how to know what stocks will go up

Practical, step-by-step guide for investors and traders on how to know what stocks will go up: fundamentals, technicals, quantitative screens, sentiment, tools, risk management and workflows. Neutr...

2025-11-06 16:00:00

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How to Know Which Stocks Will Go Up

how to know what stocks will go up is a common question for investors and traders. This guide explains the main methods and indicators used to identify stocks likely to appreciate: fundamental analysis, technical analysis, quantitative models, sentiment and analyst research. It clarifies realistic expectations, required tools (including Bitget trading and Bitget Wallet where relevant), and a reproducible workflow you can use for idea generation, validation and risk management.

Overview — predictability and realistic expectations

No method guarantees outcomes: learning how to know what stocks will go up is about increasing probability, not certainty. Successful approaches treat predictions as probabilistic, combine multiple evidence sources, and enforce risk controls (position sizing, stop rules, diversification).

As of 2026-01-15, according to Investopedia and other educational sources, the best practice is to separate two questions: (1) which companies have structural reasons to appreciate over the long term, and (2) when to buy or sell based on market timing or catalysts. This guide covers both.

Fundamental analysis

Fundamental analysis helps answer how to know what stocks will go up over medium-to-long horizons by assessing business health, profitability, growth potential and valuation.

Financial statements and key metrics

Income statement: revenue growth, gross/profit margins, operating margin, net income and EPS trends. Look for consistent revenue and EPS growth over multiple years.
Balance sheet: cash on hand, total debt, current ratio, debt/equity. Healthy balance sheets reduce the risk of distress that can depress stock prices.
Cash flow statement: free cash flow (FCF) generation and trend. Companies that convert earnings into cash sustainably have stronger upside potential.
Key ratios: P/E, PEG (P/E divided by growth), P/B, EV/EBITDA, ROE, ROIC. Compare ratios to peers and historical ranges to gauge relative valuation.

Practical thresholds vary by sector. For small‑cap or cyclicals, expect more volatility; for large‑cap, look for steady margins and cash flow. When screening, many investors filter for market cap > $500M–$1B and average daily volume > 250k–1M shares to ensure liquidity for trading.

Business quality and competitive advantages

Understand the company’s moat: proprietary technology, network effects, brand strength, regulatory barriers, or cost advantages. High-margin revenue streams, recurring revenue and low customer churn increase the probability that a stock will trend up over time. Assess management track record, governance, insider ownership and capital allocation decisions.

Valuation methods

Valuation helps decide whether potential upside is priced in. Common approaches:

Discounted cash flow (DCF): models intrinsic value by forecasting FCF and discounting to present value. Use sensitivity tables for growth and discount rate assumptions.
Comparable multiples: compare P/E, EV/EBITDA, P/S to industry peers and historical bands.
Relative and sum-of-parts: useful for conglomerates or firms with distinct businesses.

Valuation does not predict timing. A stock can remain undervalued for long periods; combine valuation with catalysts and technicals for timing.

Earnings, guidance and catalysts

Earnings surprises, upgraded guidance, product launches, regulatory approvals, strategic partnerships and M&A are common catalysts that can trigger price appreciation. Track the company’s earnings calendar, read earnings transcripts and monitor management guidance. Analyst revisions following catalysts often accelerate moves.

Technical analysis

Technical analysis answers short-to-medium-term timing questions: once you find candidates via fundamentals, technicals help determine entry, exits and risk levels.

Price trends and chart patterns

Trend identification: determine whether the stock is in an uptrend, downtrend or range. Use higher-timeframe trends (weekly/monthly) for context and daily/ intra-day for timing.
Support and resistance: price zones where buyers or sellers historically stepped in. Breaches plus confirmation often indicate sustained moves.
Chart patterns: breakouts from consolidations, flags, head & shoulders, double bottoms/tops. Patterns should be combined with volume and other indicators for validation.

