Data Sources — kScript

Data sources are timeseries feeds you open with source(...) (or via the dedicated function for some sources). Every script needs at least one. Most scripts open ohlcv; specialized indicators reach for the others.

Opening data sources

timeseries ohlcvData = source("ohlcv", currentSymbol, currentExchange);
timeseries funding = source("funding_rate", currentSymbol, currentExchange);

Data Access Methods

kScript v2 provides two ways to access market data.

1. Direct Functions (Recommended)

Use dedicated functions for each data source — cleaner and more readable, with better compile-time checking:

Direct function

timeseries trade = ohlcv(currentSymbol, currentExchange);

2. Universal `source()` Function

Use the general source() function with a data type parameter. More dynamic, but the string identifier isn't checked until runtime:

source() function

timeseries trade = source("ohlcv", currentSymbol, currentExchange);

Some sources expose dedicated functions that take additional parameters:

Dedicated function with custom params

// Treasury balance is keyed by asset, not symbol/exchange
timeseries treasuryBalance = binance_treasury_balance(asset="BTC");

// Equivalent via source()
timeseries treasuryBalance = source("binance_treasury_balance", asset="BTC");

Available Data Sources

kScript provides access to a wide range of data sources covering price data, derivatives, options, lending markets, and institutional flows.

Market data

Source	Description
`ohlcv`	Open, High, Low, Close, Volume bars. The default chart feed.
`orderbook`	Live bid/ask depth — feed the `_*` orderbook functions (`sumBids`, `sumAsks`, etc.).
`buy_sell_volume`	Volume split by aggressor side.
`liquidations`	Forced-liquidation events.
`funding_rate`	Perpetual funding rates with predicted values.
`open_interest`	Open interest series.
`long_short_ratio`	Long/short positioning ratios across all traders, top trader accounts, and top trader positions. Available for Binance, Bybit, and OKX.
`cme_oi`	CME open interest. Only available for BTC and ETH.
`volume_profile`	Per-bar volume-profile ladder — buy/sell volume bucketed by price level. Has no scalar properties; read it with the `vp*` accessor functions (`vpBuy`, `vpSell`, `vpPoc`, …).

Options & volatility

Source	Description
`options_volume`	Puts and calls volume from Binance Options or Deribit. Limited to BTC and ETH.
`options_open_interest`	Puts and calls open interest from Binance Options or Deribit. Limited to BTC and ETH.
`deribit_implied_volatility`	Implied volatility on Deribit. Returns 1W / 1M / 3M tenors. BTC and ETH only.
`deribit_volatility_index`	Deribit DVOL volatility index (OHLC). BTC and ETH only.
`skew`	% difference in IV between call and put options on Deribit. Deltas 15 and 25; tenors 1W / 1M / 3M. BTC and ETH only.

ETF, treasury & DeFi

Source	Description
`etf_flow`	ETF inflow/outflow data. Only available on 1D intervals.
`etf_holding`	Asset balance held by major BTC, ETH, and SOL ETFs.
`etf_premium_rate`	ETF premium/discount to NAV. BTC, ETH, and SOL ETFs.
`binance_treasury_balance`	Value of assets held by Binance, updated monthly. Available for BTC, ETH, SOL, USDT, USDC.
`ethena_positions`	Amount of collateral within the Ethena protocol.

Data Source Categories

Data sources are organized into categories based on the type of market information they provide.

Category	Description	Sources
Price & Volume	Core market data including price, volume, and orderbook dynamics	`ohlcv`, `buy_sell_volume`, `orderbook`, `volume_profile`
Derivatives & Futures	Futures, perpetuals, and derivative market metrics	`funding_rate`, `liquidations`, `open_interest`, `cme_oi`, `long_short_ratio`
Options & Volatility	Options data, implied volatility, and skew metrics	`options_volume`, `options_open_interest`, `deribit_implied_volatility`, `deribit_volatility_index`, `skew`
Institutional & ETF	ETF flows, institutional holdings, and treasury data	`etf_flow`, `etf_holding`, `etf_premium_rate`, `binance_treasury_balance`
Protocols & DeFi	Protocol-specific metrics and DeFi positions	`ethena_positions`

Calling source()

Most data sources are opened with source(name, symbol, exchange):

Calling source()

timeseries ohlcvData = source("ohlcv", currentSymbol, currentExchange);
timeseries fundingData = source("funding_rate", currentSymbol, currentExchange);
timeseries liquidationData = source("liquidations", currentSymbol, currentExchange);

Aligning multiple sources

When mixing feeds (e.g. liquidations on top of OHLCV), align timestamps with matchTimestamp:

Aligning multiple sources

timeseries ohlcvData = source("ohlcv", currentSymbol, currentExchange);
timeseries liquidationData = source("liquidations", currentSymbol, currentExchange);

timeseries alignedLiquidations = matchTimestamp(liquidationData, ohlcvData, "contains");

Match modes:

"exact" — exact timestamp match
"closest" — nearest timestamp
"contains" — bar contains the source timestamp (default for sub-bar events like liquidations)

Common Usage Patterns

Examples of how to use different data sources in your trading strategies.

