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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

20,364 documents

Quant Q&A

The document examines Malliavin integration by parts for estimating option sensitivities in a diffusion model. It asks whether a Delta weight concentrated up to the first payoff observation loses relevant Brownian information, and how to extend the method to…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document describes the Heston and Rouwenhorst approach to decomposing stock returns into a world component, country effects, and industry effects. It uses monthly cross-sectional weighted least squares on individual stocks, with market capitalization as…

EquitiesFactor investingStatistics
Quant Q&A

The document asks how to find the best-performing stocks on an exchange, such as NYSE-listed stocks, over either a calendar year or user-selected dates. The suggested approach is to start from a Bloomberg function that ranks performers for a major index over…

EquitiesUS markets
Quant Q&A

The document asks whether a security with positive variance can rationally offer a return below the risk-free rate. The main response says it can be attractive as part of a portfolio if its returns are negatively correlated with other assets that have…

Portfolio constructionRisk managementStatistics
Quant Q&A

The document explains why the Hull–White short-rate model’s zero-coupon bond price at the initial time is independent of volatility and mean reversion. The model is calibrated to the observed market zero curve, so its initial bond prices reproduce that curve…

Fixed incomeVolatilityStatistics
Quant Q&A

The document discusses why derivatives are often valued under a risk-neutral measure and how this connects to no-arbitrage pricing and hedging. One response frames risk-neutral valuation as an abstract link between a replicable payoff and the cost of the…

OptionsDerivatives pricingArbitrageRisk management
Quant Q&A

The document clarifies the valuation signs behind an asset swap spread. In the described arrangement, the investor pays the price of a risky fixed-rate bond and receives its fixed cash flows, while entering a swap that converts those payments into…

Fixed incomeDerivatives pricing
Quant Q&A

The document presents an approximation for pricing a geometric Asian call under Heston stochastic volatility. It replaces the random variance path with its deterministic expected variance, then integrates that expected variance over the option horizon to…

OptionsDerivatives pricingVolatilityStatistics
Quant Q&A

The document explains why an American call on a non-dividend-paying stock has the same value as its European counterpart, even though a binomial pricing algorithm may compare early exercise value with continuation value at each node. The key distinction is…

OptionsDerivatives pricing
Quant Q&A

The document addresses why a basic GARCH model may be outperformed by realized GARCH or other realized-volatility models, especially when modeling intraday volatility. Its explanation focuses on information inputs rather than a strict difference between…

VolatilityStatisticsMachine learning
Quant Q&A

The document explains the coupon effect: fairly priced bonds with the same maturity but different coupons can have different yields to maturity when the spot-rate curve is not flat. Yield to maturity compresses a bond’s cash flows into a single rate and…

Fixed incomeRisk managementDerivatives pricing
Quant Q&A

The document distinguishes two stochastic-process assumptions often applied to stock prices. A martingale constrains the conditional expected future value to equal the present value, while a Markov process says the current state contains the information…

EquitiesStatisticsMomentum
Quant Q&A

The document raises a result from expected-utility theory: if an agent ranks contingent claims only by their mean and variance, then utility must be quadratic, and asks for a mathematical explanation. It does not provide a derivation, proof, or examples; it…

Statistics
Quant Q&A

The document explains how to obtain Black–Scholes implied volatility for a European option when the underlying follows a stochastic volatility jump model. Since the model lacks a closed-form log-return density and a direct analytical option price, the answer…

OptionsVolatilityDerivatives pricingStatistics
Quant Q&A

The note offers a possible historical explanation for a fixed fallback volatility used in a bond option-adjusted spread model. It says term-structure models from that period often relied on constant volatility assumptions, commonly calibrated to realized…

Fixed incomeVolatilityStatistics
Quant Q&A

The answer frames a forecast of a later stock price as a conditional expectation based on the latest observed price and an assumed price model. It uses geometric Brownian motion to illustrate the approach: under that model, the expected future price is the…

EquitiesStatistics
Quant Q&A

The explanation derives the differential of a function evaluated along a diffusion when its time argument runs backward, as in F(T−t, X_t). It first renames the expression as a function of the running time and state, then applies Itô’s formula using the…

Statistics
Quant Q&A

The document describes a forecasting setup for daily commodity prices using an LSTM network and predictor variables drawn from current and lagged observations. The author asks whether forecast accuracy can determine if the model is suitable for managing…

CommoditiesMachine learningRisk managementFutures
Quant Q&A

The document outlines post-crisis swap valuation using overnight indexed swap rates for discounting, followed by adjustments for counterparty credit, funding, and other costs. It contrasts this approach with older conventions that used government yields or…

Fixed incomeDerivatives pricingRisk management
Quant Q&A

The document addresses why substantial end-of-day share sales by market makers may occur without an obvious price decline. Its explanation is that market makers do not all start with the same inventory: those holding long positions may want to sell, while…

EquitiesMarket microstructureExecution
Quant Q&A

The discussion separates two ideas that are often conflated: a normal distribution need not have a zero mean, and observed equity returns need not follow a normal distribution. A normal distribution is described by its mean and standard deviation; the…

EquitiesStatisticsDerivatives pricing
Quant Q&A

The document clarifies how to compute a simple period return from consecutive values of a total return index. Divide the change in the index by its previous value: this expresses the increase or decrease relative to the starting level. The reply…

EquitiesStatistics
Quant Q&A

The document asks how node values for an American option on a small stock-price tree translate into a hedge. The accepted reply identifies the commenter’s suggested stock position as delta hedging: adjusting exposure to the underlying so that small price…

OptionsDerivatives pricingVolatilityRisk management