Written using a standard MT4/MT5-style charting setup. Exact terminology and defaults can vary slightly by platform, so check your own if something doesn’t match.

A chart type controls how price data gets displayed. A timeframe controls how much time each bar represents. Those are two separate settings, and mixing them up is one of the more common points of confusion for anyone new to reading a trading screen. You can view the same one-hour data as candlesticks, OHLC bars, or a simple closing-price line, and none of that changes what timeframe you’re actually looking at.

Once that distinction is clear, everything else in this guide builds on top of it.

How Candlesticks Display OHLC Data

Every standard candle, on every timeframe, provides four pieces of information for that time period: the open, the high, the low, and the close. That’s what OHLC stands for, and it’s worth memorizing because you’ll see the acronym everywhere in trading content.

Open — the price when the candle started forming
High — the highest price reached during that period
Low — the lowest price reached during that period
Close — the price when the candle finished, or the current price if it’s still forming

The thick part of the candle, the body, represents the distance between the opening and closing prices. The thin lines above and below it, sometimes called wicks or shadows, show how far price wandered beyond that range before settling. On an H1 chart, each candlestick represents one hour. Switch to H4, and each one represents four hours. Move to a daily chart, and you’re looking at a full trading day per candle.

One thing worth flagging early, since it trips people up more than you’d think: the current, still-forming candle isn’t finished yet. Its high, low, close, body size, and whatever pattern it appears to be forming can all keep changing right up until the timeframe closes. Reading too much into an incomplete candle is a pretty common beginner habit, and honestly, I think most traders do it at least once before they learn better.

Bullish, Bearish, and Neutral Candles

A lot of beginner material ties candle color directly to a fixed rule, green means good, red means bad, but that’s a presentation choice, not the underlying logic. The actual rule comes down to where price opened relative to where it closed:

Candle type	Condition	Common (not universal) coloring
Bullish	Close above open	Green, white, or hollow
Bearish	Close below open	Red, black, or filled
Doji / neutral	Open and close are equal or very close	Varies by platform

Colors, fill styles, even whether a bullish candle is hollow or filled, all depend on your platform’s settings. Don’t assume a specific color scheme when reading someone else’s chart or screenshot. Check what open and close actually did instead.

Candlestick vs. Bar vs. Line Charts

These are the three most common chart types, and each one presents the same underlying price data with a different amount of visual detail.

Chart type	Data shown	Main advantage	Main limitation
Candlestick	Open, high, low, close	Clear visual direction and range at a glance	Can encourage overinterpretation of patterns
OHLC bar	Open, high, low, close	Compact, information-dense	Less intuitive for some beginners to read quickly
Line	Usually closing price	Clean, uncluttered trend view	Hides intrabar highs and lows entirely

Candlestick charts are one of the most widely used formats because they pack OHLC data into a compact, visually distinct shape, and honestly, they’re probably the easiest for a beginner to read at a glance. Bar charts show the exact same four values, open and close as small horizontal ticks on either side of a vertical line, high and low as the top and bottom of that line, but they take a bit more practice to read quickly. Once you’re used to them, though, spotting a bullish versus bearish bar becomes just as fast.

Line charts connect closing prices only, which strips out a lot of detail. That sounds like a downside, and often it is if you need intrabar information. But a line chart can also make a closing-price trend genuinely easier to see, since there’s no wick noise pulling your eye around. It’s less detailed, not unusable, and some traders lean on it deliberately for that reason.

Worth a quick mention too: charts showing separate bid and ask lines exist, and they’re not just a curiosity. They’re useful for understanding current spread, why a stop order triggered at a slightly different level than expected, or why your buy and sell entries display different prices on the same instrument. Less useful for broad pattern analysis, but genuinely helpful for execution-related questions.

Heikin-Ashi and Transformed Candles

Heikin-Ashi doesn’t get covered in a lot of beginner guides, which is a bit of an oversight given how often it shows up on trading platforms. Unlike standard candlesticks, Heikin-Ashi candles use transformed, averaged values rather than the instrument’s exact open and close prices.

That averaging is exactly what makes trends look smoother on a Heikin-Ashi chart. It can be genuinely useful for visualizing trend direction with less noise. But here’s the catch, and it matters: the prices shown are calculated, not the instrument’s actual tradable OHLC. Don’t treat a Heikin-Ashi close as something you could have actually executed a trade at, because you couldn’t have.

