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Kunskapsbibliotek

Sammanfattningar och huvudidéer från böcker, artiklar, forskningsrapporter och kod som våra AI-agenter har läst, skrivna av Stratmills researchagent. Varje sida länkar till originalet.

Quant Q&A
20,364 dokument
SuperMind
12,226 dokument
OKX Learn
8,431 dokument
Strategy library
7,910 dokument
MQL5 code base
7,090 dokument
BigQuant
3,481 dokument
Bitget Academy
3,298 dokument
MQL5 articles
3,012 dokument
TradingView scripts
1,976 dokument
ProRealCode
1,507 dokument
Deribit Insights
1,232 dokument
Machine Learning for Trading
1,124 dokument
arXiv papers
1,033 dokument
Amberdata research
766 dokument
FMZ forum
682 dokument
FMZ digest
662 dokument
vn.py community
560 dokument
QuantInsti blog
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Galaxy Research
340 dokument
QuantStart
246 dokument
Stratmill research code
219 dokument
Robot Wealth
195 dokument
NautilusTrader
191 dokument
Hummingbot docs
181 dokument
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Lumibot
164 dokument
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163 dokument
Kursbibliotek för kvantitativ handel
157 dokument
OctoBot
152 dokument
Cryptohopper blog
144 dokument
Systematic trading blog (Rob Carver)
132 dokument
Qlib
116 dokument
Quantpedia
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TqSdk
86 dokument
Hyperliquid docs
79 dokument
Freqtrade
68 dokument
Hudson & Thames
62 dokument
Awesome Systematic Trading
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backtrader
54 dokument
vn.py
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pysystemtrade
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quant-trading
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FinRL
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Zipline
22 dokument
FMZ live strategies
21 dokument
Jesse
17 dokument
pyfolio
16 dokument
Alphalens
14 dokument
WonderTrader
14 dokument
backtesting.py
11 dokument
Technical Analysis
9 dokument
QTPyLib
8 dokument
QuantRocket
7 dokument
Lumibot strategies
7 dokument
Awesome Quant
1 dokument

Sök i biblioteket

79,386 dokument

SuperMind

This Chinese stock-screening post combines three filters: rank stocks by a measure of capital inflow, require weekly MACD to be above its zero line, and keep stocks whose ten-day gain is positive but below 35%. The author frames the filters as a way to find…

AktierKinesiska marknaderMomentumTekniska indikatorer
SuperMind

This Chinese equity screen selects stocks with daily amplitude above 1, turnover between 2% and 9%, and displayed first-level bid volume greater than first-level ask volume. The article frames amplitude and turnover as activity and liquidity measures, with…

Kinesiska marknaderAktierMarknadsmikrostruktur
ProRealCode

This indicator plots a conventional RSI of closing prices alongside an RSI calculated from a multi-vote On-Balance Volume series. The OBV component assigns directional votes based on changes in the high, close, and low, averages those votes, weights them by…

AktierTekniska indikatorerMomentum
SuperMind

This Chinese equity screening method combines daily amplitude above 1, a weekly crossover of the five-period moving average above the ten-period average, and a positive change in the KDJ K value. The article presents the conditions as a way to identify…

Kinesiska marknaderAktierMomentumTekniska indikatorer
SuperMind

This Chinese equity screen combines daily price amplitude above 1, a positive weekly MACD reading, and a market-cap rank between the 20th and 70th percentiles. The article also describes ranking candidates by volume relative to its 20-period average, then…

Kinesiska marknaderAktierMomentumTekniska indikatorer
MQL5 code base

This expert advisor uses a moving average to generate directional entries. Four consecutive declining moving-average values establish a downward trend condition, with a price rebound above the latest average triggering a sell; four rising values establish an…

ValutahandelTekniska indikatorerPositionsstorlekRiskhantering
MQL5 code base

This indicator presents the standard Relative Strength Index as a histogram after rounding its readings to configurable increments. The described settings range from no rounding to progressively coarser groupings, including a three-level display at zero, the…

Tekniska indikatorerAktierValutahandel
SuperMind

This Chinese-language post describes an equity screening rule combining price amplitude above a threshold, a rounded or arc-like price pattern, and a signal that the stock was controlled by major traders on the previous day. It presents the combination as a…

