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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 document discusses potential drawbacks of using deep learning to calibrate and price a full implied-volatility surface. It notes that neural methods can produce very fast calibration at application time, while training may involve substantial…

OptionsMachine learningDerivatives pricingBacktesting
Quant Q&A

The document addresses why an at-the-money call’s familiar delta of about one half does not match the full payoff change in a large, single-step move. Delta is a local sensitivity: in the theoretical continuous-time setting, it approximates how an option’s…

OptionsDerivatives pricingRisk management
Quant Q&A

The document explains why a stochastic local volatility model can combine features of local volatility and stochastic volatility. It writes the asset’s instantaneous volatility as a stochastic factor multiplied by a state- and time-dependent local factor.…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document addresses whether CME options on one-month SOFR futures continue trading during the month when the underlying SOFR rate is measured. This matters for implied volatility modeling: if trading overlaps the averaging period, remaining uncertainty…

OptionsFuturesFixed incomeVolatility
Quant Q&A

The document presents an arbitrage argument for convexity of European call option prices as a function of strike. If the price at a middle strike were at least as high as the average prices of two equally spaced neighboring strikes, a trader could buy the…

OptionsDerivatives pricingArbitrage
Quant Q&A

The document explains why option delta is generally tied to a particular underlying asset, so a portfolio containing options on different stocks does not have a single ordinary delta obtained by simply adding the component deltas. For a portfolio whose value…

OptionsEquitiesRisk managementPortfolio construction
Quant Q&A

The document asks how to assign equal risk contributions across asset classes in a portfolio that includes nonlinear instruments such as options. One response recommends first converting each instrument into a return stream, estimating risk parameters from…

Risk managementPortfolio constructionOptionsStatistics
Quant Q&A

The document explains calibration as choosing a model’s parameters so its prices fit observed prices for selected liquid options. A common formulation minimizes the aggregate pricing error across instruments with specified characteristics such as strike and…

OptionsVolatilityDerivatives pricingMarket making
Quant Q&A

The document outlines the usual discrete-time Black–Scholes delta hedge for a European call on a stock. It sells the option, offsets its delta with a stock position, and places the residual value in a risk-free account. At each step, the stock price is…

OptionsFixed incomeDerivatives pricingRisk management
Quant Q&A

The note evaluates a proposed way to choose an expiration for uncovered puts: maximize option premium divided by days to expiration. It argues that this ratio tends to mechanically favor shorter-dated contracts, because option value generally does not rise…

OptionsVolatilityDerivatives pricing
Quant Q&A

The note asks how to obtain the first, second, and fourth cumulants of the variance gamma with stochastic arrival model for use in Fourier-cosine option pricing. It defines the model through a characteristic function built from a variance gamma process with…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The note explains why multiplying an option’s current theta by the days remaining can imply more decay than its current time value. It uses a deep in-the-money call as an example: most of its price is intrinsic value, while the quoted time value is small and…

OptionsDerivatives pricingVolatility
Quant Q&A

The document questions an apparent U-shaped implied-volatility pattern in SPX options, especially at far out-of-the-money strikes. A response compares the displayed pattern with a snapshot of implied volatilities for weekly options, reporting generally…

OptionsVolatilityDerivatives pricingUS markets
Quant Q&A

The document examines how to estimate expiration probabilities and expected value for a two-leg put credit spread. It divides outcomes into three price regions: above the short strike, between the strikes, and below the long strike. The author asks whether…

OptionsDerivatives pricingStatistics
Quant Q&A

The document explores how to derive a variational or weak formulation for the Black–Scholes partial differential equation. Its central issue is integration by parts in the diffusion term, where the coefficient depends on the underlying price variable.…

OptionsDerivatives pricingStatistics
Quant Q&A

The document addresses how to construct an implied volatility smile from US equity options when no traded option has a strike exactly equal to the underlying price. It asks how to estimate at-the-money volatility and connect out-of-the-money put and call…

EquitiesOptionsVolatilityDerivatives pricing
Quant Q&A

The document considers how to turn over-the-counter FX option quotes, reported at different strikes and maturities, into a usable volatility surface. One proposed workflow starts from standard delta quotes, converts each maturity’s deltas to strikes using…

ForexOptionsVolatilityDerivatives pricing
Quant Q&A

The document investigates a negative value appearing in a plotted down-and-out call price when the underlying starts below the barrier. It presents a Black–Scholes barrier pricing expression, defines its parameters, and compares that expression with an…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document examines how credit risk and contract terms affect the Black-76 valuation of options on corporate bonds. It highlights that the forward bond price must reflect the bond’s risky market value and financing or discounting assumptions; treating a…

Fixed incomeOptionsDerivatives pricing
Quant Q&A

The question seeks a way to estimate the risk-neutral variance of an underlying stock’s gross return and considers option-implied distributions alongside estimates made from data under the physical measure. One reply assumes geometric Brownian motion under…

OptionsDerivatives pricingStatisticsVolatility
Quant Q&A

The note addresses why implied volatilities calculated from option prices differ across strikes. It explains that Black–Scholes implied volatility is the volatility input that reproduces a given market price under the model; when the model assumes a single…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document asks why a strongly path-dependent option’s value is written as a function of the asset price, time, and an accumulated quantity. The payoff depends on a path summary defined as the time integral of a function of the asset price and time. Since…

OptionsDerivatives pricingStatistics
Quant Q&A

The question describes using QuantLib to price options from a dataset containing contract start dates, expirations, and strikes. The proposed workflow groups contracts by expiration, supplies implied volatilities and market inputs to Heston model helpers,…

OptionsDerivatives pricingVolatility
Quant Q&A

The document considers ways to hedge a long SPY position against a substantial decline: a volatility-linked ETF, an inverse leveraged ETF, and put options. It sketches possible gains and costs for each, but the proposed payoff estimates are uncertain and are…

EquitiesOptionsVolatilityRisk management