AML Markets Glossary
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Markets Glossary

Key Insights

  • Key terms and definitions for financial markets, quantitative analysis, and portfolio management — sourced from SEC, BIS, AQR, and MSCI research.

Key terms and definitions for financial markets, quantitative analysis, and portfolio management — sourced from SEC, BIS, AQR, and MSCI research.

This glossary covers key concepts in markets as used across AcaciaFund's research, learning materials, and knowledge base.

Core Concepts

AI Hardware Trends

AI Hardware Trends Also: AI chips, GPU market, AI accelerators

Algorithmic Trading

Algorithmic Trading Also: algo trading, automated trading, execution algorithms

Alternative Data in Markets

Alternative Data in Markets Also: alt data, satellite imagery, credit card data, web scraping

Asset Pricing Models

Asset Pricing Models Also: CAPM, asset pricing, discount factor models

Behavioral Finance

Behavioral Finance Also: behavioral economics, behavioral biases

Black-Scholes Options Pricing Model

The Black-Scholes model provides a closed-form solution for pricing European options, establishing the theoretical foundation for modern options markets. It shows that option prices can be derived from a no-arbitrage condition using a continuously rebalanced hedge portfolio. Also: Black-Scholes-Merton, BSM, options pricing model, black-scholes-1973, black-scholes-formula

Capital Asset Pricing Model (CAPM)

The Capital Asset Pricing Model (CAPM), developed by Sharpe (1964), Lintner (1965), and Mossin (1966), provides a theoretical framework for relating expected return to systematic risk. The key insight is that only non-diversifiable (market) risk is priced, and an asset's expected return is linearly related to its beta with the market portfolio. Also: CAPM, Sharpe-Lintner model, security market line, SML, capital-asset-pricing-model

Carry Trade Strategies

Carry Trade Strategies Also: currency carry, FX carry, interest rate differential

Commodity Trading Strategies

Commodity Trading Strategies Also: commodity futures, commodity hedging

Cross-Asset Trading

Cross-Asset Trading Also: multi-asset, asset allocation, correlation trading

Cryptocurrency Markets

Cryptocurrency Markets Also: digital assets, crypto trading, blockchain markets

Dark Pools & ATS

Dark Pools & ATS Also: dark liquidity, ATS, block trading, alternative trading system

Design

A concept related to design Also: design

ESG Double Materiality

ESG Double Materiality Also: double materiality, CSRD materiality, impact materiality, financial materiality

ESG Investing

ESG Investing Also: ESG, sustainable investing, responsible investing

ETF Creation & Redemption

ETF Creation & Redemption Also: ETF arbitrage, creation unit, AP authorized participant

ETF Trading & Structure

ETF Trading & Structure Also: exchange traded funds, ETF creation redemption, ETF arbitrage

Earnings Analysis

Earnings Analysis Also: earnings season, earnings reports

Efficient Market Hypothesis (EMH)

The Efficient Market Hypothesis, formalized by Eugene Fama (1970), states that asset prices fully reflect all available information. It comes in three forms: weak (past prices), semi-strong (public information), and strong (all information, including insider). The EMH provides the benchmark against which all market anomalies and behavioral finance findings are measured. Also: EMH, Fama 1970, efficient markets, random walk hypothesis, market efficiency

Equity & Stock Basics

Equity & Stock Basics Also: stocks, shares, equity securities, common stock

Event-Driven Trading

Event-Driven Trading Also: corporate actions, M&A arbitrage, event study

Execution Algorithms

Execution Algorithms Also: VWAP, TWAP, implementation shortfall, smart order routing

FX Market Structure

FX Market Structure Also: forex, spot FX, FX swap, FX prime brokerage

Factor Investing

Factor Investing Also: smart beta, factor models

Fama-French Factor Models

The Fama-French three-factor model (1993) extends the CAPM by adding size (SMB) and value (HML) factors to explain cross-sectional variation in stock returns. The five-factor model (2015) adds profitability (RMW) and investment (CMA) factors, capturing the empirical patterns that the original CAPM could not explain. Also: Fama-French 3-factor, Fama-French 5-factor, three-factor model, five-factor model, FF3, FF5, fama-french-model