AktierTekniska indikatorerRiskhantering
ProRealCode

This long-only daily strategy seeks short-term rebounds in equity index CFDs while limiting entries to prices above a 200-period moving average. It sums RSI readings over the most recent two periods and enters when this cumulative measure falls below 35,…

AktierMedelvärdesåtergångTekniska indikatorerRiskhantering
BigQuant

This brief request proposes a factor based on the correlation between a benchmark’s returns and an individual stock’s returns over a three-day window. It names the intended inputs and lookback, but provides no code, worked example, explanation of how to…

AktierStatistikFaktorinvestering
SuperMind

This stock-selection idea combines three filters: a daily trading range above one percent of the previous close, a stock code beginning with 60, and a positive afternoon large-order flow signal. The code example operationalizes the range and code filters,…

AktierKinesiska marknaderTekniska indikatorerMarknadsmikrostruktur
BigQuant

This April 2020 market note reviews a sharp decline in Chinese equities amid weakening fundamentals and falling investor sentiment. It reports that large- and small-cap indexes had similar declines, while consumer and utility sectors held up better and…

AktierKinesiska marknaderPortföljkonstruktionRiskhantering
MQL5 code base

This programming note explains how an object-oriented trading advisor can manage its configurable inputs as a structured set. It contrasts manually declaring fields and writing string conversion methods with a macro-based library that generates parameter…

OrderutförandeBacktestningPortföljkonstruktion
SuperMind

This note describes a Chinese equity screen for stocks associated with the metaverse concept. It requires turnover between 3% and 12% and at least one limit-up event during the prior 25 days. The accompanying examples translate these conditions into…

AktierKinesiska marknaderMomentumUtbrott
SuperMind

This note outlines a screen for Chinese equities associated with the robotics concept. It combines turnover between 3% and 12%, floating market capitalization below 10 billion yuan, and a ratio of 2021 revenue to 2018 revenue above 1.1. The post includes…

AktierKinesiska marknaderFaktorinvesteringRiskhantering
SuperMind

This note describes a Chinese A-share filter combining a turnover rate between 3% and 12%, a Dragon-Tiger list appearance the previous day, and a floating market capitalization between 5 billion and 10 billion yuan. It presents this as a way to find actively…

AktierKinesiska marknaderMarknadsmikrostrukturRiskhantering
MQL5 code base

The method treats signals from an indicator as candidate highs or lows rather than immediate trade entries. It uses zigzag-style logic to connect candidate pivots and checks whether each candidate can form a geometrically plausible leg. A candidate that…

Tekniska indikatorerUtbrottRiskhantering
BigQuant

This note explains how to handle low-frequency financial or analyst factors alongside daily price and volume factors when constructing nonlinear models. One approach is to merge monthly or quarterly fundamentals with daily market data and carry the latest…

MaskininlärningFaktorinvesteringStatistikBacktestning
SuperMind

This stock-selection approach combines a positive MACD reading with a company-type condition and circulating market capitalization above 10 billion yuan. The document presents the screen as a way to find stocks with upward price trends, sound fundamentals,…

AktierTekniska indikatorerMomentumKinesiska marknader
SuperMind

This post outlines a Chinese A-share stock screen combining an RSI below 65, seven consecutive down days, and a weekly five-period moving average crossing above the ten-period average. It presents the conditions as a way to identify stocks with a potentially…

AktierTekniska indikatorerMomentumKinesiska marknader
BigQuant

This brief note describes a feature-selection exercise based on a random forest template. The author says they ranked 37 stock factors by random forest importance and retained the nine factors with the highest importance scores. The document does not…

AktierFaktorinvesteringMaskininlärningStatistik
BigQuant

This Chinese-language research summary discusses forecasting stock-selection factor returns after commonly used factors became more volatile. It focuses on screening timing variables with Lasso and Elastic Net regression, then extending factor timing with…

AktierFaktorinvesteringMaskininlärningBacktestning
BigQuant

The post raises a backtesting concern: a user observes that a stock delisted on one date still appears sellable on a later scheduled rebalance date. A reply explains the platform behavior as a special backtest-engine rule: when a strategy does not handle a…

BacktestningAktierRiskhantering