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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 explains a practical way to quote a binary call by approximating its payoff with a call spread. A seller of the binary can buy a spread around the strike; the spread’s cost provides a replication-based estimate of the option’s price. The…

OptionsDerivatives pricingMarket making
Quant Q&A

The question derives a replication-error expression in which the difference between assumed local volatility and realized volatility is multiplied by option gamma over time. It interprets the sign: for positive gamma, assuming volatility above realized…

OptionsVolatilityRisk managementDerivatives pricing
Quant Q&A

The discussion clarifies how risk-neutral pricing connects to delta hedging and the Black–Scholes equation. In a standard setup, a self-financing hedged portfolio is locally risk-free, so its return is tied to the financing rate. The stock’s real-world…

OptionsDerivatives pricingStatisticsRisk management
Quant Q&A

The document asks how to distinguish a market-price-based delta from a model-price-based delta for options on Treasury futures. It describes delta as the option price's sensitivity to the underlying futures price and proposes estimating that sensitivity by…

OptionsFuturesFixed incomeRisk management
Quant Q&A

The discussion asks why equity index implied volatility surfaces often show a pronounced downside skew rather than a smile, and why smiles may have appeared historically. One explanation is that index volatility combines the volatilities of its constituents…

OptionsEquitiesVolatility
Quant Q&A

The document explains how to approximate the curvature of call prices around an at-the-money strike when option strikes are unevenly spaced. Since the risk-neutral density is related to the second derivative of call price with respect to strike, the method…

OptionsDerivatives pricingStatistics
Quant Q&A

The document investigates why QuantLib’s finite-difference Black–Scholes engine produces American put prices that diverge from a reference spreadsheet when discrete cash dividends are scheduled near expiration. The question reports that call prices are close…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document presents a slow nested-loop implementation for pricing European calls, Asian options, digital calls, and up-and-in barrier calls under the Merton jump-diffusion model. It motivates the problem as a comparison with the exponential variance-gamma…

OptionsDerivatives pricingMachine learningBacktesting
Quant Q&A

The discussion considers how to estimate the expected termination time of an American put, counting maturity as the termination date when the holder never exercises early. One proposed approximation uses the time-zero price difference between otherwise…

OptionsDerivatives pricingStatistics
Quant Q&A

The document examines delta hedging a quanto call when the underlying is priced in a foreign currency and the portfolio is accounted for in a domestic currency. A hedge based only on the foreign share count misses the currency conversion: the domestic value…

OptionsForexDerivatives pricingRisk management
Quant Q&A

The document derives a lower bound for a European put on a non-dividend-paying stock by comparing two portfolios. One portfolio holds the put and one share; the other holds a zero-coupon bond that pays the strike at expiration. At maturity, the put-stock…

OptionsDerivatives pricingArbitrage
Quant Q&A

The document asks how a delta-hedged portfolio of two options leads to a Black–Scholes pricing equation, including a term for the underlying asset’s market price of risk. It writes the portfolio as one option minus a delta-scaled position in another, then…

OptionsDerivatives pricingRisk managementStatistics
Quant Q&A

The document considers fitting an implied-volatility curve to intraday option observations, where data become sparse and variable at extreme out-of-the-money strikes. The question is whether unusual observations can be discounted and whether option-market…

OptionsVolatilityStatistics
Quant Q&A

The document asks whether a closed-form valuation exists for an American down-and-out call whose principal amortizes linearly with elapsed time if the option is knocked out. It frames the payoff as a possible time-dependent rebate and compares the problem…

OptionsDerivatives pricing
Quant Q&A

The document derives a self-financing replicating portfolio for a European put in a Black-Scholes market with a risky asset and a deterministic bank account. Applying Itô’s lemma to the option value and matching the diffusion terms identifies the risky-asset…

OptionsDerivatives pricingRisk management
Quant Q&A

The document explains how to build and plot a Heston model volatility surface using Python QuantLib. The example creates a Heston process from spot, flat risk-free and dividend curves, and model parameters, then wraps it in a Heston model and passes it to a…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document explains a Monte Carlo check for an implementation of Dupire local volatility. Simulated underlying paths use the local volatility evaluated at the current simulated spot and time, with the process initialized at the market spot. For each…

OptionsDerivatives pricingVolatilityBacktesting
Quant Q&A

The note explains a market convention for describing the right side of an implied volatility smile as call skew, even though put-call parity links those prices to in-the-money puts. The answer suggests that traders often build the smile from at-the-money and…

OptionsVolatilityMarket microstructureDerivatives pricing
Quant Q&A

The note compares delta choices for hedging short-dated at-the-money options in an index dispersion trade, which pairs long single-stock variance with short index variance. It explains that using Black–Scholes delta with the option’s initial implied…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The document explains why the Black–Scholes call price contains two different probabilities: N(d2), the risk-neutral probability that the option finishes in the money, and N(d1), the corresponding probability under a measure associated with using the stock…

OptionsDerivatives pricingStatistics
Quant Q&A

The document explains that option traders can seek directional gains as well as profit from volatility. Buying calls can express a bullish view with less upfront capital than buying the underlying or futures, while limiting the buyer’s loss to the premium…

OptionsFuturesVolatilityDerivatives pricing
Quant Q&A

The document asks how to choose volatility when using Black–Scholes deltas to hedge an option, and whether updating the volatility input with each day’s implied volatility changes expected profit and loss or its variance. It contrasts implied volatility,…

OptionsVolatilityDerivatives pricingRisk management
Quant Q&A

The document frames a relative-value trade between American-style options on different futures, potentially quoted in different currencies. The proposed view is to sell volatility in the option with higher implied volatility and buy volatility in the other,…

OptionsFuturesVolatilityDerivatives pricing