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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 document considers a cash-or-nothing claim that pays when one of two risky assets exceeds the other at maturity. Both assets are modeled with geometric Brownian motion driven by the same Wiener process, alongside a risk-free asset. The proposed pricing…

OptionsDerivatives pricingMulti-asset
Quant Q&A

The discussion asks whether an unhedgeable option should be valued using real-world probabilities rather than risk-neutral pricing. Its central point is that risk-neutral valuation relies on relationships supported by trading and hedging in the underlying.…

OptionsDerivatives pricingRisk management
Quant Q&A

Lévy processes do not necessarily have probability densities, and even when a density exists it may not have a closed-form expression. The document contrasts this with familiar exponential Lévy examples, including geometric Brownian motion and a…

OptionsDerivatives pricingStatistics
Quant Q&A

This discussion addresses whether SABR should be calibrated directly to cap quotes or to the individual caplets that compose those caps. Its proposed workflow is to first strip market cap quotes into a caplet volatility surface, then calibrate SABR…

Fixed incomeOptionsVolatilityDerivatives pricing
Quant Q&A

The document gives simple bounds for American calls and puts on an underlying with continuous dividend yield. Because an American option can be exercised at maturity, its value is at least that of the corresponding European option, so the European lower…

OptionsDerivatives pricingEquities
Quant Q&A

The document explains an approximation from options literature that links the volatility of hedging error to the uncertainty in an estimated volatility. For a lognormal stock process sampled at discrete intervals, the stated uncertainty is proportional to…

OptionsVolatilityStatistics
Quant Q&A

The document explains how to approach pricing a barrier option on a basket when the available QuantLib Monte Carlo engines do not support both features together. It uses a worst-of down-and-in put as an example of the unsupported combination. The suggested…

OptionsDerivatives pricingEquitiesBacktesting
Quant Q&A

The discussion asks why higher-order Greeks are not seen more often in practice. The answer distinguishes Black–Scholes use for quoting implied volatility from more complex models used to price products and measure their risks. Exotic options may require…

OptionsDerivatives pricingRisk management
Quant Q&A

The discussion considers whether Monte Carlo simulation can calibrate the Heston stochastic volatility model and which discretization to use. One answer recommends calibrating vanilla European options with the model’s known characteristic function and…

Derivatives pricingVolatilityOptionsStatistics
Quant Q&A

The document explains the basic construction of a bull spread using European calls with a common expiration. For the two-call example, the proposed position buys the lower-strike call and sells the higher-strike call. The intuition offered is that the…

OptionsDerivatives pricingPosition sizing
Quant Q&A

The document examines the expiry payoff and a proposed Black-style valuation for a payer option on a credit default swap index. It identifies two issues: whether the payoff’s running-spread component should reflect the surviving index factor, and how the…

OptionsDerivatives pricingRisk management
Quant Q&A

The document discusses how someone without access to an OTC derivatives desk can study prices and payoff risks for customized options. It explains that dealers generally quote only to established desk customers, who may need product-specific legal agreements…

OptionsDerivatives pricingVolatilityCommodities
Quant Q&A

For European interest rate options, the document distinguishes pricing from hedging. Vanilla prices across strikes can be represented by an implied volatility surface or interpolated total variance, so stochastic volatility is not required to price each…

Fixed incomeOptionsVolatilityDerivatives pricing
Quant Q&A

The document questions whether risk-neutral valuation remains adequate as derivatives become actively traded. It argues that the classical view treats derivatives as replicating portfolios, while trading in derivatives can produce volatility skews, smiles,…

Derivatives pricingOptionsRisk managementStatistics
Quant Q&A

The document asks why an up-and-out call is said to have a lower delta than a standard call, while a down-and-out call is said to have a higher delta. The answers reason from how the underlying’s movement affects both the call payoff and the chance that the…

OptionsDerivatives pricingVolatility
Quant Q&A

The document explains a measure change from the risk-neutral measure to an alpha measure used with a power numeraire in option pricing. It starts from a geometric Brownian motion for the underlying and expresses the Radon–Nikodym derivative in terms of the…

OptionsDerivatives pricingStatistics
Quant Q&A

The document examines whether bookmaker odds can inform option prices when an underlying asset moves up or down in response to a binary event. The proposed setup combines a real-world probability for the positive event outcome with an assumed expected…

OptionsDerivatives pricingEvent-drivenStatistics
Quant Q&A

The document shows how to calculate positions in two derivatives that offset an option portfolio’s delta and gamma. It sets up a pair of linear equations: the hedge instruments’ weighted sensitivities must cancel the portfolio’s existing delta and gamma.…

OptionsDerivatives pricingRisk management
Quant Q&A

The document considers whether characteristic function methods used to price options can be adapted to interest rate derivatives, especially swaptions. It explains the key difficulty: many interest rate models describe short rates or zero coupon bonds, while…

OptionsFixed incomeDerivatives pricingStatistics
Quant Q&A

The discussion addresses how to set an upper-domain boundary when numerically pricing options with finite differences. It recommends using linear behavior in an extreme model state as a generic boundary approximation for many products. In mathematical terms,…

OptionsDerivatives pricingVolatilityBacktesting
Quant Q&A

The discussion distinguishes estimating implied volatility from observed option prices from using machine learning to approximate prices for complex derivatives. Inverting a standard option pricing model to find implied volatility is described as a simple,…

OptionsVolatilityDerivatives pricingMachine learning
Quant Q&A

The document compares a call credit spread and a put debit spread, whose expiration payoff diagrams can appear similar. It explains that the call spread places both strikes above spot, while the put spread places both below spot. The call credit spread…

OptionsDerivatives pricingRisk management
Quant Q&A

The document poses a risk measurement question about a portfolio of plain interest rate floor options. It asks whether the change in economic value under a one basis point parallel rate shock should equal the sum of value changes under one basis point shocks…

OptionsFixed incomeDerivatives pricingRisk management
Quant Q&A

The document examines a proposed strategy for writing a call option: hold the stock when its price exceeds a time-adjusted strike threshold and otherwise sell it. The author tries to address the time value of money by lowering the threshold toward expiry and…

OptionsEquitiesArbitrageDerivatives pricing