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Knowledge library

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.

Quant Q&A
20,364 documents
SuperMind
12,226 documents
OKX Learn
8,431 documents
Strategy library
7,910 documents
MQL5 code base
7,090 documents
BigQuant
3,481 documents
Bitget Academy
3,298 documents
MQL5 articles
3,012 documents
TradingView scripts
1,976 documents
ProRealCode
1,507 documents
Deribit Insights
1,232 documents
Machine Learning for Trading
1,124 documents
arXiv papers
1,033 documents
Amberdata research
766 documents
FMZ forum
682 documents
FMZ digest
662 documents
vn.py community
560 documents
QuantInsti blog
511 documents
Galaxy Research
340 documents
QuantStart
246 documents
Stratmill research code
219 documents
Robot Wealth
195 documents
NautilusTrader
191 documents
Hummingbot docs
181 documents
Paradigm research
175 documents
Lumibot
164 documents
Kraken Learn
163 documents
Quant course library
157 documents
OctoBot
152 documents
Cryptohopper blog
144 documents
Systematic trading blog (Rob Carver)
132 documents
Qlib
116 documents
TqSdk
86 documents
Quantpedia
86 documents
Hyperliquid docs
79 documents
Freqtrade
68 documents
Hudson & Thames
62 documents
Awesome Systematic Trading
61 documents
backtrader
54 documents
vn.py
50 documents
Binance API docs
45 documents
Quantopian lectures
45 documents
FMZ guides
38 documents
pysystemtrade
34 documents
Freqtrade docs
32 documents
quant-trading
31 documents
FinRL
28 documents
Zipline
22 documents
FMZ live strategies
21 documents
Jesse
17 documents
pyfolio
16 documents
Alphalens
14 documents
WonderTrader
14 documents
backtesting.py
11 documents
Technical Analysis
9 documents
QTPyLib
8 documents
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

8,116 documents

Quant Q&A

The discussion explains why binary options have a poor reputation, focusing on the risks of trading through unregulated or unreliable websites. Unlike products traded and cleared on standard options exchanges, some binary options are offered directly by…

OptionsDerivatives pricingRisk management
Quant Q&A

The document explains why the Carr–Madan Fourier option-pricing method uses the fast Fourier transform: after discretizing the pricing integral with the trapezoid rule, one FFT can produce call prices for many strikes at a computational cost that scales as…

OptionsDerivatives pricingStatistics
Quant Q&A

The document discusses preparing for severe market declines, including financial crises and scenarios involving currency instability. One proposed hedge is to buy long-dated, low-cost puts on individual stocks or, more commonly, exchange-traded funds and…

OptionsRisk managementVolatilityEquities
Quant Q&A

The document describes an attempt to price equity calls by calibrating a GARCH(1,1) model to historical data with maximum likelihood, then simulating the stock under a risk-neutral diffusion using forecasted conditional volatility. The proposed pricing…

OptionsEquitiesVolatilityDerivatives pricing
Quant Q&A

The document examines whether the curvature of an implied-volatility skew can be summarized with a second derivative estimated from discrete option strikes. It presents a central finite-difference approximation around at-the-money and considers summing such…

OptionsVolatilityStatistics
Quant Q&A

The document explains why a finite-difference option-pricing implementation can advance its time variable even though the Black–Scholes equation is commonly solved backward from expiration. The apparent discrepancy comes from the time convention used in the…

OptionsDerivatives pricingStatistics
Quant Q&A

The document asks how to derive approximations for the expected profit and standard deviation of profit from buying an at-the-money straddle close to expiration. It reports formulas attributed to a quantitative finance textbook: expected profit is…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document frames the probability that an unhedged short European call loses money at expiration after being sold above its risk-neutral price. The premium, including the extra amount received, is invested at the risk-free rate, while the seller remains…

