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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
Quantpedia
86 documents
TqSdk
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
Quantopian lectures
45 documents
Binance API docs
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 examines whether an option’s quoted price captures the cost of hedging when implied volatility varies across the life of the trade. In an illustrative case, volatility is expected to be concentrated in one part of the option’s life. The answer…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The document considers how to form a self-financing portfolio of bonds and stocks to replicate a basket of options, with each option written on a different underlying stock. It suggests constructing a replicating portfolio for each option separately and then…

OptionsEquitiesPortfolio constructionDerivatives pricing
Quant Q&A

The document asks whether a stochastic volatility model and its Gyöngy local volatility counterpart imply equal option prices and hedging costs. It describes the relationship as matching the terminal distribution of the underlying under the two processes,…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The document compares Heston stochastic volatility with Vanna–Volga (VV), an interpolation approach used to construct an FX implied volatility smile. It describes VV as requiring a small set of market volatility quotes, commonly at-the-money and 25-delta…

ForexOptionsVolatilityDerivatives pricing
Quant Q&A

The note concerns constructing an FX volatility surface when market quotes are expressed by moneyness or delta rather than by fixed absolute strikes. It describes limitations encountered with Python bindings for QuantLib and an Open Source Risk Engine…

OptionsForexVolatilityDerivatives pricing
Quant Q&A

The note explains why option models are often calibrated directly under a risk-neutral measure using observed option prices, without first specifying a corresponding physical-measure process. The calibrated model is used to extrapolate prices beyond the…

OptionsDerivatives pricingVolatilityRisk management
Quant Q&A

The document considers a one-period security with finitely many possible terminal prices, all above a call’s strike. Since the call is certain to finish in the money, its payoff in every state equals the security price minus the strike. This makes the call…

OptionsDerivatives pricingArbitrage
Quant Q&A

The document asks whether a discretely sampled arithmetic Asian option depends on forward implied volatility. It compares the question with forward-starting and barrier options, whose values can be sensitive to the volatility smile at a future reset date,…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document raises an interview question about how a digital, or binary, option is priced when the spot price is modeled with a normal distribution versus a lognormal distribution. It suggests that the lognormal model’s heavier right tail might make the…

OptionsDerivatives pricingStatistics
Quant Q&A

The document explains why an option’s time value is generally greatest near the money and declines as the option moves deep in or out of the money. It uses delta hedging for intuition: a long option hedged with the underlying can earn from rebalancing as the…

OptionsDerivatives pricingVolatility
Quant Q&A

The document explains the role of the vector parameter that maps a multidimensional affine state process to the scalar quantity in an option payoff. In the stated call-pricing expression, the payoff depends on an exponential of that projection, and the…

OptionsDerivatives pricingStatistics
Quant Q&A

The discussion asks whether Heston option prices have a convenient approximate Black–Scholes implied volatility formula, comparable to formulas used with other stochastic volatility models. Heston European option prices can be computed accurately through…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document addresses how to estimate implied volatility for expiries shorter than the first available maturity on a volatility surface, with very short dated binary options as the motivating use case. One proposed method is to hold volatility flat at the…

OptionsVolatilityDerivatives pricingArbitrage
Quant Q&A

The document presents ways to validate option pricing and Greek calculations across analytical, finite difference, binomial, and Monte Carlo methods. For models with closed form solutions, it recommends comparing against formulas and worked examples, while…

OptionsDerivatives pricingBacktestingStatistics
Quant Q&A

The document outlines a framework for choosing how often to rebalance a delta hedge during gamma scalping. Under geometric Brownian motion, it approximates the hedge adjustment as gamma times the underlying price move, then estimates trading costs by…

OptionsVolatilityExecutionRisk management
Quant Q&A

The document considers a payoff that pays the positive amount by which one correlated lognormal stock exceeds a strike, provided a second stock finishes between two bounds. It starts from the discounted expectation and explains how to split the payoff into a…

OptionsEquitiesDerivatives pricingStatistics
Quant Q&A

The document addresses how to adjust an implied-volatility surface when its quoted option prices contain small butterfly arbitrage violations. The specific issue is a discrete set of call prices across strikes that fails convexity, which can undermine later…

OptionsDerivatives pricingArbitrageVolatility
Quant Q&A

The document compares non-callable bank certificates of deposit with brokered CDs, focusing on the bank CD holder’s ability to withdraw early at par while paying an early withdrawal penalty. It models that feature as an American-style put embedded in a…

Fixed incomeDerivatives pricingOptionsRisk management
Quant Q&A

The document is a brief request for an introductory explanation of the constant elasticity of variance (CEV) model, including its dynamics, strengths and weaknesses, applications to payoff types or hybrid models, and calibration. The response does not…

Derivatives pricingStatisticsOptions
Quant Q&A

The document asks how to interpret the Longstaff–Schwartz least-squares Monte Carlo method for pricing American options, especially how its regression target relates to the backward recursion described by Tsitsiklis and Van Roy. The central distinction is…

OptionsDerivatives pricingStatisticsMachine learning
Quant Q&A

The document examines how often to rebalance a delta hedge for a European call under Black–Scholes assumptions and geometric Brownian motion. The questioner estimates the local hedging error from the option’s gamma and the squared price move, while…

OptionsDerivatives pricingExecutionRisk management
Quant Q&A

The document asks how to price an American-style Asian option whose exercise payoff uses the average underlying price over a recent rolling window. It explains why early exercise and path dependence complicate standard approaches: Monte Carlo and tree…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

Option open-interest figures published by financial websites are generally daily snapshots, which limits their direct use in intraday analysis. The post raises the question of whether intraday estimates or suitable vendor data are available, motivated by the…

OptionsMachine learningMarket microstructureVolatility
Quant Q&A

For European call and put options in a model that includes a continuous dividend yield, the zero-dividend case can be obtained by setting the yield parameter to zero. The response also points to a separate list of formulas, though it does not reproduce those…

OptionsDerivatives pricingVolatility