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L01 FinTech Fundamentals & Payment Systems9 lectures

MainFinTech Fundamentals & Payment Systems
21 slides
  • What is FinTech?
  • What Makes FinTech Different from Traditional Finance?
  • Why Do Financial Intermediaries Exist?
  • How Did Four Technology Waves Reshape Finance?
  • What Are the Five Core Financial Functions?
  • How Do Payments Work?
  • How Does Money Actually Move When You Tap Your Card?
  • Where Does the 2--3\% Merchant Fee Actually Go?
  • Learning Objectives
  • Traditional Financial Infrastructure
  • Why Are Legacy Core Banking Systems So Hard to Replace?
  • Why Do Cross-Border Payments Take Days and Cost 7\%?
  • How Do Network Effects Drive FinTech Growth?
  • What Makes Digital Infrastructure Fundamentally Different?
  • Payment Systems
  • Should Payments Settle One-by-One or in Batches?
  • What Invisible Layers Carry Every Payment You Make?
  • How Does Wise Bypass the Correspondent Banking Chain?
  • Which Friction Point Does Each Payment Innovation Attack?
  • The FinTech Landscape
  • Why Do Payments Dominate the Global FinTech Market?
  • Why Is Switzerland a Global FinTech Laboratory?
  • How Are InsurTech and WealthTech Completing the Unbundling?
  • Which Revenue Model Reveals Which Problem a FinTech Solves?
  • Course Roadmap
  • How Do Eight Lessons Map to Five Financial Functions?
  • Summary
  • Summary
What is FinTech?How Do Payments Work?Traditional Financial InfrastructurePayment SystemsThe FinTech LandscapeCourse RoadmapSummary
ExtendedBusiness Models
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Revenue Architecture \& Unit Economics
  • How Do You Decompose a FinTech's Revenue Into Its Fundamental Engines?
  • What Does the ARPU Distribution Look Like Across FinTech Categories?
  • Can You Build a Cohort-Based LTV Calculator That Beats Naive Averages?
  • Why Does a 5\% Retention Improvement Double Lifetime Value?
  • How Fast Does Revenue Per User Decay After the First Year?
  • Which Revenue Engine Combination Maximises Long-Term Enterprise Value?
  • Market Sizing \& Opportunity Assessment
  • How Do You Size a FinTech Market Without Fooling Yourself?
  • How Wide Is the Gap Between Total Market and Serviceable Market?
  • Can You Build a Bottom-Up Market Sizer That Accounts for Regulatory Barriers?
  • Where Is the Largest Untapped Opportunity in Digital Finance?
  • Why Does Every FinTech Adoption Curve Follow the Same S-Shape?
  • Can You Spot the Winning Strategy from Five Dimensions Simultaneously?
  • Go-to-Market \& Growth Dynamics
  • What Makes a FinTech Product Genuinely Viral --- and Why Do Most Fail?
  • Which Go-to-Market Channel Delivers the Best Cost-Efficiency Over Time?
  • Can You Decompose Growth Into New, Retained, Resurrected, and Churned Users?
  • How Does Customer Acquisition Cost Change When a FinTech Pivots Strategy?
  • Why Does Customer Acquisition Cost Rise Faster Than Revenue in Saturating Markets?
  • Which Customer Segment Delivers the Highest Return on Acquisition Spend?
  • Competitive Strategy \& Moat Economics
  • Why Do Customers Stay with Bad Banks? Klemperer's Switching Cost Theory
  • How Deep Is Market Penetration Across Different FinTech Product Categories?
  • Can You Quantify Whether a FinTech Has a Durable Competitive Moat?
  • How Long Does Each Type of Competitive Advantage Last in FinTech?
  • When Does a Platform Become Too Big to Leave?
  • What Does the Complete FinTech Moat Landscape Look Like?
  • Path to Profitability \& the J-Curve
  • Can You Predict When a FinTech Will Turn Profitable --- or Never Will?
  • Where Does Each FinTech Sit on the Growth vs.\ Profitability Frontier?
  • Can You Simulate the J-Curve to Find the Break-Even Point?
  • How Many Years Does It Take Each FinTech Category to Reach Profitability?
(Introduction)Revenue Architecture \& Unit EconomicsMarket Sizing \& Opportunity AssessmentGo-to-Market \& Growth DynamicsCompetitive Strategy \& Moat EconomicsPath to Profitability \& the J-Curve
MiniBusiness Models
7 slides
  • (Slides)
  • Why Do 90\% of FinTechs Lose Money -- and Why Do Investors Keep Funding Them?
  • What Are the Six Revenue Engines That Power Digital Finance?
  • Where Does Each FinTech Sit on the ARPU vs.\ CAC Landscape?
  • How Do You Calculate Whether a Customer Will Ever Be Profitable?
  • What Are the Four Forces That Can Kill a FinTech Business Model Overnight?
  • Which Business Model Wins -- and Why Does It Depend on Where You Are?
  • What Must Every FinTech Analyst Know Before Reading a Pitch Deck?
(Slides)
ExtendedFintech
27 slides
  • (Slides)
  • What Will You Be Able to Do After This Lecture?
  • Why Do Lenders Charge Higher Rates Than They Should -- and How Does FinTech Fix It?
  • When Does It Cost More to Use a Market Than to Build a Firm?
  • Why Is a Payment Network With 10 Million Users Worth 100x More Than One With 1 Million?
  • Why Do Banks Exist -- and Why Are They Inherently Fragile?
  • Which Technology Breakthrough Triggered Each Wave of Financial Innovation?
  • Building a Four-Party Payment Fee Model in Python
  • Did Capping Interchange Fees Actually Reduce What Merchants Pay?
  • Modeling Cross-Border Payment Costs: SWIFT vs.\ Wise vs.\ Stablecoin
  • How Does the Cost of Sending \$200 Home Vary Across Corridors and Methods?
  • Simulating Winner-Take-Most Dynamics in Two-Sided Markets
  • Where Is Venture Capital Betting -- and Where Has It Already Left?
  • Which Revenue Model Reveals Which Intermediation Problem a FinTech Solves?
  • Why Does China Have 87\% FinTech Adoption While Switzerland Has 64\%?
  • What Makes Switzerland Both a Banking Fortress and a FinTech Laboratory?
  • How Much Liquidity Does a Bank Need -- and Does the Settlement Method Change the Answer?
  • What Invisible Layers Carry Every Payment -- and Where Can FinTech Innovate?
  • Which Countries Leapfrogged Cards and Went Straight to Real-Time Mobile Payments?
  • Who Actually Pays When You ``Buy Now, Pay Later''?
  • How Do the 50 Largest FinTechs Actually Make Money?
  • When Every App Becomes a Bank, Who Is Actually Doing the Banking?
  • Analyzing Two-Sided Platform Pricing and Subsidy Strategies
  • Why Can a FinTech Grow Revenue 50\% Per Year and Still Lose Money?
  • Why Has the Cost of Financial Intermediation Stayed at 2\% for 130 Years?
  • Is Finance Moving Toward Zero Intermediation or Infinite Intermediation?
  • Key Takeaways
  • References and Further Reading
(Slides)
MiniFintech
10 slides
  • (Slides)
  • Why Did the Technology That Was Supposed to Kill Banks Make Stripe Worth More Than Deutsche Bank?
  • Have You Ever Paid a `Free' Service That Still Made Money Off Every Transaction You Made?
  • What Are the Three Problems That Every Financial Intermediary -- Old or New -- Must Solve?
  • How Did Stripe Become the Invisible Backbone of the Internet Economy?
  • How Does Money Actually Move When You Tap Your Phone -- and Who Takes a Cut at Each Step?
  • What Happens When the New Intermediary Fails -- and There Is No Branch to Walk Into?
  • Where Is FinTech Replacing Banks -- and Where Is It Just a Better Front End?
  • How Much Has the Cost of Financial Intermediation Actually Fallen?
  • The Intermediation Scorecard: How to Evaluate Whether a FinTech Is Truly Disrupting or Just Repackaging
  • Your Challenge: Map the Intermediation Chain of Your Last Financial Transaction
(Slides)
LGFintech Value Creation
10 slides
  • (Slides)
  • Why Do the Most Popular FinTechs Lose the Most Money?
  • How Much Did You Pay for Your Last Financial App?
  • What Are the Five Ways a FinTech Can Actually Make Money?
  • Follow One Euro Through Revolut from Deposit to Revenue
  • What Machine Turns Users into Revenue?
  • What Happens When a FinTech Grows Fast but Never Profits?
  • How Do Five FinTech Business Models Compare on Six Dimensions?
  • Who Wins and Who Loses When FinTechs Disrupt Banking Revenue?
  • Four Questions That Reveal Whether a FinTech Business Model Is Real
  • Your Challenge: Evaluate a FinTech Business Model
(Slides)
LGPayment Systems
10 slides
  • (Slides)
  • Why Does Moving Money Still Take Longer Than Delivering a Pizza?
  • When Was the Last Time You Waited for Money That Should Have Arrived Instantly?
  • What Are the Six Competing Rails That Move Your Money?
  • Follow One Twint Payment from Your Phone to the Merchant's Bank
  • What Are the Four Layers That Every Payment Must Pass Through?
  • What Happens When the System That Moves Trillions Per Day Goes Down?
  • How Do Six Payment Systems Compare on Speed, Cost, and Reach?
  • Who Wins and Who Loses When Payments Become Instant and Free?
  • Four Questions That Reveal Any Payment System's True Cost
  • Your Challenge: Decompose the True Cost of a Cross-Border Payment
(Slides)
ExtendedMobile Money
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Payment System Architecture
  • How Does Netting Reduce Trillions in Daily Obligations to a Fraction?
