Kwant

Get Price History

Get historical OHLCV price bars for a ticker. US symbols are bare (AAPL, MSFT); TSX symbols use the Yahoo .TO form (RY.TO) or the TSX:RY form. interval is one of 1m,5m,15m,30m,1h,1d,1wk,1mo (default 1d); range is one of 5d,1mo,3mo,6mo,1y,2y,5y,max (default 1y). Returns an envelope whose values contains interval, range, currency, count, and bars (records with an ISO timestamp plus open, high, low, close, volume). (paid: $0.0050/call)

Get Quote

Get the latest available quote for a ticker. US symbols are bare (AAPL); TSX symbols use the Yahoo .TO form (RY.TO) or the TSX:RY form. Returns an envelope whose values holds the quote fields (price, currency, previous_close, change, change_percent, volume, market_state, asof as an ISO string). (paid: $0.0050/call)

Get Fundamentals

Get fundamental data for a ticker (profile + key ratios). US symbols are bare (AAPL); TSX symbols use the Yahoo .TO form (RY.TO) or the TSX:RY form. Returns an envelope whose values holds available fundamentals: name, exchange, currency, sector, industry, market_cap, pe_ratio, forward_pe, eps, dividend_yield, beta, fifty_two_week_high, fifty_two_week_low, asof. Fields not covered by the provider are null. (paid: $0.0050/call)

Compute Indicator

Compute a technical indicator (RSI, MACD, SMA, EMA, BBANDS, ATR, ADX, STOCH) over a ticker's price history. Returns the warmup-aligned series plus the latest values and a one-line summary. Tune the window with `length` (SMA/EMA/RSI/ATR/ADX/BBANDS), `fast`/`slow`/`signal` (MACD), `std` (BBANDS), or `k`/`d`/`smooth_k` (STOCH) — pass them either as top-level fields OR nested under `params`; both work. `window` and `period` are accepted as aliases for `length`. NOTE: for a long window like SMA(200)

Detect Signals

Detect classic technical-analysis signals on a ticker's price history. Each requested signal is evaluated and reported as triggered/not-triggered with a date and human-readable detail under signal_summary. Signals (omit `signals` to check all six): golden_cross = SMA(50) crosses above SMA(200) within `lookback`; death_cross = SMA(50) crosses below SMA(200); macd_cross = MACD line crosses above its signal line (bullish); rsi_oversold = RSI(14) below 30 at the latest bar; rsi_overbought = RSI(14)

Compute Stats

Compute quantitative statistics (volatility, sharpe, max_drawdown, returns, beta, correlation) over a ticker's daily price history. Omit `metrics` to default to volatility/sharpe/max_drawdown/returns. `beta` and `correlation` require a `benchmark` ticker; `risk_free_rate` is used only by the Sharpe ratio. (paid: $0.0050/call)

Compare Tickers

Rank two or more tickers against each other by a single metric (total_return, volatility, sharpe, max_drawdown, last_price). Symbols that cannot be resolved (or lack enough history) are skipped and noted in `warnings` rather than failing the call. Returns a ranked list of {ticker, value, rank, currency} (rank 1 = best). (paid: $0.0050/call)

Screen

Screen a stock universe for tickers matching quantitative filters (logical AND). Fields: price, rsi, sma_50, sma_200, volatility, sharpe, max_drawdown, total_return, dollar_volume, garman_klass_vol. Ops: lt, lte, gt, gte. (paid: $0.0100/call)

Backtest

Backtest a simple long-only technical strategy on daily price history. Strategies: sma_cross (golden/death cross of SMA 50/200), rsi_reversion (enter RSI<30, exit RSI>70), macd_cross (MACD line vs signal). No-lookahead: signals act on the next bar's close. Returns trades + performance metrics. (paid: $0.0100/call)

Screen With Scores

Rank a stock universe by a continuous cross-sectional signal score (rank 1 = highest z-score). Signals: jt_momentum, mean_reversion, rsi_filtered_momentum, trend_quality. Scores are relative to the scanned set. (paid: $0.0100/call)

Compute Universe Scores

Score and rank a universe of tickers by a cross-sectional signal. Resolves either a named universe (SP500, TSX) or an explicit tickers override, bulk-fetches daily price history over range, computes a raw per-ticker score for the chosen signal, then converts those raw scores into cross-sectional z-scores and ranks them across the universe (rank 1 = highest z-score). Signals (Jegadeesh–Titman momentum is 12-month minus 1-month return on month-end resampled closes): jt_momentum (that JT 12-1 momen

Build Monthly Universe

Rank a universe of tickers by monthly dollar volume with trailing returns. Resolves either a named universe (SP500, TSX) or an explicit tickers override, bulk-fetches daily OHLCV over range, resamples each to monthly bars (open=first, high=max, low=min, close=last, volume=sum), and per ticker computes trailing returns over 1/3/6/12 periods plus the latest monthly dollar volume (close * volume). Tickers are ranked by latest dollar volume (descending) and the top top_n are returned. Tickers that f

Construct Portfolio

Turn a {ticker: score} mapping into long-only portfolio weights. Selects names and assigns non-negative weights that sum to 1.0 using the chosen method: top_n_weighted (weight by clipped score), equal_weight, risk_parity (inverse-volatility), concentrated_vol (highest-vol from a top-score pool), or sharpe_optimized (max-Sharpe long-only). The last three fetch daily history over range (5d,1mo,3mo,6mo,1y,2y,5y,max) and convert it to returns; tickers that fail to fetch are dropped with a warning. R

Run Portfolio Backtest

Backtest a rebalanced, multi-ticker, long-only quant portfolio. Fetches daily history for every ticker over range, then runs a walk-forward simulation: at each period-end rebalance the chosen signal (jt_momentum, mean_reversion, rsi_filtered_momentum, trend_quality) scores each name using only data up to that date, and method turns those scores into long-only weights. Returns gross and net (after cost) performance. rebalance is M (monthly) or Q (quarterly); cost_bps is round-trip cost on turnove

Compute Portfolio Stats

Compute portfolio-level statistics for a weighted basket of tickers. Given a {ticker: weight} mapping, fetches each ticker's daily history over range and returns the portfolio-level (not per-ticker) volatility, sharpe, max_drawdown and total_return of the weighted basket. weights need NOT sum to 1 (normalized internally). Tickers that cannot be fetched are dropped, a note is added to warnings, and the remaining weights are renormalized. risk_free_rate is an annual rate used only by Sharpe. Retur

Compute Correlation Matrix

Compute the pairwise return-correlation matrix for a list of tickers. Fetches each ticker's daily history over range, converts it to daily returns, and computes the pairwise Pearson correlation (aligned on shared dates). Requires at least two tickers; tickers that cannot be fetched are dropped and noted in warnings (at least two must survive). Returns the standard envelope; values holds range, the tickers used, and matrix — a nested dict {rowTicker: {colTicker: correlation}} with a 1.0 diagonal.