TrendPilot · ETF Trend Trading Systems

Category: Tools

  • How to Backtest ETF Strategies for Free — 5 Tools That Work

    You don’t need a Bloomberg terminal or a paid subscription to backtest ETF trading strategies. Several high-quality tools are free for retail traders — they differ in coding requirements, data coverage, and portfolio support. The right one depends on whether you write Python, prefer visual builders, or want an all-in-one platform that can deploy live.

    The short version

    • TradingView (free tier): fastest for a quick single-symbol concept check using Pine Script. Capped at ~5,000 bars on free plans. No portfolio backtesting.
    • QuantConnect (free tier): cloud-based Python/C# engine with decades of tick-level data. Unlimited backtests on shared compute. Supports multi-asset and options. The same code can deploy live to 20+ brokers.
    • Backtrader (free, open-source): mature Python framework. Full control, runs on your machine. You supply the data (yfinance works fine). Strong for learning and custom strategies.
    • Composer (free tier): no-code visual strategy builder for US equities and ETFs. Drag-and-drop logic, backtest and paper trade without writing a line of code.
    • Yahoo Finance + Python (free): the DIY stack. Use yfinance to pull historical data, pandas to compute signals, and any metric you like. Most flexible — and most work.

    What Is Backtesting and Why Should You Do It?

    Backtesting runs your strategy rules against historical price data to see how they would have performed. It’s the only way to estimate whether a trend-following or momentum system has an edge before risking real capital. Without it, you are trading on hope. With it, you can measure win rate, max drawdown, Sharpe ratio, and other metrics that separate plausible strategies from curve-fitted noise.

    For ETF traders specifically, backtesting matters because most trend strategies produce a small number of trades per year. You need enough historical data — ideally 10–15 years covering bull and bear markets — to judge whether the strategy works across different regimes. Free tools can give you that if you pick the right one.

    1. TradingView — Free Strategy Tester (Pine Script)

    TradingView’s built-in Strategy Tester is the easiest entry point for most retail traders. You open a chart, click “Pine Editor,” write a few lines of logic, and the equity curve redraws on the chart in seconds.

    What’s free?

    • Unlimited public Pine Script strategies
    • Strategy Tester with equity curve, trade list, and performance summary
    • Up to 5,000 bars of historical data (varies by plan; free tier caps around 5 years of daily data)
    • Community library with thousands of open-source strategies to study

    Limitations

    • Single-symbol only — you cannot backtest a portfolio of ETFs simultaneously
    • Basic slippage model (fixed ticks, not volume-adaptive)
    • No direct live execution from the free tier; you need a broker webhook bridge
    • Strategy complexity is limited by Pine Script’s language constraints

    Best for: Quick validation of a single-ETF moving-average crossover or momentum rule. If you want to test whether a 50/200-day SMA crossover works on SPY, you can get an answer in 10 minutes.

    2. QuantConnect — Free Cloud Engine (Python / C#)

    QuantConnect runs the open-source LEAN engine in the cloud. The free tier gives you unlimited backtests on shared compute nodes with access to decades of US equity, ETF, options, futures, forex, and crypto data.

    What’s free?

    • Unlimited backtests (queued on shared compute)
    • Research environment for data exploration
    • Multi-asset, multi-symbol portfolio backtesting
    • Realistic execution model with configurable slippage, fees, and fill logic
    • Same code can deploy to 20+ live brokers (paid tier for live trading)

    Limitations

    • You must write code in Python or C# — no visual builder
    • Free tier uses shared compute; complex scans can be slow
    • Learning curve is steeper than TradingView or Composer

    Best for: Systematic traders who can code and want to test multi-ETF rotation, sector momentum, or any portfolio-level strategy. QuantConnect is the most powerful free option for serious strategy development.

    3. Backtrader — Free Python Framework (Self-Hosted)

    Backtrader is a mature, open-source Python backtesting library. It runs on your local machine and gives you complete control over every aspect of the simulation — data feeds, broker logic, order execution, and analytics.

    What’s free?

