What stocks have fallen the most

This guide explains what stocks have fallen the most, how that question is usually measured, the data sources and metrics used, common causes of steep declines, notable historical examples, and ste...

2025-11-16 16:00:00

By Cyber Fusion

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What stocks have fallen the most

What stocks have fallen the most is a common search for investors and traders trying to identify the largest losers over a chosen period—intraday, daily, monthly, year‑to‑date, or all‑time—either by percentage or by absolute dollar decline. In equity markets this question may focus on US stocks, a specific index (for example, the S&P 500), or global listings; analogues exist for cryptocurrencies where round‑the‑clock trading changes measurement windows. This article explains typical interpretations of "what stocks have fallen the most", the metrics and edge cases you should know, primary data sources, typical list content, causes of large drops, historical examples, how professionals use these lists, and how to build your own screener. Read on to learn practical, verifiable methods and safe best practices.

Note: All factual references to news items state reporting dates. For example, as of January 15, 2026, PA Wire reported a jump in credit‑card defaults in the UK that signals household stress, which can be an indirect driver of equity weakness in consumer‑facing sectors.

Interpretation and scope of the query

When someone asks "what stocks have fallen the most" they are usually asking for a ranked list of securities that experienced the largest decline under a chosen metric and timeframe. Clarifying the intended scope first avoids misleading results:

Metric: percent change (relative loss) versus absolute dollar decline (absolute loss). Percent change is the default for many screens; dollar decline better highlights the impact of moves in large‑cap names.
Timeframe: intraday, previous trading day, 7‑day, 30‑day, year‑to‑date (YTD), 1‑year, or all‑time decline. Rankings change materially across windows.
Universe: entire exchange(s), a single index (S&P 500, FTSE 100), country or region, or custom watchlists. Including OTC/pink sheets or penny stocks dramatically changes the output.
Asset class: the phrase applies to traditional equities and can be adapted to ETFs, ADRs, and digital assets (cryptocurrencies). For 24‑hour crypto comparisons, the standard window is different from market‑hours equities.

Common variations of the query include "what stocks have fallen the most today", "what stocks have fallen the most this month", and more specific filters such as "largest market‑cap decliners" or "index constituents that fell the most." The intended use—research, risk monitoring, short candidate identification, or watchlists for potential rebounds—helps determine the right interpretation.

Metrics and measurement methods

Percent decline vs absolute dollar decline

Percent decline (percentage loss): Calculated as (Close_t - Close_t‑1) / Close_t‑1 × 100 for a chosen timeframe. This metric normalizes for price and is useful to compare small‑cap or penny stocks with large‑caps. A $1 fall on a $5 stock (20%) is not the same economic magnitude as a $1 fall on a $500 stock (0.2%), so percent change helps show proportional moves.
Absolute dollar decline: Measures the raw change in price (Close_t - Close_t‑1). It highlights the real dollar impact and is often used to identify which large‑cap names or index members caused the largest point losses in indices.

Choosing percent versus absolute dollar is critical depending on your goal: use percent for volatility and relative performance screens; use absolute dollar decline when assessing contributions to index point moves or real wealth impact on large holdings.

Timeframes

Intraday: Measures from previous close to current intraday price or from open to current price. Useful for live trading but sensitive to pre‑market and after‑hours moves.
Daily (day‑over‑day): Compares the previous official close to today’s close. This is the standard for “day losers”.
Weekly / Monthly: Captures medium‑term trends and can expose stocks in multi‑day drawdowns or those reacting to delayed news.
Year‑to‑date (YTD): From the first trading day of the calendar year to the present; popular for performance summaries.
1‑year and all‑time: Include longer‑term structural declines and corporate disasters.

Ranking composition changes with timeframe—small‑cap speculative names often dominate intraday and short windows, while structural declines and bankruptcies appear more clearly over longer windows.