Renko and Other Non-Time-Based Charts

Renko charts ignore time entirely, which is a genuinely different way of thinking about price. Instead of a new bar forming every hour or every day, a new brick forms only after price moves by a defined amount, the box size.

A 20-pip Renko chart, for example, builds a new brick roughly every time price moves 20 pips, but “roughly” is doing some work in that sentence. Exact brick construction varies by platform. Some use closing prices, others use high/low, and reversal requirements, wick display, and whether bricks can update intrabar all differ depending on the data feed and platform you’re using. If you’re planning to build a strategy around Renko, it’s worth verifying exactly how your specific platform handles all of that before assuming it matches what you’ve read elsewhere.

Tick charts and volume-based charts follow a similar non-time-based logic, building a new bar after a set number of ticks or a set amount of traded volume rather than a fixed duration.

Standard Trading Timeframes

Here’s where the article probably should have spent more attention from the start, since timeframe selection genuinely shapes how a strategy behaves.

Timeframe	What each bar represents	Common use	Main trade-off
M1–M5	1–5 minutes	Scalping, execution timing	High noise, cost sensitivity
M15–M30	15–30 minutes	Intraday trading	Needs frequent monitoring
H1	1 hour	Day trading, short swing trading	Still reacts strongly to news
H4	4 hours	Swing trading	Overnight exposure
D1	1 trading day	Swing and position trading	Wider ranges, fewer signals
W1	1 week	Long-term market context	Slow feedback loop
MN	1 month	Structural trend analysis	Very limited execution detail

Treat these as common uses, not fixed rules. Plenty of traders scalp on M15 or swing trade off H1, depending on the instrument and their own risk tolerance.

How Timeframe Changes What You See

Same instrument, same moment in time, wildly different picture depending on which timeframe you pull up. A chart that looks choppy and directionless on M15 might show a clean, obvious uptrend on the daily. That’s not a contradiction exactly, it’s just two different resolutions of the same underlying price action.

This is where multi-timeframe analysis comes in. A trader might use the daily chart to identify the broader trend, the four-hour chart to locate a setup within that trend, and the one-hour chart to fine-tune the actual entry. Each timeframe gets a defined role in that process. What you want to avoid is randomly flipping between timeframes until one happens to confirm whatever opinion you already had going in. That’s not disciplined analysis, that’s just looking for permission.

Current-Candle and Broker-Time Considerations

Two practical details that rarely make it into beginner guides, but genuinely affect how your charts behave:

The current candle isn’t final. Until a timeframe closes, that candle’s high, low, close, and apparent shape can keep shifting. Don’t judge a pattern, or trigger a trade off one, before it’s actually done forming.

Broker server time affects candle construction. A daily candle doesn’t necessarily open and close at the same moment across every broker. Different server times can shift:

Where the daily open and close actually fall
The visible shape of daily and weekly candles
Indicator values calculated from those candles
Whether a pattern signal even appears at all
Backtest results run against that data

This matters most on daily and four-hour charts, where a server-time difference of even an hour or two can noticeably change what the candle looks like.

Chart Data for Algorithmic Trading

Here’s something that gets repeated a lot in trading content, and it’s not quite accurate: the idea that OHLC values are the only data you have available for testing a strategy. Depending on your platform and data source, you might also have access to:

Tick data
Bid and ask price history
Spread
Tick volume or real exchange volume
Timestamps
Lower-timeframe bars
Commission and swap figures
Order-book data, on some markets

OHLC bars are still a common backtesting input because they’re fast and widely available. But higher-quality testing often pulls in tick data, bid-ask history, spread, and volume too, especially for strategies sensitive to execution price.

On the volume point specifically: in spot forex, what your platform displays is usually broker-specific tick volume, meaning the number of price updates recorded, not a centralized global trading volume. That’s just how decentralized spot forex works, there’s no single exchange tallying every trade. Tick volume can still be a genuinely useful activity measure. It’s just not the same thing as, say, exchange volume on a stock or futures market, where actual transaction volume is typically available through the data feed.

OHLC vs. Tick-Based Backtesting

This is a real and important limitation, so it’s worth being precise about it: a single OHLC candle doesn’t reveal the exact sequence in which its high and low occurred. If a strategy’s profit target sits above an H1 candle’s high, and its stop loss sits below that same candle’s low, OHLC data alone can’t tell you which level got touched first. A bar-based test has to apply some documented assumption about the order, and depending on which assumption it picks, the backtest result can shift meaningfully.

