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.
28 documents
This overview compares free and paid sources for historical market data accessed through Python APIs. It describes retrieving single and multiple instruments, using daily or intraday frequencies, and handling several asset classes, with examples involving…
The article surveys stock market simulators for practicing trades with virtual funds. It describes services for manual trading, historical chart exercises, and, in some cases, automated strategies or broker connections. The listed features include market…
The article introduces Bitcoin’s transaction ledger, UTXO accounting, public nodes, and Proof of Work consensus. It explains how miners compete to find a valid nonce, how difficulty targets regulate block production, and how block rewards and transaction…
The document explains the Aroon indicator’s two components, Aroon Up and Aroon Down, which track how recently a period’s highest high and lowest low occurred. It gives a lookback-based calculation and shows that the resulting values are expressed as…
The article introduces Ethereum as a blockchain platform for running smart contracts and decentralized applications. It explains Ether and gas, the Ethereum Virtual Machine, and examples of applications in decentralized finance and autonomous organizations.…
This interview traces Praveen Singh’s move from electronics and software work into electronic trading roles at investment banks in Japan. His experience spans client connectivity and trading platforms, including work on direct market access, high-frequency…
This project applies a Random Forest classifier to intraday BTC/USD data to produce directional signals from technical features. It uses two years of one-minute OHLC observations and inputs including returns, percentage changes, RSI, ADX, moving-average…
The document explains RippleNet’s role as a payments network for financial institutions and distinguishes it from XRP, the digital asset used as a possible bridge currency. It describes the XRP Ledger, validator consensus, trusted Unique Node Lists,…
This tutorial explains a Python workflow for retrieving cryptocurrency market data from CryptoCompare. It describes authenticating with an API key, listing available coin tickers, and requesting historical prices at daily, hourly, or minute intervals. The…
The article describes collecting cryptocurrency price and volume observations at minute intervals, storing them for analysis, and accounting for delays caused by fetching data across many coins. It then presents a simple trend-following strategy that uses…
This interview follows an engineer and AI practitioner as she moves into quantitative trading and develops an algorithmic trading desk focused on crypto. Her account highlights a practical learning path: apply statistical and machine-learning methods to…
The article introduces altcoins as cryptocurrencies other than Bitcoin and describes how they emerged to offer different features, address perceived limitations, or serve particular purposes. It discusses smart contracts and decentralized applications,…
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…
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.…
This beginner guide explains that cryptocurrency wallets manage the keys used to access and transact with crypto assets. It distinguishes a public address, which can be shared to receive funds, from a private key, which must remain protected. The article…
This project outlines a statistical arbitrage approach to trading cryptocurrency perpetual contracts on Binance. It screens contract price series for stationarity and cointegration, then forms a spread between a selected pair and uses deviations from the…
This document introduces cryptocurrency algorithmic trading through an interview with a developer building a cross-exchange trading platform. The described workflow retrieves exchange order books, backtests strategies at short intervals, generates signals,…
This project studies historical ETHBTC order book data from Poloniex and tests two ways of using order flow in simulated trading. The first estimates prices from aggregated bid and ask positions and uses those estimates to filter trades generated by a…
The article introduces blockchain as a distributed ledger for recording transactions across networked computers. It explains how blocks hold records and the previous block’s hash, linking the history so that changes become detectable. Copies of the ledger…
The document explains how crypto arbitrage seeks to capture price or lending-rate differences across exchanges. It describes why gaps can arise, including capital controls, uneven liquidity and reaction speeds, volatility, and differences in transaction…
The document outlines a basic workflow for algorithmic Bitcoin trading: generate entry and exit signals from a strategy, allocate capital according to risk rules, then send orders to an exchange through its API. It describes Bitcoin as a decentralized…
This guide compares free and paid sources of financial data by access method, asset coverage, and availability of intraday, daily, fundamental, and news information. It recommends choosing a provider according to data accuracy, latency, historical depth,…
The article introduces Bitcoin’s public blockchain, mining, capped issuance, and wallet transactions, then connects these features to ransomware payments and Bitcoin’s appeal as a tradable asset. It frames price as primarily demand-driven and names…
This tutorial shows how to turn transaction-level tick data into open, high, low, and close values for fixed time intervals using Pandas resampling. A tick represents an individual trade, with the example dataset containing timestamps, last traded prices,…