    • Everything — it’s MIT-licensed open-source
    • Multiple data feed support (CSV, yfinance, IBKR, custom sources)
    • Built-in indicators, analyzers, and strategy templates
    • A 15-year equity backtest runs in under 2 minutes on a standard laptop
    • Large community and extensive documentation

    Limitations

    • You must supply your own data (yfinance is a common free source)
    • No cloud environment — everything runs on your machine
    • Project maintenance has slowed since the original author stepped back

    Best for: Python developers who want full control, don’t mind setting up their own data pipeline, and prefer coding locally over working inside a hosted browser environment.

    4. Composer — Free No-Code ETF Strategy Builder

    Composer is a visual platform where you build strategies by dragging and dropping condition blocks. It compiles your logic into a tradable algorithm without requiring any programming.

    What’s free?

    • Free tier with limited strategies
    • Visual backtesting with full equity curves and metrics
    • AI-assisted strategy generation using natural language
    • Paper trading on free tier

    Limitations

    • US equities and ETFs only — no futures, forex, or crypto
    • Limited to the building blocks Composer exposes; sophisticated logic quickly hits the ceiling
    • Paid plans start around $20/month for premium features and live execution

    Best for: Non-coders who want to build and backtest ETF rotation strategies visually. If you can describe what you want in plain English, Composer’s AI can generate the logic.

    5. Yahoo Finance + Python (The DIY Stack)

    For maximum flexibility, you can build a backtester from scratch using free Python libraries. The standard stack: yfinance pulls historical ETF data, pandas handles calculations, matplotlib plots results, and NumPy handles numerical work.

    What’s free?

    • yfinance — free Yahoo Finance data downloader
    • pandas / numpy — data manipulation and computation
    • backtesting.py — lightweight vectorized backtesting library (one afternoon to learn)
    • Unlimited custom metrics, portfolio constructs, and Monte Carlo simulations

    Limitations

    • Highest setup cost — you need Python installed and configured
    • Data quality from Yahoo Finance has known gaps (dividend adjustments, corporate actions)
    • No built-in execution model — you code slippage and commissions yourself

    Best for: Traders who already use Python and want zero platform dependency. Once your backtester runs, you own every line — no subscription changes, no API limits, no surprises.

    How to Choose the Right Free Backtesting Tool

    Your situationBest free toolWhy
    Quick concept check on one ETFTradingViewZero setup, instant visual feedback
    Multi-ETF portfolio strategyQuantConnectMulti-symbol support, realistic fill logic
    Python developer, want full controlBacktraderMature framework, runs locally
    Non-coder, ETF rotation onlyComposerVisual builder, no code required
    Maximum flexibility, own infrastructureYahoo + PythonZero platform dependency

    3 Pitfalls to Avoid in Free Backtesting

    Free backtesting tools are powerful, but they come with traps that can turn a losing strategy into a paper winner. Watch for these three:

    1. Look-ahead bias

    This happens when your signal accidentally references data from the same bar you’re trading on. Example: closing price triggers an entry at the same bar’s close instead of the next open. The backtest fills at a price your real strategy could never have known. QuantConnect and Backtrader handle bar indexing correctly if configured properly. TradingView’s Pine Script requires explicit strategy() execution model settings to avoid this.

    2. Survivorship bias

    If your data only includes ETFs that still exist today, you miss the ones that delisted or went to zero. That inflates returns. Yahoo Finance data has survivorship bias. QuantConnect adjusts for it by including delisted securities in their data bundles.

    3. Overfitting on the same dataset

    If you optimize parameters until the equity curve looks perfect, you have likely curve-fitted. The fix: hold out 20% of your historical data as an “out-of-sample” test. Develop your strategy on the first 80%, lock the rules, and run it once on the remaining 20%. If the results fall apart, your strategy was fitted to noise.

    Quick Self-Check

    Test your understanding with these three questions.

    Question 1: Which free tool supports multi-symbol portfolio backtesting?

    QuantConnect (and Backtrader if you run it locally). TradingView and Backtesting.py are single-symbol only. Composer supports multi-asset strategies but is limited to US equities and ETFs.

    Question 2: What is look-ahead bias and how do you prevent it?

    Look-ahead bias occurs when your strategy signal uses price data that wasn’t available at the time of the trade. Prevent it by configuring your backtest engine to enter on the next bar’s open after the signal triggers, and by never using same-bar closing prices as entry prices.

    Question 3: How much historical data should you use to backtest an ETF trend strategy?