Basic Price Data

Access OHLCV data for price-based technical analysis.

Price Analysis

//@version=2

define("Price Analysis", "onchart", true);

// Method 1: Direct function (recommended)
timeseries trade = ohlcv(symbol=currentSymbol, exchange=currentExchange);

// Method 2: Using source() function
// timeseries trade = source("ohlcv", currentSymbol, currentExchange);

// Calculate simple moving average on close prices
var sma20 = sma(trade, 20, 4);

plotLine(value=sma20, width=2, colors=["blue"], label=["SMA 20"], desc=["20-period Simple Moving Average"]);

Funding Rate Analysis

Monitor funding rates across perpetual futures markets.

Funding Rate Monitor

//@version=2

define("Funding Rate Monitor", "offchart", true);

// Method 1: Direct function (recommended)
timeseries funding = funding_rate(symbol=currentSymbol, exchange=currentExchange);

// Method 2: Using source() function
// timeseries funding = source("funding_rate", currentSymbol, currentExchange);

// Plot funding rate
var width = input("width", "number", 2);

plotLine(value=funding, width=width, colors=["blue", "green", "red"], label=["Funding Rate"], desc=["Funding Rate Data"]);

Liquidation Monitoring

Track liquidation events and volumes for market sentiment.

Liquidation Tracker

//@version=2

define("Liquidation Tracker", "offchart", true);

// Method 1: Direct function (recommended)
timeseries liquidationData = liquidations(symbol=currentSymbol, exchange=currentExchange);

// Method 2: Using source() function
// timeseries liquidationData = source("liquidations", currentSymbol, currentExchange);

// Plot liquidations as bars
plotBar(value=liquidationData, width=1, colors=["green", "red"], label=["Liquidations"], desc=["Liquidation Data"]);

Volume Profile Analysis

volume_profile carries a variable number of price-level buckets per bar, so it has no scalar properties — you can't read .buy / .sell off it directly. Each bar is a row shaped [timestamp, [priceLow, priceHigh, buyVol, sellVol], …] (one bucket per later slot). Extract scalar timeseries with the vp* accessor functions, or iterate buckets directly via the raw row — see Volume Profile Functions for the data structure and full accessor reference.

It takes an optional ticksPerBar parameter (default 1) that coarsens the ladder by merging every N price levels into one bucket — fewer, wider buckets, which lowers vpBucketCount — and an optional currency parameter ("USD" or "Coin", default "Coin") that quotes each bucket's volume in USD (dollar notional) instead of coins (base-asset units), mirroring the Volume Footprint indicator's currency toggle. Required params are symbol and exchange.

Volume Profile Delta & POC

//@version=2

define("Volume Profile", "offchart", true);

// Method 1: Direct function (recommended)
timeseries vpa = volume_profile(symbol=currentSymbol, exchange=currentExchange);

// Optional: ticksPerBar (default 1) merges every N price levels into one bucket
// timeseries vpa = volume_profile(symbol=currentSymbol, exchange=currentExchange, ticksPerBar=5);

// Optional: currency ("Coin" default) quotes bucket volume in USD instead of coins
// timeseries vpaUsd = volume_profile(symbol=currentSymbol, exchange=currentExchange, currency="USD");

// Method 2: Using source() function
// timeseries vpa = source("volume_profile", currentSymbol, currentExchange);

// Read scalar series with the vp* accessors — direct .buy / .sell is not available
timeseries delta = vpDelta(vpa);
timeseries poc = vpPoc(vpa);

plotBar(value=delta, colors=["#26a69a", "#ef5350"], label=["Delta"], desc=["Net buy/sell pressure"]);
plotLine(value=poc, width=2, colors=["#ff9800"], label=["POC"], desc=["Point of Control"]);

Best Practices

Choose Appropriate Sources

Select data sources that match your strategy timeframe and requirements. For example, etf_flow only updates on 1D intervals, so it's not suitable for intraday strategies.

Cache Data References

Store data source references to avoid repeated function calls.

timeseries trade = ohlcv(currentSymbol, currentExchange);
var fastMA = sma(trade.close, 10);
var slowMA = sma(trade.close, 20);

Handle Data Availability

Not all data sources are available for every symbol/exchange combination. For example, funding rates only exist for perpetual futures contracts, options data is only available on exchanges that offer options trading, and cme_oi is restricted to BTC and ETH. When data is unavailable, the timeseries will contain na values.

Data Access Methods

1. Direct Functions (Recommended)

2. Universal source() Function

Available Data Sources

Market data

Options & volatility

ETF, treasury & DeFi

Data Source Categories

Calling source()

Aligning multiple sources

Common Usage Patterns

Basic Price Data

Funding Rate Analysis

Liquidation Monitoring

Volume Profile Analysis

Best Practices

2. Universal `source()` Function