Adjustments and edge cases

Several corporate and market events require careful handling when measuring declines:

Stock splits and reverse splits: Use adjusted historical prices (adjusted close) to maintain continuity. A 10‑for‑1 split multiplies share count and reduces price; failing to adjust can make a fall look artificially large or small.
Dividends: Total return measures adjust for dividends; headline price declines do not, so clarify if you use price or total‑return data.
Delistings and bankruptcies: When a company is delisted or declares Chapter 11 (or equivalent), its last public price may not reflect ultimate investor losses. Some screens drop delisted names or flag them.
Survivorship bias: Historical lists that omit companies that ceased to exist can understate true rates of loss. Use datasets that include delistings for complete historical analysis.
Pre‑market and after‑hours moves: Many data providers report extended‑hours price changes separately or include them in intraday feeds. Be explicit whether you include extended sessions.

Inclusion rules

Define which securities to include before ranking:

ETFs: Including leveraged or inverse ETFs will place very volatile funds high on losers lists; many analysts exclude leveraged ETFs when seeking underlying equity moves.
ADRs: Include American Depositary Receipts if you want US‑listed representations of foreign stocks.
OTC / Pink Sheets: Highly speculative; include only with strict liquidity filters to avoid noise.
Minimum market cap / volume filters: Typical filters (e.g., market cap > $50m, average daily volume > X shares) reduce microcap noise and pump‑and‑dump artifacts.

Clear inclusion rules materially improve the signal‑to‑noise ratio in any "what stocks have fallen the most" report.

Primary data sources and ranking providers

Below are commonly used public sources and screeners for "biggest losers" lists. These providers differ in coverage, update frequency, and available filters.

Yahoo Finance — “Top Daily Losses / Day losers”

Yahoo Finance provides widely used intraday and daily lists for US stocks, with quick access to charts, news items, and basic financials. It is a common starting point for retail traders checking day‑to‑day losers.

TradingView — “Biggest Stock Losers”

TradingView offers an interactive screener with powerful charting and user‑defined filters (market cap, sector, technical indicators). It is useful for traders wanting to cross‑reference technical setups with daily losers.

StockAnalysis — “Today’s Top Stock Losers” and period filters

StockAnalysis lists intraday and period losers with links to financial statements and common indicators. Period filters (like monthly losers) help identify sustained drawdowns.

Investing.com — “Top Stock Losers”

Investing.com provides global coverage with country and region filters, allowing users to see top losers across many exchanges and timeframes.

The Motley Fool — “Today’s Biggest Stock Losers”

The Motley Fool pairs editorial commentary with daily losers lists, offering qualitative context that can help separate noise from fundamental stories.

MarketBeat — “Biggest Stock Losers (this year/month)”

MarketBeat offers timeframe filters and historical comparisons, making it easier to see which stocks led declines in a specified period.

Slickcharts — “S&P 500 losers”

Slickcharts focuses on index constituents, making it straightforward to rank the S&P 500 or other indices by percent change—useful for index‑centric analyses.

Hartford Funds / historical analyses

Institutional research providers and asset managers (for example, Hartford Funds) publish historical analyses of large market drops and recoveries. These are helpful for context when discussing systemic, single‑day index declines and long‑term recoveries.

Note: many investors combine more than one of the above sources to verify rankings and to link price moves to news or filings.

Typical content of a “biggest fallen” listing

A practical "biggest fallen" row or card typically contains the following fields so readers can quickly understand the context of the move:

Ticker symbol
Company name
Last price (and currency)
Absolute change and percent change (both shown)
Volume and average volume for context
Market capitalization
52‑week range (low/high)
News links or headlines (reason for move) and chart thumbnail
Exchange or region and trading status (e.g., halted, delisted)

Providing these elements makes it easier to separate meaningful declines (company news, earnings misses) from spurious moves caused by low liquidity.

Causes and common drivers of large declines

Large price drops often have identifiable drivers. Understanding categories of causes will help you interpret any "what stocks have fallen the most" list.

Company‑specific events

Earnings misses and guidance cuts: Disappointing revenue, EPS, or forward guidance often trigger sharp single‑day declines.
Fraud or restatements: Accounting irregularities or fraud allegations can cause multi‑day collapses.
Regulatory action or litigation: Investigations, fines, or bans can materially impair a business’s outlook.
Bankruptcy filings: A Chapter 11/Chapter 7 filing typically destroys equity value.
Management changes: Sudden CEO or CFO departures can spook investors if tied to performance or governance concerns.

