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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
Alphalens
Dokumentu skaits: 14
WonderTrader
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 report develops a framework for rotating between the CSI 300 and ChiNext indices, whose valuations, market capitalizations, and industry exposures differ. It organizes potential drivers of their relative performance into factors covering real economic…

Ķīnas tirgiAkcijasFaktoru ieguldīšanaPortfeļa veidošana
BigQuant

The document introduces MACD as a momentum and trend indicator derived from the difference between a short-period and a long-period exponential moving average. It describes the signal line as an EMA of MACD and the histogram as the difference between those…

Tehniskie indikatoriCenas impulssSekošana tendencei
BigQuant

This introductory overview explains machine learning as using historical data to fit a model and then applying that model to new cases. A scheduling example illustrates how prior observations can inform a prediction, while noting that a practical model may…

MašīnmācīšanāsStatistika
BigQuant

This beginner’s post describes an attempted reproduction of a quantitative research report’s “Water Drops Wear Away Stone” factor and a single-factor stock-selection backtest. The author says the implementation was prepared as a learning exercise with help…

AkcijasFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

The report estimates a fund’s equity exposure by regressing daily fund returns on daily returns for 29 first-level industry indices. It treats the sum of fitted industry coefficients as the estimated position. Because industry returns are correlated, it…

AkcijasStatistikaMašīnmācīšanāsPortfeļa veidošana
BigQuant

This weekly report describes two event-driven approaches to Chinese equities. The product-price strategy tracks listed companies’ main product prices and flags cases where a clear price increase has not yet been reflected in share prices. It is updated…

AkcijasĶīnas tirgiUz notikumiem balstīta tirdzniecībaTirgus noskaņojums
BigQuant

This forum post documents a failure in a stock strategy’s trailing-stop routine. The routine reads each position’s last sale date, subtracts it from the current date to estimate holding days, and uses that value as the bar count when requesting historical…

AkcijasRiska pārvaldībaRīkojumu izpilde
BigQuant

This brief Chinese-language page introduces a portfolio optimizer as a mathematical tool for selecting and weighting assets subject to constraints. It identifies three possible objectives: maximizing expected return, minimizing risk, or balancing the two.…

Portfeļa veidošanaRiska pārvaldība
BigQuant

The document addresses a conflict between stop-loss logic and a machine-learning strategy's next-day buy list. A stock may be sold when it reaches a trailing stop, then selected again by the model on the following trading day. The proposed fix is to track…

MašīnmācīšanāsRiska pārvaldībaAkcijas
BigQuant

This strategy note selects Chinese convertible bonds using low price, low conversion premium, and low remaining issue balance. It ranks eligible bonds by the sum of price and conversion premium, favors the lowest scores, and describes equal-weight holdings…

Ķīnas tirgiPozīcijas apjoma noteikšanaRiska pārvaldība
BigQuant

This short research note discusses how machine learning might classify stock price patterns. It uses a triple-bottom formation to show why chart labels can be ambiguous: after a decline and consolidation with three lows, an upward break may confirm a…

AkcijasMašīnmācīšanāsTehniskie indikatoriVēsturisko datu pārbaude
BigQuant

This document describes a Chinese equity strategy research approach that uses supervised neural networks to generate many weak alpha factors from a set of input factors. It proposes transforming those outputs into low-correlation components, then weighting…

AkcijasFaktoru ieguldīšanaMašīnmācīšanāsPortfeļa veidošana
BigQuant

This document describes a chart indicator that draws a price channel from the high and low of a candle on a selected higher timeframe. The user chooses the timeframe, and the indicator uses that period’s candle range as the channel boundaries on the chart.…

Tehniskie indikatoriCenas izrāviens
BigQuant

The author outlines an index-enhancement approach for Chinese large-cap and blue-chip equities. First, a human-selected universe emphasizes historically strong companies and stocks that held up against the broad market during declines. A machine-learning…

AkcijasĶīnas tirgiMašīnmācīšanāsSekošana tendencei
BigQuant

The response clarifies what a factor analysis does in the context of evaluating five candidate factors. It says the analysis is run on each factor individually, rather than testing whether a portfolio or combination of all five factors is effective. This is…

Faktoru ieguldīšanaStatistika
BigQuant

This forum post asks how a factor dashboard calculates win rates for low and high factor quantiles and for a long–short portfolio. It contrasts two possible interpretations: counting individual stocks with positive returns, or counting rebalancing periods in…

Faktoru ieguldīšanaStatistikaPortfeļa veidošana
BigQuant

The document presents a stock-selection design that first ranks Chinese market sectors using a weighted combination of price momentum, money flows, and recent policy-related news. It then scores sub-sectors using reported net-profit growth and price…

Ķīnas tirgiAkcijasCenas impulssTehniskie indikatori
BigQuant

This report summary compares cross-sectional, market-neutral commodity futures strategies based on inventory deviation and historical momentum. The inventory signal favors commodities with inventories below their own trend and shorts those above trend. It is…

Nākotnes līgumiIzejvielasCenas impulssSekošana tendencei
BigQuant

This overview outlines a quantitative workflow: collect and clean data, develop a strategy, manage risk, backtest on historical data, and automate execution. It then sketches strategies for Chinese equities and futures, including Turtle-style breakouts,…

AkcijasNākotnes līgumiPāru tirdzniecībaTehniskie indikatori
BigQuant

This forum post asks about a “Golden Cross Winner” ETF strategy that uses an unusual MACD-style calculation. The author questions why the signal line, DEA, is calculated as a 26-period exponential moving average of DIF instead of the commonly cited 9-period…

AkcijasTehniskie indikatoriVēsturisko datu pārbaudeStatistika
BigQuant

This introductory guide outlines a retail trader’s path into quantitative trading. It describes using market data and mathematical models to generate decisions, learning market concepts and a programming language, building models from historical data, and…

Vēsturisko datu pārbaudeRiska pārvaldībaPozīcijas apjoma noteikšanaPortfeļa veidošana
BigQuant

The article argues that a factor can be useful even when its strongest information lies in identifying poor-performing stocks. It describes ranking stocks into daily groups by factor value and interpreting unusually strong performance in the worst-ranked…

AkcijasAugstas frekvences tirdzniecībaFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

This study summary treats a company’s choice to capitalize or expense research and development costs as a signal about the expected future benefits of its projects. Because accounting criteria leave room for discretion, capitalization can also be used to…

AkcijasUz notikumiem balstīta tirdzniecībaĶīnas tirgiFaktoru ieguldīšana
BigQuant

This overview explains decision trees as nonparametric models that divide observations through sequential feature rules. Each path defines a group, and a leaf assigns a prediction based on the labels in that group. The same feature can be used at multiple…

MašīnmācīšanāsStatistika