    At least 10–15 years covering multiple market regimes (bull, bear, sideways). Trend-following strategies produce few trades per year, so you need enough data to generate a statistically meaningful sample. 100+ closed trades is a common minimum target.

    Frequently Asked Questions

    Click each question to reveal the answer.

    Can I backtest ETF strategies completely without coding?

    Yes. Composer is a no-code platform that lets you build, backtest, and paper trade ETF strategies with a visual drag-and-drop interface. The free tier supports a limited number of strategies. TradingView also requires minimal code (Pine Script is a readable scripting language), but Pine Script is still code — you will need to write a few lines to define entry and exit rules.

    Is QuantConnect really free for unlimited backtests?

    Yes. The QuantConnect free tier gives you unlimited backtests on shared compute nodes with access to decades of historical data across equities, ETFs, options, futures, forex, and crypto. You pay only when you upgrade to dedicated compute or live execution through their brokerage partners.

    Does Yahoo Finance data include dividend and split adjustments for ETFs?

    Yes. The yfinance library returns adjusted close prices that account for splits and dividends. However, Yahoo Finance data has known gaps and survivorship bias — delisted ETFs disappear from the database. For serious backtesting, QuantConnect or a paid data provider (like Polygon or Tiingo) is more reliable.

    What is the minimum number of trades for a statistically valid backtest?

    Most quants consider 100–200 closed trades the minimum for meaningful statistics. With fewer trades, the confidence interval around your Sharpe ratio and win rate is too wide to trust. For trend-following strategies that trade infrequently, you may need 10–15 years of daily data to reach 100 trades.

    Which free tool is best for backtesting ETF rotation strategies?

    QuantConnect. It supports multi-symbol portfolios, realistic execution modeling, and adjustable rebalancing frequencies. Composer is the best no-code alternative for ETF rotation if you prefer a visual builder. Neither TradingView’s free tier nor Backtesting.py handles portfolios.

    Educational content only — not financial advice. Past performance does not guarantee future results. Trading involves risk of loss. See our Disclaimer and Affiliate Disclosure.

  • Best Free ETF Screener for Momentum Trading in 2026 — Compared

    If you trade ETFs using momentum, you need a screener that can filter by recent performance, RSI, moving average crossovers, and relative strength — all without a monthly subscription. The best free ETF screeners for momentum in 2026 are TradingView (for technical filters and global coverage), Finviz (for its 98 ETF filter categories on the free tier), and ETF.com (for holdings overlap and fund-flow analysis). Each covers different angles of a momentum screening workflow.

    The Short Version

    • TradingView — best for technical momentum filters (RSI, MACD, moving average ribbons). Free tier covers global ETFs. Supports saved screeners and multi-chart comparison.
    • Finviz — 98 ETF filter categories on the free plan. Includes performance (1-day through 52-week), volume, and technical indicators. No registration required to screen.
    • ETF.com — 60+ free filters including total return periods, expense ratio, AUM, and holdings overlap. Best for narrowing a shortlist to the single best fund.
    • ETF Database (ETFdb) — simple free screener with asset class, yield, and performance filters. Good for quick scans but limited technical screening.
    • JustETF — the best choice for European (UCITS) ETF momentum screening. Free tier covers 2,400+ funds with performance and cost filters.

    Below is a head-to-head comparison of the five platforms, followed by a step-by-step workflow for using them to find momentum ETFs.

    What Makes a Good Free ETF Screener for Momentum?

    A momentum screener needs more than just a “performance” column. To identify ETFs with genuine trending behaviour, look for platforms that offer:

    • Multiple time-frame returns — 1-month, 3-month, 6-month, 12-month, and year-to-date views. Momentum persistence varies by lookback window.
    • Technical indicator filters — RSI (Relative Strength Index), MACD (Moving Average Convergence Divergence), and moving average crossovers. These help distinguish trending funds from random noise.
    • Relative strength ranking — the ability to compare an ETF’s recent return against its category or a broad benchmark.
    • Volume and liquidity filters — average daily volume, AUM (assets under management), and bid-ask spread estimates. Low-liquidity ETFs produce slippage that eats into momentum profits.
    • Export or save functionality — so you can track your screener results over time and backtest selection rules.

    Most free screeners offer a subset of these. The trick is combining two or three tools to cover what each one misses.

