how to find high volatility stocks: guide
How to Find High Volatility Stocks
How to find high volatility stocks is a common query from active traders and investors who want to target larger price moves, exploit option premium, or identify breakout candidates. This guide defines volatility in equities, explains why traders and options traders care about it, covers the key quantitative metrics, shows the screening tools and sample scan filters, presents indicator-based signals, and finishes with risk controls, backtesting, and a practical workflow. Read on to get step-by-step templates and a checklist you can adapt to Bitget's markets and Bitget Wallet flows.
Definition and why volatility matters
Volatility in stocks refers to the extent of price variation over time. Practically, traders measure volatility as the dispersion of returns: larger daily percent moves and wider intra-day ranges indicate higher volatility. Volatility is desirable for short-term traders, intraday scalpers, and options strategies because it creates opportunities for bigger gains (and losses) within shorter windows. For long-term investors, higher volatility often increases risk and may be undesirable unless compensated by higher expected returns.
When asking how to find high volatility stocks, consider your time frame and instruments. Day traders look for high average daily percent moves and large intraday ranges; swing traders focus on volatility expansion following consolidation; options traders seek high implied volatility or rising IV rank. All approaches must consider liquidity and catalysts — volatility without tradability is usually untradeable noise.
Volatility metrics and measurements
Below are the principal quantitative measures used to identify volatility. Understanding their differences helps you choose the right filter for your strategy.
Historical volatility (standard deviation)
Historical volatility is the standard deviation of past returns over a chosen lookback window (e.g., 20, 30, 90 days). It measures how widely past prices have dispersed around the mean. A higher historical volatility indicates that returns have varied more in the sample period. It is useful for comparing names on the same basis and for estimating realized price movement ranges.
Average True Range (ATR) and normalized ATR
ATR measures the average true range (high-low or high-previous close) over a lookback period (commonly 14 days). ATR is expressed in price units (dollars). Because ATR is absolute, normalizing ATR by dividing by price (ATR/price or ATR%) lets you compare volatility across stocks at different price levels.
Beta
Beta measures relative volatility: how a stock moves compared with a benchmark (e.g., S&P 500). A beta of 1.5 suggests the stock historically moved 1.5x the benchmark. Beta is useful for portfolio-level decisions but can miss idiosyncratic spikes and is not a good short-term volatility metric.
Implied volatility (options market)
Implied volatility (IV) is the market’s expectation of future volatility, derived from option prices. IV is forward-looking and is especially useful for options traders. IV rank and IV percentile summarize current IV relative to a historical range: IV rank tells you where current IV sits between the low and high over a lookback period (commonly 52 weeks).
Percent-range and daily high-low measures
For intraday and short-horizon traders, simple measures like daily percent change, high-low range percent, and dollar-range are practical. Relative Volume (RVOL) and percentage gap (pre-market open vs previous close) are often coupled with daily range filters to find tradable volatility.
Data and screening tools
Choosing the right data source and screener affects how quickly you can find candidate stocks. Real-time data is essential for intraday work; delayed data may be enough for swing scans.
Dedicated stock screeners (Trade Ideas, TradingView, Finviz, StockFetcher)
Trade Ideas and TradingView offer live scans and prebuilt “Most Volatile” lists. Trade Ideas provides real-time scans like "Most Volatile Stocks" or percent volatility sorts; TradingView has lists and community scripts that surface the most volatile US stocks. Finviz and StockFetcher are excellent for end-of-day or slightly delayed screening but often lack the live-feed speed for scalpers. When learning how to find high volatility stocks, start with a screener that supports live sorts and alerts.
Volatility-specific screeners and indicators (Chaikin Volatility, ATR filters)
Some services offer specialty volatility filters. Chaikin Volatility measures the difference between high-low ranges and smooths volatility expansion. MarketInOut and similar sites expose Chaikin-based screens to detect range expansion. ATR-based filters (e.g., ATR > X% of price or ATR > Y dollars) are simple and effective.