Macro and sector moves

Interest‑rate shocks: Rapid rate increases can hurt growth‑oriented stocks and sectors like real estate and utilities.
Commodity price swings: Energy and materials companies are sensitive to oil, metals, and soft‑commodity prices.
Regulatory regime changes: New laws or enforcement trends can hit entire sectors simultaneously (e.g., tighter lending rules impacting banks).

Market structure and technical causes

Forced liquidations and margin calls: Leveraged investors being forced to sell can flood markets and amplify declines.
Options‑related flows: Large option expirations or gamma squeezes in reverse can accelerate declines.
High short interest: While high short interest can set up short squeezes to the upside, it can also magnify downside when fundamentals turn.

Manipulation and low‑liquidity stocks

Penny‑stock volatility: Low‑price, low‑float securities are vulnerable to pump‑and‑dump schemes and rapid collapses.
Low float/illiquidity: Thin markets produce larger price moves on modest orders; filter these when compiling meaningful lists.

Notable historical and recent examples

A "biggest fallen" list can reflect single‑day systemic shocks or individual company collapses. Historical market events provide perspective:

Market‑wide single‑day shocks: Examples include Black Monday (October 19, 1987) and the March 2020 crash, often highlighted in historical analyses by asset managers such as Hartford Funds for magnitude and recovery timelines.
Company collapses: Individual firms that collapsed due to fraud, insolvency, or catastrophic product failures often top all‑time losers lists.

Context matters: broad market plunges will populate losers lists with many large‑cap names, while company‑specific scandals will concentrate losses in one or a few tickers.

Applications and how investors/traders use these lists

Lists answering "what stocks have fallen the most" are used for several practical purposes:

Watchlists for potential rebounds: Deep pullbacks can create long opportunities for value investors who perform thorough fundamental checks.
Short‑selling candidates: Traders look at extended declines that continue to signal weakening fundamentals or technical breakdowns.
Risk monitoring: Portfolio managers watch for sectoral concentration of losers as a stress indicator.
Idea generation: Activist investors and turnaround specialists may screen for mispriced companies with operational issues that can be corrected.
Input to algorithms: Quant strategies use loser lists as inputs for mean‑reversion or momentum strategies.

When using these lists, practitioners always combine price data with news, filings, liquidity filters, and fundamental metrics before taking action.

Limitations, caveats and best practices

A raw list of "what stocks have fallen the most" is a starting point—not a trading plan. Key limitations and best practices include:

Data latency: Real‑time feeds can lag; verify with a primary exchange or multiple sources.
Survivorship and selection bias: Historical summaries that exclude delisted entities understate tail risk.
Noise from microcaps and OTCs: Apply minimum market cap and volume filters to avoid pump‑and‑dump artifacts.
Confirm with official filings and trusted news: A large price move may be explained by an 8‑K, trading halt, or regulatory filing.
Avoid acting on lists alone: Always read the underlying news and check fundamentals. This is not investment advice—only a framework for analysis.

Variations for cryptocurrencies and digital assets

For crypto markets, the same question—what tokens have fallen the most—uses analogous metrics but with some differences:

Time windows: The standard crypto window is 24 hours for many data providers, though weekly and monthly rankings are common.
Round‑the‑clock trading: Crypto markets operate 24/7, so intraday labels differ from equity market conventions.
Tokenomics events: Burns, mints, token unlocks, or protocol upgrades can cause sharp moves.
Exchange delistings and forks: A token being delisted by major platforms or a contentious fork can precipitate steep falls.
Data providers: Common crypto trackers include CoinMarketCap, CoinGecko, TradingView, and exchange orderbooks (note: when using exchanges for price data, custody and execution can be done on regulated platforms—Bitget is recommended for trading and Bitget Wallet for custody).

Crypto losers lists tend to have more extreme percentage moves due to lower liquidity and higher retail speculation; apply strict market cap and liquidity thresholds when building screens.

How to construct your own “biggest losers” query or screener

A simple, reproducible methodology helps build a meaningful list. Below is a practical checklist and sample algorithm.