    Free ETF Screener Comparison Table

    ScreenerFree FiltersTechnical Filters (Free)Global ETFsExportBest For
    TradingViewUnlimited (custom)RSI, MACD, MA, Stochastic, 100+ indicatorsYesScreenshot, share linkTechnical momentum analysis
    Finviz98 ETF filtersRSI, MA crossover, volume signalsNo (US-listed)CSV (paid)Quick ETF screening with technical overlays
    ETF.com60+ filtersNo technical indicators (fundamental only)US-listed onlySave screen (free account)Holdings overlap and fund comparison
    ETF DatabaseBasic (asset class, yield, performance)NoneNo (US-listed)CSV (Pro)Simple initial screening
    JustETFFull (asset class, region, provider, cost)No technical indicatorsYes (UCITS focus)CSV (free)European ETF momentum screening

    How to Screen for Momentum ETFs Using TradingView (Free)

    TradingView’s free ETF screener offers the best technical filter set without a paywall. Here is the step-by-step workflow:

    1. Go to TradingView → Products → Screeners → ETF Screener. The free tier covers all US-listed ETFs and many international exchanges.
    2. Add the following momentum filters in the top panel:
      • Return 1 Month → set a minimum, e.g. > 3%
      • Return 3 Months → set > 5%
      • RSI (14) → range 50–80 (avoids overbought extremes while confirming upward momentum)
      • Volume → minimum 100,000 daily average (ensures liquidity)
      • AUM → minimum $50M (avoids micro-ETFs that may close)
    3. Sort the results table by Return 3 Months descending. The top 10–20 funds are your momentum candidate list.
    4. Click any ticker to open a multi-timeframe chart. Check whether the price is above both its 50-day and 200-day moving average — a classic trend-confirmation signal.
    5. Save the screener configuration (requires a free TradingView account) so you can re-run it weekly.

    TradingView also lets you plot the screener results directly on a heatmap or watchlist, which is useful for tracking changes week over week.

    How to Use Finviz for ETF Momentum Screening (Free)

    Finviz’s free screener does not require registration and provides 98 ETF-specific filter categories. Here is how to configure it for momentum:

    1. Open Finviz.com → Screener → ETF tab (next to the “All” tab).
    2. In the Performance group, set:
      • Performance (Week) → Over 0% (eliminates short-term losers)
      • Performance (Quarter) → Over 5%
      • Performance (Half Year) → Over 8%
    3. In the Technical group, set:
      • RSI (14) → Between 50 and 80
      • 20-Day Simple Moving Average → Price above SMA20 (confirms short-term trend)
      • 50-Day Simple Moving Average → Price above SMA50 (confirms medium-term trend)
    4. Use the Volume filter to set a minimum (e.g., 200,000 average volume). This avoids illiquid ETFs that produce poor fills.
    5. Click the column headers to sort by any metric. The free view displays the data inline — no CSV export without Elite, but the screen is usable for manual review.

    Finviz’s strength is speed: the interface loads fast and the results table is dense with information. For a quick weekly scan, it is hard to beat.

    What About ETF.com and ETF Database?

    ETF.com (owned by VettaFi) offers 60+ free filter criteria but no technical indicator filters. It is best used after you have a shortlist from TradingView or Finviz. Its holdings overlap tool and fund-flow data (30-day, 90-day, 1-year) help you decide between two ETFs that track similar themes. For example, if your momentum screen returns two technology ETFs with similar performance, ETF.com can show you whether their top 10 holdings overlap by 80% — if they do, buy the cheaper one.

    ETF Database (ETFdb) provides the simplest interface for a quick asset-class or yield-based screen. It lacks technical filters entirely, so it is not suitable as a standalone momentum tool. Use it to generate candidate ideas, then cross-reference against TradingView or Finviz for technical confirmation.

    Can You Screen European (UCITS) Momentum ETFs for Free?

    Yes — JustETF is the dominant free screener for UCITS ETFs listed on European exchanges. It covers 2,400+ funds with filters for asset class, region, provider, fund size, and ongoing charges. Performance data (1-month, 3-month, 1-year, 3-year) is available for every fund on the free tier. You cannot filter by RSI or moving averages, but you can sort by trailing returns and then check the underlying index methodology to confirm a momentum strategy. JustETF also lists which brokers offer savings-plan access to each ETF — a practical detail that US-focused screeners ignore.