Exchange and market "most active / most volatile" lists
Major exchange pages and market portals publish lists like “Most Active,” “Top Gainers/Losers,” and “Most Volatile.” These quick lists are suitable for a rapid scan, but they are often delayed and should be combined with your own filters.
Crypto screeners (brief)
For crypto, similar tools exist — many crypto screeners rank tokens by percent move, volume spike, and liquidity. The same principles apply: combine percent move, relative volume, and market cap to avoid illiquid penny tokens. If you custody or trade tokens, prefer Bitget and Bitget Wallet for on-ramp and custody integration when applicable.
Screener criteria and sample scans
Below are practical filter designs and ready-to-adapt examples. Each template is framed for a typical trading style: day trading, swing trading, and options-based approaches. Remember that how to find high volatility stocks depends heavily on your time frame and execution constraints.
Day-trading / intraday volatility scan (example filters)
- Price: > $2 (avoid penny / microcap traps)
- Average daily volume (30-day): > 300k shares
- Relative volume (RVOL): > 2.0 (today’s volume vs average)
- Pre-market gap: > 2% or < -2%
- ATR(14)/Close > 1.5% (normalized ATR threshold)
- Daily % move (since open) > 3% or high-low % > 4%
These filters prioritize intraday tradability: avoid very low-priced, low-volume names. When using these filters you will surface names with both high volatility and sufficient liquidity.
Swing-trade / breakout volatility scan (example filters)
- Price: > $5
- Average daily volume (30-day): > 200k
- ATR(14) rising compared to ATR(50) (ATR expansion signal)
- Recent volatility expansion: ATR(14) up > 25% over last 10 trading days
- Price breaking above consolidation (e.g., 20-day high) on > 1.5x average volume
- Optional: float < 100M for amplified moves (but check liquidity)
Options-based volatility scan (example filters)
- Implied volatility (30-day) > historical 30-day vol
- IV Rank > 50 (expensive relative to 52-week range)
- Unusual options volume or high Vol/OI > 10 (spikes in options flow)
- Options volume > 1.5x 30-day avg
- Check upcoming catalyst windows (earnings, FDA, filings)
Options scans help you locate stocks where expected future moves are pricing in higher volatility. You can then choose strategies aligned with IV conditions — e.g., selling premium when IV is very high or buying volatility when expecting a big swing.
Sample Trade Ideas / TradingView configurations
On Trade Ideas, sort by percent volatility or use the "Most Volatile by %" preset, then apply filters: price floor (> $3), average volume (> 200k), and RVOL threshold (> 2). On TradingView, use the stock screener, sort by 1D volatility or ATR, and add filters for volume and market cap. These platforms let you save templates and set real-time alerts — a key step when learning how to find high volatility stocks on a schedule.
Technical indicators and signals for volatility
Indicators help confirm that volatility is expanding or contracting. Combine price action with volume and volatility indicators for higher-probability setups.
Bollinger Bands and %B / Bandwidth
Bollinger Bands widen when volatility rises. The Bandwidth indicator (upper band minus lower band normalized) is a compact volatility oscillator. A widening band signals volatility expansion, which often precedes sustained directional moves or large intraday swings. %B shows price position relative to the bands and helps detect breakout strength.
Keltner Channels and ATR-based channels
Keltner channels are ATR-based and can be used alongside Bollinger Bands. When price exits both Keltner and Bollinger extremes with volume, this is a stronger breakout signal — confirming both trend and volatility expansion.
Chaikin Volatility and other volatility oscillators
Chaikin Volatility gauges the difference between high-low ranges over time, smoothing the series to show range expansion. Tools like MarketInOut implement Chaikin-based screeners that flag volatility spikes. Use such oscillators to detect sudden increases in trading range that might not be obvious from percent-change lists alone.
Volume and Relative Volume (RVOL)
Volume confirms whether a price move is tradable. Relative Volume (RVOL) compares current volume to average volume: RVOL > 2 suggests institutional or retail attention and increases the chance the move is actionable. Never ignore low-volume moves as they are costlier and riskier to trade.