Fixed Income Markets

Fixed Income Markets Also: bond markets, fixed income, credit markets

Funding

A concept related to funding Also: funding

Glosten-Milgrom (1985) Bid-Ask Model

The Glosten-Milgrom model explains the bid-ask spread as a consequence of adverse selection: market makers widen spreads to protect themselves against informed traders, making the spread a measure of information asymmetry in the market. Also: Glosten-Milgrom model, adverse selection model, bid-ask model 1985, glosten-milgrom

Hawkes Process

Hawkes Process Also: Hawkes self-exciting process

Hedge Fund Strategies

Hedge Fund Strategies Also: hedge funds, alternative investments, long short equity

High Frequency Trading

High Frequency Trading Also: HFT, algorithmic trading, low latency

Implied Volatility Surface

Implied Volatility Surface Also: IV surface, vol surface

Kyle (1985) Insider Trading Model

Kyle's 1985 model of informed trading and price impact, establishing the theoretical foundation for how an informed trader optimally splits orders and how market makers set prices under information asymmetry. Also: Kyle 1985, insider trading model, continuous auctions, kyle-lambda, kyle-model

Limit Order Book

Limit Order Book Also: LOB, order book

Machine Learning in Markets

Machine Learning in Markets Also: ML trading, deep learning markets, AI trading

Macroeconomic Analysis

Macroeconomic Analysis Also: macro analysis, economic indicators

Market Data Infrastructure

Market Data Infrastructure Also: market data, TAQ data, market feed, OPRA

Market Impact Models

Market Impact Models Also: price impact, market impact cost, implementation shortfall

Market Indices

Market Indices Also: S&P 500, Dow Jones, index construction, benchmark indices

Market Making

Market Making Also: liquidity provision, market maker, quote-driven trading

Market Microstructure

Market Microstructure Also: microstructure

Market Participants

Market Participants Also: retail investors, institutional investors, market makers, HFT firms

Market Regime Detection

Market Regime Detection Also: regime switching, market states, HMM, volatility regime

Market Surveillance

Market Surveillance Also: insider detection, market manipulation, wash trading

Mean Reversion Strategies

Mean Reversion Strategies Also: statistical arbitrage, pairs trading, reversal trading

Momentum & Trend Following

Momentum & Trend Following Also: time-series momentum, cross-sectional momentum, trend following

Options Trading Strategies

Options Trading Strategies Also: options strategies, derivatives trading

Order Book Dynamics

Order Book Dynamics Also: LOB, limit order book, order flow, order book depth

Order Types & Execution

Order Types & Execution Also: market order, limit order, stop loss, order routing

Portfolio Optimization

Portfolio Optimization Also: asset allocation, portfolio construction

Prospect Theory (Kahneman & Tversky 1979)

Prospect Theory, developed by Daniel Kahneman and Amos Tversky (1979), describes how people make decisions under risk. It shows that individuals evaluate gains and losses relative to a reference point, are loss-averse (losses hurt ~2x more than equivalent gains feel good), and overweight small probabilities while underweighting large ones. Also: Kahneman-Tversky 1979, loss aversion theory, prospect theory, cumulative prospect theory, kahneman-tversky

Quantitative Trading

Quantitative Trading Also: quant trading, systematic trading, quantitative strategies, q-fin, math.fin

