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 notebook evaluates NLinear, a simple sequence model that subtracts the latest observed level from a lookback window and maps the resulting sequence to a forecast with a linear transformation. It fits the ETF model population on walk-forward folds and…

Mga equityMachine learningEstadistikaBacktesting
Machine Learning for Trading

This case study fits linear models to predict returns and direction in crypto perpetual futures. Its feature matrix is dominated by variations of the perpetual premium, the gap between the contract and spot price that drives funding payments. It contrasts…

CryptoPerpetual futuresMachine learningEstadistika
Machine Learning for Trading

This notebook presents a conditional autoencoder for equity returns in which a neural network maps stock characteristics to nonlinear factor loadings, while another network extracts contemporaneous latent factors from characteristic-managed portfolio…

Mga equityMachine learningPamumuhunan batay sa mga factorEstadistika
Machine Learning for Trading

This notebook measures how transaction costs affect a fixed CME futures strategy configuration. It selects the reported configuration through a shared validation-stage process, carries its risk overlay into the cost runs, and applies a declared grid of…

FuturesMga kalakalBacktestingPagpapatupad ng trade
Machine Learning for Trading

This notebook explains how to rebuild a limit order book from DataBento market-by-order messages for a single NASDAQ symbol and trading day. It models each order, aggregates orders into price levels, and maintains separate bid and ask sides. Correct message…

Mga equityMicrostructure ng merkadoPagpapatupad ng tradeEstadistika
Machine Learning for Trading

This notebook compares ways to hedge a short European call when rebalancing is discrete and trades incur proportional costs. It defines self-financing terminal P&L, then trains a neural hedger to minimize expected shortfall under Heston simulated prices. The…

Mga optionMachine learningPamamahala ng panganibPagpapatupad ng trade
Machine Learning for Trading

This notebook compares six long-only ETF allocation methods designed to reduce reliance on unstable estimates. It applies Ledoit-Wolf covariance shrinkage to estimators that use covariance, and contrasts mean-variance maximum Sharpe with minimum variance,…

Maraming assetMga equityFixed incomePagbuo ng portfolio
Machine Learning for Trading

This notebook compares single-objective hyperparameter tuning with a multiobjective search for LightGBM prediction models. The baseline maximizes validation information coefficient (IC). The NSGA-II search instead maximizes IC while minimizing normalized…

Machine learningEstadistikaBacktestingPagpapatupad ng trade
Machine Learning for Trading

This chapter synthesizes nine case studies that take machine-learning signals through portfolio construction, trading costs, risk overlays, and frozen holdout evaluation. It treats each case study’s progression as the unit of analysis instead of ranking…

Machine learningMga equityBacktestingPagbuo ng portfolio
Machine Learning for Trading

This assessment traces a single US equities strategy from a frozen validation backtest set to its holdout evaluation. It applies a deterministic rule: choose the candidate with the highest validation Sharpe, breaking ties by backtest hash. Registry records…

Mga equityBacktestingEstadistikaPamamahala ng panganib
Machine Learning for Trading

This notebook runs a selected NASDAQ-100 microstructure configuration on its registered holdout predictions. The model, allocator, concentration, rebalance schedule, risk overlay, and cost assumptions are inherited from earlier work and applied unchanged;…

Mga equityMga merkado sa USBacktestingPamamahala ng panganib
Machine Learning for Trading

This notebook compares ways to size positions in a US equities panel while holding the model, checkpoint, rebalance dates, and selected stocks fixed. Prediction-based methods scale capital by forecast magnitude or interval uncertainty; inverse volatility and…

Mga equityMga merkado sa USPagbuo ng portfolioPagtatakda ng laki ng posisyon
Machine Learning for Trading

This notebook explains how to select one strategy from a fixed set of US equity backtests and assess the resulting strategy on a separate holdout period. It validates that candidates share the required data and protocol identities, then ranks them by…

Mga equityBacktestingPamamahala ng panganibEstadistika
Machine Learning for Trading

This notebook demonstrates an operational workflow for connecting a shared backtest and live strategy to an Interactive Brokers paper-trading session. It checks account identity and state, requests historical bars to initialize indicators, subscribes to…

Mga equityMomentumPagpapatupad ng tradePamamahala ng panganib
Machine Learning for Trading

This notebook compares three linear time-series models, a Transformer encoder, and parameter-free forecasts on daily SPY returns. The linear approaches map a historical window to a multi-day forecast, with variants that separate a smooth component from its…

Mga equityMachine learningEstadistikaBacktesting
Machine Learning for Trading

This notebook presents a multi-round forecasting debate between bull and bear roles. Each side argues for a higher or lower probability of an event, sees the other side’s prior argument in later rounds, and reports a probability and supporting evidence. The…

Machine learningEstadistikaSentimyentoPamamahala ng panganib
Machine Learning for Trading

This notebook examines whether gradient-boosted trees can find nonlinear relationships in NASDAQ-100 microstructure features that a linear model may miss. It focuses on the possibility that order-flow imbalance predicts returns differently depending on the…

Mga equityMachine learningMicrostructure ng merkadoEstadistika
Machine Learning for Trading

This notebook explains an operator-style research agent for iterating on quantitative case studies. Instead of limiting the model to predefined forecasting actions, it gives it general tools for files, shell commands, registry queries, and data inspection.…

Machine learningBacktestingEstadistikaPamamahala ng panganib
Machine Learning for Trading

This feasibility analysis checks whether a daily long-short equity ranking strategy can be researched with the available US stock panel. It examines point-in-time universe construction using price and trailing turnover thresholds, compares proportional…

Mga equityMga merkado sa USBacktestingPagpapatupad ng trade
Machine Learning for Trading

This notebook refits the configuration selected by earlier validation stages using pre-2021 history, then publishes predictions for a 2021 holdout. It retrieves the chosen configuration from a recorded candidate set or applies the same ranking rule when that…

Mga equityMga optionMachine learningBacktesting
Machine Learning for Trading

This analysis introduces option-chain structure and examines a 2020 slice of S&P 500 options for eight underlyings. It explains moneyness, intrinsic and time value, Greeks, implied volatility, and the information represented by volatility skew and term…

Mga optionVolatilityPagpepresyo ng derivativesMicrostructure ng merkado
Machine Learning for Trading

This notebook implements an ESG headline workflow that selects news with keywords, assigns each selected headline to an environmental, social, or governance category, and scores sampled headlines with FinBERT sentiment. It measures the selected pool’s…

Machine learningSentimyentoEstadistika
Machine Learning for Trading

This notebook audits an annual-report corpus before it is indexed for financial research. It measures the delay between a fiscal period end and the public filing date, showing why point-in-time applications must use the publication date. It also identifies…

Mga equityMachine learningPagpapatupad ng tradeBacktesting
Machine Learning for Trading

This notebook screens financial and model-based features for their relationship with the next eight-hour return of crypto perpetual contracts. For each settlement, it computes cross-sectional Spearman correlations across eligible contracts, then summarizes…

CryptoPerpetual futuresMachine learningEstadistika