's before summation. The emphasizes that analysts should rigorously identify and remove these items to enhance the quality of , aligning with standards that promote transparent non-GAAP adjustments only when they provide meaningful insights into core operations. For multinational firms, currency fluctuations require restatement of historical quarterly figures to a consistent reporting currency, typically using the current rate method under ASC 830, where income statement items are translated at average exchange rates for the period and balance sheet items at closing rates, with resulting translation adjustments recorded in other comprehensive income rather than net income to maintain TTM comparability. In cases of mergers or acquisitions, pro forma adjustments under SEC Regulation S-X Article 11 are applied to historical quarters, incorporating the acquired entity's results as if the transaction occurred at the start of the TTM period, including synergies, financing costs, and eliminated intercompany transactions to ensure a consistent entity view. TTM metrics are updated in real time following each quarterly earnings release, with full revisions typically occurring every 90 days upon 10-Q filing, allowing for the "rolling" replacement of the oldest quarter with the newest to capture the most current twelve-month performance. This frequency aligns with requirements for quarterly reporting, ensuring timely data availability while necessitating prompt analyst adjustments for any interim events disclosed in earnings calls or press releases.

Applications in Finance

Financial Reporting and Analysis

Trailing twelve months (TTM) figures play a key role in by providing a rolling, up-to-date view of a company's performance, often presented alongside quarterly data to highlight trends beyond static fiscal periods. In income statements, TTM metrics such as or are derived by aggregating the most recent four quarters' results, offering stakeholders a smoothed perspective on operational results that mitigates seasonal variations. During earnings calls, management and analysts frequently reference TTM data to discuss recent performance dynamics, enabling more timely assessments than annual figures alone. In and 10-K filings, TTM figures are commonly incorporated to evaluate short-term financial trends, liquidity, and growth trajectories, enhancing the explanation of quarterly results. These SEC-required documents update TTM calculations quarterly based on the latest data, providing a current snapshot for investors derived from reported . Public companies voluntarily include TTM metrics in supplemental tables within earnings releases and investor presentations, a widespread practice that promotes comparability across entities with varying fiscal year-ends, as seen in filings from companies like Technologies and . TTM data is integral to ratio analysis, where it forms the basis for key metrics that reveal operational health and efficiency over the recent period. For instance, the price-to-earnings (P/E) ratio using TTM earnings per share (EPS) allows analysts to gauge valuation relative to the most current profitability, avoiding distortions from outdated annual data. Similarly, the debt-to-EBITDA ratio, computed with TTM EBITDA, assesses a company's leverage and debt-servicing capacity by comparing total debt to trailing earnings before interest, taxes, depreciation, and amortization, aiding in trend identification for credit and operational analysis. These TTM-based ratios are preferred in financial workflows for their timeliness, enabling better spotting of shifts in performance compared to calendar-year equivalents. Financial analysts routinely incorporate TTM updates into their models to monitor intra-quarter developments, adjusting figures as preliminary data or estimates emerge to maintain accuracy in forecasting and performance tracking. This practice, drawn from quarterly filings, supports dynamic analysis in , where TTM metrics are recalculated to reflect the evolving twelve-month window and inform ongoing evaluations of health.

