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.
765 documents
The answer explains how the sign of a hedge-adjusted spread can guide the direction of a pair trade. Under the stated spread definition, a positive spread prompts a short position in the first asset and a long position in the second; a negative spread…
The answer treats a cointegration spread as a synthetic position: going long the spread means buying one leg and shorting a hedge-ratio-weighted amount of the other, with the reverse positions for a short spread. It then discusses practical sizing across…
The document describes a Python error in code that retrieves two stock price series, calculates their returns, and uses the difference between the returns to form a pair-trading signal. The reported missing key is the concatenated pair name, even though that…
The document asks why pairs traders commonly size the two legs using a regression coefficient rather than equal dollar amounts. Regression estimates how one stock’s movement relates to the other and can define a mean-reverting spread; dollar neutrality…
The document explains how to calculate the return of a long position in one stock and a short position in another over a holding period. It recommends calculating each asset’s ordinary return, then multiplying by its portfolio weight: positive for the long…
The discussion challenges the idea that financial models should always use returns simply because price levels are often nonstationary. It notes that returns are a common starting point for time-series analysis and can represent price behavior indirectly,…
The document asks why normalized prices for a pair can keep separating despite correlated returns and tests suggesting cointegration. The response distinguishes similar short-term return behavior from a stable long-term relationship: two series can move in…
This exchange examines why an augmented Dickey–Fuller test can produce surprising results for a constructed spread. The question compares a cumulative random series with minute-by-minute spread data and reports that the spread's p-value changes when its…
The document describes a pairs trading setup that estimates a hedge ratio and intercept as time-varying states in a Kalman filter. Its observation equation relates one asset to another, with measurement noise, and the filter updates the relationship as new…
The document asks whether cointegrated time-series pairs can be ranked by how strongly they are cointegrated. It seeks an intuitive comparison for identifying which candidate series is most closely cointegrated with a given series, down to the weakest pair.…
This example builds a spread-like series from the closing prices of the YM and NQ futures contracts. It smooths their price ratio with a long moving average, uses that ratio to scale one contract against the other, and calculates Bollinger Bands around the…
This strategy compares two instruments by calculating a rolling z-score for each price series, then subtracting the paired instrument’s score from the main instrument’s score. It applies a modified z-score to that spread using the rolling median and median…
This strategy compares a charted asset with a user-selected ticker to estimate a cointegrating relationship. It fits linear regressions across several rolling lookback lengths, tests changes in the residual series for stationarity with a Dickey–Fuller…
This indicator visualizes the relative cycles of two securities to help time a strategy that holds a long position in whichever is stronger. It applies the same high-pass and smoothing filters to both price series, then scales each filtered stream by its…
This TradingView indicator compares a user-selected set of assets using sampled weekly or monthly returns. For each pair, it fits a linear regression, measures the standard deviation of recent residuals, and displays the inverse deviation as a heatmap score.…
The article presents eight U.S. stocks as candidates for short-term, high-volatility trading: Micron, SK Hynix, Nebius, Circle, MicroStrategy, Coinbase, Palantir, and Robinhood. It groups potential drivers such as AI infrastructure demand, crypto price…
The document explains short and long futures hedges for traders with spot exposure or planned purchases. It distinguishes perpetual contracts, which have no expiry and use funding payments to keep prices near spot, from dated futures. Funding rates can…
The document explains the gold-silver ratio (GSR), calculated by dividing gold’s price per ounce by silver’s. It presents high readings as possible evidence that silver is cheap relative to gold and low readings as possible evidence that silver is expensive.…
The article presents a scenario in which high interest rates could weigh on growth-oriented Nasdaq stocks while deregulation could benefit financial and industrial companies represented more heavily in the Dow. It suggests three ways to trade that possible…
The article explains a cash equity short sale: a trader borrows shares, sells them, and later buys shares to return to the lender. The difference between sale and repurchase prices determines gross profit or loss, while borrowing charges and dividends affect…
The article attributes strength in gold and silver to a mix of macroeconomic support and market-specific supply and demand. It argues that silver may benefit from constrained mine supply and industrial uses linked to AI hardware and the energy transition,…
The document explains silver’s higher volatility through its dual role as an investment metal and an industrial input. Investment demand responds to currency, rates, and risk sentiment, while industrial demand is tied to manufacturing and clean-energy…
The article outlines factors that may influence platinum and palladium prices, including mine supply constraints, automotive demand, substitution between the metals, geopolitical conditions, and the transition to hydrogen and electric vehicles. It explains…
The document surveys common approaches used by crypto hedge funds, emphasizing long-short trading and early-stage investments in blockchain projects. Long-short positions aim to benefit from relative price differences across assets and can be used in rising…