  • How Fast Is ``Instant'' -- And Where Does Latency Hide?
  • How Do You Prove a Payment Message Has Not Been Tampered With?
  • Why Do Payment Systems Collapse Under Load -- and How Do You Predict It?
  • Why Does Sending \$200 Cost \$1 in Some Corridors and \$20 in Others?
  • What Are the Four Layers Every Payment Must Traverse?
  • Mobile Money Economics
  • Which Countries Leapfrogged Banks Entirely -- and Why?
  • What Interchange Fee Maximises Platform Revenue on Both Sides?
  • Why Is the Socially Optimal Interchange Fee Not Zero?
  • Why Does Agent Density Determine Mobile Money Success or Failure?
  • How Does M-Pesa Earn Interest on Money That Is Always Moving?
  • What Does the Velocity of Mobile Money Tell Us About Financial Behaviour?
  • Network Effects \& Two-Sided Markets
  • Is a Payment Network Worth $n^2$ or $n \log n$ -- and Why Does It Matter?
  • How Do You Simulate the S-Curve That Every Payment Network Follows?
  • Which Networks Reached Critical Mass Fastest -- and What Did They Sacrifice?
  • Where Does Each Basis Point of the Merchant Discount Rate Go?
  • How Do You Launch a Network Nobody Wants to Join Because Nobody Has Joined?
  • Interoperability \& Cross-Border Rails
  • Where Do the Hidden Costs in a Currency Conversion Actually Hide?
  • Which Payment Rails Carry the Most Value -- and Which Carry the Most Transactions?
  • Can You Compute the True Cost When Providers Hide Half of It?
  • Which Corridors Dominate Global Remittance Flows -- and Why?
  • Why Did Real-Time Payments Explode in Some Countries and Stall in Others?
  • Why Is the 50-Year-Old Correspondent Banking Model Still Alive?
  • Financial Inclusion Measurement
  • How Do You Measure Something as Multidimensional as Financial Inclusion?
  • Can You Build a Financial Inclusion Score from Raw World Bank Data?
  • Which Countries Excel on Access but Fail on Quality?
  • Is the Death of Cash a Liberation or an Exclusion?
  • Where Does the Revenue Come from When the Average Transaction Is \$12?
(Introduction)Payment System ArchitectureMobile Money EconomicsNetwork Effects \& Two-Sided MarketsInteroperability \& Cross-Border RailsFinancial Inclusion Measurement
MiniMobile Money
10 slides
  • (Slides)
  • Why Did M-Pesa Succeed Where Banks Failed for 50 Years?
  • What Would You Do If the Nearest Bank Were a Three-Hour Walk Away?
  • What Separates a Payment Rail from a Payment Product -- and Why Does It Matter?
  • Follow One Dollar from a Nairobi Street Vendor to a Rural Farmer -- Step by Step?
  • How Do You Build a Payment System on Top of a Telephone Network?
  • What Happens When Your Entire Financial Life Lives on a SIM Card?
  • Where Has Mobile Money Leapfrogged Traditional Banking -- and Where Has It Not?
  • Who Captures the Value When Cash Disappears -- Consumers, Telcos, or Governments?
  • The Leapfrog Checklist: When Does Skipping Infrastructure Actually Work?
  • Your Challenge: Design a Payment System for a Country with 10\% Bank Penetration?
(Slides)

L02 Neobanks & Open Banking7 lectures

MainNeobanks & Open Banking
19 slides
  • PSD2 and Open Banking Regulation
  • How Did PSD2 Turn Regulation into a Weapon for Competition?
  • Market Structure and Disruption
  • Why Could Neobanks Challenge Century-Old Banks?
  • What Happens When Banking Gets Unbundled?
  • The Rise of Neobanks
  • What Is a Neobank and How Does It Differ from a Challenger Bank?
  • Why Don't Customers Leave Bad Banks?
  • What Does 400M Users Tell Us About Market Contestability?
  • Learning Objectives
  • Can Neobanks Actually Make Money?
  • Why Does Your Bank App Demand Your Fingerprint AND a PIN?
  • Who Are the New Players PSD2 Created?
  • Open Banking Architecture
  • Why Was Screen Scraping the Wild West of Data Access?
  • Who Controls Your Financial Data -- You or Your Bank?
  • What Is Open Banking and Where Is It Heading?
  • What Can Third Parties Actually Do with Bank APIs?
  • How Does the Technical Architecture Keep Data Sharing Secure?
  • Which Real-World Problems Does Open Banking Solve?
  • Challenges and Future
  • Why Hasn't Open Banking Lived Up to the Hype Yet?
  • What Comes After Open Banking?
  • Summary
  • Summary
PSD2 and Open Banking RegulationMarket Structure and DisruptionThe Rise of NeobanksOpen Banking ArchitectureChallenges and FutureSummary
ExtendedEmbedded Finance
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • BaaS Architecture \& Value Chain
  • How Do You Split Revenue When Three Companies Deliver One Bank Account?
  • How Large Is the Embedded Finance Opportunity by Vertical?
  • Where Does Value Leak in the BaaS Stack?
  • What Does a Real BaaS API Integration Look Like?
  • When Do Consumers Actually Use Embedded Financial Services?
  • What Are the Three Architectural Layers That Make BaaS Possible?
  • Embedded Lending \& BNPL Economics
  • Which Age Groups Adopted BNPL -- and Which Are Getting Burned?
  • What Is the True Cost of ``Pay in 4'' When You Miss a Payment?
  • How Do You Model Default Probability for Someone with No Credit File?
  • Are BNPL Default Rates Converging Toward or Diverging from Credit Cards?
  • Can You Build a Credit Scorer Without a Credit Bureau?
  • Is BNPL a New Product or Just a Credit Card in Disguise?
  • Embedded Insurance \& Wealth
  • Why Does Insurance Convert 5x Better When Sold Inside Another Product?
  • How Do You Price Insurance When the Buyer Never Reads the Policy?
  • Who Captures the Most Value in the Embedded Finance Ecosystem?
  • Can Your Shopping App Become Your Financial Advisor?
  • Regulatory Architecture for BaaS
  • Which Regulatory Regime Actually Covers the Full BaaS Stack?
  • What Happens to the Financial System When Every Brand Uses the Same BaaS Provider?
  • How Does a Regulator Decide Who Needs a License in a BaaS Arrangement?
  • How Do BaaS Platforms Prevent One Brand from Overwhelming the System?
  • How Interconnected Are the Players in the BaaS Ecosystem?
  • What Happens When the Invisible Middle Layer of BaaS Disappears?
  • Platform Economics \& Moat Analysis
  • Why Is It Harder to Leave a BaaS Provider Than to Leave a Bank?
  • How Should a Brand and a BaaS Provider Split the Revenue?
  • Why Do BaaS Platforms Subsidize One Side and Tax the Other?
  • Which BaaS Providers Are Positioned for Dominance -- and Which Are Vulnerable?
  • Which Factor Contributes Most to BaaS Switching Costs?
  • How Fast Will Embedded Finance Grow -- and What Could Go Wrong?
(Introduction)BaaS Architecture \& Value ChainEmbedded Lending \& BNPL EconomicsEmbedded Insurance \& WealthRegulatory Architecture for BaaSPlatform Economics \& Moat Analysis
MiniEmbedded Finance
10 slides
  • (Slides)
  • Why Is Shopify a Bigger Lender Than Most Community Banks?
  • How Many Financial Products Did You Use Today Without Visiting a Bank?
  • What Is the Difference Between a Bank, a BaaS Provider, and a Brand?
  • Follow One Buy-Now-Pay-Later Transaction from Click to Settlement?
  • How Does a Non-Bank Offer Banking -- and Who Holds the License?
  • What Happens to Your Deposits When a BaaS Middleware Company Fails?
  • Where Is Embedded Finance Growing Fastest -- and Where Are the Regulatory Gaps?
  • Who Wins When Every App Becomes a Bank -- Brands, Banks, or Consumers?
  • The BaaS Evaluation Checklist: When Is Embedded Finance Real Innovation vs Regulatory Arbitrage?
  • Your Challenge: Design an Embedded Finance Product for a Non-Financial Brand?
(Slides)
LGOpen Banking Apis
10 slides
  • (Slides)
  • Why Did It Take a Law to Make Banks Share Your Own Financial Data?
  • How Many Third-Party Apps Can See Your Bank Balance Right Now?
  • What Can a Third-Party App Actually Do With Your Bank Account?
  • Follow One Klarna ``Pay Later'' Transaction Through the Open Banking Stack
  • How Does a Third-Party App Talk to Your Bank Without Knowing Your Password?
  • What Happens When Consent Becomes a Checkbox No One Reads?
  • How Fast Is the Open Banking API Ecosystem Growing?
  • Who Wins and Who Loses When APIs Replace Proprietary Bank Channels?
  • Four Questions to Ask Before Granting Any App Access to Your Bank
  • Should Open Finance Extend Beyond Banking to Insurance, Pensions, and Investments?
(Slides)
MiniNeobank
10 slides
  • (Slides)
  • Why Would a Tech Company Want to Become a Bank?
  • Opening a New Account -- Did Friction Even Cross Your Mind?
  • What Makes a Neobank Different from a Digital Bank?
  • Follow One Customer from Download to Daily Use
  • Who Should Hold the Banking License -- the Neobank, a Partner, or Both?
  • What Could Go Wrong If Your Neobank Runs Out of Money?
  • Why Are So Many Customers Adopting Digital-Only Banks?
  • Who Wins and Who Loses When a Neobank Launches?
  • 5 Questions That Reveal a Neobank's True Viability
  • Your Challenge: Evaluate a Real Digital-Only Bank
(Slides)
ExtendedNeobanks Open Banking
27 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Market Structure and Contestability
  • Why Can a Startup With No Branches Challenge a 200-Year-Old Bank?
