Market data & backtesting

Four modules form a chain: Historical Data downloads price history into local datasets; Visualization, Backtest and Quant Tools all work on those datasets and require Historical Data to be installed.

Historical Data

Download OHLCV candles from external providers into datasets stored in your database. Once downloaded, the data is yours — chart it, backtest it, export it, no re-fetching.

Providers & credentials

The Settings tab lists the available providers with their docs and rate limits. Some are keyless (work immediately), others need an API key — most have free tiers. Enter credentials once; they are stored encrypted. A provider that needs credentials shows Needs credentials in the download form until you set them.

Outbound calls are counted in Settings → API rate so you can watch your free-tier usage.

Downloading

Pick provider, asset type, timeframe, ticker and date range, then Download. Notes:

• Futures use contract codes: base + month letter + year digit (F G H J K M N Q U V X Z = Jan…Dec), e.g. GCJ5 for April 2025 gold.
• Options are built from underlying, expiry, call/put and strike.
• Intraday limits: providers only serve intraday granularity for a limited lookback (e.g. ~7, 60 or 730 days depending on provider). Older history is available at 1d / 1w without limit. The form warns you before you queue an impossible range.

Downloads run as background jobs, chunk by chunk, with live progress. Filter jobs by status, provider, timeframe or ticker.

Datasets

The Datasets tab lists everything stored: bar counts, date range, size. From here you can:

• Fetch newer — pull bars newer than the last one stored (top up a dataset).
• Export the data.
• Delete a dataset (drops all its bars).
• Jump straight to a chart of it.

Historical Data Visualization

Charts any stored dataset. Pick a dataset (search by ticker/provider, filter by asset type and timeframe) and you get:

• Chart types — candles, OHLC bars, line, and Renko (with brick size).
• Indicators — add SMA, RSI, MACD and more, as overlays or separate panes, each with configurable source, line/fill colors and width.
• Chart settings — linear or logarithmic price scale, grid lines, crosshair, hover tooltip, up/down colors.
• Volume pane, fullscreen mode, and jump-to-start / fit / jump-to-latest navigation.

If the dataset you want isn't there yet, the picker links straight to a new download.

Backtest

Combine indicator signals, size with pyramiding, measure the edge. Pick one dataset or a whole portfolio, define rules, run — no code.

Strategy

• Entry / exit rules per side, built from comparisons between indicators, price and fixed values. Group rules with AND (all must hold) or OR (any one is enough).
• Direction — long, short, or both. Options: derive the short side as the inverse of long, and stop & reverse (flip position when the opposite signal fires).
• Stop-loss / take-profit per side — each is a checkbox you turn on or off independently (percent of average entry, or an ATR multiple). With no exit rules, exits happen via SL/TP or reversal.

Sizing, account & costs

• Size by percent of equity or fixed quantity/lots/contracts, with leverage and starting capital. Fixed quantity scales with leverage, following the retail convention — a leverage of 3 on a fixed size of 1 opens 3 units.
• Pyramiding — allow up to N stacked entries when the entry signal re-fires; SL/TP then track the average entry price.
• Costs — fee (fixed or % of notional, per trade or per unit) and spread %, so results aren't fantasy.

Sizing (advanced)

Beyond percent-of-equity and fixed quantity:

• Risk per trade — size so a stop-loss hit costs a fixed % of equity (needs a stop on the traded side).
• Fractional Kelly — size from the win rate and payoff of the last N closed trades, scaled by your chosen fraction and capped; a warm-up size is used until the window fills.
• Equity tiers — a table of thresholds; the highest tier whose level is ≤ current equity sets the size.

Portfolio (multi-asset)

Add several datasets and run one strategy across all of them on a merged clock (all locked to the same timeframe):

• An alignment preview shows the merged-clock length, the overlapping window, indicator warm-up bars (including the cumulative lookback of a chained custom indicator), and per-asset missing bars — before you simulate.
• Portfolio limits — cap the number of open positions and total / per-asset exposure.
• A per-asset breakdown reports trades, net PnL, fees, win rate and exposure for each instrument.