    For European traders who need technical screening, the best approach is: find candidate UCITS ETFs on JustETF, then chart them on TradingView (which covers European ETFs on its free tier) to check the moving average and RSI setup.

    How to Build a Weekly Momentum Screening Routine

    A repeatable weekly routine keeps your momentum watchlist current without hours of manual work each time. Here is a practical 15-minute workflow:

    1. Monday morning: Run your saved TradingView ETF screener (the five-filter configuration from the section above). Export the top 15 results by 3-month return to a watchlist.
    2. Monday morning (part 2): Cross-reference the top 5–7 candidates on Finviz. Confirm they pass the moving average and RSI filters. Remove any that triggered a volume spike that looks like a blow-off top rather than sustained momentum.
    3. Wednesday: Use ETF.com’s holdings overlap tool to compare your top 2–3 candidates. If they are essentially the same basket of stocks, drop the one with the higher expense ratio.
    4. Friday: Review the week’s performance of your watchlist. Note any that broke below their 50-day moving average — these are candidates to remove the following Monday.

    This routine uses only free tools and takes under 15 minutes once the screener configurations are saved.

    Quick Self-Check

    Test your understanding before you start screening.

    Why is an RSI filter important when screening for momentum ETFs?

    RSI helps distinguish genuine trending funds from overbought spikes. A filter of 50–80 captures ETFs with confirmed upward momentum (above 50) while avoiding those that may be due for a pullback (above 80). Without it, your momentum screen might simply return the most volatile funds rather than the most consistently trending ones.

    Which free screener works best for European-listed UCITS momentum ETFs?

    JustETF is the best free tool for UCITS ETFs, covering over 2,400 funds with performance data across multiple time frames. It lacks technical filters, so pair it with TradingView (which supports European ETFs on its free tier) to check RSI and moving average confirmation before entering a position.

    What is the minimum AUM and volume I should set in a momentum ETF screener?

    A minimum AUM of $50 million and average daily volume of 100,000–200,000 shares avoids micro-ETFs that may close or produce wide bid-ask spreads. Low-liquidity ETFs can erode momentum profits through slippage alone, especially if you trade positions larger than a few thousand dollars.

    Frequently Asked Questions

    Is Finviz’s ETF screener really free?

    Yes, the basic Finviz ETF screener is free and requires no registration. It provides 98 ETF filter categories including performance, volume, and technical indicators. The free tier displays results inline with column sorting. CSV export and real-time data require the paid Elite plan ($39.50/month or $299.50/year as of 2026), which includes a 7-day free trial.

    Can I screen global ETFs for momentum, or only US-listed?

    TradingView’s free ETF screener covers US-listed funds and many international exchanges. JustETF is the best option for European UCITS ETFs. Finviz and ETF.com are limited to US-listed ETFs. If you trade ETFs on Asian or Australian exchanges, TradingView or exchange-specific screeners (e.g., ASX’s ETF screener) are your best free options.

    How often should I re-run my momentum ETF screener?

    Weekly is the standard cadence for momentum screening. Monthly is too slow — you will miss trend reversals. Daily is overkill for most traders because momentum tends to persist on a weekly time frame (Jegadeesh and Titman, 1993). A consistent Monday morning screen gives you a fresh watchlist before the trading week begins.

    Do free ETF screeners include leveraged or inverse ETFs?

    All five tools listed in this guide include leveraged and inverse ETFs in their results. Most allow you to filter them out via the asset class or category filter. ETF Database has a quick “Leveraged” toggle. Finviz lets you exclude them under the “Descriptive” filter group. For momentum screening, it is generally wise to exclude leveraged ETFs — their daily rebalancing creates decay that makes multi-month momentum signals unreliable.

    Can I screen for ETFs with a specific moving average crossover pattern?

    Finviz offers moving average relationship filters (price vs SMA20, SMA50, SMA200) on the free tier. TradingView allows full customisation of moving average crossovers as screener conditions. Neither ETF.com nor ETF Database support MA crossover filtering. For a golden cross (SMA50 crossing above SMA200) or death cross strategy, TradingView is the best free choice.

