Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
59 documents
The post questions whether the minimum option price checks used before implied volatility calculations are correct in the Black–Scholes and Black–76 models. It observes that the two implementations use the same expressions, even though Black–76 uses a…
This forum question examines why changing the initialization length of a trading system’s ArrayManager can materially alter a backtest. The strategy uses RSI generated through TA-Lib, and the author suspects that the indicator’s path dependence makes its…
This Chinese-language forum post concerns calculating higher-timeframe indicators in real time from a lower-timeframe bar callback, such as updating 30- or 60-minute KDJ or RSI while processing five-minute bars. The example creates separate bar generators…
The discussion describes a rolling-window backtest in which parameters are optimized on a sequence of historical months and then applied to the next month. As the test advances, the training window shifts forward by one month, so each new period is evaluated…
A trader asks where an individual can access tick-by-tick trades that include buyer or seller initiation, intending to calculate aggressive buying and selling volume at each price for an order-imbalance strategy. The reply says that ready-made aggressor-side…
This forum exchange addresses a question about changing historical EMA readings and repeated signals in a VeighNa CTA strategy using ArrayManager. The answer explains EMA as a recursive indicator: each new bar updates the current value using the latest price…
This forum exchange clarifies how VeighNa’s CTA strategy state file is used during initialization. A strategy first derives variable values from historical data and indicators, then reads saved JSON data to overwrite corresponding strategy variables.…
The article describes an integrated order flow imbalance factor built from changes in bid and ask quantities across five limit order book levels. It explains how each level’s imbalance can be normalized by typical depth, then combined with principal…
A user reports that minute-bar open and close prices generated from CTP market data sometimes differ from values shown in mainstream trading software, with discrepancies of about one currency unit. The reply identifies a timestamp convention as a possible…
This forum discussion documents installation problems while setting up vnpy_ctp on a freshly reinstalled Intel Mac. The initial failure occurred during an editable package installation because pip could not obtain the required meson-python dependency. A…
This document lays out a sequence of practical exercises for learning quantitative trading with VN.PY. The projects cover market data retrieval and database storage, vectorized indicator calculations, CTA strategy development, cleaning futures data, and…
This community post reports a failure in a VeighNa CTA backtest on Windows with a Tushare data service. Historical one-minute futures data downloads successfully and the strategy loads, but the run fails when the backtesting engine calculates performance…
This forum post reports a possible data-handling issue in a bar generator that aggregates ticks into one-minute bars. When the first tick arrives just after 9:30, its last traded price is used to initialize the bar’s open, high, low, and close. The post says…
A VeighNa community exchange answers whether the `self.sync_data()` method is available in version 2.5.7 spread-trading strategies. A user reports that the method works in CTA strategies but raises an error when called from a spread strategy while attempting…
The forum post addresses why the Average True Range calculated in VeighNa may differ substantially from the value shown in TradingView. It proposes checking several potential causes: differences in the ATR formula or smoothing method, discrepancies in the…
The article recommends cleaning tick data before using it in strategy research or backtests, since duplicate records, implausible prices, out-of-order timestamps, and missing fields can distort results. Its example workflow sorts records by timestamp,…
This VeighNa community contribution describes additions to a backtesting statistics engine for evaluating strategies with regressed annual return (RAR), R-Cubed, and Robust Sharpe. RAR is calculated by regressing cumulative returns across time intervals and…
This short forum exchange concerns a VeighNa Trader configuration error. An initial response interprets an invalid integer conversion as a nonnumeric value in a field expected to contain an integer and recommends deleting the settings file so the application…
A trader reports an error while running an rb-hc spread strategy in a simulated environment. The failure occurs when the strategy attempts to convert its current grid position into an integer target position, but the value is NaN. The trader suspects that a…
This forum exchange explains why a futures backtest can differ from a course example even when the strategy and settings are the same: the data series may be revised over time. It describes the platform’s 888 series as a continuously smoothed main-contract…
This forum exchange concerns missing hourly bars created by aggregating minute data for a futures contract. A user reports that the stored hourly series is incomplete on a particular date, despite the underlying minute records appearing intact, and later…
This excerpt describes a problem while building a five-minute bar series from minute bars or ticks with VeighNa’s BarGenerator and storing the results in an ArrayManager. The author reports that keeping direct edits to arrays such as close and high arrays…
The article explains how to calculate the Resistance Support Relative Strength (RSRS) market-timing indicator more quickly. RSRS fits a rolling regression of highs against lows; its slope is used as a measure of the relationship between resistance and…
The document outlines a training program on cross-sectional multi-factor strategies, also described as alpha strategies. Its curriculum spans factor data preparation, supervised learning, model evaluation and interpretation, portfolio construction, and…