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
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

12,303 documents

Quant Q&A

The post investigates why annualized GARCH(1,1) volatility forecasts from Python's ARCH package matched observed volatility for a more volatile futures return series but appeared far too high for a less volatile series. The author initially assumed that…

FuturesVolatilityBacktestingStatistics
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
Quant Q&A

The answer outlines a possible explanation for technical patterns: prices may reflect how participants are positioned before news arrives, so a seemingly positive surprise can trigger selling if buyers are already committed and profit takers are ready.…

Technical indicatorsSentimentStatisticsVolatility
Quant Q&A

The note clarifies why a daily volatility formula may use closing prices without dividing by the sample degrees of freedom. In the geometric setting, the relevant price variable is the logarithm of the original price, so the daily change corresponds to a log…

VolatilityStatistics
Quant Q&A

The document explains how the at-the-money level for an interest-rate cap or floor is determined and why volatility quotes are often organized around it. The relevant level is the forward swap rate for a swap with the same maturity, schedule, and other terms…

OptionsFixed incomeVolatilityDerivatives pricing
Quant Q&A

The document explains the drift term used when simulating a stock price under the risk-neutral measure to price a European call by Monte Carlo. The simulated log return has mean (r − σ²/2)T and a random component scaled by volatility and the square root of…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

This question concerns execution after an investor has already decided to buy or sell a particular instrument. The investor has a short window of several days to seek a better price and will use a market order at the deadline if the trade remains unfilled.…

ExecutionTechnical indicatorsVolatility
Quant Q&A

This question asks how to transform implied volatilities indexed by strike and expiry into a surface indexed by delta and expiry. It highlights an apparent ambiguity: two options at the same expiry can appear to have nearly identical deltas while carrying…

OptionsDerivatives pricingArbitrageVolatility
Quant Q&A

This short question raises a central issue in option replication: transaction costs make the market incomplete, and asks what Leland’s modified volatility contributes to pricing and hedging. It also asks whether using that adjusted volatility allows an…

OptionsDerivatives pricingVolatilityExecution
Quant Q&A

The document considers forecasting returns and volatility from data sampled at intervals of one second or less. It notes a limitation of relying on ARMA and conventional GARCH alone: these time-series models do not directly represent order imbalance or order…

High-frequency tradingVolatilityStatisticsMarket microstructure
Quant Q&A

The document addresses how to revalue an options portfolio in a Monte Carlo VaR simulation when the underlying is simulated with a historical stochastic-volatility model such as GARCH. Its central distinction is that historical volatility of the underlying…

OptionsVolatilityRisk managementBacktesting
Quant Q&A

The document answers how to select the at-the-money strike when calibrating the volatility level in a shifted SABR model. The shift is added to both the forward and strike in the model’s implied-volatility calculation. Consequently, an option that is at the…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document presents a simulation of index prices using log returns and a GARCH(1,1) variance recursion. The author selects parameters using the lowest Akaike information criterion and generates repeated paths by drawing innovations from a normal…

StatisticsVolatilityBacktestingEquities
Quant Q&A

The document considers a borrower’s option to choose between a fixed-rate loan, a floating-rate loan, or cancellation after a decision window. It frames the choices as embedded options with value linked to the borrower’s credit spread, interest rates, and…

OptionsFixed incomeDerivatives pricingVolatility
Quant Q&A

The document solves an arithmetic Brownian motion with constant drift and volatility over an interval from the current time to a future time. Directly integrating the stochastic differential equation expresses the future state as the current state, plus the…

StatisticsVolatility
Quant Q&A

This discussion examines why longer-dated options can cost more even when implied volatility appears to fall with maturity. It cautions that implied volatility term structures vary: they may rise, fall, or fluctuate, including at the money. In the…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document compares a one-touch option, which pays when the underlying crosses a threshold at any time through maturity, with a binary option that pays when the underlying is above the threshold at maturity. It reports that the one-touch price is…

OptionsDerivatives pricingVolatility
Quant Q&A

The document presents a QuantLib setup for calibrating a one-factor Hull–White short-rate model to a EUR overnight-indexed discount curve and a normal-volatility surface for three-month Euribor swaptions. It describes fitting the model’s mean-reversion and…

Fixed incomeDerivatives pricingVolatilityBacktesting
Quant Q&A

The document distinguishes calculating implied volatility from choosing coordinates for interpolation and display. To calculate implied volatility from market prices, supply the actual spot, strike, maturity, rates, and dividend yield required by the pricing…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The document addresses whether the vanilla option portfolio used to replicate a variance swap still applies when the underlying pays dividends and the risk-free rate is nonzero. Its answer says the replication formula remains valid, provided the forward…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document explains why a long position in a standard European vanilla option generally has positive vega, even when the option is already in the money. Vega measures how an option’s value responds to a change in volatility. The key idea is that a vanilla…

OptionsVolatilityDerivatives pricing
Quant Q&A

The document derives a one-sided probability threshold for a standardized normal variable, using the inverse error function to obtain a value of about 1.28155 for 90% cumulative probability. It then asks whether this threshold, multiplied by daily volatility…

VolatilityStatisticsFutures
Quant Q&A

The document asks how to estimate monthly volatility from a year of five-minute stock prices, including whether to fit a GARCH-family model at the intraday or monthly frequency and how to scale the resulting volatility. Its only suggested procedure is to try…

EquitiesVolatilityStatistics