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Документів: 61
This post describes a Chinese A-share stock screen combining three conditions: daily amplitude above 1%, a closing price of 18.5 yuan, and a positive MACD value. It frames these as a volatility filter, a fixed-price constraint, and a momentum or trend…
This strategy forms a dollar-neutral stock portfolio by identifying securities that rank among the strongest or weakest performers over two overlapping six-month return windows. It buys stocks in the top decile in both windows and shorts those in the bottom…
This strategy ranks stocks by their return during the month one year earlier, then buys the strongest group and shorts the weakest. It forms portfolios monthly and rebalances at month end. The described source approach uses equal weighting and a large-cap…
This algorithm describes a weekly long-short strategy among large U.S. equities. It first filters for liquid stocks, then selects the largest companies by market capitalization. From that group, it buys the ten stocks with the weakest returns over the prior…
This strategy ranks country exchange-traded funds by estimated market beta, measured against a U.S. equity index using a rolling year of daily prices. Each month, it divides the available funds around the median beta, going long the lower-beta group and…
The strategy allocates across five exchange-traded funds representing US equities, foreign equities, bonds, real estate, and commodities. At a monthly rebalance, it holds each asset class whose price is above its 10-month simple moving average and moves the…
The strategy forms a monthly long-short equity portfolio from NYSE, AMEX, and NASDAQ stocks priced above five dollars. It first keeps the larger half of the eligible universe by market capitalization, then ranks stocks by six-month realized return and…
The document describes a chart indicator for calculating trade size from an entry price, stop level, and a user-selected risk budget. Traders can set risk as a percentage of account balance, a percentage of equity, or a fixed cash amount. The calculation…
This Japanese-language README curates resources for systematic trading research and implementation, including backtesting and live-trading frameworks, analytics tools, data sources, books, papers, blogs, and courses. Its practical framing is to reproduce…
This strategy ranks stocks monthly by the share of their trading volume occurring in recent earnings-announcement months. It uses a 48-month history and focuses on the latest 16 announcement months, then divides stocks into quintiles by the resulting…
The document outlines a short-horizon SPY strategy based on changes in synthetic lending or borrowing intensity. It averages borrow-intensity readings across a broad set of stocks and ETFs, compares the daily aggregate with the prior day, and uses the sign…
This document describes a cross-sectional momentum strategy for equity mutual funds. It first limits the universe to no-load funds, then ranks eligible funds by their trailing six-month returns. The portfolio holds the top decile, equally weighted, and…
This strategy uses SPY, VIX, and the Brain Market Sentiment indicator to determine exposure to an overnight SPY trade. It checks each series against its 20-day average: SPY and sentiment must be above their averages, while VIX must be below its average. Each…
This Chinese-language README catalogs resources for systematic trading research and implementation, including backtesting frameworks, trading libraries, data sources, strategies, books, videos, blogs, and courses. Its listings span multiple asset classes and…
This document outlines a dispersion trade using options on constituents of the S&P 100 and options on the index. The research concept measures disagreement in analyst earnings forecasts, scaled by an earnings-uncertainty measure, and sorts stocks into groups…
This strategy ranks commodity futures by roll return each month, buys the highest-return group, and shorts the lowest-return group. The groups are equally weighted, and positions are held for one month. The implementation calculates roll return from the…
The strategy tracks the daily price difference between continuous WTI and Brent crude futures and compares it with a 20-day simple moving average. When the spread is above its average, it takes positions intended to profit from a decline toward that…
The document describes a cross-market futures reversal strategy. It groups contracts by recent changes in trading volume and open interest, then selects contracts in the high-volume, low-open-interest group. Within that subset, the stated method goes long…
The strategy ranks currency futures using purchasing power parity data as a currency-value signal. Its description proposes a universe of roughly ten to twenty currencies, estimates fair values using OECD PPP figures adjusted with monthly CPI and…
The strategy described in the code sorts stocks around earnings announcements by their returns from four to two trading days before the event. The underlying research description first divides stocks by firm size, then sorts the largest size group into…
This QuantConnect algorithm ranks six U.S. equity style ETFs covering small-, mid-, and large-cap value and growth. It measures each ETF’s momentum over roughly twelve months of daily data, then takes a long position in the strongest style and a short…
The document implements a monthly long-only stock-selection approach based on historical volatility. It describes ranking large-cap stocks by the volatility of weekly returns over roughly three years, then holding an equally weighted group from the…
The strategy shorts publicly traded soccer club stocks at the close before a major match and holds positions for one day. When several clubs play on the same date, their short positions are equally weighted. The implementation uses match-date data to…
The strategy ranks equities by a short-activity measure and forms a monthly long-short portfolio. It sorts stocks into deciles using short interest relative to shares outstanding, buys the lowest-ratio group, and shorts the highest-ratio group, with equal…