  • Which Features Separate Neobanks from Traditional Banks?
  • How Does Digital Banking Market Share Vary by Region and License Type?
  • What Makes Customers Stay with Bad Banks -- and How Does PSD2 Change the Equation?
  • Simulating Neobank Entry Under Varying Sunk Cost Regimes
  • Which Neobanks Rose and Fell in the Valuation Rankings?
  • Neobank Economics
  • Who Pays When Banking Is `Free' -- and Where Does the Interchange Fee Go?
  • Who Actually Uses Neobanks -- and Are They the Customers Banks Want?
  • Why Can a Neobank Grow 50\% Per Year and Still Lose EUR 200 Million?
  • Building a Neobank Unit Economics Simulator in Python
  • Where Is Venture Capital Betting on Digital Banking -- and Where Has It Retreated?
  • If You Score Banks on Six Dimensions, Who Actually Wins?
  • PSD2 and Regulatory Architecture
  • How Does Customer Data Actually Flow Through the PSD2 Ecosystem?
  • Why Does the First Open Banking Platform Past Critical Mass Capture Everything?
  • Simulating How PSD2 Changes Customer Switching Behavior
  • What Are Third Parties Actually Doing with Bank APIs?
  • What Measurably Changed in the Five Years After PSD2?
  • How Does the OAuth 2.0 Protocol Keep Open Banking Data Sharing Secure?
  • Open Banking Technical Infrastructure
  • How Dense Is the Web of API Connections Between Financial Institutions?
  • Simulating the OAuth 2.0 Authorization Code Grant for Open Banking
  • Is There a Sweet Spot Between Customer Engagement and Revenue Per User?
  • Benchmarking Open Banking API Response Times Across Banks
  • How Much Better Can You Assess Credit Risk When You Can See Every Transaction?
  • Synthesis and Future
  • Did Open Banking Create More Freedom or More Dependency?
  • Key Takeaways
  • References and Further Reading
(Introduction)Market Structure and ContestabilityNeobank EconomicsPSD2 and Regulatory ArchitectureOpen Banking Technical InfrastructureSynthesis and Future
MiniOpen Banking
10 slides
  • (Slides)
  • Why Does Your Bank Refuse to Share Your Own Data?
  • Have You Ever Wished All Your Accounts Were in One Place?
  • What Is Open Banking and How Does It Differ from Traditional Banking?
  • Follow Your Data from Bank Vault to Budgeting App
  • Screen Scraping or Secure APIs -- Which Would You Trust?
  • What Happens When Your Financial Data Leaks?
  • How Fast Are Open Banking APIs Replacing Screen Scraping?
  • Who Wins and Who Loses When Banks Must Open Their Vaults?
  • The Consent Paradox: 3 Questions to Ask Before Sharing Your Data
  • Your Challenge: Map the Data Flows Behind a Financial App
(Slides)

L03 P2P Lending & Robo-Advisors8 lectures

MainP2P Lending & Robo-Advisors
21 slides
  • Information Problems in Finance
  • Why Do the Riskiest Borrowers Want Loans the Most?
  • What Happens After the Loan Is Signed?
  • Can a Platform Replace a Bank -- and Who Bears the Risk?
  • Peer-to-Peer Lending
  • How Does a P2P Loan Go from Application to Repayment?
  • Is Cutting Out the Bank Worth the Extra Risk?
  • Credit Scoring and Data-Driven Lending
  • How Does a Three-Digit Number Decide Your Financial Future?
  • Learning Objectives
  • How Much Regulation Should Replace Market Discipline?
  • Can Your Phone Usage Predict Whether You'll Repay a Loan?
  • What Are the Three Ways Machines Learn from Financial Data?
  • What Does the Journey from Raw Data to Credit Decision Look Like?
  • How Do Risk Grades Translate to Returns for Investors?
  • Risk and Return Basics
  • Why Do Higher Returns Always Come with Higher Risk?
  • How Can Combining Risky Assets Reduce Overall Risk?
  • Robo-Advisory Services
  • Can an Algorithm Give Better Financial Advice than a Human?
  • How Do Robo-Advisors Build an Optimal Portfolio?
  • What Does a Conservative vs. Aggressive Portfolio Look Like?
  • When Should You Choose a Robot Over a Human Advisor?
  • Data-Driven Finance
  • Do the Same ML Techniques Power All Financial Functions?
  • Is Data Replacing Banks as the Financial Middleman?
  • Summary
  • Summary
Information Problems in FinancePeer-to-Peer LendingCredit Scoring and Data-Driven LendingRisk and Return BasicsRobo-Advisory ServicesData-Driven FinanceSummary
ExtendedCredit Scoring
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Feature Engineering for Credit
  • Why Does Every Regulator Still Trust a Model Invented in the 1950s?
  • Which Features Actually Drive Default Prediction -- and Which Are Just Noise?
  • How Do You Turn Raw Transaction Data into Credit-Worthy Features?
  • Can You Spot the Hidden Redundancy in Your Feature Matrix?
  • How Do You Mathematically Prove a Feature Is Worth Including?
  • What Happens When You Score Credit with Data the Borrower Never Knew You Had?
  • Classification Models Compared
  • Is There a Model That Is Both Accurate and Explainable -- or Must You Choose?
  • Can You Build a Regulatory-Grade Credit Scorer in 18 Lines?
  • What Does the Area Under the Curve Actually Measure -- and When Does It Lie?
  • Where Is the Threshold That Balances Catching Defaults and Not Rejecting Good Borrowers?
  • If You Can Only Review 10\% of Applications, How Many Defaults Will You Catch?
  • How Do You Choose a Model When Accuracy, Fairness, and Explainability All Conflict?
  • Model Validation \& Calibration
  • When Your Model Says ``5\% Chance of Default,'' Does It Actually Mean 5\%?
  • How Do You Fix a Model That Ranks Well but Assigns Wrong Probabilities?
  • How Do You Compute and Plot an ROC Curve from Scratch?
  • Does a Loan Originated in January Behave Differently from One in July?
  • How Sensitive Is Your Model's Performance to Hyperparameter Choices?
  • Fairness \& Bias Detection
  • Can a Credit Model Be Fair to Everyone at the Same Time?
  • Which Demographic Groups Are Being Disproportionately Denied Credit?
  • How Do You Detect Whether Your Model Discriminates -- Before the Regulator Does?
  • Can You See Exactly How Each Feature Pushes a Prediction Toward or Away from Default?
  • Why Are SHAP Values the Only Mathematically Fair Way to Attribute Predictions?
  • If You Make a Model Fairer, Do You Also Make It Less Accurate?
  • Deployment \& Monitoring
  • How Do You Mathematically Detect When Your Model's World Has Changed?
  • Can You Build an Early Warning System for Model Drift in 18 Lines?
  • When Did the Model Start Drifting -- and What Triggered Each Shift?
  • Where Do Applicants Drop Out in the Credit Scoring Pipeline?
  • How Often Should You Retrain a Credit Model -- and What Triggers a Rebuild?
(Introduction)Feature Engineering for CreditClassification Models ComparedModel Validation \& CalibrationFairness \& Bias DetectionDeployment \& Monitoring
MiniCredit Scoring
10 slides
  • (Slides)
  • Why Can Your Phone's Data Predict Your Creditworthiness Better Than Your Credit Score?
  • What If You Were Denied a Loan Because of How You Hold Your Phone?
  • What Data Goes Into an Alternative Credit Score -- and What Should Be Off-Limits?
  • Follow One Loan Application Through Three Scoring Models -- and Get Three Different Answers
  • How Do You Build a Credit Scoring Pipeline from Raw Data to Default Probability?
  • What Goes Wrong When the Training Data Reflects Historical Discrimination?
  • Where Does Model Complexity Help and Where Does It Hurt?
  • Who Benefits from Alternative Data -- Thin-File Borrowers or Predatory Lenders?
  • The Scoring Evaluation Framework: Accuracy, Fairness, Explainability -- Pick Two?
  • Your Challenge: Audit a Credit Model for Disparate Impact
(Slides)
LGData Driven Finance
10 slides
  • (Slides)
  • Why Are Banks Replacing Bankers With Algorithms?
  • Has an Algorithm Ever Said No to You Without Explaining Why?
  • What Five Data-Driven Approaches Are Transforming Finance?
  • Follow One Loan Application from Data Input to Automated Decision
  • What Does the Machine Learning Pipeline Look Like Inside a Bank?
  • What Happens When an Algorithm Discriminates and Nobody Notices?
  • Where Have Data-Driven Techniques Reached Mainstream Adoption -- and Where Are They Still Emerging?
  • Who Wins and Who Loses When Algorithms Replace Human Judgment?
  • Four Questions That Reveal Whether a Data-Driven System Is Fair
  • Your Challenge: Apply the ML Pipeline to Classify Sample Transactions
(Slides)
ExtendedP2P Lending
27 slides
  • (Slides)
  • What Will You Be Able to Do After This Lecture?
  • How Do Economists Formalize the Lemon Problem?
  • What Is the Business Model of a P2P Lending Platform?
  • Where Does Information Get Lost Between Borrower and Lender?
  • How Does Logistic Regression Predict Default Probability?
  • Building a Credit Scoring Model in 20 Lines of Python
  • How Do You Choose the Right Threshold for Loan Approval?
  • Why Is Missing a Default 10x Worse than Rejecting a Good Borrower?
  • How Does the Model Find the Best Weights?
  • What Separates a Raw Variable from a Predictive Feature?
  • Transforming Raw Data into Credit Features in Python
  • How Do You Measure Risk Mathematically?
  • Why Does Correlation Between Assets Determine Diversification Benefit?