    Educational content only — not financial advice. Past performance does not guarantee future results. Trading involves risk of loss. Disclaimer · Affiliate Disclosure

  • Short-Term ETF Trade vs Cash Break-Even Calculator

    This free calculator estimates whether a short-term ETF trade covers its own costs and beats the alternative of simply holding cash. Enter your trade, its costs, and a cash comparison, and it shows your net result and the break-even price. It uses only the numbers you type in.

    Step 1 of 3

    Trade setup

    The result uses your expected exit price. It is an estimate, not a prediction.

    Trading and ETF costs

    Total spread impact for entering and exiting.
    Prorated for your holding period.

    Compare with cash

    What you could earn holding cash instead.
    Applied only to a positive taxable result.
    Tax treatment varies by jurisdiction and account type. This is a simplified estimate.

    How to use it

    Enter your starting amount, entry and expected exit price, and holding dates. Then add your trading costs and fund expense ratio, and finally the cash return you could earn by doing nothing. The calculator shows your net profit or loss, the break-even exit price, and whether the trade beats cash. For the strategy behind the trade, see our ETF swing trading strategies guide.

    FAQ

    What does the break-even price tell me?

    The break-even exit price is the price you need to reach so that your proceeds cover your entry cost plus the buy fee, sell fee, spread, and the prorated fund expense. It is a pre-tax number, so taxes are handled separately in the comparison.

    What is the cash alternative?

    The cash alternative is the estimate of what the same money would grow to if held in cash or a cash-based ETF at the annual return you enter, over the same holding period.

    Is the result a prediction?

    No. It is an estimate built entirely from the prices and assumptions you enter. Actual execution prices, spreads, fees, and tax treatment can all differ.

    Disclaimer: This calculator provides an estimate based on the assumptions entered. Actual execution prices, spreads, fees, distributions, market movements, and tax treatment may differ. It is not personal financial or tax advice. Full disclaimer and affiliate disclosure.

  • ETF Momentum Ranker: Rank Your Watchlist by Strength

    This free tool ranks your ETFs by momentum, so you can see which ones have been strongest over a window you choose. Enter two prices per ETF (the price some months ago and the price now), and it sorts them from strongest to weakest. It uses only the numbers you type in.

    Step 1 of 3

    What momentum window do you want to measure?

    How many ETFs do you want to rank?

    Enter each ETF’s price

    How to use it

    Pick a lookback window (3, 6, or 12 months), choose how many ETFs to compare, then enter each ETF’s ticker, its price at the start of the window, and its price today. The tool ranks them by percentage change. You can read both prices off any chart, so no data export is needed.

    Momentum ranking is the same idea behind relative strength and our step-by-step ETF momentum strategy guide. To see how a trend rule held up over a full price history, use the backtest calculator.

    FAQ

    How is momentum calculated here?

    Momentum is the percentage change from the price you enter for N months ago to the price you enter for today. A positive number means the ETF rose; a negative number means it fell. The ETFs are then ranked highest to lowest.

    What price data do I need?

    Just two numbers per ETF: the price at the start of your chosen window and the price now. You can read both off any chart. The tool does not fetch or invent any market data.

    Does a high rank predict future returns?

    No. Momentum is a screen that shows what has been strong recently, not a promise about what comes next. Rankings change, and past strength does not guarantee future returns.

    Disclaimer: Educational tool only, not financial advice. It ranks the numbers you enter; it does not predict future performance or recommend any trade. Full disclaimer and affiliate disclosure.

  • Trend-Following ETF Backtest Calculator: Test a Moving-Average Rule

    This free calculator tests whether a simple moving-average trend rule improved an ETF’s historical risk-adjusted performance. You paste your own price data, and it replays the rule with no lookahead bias, comparing the trend strategy against buy-and-hold. It does not fetch or invent any market data.

    1Enter ETF price data

    Paste two columns: date and close. Accepts headers like date, time, close, adj close. Order does not matter; blank lines are ignored.

    2Configure the strategy

    A transaction cost is applied every time the strategy switches between invested and cash.

    3Optional benchmark

    How to use it

    Download or copy daily closing prices for any ETF (Yahoo Finance and most brokers export a CSV), paste the date and close columns into step 1, set your lookback period (200 is the classic trend-following default), and run it. The calculator moves the strategy to cash whenever the price closes below its moving average, and back in when it closes above, applying your transaction cost on each switch.