Research

A concept related to research Also: research

Retail Trading Trends

Retail Trading Trends Also: retail investors, meme stocks, retail flow

Risk Parity

Risk Parity Also: risk-balanced portfolio

Securities Lending

Securities Lending Also: stock loan, short selling, borrow rate

Semiconductor Industry

Semiconductor Industry Also: chip industry, semiconductor supply chain

Statistical Arbitrage

Statistical Arbitrage Also: stat arb, pairs trading, mean reversion

Supply Chain Analysis

Supply Chain Analysis Also: supply chain risk

Technical Analysis

Technical Analysis Also: chart patterns, technical indicators

Trading Venues

Trading Venues Also: stock exchanges, NYSE, NASDAQ, dark pools, ATS

VPIN Toxicity

VPIN Toxicity Also: Volume-Synchronized Probability of Informed Trading

Volatility Arbitrage

Volatility Arbitrage Also: vol arb, dispersion trading, volatility strategies

Volatility Trading

Volatility Trading Also: VIX trading, vol arbitrage, volatility strategies

Relationships

  • AI Hardware Trends: influences Semiconductor Industry, requires Semiconductor Industry
  • Algorithmic Trading: related_to High Frequency Trading, requires Market Impact Models, requires Execution Algorithms
  • Alternative Data in Markets: enables Market Microstructure, requires Technical Analysis
  • Asset Pricing Models: requires Portfolio Optimization, related_to Factor Investing
  • Behavioral Finance: influences Market Microstructure, influences Technical Analysis, requires Portfolio Optimization
  • Black-Scholes Options Pricing Model: part_of Asset Pricing Models, enables Options Trading Strategies
  • Capital Asset Pricing Model (CAPM): part_of Asset Pricing Models, enables Portfolio Optimization
  • Carry Trade Strategies: requires Fixed Income Markets, requires Quantitative Trading
  • Commodity Trading Strategies: related_to Macroeconomic Analysis, requires Market Participants
  • Cross-Asset Trading: implements Portfolio Optimization, requires Portfolio Optimization
  • Cryptocurrency Markets: influences Market Microstructure, requires Market Participants
  • Dark Pools & ATS: related_to Order Book Dynamics, requires Trading Venues
  • ESG Double Materiality: regulates ESG Investing, requires ESG Investing
  • ESG Investing: implements Factor Investing, requires Portfolio Optimization
  • ETF Creation & Redemption: requires ETF Trading & Structure, enables Order Book Dynamics, requires Market Participants
  • ETF Trading & Structure: requires Market Microstructure, requires Limit Order Book, requires ETF Creation & Redemption
  • Earnings Analysis: related_to Macroeconomic Analysis, requires Equity & Stock Basics
  • Efficient Market Hypothesis (EMH): part_of Asset Pricing Models
  • Equity & Stock Basics: requires Market Participants
  • Event-Driven Trading: implements Earnings Analysis, requires Quantitative Trading
  • Execution Algorithms: implements Algorithmic Trading, requires Order Types & Execution
  • FX Market Structure: related_to Market Microstructure, requires Market Participants
  • Factor Investing: implements Portfolio Optimization, requires Portfolio Optimization
  • Fama-French Factor Models: enables Asset Pricing Models, part_of Factor Investing
  • Fixed Income Markets: related_to Macroeconomic Analysis, requires Market Participants
  • Glosten-Milgrom (1985) Bid-Ask Model: enables Market Making, part_of Market Microstructure
  • Hawkes Process: influences Market Microstructure, requires High Frequency Trading
  • Hedge Fund Strategies: implements Portfolio Optimization, requires Portfolio Optimization
  • High Frequency Trading: enables Market Microstructure, requires Market Microstructure
  • Implied Volatility Surface: related_to Market Microstructure, requires Volatility Trading
  • Kyle (1985) Insider Trading Model: enables Market Impact Models, part_of Market Microstructure
  • Limit Order Book: requires Order Book Dynamics
  • Machine Learning in Markets: enables Alternative Data in Markets, requires ml-pipeline, requires Quantitative Trading
  • Macroeconomic Analysis: requires Market Indices
  • Market Data Infrastructure: requires Limit Order Book, requires data-pipeline, requires Trading Venues
  • Market Impact Models: part_of Market Microstructure, related_to High Frequency Trading, requires Market Microstructure
  • Market Indices: requires Equity & Stock Basics
  • Market Making: enables Order Book Dynamics, requires Execution Algorithms
  • Market Microstructure: requires Limit Order Book
  • Market Regime Detection: enables Implied Volatility Surface, requires Machine Learning in Markets
  • Market Surveillance: detects Market Impact Models, requires data-pipeline, requires Market Microstructure
  • Mean Reversion Strategies: implements Statistical Arbitrage, requires Statistical Arbitrage
  • Momentum & Trend Following: implements Technical Analysis, requires Quantitative Trading
  • Options Trading Strategies: requires Implied Volatility Surface, influences Market Microstructure, requires Volatility Trading
  • Order Book Dynamics: implements Limit Order Book, requires Order Types & Execution
  • Order Types & Execution: requires Equity & Stock Basics
  • Portfolio Optimization: implements Risk Parity, requires Equity & Stock Basics
  • Prospect Theory (Kahneman & Tversky 1979): part_of Behavioral Finance
  • Quantitative Trading: implements Algorithmic Trading, requires Algorithmic Trading
  • Retail Trading Trends: requires Behavioral Finance
  • Risk Parity: requires Portfolio Optimization
  • Securities Lending: enables Market Making, related_to Market Impact Models, requires Market Participants
  • Semiconductor Industry: part_of Supply Chain Analysis, requires Supply Chain Analysis
  • Statistical Arbitrage: requires Market Impact Models, requires Quantitative Trading
  • Supply Chain Analysis: requires Macroeconomic Analysis
  • Technical Analysis: influences Market Microstructure, requires Market Data Infrastructure
  • Trading Venues: requires distributed-systems, requires Order Types & Execution
  • VPIN Toxicity: measures Market Microstructure, requires Market Impact Models
  • Volatility Arbitrage: implements Volatility Trading, requires Volatility Trading
  • Volatility Trading: requires Implied Volatility Surface, requires Options Trading Strategies, requires Quantitative Trading