  • How Do Robo-Advisors Find the Optimal Portfolio?
  • Mean-Variance Portfolio Optimization in Python
  • How Does Your Risk Tolerance Translate to an Asset Mix?
  • What Happens When Your Portfolio Drifts from Its Target?
  • How Much Does a 1.25\% Fee Difference Really Cost Over 30 Years?
  • What Does `Fair' Actually Mean -- Mathematically?
  • How Do Different Models Score on Fairness Across Groups?
  • Auditing a Credit Model for Bias in Python
  • What Do Regulators Demand from Algorithmic Lending?
  • When Does an Algorithm Actually Outperform a Human Advisor?
  • Automated Rebalancing: The Code Behind the Robo-Advisor
  • When Alternative Data Crosses the Line: Three Real Cases
  • Is Data Replacing Banks, or Just Creating New Middlemen?
  • Key Takeaways
(Slides)
MiniP2P Lending
10 slides
  • (Slides)
  • Why Would an Algorithm Designed to Help You Get a Loan Reject You for Where You Live?
  • Have You Ever Been Judged by Data You Didn't Choose to Share?
  • What Separates a Credit Score from an Algorithmic Verdict?
  • Follow One Loan Application Through Three Different Scoring Models
  • How Do You Build a Model That Is Both Accurate and Fair?
  • What Happens When the Fair Model Costs More and the Accurate Model Discriminates?
  • Where Is Algorithmic Lending Actually Expanding -- and Where Is It Contracting?
  • Who Wins and Who Loses When Algorithms Replace Loan Officers?
  • The Fairness Dial: Every Model Makes a Choice -- Where Do You Set It?
  • Your Challenge: Audit a Credit Scoring Model for Bias
(Slides)
ExtendedRobo Advisor
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Modern Portfolio Theory Mathematics
  • Why Is the Efficient Frontier Shaped Like a Parabola?
  • What Does the Efficient Frontier Look Like in Three Dimensions?
  • Can You Solve Markowitz Optimization in 18 Lines?
  • Why Is Variance a Terrible Measure of Investment Risk?
  • Which Input Error Hurts Your Portfolio the Most?
  • Black-Litterman \& Robust Optimization
  • How Do You Combine Market Consensus with Your Own Views?
  • Can You Implement Black-Litterman in Python?
  • How Does a Portfolio Drift Between Rebalancing Events?
  • How Do Investor Views Shift the Return Distribution?
  • What If You Equalize Risk Contribution Instead of Capital?
  • Rebalancing, Tax Optimization \& Algorithms
  • How Often Should You Rebalance -- and Can Math Answer This?
  • Can You Build a Tax-Aware Rebalancing Engine?
  • Which Tax-Loss Harvesting Opportunities Matter Most?
  • When Do Behavioral Biases Push Portfolio Decisions Out of Control?
  • Behavioral Finance \& Risk Profiling
  • Why Do Investors Feel Losses Twice as Much as Gains?
  • Can You Build a Risk Profiler That Accounts for Behavioral Bias?
  • What Asset Mix Does Each Risk Profile and Time Horizon Demand?
  • How Do Factor Strategies Differ Inside a Robo-Advisor?
  • ESG Integration \& Fairness in Wealth Management
  • Does Adding an ESG Constraint Always Cost You Returns?
  • How Does an ESG Tilt Move Your Portfolio on the Risk-Return Plane?
  • Can You Build an ESG-Aware Robo-Advisor Allocation?
  • Can a Robo-Advisor Discriminate Without Knowing Your Race?
  • How Should Your Portfolio Evolve as You Approach Retirement?
  • Which Robo-Advisor Is Winning the AUM Race?
  • Can You Simulate How Retirement Timing Risk Destroys Wealth?
  • How Much Does the Fee Drag Actually Cost Over a Lifetime?
  • What Have We Learned -- and What Remains Unsolved?
  • Key Takeaways
(Introduction)Modern Portfolio Theory MathematicsBlack-Litterman \& Robust OptimizationRebalancing, Tax Optimization \& AlgorithmsBehavioral Finance \& Risk ProfilingESG Integration \& Fairness in Wealth Management
MiniRobo Advisor
10 slides
  • (Slides)
  • What If Your Financial Advisor Could Never Panic?
  • Would You Trust a Machine with Your Retirement?
  • What Makes a Robo-Advisor Different from a Spreadsheet?
  • How Does Betterment Turn Your Risk Score into a Portfolio?
  • Why Does Modern Portfolio Theory Still Power Every Robo-Advisor?
  • What Goes Wrong When the Algorithm Meets the Real World?
  • How Big Is the Robo-Advisory Market -- and Who Is Winning?
  • Who Gains Access and Who Loses Their Job?
  • The Suitability Spectrum -- When Should You Use a Robot?
  • Your Challenge -- Design a Robo-Advisor for Swiss Retirees
(Slides)

L04 RegTech & Compliance7 lectures

MainRegTech & Compliance
18 slides
  • Regulatory Technology (RegTech)
  • Why Did Compliance Costs Explode After 2008?
  • How Did Compliance Costs Grow Faster than Bank Revenue?
  • Which Regulatory Problem Does Each RegTech Category Solve?
  • Why Regulate Financial Markets?
  • Why Can't We Just Let Financial Markets Regulate Themselves?
  • What Happens When a Bank Is Too Big to Fail?
  • Who Watches the Watchmen in Financial Regulation?
  • Learning Objectives
  • KYC and AML Processes
  • Why Must Your Bank Know So Much About You?
  • How Does Each KYC Step Reduce the Bank's Uncertainty?
  • How Do Criminals Make Dirty Money Look Clean?
  • Can AI Reduce the 95\% False Positive Rate in Transaction Monitoring?
  • Why Does Privacy Law Clash with Anti-Money Laundering?
  • Compliance Automation
  • What Can Automation Handle -- and What Still Needs Human Judgment?
  • Why Do Costs Keep Rising Despite RegTech?
  • Regulatory Reporting and SupTech
  • What Do Regulators Actually Need to See -- and Why?
  • How Are Regulators Using the Same Technology as Banks?
  • Implementing RegTech
  • What Blocks Banks from Adopting RegTech?
  • Summary
  • Summary
Regulatory Technology (RegTech)Why Regulate Financial Markets?KYC and AML ProcessesCompliance AutomationRegulatory Reporting and SupTechImplementing RegTechSummary
ExtendedPrivacy Compliance
30 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • GDPR Foundations \& Information Theory
  • How Much Does Your Bank Know About You -- and Can We Measure It?
  • How Much Information Does Each Data Field Carry -- Before and After Privacy Transforms?
  • Can You Measure How Much a Privacy Transform Destroys?
  • Can You Write the Regulatory Contradiction as a Math Problem?
  • Differential Privacy
  • What Does It Mean Mathematically to Guarantee Individual Privacy?
  • Can You Add Privacy-Preserving Noise to an AML Query?
  • How Much Accuracy Do You Sacrifice for Each Level of Privacy?
  • How Fast Does Your Privacy Budget Run Out?
  • How Do You Make a Privacy Budget Last Through Thousands of AML Queries?
  • Anonymization Techniques
  • When Is `Anonymous' Not Really Anonymous?
  • Can You Build a k-Anonymity Engine for Financial Data?
  • How Large Are the Equivalence Classes After k-Anonymization?
  • How Many Linkage Rounds Does It Take to Re-Identify an `Anonymous' Customer?
  • Privacy-Preserving Analytics
  • Can You Do Math on Data You Cannot See?
  • Can You See Homomorphic Encryption in Action -- Simplified?
  • How Much Slower Is Privacy-Preserving Computation?
  • Can Banks Train a Shared AML Model Without Sharing Any Data?
  • How Does Federated AML Model Accuracy Converge Compared to Centralized?
  • The Compliance Paradox \& Regulatory Engineering
  • Is There a Sweet Spot Where Both GDPR and AML Are Satisfied?
  • How Many Distinct Legal Bases Does a Single Customer Record Require?
  • Can You Automate a GDPR-AML Retention Schedule?
  • How Does Data Flow Through the Consent Architecture?
  • Where Do GDPR, 6AMLD, ePrivacy, and DORA Overlap -- and Where Do They Conflict?
  • Can Regulators Test the Paradox Before Banks Must Solve It?
  • Does the EU AI Act Make the Privacy-Compliance Paradox a Trilemma?
  • How Has Privacy Compliance Maturity Evolved Across European Banks?
  • Can You Automate a Data Protection Impact Assessment?
  • What Have We Learned -- and What Remains Unsolvable?
  • What Are the Six Things Every Compliance Officer Must Remember?
(Introduction)GDPR Foundations \& Information TheoryDifferential PrivacyAnonymization TechniquesPrivacy-Preserving AnalyticsThe Compliance Paradox \& Regulatory Engineering
MiniPrivacy Compliance
10 slides
  • (Slides)
  • Why Does the EU Tell Banks to Collect Everything AND Collect Nothing?
  • Have You Ever Been Asked to Do Two Contradictory Things by the Same Boss?
  • What Makes Privacy-Preserving Compliance Different from Regular Compliance?
  • What Happens to One Customer's Data in the GDPR-AML Collision?
  • How Do You Build a System That Knows Everything but Remembers Nothing?
  • What Goes Wrong When Privacy Technology Fails in a Compliance System?
  • Which Countries Lead in Privacy-Preserving Compliance -- and Which Are Still Stuck?
  • Who Wins and Who Loses When Privacy Meets Compliance?
  • The Privacy-Compliance Dial -- Where Should Your Institution Sit?
  • Can You Design a GDPR-Compliant AML System?
(Slides)
ExtendedRegtech
27 slides
  • (Slides)
  • What Will You Be Able to Do After This Lecture?
