Start with the basics or go straight to a topic you want to understand. Lessons explain the concepts, and the app lets you put them on charts, change the settings and test what you have learned.
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The courses cover the main topics. Start with the foundations, jump to a specific topic, or follow the suggested path. Several lessons open the relevant tool with the exact settings to enter.
Extend the market. The lesson How to extend the market in GU Analyser shows Premium subscribers how to connect their own free Tiingo key and take the same tools to 14,000+ US stocks and ETFs, with candlestick charts.
Start here if you're new. Ten short lessons that give you the vocabulary and the mental model everything else depends on.
10 lessons · tap any one for what it covers
How a market matches buyers to sellers, what actually makes a price move, and what the bid, the ask and liquidity mean — the mechanics every chart rests on
What you genuinely own when you buy a stock, an ETF or an index, and why each one has to be read in a different context
Reading the four prices packed into every candlestick — open, high, low and close — and what the body and the wicks reveal about who controlled that period
When US markets are open, why a stock can gap from Friday’s close to Monday’s open with no trading in between, and what that means for holding overnight
The three costs taken out of every round trip — spread, fees and slippage — and why a strategy that looks profitable on paper can be a net loser once they are subtracted
Choosing your timeframe before you touch a chart — investor, swing trader or day trader — because it decides which tools, risks and mindset apply, and how trouble starts when a swing trade quietly "becomes an investment"
The arithmetic that gets least attention: lose 20% and it takes 25% to get back, lose 50% and it takes 100%. Why the cost of a deep loss grows faster than the loss itself
How position size decides whether being wrong is survivable — what "risk" refers to in this context, the widely cited convention of risking 1–2% of an account on a single trade, and why sizing is what lets someone sit through a losing streak with an account still intact
What real progress looks like against what gets sold as progress, why consistent results take a long learning curve, and how to recognise get-rich-quick framing before it costs you
Putting the whole course to work: look up your first ticker and read its candles, costs and structure on a real chart
The core of the app. Four stages: read price, understand indicators, turn a setup into rules, then test and execute it — and a closing lesson on extending the market with your own data key. Two lessons complete themselves the first time you use the tools for real.
14 lessons · tap any one for what it covers
Reading raw price structure before a single indicator is added — how to identify a trend, and why support and resistance levels hold as often as they do
How volume is conventionally read as a confirmation layer, where higher volume behind a move is generally treated as stronger confirmation than the same move on thin volume — and what that reading can and cannot tell you
Spotting where momentum and price start to disagree. Traders commonly treat this as an early warning that a move is weaker than it appears, and the lesson covers how often that reading holds and how often it does not
One-to-three-bar candlestick patterns and what each is conventionally read to suggest, plus the context that is generally held to matter more than the shape itself: where on the chart the pattern appears
The larger formations that take ten to fifty bars or more to build, what they are conventionally read to suggest about continuation or reversal, and why longer-forming patterns are usually given more weight
The idea worth more than memorising individual indicators: all 60+ sort into four jobs. Five momentum indicators agreeing is arguably one piece of evidence counted five times rather than five confirmations
Why the same indicator can give opposite results in different market conditions, and how to judge whether you are in a trending, ranging, volatile or disorderly regime before choosing tools
The anti-indicator-soup framework — one indicator per layer, so that agreement between four different kinds of evidence carries more weight than agreement between four measures of the same thing
Turning "buy when it looks oversold in an uptrend" into an explicit rule that can be tested — conditions joined by AND and OR, read back as a live expression such as (RSI < 30 OR MACD > Signal) AND ADX > 25
What a backtest scorecard actually means — the four numbers that only make sense read together, and expectancy, which combines win rate and risk-to-reward into an average historical result per trade
Replaying a saved strategy across years of real history before any money is at risk — and the over-optimisation trap, where settings tuned until the past looks perfect are fitted to that history and tend not to hold up afterwards
The behavioural mistakes commonly identified behind beginner losses — none of them about picking the wrong indicator, all of them about discipline
How the tools connect: explore indicators on charts, build rules without code, backtest them, investigate what follows a market condition, and practise on historical replays
Adding a free Tiingo key of your own: where to get it, where it goes in the app, what it changes — a broader market, full candlesticks, the hourly indicators the built-in data holds back, deeper history — and how the free plan’s 50 requests an hour fit
An event study asks one question: when this condition was true in the past, what happened around it? Eight lessons cover what the page measures, how to set a study up, what preconditions and side-by-side comparisons read, and how to tell a real pattern from an accident.
