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.
4,613 documents
This script lays out a ten-level long grid around a user-defined center price. Grid levels are spaced by a percentage of that center, with orders set as limits or stops depending on whether the current price is above or below each level. Each successive…
This strategy uses two layers of pivot analysis to identify potential turning points. Basic price highs and lows form the first layer; a second layer selects more significant pivots from those points. A break through a selected pivot level can trigger a long…
This trend-following framework uses Heikin Ashi candle conditions to signal long or short entries. It describes an initial position with a preset target and stop, followed by a possible second entry if the first target is reached and favorable candle signals…
This trend-following framework uses Heikin Ashi candle conditions to identify direction, then manages trades with separate initial and possible second entries. Each entry can have its own target and stop settings. After the first target is reached, the…
This long-only SOL perpetual futures strategy arms an entry when 4-hour RSI(14) falls below 33. After the base order, it places up to five averaging orders at fixed price declines of 2%, 5%, 9.5%, 16%, and 25% from the base entry, with order sizes scaling by…
This BTCUSDT strategy description combines RSI extremes with engulfing candles to generate long and exit signals. It uses RSI levels of 70 and 30, then looks for a bearish engulfing candle near an overbought reading or a bullish engulfing candle near an…
This short-term strategy generates initial signals from Stochastic RSI K/D crossovers on a five-minute chart and seeks confirmation from the 15-minute indicator within a waiting window. Thresholds distinguish long and short setups, and a cooldown limits…
This strategy uses five EMAs, with periods of 12, 144, 169, 576, and 676, to define aligned bullish or bearish trends. It looks for price interaction with EMA144 and a close on the appropriate side of EMA169 to trigger entries. Additional positions can be…
This paper describes the motivation and design of a Python research package intended to make methods from financial machine learning easier to implement and study. It frames Lopez de Prado’s work as a research process built around data preparation, sampling,…
The article demonstrates a spreadsheet workflow for exploring a claimed weekday pattern in gold-related prices. Using GLD price history, it derives log returns and calendar fields, groups returns by weekday in a pivot table, and charts the sums. It reports…
The volatility risk premium (VRP) is the tendency for option implied volatility to exceed the volatility that later occurs. The article explains this as compensation for bearing the risk of sharp volatility spikes, comparing option selling to insurance:…
The article illustrates how a put option can limit downside on an equity holding and shows how the premium changes the portfolio’s payoff. It first models a position in an index-tracking fund, identifying the price level associated with a chosen loss and…
The article explains why doubling position size after each loss can make a losing strategy appear attractive until a sufficiently long loss streak causes severe losses or account ruin. It outlines a simulation using random trades and Martingale sizing, then…
The article reviews a strong year for diversified systematic trading and focuses on a bond strategy that buys shortly before month-end, sells at month-end, and re-enters after a few days. The author describes institutional rebalancing and portfolio…
This quiz presents a compact lesson about the tension between market efficiency and noisy price movements. Its central implication is that even sound trading decisions can feel messy, imprecise, or uncomfortable because a trader’s edge may be small relative…
The article argues that systematic traders should expect short-term randomness to obscure an edge, and avoid changing a strategy in response to every losing trade or market fluctuation. It frames the trader’s task as following a researched plan over time,…
The article explains how a put option can cap losses on a stock portfolio while preserving upside beyond the option premium. It first illustrates the payoff for a holding of 100 SPY shares, then shows how a chosen maximum loss can inform the put strike. In…
The article examines why a few weeks of weak performance cannot establish that a strategy has lost its edge. In a simulation, a strategy with positive long-run drift shifts to zero drift for one month while volatility remains high. A comparison of the…
This short note lists ways traders can lose money: excessive trading increases fees and market impact, oversized positions can impair compounding or cause ruin, and shorting positive drift or risk premia can create persistent losses. It also cautions against…
The article argues that a stop loss is useful only when losses carry information about likely future returns. For a signal based on a factor such as sentiment, a falling position value does not by itself show that the signal has weakened. Exiting solely…
This excerpt presents a quantitative perspective on drawdowns as an expected part of trading. Its suggested response combines understanding market behavior, using a sound systematic research process, and keeping a measured perspective during losing periods.…
This article uses simulated cryptocurrency price paths to explore how often a leveraged trend strategy might need rebalancing to manage drawdowns. The author builds a geometric Brownian motion simulator with autocorrelated returns and random jumps, using a…
The document explains how UVXY’s daily leverage target and maturity maintenance lead to recurring portfolio rebalancing, and uses spreadsheet models to examine two trades: shorting UVXY with periodic rebalancing, and shorting a basket of UVXY and an inverse…
This guide explains volatility-targeted position sizing and describes tools for calculating target exposure, visualizing it over time, and simulating rebalancing. The position is scaled according to the ratio between the desired portfolio volatility…