  • How Do Economists Model the Regulator-Bank Relationship?
  • How Much Have Banks Paid for Getting Compliance Wrong?
  • Where Does the Compliance Budget Actually Go?
  • Why Has SAR Volume Quadrupled While Crime Detection Stayed Flat?
  • How Many Transactions Does It Take to Produce One Conviction?
  • Building a Rule-Based AML Monitor in Python
  • Can a 130-Year-Old Math Formula Catch Modern Financial Criminals?
  • Implementing Benford's Law Analysis in Python
  • Why Can't Individual Transaction Monitoring See Corporate Networks?
  • Building a Shell Company Detection Pipeline in Python
  • How Can Machines Read 30,000 Pages of Financial Regulation?
  • Parsing Regulatory Text with TF-IDF in Python
  • When the Model Says 80\% Risk, How Often Is It Actually Right?
  • Is RegTech a Trend or a Structural Transformation?
  • Are Regulators Practicing What They Preach About Technology?
  • Is It Cheaper to Comply or to Pay the Fine?
  • How Do You Model Customer Risk as a Bayesian Inference Problem?
  • How Does an ML Model Decide What Looks `Abnormal'?
  • What Language Do Machines Use to Talk to Regulators?
  • Why Is the EU Now Regulating Banks' Cloud Providers?
  • Generating Regulatory Reports Programmatically
  • What Does the EU AI Act Mean for Your AML Model?
  • What Happens When the Compliance Model Itself Is Wrong?
  • Should Your Bank Build Its Own RegTech or Buy Off-the-Shelf?
  • Is Compliance Moving Toward Continuous Monitoring or Just Continuous Reporting?
  • Key Takeaways
(Slides)
MiniRegtech
10 slides
  • (Slides)
  • Why Does Filing Two Million Suspicious Activity Reports Still Miss 98\% of Money Laundering?
  • Have You Ever Searched Through So Much Information That You Stopped Finding Anything?
  • What Separates Watching Everything from Understanding Anything?
  • Follow One Suspicious Transaction Through Three Compliance Systems
  • How Do You Build a System That Sees the Needle Without Drowning in the Haystack?
  • What Happens When the Compliance System Becomes the Risk?
  • Where Is Smart Regulation Actually Working -- and Where Is It Just More Paperwork?
  • Who Wins and Who Loses When Compliance Goes Algorithmic?
  • The Transparency Dial: How Much Oversight Is Enough -- and When Does More Become Less?
  • Your Challenge: Design a RegTech System That Reports Less but Detects More
(Slides)
ExtendedSanctions Screening
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Sanctions Architecture \& Data Sources
  • Why Does ``Muhammad Al-Rashid'' Match ``Muhd El Rasheed''?
  • How Much Do OFAC, EU, and UN Sanctions Lists Overlap?
  • Can You Implement Jaro-Winkler Without Any String Library?
  • Where Does the Ambiguous Zone Between True and False Matches Fall?
  • What Is the Minimum Number of Edits to Turn One Name Into Another?
  • What Are the Four Major Sanctions and Risk Databases Banks Must Screen?
  • Fuzzy Matching \& NLP for Name Screening
  • Which Name Pairs Fall Into the Ambiguous Matching Zone?
  • How Do You Build the Levenshtein DP Matrix Step by Step?
  • Which Node in a Transaction Network Is Most ``Central'' to Illicit Flows?
  • Do High-Centrality Nodes Also Have High Transaction Volume?
  • How Do Shell Companies Move \$10M Across Jurisdictions in Three Layers?
  • What Are the Three Families of Name Normalization for Multilingual Screening?
  • Graph Analytics for Transaction Networks
  • How Has the Alert Composition Changed as Graph Analytics Was Adopted?
  • How Does PageRank Propagate Suspicion Through a Transaction Network?
  • How Do You Implement PageRank on an Adjacency Matrix in 18 Lines?
  • Does ML Re-Ranking Promote the Highest-Risk Alerts to the Top of the Queue?
  • Can a 2D Contour Map Reveal Transaction Patterns Invisible to Threshold Rules?
  • Alert Triage \& Machine Learning
  • How Does Bayes' Theorem Transform Raw Alert Features Into a Risk Score?
  • Which Features Drive the Most Variance in False Positive Investigation Cost?
  • Does Your Transaction Dataset Follow Benford's Law -- or Is Someone Gaming It?
  • Where Does Your Screening Engine Sit on the Precision-Recall Frontier?
  • What Threshold Minimizes the Total Expected Cost of Sanctions Screening?
  • How Does a Human-in-the-Loop ML Triage System Cut Investigation Time in Half?
  • De-Risking \& Financial Exclusion
  • What First-Digit Distribution Should Naturally-Occurring Amounts Follow?
  • How Do You Build a Lightweight Transliteration Normalizer for Arabic Names?
  • Which Remittance Corridors Have Lost the Most Bank Coverage Since 2015?
  • How Much Does Sanctions Screening Cost Across Bank Size Tiers -- Per Transaction?
  • Can Shared Infrastructure Solve the De-Risking Paradox Without Raising Risk?
(Introduction)Sanctions Architecture \& Data SourcesFuzzy Matching \& NLP for Name ScreeningGraph Analytics for Transaction NetworksAlert Triage \& Machine LearningDe-Risking \& Financial Exclusion
MiniSanctions Screening
10 slides
  • (Slides)
  • Why Does Every Bank Spend \$500M on Compliance and Still Miss Sanctions Violations?
  • What If Your Wire Transfer Were Frozen for Three Weeks Because Your Name Matches a Sanctioned Person?
  • What Is the Difference Between a Sanctions List, a Watch List, and a PEP Database?
  • Follow One Wire Transfer Through the Screening Engine -- and Count the False Alarms?
  • How Does Fuzzy String Matching Find `Mohammad' When the List Says `Muhammed'?
  • What Happens When the Screening System Learns to Ignore Alerts -- and Misses a Real One?
  • Where Does Screening Accuracy Break Down -- and What Drives False Positive Rates?
  • Who Pays the Cost of Over-Screening -- Banks, Customers, or Entire Countries?
  • The Screening Optimization Framework: How Do You Tune for Risk Without De-Banking the Innocent?
  • Your Challenge: Redesign an Alert Triage Workflow to Cut False Positives by 50\%
(Slides)

L05 Blockchain Fundamentals10 lectures

MainBlockchain Fundamentals
21 slides
  • The Trust Problem in Digital Transactions
  • Why Is Trust the Most Expensive Ingredient in Finance?
  • Why Can't You Copy-Paste a Digital Dollar?
  • How Does Blockchain Make Digital Things Scarce?
  • Learning Objectives
  • Blockchain Technology
  • Is a Blockchain a Database or a Trust Machine?
  • How Does Changing One Block Break the Entire Chain?
  • What Happens Between Clicking ``Send'' and Confirmation?
  • Consensus Mechanisms
  • How Do Strangers Agree When Some of Them Are Liars?
  • Why Does Bitcoin Burn More Energy than Argentina?
  • Can Economic Bonds Replace Energy as a Security Mechanism?
  • Which Consensus Mechanism Wins -- and What Does It Sacrifice?
  • Types of Blockchains
  • When Should You Use a Public vs. Private Blockchain?
  • How Do You Choose the Right Blockchain for a Financial Use Case?
  • Smart Contracts and Tokens
  • What If Contracts Could Enforce Themselves?
  • Why Does It Matter Whether a Token Is a Security or a Utility?
  • What Can Go Wrong with Smart Contracts and Blockchains?
  • How Can Layer 2 Solutions Break the Scalability Trilemma?
  • Can You Prove Something Without Revealing What You Know?
  • Blockchain in Financial Services
  • Where Does Blockchain Actually Reduce Costs in Finance?
  • Why Hasn't Blockchain Replaced Traditional Finance Yet?
  • Summary
  • Summary
The Trust Problem in Digital TransactionsBlockchain TechnologyConsensus MechanismsTypes of BlockchainsSmart Contracts and TokensBlockchain in Financial ServicesSummary
ExtendedBlockchain
27 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Cryptographic Foundations
  • Why Is a Hash Function the Foundation of All Blockchain Security?
  • How Does a Merkle Tree Let You Verify One Transaction Without Downloading the Whole Chain?
  • Can You Build a Working Hash Chain in 20 Lines of Python?
  • Consensus Mechanisms -- Game Theory
  • What Makes Proof of Work a Game -- and What Is the Nash Equilibrium?
  • How Much Energy Does Trust Cost -- and When Did the Price Change?
  • Can You Simulate a Proof-of-Work Mining Race?
  • When Does Staking Your Own Money Make You More Honest Than Spending Electricity?
  • How Sensitive Are Consensus Mechanisms to Parameter Changes?
  • Which Blockchain Can Actually Handle Visa-Scale Transactions?
  • The Scalability Trilemma
  • Why Can You Only Have Two of Three -- and Can You Prove It?
  • Where Do Major Blockchains Sit on the Trilemma Triangle?
  • Can You Build a Merkle Tree and Verify a Transaction Proof?
  • How Much Does It Cost to Use Ethereum -- and What Drives the Price?
  • Smart Contracts and Security
  • How Do You Formally Model a Smart Contract as a State Machine?
  • Can You Simulate a Simple Smart Contract in Python?
  • Does Bitcoin Hashrate Follow Price -- or Does Price Follow Hashrate?
  • How Long Do You Actually Wait for a Block?
  • Advanced Topics -- ZKPs, Forks, DeFi Infrastructure
  • How Do Zero-Knowledge Proofs Work -- and What Do They Actually Prove?
  • Can You Verify a Zero-Knowledge Proof Without Understanding the Math?