8 lessons · tap any one for what it covers
Measuring one condition on its own — every bar in history where it was true, and what price did around those bars, with no entry, exit, fee or position involved
Writing a condition in the same rule editor used for buy and sell rules, and how often a condition fires shapes what can be learned from it
Choosing the windows either side of the trigger, why a snapshot counts bars rather than days, and the three ways a study can be run across tickers and conditions
What trend, volatility, squeeze and prior move read, and which one uses the future
Whether the condition fired once, or kept firing
Reading the figures around the trigger, what the shaded band does and does not claim, and how the indicator panels reveal whether a rule fired where it was meant to
What each column measures — price change, speed, volatility, volume measured against that instrument’s own normal, share rising, worst dip, the extremes, and the worst tenth of cases
The four event counts and why they differ, how clustered dates inflate an apparent sample, what a confidence interval containing zero means, and the limits of the method
Two questions answered end to end with the app: does buying on RSI alone actually work, and how do you build a screen that combines indicators properly?
11 lessons · tap any one for what it covers
The four steps behind testing any trading claim — state it precisely, express it as rules, run it on history, then read the result honestly
What an RSI reading below 30 actually looks like on a real chart, and why "oversold" is not the same as "about to go up"
Turning "buy when RSI is oversold" into exact buy and sell rules a backtest can execute — the point where a claim becomes testable
Running one RSI strategy across four different stocks, because a result from a single chart over a single period is not evidence
Reading a backtest result properly — return against drawdown, win rate against the size of the losses, and what the equity curve shows that a summary number hides
Adding a single trend condition to the same strategy and re-running it, to see how much one rule changes the outcome
Four questions about indicators worth putting through the same test yourself, on tickers you pick
Building a stock screen from four indicators that each answer a different question — trend, momentum, volatility and volume — rather than four that repeat one another
Checking a screen against the charts, saving it, then backtesting it — and why a screen produces a shortlist to investigate, never a decision
Four more screens worth building, and how to tell whether yours is too loose or too tight
The seven questions worth answering before risking anything — and the eighth question nobody can answer, which is how you spot who is selling something
Every Test Bench study states its method so it can be rebuilt. Three lessons cover the approach: why rebuild, what to copy out of an article, and how to define a benchmark. The first studies each have a lesson with the complete rebuild on the real screens; later studies end with their rebuild steps on the study page in the app, and studies on one subject are collected on a series page.
11 lessons · tap any one for what it covers
A result you can reproduce is evidence; one you cannot is a claim
The six things to copy out of any study
A result means nothing until you say what it is being measured against
The complete rebuild: custom indicators, both rules, the run, and the benchmark
The complete rebuild: the event, the zero-line split, and the check the study turned on itself
Study 002's event inside one trend and volatility combination at a time
One derived signal, ANDed into the crossover
A 15-minute range, a whole-candle entry and a partial exit, on 5-minute candles
Long above the session VWAP, out below it and at 16:00, on 5-minute candles
Buy a dip above the 200-day average, sell after the first close above the 5-day average
Hold while the fast line is above the slow one, sell at the next open when it drops below
Published studies by subject: MACD Crossover Studies · Opening Range Breakout (ORB) Studies · Candlestick Pattern Studies · VWAP and Anchored VWAP Studies · Mean Reversion Strategy Studies · Moving Average Strategy Studies · all studies on The Test Bench.
Pages to read alongside the courses and to come back to. Grouped below by the course they sit closest to, as the map draws them; published Test Bench studies sit beside the course that rebuilds them.
How trading scams work and how to recognise them: Ponzi schemes, signal sellers and paid “gurus”, pump-and-dumps, managed-account and credential theft, and high-cost courses and mentorships — with the red flags they share and how to verify a broker or platform.
