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Zināšanu bibliotēka

Stratmill pētniecības aģenta sagatavoti kopsavilkumi un galvenās atziņas par grāmatām, pētījumiem, rakstiem un kodu, ko lasa mūsu MI aģenti. Katrā lapā ir saite uz oriģinālu.

Quant Q&A
Dokumentu skaits: 20,364
SuperMind
Dokumentu skaits: 12,226
OKX Learn
Dokumentu skaits: 8,431
Strategy library
Dokumentu skaits: 7,910
MQL5 code base
Dokumentu skaits: 7,090
BigQuant
Dokumentu skaits: 3,481
Bitget Academy
Dokumentu skaits: 3,298
MQL5 articles
Dokumentu skaits: 3,012
TradingView scripts
Dokumentu skaits: 1,976
ProRealCode
Dokumentu skaits: 1,507
Deribit Insights
Dokumentu skaits: 1,232
Machine Learning for Trading
Dokumentu skaits: 1,124
arXiv papers
Dokumentu skaits: 1,033
Amberdata research
Dokumentu skaits: 766
FMZ forum
Dokumentu skaits: 682
FMZ digest
Dokumentu skaits: 662
vn.py community
Dokumentu skaits: 560
QuantInsti blog
Dokumentu skaits: 511
Galaxy Research
Dokumentu skaits: 340
QuantStart
Dokumentu skaits: 246
Stratmill research code
Dokumentu skaits: 219
Robot Wealth
Dokumentu skaits: 195
NautilusTrader
Dokumentu skaits: 191
Hummingbot docs
Dokumentu skaits: 181
Paradigm research
Dokumentu skaits: 175
Lumibot
Dokumentu skaits: 164
Kraken Learn
Dokumentu skaits: 163
Kvantitatīvās tirdzniecības kursu bibliotēka
Dokumentu skaits: 157
OctoBot
Dokumentu skaits: 152
Cryptohopper blog
Dokumentu skaits: 144
Systematic trading blog (Rob Carver)
Dokumentu skaits: 132
Qlib
Dokumentu skaits: 116
TqSdk
Dokumentu skaits: 86
Quantpedia
Dokumentu skaits: 86
Hyperliquid docs
Dokumentu skaits: 79
Freqtrade
Dokumentu skaits: 68
Hudson & Thames
Dokumentu skaits: 62
Awesome Systematic Trading
Dokumentu skaits: 61
backtrader
Dokumentu skaits: 54
vn.py
Dokumentu skaits: 50
Binance API docs
Dokumentu skaits: 45
Quantopian lekcijas
Dokumentu skaits: 45
FMZ guides
Dokumentu skaits: 38
pysystemtrade
Dokumentu skaits: 34
Freqtrade docs
Dokumentu skaits: 32
quant-trading
Dokumentu skaits: 31
FinRL
Dokumentu skaits: 28
Zipline
Dokumentu skaits: 22
FMZ live strategies
Dokumentu skaits: 21
Jesse
Dokumentu skaits: 17
pyfolio
Dokumentu skaits: 16
WonderTrader
Dokumentu skaits: 14
Alphalens
Dokumentu skaits: 14
backtesting.py
Dokumentu skaits: 11
Technical Analysis
Dokumentu skaits: 9
QTPyLib
Dokumentu skaits: 8
QuantRocket
Dokumentu skaits: 7
Lumibot strategies
Dokumentu skaits: 7
Awesome Quant
Dokumentu skaits: 1

Meklēt bibliotēkā

Dokumentu skaits: 3,481

BigQuant

This brief Q&A explains why neutralizing individual factors for market capitalization does not guarantee that a trained stock-selection model will have no size exposure. After neutralization, linear groupings of the factor may contain both large- and…

AkcijasFaktoru ieguldīšanaMašīnmācīšanāsRiska pārvaldība
BigQuant

The strategy combines model-based stock ranking with trend and timing filters for a selected universe of China A-shares. The author describes ranking stocks by predicted prospects, then screening for recent relative strength, liquidity, large-order money…

AkcijasĶīnas tirgiMašīnmācīšanāsCenas impulss
BigQuant

This Chinese research note proposes using capital flow ratios within style-factor portfolios to guide style rotation. It argues that raw inflow and outflow totals mostly move alongside prices, while flows measured against trading value or by…

AkcijasFaktoru ieguldīšanaĶīnas tirgiVēsturisko datu pārbaude
BigQuant

This brief BigQuant forum entry asks whether an already running simulated trading instance automatically follows edits made to its original strategy definition, or remains on the earlier version. The response indicates that the running simulation can be…

Vēsturisko datu pārbaudeRīkojumu izpilde
BigQuant

This BigQuant strategy note describes a stock selection approach based on a fast and slow moving average crossover, identified as MACD-style golden and death crosses. It buys after an upward cross and treats a downward cross as a sell signal. The universe…

AkcijasTehniskie indikatoriCenas impulssVēsturisko datu pārbaude
BigQuant

This short troubleshooting note explains why a pandas table may appear out of order after a sort. In the reported case, rows were first sorted by date and a field named double_low, then sorted again by index, which disrupted the intended ordering. The…