Indicators and overlays

Moving averages: 50-day and 200-day simple or exponential moving averages are popular trend filters. Golden cross (50 crossing above 200) signals medium-term strength; death cross is the opposite.
RSI (Relative Strength Index): measures momentum and potential overbought/oversold conditions (commonly 30/70 thresholds).
MACD: trend-following and momentum indicator for crossovers and divergence.
Bollinger Bands: measure volatility and possible reversion or continuation setups when price breaks bands with volume confirmation.

Indicators are tools, not rules. Combine multiple indicators and timeframes to reduce false signals.

Volume and confirmation

Volume confirms price moves. A breakout on rising volume is more reliable than one on thin volume. For liquid US equities, look for relative volume (current volume vs average) to validate entries: breakouts with relative volume > 1.5–2x carry more conviction for many traders.

Scanning and pattern-based screening

Use charting platforms to run scans for momentum, new highs, moving-average crossovers and volume surges. Weekly and daily scans produce idea lists you can subject to fundamental triage. Maintain watchlists and alerts for follow-up.

Quantitative and algorithmic methods

Quant approaches formalize signals into rules and rank stocks systematically. They can scale idea generation and remove some behavioral bias—but they require careful validation.

Factor models and quantitative screens

Common factors:

Value: low price multiples (P/E, P/B, EV/EBITDA).
Momentum: price performance over 3–12 months.
Quality: profitability, stable earnings, low leverage.
Size: small‑cap premium (higher risk).
Low volatility: stocks with lower drawdowns.

Combine factors (e.g., quality + momentum) to improve robustness.

Backtesting and statistical validation

Backtest strategies on historical data, separate in-sample and out-of-sample periods, and use walk-forward tests to evaluate stability. Beware overfitting: a model that perfectly explains the past may fail out-of-sample. Key metrics: CAGR, Sharpe ratio, max drawdown, win rate and turnover. Validate transaction costs and slippage, especially for frequent trading.

Machine learning and automation (limits)

Machine learning can uncover non-linear patterns but requires high-quality, extensive datasets and careful feature engineering. Typical limits: data snooping, look-ahead bias and interpretability challenges. ML models can assist in scoring candidates but do not guarantee future returns.

Analyst research and market consensus

Sell-side and independent analysts aggregate company knowledge and provide forecasts. Use analyst output as one input, not the sole reason to trade.

Analyst ratings and price targets

Consensus price targets and upgrade/downgrade activity can signal perceived upside. For example, a material increase in consensus price targets across multiple reputable analysts may indicate reassessed prospects. However, analyst coverage is not available for all stocks (less for microcaps), and conflicts of interest exist.

Using sell-side research and institutional reports

Read sell-side research for financial models and scenario analysis; cross-check with independent research and company filings. Institutional reports (when accessible) can show trend adoption data, but remember institutional intent does not necessarily predict stock moves.

Sentiment, news and alternative data

Sentiment and alternative data capture behavioral and real‑world signals that fundamentals or price history may miss.

Newsflow and event-driven moves

News events—earnings surprises, M&A, regulatory changes—cause sharp moves. Use real-time news feeds and monitor SEC filings and company press releases. Quick, documented news reactions often form short-term trading opportunities; for longer-term investors, reassess thesis when news materially changes fundamentals.

Market sentiment indicators

Useful indicators: VIX (market volatility gauge), put/call ratios, short interest, mutual fund/ETF flows and retail sentiment indexes. Social media sentiment (message boards, platform chatter) can hint at retail-driven momentum but carries noise and manipulation risk.

Alternative data and channel checks

Alternative data includes web traffic, app downloads, transactional volumes, satellite imagery, supplier checks and job postings. For public companies, these can validate demand trends before earnings. For tokenized assets, on-chain metrics (transactions, active addresses, staking rates) are key analogues. Ensure data sources are reliable and legally obtained.

Macroeconomic and sector context

Macro conditions often determine sector leadership and valuation multiples. Knowing macro trends helps answer how to know what stocks will go up within specific environments.

