Μετάβαση στο περιεχόμενο

Βιβλιοθήκη γνώσης

Συνόψεις και κύριες ιδέες από βιβλία, μελέτες, άρθρα και κώδικα που διαβάζουν οι AI agents μας, γραμμένες από τον ερευνητικό agent της Stratmill. Κάθε σελίδα παραπέμπει στο πρωτότυπο.

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

Αναζήτηση στη βιβλιοθήκη

511 έγγραφα

QuantInsti blog

This overview explains index options as contracts whose value depends on a market index, and describes how they can be used to speculate on index moves or hedge exposure. It distinguishes index options from options on individual stocks and surveys broad…

Δικαιώματα προαίρεσηςΜετοχέςΜεταβλητότηταΔιαχείριση κινδύνου
QuantInsti blog

The article describes three sentiment measures and proposes contrarian trades based on them. VIX is presented as an options-derived estimate of expected S&P 500 volatility; high readings are associated with fear and falling prices, while low readings are…

Επενδυτικό κλίμαΜεταβλητότηταΔικαιώματα προαίρεσηςΣυμβόλαια μελλοντικής εκπλήρωσης
QuantInsti blog

The document explains the difference between syntax errors, which prevent code from being parsed, and exceptions, which arise when syntactically valid code encounters a problem during execution. A division function illustrates runtime failures such as…

Μηχανική μάθησηΣτατιστική
QuantInsti blog

Overnight trading means placing orders after a market closes for execution when it next opens. The article describes reviewing the day’s price action and relevant overnight news, then submitting an after-market order through a broker. It contrasts this with…

ΜετοχέςΕκτέλεση εντολώνΔιαχείριση κινδύνουΜικροδομή αγοράς
QuantInsti blog

This profile describes Ryan Soriano’s experience learning automated trading, including a course focused on connecting Python strategies to Interactive Brokers. He highlights practical steps such as linking to the broker for paper and live trading. His stated…

BacktestingΕκτέλεση εντολώνΜηχανική μάθησηΔιαχείριση κινδύνου
QuantInsti blog

This guide explains autocovariance and autocorrelation as measures of how a time series relates to its own past values. Autocovariance retains the units and scale of the data, while autocorrelation standardizes the relationship by variance, making it bounded…

ΣτατιστικήBacktestingΕπαναφορά στον μέσο όροΟρμή
QuantInsti blog

The document surveys neural network concepts and architectures relevant to trading, including perceptrons, feed-forward networks, multilayer perceptrons, convolutional networks, recurrent networks, and modular networks. It explains their broad structural…

Μηχανική μάθησηΜετοχέςΣτατιστικήBacktesting
QuantInsti blog

The document introduces Zipline as an event-driven Python library for running trading algorithms and backtests. It outlines the algorithm structure: an initialization step stores the selected security, while a handler processes each market bar, places…

ΜετοχέςΤεχνικοί δείκτεςΑκολούθηση τάσηςBacktesting
QuantInsti blog

This article explains why index volatility depends on both the volatility of constituent stocks and the correlation among them. When stocks move more independently, their individual volatility can rise without a comparable increase in index volatility; when…

Δικαιώματα προαίρεσηςΜεταβλητότηταΑρμπιτράζΜετοχές
QuantInsti blog

This document explains how the IBrokers R package connects a strategy to Interactive Brokers through Trader Workstation (TWS). It outlines functions for requesting contract details, live quotes, market depth, real-time bars, and historical data, along with…

Εκτέλεση εντολώνΜικροδομή αγοράςΜετοχέςΔικαιώματα προαίρεσης
QuantInsti blog

This interview presents one learner’s route from long-term investing and manual indicator-based trading into algorithmic trading education. The interviewee describes choosing a structured course to study a range of subjects, including statistics, options,…

BacktestingΤεχνικοί δείκτεςΜηχανική μάθησηΜικροδομή αγοράς
QuantInsti blog

The article introduces Bayesian statistics as a way to update beliefs about market hypotheses and model parameters when new evidence arrives. It explains priors, likelihoods, and posterior probabilities, then works through a simplified earnings scenario in…