Authoritative Sources

Article Metadata

Bloom Taxonomy Questions

Remember

What are the core concepts in Markets?

Understand

How do the concepts in this glossary relate to each other?

Apply

How would you use these terms when analyzing a real-world scenario?

Further Reading

Feynman Concept Cards

Master each concept: read the ELI5, explore analogies, work examples, and teach it back.

AI Hardware Trends is a concept in industry analysis. In simple terms, AI Hardware Trends covers industry analysis in Markets. This markets concept addresses key topics in the industry analysis in markets domain. Also known as: AI chips, GPU market, AI accelerators. Rela

Analogy
Think of AI Hardware Trends like a medical diagnosis of an entire industry — it helps you handle industry analysis tasks more effectively.
Example
Consider a scenario where AI Hardware Trends applies: AI Hardware Trends covers industry analysis in Markets. This markets concept addresses key topics in the industry analysis in markets domain. Also known as: AI chips, GPU market, AI accelerators. Rela...
Find Gaps
What are the key components or steps involved in AI Hardware Trends?
Can you explain AI Hardware Trends without using jargon?
What happens if AI Hardware Trends is not applied correctly?
How does AI Hardware Trends relate to other concepts in industry analysis?
Teach Back

Explain AI Hardware Trends as if teaching a colleague who is new to industry analysis. Cover: what it is, how it works, and why it matters.

Create

Create a diagram that demonstrates AI Hardware Trends in a real-world industry analysis scenario. Walk through your design decisions.

Show solution
A diagram for AI Hardware Trends should include: 1. The core components of ai hardware 2. How they interact 3. Expected outcomes or outputs
Difficulty: Beginner-friendly — 2/5

Algorithmic Trading is a concept in advanced techniques. In simple terms, Algorithmic Trading covers advanced techniques in Markets. This markets concept addresses key topics in the advanced techniques in markets domain. Also known as: algo trading, automated trading, execu

Analogy
Think of Algorithmic Trading like a high-precision instrument in a trader's toolkit — it helps you handle advanced techniques tasks more effectively.
Example
Consider a scenario where Algorithmic Trading applies: Algorithmic Trading covers advanced techniques in Markets. This markets concept addresses key topics in the advanced techniques in markets domain. Also known as: algo trading, automated trading, execu...
Find Gaps
What are the key components or steps involved in Algorithmic Trading?
Can you explain Algorithmic Trading without using jargon?
What happens if Algorithmic Trading is not applied correctly?
How does Algorithmic Trading relate to other concepts in advanced techniques?
Teach Back

Explain Algorithmic Trading as if teaching a colleague who is new to advanced techniques. Cover: what it is, how it works, and why it matters.

