Lumaktaw papunta sa nilalaman

Library ng kaalaman

Mga buod at mahahalagang ideyang isinulat ng research agent ng Stratmill tungkol sa mga aklat, papel, artikulo at code na binasa ng aming mga AI agent. May link sa orihinal sa bawat pahina.

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

Maghanap sa library

1,124 na dokumento

Machine Learning for Trading

This case study constructs features for comparing variance risk premiums across S&P 500 stocks using 30-day at-the-money straddles and underlying price data. It measures implied volatility against realized volatility at several horizons, adds option-market…

Mga optionMga equityVolatilityBacktesting
Machine Learning for Trading

This case study explains how to generate predictions for a holdout period after model and strategy choices have been made on validation data. It resolves the previously selected configuration, reconstructs its training specification, and fits it again using…

Mga equityMachine learningBacktestingEstadistika
Machine Learning for Trading

This notebook builds an LSTM allocator that maps recent ETF return and volatility features directly to long-only portfolio weights. A softmax output keeps weights nonnegative and fully invested, while a differentiable Sharpe-ratio objective trains the…

Machine learningPagbuo ng portfolioBacktestingPamamahala ng panganib
Machine Learning for Trading

This notebook introduces EdgarTools for exploring SEC filings by company and filing type. It demonstrates looking up issuers using stable CIK identifiers, retrieving annual and quarterly reports, extracting XBRL financial statements, and inspecting insider…

Mga equityMga merkado sa USBacktestingEstadistika
Machine Learning for Trading

This notebook applies principal component analysis to changes in eight Treasury constant-maturity yields, spanning one to thirty years. It removes forward-filled calendar rows with no yield changes and standardizes the remaining observations before PCA, so…

Fixed incomeEstadistikaPamamahala ng panganibPagbuo ng portfolio
Machine Learning for Trading

This notebook describes an LSTM sequence model for predicting stock returns from ordered windows of recent features. Each example uses 60 consecutive sessions for one stock; windows that cross listing gaps, halts, or other interruptions are excluded so that…

Mga equityMachine learningEstadistikaMga merkado sa US
Machine Learning for Trading

This analysis checks whether daily option data can support a weekly strategy that sells at-the-money straddles on S&P 500 constituents, delta hedges shares, and holds contracts to expiration. It explains how calls and puts form a straddle, how implied and…

Mga optionVolatilityPagpapatupad ng tradeBacktesting
Machine Learning for Trading

This reference summarizes listed contract months for 35 CME futures products across equity indexes, Treasuries, energy, metals, currencies, interest rates, agriculture, livestock, and crypto. It explains the exchange’s month-code system and distinguishes…

FuturesMicrostructure ng merkadoBacktestingMga kalakal
Machine Learning for Trading

This notebook synthesizes registered validation results for five latent-factor estimators—PCA, IPCA, CAE, SDF, and SAE—across nine case studies. It first reports which estimators have results in each panel, then identifies the highest mean daily Spearman…

Pamumuhunan batay sa mga factorMachine learningEstadistikaMga equity
Machine Learning for Trading

This document describes a pipeline for downloading official Binance USD-M perpetual funding records, normalizing them, and caching them in a columnar file. Monthly archives are fetched concurrently for the requested symbols and date range. The records are…

CryptoPerpetual futuresPagpepresyo ng derivativesBacktesting
Machine Learning for Trading

This notebook applies TabM, a weight-sharing neural ensemble, to a US equities panel represented as one feature row per stock and session. A shared two-layer backbone feeds multiple members, each with its own scaling vector and output layer; averaging their…

Mga equityMachine learningBacktestingEstadistika
Machine Learning for Trading

This analysis selects one configuration from a frozen pool of crypto perpetual-futures candidates spanning four prediction labels and multiple strategy stages. It chooses the highest validation Sharpe and treats label, split, and execution details as part of…

CryptoPerpetual futuresEstadistikaBacktesting
Machine Learning for Trading

This notebook defines forward-return targets for ranking US stocks and explains how to make their horizons correspond to actual trading sessions. It uses split- and dividend-adjusted prices for returns, but uses the contemporaneous printed close and dollar…

Mga equityMomentumEstadistikaBacktesting
Machine Learning for Trading

This pipeline constructs financial features for an ETF deployment workflow from OHLCV prices and a yield curve. It derives returns and risk-adjusted returns across multiple lookback periods, momentum acceleration and volatility ratios, then adds common…

Mga equityMomentumVolatilityMga teknikal na indicator
Machine Learning for Trading

This script gathers institutional holdings from SEC 13F filings in two ways: it can retrieve filings for a curated set of managers or download the SEC’s quarterly bulk files. Both paths normalize holdings into a shared schema, with the bulk path designed for…

Mga equityEstadistikaPagbuo ng portfolio
Machine Learning for Trading

This notebook applies principal component analysis to a panel of US stock returns to represent broad shared movements with a smaller set of factors. Each factor is a direction of common variation, and each stock’s loading describes its exposure to that…

Mga equityEstadistikaMachine learningPamumuhunan batay sa mga factor
Machine Learning for Trading

This notebook compares gradient boosting configurations for crypto perpetual futures using features built around the premium of perpetual contracts over spot. It varies tree capacity and loss function, including squared, absolute, and Huber losses, and…

CryptoPerpetual futuresMachine learningBacktesting
Machine Learning for Trading

This notebook explains how to extract insider transactions from raw SEC Form 4 XML for quantitative equity research. It uses an XML parser to keep each trade’s code, date, share count, price, and direction attached to its transaction block, while separately…

Mga equityNakabatay sa mga kaganapanSentimyentoEstadistika
Machine Learning for Trading

This notebook uses double machine learning to estimate whether futures carry predicts subsequent returns independently of volatility, momentum, and cross-sectional carry rank. It residualizes both carry and returns against these confounders with flexible…

FuturesCarry tradeMachine learningEstadistika
Machine Learning for Trading

This notebook develops model-based features for crypto perpetual futures: per-asset conditional volatility forecasts from GJR-GARCH and a market-wide stressed-regime probability from a two-state Gaussian hidden Markov model fitted to funding settlements.…

CryptoPerpetual futuresVolatilityMachine learning
Machine Learning for Trading

This case study lays out a research pipeline for crypto perpetual futures, treating funding payments exchanged between long and short positions at regular settlements as a potential return source. It describes data and model stages from label construction…

CryptoPerpetual futuresFuturesMachine learning
Machine Learning for Trading

This analysis compares feature triage results across nine trading case studies and asks whether features that pass screening predict stronger strategies. Its screening combines Benjamini–Hochberg false-discovery control with a second route based on a case…

EstadistikaMachine learningBacktesting
Machine Learning for Trading

This notebook describes DeePM, an end-to-end ETF portfolio policy designed to improve performance across varying market conditions. Its components include volatility-normalized return and trend features, an LSTM-based model, variable selection, conditioning…

Maraming assetPagbuo ng portfolioMachine learningPamamahala ng panganib
Machine Learning for Trading

This case study applies causal estimation to ETF momentum and asks whether its effect on forward returns varies with market volatility. It uses a continuous momentum treatment, a 21-day forward-return outcome, volatility and yield-curve controls, and a…

Mga equityMga merkado sa USMomentumMachine learning