Interest rates, inflation and GDP effects

Higher interest rates compress valuation multiples for growth stocks and favor financials or commodity-linked sectors, while lower rates often support higher valuations for growth names. Track central bank guidance, inflation prints and GDP growth to anticipate sector rotations.

Sector rotation and relative strength

Compare sector relative strength vs. broad benchmarks. A stock with strong fundamentals but in a weak sector may lag. Leaders often emerge within leading sectors—focus screening on outperforming sectors to increase odds of picking stocks that will go up.

Tools, screeners and resources

Efficient tooling accelerates research: screeners, charting platforms, broker research, filings and data providers.

Stock screeners and filters

Set screens for growth/value/momentum criteria. Example starter filters: market cap > $1B (for tradability), 3–5 year revenue growth > 10% (growth screen), PEG < 1.5 (value+growth blend), or 3‑month price performance > 20% (momentum). Refine by sector and liquidity.

Broker/platform research tools and charting software

Use institutional-grade charting and alerts. If you trade or hold on an exchange, consider executing via Bitget for spot and derivatives needs, and use Bitget Wallet for custody and token interactions. Charting platforms like TradingView-style interfaces, StockCharts-style scans and broker tools provide the technical functionality required for scans, backtests and alerts.

Financial filings and regulatory sources

Primary sources: annual reports (10‑K), quarterly reports (10‑Q), current reports (8‑K), earnings transcripts and proxy statements. These sources provide verifiable facts: revenue, guidance, legal risks and capital structure changes. As of 2026-01-15, reading filings remains the most reliable way to verify company-reported metrics (source: The Motley Fool / Fidelity educational material).

Research workflow — step-by-step checklist

Idea generation: screens, news, analyst notes, sector leaders, alternative data or thematic bets.
Fundamental triage: quick filter for market cap, revenue/EPS trend, margin stability, debt levels and primary risks.
Deep fundamental check: read filings, model cash flows, assess moat and catalysts.
Technical timing: identify entry/exit levels, stop-loss, and required volume confirmation.
Position sizing & risk plan: decide allocation, max drawdown tolerance and correlation to portfolio.
Execution & monitoring: enter trades on a reliable platform (e.g., Bitget), monitor news/metrics and adjust stops or book profits per the plan.

Document thesis and exit rules before entering a position. Keep concise watchlists and revisit theses after new earnings or material news.

Strategies by time horizon

Long-term investing approach

Long-term investors focus on fundamentals, valuation and business durability. Metrics: multi-year revenue and EPS growth, FCF yield, return on capital and durable competitive advantages. Rebalance periodically and focus on compounding drivers like dividends and reinvestment. Use tax-advantaged accounts and avoid excessive trading friction.

Short-term trading/swing trading approach

Swing traders prioritize technicals and catalysts. Liquidity, tight spreads and clear stop rules are essential. Typical tools: daily/weekly charts, momentum indicators, relative volume filters and event calendars for earnings or product releases.

Day trading and momentum strategies

Day traders require real-time data, low-latency execution and strict risk controls. Focus on intraday patterns, order flow, level‑2 data and volatility. These strategies demand resources, disciplines and often higher margins; they are not suitable for all investors.

Stocks vs cryptocurrencies — differences in prediction

When asking how to know what stocks will go up compared with crypto tokens, note key differences:

Fundamentals: stocks have earnings, cash flows and regulatory filings; tokens may rely on protocol usage metrics, tokenomics and on-chain activity.
Market hours and liquidity: crypto trades 24/7; US equities have set market hours, affecting the timing and nature of price moves.
Volatility: tokens often show higher volatility; position sizing and stop rules must adapt accordingly.
Data sources: for tokens, use on-chain metrics (transactions, active addresses, staking rates) and Bitget Wallet analytics; for stocks, use filings, corporate guidance and broker research.

While the analytical frameworks (fundamentals, technicals, sentiment) overlap, the inputs and execution differ materially between equities and crypto assets.

