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
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

21,023 documents

Quant Q&A

Ross recovery seeks to infer transition probabilities and risk preferences from state prices by removing a stochastic discount factor. The discussion distinguishes two questions: when a positive pricing measure can be transformed into a probability measure,…

StatisticsFixed incomeRisk management
Quant Q&A

The document addresses numerical instability when a finite-difference method prices a call option using its terminal payoff, which has a kink at the strike. Near that point, a coarse grid can make a central approximation to the second derivative very large,…

OptionsDerivatives pricingStatistics
Quant Q&A

The document explains how to estimate the inputs of a Cobb–Douglas production function from observations of company output, capital, labor, and materials. Taking logarithms turns the multiplicative model into a linear regression: the input quantities are…

Statistics
Quant Q&A

The document gives a closed-form expression for the probability that an arithmetic Ornstein–Uhlenbeck process reaches one of two barriers first. It considers a process starting between a lower and upper level, with positive mean-reversion speed, and…

StatisticsMean reversion
Quant Q&A

The document explains how to test whether an event day produced abnormal stock returns across a group of companies. It uses a market model fitted over an estimation window, then defines the daily average abnormal return as the cross-sectional mean across the…

Event-drivenEquitiesStatisticsBacktesting
Quant Q&A

The document asks how to compute higher moments of the time integral of an exponential Brownian motion, a quantity relevant to arithmetic Asian options. It first gives the expected value, then presents a general expression for the m-th moment using divided…

OptionsDerivatives pricingStatistics
Quant Q&A

The post asks how to build a yield curve from three-month interest-rate futures, using Euribor as an example, and whether cubic-spline interpolation is available in Python. It points to a reference on multi-curve bootstrapping and a worked Python…

Fixed incomeFuturesStatistics
Quant Q&A

The post asks whether a GARCH model implies zero covariance between a squared return and a lagged return. It identifies the conditional variance as a function of past squared returns and variance, then considers how that dependence affects the expectation…

StatisticsVolatility
Quant Q&A

The document explains how to infer a compounding frequency from a quoted nominal annual rate and an effective annual yield. It considers an account advertised at a nominal rate of 9.5% with an annual yield of 9.84%, then applies the quarterly compounding…

Fixed incomeStatistics
Quant Q&A

The response interprets personal finance decisions broadly, covering choices such as saving, pension planning, purchases, and risk taking, along with rational and irrational behavior. It recommends searching under behavioral economics and related terms about…

StatisticsRisk management
Quant Q&A

The answer proposes a game-theoretic explanation for possible inflation in bond credit ratings. It assumes that agencies compete for rating work, issuers pay for the service, and issuers prefer agencies that offer higher ratings because those ratings can…

Fixed incomeStatistics
Quant Q&A

The document asks how large institutional stock sales affect prices over weeks, months, or years, including the lasting losses that other large holders might face. It raises questions about whether permanent impact relates to peak temporary impact, how…

EquitiesMarket microstructureExecutionStatistics
Quant Q&A

The document considers whether two cointegrated price series can be combined into a stationary spread and modeled with an Ornstein-Uhlenbeck process. The proposed workflow estimates a hedge coefficient through regression, constructs the residual spread, and…

Pairs tradingMean reversionStatisticsEquities
Quant Q&A

The document outlines several mechanisms that can produce negative autocorrelation in short-horizon returns. The classic explanation is bid-ask bounce: trades initiated by buyers and sellers alternate between ask and bid transaction prices, creating…

EquitiesHigh-frequency tradingMarket microstructureStatistics
Quant Q&A

The document considers how to improve an Ornstein–Uhlenbeck model of EUR/USD when it understates large two-hour price ranges. The author has calibrated the process to historical mean, standard deviation, and total absolute variation, then explored adding…

ForexStatisticsVolatilityMarket microstructure
Quant Q&A

The document derives a way to constrain a fund’s next weekly return so that its rolling five-year, annualized ex-post volatility is less likely to exceed a chosen threshold. It treats the historical weekly returns as fixed, assumes the next return is…

VolatilityRisk managementStatisticsPosition sizing
Quant Q&A

The document shows how to price a payoff of the form (S_T f(S_T))^+ by changing from the money-market numeraire to the stock numeraire. Starting with a risk-neutral geometric Brownian motion, it defines the new measure using the discounted stock as the…

Derivatives pricingOptionsStatistics
Quant Q&A

The document describes how to enumerate every sequence of up, middle, and down moves in a trinomial tree. Its example uses recursive depth-first search: extend a partial path with each of the three moves until the desired number of steps is reached, then…

BacktestingStatistics
Quant Q&A

The document explains leptokurtosis as a return distribution with heavier tails than a normal distribution, which means extreme outcomes occur with greater probability. For investors, that can translate into a higher chance of unusually large gains or…

StatisticsRisk managementVolatility
Quant Q&A

The document raises a portfolio optimization problem in which tracking error is constrained using a sample covariance matrix. It describes a case with 1,000 assets but only 60 monthly return observations, producing a covariance estimate that is not positive…

Portfolio constructionStatisticsRisk management
Quant Q&A

The question concerns building an inflation-swap curve with QuantLib rate helpers and encountering an error because multiple instruments share a pillar date. The practical diagnostic is to inspect each helper’s pillar date, which is the date used as a curve…

Fixed incomeDerivatives pricingStatistics
Quant Q&A

The exchange addresses where to obtain financial and related company data for U.S.-listed firms, including balance sheets, income statements, cash flows, market information, and records relevant to bankruptcy, fraud, and governance. One answer points to a…

EquitiesUS marketsStatistics
Quant Q&A

The discussion distinguishes contemporaneous factor models from forecasting models for portfolio optimization. In the Fama–French three-factor setup described, an asset’s return is related to factor returns from the same period. That relationship can help…

Factor investingPortfolio constructionStatistics
Quant Q&A

The document asks whether initial nonstationarity in a simulated VAR series matters when estimating a copula with kernels. It describes an experiment in a cited paper using repeated series of length 1,024 and asks whether every observation, including early…

StatisticsMulti-asset