Grid strategy

A ladder of price levels between a lower and upper bound; each cell buys low and sells at the next level up — long, short or neutral. Size a fixed quantity per level or split a total budget across cells, with optional stops above/below the ladder. Results report fills, round trips and end inventory.

Costs & execution realism

• Slippage — a fixed number of ticks or a percent of price, applied to every fill.
• Funding — a constant annual rate on open notional for perp estimates (longs pay, shorts receive).
• Circuit breakers — halt trading after a max daily loss (for the day) or a max drawdown (for the run).
• Instrument profile — tick size, lot step, minimum quantity and contract multiplier, so sizes and prices snap to a realistic contract.

Expert mode

A full-screen builder for power users:

• Named strategies — save, search, duplicate and edit full strategy configurations.
• Custom indicators — build your own from named steps, no code. Each step either applies a built-in indicator to a source — a price field or the output of an earlier step — or computes a formula referencing earlier steps by name (@volume / SMA(@volume), with + − × ÷, min, max, abs, clamp). This lets you chain indicators: a Hull MA of an RSI, a MACD of an RSI, a smoothed volume ratio, and so on. Indicators that read full candles (ATR, Stochastic, ADX, VWAP…) only apply to the price, not to a derived step. The highlighted step(s) are the output. Custom indicators become operands in the rule editor alongside the built-ins.
• Searchable indicator picker — pick indicators from a grouped, type-to-filter list (in both the rule editor and the custom-indicator builder) instead of scrolling one long dropdown.

Out-of-sample split

Split the data into an in-sample head and an out-of-sample tail; the strategy runs on both and the two stat blocks (return, profit factor, win rate, max drawdown, trades) are shown side by side. A large gap between the columns is a sign of overfitting.

Results

• Headline stats: return (vs buy & hold), net PnL and fees, win rate, profit factor, expectancy, max drawdown, Sharpe/Sortino.
• Equity curve overlaid on price with entry/exit markers.
• A full performance summary (gross profit/loss, payoff ratio, largest win/loss, max consecutive wins/losses, average bars in trade…) and the complete list of trades with per-trade MAE/MFE (worst open loss / best open profit while in the trade), filterable, and exit reasons (signal faded, exit signal, stop-loss, take-profit, reversed, data end).
• Save runs by name and keep a history to compare strategies later; each saved run has a downloadable Markdown report.

Quant Tools

Risk/return analytics on your datasets and trade history, in six tabs:

Single Asset

Pick a dataset and a time range, and get the risk profile: historical volatility (annualized), max drawdown, Value at Risk and Conditional VaR at your chosen confidence, plus drawdown and return-distribution charts.

Portfolio

Select 2+ datasets with the same timeframe:

• Correlation matrix — are you diversifying, or buying the same asset twice?
• Efficient frontier — a cloud of random allocations; click the highlighted max-Sharpe or min-volatility points to read their weights.
• Risk parity — weights that size volatile assets smaller so no single name dominates risk.

Position Size

The everyday one: given your stack, entry, stop and risk, it computes position size, notional, margin needed, exposure and reward:risk. It can also suggest stops from a dataset — volatility-, ATR- and swing-based — and fill entry from the last close.

Kelly

From win rate and payoff (or avg win/loss), computes the Kelly fraction with half- and quarter-Kelly variants. Full Kelly maximizes long-run growth but is volatile; most traders size at half or quarter Kelly.

Monte Carlo

Pick a saved backtest run and resample its realized trade sequence thousands of times to see how much of your result was skill versus luck. You get percentile bands on final equity and max drawdown (a fan chart of the paths and a distribution chart), plus a risk of ruin — the fraction of paths whose equity ever fell to a threshold you set — with your real, un-resampled equity curve overlaid for reference.

Seasonality

Over a single dataset, a set of heatmaps of average return by month of year, day of week and hour of day, each cell showing the mean and its sample count — so you can spot recurring calendar patterns. The hourly clock is UTC.