Eight major market events, their drawdowns and recovery periods: the 1929 Wall Street Crash, Black Monday, the dot-com bust, the 2008 financial crisis, the COVID crash, the GameStop squeeze and the inflation bear market.
The investors worth knowing about — Charles Dow, Benjamin Graham, Jesse Livermore, Warren Buffett, Peter Lynch, George Soros, Jim Simons, Ray Dalio — and the people who invented the indicators in your charts panel: Wilder, Bollinger, Appel, Lane, Donchian, Keltner, Chaikin and others, with what each was arguing.
Eight common errors involving risk, stops, over-optimisation and trading discipline — indicator soup, fighting the trend, moving a stop loss, chasing on FOMO, revenge trading, poor risk-to-reward, ignoring the regime and over-optimisation — each with a specific fix.
How emotions, discipline and loss tolerance can affect decisions: fear, greed, and why a plan made at the weekend gets abandoned on Tuesday morning.
An introduction to earnings, valuation and balance sheets, and what a company's numbers show that price and volume do not.
Candlesticks and OHLC, support and resistance, telling a trend from a range or a chop, timeframes and why they disagree, volume, divergence, moving averages, chart patterns and the basics of risk.
The four market regimes — trending, ranging, high volatility, and bear or capitulation — how to recognise which one you are in, and which indicators behave differently in each.
A page for every one of the 60+ indicators in the app: what it measures, the thresholds conventionally treated as meaningful, the conditions where it is considered more or less useful, which indicators it is normally read alongside, and its known limitations. Free to read outside the app, with no account needed.
Eight candlestick patterns drawn out bar by bar — doji, hammer, shooting star, bullish and bearish engulfing, morning and evening star, and the inside bar — with what forms each one, what it is conventionally read to mean, and how reliable that reading is.
Build the condition on its own one-terminal canvas, then configure the study: pooled instruments, history, horizons, preconditions and side-by-side comparisons.
Three classic breakout rules tested across 179 US stocks, with Buy & Hold comparisons, fees, drawdowns, ADX and different market conditions.
A series of event studies on the MACD signal-line crossover in US large-cap stocks: what follows a crossover, whether the benchmark it is measured against is fair, and whether the size of the crossover carries information of its own.
15,698 bullish MACD signal-line crossovers across 197 US large-cap stocks, 2018 to 2026, measured over the following 35 trading days against the same measurement taken from every trading day in those stocks.
Study 002 compared MACD crossovers with every trading day. A reader asked if that was fair, so we re-ran the test only against days with similar trend and volatility, with a calendar-block bootstrap interval on each crossover-minus-comparison difference.
Not every MACD crossover crosses by the same amount. We measured the size of the one-day histogram move, scaled it by the share price, and tested whether sharper crossovers were followed by larger 35-day returns — with one threshold fixed in advance and applied once to data it had not seen.
The opening range breakout explained — how the range is set, entries, stops, targets and the common variants — with our backtests of it on large US stocks after trading costs.
One 15-minute opening range breakout rule on 149 large US stocks over six months of 5-minute candles: the result per trade, as a portfolio, at four trading costs, and its strongest and weakest stocks.
Gap and go tested on 149 US stocks over six months: ORB trades on gap-up, flat and gap-down days, and whether the breakout added anything to the gap.
One ORB rule on SPY run on two platforms’ 5-minute data: why backtest results change with the price feed, and how to separate the rule from the data.
Candlestick patterns explained, starting with the bullish and bearish engulfing, with our tests of what followed them on weekly candles in US large-cap stocks.
Across 480 current S&P 500 companies, the weekly bullish engulfing underperformed ordinary weeks by 0.80 percentage points over the next 12 weeks.
Across 480 current S&P 500 companies, the weekly bearish engulfing showed almost no difference from ordinary weeks.
VWAP and Anchored VWAP explained: the calculation, the anchors and a published VWAP trading rule, with our tests of that rule on QQQ, on large US stocks and after trading costs.
The long side of a published VWAP rule rebuilt on QQQ, then tested after the study’s years, on 149 large US stocks and against trading costs.
How much each trade can cost before the long-only VWAP rule falls behind buying and holding QQQ, and where spreads, fees and currency conversion sit against that.