Risk management, position sizing and portfolio construction

Risk management determines whether you survive long enough for a prediction to be profitable. Key elements:

Diversification: avoid concentrated bets unless conviction and position sizing justify them.
Position sizing rules: use fixed fractional sizing (e.g., risk 1–2% of portfolio per trade) or volatility‑adjusted sizing.
Stop losses and exit criteria: set rules based on technical invalidation points or changes to the investment thesis.
Expected drawdowns: prepare for multi-week or multi-month drawdowns; measure portfolio risk with stress tests and scenario analysis.

Common pitfalls and cognitive biases

Watch for bias and errors that can undermine attempts to learn how to know what stocks will go up:

Confirmation bias: seeking information that supports a preformed view.
Overfitting: tailoring models to historical noise rather than signal.
Herd behavior and FOMO: chasing popularity rather than quality.
Survivorship bias: ignoring delisted or failed companies when evaluating past performance.
Misinterpreting correlation as causation: two trends moving together doesn’t mean one caused the other.

Limitations, ethics and regulatory considerations

No method guarantees success. Researchers must avoid using or acting on material non-public information; insider trading laws apply. Maintain ethical research standards: verify data sources, disclose conflicts and avoid manipulative practices (e.g., posting false social-media claims to influence price).

Practical examples and case studies

Below are illustrative workflows (not trade recommendations) showing how different approaches find candidates that may appreciate.

Example 1 — undervalued company (fundamental workflow)

Screen for companies with PEG < 1, positive FCF and ROIC > 10%.
Read latest 10-K/10-Q and check free cash flow trends and debt maturities.
Model 3–5 year FCF scenarios and run DCF sensitivity for discount rates and growth assumptions.
If intrinsic value materially exceeds current price and catalysts exist (cost cuts, new product), place a scaled buy with defined stop based on thesis invalidation.

Example 2 — momentum breakout (technical workflow)

Run a weekly scan for new 52-week highs with relative volume > 2x and 50-day MA above 200-day MA.
Filter by liquidity (avg daily dollar volume) to ensure smooth execution.
Enter on a daily breakout confirmed by volume, set initial stop under breakout support, and trail stop as price advances.

Example 3 — analyst revision play

Monitor for a cluster of analyst upgrades or price-target increases after an earnings beat.
Confirm fundamentals or catalyst details in filings or conference calls.
Short-term traders may trade the re-rating; longer-term investors reassess valuation and thesis.

As of 2026-01-15, educational sources such as WallStreetZen, Motley Fool and Kiplinger emphasize combining these approaches rather than relying on a single signal.

References

Primary sources referenced in preparation of this guide (titles and publishers; date-stamped reporting where applicable):

"Comprehensive Guide to Stock Analysis: Fundamental vs. Technical Methods" — Investopedia.
"How to Research Stocks" — The Motley Fool.
"Stock Research: How to Analyze Stocks in 5 Steps" — NerdWallet.
"How to pick stocks: A practical guide for smart investing" — Saxo.
"How to Predict If a Stock Will Go Up or Down" — Briefing.com.
"How to Predict When a Stock Will Go Up or Down? [Beginner's Guide]" — WallStreetZen.
"33 Stocks That Could Rally 33% or More" — Kiplinger.
StockCharts educational material and example scans.

As of 2026-01-15, these sources remain useful starting points for learning the indicators and processes described above.

Practical next steps

If you want to practice these methods: (1) create a watchlist using a stock screener with clear filters for fundamentals and momentum; (2) paper-trade your workflow for several months to validate your process; (3) use a platform with research and execution capabilities—consider Bitget for trading and Bitget Wallet for custody and token analytics when working with tokenized assets. Always document trade rationale and review outcomes to improve decisions over time.

Learning how to know what stocks will go up is an iterative process: combine evidence, manage risk and keep records. Explore Bitget’s platform tools and educational resources to build practical experience safely.

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