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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
Quantpedia
Dokumentu skaits: 86
TqSdk
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
Quantopian lekcijas
Dokumentu skaits: 45
Binance API docs
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: 7,910

Strategy library

This document describes a polling tool for comparing prices from two exchanges, including spot and futures markets. Users can choose each market’s quote currency, futures contract and leverage settings, and whether to compare best ask, last price, or best…

Vairāku aktīvu tirdzniecībaNākotnes līgumiTūlītējo darījumu tirgiArbitrāža
Strategy library

This simple long-only strategy aims to buy a short-term price dip and capture a possible rebound. It subtracts a multiple of 20-bar ATR from the low, smooths that adjusted series with a simple moving average, and enters when the market low crosses below the…

Atgriešanās pie vidējās vērtībasTehniskie indikatoriRiska pārvaldībaVēsturisko datu pārbaude
Strategy library

This short-term system looks for breakout conditions in a one-minute MACD histogram, using Bollinger Bands around the histogram as trigger levels. Long entries require the histogram to fall below its lower band, an RSI reading above the stated threshold, and…

KriptoaktīviNākotnes līgumiCenas izrāviensTehniskie indikatori
Strategy library

This strategy uses Keltner Channel levels to place opposing stop entries on five-minute bars. When flat, it submits a buy stop at the upper band and a sell stop at the lower band as an OCO-style pair; when one side fills, it cancels the opposing order.…

Tehniskie indikatoriCenas izrāviensSekošana tendenceiRiska pārvaldība
Strategy library

This TradingView paper strategy describes a long-only Turtle-style approach for daily Bitcoin prices on Bitstamp. It enters when the close rises above the previous 20 days’ high, provided price is above a 50-day simple moving average. An initial stop is set…

KriptoaktīviSekošana tendenceiCenas izrāviensTehniskie indikatori
Strategy library

This QuantConnect example demonstrates how a custom buying power model can change order sizing and buying-power checks in a backtest. It applies the model to hourly SPY data, rounds the maximum order quantity down to a multiple of 100 shares, and then…

AkcijasVēsturisko datu pārbaudePozīcijas apjoma noteikšanaRiska pārvaldība
Strategy library

This strategy uses fast and slow zero-lag least-squares moving averages (ZLSMA) to describe market direction, then uses MACD behavior to time entries. The accompanying explanation proposes taking trades when the moving-average trend and a MACD crossover…

KriptoaktīviNākotnes līgumiSekošana tendenceiTehniskie indikatori
Strategy library

This strategy combines the Stochastic Momentum Index (SMI) and the Relative Strength Index (RSI) to generate long and short signals. An oversold SMI or low RSI can support a long entry, while the corresponding overbought conditions support a short. In…

KriptoaktīviNākotnes līgumiTehniskie indikatoriVēsturisko datu pārbaude
Strategy library

This strategy draws on Elder Ray's bull and bear power concept, measuring the day's high and low relative to an exponential moving average used as a value reference. The article describes using these differences to represent buying and selling pressure, then…

KriptoaktīviNākotnes līgumiTehniskie indikatoriCenas impulss
Strategy library

This trend-following approach pairs a short-period EMA with a longer-period EMA and checks the crossover against RSI momentum. An upward crossover generates a long signal only when RSI exceeds a configurable level; a downward crossover generates a short…

KriptoaktīviNākotnes līgumiSekošana tendenceiCenas impulss
Strategy library

This combined strategy requires agreement between a stochastic-based reversal signal and a two-period exponential moving average signal. The reversal component evaluates recent closing-price sequences alongside fast and slow stochastic values relative to a…

KriptoaktīviNākotnes līgumiAtgriešanās pie vidējās vērtībasSekošana tendencei
Strategy library

This strategy uses a moving-average center line and standard-deviation bands to identify price breakouts. The basis can use several moving-average types, while the band width is set by a standard-deviation multiplier. A close crossing above the upper band…

KriptoaktīviNākotnes līgumiCenas izrāviensSvārstīgums
Strategy library

This strategy uses Average True Range to form adaptive long and short stop lines around the midpoint of each bar. A direction state changes when price crosses the prior opposing stop, providing trend-reversal signals. After entry, the described trailing…

KriptoaktīviNākotnes līgumiSekošana tendenceiSvārstīgums
Strategy library

This document describes a crossover approach using a linear regression line, a moving average of that line, and an exponential moving average of price. The stated method treats an EMA crossing the averaged regression line as an entry or exit signal, and…

Tehniskie indikatoriSekošana tendenceiStatistikaRiska pārvaldība
Strategy library

This strategy combines prior-day price levels with moving average signals. It treats a move beyond the previous day's high or low as a breakout, then uses a fast 10-period and slow 30-period moving average crossover to confirm direction. The described…

KriptoaktīviNākotnes līgumiCenas izrāviensSekošana tendencei
Strategy library

This strategy applies the Fisher Transform to normalized midpoint prices over a lookback window. It smooths the normalized value, constrains it near its allowable bounds, then transforms it; the direction of change in the resulting indicator determines…

KriptoaktīviNākotnes līgumiAtgriešanās pie vidējās vērtībasTehniskie indikatori
Strategy library

This strategy measures momentum as the difference between the current close and the close 18 periods earlier, then measures the one-period change in that momentum. Positive values for both measures indicate a long bias; negative values for both indicate a…

KriptoaktīviNākotnes līgumiSekošana tendenceiCenas impulss
Strategy library

This strategy combines MACD crossover signals with a 200-day simple moving average as a broad trend filter. It describes buying when the MACD line is above its signal line, remains below zero, and price is above the moving average. It describes short entries…

KriptoaktīviNākotnes līgumiSekošana tendenceiCenas impulss
Strategy library

This strategy uses On-Balance Volume to identify an upward trend, then builds a long position through repeated entries. A signal occurs when OBV, centered by its moving average, crosses above zero while the fast EMA is above the slow EMA. The source allows…

KriptoaktīviNākotnes līgumiSekošana tendenceiTehniskie indikatori
Strategy library

This trend-following strategy applies a Fisher Transform to the midpoint of each bar, normalized over a configurable lookback using recent highs and lows. The calculation is smoothed and bounded before transformation. It opens a long position when the…

KriptoaktīviNākotnes līgumiSekošana tendenceiTehniskie indikatori
Strategy library

This educational moving-average strategy uses separate EMA crossover settings for entries and exits. It opens a long position after the entry crossover persists for a configured observation period, sizing the purchase as a fraction of available cash. While…

KriptoaktīviTūlītējo darījumu tirgiSekošana tendenceiTehniskie indikatori
Strategy library

This strategy combines Bollinger Bands and Keltner Channels to identify volatility compression and subsequent breakouts. The visible script configures both indicators with 20-period lengths, uses standard deviation for the Bollinger Bands and ATR for the…

Cenas izrāviensSvārstīgumsTehniskie indikatoriRiska pārvaldība
Strategy library

This market-making bot adjusts its orders according to the relative value of its coin inventory and cash balance. It values inventory using prices offset from the best ask and bid by a configured percentage spread. When coin value is high relative to cash,…

Tirgus veidošanaRīkojumu izpildeTirgus mikrostruktūraKriptoaktīvi
Strategy library

This Bitcoin futures strategy uses 9-period and 21-period exponential moving averages to signal trend changes. It enters long when the shorter average crosses above the longer one and short on the reverse crossover. The stop is placed at the recent…

KriptoaktīviNākotnes līgumiSekošana tendenceiTehniskie indikatori