StatistikaVēsturisko datu pārbaude
BigQuant

This report studies whether the most unusual intraday price bar contains useful stock-selection information. It defines extremeness as the absolute distance between a bar’s return and the median intraday return, then examines the bar with the greatest…

AkcijasFaktoru ieguldīšanaAtgriešanās pie vidējās vērtībasCenas impulss
BigQuant

This tutorial walks through a basic Skip-gram word2vec training workflow. A center word is represented by an input vector, and the model predicts each word in its context window using a softmax output layer. The article describes calculating the prediction…

MašīnmācīšanāsTirgus noskaņojumsStatistika
BigQuant

This study compares six cross-validation approaches for tuning machine-learning models on financial time series. It argues that ordinary shuffled K-fold validation can leak temporal structure and select overly complex models. Expanding-window time-series…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaudeĶīnas tirgi
BigQuant

The document gives a conversion procedure for obtaining forward-adjusted stock prices when a platform supplies backward-adjusted prices and their adjustment factors. The first step is to recover the unadjusted market price by dividing the backward-adjusted…

AkcijasStatistika
BigQuant

This short market commentary presents a July 2020 view of Chinese indices and sector positioning. It describes the Shanghai Composite and SSE 50 as correcting while potentially forming daily-chart continuation setups, and says the ChiNext remained in a…

AkcijasĶīnas tirgiSekošana tendenceiRiska pārvaldība
BigQuant

This December 2024 market note tracks sentiment, fund crowding, and two stock-selection approaches in Chinese equities. It describes breadth and moving-average sentiment measures as elevated, with momentum indicators pointing upward. It also reports that…

AkcijasĶīnas tirgiTirgus noskaņojumsFaktoru ieguldīšana
BigQuant

This forum post asks how to implement minute-level backtesting for a stock strategy that receives signals at the daily level and refines exits using intraday prices. The proposed rules would sell a holding after it rises by a specified amount and then…

AkcijasVēsturisko datu pārbaudeRīkojumu izpildeRiska pārvaldība
BigQuant

This research summary examines additional ways to monitor crowding in equity investment factors. Factor crowding refers to a situation in which heavy investment in a factor may weaken its returns or make them less stable. The analysis considers asset…

Faktoru ieguldīšanaAkcijasStatistikaSvārstīgums
BigQuant

This summary of a 2020 study examines equity factor strategies in China’s A-share market, where market structure and regulation can affect how familiar investment signals behave. It reports that carefully designed traditional factor strategies delivered…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaAtgriešanās pie vidējās vērtības
BigQuant

This fund analysis describes a Chinese equity strategy that combines quantitative signals with qualitative judgment. Its inputs include mean reversion in returns and valuations, sector rotation, fundamental reversals, event effects, investor behavior and…

Ķīnas tirgiAkcijasAtgriešanās pie vidējās vērtībasUz notikumiem balstīta tirdzniecība
BigQuant

This overview introduces ten supervised learning approaches: linear and logistic regression, linear discriminant analysis, decision trees, naive Bayes, k-nearest neighbors, learning vector quantization, support vector machines, bagging and random forests,…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaude
BigQuant

This platform support discussion reports sparse cross-sectional coverage for two company growth fields: year-over-year growth in free cash flow and year-over-year growth in adjusted net profit. The author says the free cash flow field has only about 800…

AkcijasĶīnas tirgiFaktoru ieguldīšanaStatistika
BigQuant

The document summarizes research on a listwise learning-to-rank loss designed for constructing long-short stock portfolios. The proposed loss builds on ListMLE but gives extra emphasis to the top and bottom of the ranking, where long and short selections are…

AkcijasMašīnmācīšanāsFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

This document describes an equity factor based on intraday volume moving through a low-to-high-to-low cycle. It smooths volume with a nine-minute neighborhood, identifies a peak and the lowest-volume points before and after it, then measures price-change…

AkcijasFaktoru ieguldīšanaStatistikaVēsturisko datu pārbaude
BigQuant

The article presents a workflow for translating a written trading specification into a QMT strategy. Its example applies ADX and directional indicators to one Chinese-listed equity: buy when ADX exceeds a threshold and positive directional movement is…

Ķīnas tirgiAkcijasSekošana tendenceiTehniskie indikatori
BigQuant

This short strategy summary describes a quantitative stock-selection approach built with TabNet, a machine-learning model. It says the approach extracts 98 price and volume factors, trains the model on data from 2010 through 2018, and applies predictions to…

AkcijasMašīnmācīšanāsFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

This document explains why cash dividends matter when pricing Chinese equity index futures and estimating hedge costs. Because the contracts track price indices, expected constituent dividends affect fair value and the apparent futures basis. The proposed…

Ķīnas tirgiAkcijasNākotnes līgumiAtvasināto instrumentu cenu noteikšana
BigQuant

This study groups 50 Wind order-flow indicators into eight categories, then tests whether they help rank A-share stocks. Its framework combines industry-neutral portfolio sorts, cross-sectional regressions, and information coefficient analysis. The tests use…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaTirgus mikrostruktūra