Valuation and Investment Decisions

The trailing twelve months (TTM) metric plays a pivotal role in valuation multiples, particularly in comparable company analysis, where it is commonly applied to ratios such as enterprise value to EBITDA (EV/EBITDA). Analysts prefer TTM-based multiples over single-year figures because they provide a more stable and representative view of a company's operational performance by incorporating the most recent quarterly data, thereby reducing the impact of short-term volatility or anomalies in annual reporting periods. For instance, in assessing EV/EBITDA, the TTM EBITDA captures earnings from the past four quarters, allowing for a smoother comparison across peers and avoiding distortions from fiscal year-end timing differences. In (DCF) models, TTM serves as a foundational input for normalizing recent cash flows prior to developing forward projections. By using TTM figures, valuation practitioners establish a that reflects current operational realities, which can then be adjusted for expected growth rates and normalized for one-time events to forecast future periods more accurately. This approach ensures that the explicit forecast period—typically five to ten years—builds on a recent, annualized performance metric rather than outdated annual data, enhancing the reliability of the calculations. For investors, TTM metrics offer significant benefits in identifying cyclical trends and mitigating biases inherent in seasonal industries, such as , where quarterly sales can fluctuate dramatically due to periods. By aggregating the past twelve months of sales data, TTM helps investors discern underlying performance patterns without the distortion of peak-season spikes, enabling more informed decisions on entry or exit points in volatile sectors. This is particularly valuable for spotting sustainable growth amid cyclicality, as it provides a rolling view that adapts to evolving market conditions. In private equity contexts, TTM is integral to leveraged buyout (LBO) models for evaluating a target company's trailing performance ahead of acquisition. Private equity firms often derive the transaction enterprise value by applying a multiple to TTM EBITDA, which offers a current snapshot of profitability to assess debt capacity and potential returns under leverage. This method allows sponsors to gauge post-acquisition value creation based on recent operational metrics, ensuring the model's assumptions align with the target's immediate financial health rather than historical fiscal years.

Comparisons with Other Periods

TTM versus Calendar or Fiscal Year

The , spanning from January 1 to December 31, represents a fixed 12-month period that aligns with the standard and is the default for many and reporting obligations. However, this rigidity can introduce end-of-year distortions that may obscure true operational performance. In contrast, the trailing twelve months (TTM) metric rolls forward continuously by incorporating the most recent quarterly data, thereby mitigating these distortions and providing a smoother, more current view of financial health. Fiscal years, which may end on any month other than December to better match business cycles, further complicate direct comparisons among peers. For instance, operates on a ending in late September, creating temporal misalignment when against companies using a December year-end. TTM addresses this by standardizing evaluations to the latest 12 consecutive months, irrespective of individual fiscal calendars, enabling apples-to-apples peer analysis focused on contemporaneous performance. Fixed periods like or fiscal years offer advantages in regulatory contexts, including simplified auditing processes due to standardized timelines and alignment with filing requirements, which facilitate with statutory deadlines. Yet, these structures are inherently less responsive to intra-year shifts, such as market disruptions or operational changes, as they lock in historical boundaries until the next reporting cycle. Analysts and managers prefer fixed periods for statutory reporting and tax , where consistency with legal frameworks is , while TTM is favored for operational insights and dynamic , as it captures the most recent trends without waiting for closures.

TTM versus Forward-Looking Metrics

The trailing twelve months (TTM) relies on historical financial data to provide a backward-looking of , whereas forward-looking metrics, such as the forward twelve months (FTM) or next twelve months (NTM), are based on projected estimates for the upcoming 12-month period. FTM is commonly used in valuation multiples like the forward price-to-earnings (P/E) ratio, where the current stock price is divided by anticipated (EPS) over the next year, offering a prospective view that contrasts with TTM's reliance on audited past results. This distinction allows FTM to incorporate expected growth or changes, but it introduces greater subjectivity compared to TTM's factual basis. Analyst estimates form the core of FTM calculations, drawing from consensus forecasts aggregated by providers like , which compile projections from multiple analysts on metrics such as , , and EBITDA. These estimates are derived from company guidance, industry trends, and economic outlooks, but they carry inherent uncertainty due to potential revisions or inaccuracies in projections, often leading to variances when actual results are reported. For instance, forward P/E ratios using FTM can fluctuate based on updated consensus data, highlighting the predictive risks absent in TTM's historical accuracy. In practice, TTM is favored for conservative valuations in volatile markets, such as or commodities, where historical data provides a amid fluctuations, avoiding over-optimism from unproven forecasts. Conversely, FTM is more suitable for growth-oriented sectors like , where rapid innovation and expansion justify emphasizing projected performance over past results, as seen in valuations of companies like with expected earnings acceleration. Hybrid approaches blend TTM and FTM to enhance robustness, particularly in scenario analysis for testing, where analysts assign weights to each—such as 40% TTM and 60% FTM for stable earnings profiles or 70% TTM and 30% FTM for high-growth scenarios—to evaluate valuation outcomes under varying assumptions. This method allows for anchoring projections in historical data while stress-testing future possibilities, improving decision-making in uncertain environments.

