When does the weekly candle open and close? Weekly bar boundaries by asset class
Weekly candle open and close times for forex, crypto, and US stocks, and how to rebuild either week convention from timestamped SiftingIO bars in pandas.
Category · Quant Research & Backtesting
Quant Research & Backtesting
Strategy research, backtesting harnesses, and signal construction.
Latest in Quant Research & Backtesting
How accurate is real-time market data? A live spread snapshot across crypto, FX, and gold
Consolidated bid/ask spreads measured live on BTCUSD, EURUSD, XAUUSD and more: why one price is really a band, and how to reproduce the numbers yourself.
Intraday stock data for student research: how Quantitative Trading at Brown uses the SiftingIO API
How Quantitative Trading at Brown uses intraday US equities OHLCV bars from the SiftingIO API for student research on returns, volatility, and trading volume.
1-minute OHLCV data: how to resample minute bars into 5m, 15m, and 1h
1-minute OHLCV bars are the base timeframe. The exact rules for resampling minute bars into 5m, 15m, and 1h bars, with the alignment and gap traps to avoid.
Daily candle open and close times: forex, crypto and US stocks
Compare daily candle open and close times for forex, crypto and US stocks, including UTC vs New York cutoffs, daylight saving and regular trading sessions.
Why two backtests of the same strategy disagree: the historical price data faults to check first
Five ways historical price data silently corrupts a backtest: adjustment method, venue-dependent highs and lows, gap policy, session cuts, and restated bars.
Adjusted vs unadjusted stock prices: total return vs price return in a backtest
Build a total-return series from as-traded prices, split factors, and cash dividends with reinvestment math, and see where the adjusted-close shortcut misleads a backtest.
Weighted median price aggregation: why averaging venue prices fails
Why the same asset shows different prices on different venues, how naive averages get poisoned by bad feeds, and how a weighted median keeps the price honest.