Skip to content

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

10,263 documents

Quant Q&A

The document discusses why the differential equation for an American put may be written as an inequality in the continuation region above the optimal exercise boundary. One response links the inequality to the option’s delta at the boundary and the condition…

OptionsDerivatives pricingStatisticsBacktesting
Quant Q&A

The document explains that short-rate models describe the evolution of an instantaneous interest rate and use it to derive discount factors as expected accumulated discounting over time. Because the instantaneous rate is not directly observable, the response…

Fixed incomeOptionsDerivatives pricingStatistics
Quant Q&A

The document recommends a practical scenario approach for pricing down-and-in puts when vanilla option prices and implied volatilities are available. Apply a spot shift and test a small set of implied volatility shifts, using the existing volatility surface…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The document describes using quasi-Monte Carlo (QMC) points to generate Gaussian shocks for simulated asset paths, with a Brownian bridge (BB) arranging those shocks across time. It recommends mapping low-discrepancy uniform points through the inverse normal…

OptionsDerivatives pricingStatisticsBacktesting
Quant Q&A

The document explains how to calculate the yield to maturity of a semiannual coupon bond when the valuation date falls between coupon dates. It converts the quoted price from fractional bond notation into a decimal price, then identifies the timing issue in…

Fixed incomeDerivatives pricingStatistics
Quant Q&A

The document discusses estimating a Heston stochastic volatility model with an Unscented Kalman Filter. The response recommends expressing the system in log prices or returns rather than raw prices, then discretizing the price and variance dynamics as a…

OptionsVolatilityStatisticsDerivatives pricing
Quant Q&A

The document considers how to price options with maturities as long as several decades when market quotes for those maturities are unavailable or illiquid. It raises three possible inputs: calibrating to the liquid portion of the volatility surface, using…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document asks why derivatives traders use stochastic-volatility models when pricing and hedging products such as digital options. It frames the issue through approximate static replication: a digital payoff can be approximated with a narrow put spread,…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The document asks where academics can obtain free data to train an approximation of the Black–Scholes pricing model. It identifies the model inputs the author has in mind: share price, strike, risk-free rate, volatility, and time to expiration. The author…

OptionsDerivatives pricingMachine learningStatistics
Quant Q&A

The discussion explains how Fourier transforms and characteristic functions can price European options when the underlying log-price density is difficult to obtain directly. It starts from the discounted expected payoff, expresses that expectation as an…

OptionsDerivatives pricingVolatilityBacktesting
Quant Q&A

The question applies Itô’s lemma to derive the distribution of a stock price under a risk-neutral model with deterministic, time-varying rates and volatility. The attempted derivation encounters random stock-price terms in the drift and diffusion after…

EquitiesStatisticsDerivatives pricing
Quant Q&A

A payer swaption gives its holder the right to enter a swap in which fixed is paid and floating is received. The discussion clarifies the option’s rate and bond-price interpretation: a payer swaption behaves like a call on the future swap rate and a put on a…

Fixed incomeOptionsDerivatives pricingRisk management
Quant Q&A

The document asks why Itô’s multiplication rules set products involving dt to zero while treating the square of a stochastic increment as dt. The answer offers a discrete branching intuition: consider the possible paths over a small step, square their…

StatisticsDerivatives pricing
Quant Q&A

The document discusses why the binomial call option delta implies that a portfolio holding delta shares and short one call has the same value in the up and down states. Delta is the change in option value divided by the change in stock price, so the equality…

OptionsDerivatives pricingRisk management
Quant Q&A

The discussion explains why a deep-in-the-money European put can have positive theta when interest rates are positive. As the stock price approaches zero, the put behaves roughly like a zero-coupon bond paying its strike at expiration; the passage says this…

OptionsDerivatives pricingRisk management
Quant Q&A

The document describes a passport option whose terminal payoff is the positive part of the trading portfolio value. The portfolio holds a bounded quantity of the underlying asset, with the remainder in cash, and its value depends on both the asset price and…

OptionsDerivatives pricingRisk managementStatistics
Quant Q&A

The document explains how to price a zero-coupon bond at an intermediate time in the one-factor Hull–White model and debug a QuantLib simulation. The bond value is expressed as a time-dependent factor multiplied by an exponential function of the current…

Fixed incomeDerivatives pricingBacktesting
Quant Q&A

The discussion explains how a known discount margin (DM) can be used to estimate the price of a floating-rate note. For a simple floater, DM can be understood as the reference index plus the coupon spread and an additional yield component reflecting any…

Fixed incomeDerivatives pricing
Quant Q&A

The end-of-month Boolean in QuantLib date helpers determines how a tenor is added when a start date falls at month end. With the rule enabled, adding one month to June 30 produces July 31; with it disabled, the resulting date is July 30. This convention can…

Fixed incomeDerivatives pricing
Quant Q&A

The document explains how to interpret a forward-price stochastic differential equation containing both Brownian motion and Poisson jumps. It treats the counting-process increment as zero between event times and one at a jump, which lets the exponential jump…

FuturesDerivatives pricingStatistics
Quant Q&A

The post asks whether QuantLib’s Longstaff–Schwartz Monte Carlo engine for American options can use non-Gaussian random draws, such as Student-t variates, while pricing under a Black–Scholes–Merton process. The author considers changes to distribution and…

OptionsDerivatives pricingMachine learning
Quant Q&A

The post questions why Micro E-mini S&P 500 futures expiring in June 2021 were quoted below the March 2021 contract, despite the author’s expectation that later expiries should cost more to avoid arbitrage. It notes that the S&P 500 is a total return index…

FuturesDerivatives pricingUS markets
Quant Q&A

The document explains why a stochastic-volatility model writes wealth changes in terms of the dollar amount invested in a risky asset rather than the asset price itself. If an investor commits an amount to the asset, the number of units held is that amount…

Derivatives pricingRisk managementStatistics
Quant Q&A

The document compares a dividend swap with a dividend future when both provide exposure to dividends through a stated strike or entry price. In the example, a long position entered at 100 gains when the dividend outcome or futures price rises to 102, but the…

Derivatives pricingFuturesEquities