Practical Examples

Corporate Earnings Illustration

To illustrate the application of trailing twelve months (TTM) earnings, consider Corporation's diluted () over its 2025 (FY2025), which ended on June 30, 2025. In Q1 FY2025 (July–September 2024), was $3.30; in Q2 (October–December 2024), it was $3.23; in Q3 (January–March 2025), $3.46; and in Q4 (April–June 2025), $3.65. The TTM at the end of FY2025, summing these four quarters, totaled $13.64, providing a comprehensive view of annual performance. This TTM metric updates on a rolling basis with each new quarterly report. For example, following the release of FY2026 results (July–September 2025) on October 29, 2025, where reached $3.72, the updated TTM subtracts the oldest quarter (Q1 FY2025's $3.30) and adds the new one: $13.64 - $3.30 + $3.72 = $14.06. This adjustment reflects the most recent twelve months as of September 30, 2025. The following table visualizes the quarterly and corresponding TTM at the end of each period, highlighting how TTM smooths fluctuations:
QuarterPeriodQuarterly EPSTTM EPS
Q1 FY2025Jul–Sep 2024$3.30$12.12
Q2 FY2025Oct–Dec 2024$3.23$12.42
Q3 FY2025Jan–Mar 2025$3.46$12.94
Q4 FY2025Apr–Jun 2025$3.65$13.64
Q1 FY2026Jul–Sep 2025$3.72$14.06
All figures are GAAP diluted EPS. This TTM progression demonstrates steady growth in Microsoft's , with the metric rising from $12.42 at the end of Q2 FY2025 to $14.06 by Q1 FY2026, despite a slight quarterly dip in Q2 FY2025 relative to Q1. The smoothing effect underscores underlying profitability trends, aiding in assessing sustained performance amid seasonal or one-off variations.

Economic and Market Indicators

The trailing twelve months (TTM) approach is applied to to provide a smoothed, recent view of economic performance, often using monthly or quarterly from official sources like the (BEA) and the (BLS). For instance, TTM GDP growth can be calculated by summing the real GDP values over the past four quarters and comparing the change to the prior four quarters, offering a rolling assessment that captures intra-year fluctuations better than fixed calendar-year measures. This method helps economists track economic expansions or contractions, such as identifying potential when TTM growth falls below 2% for sustained periods, as seen in analyses of BEA quarterly . Similarly, TTM rates are derived by averaging the monthly rates from BLS over the preceding 12 months, which mitigates seasonal and provides a clearer signal of labor market trends; for example, a rising TTM above 5% has historically signaled weakening economic conditions ahead of official declarations. In market indices, TTM returns aggregate daily or monthly price changes plus dividends over the past 12 months to benchmark overall performance, with the serving as a prime example. The TTM total return is computed by taking the index value at the start of the 12-month period, adding reinvested dividends, and dividing by the ending value minus one, yielding a that reflects gains; as of late 2025, this stood at approximately 17.5%, highlighting post-recovery market strength amid varying economic cycles. This rolling calculation enables investors and analysts to evaluate short-term momentum without the distortions of fiscal year-end reporting. Sector-specific applications of TTM further illustrate its utility in assessing cyclical industries, where volatility is high. In the energy sector, the TTM average WTI crude oil price is calculated by averaging monthly spot prices from the over the prior 12 months, providing a stable reference for production decisions and profitability forecasts; for instance, a TTM average below $60 per barrel in 2020 contributed to widespread cutbacks in drilling activity. Likewise, TTM housing starts sum the monthly figures reported by the U.S. Census Bureau to gauge residential trends, which are sensitive to interest rates and consumer confidence; a declining TTM total, such as the sharp declines observed in mid-2025 including an 8.5% month-over-month drop in August, signals cooling in the housing market and potential broader economic slowdowns in related industries like and materials. A notable real-world application of TTM metrics occurred with the (CPI) during the 2022-2023 surge, where the BLS's 12-month CPI change—essentially a TTM rate—peaked at 9.1% in June 2022, prompting the to implement aggressive rate hikes to curb demand. As TTM CPI cooled to 3.7% by September 2023, (FOMC) minutes reflected a shift toward monitoring progress, with core CPI at 5.3% in May 2023 influencing decisions to maintain elevated rates at 5.00-5.25% to guide back to the 2% target. This TTM-based tracking allowed policymakers to respond dynamically to volatile and food price swings, demonstrating the metric's role in real-time economic stabilization efforts.