ΣτατιστικήΜηχανική μάθησηΔιαχείριση κινδύνουΜετοχές
QuantInsti blog

The document outlines conditions in which quantified news sentiment may be more useful for equity trading. It suggests that small-cap stocks can react more strongly than larger firms, low-beta stocks may be sensitive to sentiment shifts, and low-volatility…

ΜετοχέςΕπενδυτικό κλίμαΣτρατηγικές βάσει γεγονότωνΜικροδομή αγοράς
QuantInsti blog

The article corrects common assumptions about algorithmic trading. It explains that returns depend on strategy design, quantitative analysis, historical testing, and changing market conditions, so no particular outcome is guaranteed. It also distinguishes…

BacktestingΔιαχείριση κινδύνουΕκτέλεση εντολώνΣυναλλαγές υψηλής συχνότητας
QuantInsti blog

This interview describes how Pranav Lal, who is blind, uses screen readers and programming tools to study and run algorithmic trading systems. He contrasts the effort of interpreting charts with a workflow based on accessible command-line tools, code, price…

Μηχανική μάθησηBacktestingΜετοχέςΕκτέλεση εντολών
QuantInsti blog

This beginner guide explains cryptocurrency as digital assets recorded on distributed blockchains, outlining transactions, cryptographic security, decentralization, consensus, and the distinction between proof of work and proof of stake. It then walks…

ΚρυπτονομίσματαΔιαχείριση κινδύνουΑγορές spot
QuantInsti blog

The Hurst exponent is presented as a measure of long-term dependence in a time series. Values above 0.5 are associated with persistence and possible trending behavior, values below 0.5 with anti-persistence, and a value near 0.5 with random-walk behavior.…

ΣτατιστικήΤεχνικοί δείκτεςΚρυπτονομίσματα
QuantInsti blog

This overview traces computing from early mechanical calculators and punched-card systems through programmable computers, telecommunications, personal computing, and machine learning. It describes milestones such as the Pascaline, Babbage’s engines,…

Συναλλαγές υψηλής συχνότηταςΜηχανική μάθησηΣτατιστική
QuantInsti blog

The document explains beta as a historical estimate of how an asset’s returns move relative to a market benchmark. A regression of asset returns on benchmark returns estimates beta as the slope, while the intercept represents historical excess return in the…

ΜετοχέςΣτατιστικήΔιαχείριση κινδύνουΚατασκευή χαρτοφυλακίου
QuantInsti blog

Boruta-Shap combines Boruta’s comparison of original features against shuffled versions with Shapley-based importance estimates. The described workflow uses a tree-based model to assess tentative features across repeated trials, counts how often features…

Μηχανική μάθησηΣτατιστικήBacktesting
QuantInsti blog

This compilation describes QuantInsti’s 2018 webinars on systematic trading, covering risk management, strategy development and backtesting, foreign exchange, and equity products on SGX. The risk session outlines leverage choices, drawdown, stop losses,…

Διαχείριση κινδύνουBacktestingΣυνάλλαγμαΜετοχές
QuantInsti blog

This article surveys twenty videos and webinars for people learning algorithmic trading. The descriptions span foundational topics such as Python setup, market data, strategy development, backtesting, and live trading through broker APIs. Specific examples…

BacktestingΕκτέλεση εντολώνΤεχνικοί δείκτεςΔιαχείριση κινδύνου
QuantInsti blog

This interview traces Vijayakumar’s progression from early stock investments and repeated losses to options trading and work on algorithmic strategies. He describes learning through books and practice, then studying derivatives, Python, and quantitative…

Δικαιώματα προαίρεσηςΔιαχείριση κινδύνουΜεταβλητότηταΜηχανική μάθηση
QuantInsti blog

The document explains Python’s lambda expressions as short, unnamed functions that evaluate one expression and return a value. It contrasts them with named functions defined in blocks, noting that lambdas suit small, single-purpose operations but cannot…

ΣτατιστικήΜηχανική μάθηση