Fundamental, news and catalyst-driven volatility
Volatility often follows news. Incorporating fundamental and event-based filters helps you find names that will move around an event window.
Earnings, guidance, FDA/approval/regulatory events
Earnings and regulatory events create predictable windows of increased volatility. Screen for stocks with upcoming earnings or regulatory decisions and couple that with IV and volume filters if trading options. If you want to learn how to find high volatility stocks before earnings, filter for upcoming dates and monitor IV rises and unusual options activity.
M&A, filings, short interest and catalysts
M&A rumors, SEC filings, and high short interest percentages can lead to squeezes and volatile moves. A name with elevated short interest and a news catalyst can produce outsized moves; ensure liquidity and check the borrow availability before attempting to short.
Market-wide macro or sector events
Macro data releases (inflation, jobs, Fed announcements) and sector-specific news can spike volatility across groups. Keep an eye on VIX and sector volatility charts to know when market-wide volatility tailwinds or headwinds are present.
Volatility in options and volatility products
Options markets provide both a measure of expected volatility and instruments to trade it directly. Understanding IV, IV rank, and volatility products is essential for volatility-focused traders.
IV, IV rank/percentile and option skews
IV rank indicates where current IV stands within the prior 52-week range. IV percentile shows how often IV has been below the current level. Option skews (differences in IV across strikes) give clues on directional hedging demand. These metrics are core when determining whether to buy or sell options around a candidate stock.
Volatility ETFs and leveraged products (VIX-related, leveraged ETFs)
There are ETFs and products that provide exposure to volatility indices and leveraged equity moves. These instruments can be used for hedging or speculative plays, but they carry structural decay and tracking differences. Traders should understand product design and path-dependency before using them. For custody and trading, Bitget's suite can be a platform to consider for derivatives exposure where available.
Risk management and position sizing for volatile stocks
Volatility increases both opportunity and risk. Discipline in sizing and stops is essential.
Position sizing rules (ATR-based sizing)
Size positions so that a move of X ATR would be within your risk tolerance. Example: risk no more than 1% of portfolio value per trade. If ATR(14) = $1 and you place a stop 2 ATR away (=$2), then for a $10k portfolio you should trade a position where $2 * shares < $100 (1% of $10k), so shares < 50. ATR-based sizing links stop distance and size directly to volatility.
Stop-loss placement and exit rules
Place stops based on price structure (support/resistance) or ATR multiples. Avoid arbitrary dollar stops; instead use technical levels or ATR-based distances. Also predefine exit rules — profit targets, trailing stops, or time-based exits — to prevent emotion-driven decisions during volatile moves.
Avoiding illiquid / penny traps
High volatility in illiquid names often produces wide spreads and slippage. Apply minimum average volume, minimum ask liquidity, and minimum price filters. Prefer higher-liquidity volatile names even if potential percentage moves are smaller.
Backtesting, paper trading and verification
Before committing real capital, backtest your scans and indicators on historical data and paper-trade your setups. Confirm execution feasibility (fills, slippage) and that your screener doesn’t produce false positives due to delayed data. Use platform-sourced historical tick or minute data for intraday strategies and daily OHLC for swing rules.
Practical workflow and checklist
Here is a repeatable workflow to operationalize how to find high volatility stocks for a trading session or a swing trade.
- Run saved screener template (day or swing).
- Filter by liquidity and price rules; remove low-volume names.
- Validate catalyst: earnings, filings, unusual options flow, or sector news.
- Check intraday chart/price action and indicators (ATR, Bollinger, RVOL).
- If trading options, check IV, IV Rank, and unusual options volume.
- Size the position using ATR-based sizing and set stop and target.
- Execute using limit or proper order types and monitor volume & book depth.
- Log and review trades for continuous improvement.
Note: how to find high volatility stocks effectively is not just about the screener; it is about the full verification chain: liquidity, catalyst, volatility metric confirmation, and risk controls.
