de stock history: Deere & Company guide

DE stock history (Deere & Company)

de stock history here refers to the historical price data, corporate actions and major market milestones for DE — Deere & Company. This article compiles long‑run price series, split and dividend adjustments, notable highs and lows, and guidance on using DE historical data from common vendors. Read on to learn where DE trades, how historical series are adjusted, what drove price moves across decades, and practical tips for analysis with authoritative data sources.

Company overview and listing information

Deere & Company is a global manufacturer of agricultural, construction and forestry machinery, as well as precision agriculture technology and related services. Founded in the 19th century and headquartered in the United States, Deere is widely recognized by its green-and-yellow brand. The company’s shares trade under the ticker DE and are followed closely by investors for exposure to agricultural cycles and industrial equipment demand.

Ticker, exchange and trading identifiers

DE trades on the New York Stock Exchange under the symbol DE. Common identifiers used in data systems include the company’s ISIN and CUSIP (used in market data and regulatory filings). Typical U.S. equity trading hours apply: regular session from 09:30–16:00 Eastern Time, with pre-market and after‑hours liquidity available from many vendors and broker platforms.

Market classification and index membership

Deere is classified in industrials or machinery sectors and is commonly grouped within the agricultural equipment and heavy machinery subsectors. It is included in several major U.S. indices and large‑cap benchmarks depending on the index provider. Market‑cap classification is typically large‑cap, reflecting Deere’s multi‑dozen billion dollar market capitalization and global footprint.

Historical price data — scope and availability

Public data vendors provide DE price history at daily, weekly and monthly frequencies. Many vendors also supply intraday tick and minute data for recent periods. Historical series are commonly published in both nominal (raw close) and adjusted forms; adjusted series account for corporate actions such as splits and, where provided, dividend adjustments for total‑return studies.

Long-term coverage (decades)

Long‑run datasets for DE are available across multiple decades in major data repositories. Sources that compile long histories often include each trading day back to the 1970s or earlier, subject to vendor coverage. These long‑term series are typically adjusted for stock splits and sometimes for dividends (depending on the series), enabling multi‑decade return and CAGR calculations.

Short-term and intraday data

For short‑term work — daily and intraday — exchanges and market data vendors provide up‑to‑the‑minute quotes. Intraday data (minute bars, tick prints) is generally limited to recent years due to storage and licensing. Common providers publish daily open/high/low/close/volume files that researchers download for technical analysis and event studies.

Chronological price history and major periods

This section summarizes how DE’s share price evolved across broad multi‑year periods. The narrative complements numeric series and focuses on major drivers rather than exhaustive daily detail.

Early decades (listing to 1990s)

In its early public years and through the latter half of the 20th century, DE’s share price reflected the cyclical nature of farm equipment demand and industrial capital spending. Price movements were influenced by agricultural commodity cycles, interest rates and broader industrial demand. Historical price ranges for this period are available in long‑run datasets that are adjusted for splits but may require care when comparing nominal values across decades.

2000s and 2010s

The 2000s and 2010s saw pronounced cycles tied to farm incomes, biofuel policies, global commodity prices and construction activity. Periods of strong agricultural commodity prices and improving farm balance sheets supported equipment demand and helped lift DE stock. Conversely, commodity price declines, global recessions and weak farm cash flow depressed revenue and resulted in slower pricing trends during downturns. The 2010s also included product diversification and technology investments that influenced investor expectations.

2020s and recent performance

In the 2020s, DE’s performance reflected pandemic‑era dynamics, supply‑chain disruptions, and post‑pandemic demand swings. Supply constraints affected production and delivery schedules, while elevated agricultural commodity prices and infrastructure investment outlooks supported revenue expectations at times. As of January 2026, according to CNN Business’ Nightcap newsletter, macroeconomic discussions at global forums emphasized diverging economic outcomes, which provides useful context for understanding sector‑level demand disparities. Broader market patterns — such as elevated equity valuations and shifts in investor sentiment — have intersected with DE‑specific drivers like order backlogs and capital expenditure cycles.

Corporate actions affecting historical prices

Corporate actions materially change per‑share statistics. When working with de stock history, analysts should explicitly confirm whether a series is adjusted for splits, dividends or other actions.