    To understand what the numbers mean before trusting them, read how to backtest without fooling yourself, and pair the result with our other free tools.

    FAQ

    How does this backtest avoid lookahead bias?

    The moving average at each period uses only prior closing prices, and the signal sets the position for the NEXT period. So no future information leaks into the trading decision.

    What data do I need to run it?

    A CSV with two columns: date and close price, pasted from any source such as Yahoo Finance or your broker. The calculator does not fetch or invent any market data.

    Does it predict future returns?

    No. It replays a rule on the prices you supply. Historical backtests are hypothetical and do not predict future performance.

    Disclaimer: Educational tool only, not financial advice. It performs arithmetic on data you supply; it does not predict future performance or recommend any trade. Full disclaimer and affiliate disclosure.

  • ETF Trading Cost Calculator: What Turnover Really Costs

    Trading costs are invisible until you add them up, and in a high-turnover trend system they can quietly erase the edge. Commissions, spreads, and slippage compound with every trade. Enter your numbers to see the annual cost in dollars and as a percentage of your portfolio.

    Your turnover
    Annual trading cost
    $0
    Cost per trade$0
    Cost as % of portfolio0%
    Cost per trade = commission + (portfolio × spread %). Annual cost = cost per trade × trades per year. High-turnover systems bleed returns here.

    Why turnover is the hidden tax

    A system that trades monthly makes roughly two dozen round trips a year. If each round trip costs a fraction of a percent, the annual drag can reach several percent. That is why the signal you choose matters: a faster signal trades more and costs more. Prefer liquid ETFs with tight spreads, and keep turnover as low as your rules allow.

    FAQ

    What is spread and slippage?

    The spread is the difference between the bid and ask price. Slippage is the difference between the price you expected and the price you actually got. Both are costs you pay on every trade, on top of commissions.

    How much do ETF trading costs matter?

    Enough to change a system’s outcome. A 3% annual cost drag compounds over years and can turn a marginal strategy negative. Low-cost, low-turnover systems have a real advantage.

    How can I lower trading costs?

    Use liquid ETFs with tight spreads, trade less often, and choose a broker with low or zero commissions. Avoid trading in the first minutes of the open, when spreads are often wider.

    Disclaimer: Educational tool only, not financial advice. It performs arithmetic on your inputs; it does not recommend any trade, position, or strategy. Full disclaimer and affiliate disclosure.

  • ETF Portfolio Rebalance Calculator: Get Back to Target Weights

    Rebalancing is how you return a drifted portfolio to its target weights. After a trend or momentum move, some positions grow and others shrink. This calculator tells you the exact dollar amount to buy or sell in each to get back on target. Enter your positions below.

    Your positions
    ETF / holdingCurrent $Target %
    Total portfolio
    $0
    Target % should sum to 100. “Buy” means add that dollar amount; “sell” means trim that amount back to target.

    How rebalancing fits a trend system

    Most trend systems rebalance on a schedule, usually monthly. The weights drift between reviews as winners grow and losers shrink. Rebalancing forces you to trim winners and add to laggards, which is uncomfortable but is exactly what keeps the portfolio's risk at the level you chose. Use the target weights you wrote down when you designed the system, and the review becomes mechanical.

    FAQ

    How often should I rebalance an ETF portfolio?

    Monthly is the common default for trend systems. Weekly rebalancing trades more and raises costs; quarterly reacts more slowly. The right cadence is the one you can follow mechanically.

    Why do target weights drift?

    Weights drift because positions grow at different rates. A winning ETF becomes a larger share of the portfolio, and a losing one becomes smaller. Rebalancing returns them to the proportions you originally chose.

    Do target weights need to add up to 100%?

    Yes. If your target weights do not sum to 100%, the portfolio is not fully allocated and the calculator will flag it.

    Disclaimer: Educational tool only, not financial advice. It performs arithmetic on your inputs; it does not recommend any trade, position, or strategy. Full disclaimer and affiliate disclosure.