Special considerations for cryptocurrencies (brief)
Principles are similar for tokens: use percent-move and volume spike filters, watch market cap and order-book depth, and factor in 24/7 trading and exchange counterparty risk. When trading or holding tokens, prefer Bitget and Bitget Wallet for custody and trading access where Bitget supports the coin — and factor in on-chain metrics (transactions, active addresses) as analogs to volume and fundamentals.
Common mistakes and pitfalls
- Relying on a single metric (e.g., percent move alone) — combine ATR, volume, and IV for confirmation.
- Ignoring liquidity — high volatility with low liquidity equals high execution risk.
- Overtrading volatility — too many small bets increase transaction costs and emotional strain.
- Forgetting options decay and slippage in options trades; high IV can be expensive.
- Not verifying catalysts — some volatility is random and untradeable noise.
Resources, platforms and further reading
Recommended platforms and resources to continue learning how to find high volatility stocks include Trade Ideas (real-time volatility presets), TradingView (community scripts and screener), MarketInOut (Chaikin Volatility screens), and Investopedia articles on trading volatile stocks and researching volatile names. For options flow and unusual options activity, monitor Vol/OI and unusual options alerts from reputable data providers. When selecting an exchange or custody, consider Bitget and Bitget Wallet as part of your operational stack.
Appendix
Glossary of terms
- ATR: Average True Range — average of true ranges over a period; measures absolute volatility.
- IV: Implied Volatility — market-implied expected future volatility from option prices.
- IV Rank: Position of current IV within past 52-week high/low range.
- Beta: Relative volatility vs a benchmark index.
- RVOL: Relative Volume — current volume divided by average volume.
- Chaikin Volatility: An oscillator that measures range expansion using highs and lows.
- Vol/OI: Volume-to-Open-Interest ratio — used to spot unusual options activity.
Example screener templates (concise)
Day-trade template (paste into a screener):
Swing-trade template:
Options template:
These templates are designed to help you operationalize how to find high volatility stocks quickly. Adjust thresholds to match your execution and risk tolerance.
Illustrative example from recent market flow
To show how unusual options activity can signal volatility, consider a recent example: As of Jan 14, 2026, according to Barchart, Pfizer (PFE) had an options contract — the March 20 $29 put — with a Vol/OI ratio of 210.16 (volume 30,263 vs open interest 144). This elevated Vol/OI ratio represented unusually active options interest and was noted alongside additional active strikes that implied a long straddle (buying both call and put) or alternative spread strategies.
That day’s options flow illustrates a few points for volatility-seeking traders: unusual Vol/OI can highlight where market participants expect a big move; comparing options volume to the 30-day average (Pfizer’s 30-day average options volume in the cited report was 142,695) helps quantify the activity spike; and examining the implied strategies (straddle vs spread) clarifies whether participants are buying volatility outright or selling premium with defined risk. None of this is investment advice — it is an example of how data points (volume, OI, IV, and catalyst timelines) combine when assessing volatility.
Practical closing and next steps
Knowing how to find high volatility stocks requires combining metrics, screeners, and a disciplined workflow: choose appropriate volatility measures (ATR, IV, percent-range), screen with liquidity and volume filters, verify catalysts and options flow, and manage risk using ATR-based sizing and technical stops. Always backtest and paper-trade new scans.
Explore Bitget’s trading tools and Bitget Wallet to streamline market access, alerts, and custody for both equities (where supported via integrated products) and crypto volatility plays. If you’d like, I can provide ready-to-run screener templates formatted specifically for Trade Ideas, TradingView, or Finviz, and I can expand any of the sections above into further detail.
Sources and methodology: This article synthesizes screening approaches and indicators from Trade Ideas and TradingView volatility presets, MarketInOut’s Chaikin Volatility resources, Investopedia’s “Finding and Trading Volatile Stocks” guides, and recent market reporting from Barchart (Pfizer options flow example). As of Jan 14, 2026, the Pfizer example cited was reported by Barchart.