  • How Did Bitcoin Become 100 Blockchains?
  • Where Is the Money in DeFi -- and How Concentrated Is It?
  • What Is the Formal Security Bound of a 51\% Attack?
  • How Fast and Small Can a Zero-Knowledge Proof Get?
  • What Have We Learned -- and What Remains Unsolved?
  • Key Takeaways
  • References and Further Reading
(Introduction)Cryptographic FoundationsConsensus Mechanisms -- Game TheoryThe Scalability TrilemmaSmart Contracts and SecurityAdvanced Topics -- ZKPs, Forks, DeFi Infrastructure
MiniBlockchain
10 slides
  • (Slides)
  • Why Would You Trust a Network of Strangers with Your Money?
  • When Was the Last Time You Thought About Who You Trust with Your Money?
  • What Does Blockchain Actually Replace -- and What Does It Keep?
  • Follow One Bitcoin from Alice to Bob -- Where Does Trust Enter?
  • What Do You Sacrifice to Get Consensus -- Energy, Capital, or Control?
  • What Happens When the Code Is the Contract -- and the Code Has a Bug?
  • Where Does Blockchain Actually Save Money in Finance?
  • Who Wins and Who Loses When You Remove the Middleman?
  • The Trust Spectrum: Every Blockchain Design Tips the Balance
  • Your Challenge: Evaluate a Blockchain Proposal
(Slides)
ExtendedComposability
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Protocol Composability Fundamentals
  • What Does the DeFi Dependency Graph Actually Look Like?
  • How Do You Formalize the Concept of Protocol Composability?
  • How Many Layers Deep Can You Stack DeFi Protocols?
  • What Are the Fundamental Building Blocks of Composable DeFi?
  • Why Is the ``Money Lego'' Metaphor Both Powerful and Dangerous?
  • Flash Loans \& Atomic Transactions
  • Why Can Flash Loans Exist Without Any Collateral?
  • How Fast Has Flash Loan Usage Grown Since 2020?
  • Can You Calculate Whether a Flash Loan Arbitrage Is Profitable?
  • What Are the Five Categories of Flash Loan Exploits?
  • What Does a Composability Failure Cascade Look Like in Practice?
  • Yield Aggregation \& Protocol Stacking
  • How Is DeFi's Total Value Locked Distributed Across Protocol Layers?
  • Where Does Your Money Actually Go When You Deposit Into a Yield Aggregator?
  • Can You Stack Yields or Do Risks Stack Faster Than Returns?
  • How Much Does Each Composability Layer Cost in Gas Fees?
  • Can You Simulate Whether Yield Stacking Beats Simple Strategies?
  • Oracle Dependencies \& Systemic Risk
  • Which Oracle Controls the Most DeFi Capital -- and What If It Fails?
  • How Do You Model the Probability of an Oracle-Driven Cascade?
  • How Correlated Are DeFi Protocols -- and Does Diversification Actually Work?
  • Can You Build a Real-Time Oracle Manipulation Detection System?
  • How Do You Quantify Systemic Risk in a Composable Protocol Stack?
  • Why Does Integration Complexity Grow Exponentially With Protocol Count?
  • Future of Composable Finance
  • What Were the Key Moments That Shaped DeFi Composability?
  • Can DeFi Build Circuit Breakers Without Destroying Composability?
  • Will Regulators Force Composability Into Walled Gardens?
  • Does Cross-Chain Composability Solve the Problem or Double the Risk?
  • Can You Simulate Cascading Failures Across a Composable Protocol Stack?
  • What Have We Learned About the Composability Paradox?
  • What Are the Six Composability Lessons Every DeFi Participant Must Know?
(Introduction)Protocol Composability FundamentalsFlash Loans \& Atomic TransactionsYield Aggregation \& Protocol StackingOracle Dependencies \& Systemic RiskFuture of Composable Finance
MiniComposability
10 slides
  • (Slides)
  • Why Can a Developer with Zero Capital Steal \$200 Million in a Single Transaction?
  • What If Anyone Could Rearrange the Legos in Your Financial Life -- Without Asking?
  • What Are Money Legos -- and When Do They Become Money Grenades?
  • Follow a Flash Loan Attack: How \$0 Became \$8.1 Million in 15 Seconds
  • How Do Protocols Defend Against Attacks That Chain Through Other Protocols?
  • What Happens When One Broken Oracle Brings Down an Entire Ecosystem?
  • Where Do Flash Loan Attacks Hit Hardest -- and Which Chains Are Most Vulnerable?
  • Who Profits from the Money Lego Economy -- and Who Pays the Hidden Tax?
  • The Composability Spectrum: How Much Openness Is Too Much Openness?
  • Your Challenge: Trace a Composability Chain and Identify the Weakest Link
(Slides)
LGBlockchain Fundamentals
10 slides
  • (Slides)
  • Why Did Someone Invent a System Designed to Make Banks Unnecessary?
  • How Many Intermediaries Do You Trust With Your Money Right Now?
  • What Makes a Blockchain Different from a Regular Database?
  • Follow One Bitcoin Transaction from Send Button to Confirmed Block
  • How Does a Chain of Blocks Become Tamper-Proof?
  • What Happens When a ``Trustless'' System Requires You to Trust the Wrong People?
  • Where Is Blockchain Actually Being Adopted in Finance?
  • Who Wins and Who Loses When a Database Replaces an Institution?
  • Four Questions That Reveal Whether a Use Case Actually Needs a Blockchain
  • Should the Swiss Land Registry Use Blockchain?
(Slides)
ExtendedSmart Contracts
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Solidity Fundamentals \& Gas Economics
  • How Does a Stack Machine Execute Your Smart Contract -- and Why Does Every Instruction Have a Price?
  • How Much Does Each Type of Computation Cost on Ethereum?
  • Can You Cut a Smart Contract's Gas Cost in Half with Three Tricks?
  • Vulnerability Taxonomy \& Formal Verification
  • What Are the Species in the Smart Contract Vulnerability Zoo?
  • Why Is Reentrancy a Cycle in the Call Graph -- and How Do You Prove Its Absence?
  • Can You Build a Reentrancy Detector in 15 Lines of Python?
  • How Good Are Automated Tools at Finding Smart Contract Bugs?
  • AMM Mathematics \& Liquidity
  • Why Does x Times y Equals k Actually Work as a Market?
  • How Much Do Liquidity Providers Actually Lose -- and Is It Really ``Impermanent''?
  • When Do AMMs Generate the Most Revenue -- and Who Captures It?
  • When Do Liquidity Providers Actually Make Money?
  • Can You Simulate a Constant Product AMM and Calculate Impermanent Loss?
  • Flash Loans \& MEV
  • What Is the Formal Profit Condition for a Flash Loan Attack?
  • What Does a Flash Loan Attack Look Like from the Inside?
  • What Is the Nash Equilibrium of the Sandwich Attack Game?
  • Can You Simulate a Sandwich Attack and Calculate the Optimal Frontrun Size?
  • How Much Value Do MEV Bots Extract -- and Which Strategies Dominate?
  • What Does a Sandwich Attack Look Like Inside a Block?
  • Governance, Oracles \& Composability Risk
  • What Does It Cost to Buy a Vote in a Decentralized Democracy?
  • Which Protocols Are Most Vulnerable to Governance Attacks -- and How?
  • Can You Detect When an Oracle Price Feed Is Being Manipulated?
  • What Happens When One Corrupted Price Feed Cascades Through DeFi?
  • How Do You Quantify the Risk of Interconnected Protocols Failing Together?
  • How Fast Does Risk Grow as You Stack More Protocols Together?
  • Can You Simulate a Cascading Failure in a Composable Protocol Stack?
  • What Have We Learned -- and What Remains Unsolved in DeFi Engineering?
  • What Are the Six Engineering Lessons Every DeFi Developer Must Internalize?
  • References and Further Reading
(Introduction)Solidity Fundamentals \& Gas EconomicsVulnerability Taxonomy \& Formal VerificationAMM Mathematics \& LiquidityFlash Loans \& MEVGovernance, Oracles \& Composability Risk
MiniSmart Contracts
10 slides
  • (Slides)
  • Why Did a Single Missing Keyword Cost Ethereum \$60 Million?
  • Would You Sign a Contract That Can Never Be Changed -- Not Even to Fix a Typo?
  • What Makes a Smart Contract Smart -- and What Makes It Dangerous?
  • Follow the DAO Hack: How 3.6 Million Ether Disappeared in Broad Daylight
  • How Do Developers Build Upgradeable Systems on an Immutable Platform?
  • What Breaks When the Bridge Between Blockchain and Reality Has a Bug?
  • Where Are Smart Contracts Actually Reducing Costs -- and Where Are They Adding Risk?
  • Who Wins and Who Loses When Code Replaces Contracts?
  • The Immutability Dial: How Much Permanence Is Too Much?
  • Your Challenge: Audit a Smart Contract and Find the Vulnerability
(Slides)
ExtendedTokenization
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Token Taxonomy \& Standards
  • Does the Quantity Theory of Money Apply to Token Economies?
  • Which Token Standard Is Right -- and What Are You Sacrificing?
  • Can You Simulate an ERC-20 Token: Balances, Transfer, and Allowance?
  • How Much Does Tokenization Lower the Minimum Investment Threshold?
  • What Are the Formal Rights of a Fractional Token Holder?
  • What Decision Tree Should a Token Issuer Follow to Select the Right Standard?
  • Legal Architecture of Tokenized Securities
  • Which Asset Classes Remain Illiquid Even After Tokenization?
  • How Do You Split a Real Estate Asset into 10{,
  • How Much Is Illiquidity Worth -- and What Does the Longstaff Model Predict?