Create

Create a diagram that demonstrates Algorithmic Trading in a real-world advanced techniques scenario. Walk through your design decisions.

Show solution
A diagram for Algorithmic Trading should include: 1. The core components of algorithmic trading 2. How they interact 3. Expected outcomes or outputs
Difficulty: Advanced — 5/5

Execution Algorithms is a concept in high frequency trading. In simple terms, Execution Algorithms covers high-frequency trading in Markets. This markets concept addresses key topics in the high-frequency trading in markets domain. Also known as: VWAP, TWAP, implementation shor

Analogy
Think of Execution Algorithms like a specialized tool in a toolbox — it helps you handle high frequency trading tasks more effectively.
Example
Consider a scenario where Execution Algorithms applies: Execution Algorithms covers high-frequency trading in Markets. This markets concept addresses key topics in the high-frequency trading in markets domain. Also known as: VWAP, TWAP, implementation shor...
Find Gaps
What are the key components or steps involved in Execution Algorithms?
Can you explain Execution Algorithms without using jargon?
What happens if Execution Algorithms is not applied correctly?
How does Execution Algorithms relate to other concepts in high frequency trading?
Teach Back

Explain Execution Algorithms as if teaching a colleague who is new to high frequency trading. Cover: what it is, how it works, and why it matters.

Create

Create a diagram that demonstrates Execution Algorithms in a real-world high frequency trading scenario. Walk through your design decisions.

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A diagram for Execution Algorithms should include: 1. The core components of execution algos 2. How they interact 3. Expected outcomes or outputs
Difficulty: Intermediate — 3/5

High Frequency Trading is a concept in advanced techniques. In simple terms, High Frequency Trading covers advanced techniques in Markets. This markets concept addresses key topics in the advanced techniques in markets domain. Also known as: HFT, algorithmic trading, low laten

Analogy
Think of High Frequency Trading like a high-precision instrument in a trader's toolkit — it helps you handle advanced techniques tasks more effectively.
Example
Consider a scenario where High Frequency Trading applies: High Frequency Trading covers advanced techniques in Markets. This markets concept addresses key topics in the advanced techniques in markets domain. Also known as: HFT, algorithmic trading, low laten...
Find Gaps
What are the key components or steps involved in High Frequency Trading?
Can you explain High Frequency Trading without using jargon?
What happens if High Frequency Trading is not applied correctly?
How does High Frequency Trading relate to other concepts in advanced techniques?
Teach Back

Explain High Frequency Trading as if teaching a colleague who is new to advanced techniques. Cover: what it is, how it works, and why it matters.

Create

Create a diagram that demonstrates High Frequency Trading in a real-world advanced techniques scenario. Walk through your design decisions.

Show solution
A diagram for High Frequency Trading should include: 1. The core components of high frequency trading 2. How they interact 3. Expected outcomes or outputs
Difficulty: Advanced — 5/5

Research is a concept in specialized. In simple terms, A concept related to research

Analogy
Think of Research like a specialized tool in a toolbox — it helps you handle specialized tasks more effectively.
Example
Consider a scenario where Research applies: A concept related to research...
Find Gaps
What are the key components or steps involved in Research?
Can you explain Research without using jargon?
What happens if Research is not applied correctly?
How does Research relate to other concepts in specialized?
Teach Back

Explain Research as if teaching a colleague who is new to specialized. Cover: what it is, how it works, and why it matters.

Create

Create a diagram that demonstrates Research in a real-world specialized scenario. Walk through your design decisions.

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A diagram for Research should include: 1. The core components of research 2. How they interact 3. Expected outcomes or outputs
Difficulty: Beginner-friendly — 2/5

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