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

8,116 documents

Quant Q&A

The document describes diagnosing weak convergence in Monte Carlo simulations of an option-pricing model with state-dependent volatility. The original comparison estimates expectations at two time-step sizes, but uses independent simulated paths. Sampling…

OptionsDerivatives pricingStatisticsBacktesting
Quant Q&A

The document presents Gyöngy’s theorem as a way to construct a local volatility process whose one-time probability distributions match those of a given stochastic process. In the stated result, the local drift and variance are conditional expectations of the…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document addresses how to infer forward rate or caplet volatilities from cap prices or quoted cap volatilities. Its central method is volatility stripping: order caps by maturity, take price differences between consecutive maturities, associate each…

Fixed incomeOptionsVolatilityDerivatives pricing
Quant Q&A

The document examines claims that artificial neural networks outperform Black–Scholes in option pricing. The cited study generates Black–Scholes estimates using simplified inputs, including a closing spot price, fixed volatility and interest rate, no…

OptionsMachine learningDerivatives pricingBacktesting
Quant Q&A

The document examines whether negative forward variance inferred from at-the-money-forward implied volatility across two maturities signals an arbitrage. It defines forward variance from the difference in total implied variance over the two time intervals.…

OptionsVolatilityArbitrageDerivatives pricing
Quant Q&A

The document compares shorting borrowed shares with constructing a synthetic short using a long put and short call at the same strike and expiry. Its example uses a hard-to-borrow stock and reports that the option combination produces a credit and an…

OptionsEquitiesDerivatives pricingCarry
Quant Q&A

The document gives an intuitive argument for uniqueness of the risk-neutral probability measure in the Black–Scholes setting. It invokes Arrow–Debreu claims, each paying one unit in a particular state. If the same claim must have the same arbitrage-free…

OptionsStatisticsRisk management
Quant Q&A

The document examines a one-period market with three assets and states, asking whether a European call can be priced by replicating its payoff when the market admits arbitrage. The stated replication produces a cost of 0.5, but solving for state prices…

OptionsArbitrageDerivatives pricingRisk management
Quant Q&A

The document asks how to calculate the variance of a discounted European call or put payoff under the Black–Scholes assumptions. Its answer outlines a second-moment approach: variance equals the expected squared payoff minus the square of its expected value.…

OptionsDerivatives pricingStatistics
Quant Q&A

The note considers which call strike to use when a trader expects realized volatility to exceed implied volatility and plans to delta hedge, aiming for gamma gains to outweigh option decay. It explains that the approximate gamma contribution to daily profit…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document considers whether option pricing should distinguish upward from downward volatility. One response frames asymmetric volatility as a choice of a different underlying model, with risk-neutral pricing still used to value options. It suggests…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document asks what implied-volatility fitting error is acceptable for an equity-index surface calibrated with stochastic-volatility models such as Heston or SABR. The replies do not establish a universal tolerance. One practical suggestion is to compare…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The document asks how to adapt a closed-form implied volatility estimator from a call option to a put. It presents an equation attributed to Hallerbach (2004) for estimating volatility from a call price, spot price, strike, and time to expiry. This makes the…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document explains how Greeks for swaptions, caps, floors, and other interest rate options are defined and calculated. They measure sensitivity of a derivative’s value to pricing inputs. Because interest rate pricing depends on an entire curve, the…

Fixed incomeOptionsDerivatives pricingRisk management
Quant Q&A

The document asks how to identify the most likely value associated with a call option when the underlying price is lognormally distributed. It starts from the discounted expected call payoff and distinguishes the mode of the underlying price distribution…

OptionsDerivatives pricingStatistics
Quant Q&A

The document examines whether adding a swap payment period changes the value of American and Bermudan swaptions in a predictable order. It defines co-terminal and co-initial swap structures, their exercise schedules, and the proposed comparisons between…

OptionsFixed incomeDerivatives pricing
Quant Q&A

The document addresses two points about an example of VaR manipulation: a likely sign error in an inequality and how a put strategy changes reported risk and profit. The answer says the displayed ordering is consistent if the intended condition is that both…

Risk managementOptionsDerivatives pricing
Quant Q&A

The document considers a bond with a call and a put exercisable on the same date, using different strikes to illustrate how the embedded options affect value. Under its stated assumptions—a forward bond price of 100 and no discounting—the example values the…

Fixed incomeOptionsDerivatives pricing
Quant Q&A

The document describes an attempt to infer local volatility from synthetic option prices generated under a Heston stochastic volatility model. Prices are computed with the COS method, while finite differences estimate the time derivative of call prices and…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document describes using a normal, or Gaussian, model to price caplets and floorlets when rates can be negative. Under the stated setup, the forward rate evolves as a Gaussian martingale with constant absolute volatility, so its value at expiry has a…

Fixed incomeOptionsDerivatives pricingVolatility
Quant Q&A

The document explains why options on the same underlying can imply different volatilities across strikes even though the Black-Scholes model assumes constant volatility. It presents several interpretations: the smile can reflect model misspecification,…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The discussion considers whether high-dimensional Sobol sequences are practical for large market simulations and Monte Carlo pricing, where the required dimension may exceed the limits of common implementations. One answer points to established Sobol…

StatisticsBacktestingOptionsDerivatives pricing
Quant Q&A

The document explains why foreign exchange option data may arrive as volatility quotes and delta-based smile points rather than as a ready-made table of implied volatilities by strike and maturity. In much of the over-the-counter market, options are quoted…

ForexOptionsVolatilityDerivatives pricing
Quant Q&A

The document derives a static option replication for a payoff equal to the square of a non-dividend-paying stock’s terminal price. It rewrites the square as twice the integral, over strikes from zero to infinity, of the call payoff at each strike. This…

OptionsDerivatives pricingStatistics