  • Where Does the Money Go? Anatomy of Tokenization Fees
  • Which Jurisdictions Have a Workable Regulatory Framework for Tokenized Securities?
  • What Legal Structure Sits Between the Token and the Physical Asset?
  • Fractional Ownership \& Market Microstructure
  • How Fast Is the Real-World Asset Tokenisation Market Growing?
  • Can a Single Formula Replace the Order Book in a Tokenized Asset Market?
  • How Does a Real Estate AMM React to a Large Block Trade?
  • Do Larger Tokenized Asset Markets Automatically Generate More Liquidity?
  • By How Much Does Tokenization Narrow the Illiquidity Discount Over Time?
  • Valuation \& Pricing of Tokenized Assets
  • How Does a Walrasian Auction Find the Clearing Price in a Thin Market?
  • Which Institutions Are Leading the Tokenization Race -- and How Fast Are They Growing?
  • How Do You Distribute Dividends to 10{,
  • Are Tokenized Assets Equally Distributed -- or Is Ownership Concentrated?
  • What Is the Formal Definition of the Gini Coefficient for a Token Distribution?
  • Why Is Valuing a Tokenized Illiquid Asset Harder Than Valuing Its Underlying?
  • Regulatory Frameworks \& Institutional Adoption
  • Can You Write the Howey Test as a Boolean Predicate?
  • How Does an ERC-1400 Smart Contract Enforce Investor Whitelisting?
  • How Much Does It Cost to Audit a Tokenized Security Smart Contract?
  • What Happens to Settlement Times When Assets Move On-Chain?
  • What Needs to Happen Before Tokenized Assets Reach \$10 Trillion?
(Introduction)Token Taxonomy \& StandardsLegal Architecture of Tokenized SecuritiesFractional Ownership \& Market MicrostructureValuation \& Pricing of Tokenized AssetsRegulatory Frameworks \& Institutional Adoption
MiniTokenization
10 slides
  • (Slides)
  • Why Can You Buy 0.001 Bitcoin but Not 0.001 of a Skyscraper?
  • What If You Could Sell 10\% of Your Home Equity to Pay for Grad School?
  • What Is the Difference Between a Token, a Security, and a Digital Twin?
  • Follow One Tokenized Bond from Issuance to Secondary Market Trade
  • How Do You Represent a Legal Claim on a Physical Asset as a Blockchain Token?
  • What Happens to Your Token When the Real-World Asset Burns Down?
  • Where Is Real-World Asset Tokenization Growing -- and Which Asset Classes Lead?
  • Who Wins When Illiquid Assets Become Tradeable -- Issuers, Investors, or Intermediaries?
  • The Tokenization Readiness Checklist: When Does Tokenization Add Value vs Complexity?
  • Your Challenge: Design a Tokenized Fund for an Illiquid Asset Class
(Slides)

L06 Financial Markets & Trading Infrastructure10 lectures

MainFinancial Markets & Trading Infrastructure
21 slides
  • (Introduction)
  • Is Speed an Unfair Advantage in Trading?
  • What Does a Real-Time Map of Supply and Demand Look Like?
  • Who Are the Players in a Financial Market?
  • Learning Objectives
  • Why Financial Markets Exist
  • Why Do Financial Markets Exist at All?
  • Why Can Asset Demand Rise When Prices Rise?
  • Can Anyone Consistently Beat the Market?
  • How Do Derivatives Enable the Transfer of Risk?
  • What Role Did Derivatives Play in the 2008 Financial Crisis?
  • Market Structure and Order Execution
  • When Is a Centralized Exchange Better than Bilateral Trading?
  • How Do You Choose Between Price Certainty and Execution Speed?
  • What Determines Which Orders Execute First?
  • How Does Regulation Prevent Brokers from Cheating Clients?
  • Trading Technology
  • Can Satellite Photos and Credit Card Data Predict Stock Prices?
  • Which Market Trades 7.5 Trillion Dollars Every Day?
  • Clearing and Settlement
  • What Happens After You Click ``Buy''?
  • How Does a CCP Become the Buyer to Every Seller?
  • Why Does Settling a Trade Still Take Two Days?
  • Digital Transformation
  • Is Commission-Free Trading Really Free?
  • Can Blockchain Finally Deliver Instant Settlement?
  • Summary
  • Summary
(Introduction)Why Financial Markets ExistMarket Structure and Order ExecutionTrading TechnologyClearing and SettlementDigital TransformationSummary
ExtendedAlgo Trading
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Optimal Execution Theory
  • Why Does Slicing a Large Order into Pieces Save Money?
  • How Does Intraday Volume Shape the Optimal Execution Schedule?
  • What Is the True Cost of Executing a Large Order?
  • Can You Compute the Optimal Execution Trajectory in 20 Lines?
  • Market Impact \& the Almgren-Chriss Model
  • What Shape Does the Optimal Execution Path Take?
  • Where Is the Sweet Spot Between Execution Cost and Execution Risk?
  • How Much of Your Execution Cost Is Permanent vs Temporary?
  • How Quickly Does Market Impact Fade After a Large Trade?
  • Can You Build a VWAP Engine That Adapts to Live Volume?
  • HFT Strategies \& Market Making
  • How Does a Market Maker Set the Optimal Bid-Ask Spread?
  • How Does a Market Maker's Inventory Drive Their Quotes?
  • How Much Money Does a Microsecond of Speed Advantage Generate?
  • At What Point Does Faster Hardware Stop Paying for Itself?
  • Can You Simulate a Market Maker's Day in 20 Lines?
  • Smart Order Routing \& Transaction Cost Analysis
  • Where Did the Money Go Between Decision and Execution?
  • Which Component of Transaction Cost Eats Most of Your Alpha?
  • Can You Build an Implementation Shortfall Calculator?
  • Why Does Your Broker Route Orders to One Exchange Instead of Another?
  • How Do You Mathematically Optimize Where to Send Each Child Order?
  • Can You Build a Simple Smart Order Router?
  • Backtesting, Overfitting \& Regulation
  • How Many Backtests Does It Take to Find a Strategy That Only Looks Good?
  • How Do You Tell a Genuine Edge from a Backtest Mirage?
  • Why Do Brilliant Backtests Fail in Live Trading?
  • Can You Compute the Probability Your Backtest Is Overfitted?
  • What Does MiFID II Require from Every Algorithm That Trades in Europe?
  • How Does a Smart Order Router Choose Between Lit Exchanges and Dark Pools?
  • How Has Regulation Evolved to Keep Pace with Algorithmic Trading?
  • References and Further Reading
(Introduction)Optimal Execution TheoryMarket Impact \& the Almgren-Chriss ModelHFT Strategies \& Market MakingSmart Order Routing \& Transaction Cost AnalysisBacktesting, Overfitting \& Regulation
MiniAlgo Trading
10 slides
  • (Slides)
  • Why Did We Build Machines That Trade Faster Than We Can Think?
  • How Many Algorithms Touched Your Last Investment Before You Even Saw the Price?
  • What Separates a Helpful Execution Tool from an Autonomous Trading Machine?
  • Follow One VWAP Order from Portfolio Manager to Execution Across Six Hours
  • How Does a Human-Driven Trading Desk Differ from an Algorithmic One?
  • What Happens When an Algorithm Crashes the Market in 36 Minutes?
  • How Did Algorithms Go from Executing Orders to Dominating Markets?
  • Who Wins and Who Loses When Machines Replace Human Traders?
  • Four Questions That Reveal Whether an Algorithmic System Helps or Harms the Market
  • Your Challenge: Evaluate an Algorithmic Trading Strategy
(Slides)
ExtendedFinancial Markets
28 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Market Microstructure
  • How Does the Order Book Turn Individual Intentions into a Market Price?
  • What Does the Full Depth of Supply and Demand Look Like?
  • Can You Simulate Price Discovery in 25 Lines of Python?
  • How Much Does Your Order Move the Market -- and Can You Predict It?
  • When Is the Market Most Liquid -- and When Should You Avoid Trading?
  • Market Efficiency and Price Formation
  • How Do You Statistically Test Whether a Market Is Efficient?
  • Can You Test Market Efficiency in 20 Lines of Python?
  • Are Stock Returns Really Normally Distributed -- or Is That a Dangerous Assumption?
  • What Fraction of Trades Are Truly Large -- and Why Does the Distribution Matter?
  • Do Markets Move Together -- and When Does Diversification Fail?
  • Trading Infrastructure
  • How Much Is One Microsecond Worth in the Latency Arms Race?
  • Can You See the Speed of Markets -- and the Gaps Between Trades?
  • Can You Build a VWAP Execution Algorithm That Beats the Benchmark?
  • Where Have All the Trades Gone -- and Why Are They Spread Across So Many Venues?
  • How Do Dark Pools Match Orders Without Revealing Prices?
  • Post-Trade and Settlement
  • How Does a CCP Turn 1,000 Bilateral Exposures into 50 Net Positions?
  • What Happens to Your Collateral If a CCP Member Defaults?
  • Can You Calculate How Much Collateral a CCP Saves the Market?
  • Which Countries Settled Fastest -- and Who Is Still Waiting?
  • Digital Markets and Regulation
  • Is Commission-Free Trading Really Free -- or Does Someone Else Pay the Price?
  • When Do Retail Traders Trade -- and How Does It Differ from Institutions?
  • Can You Measure Whether Your Broker Gave You Best Execution?
  • How Does Tokenization Change the Economics of Owning and Trading Securities?
  • How Many Retail Investors Entered the Market -- and What Changed?
  • What Have We Learned -- and What Remains Unsolved?
  • Key Takeaways
  • References and Further Reading
(Introduction)Market MicrostructureMarket Efficiency and Price FormationTrading InfrastructurePost-Trade and SettlementDigital Markets and Regulation
MiniFinancial Markets
10 slides
  • (Slides)
  • Why Did We Automate Markets If Speed Creates Fragility?