Stock splits and reverse splits

When Deere has undertaken stock splits, adjusted price series reflect these events so that long‑run charts display continuous price behavior. Data vendors list split dates and ratios in corporate action tables. In adjusted series, prices and volume prior to a split are scaled to maintain consistency. Analysts should consult primary filings for exact split ratios and effective dates when precision is required.

Dividend history and yield

Deere has a history of paying regular cash dividends. Dividend policy can shift over time in response to earnings, cash flow and board decisions. For total‑return analyses, many vendors provide dividend‑adjusted or total‑return series that assume dividends are reinvested on the payment date. Adjusted close prices often incorporate split adjustments and sometimes dividend adjustments; confirm the vendor’s methodology when comparing series. Dividend yields are calculated as annual dividends divided by share price and are reported by major data providers.

Share repurchases and other capital actions

Share repurchase programs reduce outstanding shares and can increase per‑share earnings and cash flow metrics. Deere’s major buyback announcements and authorization sizes are disclosed in investor relations materials and SEC filings. Significant buybacks can influence price performance over time, particularly when executed alongside dividends and strong free cash flow.

Price milestones and records

Authoritative data providers record DE’s all‑time highs and lows, notable single‑day moves and multi‑year performance peaks. When citing a record, call out whether the figure is adjusted or nominal.

All-time high/low closing prices

All‑time closing highs and lows for DE vary slightly among vendors depending on adjustment methodology. Long‑term series from reputable providers report historical peaks (adjusted for splits) and deep troughs in prior decades. When referencing an all‑time high or low, indicate whether the value is split‑adjusted and include the reporting vendor or primary filings as the source.

Notable intraday and single-session moves

Single‑session volatility often coincides with earnings releases, macro announcements, major order or guidance updates, and geopolitical or trade developments. Intraday spikes in DE volume and price have historically followed quarterly earnings and major trade or subsidy announcements affecting agricultural markets. Data vendors provide intraday prints and daily‑change summaries to help identify these events.

Performance metrics and historical returns

There are standard metrics for summarizing de stock history: annual returns, CAGR, dividend‑adjusted total return, volatility and beta. These metrics require consistent, well‑documented input series.

Annual returns and year-by-year table

Annual return tables present opening, high, low, close and percent change for each calendar year. Vendors like those used by institutional researchers publish precomputed annual tables, and analysts can reconstruct them from daily data. When building year‑by‑year tables, clearly state whether returns are price only or dividend‑adjusted total returns.

Total return (with dividends reinvested) and CAGR

Total return measures assume dividends are reinvested on payment dates and thus capture the compounding effect of dividends plus price appreciation. CAGR (compound annual growth rate) is often used to summarize growth of a hypothetical investment over multi‑year horizons. Example studies from long‑run providers illustrate how $10,000 invested at a past date would grow under price‑only and dividend‑reinvested assumptions; those illustrations rely on consistent adjustment for splits and dividends.

Volatility, Beta and other risk metrics

Typical risk measures include historical volatility (standard deviation of returns), beta versus a market index, and drawdown statistics. Providers like Morningstar and other analytics platforms report these metrics over rolling windows (1‑, 3‑, 5‑year). For reproducibility, state the return frequency (daily, weekly, monthly) and window used to compute volatility or beta.

Drivers of historical price movements

Understanding what has driven DE’s historical price changes helps place past returns into context. Key drivers include company fundamentals, industry cycles and macro factors.

Company fundamentals and earnings

Revenue trends, margin expansion or contraction, product cycle timing, and management guidance materially affect DE stock moves. Quarterly earnings releases and annual reports are primary sources for understanding how operational performance translated into market reactions. Analysts often align earnings surprise dates with price moves to quantify sensitivity.

Industry cycles and commodity exposure

Deere’s performance is sensitive to farm incomes, crop prices, and commodity cycles. Strong commodity prices generally lift farm cash flows and equipment replacement cycles, benefiting revenues. Conversely, prolonged commodity weakness or adverse weather can suppress demand. Construction and forestry cycles also introduce additional sensitivity to infrastructure spending and broader industrial activity.

Macroeconomic and market-wide factors

Interest rates, inflation, global trade policies and investor risk appetite have affected DE historically. For example, higher interest rates can raise financing costs for equipment purchases, while trade disruptions can affect global parts sourcing and export demand. Broader equity market moves also influence DE through sector rotation and liquidity conditions.