Testing method	Data used	Main advantage	Main limitation
OHLC bar test	Open, high, low, close	Fast to run	Intrabar sequence often unknown
Lower-timeframe reconstruction	Smaller bars within the tested bar	Better approximation of price path	Still an approximation, not exact
Tick-based test	Individual price updates	More realistic execution simulation	Data-intensive, feed-dependent
Real-time forward test	Live or demo price stream	Tests actual operational behavior	Time-consuming, may still differ from live fills

To be clear about a claim that shows up occasionally in older guides: it’s not accurate to say lower-timeframe data can’t be used to reconstruct what happened inside a higher-timeframe candle when coding an Expert Advisor. It can, depending on your platform, backtester, and the quality of the data you’re feeding it. It’s an approximation rather than a perfect reconstruction, but it’s a meaningfully better approximation than OHLC bars alone. A complete backtest should also account for variable spread, commission, slippage, swap, and broker time zone, on top of whichever price-data method you’re using.

How to Choose a Chart Type and Timeframe

There’s no single correct combination. It genuinely depends on how you trade. A quick checklist worth running through:

Question	Why it matters
How long will trades stay open?	Your holding period should roughly match your analysis timeframe
How often can you actually check the chart?	Shorter timeframes demand more frequent attention
How wide are typical candles on this timeframe?	Affects your stop distance and position sizing
Are positions held overnight?	Brings in swap, gap, and event risk
Which session are you trading?	Liquidity shifts meaningfully across the day
Is the strategy manual or automated?	Changes how much monitoring you actually need
How many trades do you need for a valid test?	Longer timeframes generate fewer data points over the same period

If you’re building or coding a strategy for algorithmic trading, chart type itself stops mattering much at that point. A trading robot follows whatever entry and exit conditions live in its code, and it doesn’t care whether the chart in front of you is showing candlesticks, bars, or a line. The chart type is for your eyes; the underlying price data is what the code actually reads.

Frequently Asked Questions

What’s the difference between a chart type and a timeframe?

A chart type is how price data gets visually displayed, candlesticks, bars, a line, Renko, and so on. A timeframe is how much time (or, for Renko, how much price movement) each individual bar represents. You can view the exact same underlying price data on an H1 timeframe as a candlestick chart, a bar chart, or a line chart, and the timeframe itself won’t change. These are two independent settings, not one combined choice.

Are candlestick patterns reliable trading signals on their own?

Not on their own, no. Patterns like hammers, engulfing candles, or doji formations describe recent price behavior, but their reliability depends heavily on context: the prior trend, nearby support and resistance, volatility, volume, and confirmation from subsequent price action. Treating a single candlestick pattern as a guaranteed reversal signal, without that surrounding context, is one of the more common mistakes newer traders make.

Why does my daily candle look different from another trader’s daily candle on the same pair?

This usually comes down to broker server time. Daily candles don’t necessarily open and close at the identical moment across every broker, since each one runs on its own server clock. That difference can shift where the daily open and close actually land, change the candle’s visible shape, and even alter indicator values or pattern signals calculated from it. It’s especially noticeable on daily and four-hour charts.

Is tick volume the same as real trading volume in forex?

Generally, no. Spot forex has no single centralized exchange, so most platforms display broker-specific tick volume, essentially a count of price updates, rather than consolidated global trading volume. It’s still a reasonable proxy for market activity, but it isn’t directly comparable to actual transaction volume on an exchange-traded instrument like a stock or futures contract, where volume data usually comes from a centralized source.

Can lower-timeframe data improve a backtest run on higher-timeframe candles?

Yes, generally. A strategy tested purely on H1 OHLC data can’t determine the exact sequence of events inside each candle, which matters if both a stop loss and a profit target sit within that candle’s range. Lower-timeframe or tick data can reduce that ambiguity by approximating the actual price path more closely. It’s not a perfect reconstruction, and results still depend on data quality and the backtester’s assumptions, but it’s a meaningful improvement over OHLC alone.

Final Summary

Chart type and timeframe are two separate dials, not one setting, and getting that straight early makes everything else about reading a chart click into place faster. Candlesticks remain the most visually intuitive option for most traders, bars carry the same information in a more compact form, and line charts trade detail for clarity. Layer timeframe selection on top of that, along with an honest understanding of what your backtesting data can and can’t tell you, and you’ve got a genuinely solid foundation for reading any chart in front of you.

This article is for educational purposes only and does not constitute financial or trading advice. Past chart patterns and backtest results do not guarantee future performance.