Technical indicators explained simply

What an indicator actually does

A daily stock file contains Open, High, Low, Close, and Volume. An indicator turns some of those observations into another series. A 20-day moving average, for example, replaces each day’s Close with the average of the latest 20 closes. RSI compares recent upward and downward changes. ATR summarizes recent price ranges.

The result may look smoother or easier to interpret, but it contains no new market information. It is a transformation of data that already exists. Its value comes from expressing a clear idea consistently—not from predicting by itself.

Most indicators in TickRun fit into four broad families: trend, momentum, volatility, and volume. Some combine more than one family.

Trend indicators

Trend indicators ask whether price has been moving persistently in one direction. Moving averages are the clearest example. A short average reacts quickly; a long average changes slowly. A crossover strategy may enter when the fast average moves above the slow one and exit when it falls below.

MACD compares two exponential averages. DEMA, TEMA, ZLEMA, KAMA, and HMA are alternative smoothing methods designed to respond differently to recent prices. Ichimoku uses several midpoint calculations to describe trend and possible support or resistance zones. PSAR places a trailing level above or below price.

Trend rules usually react after a move begins. That delay is not necessarily a defect: confirmation is what filters some small fluctuations. The trade-off is that sideways markets can create repeated entries and exits called whipsaws.

Momentum indicators

Momentum asks how strongly price has moved. RSI compares average recent gains with average recent losses and places the result between 0 and 100. Stochastic oscillators compare the Close with the recent high-low range. Williams %R expresses a related position on a negative scale. ROC measures percentage change over a chosen window.

Terms such as “overbought” and “oversold” can be misleading. A high RSI does not mean price must fall; strong trends can remain high for a long time. In a mean-reversion rule, a low reading may be used as a possible entry. In a momentum rule, strength may instead confirm an existing rise. The number only gains meaning through the rule around it.

Volatility indicators

Volatility describes the size of price movement, not its direction. ATR uses true range, including gaps from the previous close. Bollinger Bands place bands around a moving average using standard deviation. Donchian Channels track recent highs and lows and are often used for breakouts.

A quiet market produces narrower ranges; an active market produces wider ones. Volatility can help adapt thresholds or position rules, but high volatility does not say whether the next move is up or down. A breakout strategy and a mean-reversion strategy can look at the same wide band and reach opposite decisions.

Volume and money-flow indicators

Volume indicators ask whether trading activity supports a price move. OBV adds volume on up days and subtracts it on down days. VPT weights volume by percentage price change. MFI combines price and volume into an oscillator. CMF considers where the Close sits inside the daily range and weights that position by volume.

Volume must be adjusted consistently around stock splits. A broken volume series can permanently distort cumulative indicators such as OBV. Volume also measures shares traded, not whether “smart money” bought: every completed transaction has a buyer and seller.

Why lookback length matters

A short window responds quickly and creates more signals. It also reacts to more noise and can increase turnover. A long window is smoother but recognizes changes later. Neither is universally correct.

Imagine Close rises from 100 to 110 and then falls to 105. A 5-day average will turn sooner than a 50-day average. Whether that is helpful depends on the strategy’s horizon and costs. Optimizing until one exact window wins historically can fit chance. Prefer settings that behave reasonably across nearby values.

Level versus crossover rules

A level condition says an indicator is above or below a threshold. A crossover says it moved from one side to the other. These are not the same. If RSI stays below 30 for five sessions, “RSI below 30” is true five times, while “RSI crosses below 30” occurs only at the transition.

TickRun converts candidate events into a long-only state: a valid buy opens a position, repeated buys while long are ignored, and a valid sell closes it. This prevents a true condition from creating a new trade on every row.

Should you combine indicators?

Combining indicators can express a sensible hypothesis, such as taking a momentum signal only when the long-term trend is positive. But several indicators calculated from the same prices may repeat the same information. Adding filters also adds parameters and more opportunities to fit history.

Start with one understandable rule. Learn when it works and fails. Add a condition only when it has a clear job, then test whether improvement survives different dates, costs, and instruments.

A simple learning workflow

1. Choose one indicator family and read its rule in the 36-strategy guide.
2. Run the default configuration before changing anything.
3. Look at the price, indicator, and signal markers together.
4. Explain each entry and exit in plain language.
5. Add realistic transaction costs.
6. Change one parameter at a time and observe signal behavior.
7. Compare with Buy & Hold and inspect risk, not return alone.
8. Treat optimized settings as ideas that need later validation.

The useful mental model

Indicators are lenses. Trend indicators summarize direction, momentum indicators summarize speed, volatility indicators summarize movement size, and volume indicators summarize activity. No lens is always correct. A useful strategy states why a measurement should matter, turns it into an executable rule, and tests that rule without using future information.