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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 BigQuant example shows how a China stock universe selector can be connected to a trading engine that reads a daily signal table. The engine filters rows to the current date, closes existing positions once the elapsed time since their last sale reaches…

Ķīnas tirgiAkcijasRīkojumu izpildePozīcijas apjoma noteikšana
BigQuant

This report summary examines whether Chinese equity index returns and industry performance vary by lunar calendar month. It analyzes eight major mainland indices using historical monthly average returns and regression tests with autocorrelation-consistent…

AkcijasStatistikaĶīnas tirgiUz notikumiem balstīta tirdzniecība
BigQuant

This weekly market note links macro conditions, Bitcoin exchange-traded fund flows, spot momentum, and options positioning. It reports that diminishing outflows from one fund and inflows to other funds accompanied a rise in Bitcoin, and discusses the…

KriptoaktīviOpcijasSvārstīgumsCenas impulss
BigQuant

This study tests whether machine learning can explain stock returns left unexplained by a conventional linear equity factor model. It uses 22 style factor exposures to predict standardized stock specific returns, then evaluates boosted trees, random forests,…

AkcijasFaktoru ieguldīšanaMašīnmācīšanāsStatistika
BigQuant

This research summary examines why firms repurchase shares when short sellers increase their positions. It contrasts managerial myopia, in which buybacks protect near-term prices or earnings at a cost to long-term owners, with a private-information…

AkcijasUz notikumiem balstīta tirdzniecībaStatistikaASV tirgi
BigQuant

This discussion explains why a stock-selection template that lists close divided by the adjustment factor may not produce that calculated feature in its results. The reported output shows the two inputs as separate columns, suggesting the expression was not…

AkcijasTehniskie indikatori
BigQuant

This discussion explains how to calculate the number of consecutive days since a moving average golden cross using BigQuant’s DAI functions. The suggested approach counts consecutive observations for which the golden-cross condition is false, including the…

AkcijasTehniskie indikatori
BigQuant

The document outlines a rule-based strategy for the Tianhong ChiNext ETF, using recent closing prices to create a reference price and comparing the current price and volume with that reference. It describes buying after a large decline and selling after a…

Ķīnas tirgiAtgriešanās pie vidējās vērtībasTehniskie indikatoriRīkojumu izpilde
BigQuant

This retrospective contrasts rule-based stock selection with machine-learning ranking and describes backtesting as a way to evaluate a strategy on historical market data. Its central caution is that a strong fit on a small sample can reflect an irrelevant…

Vēsturisko datu pārbaudeMašīnmācīšanāsRīkojumu izpildeRiska pārvaldība
BigQuant

This research report examines market timing with breadth measures built from the constituents of the CSI 300. A diffusion indicator estimates the share of index stocks showing positive trends, offering a view of how broadly market direction is shared. The…

AkcijasĶīnas tirgiTehniskie indikatoriVēsturisko datu pārbaude
BigQuant

This assignment turns a discretionary idea—finding concentrated holdings in recent hot industries—into a proposed equity research process. It suggests first identifying strong sectors with a sector momentum factor, then ranking stocks within those sectors…

AkcijasCenas impulssMašīnmācīšanāsVēsturisko datu pārbaude
BigQuant

The document describes a framework for evaluating equity factors and combining selected factors into a portfolio. It estimates factor returns with periodic cross-sectional robust regressions, measures the relationship between factor exposures and subsequent…

AkcijasFaktoru ieguldīšanaStatistikaVēsturisko datu pārbaude
BigQuant

This Chinese equities strategy looks for stocks with a bullish moving-average stack: the five-day average exceeds the ten-day, then the twenty-day, forty-day, and one-hundred-twenty-day averages. It adds a pullback condition: the day’s low must fall below…

Ķīnas tirgiAkcijasSekošana tendenceiTehniskie indikatori
BigQuant

The document discusses how to estimate hedging costs for Chinese equity index futures. It argues that raw futures premiums or discounts need adjustment for time to expiry, convergence, and expected dividends. A dividend model and quadratic equation are…

Nākotnes līgumiĶīnas tirgiRiska pārvaldībaStatistika
BigQuant

This brief troubleshooting exchange addresses a KeyError in a trading strategy. The suggested first step is to inspect the value represented by the variable `s`, since the exception may arise when that value is used to look up a position that is not present…

Rīkojumu izpilde
BigQuant

This overview explains how deep learning models can be assembled from input, intermediate, and output layers in a visual strategy-building platform. It surveys layer families including convolution, pooling, recurrent networks, embeddings, noise and dropout,…

MašīnmācīšanāsStatistikaVēsturisko datu pārbaude
BigQuant

The document contrasts selecting stocks by relative rank with selecting them by an absolute model score. A ranking method can always choose the highest-ranked names in a universe, even when their scores are weak. The proposed alternative sets a minimum score…

AkcijasMašīnmācīšanāsFaktoru ieguldīšanaVēsturisko datu pārbaude
BigQuant

This short indicator description covers a chart tool that displays four semaphore-style signals based on money flow index (MFI) oscillators with different periods. It presents the signals as trend cues when oscillator readings enter user-defined overbought…

Tehniskie indikatoriCenas impulssValūtu tirgus
BigQuant

This summary describes an analysis of actively managed equity funds and funds with substantial equity exposure. Its stated selection process combines historical return data with portfolio holdings, sector exposure, and risk considerations to identify funds…

AkcijasFaktoru ieguldīšanaPortfeļa veidošanaRiska pārvaldība
BigQuant

This research review examines whether predictable stock returns in particular months reflect changing risk or temporary mispricing. Its central test is seasonal reversal: if a stock earns unusually high returns in one calendar period because demand…

AkcijasStatistikaFaktoru ieguldīšanaCenas impulss
BigQuant

This forum question concerns modifying a portfolio sell routine so that, when the stock allocation exceeds 60% of total portfolio value, the excess exposure is reduced by selling holdings from the bottom of a ranking. The supplied code builds a set of…

AkcijasPortfeļa veidošanaPozīcijas apjoma noteikšanaRīkojumu izpilde
BigQuant

The article explains robust portfolio optimization as a way to reduce the effect of errors in expected-return forecasts. Rather than optimize only for a single set of estimates, the methods consider adverse plausible cases and seek a portfolio that performs…

Portfeļa veidošanaRiska pārvaldībaPozīcijas apjoma noteikšanaVēsturisko datu pārbaude
BigQuant

This study examines whether investors chasing Morningstar mutual fund ratings can move stock prices through fund flows. Before Morningstar’s June 2002 methodology change, ratings were closely tied to broad fund performance and therefore favored some…

AkcijasASV tirgiUz notikumiem balstīta tirdzniecībaCenas impulss
BigQuant

The article discusses data integration challenges when developing strategies across US equities and forex. It highlights differences in update speed, price conventions, and data formats, arguing that timestamp misalignment and latency can create gaps between…

Vairāku aktīvu tirdzniecībaASV tirgiValūtu tirgusRīkojumu izpilde