Data sources, adjustment methodology and reliability

When compiling de stock history, choose vendors and series carefully. Differences in adjustment rules and corporate‑action treatment create variation among providers.

Adjusted vs. unadjusted closing prices

Adjusted close is a transformed value that accounts for stock splits and sometimes dividends so that the historical series reflects a continuous total‑return or split‑adjusted price. Unadjusted close shows the nominal closing price on each calendar day. For long‑term return calculations and charts, adjusted series are typically preferred; for reporting a historical nominal closing price at a given date, use the unadjusted value and disclose it as nominal.

Differences among data vendors

Different vendors may display slightly different historical highs/lows or adjusted series due to data cleaning, corporate‑action timing, or dividend reinvestment rules. To avoid inconsistencies in research, use the same vendor and adjustment method across a study and document the source. Reputable vendors maintain corporate action logs and publish methodology notes that explain adjustments.

How to cite and download historical data

Major vendors provide CSV exports, APIs or downloadable tables for daily and historical data. When downloading, note whether the file contains adjusted close fields and if corporate actions are listed separately. Observe data licensing and attribution requirements; institutional or commercial uses may require paid subscriptions or licensing agreements.

How to analyze and use DE historical data

Practical guidance helps analysts and investors turn de stock history into actionable insights without making investment recommendations.

Long-term investors vs. traders

Long‑term investors typically focus on total return, dividend history, CAGR and fundamental metrics such as revenue and free cash flow. Traders and technical analysts may prefer intraday or daily unadjusted series, volume patterns, moving averages and volatility indicators. Select data frequency and adjustment rules aligned with your horizon and analysis objectives.

Common pitfalls and adjustments

Watch for corporate‑action misadjustments, survivorship bias in peer comparisons, and mixing adjusted and unadjusted series. When performing backtests, use consistently adjusted price series and handle dividends explicitly. For intraday event studies, ensure timestamps and trade session definitions match the exchange’s official market hours.

Price‑event case studies and context (selected examples)

Below are representative examples of event‑driven moves and how to interpret them in the context of de stock history. These are illustrative and not exhaustive.

Earnings surprises and guidance changes

Earnings releases that materially beat or miss consensus often generate sizable single‑day moves. Positive order activity or upward guidance typically supports higher prices, while supply constraints or downward guidance can trigger sell‑offs. Compare pre‑ and post‑earnings adjusted series to isolate reaction magnitude.

Commodity and policy shocks

Sharp moves in crop prices, changes in biofuel mandates, or tariffs affecting agricultural trade can alter farmer economics and equipment demand. In some years, commodity rallies have coincided with multi‑quarter gains in order books and stock appreciation for DE.

Supply‑chain constraints and inflationary pressures

Global supply‑chain disruptions have periodically delayed deliveries and constrained revenue recognition. Inflationary input cost increases can compress margins absent offsetting price pass‑through. Monitoring order backlog and margin trends in earnings materials helps link these operational issues to price action.

Price milestones and records (select figures)

Compiling authoritative milestone figures requires using a single vendor and clearly stating adjustment conventions. Below are typical milestone categories to report when building a milestone table from primary sources.

• All‑time adjusted closing high and date (state vendor and adjustment basis).
• All‑time nominal closing high and date (unadjusted).
• Historic low closing prices (adjusted and nominal) and context.
• Largest single‑day percent gain and loss with event context.
• Multi‑year total‑return multiples (e.g., 10‑, 20‑, 30‑year growth of $10,000 under dividend reinvestment).

Data sources and recommended providers

For de stock history, use a mix of primary filings and reputable market data vendors. Primary sources include the company’s investor relations materials and regulatory filings. Secondary data providers compile historical series and corporate action logs that facilitate research. Recommended source types:

• Company investor relations and SEC filings for official corporate actions, filings and IR disclosures.
• Major financial data vendors providing daily and intraday series and corporate‑action tables.
• Specialized historical datasets and academic sources for very long‑run series and total‑return reconstructions.

When citing data, identify the vendor and whether the series is adjusted for splits or dividends. Where small differences among providers appear, reconcile by checking corporate action logs and the vendor's stated methodologies.

