Praleisti ir pereiti prie turinio

Žinių biblioteka

Stratmill tyrimų agento parengtos knygų, straipsnių, mokslinių darbų ir kodo, kuriuos skaito mūsų DI agentai, santraukos ir pagrindinės mintys. Kiekviename puslapyje pateikiama nuoroda į originalą.

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

Ieškoti bibliotekoje

3,481 dokumentų

BigQuant

This overview surveys six ICLR 2022 studies: periodic time-series forecasting, model-based policy optimization, disentangled representations, Stein-based sampling, deployment-efficient reinforcement learning, and training with privileged observations. The…

Mašininis mokymasisStatistikaImpulsasIstorinis testavimas
BigQuant

This article explains why selecting useful input features matters in predictive modeling. Irrelevant variables can add training time, contribute to overfitting, and make it harder for a model to generalize. Feature selection is presented as a way to reduce…

Mašininis mokymasisStatistika
BigQuant

This forum post responds to a question about selling after a 10% gain or cutting a position after a 10% loss. The included example checks open equity positions against current prices, retrieves the highest price since purchase, and exits when price falls 7%…

AkcijosRizikos valdymasPavedimų vykdymas
BigQuant

This article describes a daily process for building a watchlist of strong stocks. After the close, rank shares by traded value and keep the top 30. From that group, look for stocks rising more than 3% on increased volume, giving extra attention to volume…

AkcijosImpulsasPramušimasTechniniai rodikliai
BigQuant

This Chinese-language article introduces a workflow for building custom stock-selection strategies on the older BigQuant platform. It contrasts platform-generated AI strategies, which learn from selected factors but may be difficult to interpret or tune,…

AkcijosInvestavimas pagal veiksniusIstorinis testavimasMašininis mokymasis
BigQuant

This study compares ways to hedge stock holdings, motivated by investors who hold equities as a base for IPO subscriptions and want to reduce exposure to price swings. It measures hedge costs using annualized futures discounts and compares those costs across…

Ateities sandoriaiPasirinkimo sandoriaiAkcijosRizikos valdymas
BigQuant

This article explains how to assess a systematic futures model through test design and several complementary performance measures. It recommends testing across multiple instruments and long historical periods, and including commissions and slippage. The…

Ateities sandoriaiIstorinis testavimasRizikos valdymasPavedimų vykdymas
BigQuant

This article proposes studying Chinese A-share stocks during days when the broader market falls sharply. It suggests identifying historical selloff days, then examining two setups: stocks that close at the daily upper price limit despite the market decline,…

AkcijosKinijos rinkosIstorinis testavimasTechniniai rodikliai
BigQuant

This document summarizes two external research papers. The first concerns allocating capital among private fund strategies within a fund-of-funds portfolio, using multi-objective linear programming to derive allocation weights. The second examines the ratio…

Portfelio konstravimasPasirinkimo sandoriaiRinkos mikrostruktūraStatistika
BigQuant

This article explains random forests and decision trees, then applies a random forest regressor to short-horizon Chinese stock selection. It describes bootstrap sampling, random feature selection, averaging tree predictions, tree pruning, regression split…

AkcijosMašininis mokymasisInvestavimas pagal veiksniusIstorinis testavimas
BigQuant

The document describes why quantitative investors use machine learning to analyze large datasets, forecast market direction, and select portfolios. It highlights the ability of these methods to represent nonlinear relationships and process data efficiently,…

Mašininis mokymasisIstorinis testavimasStatistika
BigQuant

This overview presents basic ways to assess broad equity-market conditions and limit portfolio exposure during potential declines. It describes moving-average crossovers as timing signals, with a shorter average crossing above a longer one treated as bullish…

AkcijosTechniniai rodikliaiRizikos valdymasPortfelio konstravimas
BigQuant

This opinion piece presents stock trading as a possible independent career, emphasizing schedule autonomy, reduced dependence on an employer, access to shares in public companies, and the ability to shift attention among sectors. It argues that market…

AkcijosKinijos rinkosRizikos valdymas
BigQuant

This commentary argues that oversight of quantitative trading should focus on predictable, transparent market rules and enforcement of misconduct, rather than suppressing algorithmic methods as a category. It frames the regulatory challenge as balancing…

Kinijos rinkosRinkos mikrostruktūraDidelio dažnio prekybaPavedimų vykdymas
BigQuant

Risk parity allocates portfolio weights so that assets contribute more evenly to total portfolio risk, rather than assigning capital according to expected returns or equal dollar amounts. The document outlines a workflow: estimate asset volatilities and…

Portfelio konstravimasRizikos valdymasKelių turto klasiųStatistika
BigQuant

This review surveys three directions in factor investing: refining established factor methods, incorporating new data and models, and using factors as a basis for asset allocation. It describes improving value signals with multiple valuation measures,…

Investavimas pagal veiksniusPortfelio konstravimasMašininis mokymasisRizikos valdymas
BigQuant

The document addresses a screening condition that combines a stock closing above a rolling maximum with a recent limit-up requirement. The questioner reports that the combined filters return no candidates even though individual conditions seem to identify…

Kinijos rinkosAkcijosPramušimasTechniniai rodikliai
BigQuant

The article introduces trend following as buying when prices rise and selling when they weaken, then reviews five indicators that may inform such decisions: moving averages, Bollinger Bands, MACD, RSI, and On-Balance Volume. It describes using price relative…

AkcijosPrekyba pagal tendencijąTechniniai rodikliaiImpulsas
BigQuant

The report argues that ranking fund managers can reduce redundant information when one manager oversees several similar funds. It proposes tracking manager style across market capitalization, value versus growth, industry concentration, individual-stock…

AkcijosKinijos rinkosInvestavimas pagal veiksniusPortfelio konstravimas
BigQuant

This research summary presents cash-flow duration as a framework for understanding why equity characteristics such as value, profitability, investment, low beta, and dividend payout are associated with returns. Duration measures the timing of a company’s…

AkcijosInvestavimas pagal veiksniusPortfelio konstravimasStatistika
BigQuant

This brief review interprets the CSI 300’s movements through valuation bands tied to an assumed earnings growth rate. Using a 12-times valuation assumption and projected 2018 net profit growth, it describes an estimated index range and treats the July move…

AkcijosKinijos rinkosStatistika
BigQuant

This article presents a multi-asset allocation framework that combines traditional asset selection with allocation to systematic factors. It maps macroeconomic variables and style factors to asset classes, estimates exposures with time-series regressions,…

Kelių turto klasiųInvestavimas pagal veiksniusPortfelio konstravimasIstorinis testavimas
BigQuant

This research note discusses how to turn equity alpha signals into portfolio forecasts and combine multiple factors. It suggests converting factor z-scores into expected returns using average results from repeated cross-sectional regressions, and favors…

AkcijosInvestavimas pagal veiksniusStatistikaPortfelio konstravimas
BigQuant

This research summary describes a machine-learning approach to predicting very short-term price changes from futures order-book data. It proposes using support vector machines with features such as best bid and ask prices and sizes, order-book depth, slope…

Ateities sandoriaiMašininis mokymasisDidelio dažnio prekybaRinkos mikrostruktūra