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.
55 documents
The article introduces derivatives as contracts whose value depends on an underlying asset, index, or rate. It describes forwards, futures, options, and swaps, explaining basic contract features such as long and short positions, strike prices, option…
The article introduces delta as option price sensitivity and gamma as the rate at which delta changes with the underlying price. It describes gamma scalping as repeatedly adjusting an options portfolio to manage its Greek exposures while seeking to benefit…
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…
Sourabh Sisodiya describes moving from discretionary trading based on technical analysis and candlestick patterns toward rule-based strategies after questioning whether his approach had a reliable edge. He presents backtesting as a way to assess a system and…
The article explains market sentiment as investors’ broad outlook, shaped by economic, fundamental, technical, and other information. It distinguishes momentum approaches that follow prevailing sentiment from contrarian approaches that anticipate a reversal…
This overview introduces multi-leg options strategies, including straddles, strangles, iron condors, and iron butterflies. It explains Delta, Gamma, Theta, Vega, and Rho as measures of how option values and portfolio exposures respond to changes in the…
The document introduces LEAPS as options with expirations more than a year away, allowing investors to take long-horizon directional positions or hedge stock holdings without buying or shorting shares outright. It explains that long-dated contracts can…
The document introduces volatility as a measure of return dispersion and distinguishes historical volatility, calculated from past prices, from implied volatility inferred from option prices. Its historical-volatility example uses logarithmic returns and a…
This introductory tutorial presents NumPy as a tool for efficient numerical work in Python. It explains how arrays differ from lists: arrays support element-wise arithmetic, can be multidimensional, and generally hold values of a single type. Examples use…
This article uses simple betting examples to explain expected value as the probability-weighted average of gains and losses. It shows how a favorable payoff structure can produce positive expectation even when a win is uncertain, while a symmetric…
The article introduces spread trading as a hedged position that buys and sells related contracts, such as options on the same security with different strikes or expiries, or futures with different delivery months, commodities, or locations. It recommends…
A mechanical engineering professor describes developing an interest in quantitative finance through mathematical study of options models, earlier programming in Fortran, and later adoption of Python for algorithmic trading. After joining a formal trading…
A retail trader describes moving from options volatility trading toward a broader systematic approach after the 2018 bear market exposed limits in relying on one strategy. He is refining his earlier short volatility system and exploring a floor-and-ceiling…
The article explains proprietary trading as a firm’s use of its own capital, then surveys strategies including merger arbitrage, index arbitrage, global macro trading, and volatility arbitrage. Its index example illustrates buying an ETF while shorting its…
This project describes an intraday Nifty strategy using five-minute data, a 200-period simple moving average, and a 50-period exponential moving average. It takes long or short positions when the index closes beyond both averages, with no position when the…
The project backtests a mechanical strategy of selling an at-the-money SPY straddle each week, using options with roughly 45–60 days to expiry and holding each position until expiration. It describes sourcing option prices, matching entry dates with expiries…
This interview follows Xavier, an Australian IT architect with engineering and computer science training, as he moves from market research and investing to day trading and an interest in building an algorithmic trading desk. He describes exploring company…
This roundup introduces a range of options topics through summaries of ten articles and several additional strategy guides. It describes options as tools for transferring risk and outlines strategies such as butterflies, spreads, straddles, and calendar…
This project describes a directional index options strategy that uses NIFTY daily candles and 15-day simple moving averages of highs and lows to generate long call or put signals. Entry rules combine the current candle’s position relative to the averages…
The document introduces the Heston model as an option-pricing framework that allows both the underlying asset price and its variance to evolve stochastically. Unlike constant-volatility Black–Scholes, it models variance as mean reverting, with random…
The article examines market effects associated with the early COVID-19 outbreak and the Russia–Saudi Arabia oil price dispute. It describes calculating average forward returns after historical drawdowns: compute cumulative returns and running peaks, identify…
This article introduces exotic options as contracts whose payoff, exercise conditions, or underlying can differ from standard calls and puts. It describes barrier options, which activate or expire when a price threshold is reached; binary options, which pay…
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…
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…