OptionsDerivatives pricingStatistics
Quant Q&A

The discussion explains when least-squares Monte Carlo (LSMC), also known as the Longstaff–Schwartz method, is relevant for pricing American or Bermudan calls. For a call on a non-dividend-paying stock, early exercise is not beneficial under standard…

OptionsDerivatives pricingStatisticsBacktesting
Quant Q&A

The discussion asks whether historical volatility can be substituted for implied volatility in a formula for estimating an instrument’s move over a chosen period. It treats the calculation as a conditional estimate: if volatility stays at its historical…

VolatilityOptionsStatistics
Quant Q&A

The document asks whether a call-price process expressed as C(K, S_t) is a martingale when put–call symmetry holds, and whether that property persists when the symmetry is broken. It states a symmetry relation connecting put and call prices under an assumed…

OptionsDerivatives pricingStatistics
Quant Q&A

The document examines a challenge to the continuous-time self-financing condition used in Black–Scholes–Merton option pricing. The challenge argues that the standard condition mishandles portfolio rebalancing and questions whether the resulting strategy…

OptionsDerivatives pricingStatistics
Quant Q&A

The document considers doubling exposure to a diversified permanent-portfolio variant holding equities, long-term government bonds, gold, and real estate. Its proposed construction uses deep in-the-money call options intended to have deltas near one, with…

Multi-assetOptionsPortfolio constructionRisk management
Quant Q&A

The document asks whether squared VIX, converted to decimal units, is a suitable proxy for instantaneous market variance in a continuous-time variance model. Since VIX reflects option-implied expected volatility over the next month, its square represents a…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document asks whether a discounted characteristic function written in the Duffie, Pan, and Singleton representation already avoids the little Heston trap. It presents formulas for the transform’s coefficients, including a square-root term and a…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document raises a question about the relationship between maturity and the delta of an at-the-money option. It contrasts the common textbook statement that at-the-money delta is one half with the author’s observation that longer-dated options may show…

OptionsDerivatives pricingVolatility
Quant Q&A

The document clarifies how to interpret the stock-price process in a Dupire local volatility model. The initial value is the underlying’s spot price, while the evolving price is random because it depends on a Wiener process. Repeatedly simulating paths, or…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document considers whether adding limit orders to a stock’s book can stabilize prices, change volatility, attract traders, or improve price discovery. The responses offer competing mechanisms rather than a settled empirical conclusion. Resting depth may…

EquitiesOptionsVolatilityMarket microstructure
Quant Q&A

The document distinguishes a relative-value volatility position from a true arbitrage when options reference different assets. A trader might buy the lower implied-volatility option and sell the higher one, sizing the legs to manage delta and possibly vega…

OptionsVolatilityArbitrageRisk management
Quant Q&A

This document derives the pricing equation for European or American-style claims in a double exponential jump-diffusion model. It describes the risk-neutral log-price process, compensates the jump component so the discounted asset price is a martingale, and…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document clarifies that implied volatility conventionally means the volatility input to the Black-Scholes or Black formula that reproduces an observed option price. Parameters calibrated in another model, such as a stochastic variance model, are not…

OptionsDerivatives pricingVolatilityRisk management
Quant Q&A

The response derives a delta hedge for a European call on the ratio of two assets. It models both assets as correlated geometric Brownian motions with the same risk-free drift, derives the dynamics and effective volatility of their ratio, and uses that ratio…

OptionsDerivatives pricingRisk managementStatistics
Quant Q&A

The document asks how to combine calibration errors for two instrument groups, each containing multiple assets. It compares an unweighted sum of group-level Euclidean errors with versions that apply weights within each group and a mixing parameter between…

OptionsFixed incomeDerivatives pricingStatistics
Quant Q&A

An underlying’s quoted implied volatility is a summary measure, not the volatility of one universal option. The document describes two common approaches: use an at-the-money option’s implied volatility, often interpolated to a 30-day maturity, or estimate a…

OptionsVolatilityDerivatives pricingStatistics