Practical steps to build a reliable DE historical series

1. Start with a primary price series (daily OHLCV) from a single vendor to ensure consistency.
2. Download corporate action logs (splits, dividends, buybacks) from company filings and the vendor.
3. Decide on an adjustment policy: splits only (for price continuity) or splits plus dividends (for total return).
4. Apply adjustments consistently and document the dates and ratios used.
5. Validate milestone values (all‑time highs/lows) against the adjusted series and source notes.

How to use DE historical data for specific analyses

Common studies using de stock history include total return computations, event studies around earnings and product announcements, seasonality analysis across planting/harvest cycles, and cross‑sectional comparisons with peers.

Total‑return performance over multi‑decade horizons

To compute total return, use a dividend‑reinvestment approach where dividend cash flows purchase additional shares on payment dates. Ensure splits are accounted for by rescaling shares consistently. Present both price‑only and total‑return series for transparency.

Seasonality and rolling returns

Seasonality tests examine whether certain months or quarters systematically produce stronger or weaker returns — for example, aligning price behavior with planting seasons or harvest outcomes. Rolling return windows (1‑, 3‑, 5‑year) help show how performance evolves across market cycles.

Volatility and risk analysis

Compute annualized volatility from daily returns and report maximum drawdowns. For beta, regress DE returns on a broad market index over a fixed window and report the estimation period. Provide sensitivity tables to show how beta and volatility change with different windows.

Limitations, reliability and best practices

Historical price work is subject to data quality limits. Best practices include confirming corporate actions with primary filings, documenting all adjustment steps, and using consistent vendor series for backtests. Avoid mixing adjusted and unadjusted series and always state the basis of reported figures.

See also

• Deere & Company (company profile and investor materials)
• List of agricultural equipment manufacturers and industry peers
• Stock split history and dividend policy pages
• Methodology articles on adjusted historical prices and total‑return calculation

References

Primary data and background for this de stock history guide are drawn from the following types of sources (vendor names and primary filings):

• Deere & Company investor relations and SEC filings (official corporate actions and disclosures)
• Major financial data vendors and historical price compilers
• Market quote aggregators and historical archives for long‑run series
• Independent financial research platforms that publish annual tables and total‑return illustrations
• CNN Business’ Nightcap newsletter (context on global economic themes). As of January 2026, according to CNN Business’ Nightcap newsletter, global forum discussions highlighted widening economic divergence and the implications for markets and policy.

Notes for editors / data maintainers

Numerical tables (annual returns, split schedules, dividend tables) should be constructed from primary sources: company filings and reputable historical data vendors. All figures must clearly state whether values are adjusted for splits or dividends. Update the recent‑year performance and metrics after each quarterly release and after any corporate action.

• State the update cadence for price and corporate action tables (recommended: monthly for price snapshots, immediate after corporate actions).
• Indicate the vendor used for the master time series and include a methodology note explaining adjustments.
• When publishing milestone numbers (all‑time highs/lows), report whether values are nominal or adjusted and the vendor source.

Further reading and practical tools

To work with DE historical series, analysts commonly export CSV files from vendors, use scripting languages for adjustment (Python/pandas, R), and validate with company filings. For on‑platform execution and trading access, Bitget offers market access and wallet tools — explore Bitget for trading infrastructure and Bitget Wallet for custody of digital assets where relevant. Note: this article is informational and does not constitute investment advice.

Editorial and citation reminders

Always include the reporting date when citing news context. For example: "As of January 2026, according to CNN Business' Nightcap newsletter..." Quantitative metrics cited in the article (market cap, daily volume, dividend amounts) should be verifiable from the referenced provider or filing and labeled with the observation date.

Actionable next steps

If you want a ready dataset or tables:

• I can produce a filled‑in draft article with annual return, split schedule and dividend history tables built from selected vendors and Deere filings.
• I can export a daily adjusted close CSV for DE from a preferred vendor and provide methodology notes for adjustments.

Explore Bitget for trading infrastructure and Bitget Wallet for custody and wallet management. For data downloads, use your preferred data vendor and ensure licensing compliance.

Further edits or a downloadable dataset can be prepared on request — please specify the vendor, adjustment basis (splits only or splits+dividends), and desired time range.