  • ETF Drawdown Calculator: Measure and Recover From Losses

    Drawdown is how far your portfolio has fallen from its peak, and it is the single most honest measure of risk in a trend system. More important than the loss itself is what it takes to recover: a 50% drawdown needs a 100% gain just to get back to even. Enter your numbers below.

    From peak to now
    Drawdown
    0%
    Dollar loss$0
    Gain needed to recover0%
    Drawdown = (peak − current) ÷ peak. The recovery number is why drawdowns hurt: a 50% loss needs a 100% gain just to break even.

    Why the recovery number matters

    The recovery math is asymmetric, and that is the point. Losing 20% needs a 25% gain to recover. Losing 50% needs a 100% gain. This is why risk control and position sizing come before everything else: keeping drawdowns small keeps recovery achievable. A trend system that steps aside in downtrends is, at its core, a drawdown-control machine.

    FAQ

    What is a drawdown in trading?

    A drawdown is the decline from a portfolio’s peak value to a later low, usually expressed as a percentage. It measures the worst loss an investor would have experienced over that period.

    How much gain do I need to recover from a drawdown?

    The gain needed is drawdown% divided by (100 minus drawdown%). A 10% drawdown needs an 11.1% gain, a 20% drawdown needs 25%, and a 50% drawdown needs 100%.

    Why does drawdown matter in trend following?

    Trend following aims to cut losses in downtrends, which keeps drawdowns shallower. A shallow drawdown is recoverable; a deep one can take years of compounding gains to repair.

    Disclaimer: Educational tool only, not financial advice. It performs arithmetic on your inputs; it does not recommend any trade, position, or strategy. Full disclaimer and affiliate disclosure.

  • ETF Position Size Calculator: Size Your Trades by Risk

    Position sizing is how much of your account you put into a single trade, chosen so that a stopped-out loss costs you a fixed, survivable amount. It is the risk layer of any ETF trend trading system, and it matters more than the entry signal: a great signal with terrible sizing still blows up an account.

    The most common method is risk-based sizing. You decide the percentage of your account you are willing to lose if your stop is hit, then buy just enough shares so that the loss equals that amount. Enter your numbers below and the tool does the rest.

    Your trade
    Position size
    0 shares
    Risk per share$0.00
    Position value$0
    Dollar at risk$0
    % of account0%
    Shares = (account × risk %) ÷ (entry − stop). Round down to whole units if your broker does not allow fractional shares. This is a tool, not a recommendation.

    How the calculation works

    The formula is simple: shares = (account size × risk %) ÷ (entry − stop) for a long position.

    Example: a $10,000 account, risking 1% ($100), buying an ETF at $100 with a stop at $95. Risk per share is $5, so you buy 20 shares. If the stop is hit, you lose 20 × $5 = $100, exactly 1% of the account.

    Why this is the number that keeps you in the game

    Trend systems lose small and win big. A losing streak is normal and expected. If each loss is capped at 1% of your account, ten straight losses cost you about 10% and you survive to catch the next trend. If you size every trade to the maximum, the same streak ends the account. Sizing is the difference between a losing streak being an inconvenience and being a catastrophe.

    Use it with a stop rule

    Risk-based sizing only works if you actually have a stop. Many trend traders use a rule like the 7% to 8% stop: sell if a position falls that far below your entry. Pair a defined stop with the sizing above and your downside is capped before you ever place the order. See the risks guide for the other things that can go wrong.

    FAQ

    How do I calculate position size for a trade?

    Divide your dollar risk by the risk per share. Dollar risk is your account size multiplied by the risk percentage you are willing to lose. Risk per share is the entry price minus the stop-loss price for a long position. The result is the number of shares to buy.

    What risk percentage should I use?

    Many traders risk 1% or less of their account on a single trade, and 2% is generally considered aggressive. The right number is the loss you can take repeatedly without abandoning your system, so start small.

    Why does position sizing matter in trend trading?

    Trend systems win by cutting losses small and letting winners run. Correct sizing keeps a normal losing streak survivable, while over-sizing turns that same streak into account damage.

    Can I buy fractional ETF shares?

    Many brokers now allow fractional shares, but some exchanges still settle in whole units. Round down to whole units if your broker does not support fractions.

    Disclaimer: Educational tool only, not financial advice. It performs arithmetic on your inputs; it does not recommend any trade, position, or strategy. Full disclaimer and affiliate disclosure.