AcaciaFund · Compliance · Markets · Data
Invest in understanding,
to build resilience.
Three pillars of modern finance โ explained from first principles, in plain language, with ideas you can hold on to.
Compliance
Compliance & Financial Crime
- Levi & Reuter (2006) - Money Laundering: A Review of the Economics of Crime
- Takats (2007) - A Theory of 'Crying Wolf': The Economics of Money Laundering Enforcement
- Unger et al (2007) - The Amounts and Effects of Money Laundering
Markets
Markets & Industry
- Kyle (1985) - Continuous Auctions and Insider Trading
- Glosten & Milgrom (1985) - Bid, Ask and Transaction Prices
- Easley, Kiefer, O'Hara & Paperman (1996) - Probability of Informed Trading (PIN)
Data Engineering
Data Engineering & Infrastructure
- Delta Lake vs Apache Iceberg vs Apache Hudi: Lakehouse Format Shootout
- Fellegi & Sunter (1969) - A Theory for Record Linkage
- Wang & Strong (1996) - Beyond Accuracy: What Data Quality Means to Data Consumers
How it works
Pick a Topic
Choose from compliance, markets, or data engineering โ each explained from the ground up.
Learn Simply
Every concept starts with an ELI5, then builds through analogies, examples, and diagrams.
Test Yourself
Teach back what you learned, find gaps, and build real understanding that sticks.
Fresh thinking
Featured
Levi & Reuter (2006) - Money Laundering: A Review of the Economics of Crime
Levi and Reuter critically review the evidence for AML effectiveness, questioning whether the massive global investment in AML compliance reduces crime. Foundational critique of AML regime effectiveness.
MarketsKyle (1985) - Continuous Auctions and Insider Trading
Kyle's seminal model of informed trading shows how an informed trader strategically splits orders to maximize profit while market makers adjust prices under adverse selection, introducing Kyle's lambda as a measure of market illiquidity.
Data EngineeringDelta Lake vs Apache Iceberg vs Apache Hudi: Lakehouse Format Shootout
Head-to-head comparison of the three major lakehouse storage formats: table mutation semantics, time travel, schema evolution, compaction, and ecosystem integration (Spark, Flink, Trino, DuckDB). Benchmark results included.
Fresh from the field
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Learning Paths
Designing a Comprehensive AML Compliance Program
Create a complete AML compliance program: risk assessment methodology with weighted scoring, transaction monitoring rule design, SAR governance frameworks, fintech compliance case study, training program design, and regulatory exam preparation. Advanced level.
Advanced LearnSector and Competitive Analysis: Industry Frameworks, Moats, and TAM Analysis
Analyze industries and competitive positioning: Porter's Five Forces, types of competitive moats (network effects, switching costs, intangibles, cost advantages, efficient scale), TAM/SAM/SOM market sizing, financial statement analysis by sector, and a case study of the semiconductor industry.
Intermediate LearnDesigning a Production Data Platform: From Requirements to Architecture
Master the full lifecycle of data platform design: requirements gathering, architecture methodology, a fintech case study, data mesh decentralization, open source vs managed decision framework, budget-friendly stacks, and evolving a platform into a data product.
AdvancedWhy the Feynman Technique?
If you can't explain it simply, you don't understand it well enough. Every concept on AcaciaFund is structured with this principle: start with a plain-English explanation, connect it through analogy, test it with examples, find the gaps, and build something real. No fluff. Just understanding.
Learn how it works →Where do you stand?
Take the nine-question diagnostic to be placed into a learning mode โ beginner, intermediate, or expert โ that tunes your study queue and the whole site to your level.
Take the diagnostic →Walk a guided path
Three curated journeys cross the Compliance, Markets and Data Engineering pillars โ from fiat to crypto compliance, from raw data to a trading operation, from suspicious activity to SAR. Linear steps, tracked progress.
Browse journeys →