Mean reversion trading explained: why prices revert, the entry and exit rules and the risks, with our tests of RSI, RSI(2), ConnorsRSI and Stochastic RSI signals on S&P 500 stocks and a backtest of the four.
RSI(2) crossing 10 and 90 on 483 S&P 500 stocks, 2006 to 2026: 4 of 8 signal tests differed clearly from ordinary days over the next 5 days.
RSI(14) crossing 30 and 70 on 483 S&P 500 stocks, 2006 to 2026: 3 of 8 signal tests differed clearly from ordinary days over the next 20 days.
ConnorsRSI crossing 10 and 90 on 483 S&P 500 stocks, 2006 to 2026: 4 of 8 signal tests differed clearly from ordinary days over the next 5 days.
Four RSI entries under one dip-buying rule (above the 200-day average, out on a close above the 5-day average) on 483 S&P 500 stocks, 2006 to 2026, against buying and holding.
Stochastic RSI crossing 20 and 80 on 483 S&P 500 stocks, 2006 to 2026: no clear difference from ordinary days over the next 10 days in any of 8 signal tests.
Moving average trading explained: SMA and EMA, crossovers, the golden cross and the 200-day average, with our tests of three rules on S&P 500 stocks and a backtest of the three.
Golden and death crosses on 483 S&P 500 stocks, 2006 to September 2026: no clear difference from ordinary days over the next 100 trading days in any of the four signal tests.
Price crossings of the 200-day average on 483 S&P 500 stocks, 2006 to September 2026: no clear difference from ordinary days over the next 100 trading days in either of the two signal tests.
The 9/21 EMA crossover on 483 S&P 500 stocks, 2006 to September 2026: no clear difference from ordinary days over the next 20 trading days in any of the four signal tests.
The golden cross, the 200-day average and the 9/21 EMA as trading rules on 483 S&P 500 stocks, 2006 to September 2026, with next-open fills and costs, against buying and holding.
How to assemble a coherent setup: a position-sizing calculator, a four-layer framework separating trend, momentum, volatility and risk, and example stacks to take apart and modify.
Every unit on the builder palette, drawn as it appears on the canvas — what each one does, a worked example, and where it is allowed to wire.
How to write buy and sell rules precisely enough for a computer to follow, without code: the shape of a single condition, what each operator means including crossovers, comparing an indicator against a number or against another indicator, and how AND/OR groups resolve the ambiguity in a rule like “A and B or C”.
A walkthrough of Charts, Screening and the indicator Configuration — one concrete task each, the exact values to enter, and what you should see when it has worked.
Real screenshots of the current screens: pick or build a strategy, then configure Mode, Run over, Period, cash and fees before you run it.
Where everything lives: getting started, each tool in depth, and an example workflow from looking up a stock to reading a finished backtest.
What this app is for, what it refuses to be — no signals, no alerts, no recommendations — and how it treats your data and your money.
Lessons explain what a concept or indicator measures. Charts let you explore it on historical data. Strategy Builder and Backtesting let you turn an idea into rules and test them without code. Event Analysis lets you examine what happens around a defined condition.
The Indicators section above is also published outside the app, with no account needed: a page for every indicator in GU Analyser covering what it measures, how its readings are conventionally interpreted, the levels people use, and where it is known to fall short. Start at the technical indicator reference, or go straight to a common one — RSI, MACD, Bollinger Bands or ADX.
Lessons explain indicators and concepts. The Test Bench examines specific market claims using defined methods and historical data. Published studies show the question, the assumptions, the comparison and the result.
Studies on one subject are also collected on a series page: MACD Crossover Studies · Opening Range Breakout (ORB) Studies · Candlestick Pattern Studies · VWAP and Anchored VWAP Studies · Mean Reversion Strategy Studies · Moving Average Strategy Studies.
All 50+ lessons and every reference section are free. The free plan also runs the tools on the S&P 500 ETF (SPY), with the screener on the Magnificent 7. Premium widens the same tools across 400+ US stocks, ETFs and indices — see pricing.
Plot it yourself. Add this indicator to a chart, change every parameter and watch the line move, then backtest how the rule would have behaved on historical data — free on the S&P 500 ETF, no card.
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