Advantages and Limitations

Key Benefits

One primary advantage of the trailing twelve months (TTM) metric in is its ability to smooth out seasonal fluctuations, providing a clearer view of underlying performance trends. By aggregating data over a rolling 12-month period, TTM mitigates the impact of quarterly variations, such as holiday sales spikes in sectors, allowing analysts to discern long-term patterns rather than short-term anomalies. TTM also enhances timeliness in financial reporting, as it incorporates the most recent data available without requiring a full to elapse. This real-time perspective enables quicker and more informed decision-making for investors and managers, contrasting with static annual reports that may lag by several months. Furthermore, TTM facilitates greater comparability across companies with differing fiscal year-ends, standardizing evaluations on a consistent 12-month basis. This apples-to-apples approach reduces distortions from arbitrary calendar alignments, making it easier to performance in industries with diverse cycles. Finally, TTM diminishes the risk of earnings manipulation by diluting the effects of one-off adjustments or window-dressing at fiscal year-ends, as the draws from a broader, ongoing rather than isolated periods. This results in a more reliable of financial health, less susceptible to artificial distortions.

Potential Drawbacks

One significant limitation of trailing twelve months (TTM) metrics is their inherently backward-looking nature, which focuses solely on historical performance and may fail to account for imminent changes or future growth opportunities. For instance, in dynamic industries like , TTM figures might overlook the potential from a newly launched product that has not yet impacted the past 12 months of data, leading analysts to undervalue a company's . This bias can result in misguided decisions, as TTM does not incorporate forward projections, unlike next twelve months (NTM) estimates that anticipate upcoming developments. Additionally, TTM calculations rely on quarterly financial releases, which often involve reporting delays, rendering the data potentially outdated in fast-paced sectors. Public companies typically file quarterly reports 40-45 days after quarter-end under regulations, meaning TTM metrics as of a given date might exclude the most recent month's activity or reflect incomplete information. In rapidly evolving fields such as or software, where market conditions shift quickly, this lag can distort assessments of current operational health, as the trailing period may not capture recent innovations or disruptions. The process of adjusting TTM for non-recurring or one-off items introduces subjectivity, as analysts must decide which expenses or gains—such as costs or asset sales—to exclude, potentially leading to inconsistent results across evaluations. Without standardized guidelines, different practitioners might normalize figures variably, for example, debating whether a qualifies as truly non-recurring, which undermines comparability in valuations. This variability is particularly problematic in , where divergent TTM adjustments can inflate or deflate perceived enterprise value. Finally, TTM's emphasis on the immediate past 12 months can undervalue longer-term cyclical patterns, especially in industries like commodities where earnings fluctuate with multi-year economic cycles. In and gas or , a TTM snapshot might coincide with a temporary downturn, ignoring broader trends that span decades and thus misrepresenting sustainable profitability. Such overreliance on recent data risks overlooking structural factors, like cycles, that better inform long-term strategies.

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