Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
1,625 documents
These reading notes survey high-frequency trading from market structure through strategy and infrastructure. They describe electronic order books, the roles of investors, market makers, arbitrageurs, and directional predictors, and how market makers earn…
This overview explains controllers as reusable, configurable components in Hummingbot Strategy V2. A controller receives market data such as order books, trades, and candles, then emits actions that direct a parent script to create or stop executors.…
The document introduces algorithms for generating every selection of k items from a set of N, either with order ignored (combinations) or preserved (permutations). It frames exhaustive enumeration as a brute-force way to search for an optimal solution when…
A forum user asks how to check whether enough funds are available before starting a spread-arbitrage order algorithm. The stated motivation is to avoid opening only one leg of a paired trade when the account cannot support both sides. A reply points to…
A forum exchange discusses why VeighNa’s StatisticalArbitrageStrategy example uses a ten-unit price offset when starting its spread-trading algorithm. The questioner describes the order logic: a leg order is sent when the spread order price would otherwise…
The document explains how executed trades and resting orders provide different views of Bitcoin markets. Trade volume shows what has already happened, while order book depth aggregates buy and sell interest at unexecuted price levels. A depth chart gives a…
A trading-system forum discussion explains why a conventional CTA strategy that works on outright futures may fail when applied directly to exchange-listed spread contracts. The reported symptoms include missing backtest data and occasional trades with…
The guide explains what a crypto market ticker typically contains: last price, best bid and ask, rolling 24-hour change, high and low, volume, and a timestamp. It shows how these snapshots can support broad scans for top movers, unusual volume relative to a…
These release notes describe Hummingbot 1.19.0, focusing on a developing modular strategy framework and early dashboard tools for managing bots and backtests. The framework separates market data candles, controllers that choose actions, and executors that…
This tutorial develops an earlier cryptocurrency spot hedging bot for trading price spreads between two exchanges. It adds optional spot margin mode switching for Binance, separate trigger thresholds for trades in each direction, chart lines and live spread…
The article introduces calendar spread arbitrage as opposing positions in contracts on the same underlying asset with different maturities. It describes monitoring the price difference between crypto contracts and acting when the spread widens beyond a…
The article surveys possible uses of artificial intelligence in crypto trading and decentralized finance. It discusses robo-advisory, automated bots, strategy development and backtesting, risk assessment, arbitrage monitoring, sentiment analysis, predictive…
This talk overview explains four broad approaches to quantitative trading: market making, statistical arbitrage, price prediction, and microstructure trading. Market makers post bids and offers to supply liquidity and seek to earn the spread, while managing…
This overview describes an automated cross-exchange market-making executor in the Hummingbot framework. The strategy seeks to capture price differences between venues or markets by placing a maker order on one side and executing against a taker market when…
This README introduces a planned quantitative research project connecting iron ore spot prices with the currencies of countries that export iron ore. It presents the project as an extension of an earlier commodity-focused trading strategy, with an intended…
This 2018 report reviews managed futures, including how CTA strategies trade futures and options and how they differ by analysis method, trading style, holding period, and markets covered. It describes systematic and discretionary approaches alongside trend…
The document explains how crypto data aggregators combine information from centralized and decentralized exchanges into normalized time series. It frames fragmentation across venues, trading pairs, and blockchains as an infrastructure problem for…
This podcast summary discusses crypto market structure, decentralized finance, governance, and emerging chain ecosystems. Its trading content centers on automated arbitrage between centralized exchanges: bots use exchange APIs to act on price differences,…
The article characterizes high-frequency trading as automated, rapid intraday trading based on fine-grained market data, with rapid order entry and cancellation and high capital turnover. It surveys four approaches: providing liquidity through market making,…
These release notes describe a Hummingbot update that adds connectivity to several decentralized and centralized crypto markets, including spot and perpetual futures venues. The highlighted strategy, cross-exchange mining, places maker orders on one exchange…
This Chinese-language article surveys quantitative finance work through six role types: desk quant, model validation, research, quant development, statistical arbitrage, and capital modeling. It describes how these roles differ in their proximity to trading,…
This module implements analytical trading calculations for an Ornstein–Uhlenbeck mean-reverting process, following a published statistical-arbitrage model. Given an entry threshold, an exit threshold, and transaction costs, it computes expected trade length,…
The article compares decentralized liquidity provision in automated market makers (AMMs) with liquidity mining on centralized exchange order books. In an AMM, providers supply assets while a smart contract sets prices; arbitrageurs trade against the pool and…
This weekly digital-asset snapshot combines price action with derivatives positioning, institutional flows, order-book liquidity, spreads, and DeFi indicators. It describes Bitcoin testing support near $86,000 amid a broader risk-off move, while ETF…