Checklist before building a screener:

Choose timeframe (e.g., daily, 30‑day)
Choose metric (percent change or absolute dollar decline)
Choose universe (exchange(s), index, or global)
Apply minimum market cap filter (e.g., > $50m) and minimum average daily volume
Decide whether to include ETFs, ADRs, and OTC listings
Use adjusted closes to handle corporate actions

Sample algorithm (percent losers, daily):

Universe = all US‑listed equities with market cap >= $50m and average daily volume >= 100k shares.
For each security compute percent change = (close_today - close_yesterday) / close_yesterday × 100.
Exclude securities with trading halts or delisting notices.
Rank descending by absolute percent decline and present top N losers with volume and market cap.
Flag items with recent filings (8‑K, earnings release) or regulatory notices for user review.

Sample algorithm (absolute dollar decline, daily):

Universe = S&P 500 constituents only.
For each constituent compute dollar decline = close_today - close_yesterday.
Rank by dollar decline to identify names that drove index point moves.

Advice on handling corporate actions: Always use adjusted close series (adjusted for splits and dividends) for percent calculations and store raw corporate action flags to explain abrupt history breaks.

References and external sources

For live lists and up‑to‑date rankings, consult the following providers (site names only; live lists should be checked on the provider platforms):

Yahoo Finance — Day Losers (top daily losses)
TradingView — Biggest Stock Losers (US)
StockAnalysis — Today’s Top Stock Losers / Monthly losers
Investing.com — Top Losers (global)
The Motley Fool — Today’s Biggest Stock Losers
MarketBeat — Biggest Stock Losers (this year / this month)
Slickcharts — S&P 500 losers (index‑constituent focus)
Hartford Funds — Historical top market drops & recoveries

As of January 15, 2026, according to PA Wire (Daniel Leal‑Olivas/PA Wire), lenders reported a jump in credit‑card defaults that was the largest increase in nearly two years for the UK. Such macro conditions—rising defaults, weakening mortgage demand, and a softer job market—create sector‑level stress that can appear on "what stocks have fallen the most" lists, particularly among domestically focused consumer names.

Appendix: Example methodologies

Example 1 — Daily percent losers (pseudo‑code):

Data inputs: adjusted_close(t‑1), adjusted_close(t), avg_daily_volume_30d, market_cap
Filters: market_cap >= 50_000_000 and avg_daily_volume_30d >= 100_000
Compute percent_change = (adjusted_close(t) - adjusted_close(t‑1)) / adjusted_close(t‑1) × 100
Exclude securities with delisting_flag == true
Output: top 50 by lowest percent_change with columns [ticker, company_name, adjusted_close, percent_change, volume, market_cap, 52wk_low, 52wk_high]

Example 2 — S&P 500 dollar impact screener (pseudo‑code):

Data inputs: close(t), close(t‑1), index_members
For each S&P 500 constituent compute dollar_change = close(t) - close(t‑1)
Multiply by float_shares to compute market‑value change contribution
Rank by market‑value change to see which names contributed most to index point losses

Note: Use adjusted pricing and corporate action flags; test logic across multiple sample days to ensure expected behavior.

Final guidance and platform note

Lists answering "what stocks have fallen the most" are a useful starting point for research, alerts, and risk monitoring, but they should never replace careful fundamental and news verification. To act on ideas or to execute trades derived from loser lists, use a trusted trading platform and secure custody. For traders and investors looking for a reliable trading partner and noncustodial custody, consider Bitget for execution and Bitget Wallet for secure custody and token management within the Web3 ecosystem. Bitget provides order types, risk management tools, and wallet integration to help users transition from research to execution responsibly.

Further exploration: build a screener with clear filters, cross‑check ranked names against filings and trusted news, and maintain a watchlist of flagged stocks with reasons for each entry. If you want to track daily losers quickly, consult the live lists on the data providers named above and verify any extreme moves with filings or exchange notices.

Next step: If you want, I can provide a ready‑to‑run screener template (CSV or pseudo‑SQL) using percent decline or dollar decline logic and suggested filter thresholds to help you generate a clean "what stocks have fallen the most" list for a chosen universe.

The content above has been sourced from the internet and generated using AI. For high-quality content, please visit Bitget Academy.