  • Where Were You When \$1 Trillion Vanished in 36 Minutes?
  • What Makes Modern Markets Tick -- Order Books, Engines, and Data?
  • What Happens When Retail Traders Meet Market Microstructure -- GameStop 2021?
  • How Did Electronic Trading Reshape Both Volume and Trade Size Simultaneously?
  • What Systemic Risks Does a Hyper-Connected Market Create That a Slow One Did Not?
  • Where Are Financial Markets Heading -- AI, DeFi, and the Race to T+0?
  • What Changes When Markets Never Close and Prices Never Rest?
  • How Did Regulators Respond When Markets Moved Faster Than Their Rule Books?
  • Your Challenge: Design a Circuit Breaker for a Market That Never Closes?
(Slides)
LGTraditional Infrastructure
10 slides
  • (Slides)
  • Why Does Your Bank Run on Software Written Before You Were Born?
  • What Invisible Infrastructure Sits Between Your Paycheck and Your Bank Balance?
  • What Five Systems Form the Backbone of Global Finance?
  • Follow Your Salary From Your Employer's Account to Your Bank Balance
  • What Does a Core Banking System Actually Look Like Inside?
  • What Happens When Fifty-Year-Old Infrastructure Finally Breaks?
  • How Fast Is Each Layer of Financial Infrastructure -- and Why Does It Matter?
  • Who Wins and Who Loses as Legacy Infrastructure Gets Replaced?
  • Four Questions That Reveal Whether Your Bank's Infrastructure Is a Strength or a Liability
  • Should a Mid-Sized Swiss Bank Migrate to Cloud or Keep the Mainframe?
(Slides)
ExtendedMicrostructure
31 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Order Book Architecture
  • How Does a Limit Order Book Match Buyers and Sellers?
  • Can the Shape of the Order Book Predict Where Prices Are Heading?
  • What Does Order Book Imbalance Look Like Through Time?
  • Can You Rebuild an Order Book from a Raw Message Feed?
  • Which Venue Actually Discovers the True Price?
  • How Does Each Trade Permanently Shift the Price?
  • Spread Decomposition \& Information Content
  • Why Must the Spread Exist Even Without Any Operating Costs?
  • How Does the Composition of the Spread Change Across Stock Types?
  • How Do Econometricians Separate the Three Spread Components?
  • Why Do Larger Trades Carry More Information About the True Value?
  • How Does Information Asymmetry Scale with Company Size?
  • Can You Estimate the Adverse Selection Component from Trade Data?
  • Market Making \& Liquidity Provision
  • What Is the Market Maker's Fundamental Optimization Problem?
  • What Does a Market Maker's P\&L Actually Look Like?
  • Does Making the Minimum Price Increment Smaller Help or Hurt Traders?
  • Why Is Liquidity Worst When You Need It Most?
  • Can You Simulate a Market Maker's Quoting Strategy?
  • Do All Trading Venues Attract Equally Informed Order Flow?
  • Dark Pools \& Venue Fragmentation
  • Why Would Anyone Want to Trade in the Dark?
  • How Did US Equity Trading Go from Two Venues to Fifty?
  • How Much of the Market Has Gone Dark?
  • How Do You Measure Whether Fragmentation Helps or Hurts?
  • Can You Simulate Whether a Dark Pool Improves Execution?
  • How Should a Trader Choose Between Lit, Dark, and Periodic Auction?
  • HFT \& The Speed Arms Race
  • What Exactly Do High-Frequency Traders Do All Day?
  • How Fast Is Fast in Today's Markets?
  • How Much Is a Microsecond Worth in Dollar Terms?
  • Could Batch Auctions Eliminate the Socially Wasteful Speed Race?
  • Has HFT Made Markets Better or Worse for Everyone Else?
  • References and Further Reading
(Introduction)Order Book ArchitectureSpread Decomposition \& Information ContentMarket Making \& Liquidity ProvisionDark Pools \& Venue FragmentationHFT \& The Speed Arms Race
MiniMicrostructure
10 slides
  • (Slides)
  • Why Do Markets That Show Every Order Still Hide Half Their Trades?
  • How Much of the Price You Paid Was the Cost of Someone Else Knowing Your Order?
  • What Are the Building Blocks That Determine Every Price You See?
  • Follow One Institutional Order Through the Order Book and Watch the Price Move
  • How Do Dark Pools Hide Orders Without Hiding the Market?
  • What Happens When Transparency Vanishes in a Crisis -- and Everyone Wants to Sell?
  • How Wide Is the Spread -- and How Much Does It Change During a Crisis?
  • Who Pays for Transparency -- and Who Profits from Opacity?
  • Three Questions That Reveal Whether a Market Is Truly Fair
  • Your Challenge: Design a Market Rule That Balances Transparency and Protection
(Slides)
ExtendedVolatility
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Stylized Facts of Financial Returns
  • How Does One Equation Capture the Fact That Large Moves Predict Large Moves?
  • Why Does the Normal Distribution Fail at the Tails of Financial Returns?
  • How Do You Estimate GARCH Parameters from Return Data?
  • Why Do Squared Returns Show Autocorrelation When Raw Returns Do Not?
  • How Does EGARCH Capture the Asymmetry That Symmetric GARCH Misses?
  • Which Stylized Facts Does Each Model Capture -- and Which Does It Miss?
  • GARCH Family Models
  • What Does the GARCH Variance Path Look Like Through Calm and Crisis?
  • How Does the EWMA Estimator Trade Off Responsiveness Against Stability?
  • How Does Maximum Likelihood Find the Best GARCH Parameters?
  • Why Do Negative Returns Amplify Future Volatility More Than Positive Ones?
  • Why Does Implied Volatility Almost Always Exceed Realized Volatility?
  • When Should You Choose GARCH, EGARCH, or GJR-GARCH?
  • Realized Volatility \& HF Estimation
  • Why Does Realized Volatility Explode When You Sample Too Frequently?
  • How Does Quadratic Variation Connect High-Frequency Returns to True Volatility?
  • How Do You Compute Realized Volatility from Tick Data in Practice?
  • What Does the Full Implied Volatility Surface Look Like?
  • How Does the Volatility Smile Change Across Maturities?
  • Implied Volatility \& Surface
  • How Do You Extract the Market's Fear from a Single Option Price?
  • What Does the VIX Futures Curve Tell You About the Market's Fear Timeline?
  • How Do You Extract the Volatility Smile from Option Prices?
  • How Much Does the Normal Distribution Underestimate Tail Risk?
  • How Do You Parameterize the Volatility Surface for Pricing and Interpolation?
  • What Does Each Region of the Volatility Surface Tell You About Market Fear?
  • Volatility Trading \& Risk Management
  • How Do You Price a Bet on Future Volatility Without a Volatility Model?
  • How Do You Test Whether Returns Follow a Random Walk?
  • At Which Horizons Do Returns Depart from the Random Walk?
  • Where Does Volatility Cluster -- and What Triggers Regime Switches?
  • How Do Institutions Trade Volatility as a Standalone Asset Class?
(Introduction)Stylized Facts of Financial ReturnsGARCH Family ModelsRealized Volatility \& HF EstimationImplied Volatility \& SurfaceVolatility Trading \& Risk Management
MiniVolatility
10 slides
  • (Slides)
  • Why Do Markets Alternate Between Long Calms and Sudden Storms?
  • What Does It Feel Like to Lose a Year of Gains in a Single Afternoon?
  • What Is Volatility -- and Why Are There At Least Three Ways to Measure It?
  • Follow the VIX Through One Market Crash -- and Watch Predicted vs Actual Diverge
  • How Does a GARCH Model Capture the Fact That Volatility Breeds Volatility?
  • What Happens When Everyone Uses the Same Volatility Model -- and the Model Is Wrong?
  • Where Does Volatility Cluster -- and What Triggers Regime Switches?
  • Who Benefits from Volatility -- Dealers, Quants, or Long-Term Investors?
  • The Volatility Estimation Checklist: When Should You Trust the Model and When Should You Override It?
  • Your Challenge: Estimate GARCH Parameters from Return Data and Forecast 5-Day Volatility
(Slides)

L07 Risk Management & Regulation10 lectures

MainRisk Management & Regulation
25 slides
  • Why Manage and Regulate Risk?
  • What Is the Difference Between Risk and Uncertainty?
  • Why Are Banks the Most Heavily Regulated Firms?
  • How Do the Four Types of Financial Risk Interact?
  • Learning Objectives
  • Types of Financial Risk (Detail)
  • How Do You Calculate Expected Loss on a Loan?
  • Can a Bank Run Become a Self-Fulfilling Prophecy?
  • Statistical Foundations for Risk Measurement
  • Why Do Risk Managers Need Statistics?
  • Why Do Risk Managers Care Most About the Tails?
  • Risk Measurement
  • How Bad Could a Normal Bad Day Get?
  • Which VaR Method Should You Use -- and Why?
  • If VaR Is the Cliff Edge, How Far Is the Fall?
  • Stress Testing
  • What Happens When Model Assumptions Break Down?
  • How Do You Know If Your Risk Model Is Any Good?
  • Basel Framework
  • Why Does Every Basel Accord Follow a Crisis?
  • How Do Three Pillars Work Together to Keep Banks Safe?
  • How Much Capital Must a Bank Hold -- and Why?
  • Can a Bank Survive 30 Days Without New Funding?
  • European and Swiss Regulation
  • How Does MiFID II Protect Investors Across Europe?
  • What Changed When Research Was Unbundled from Trading?
  • How Do Europe's Three Major Regulations Fit Together?
  • Why Is a Messaging Standard Transforming Global Payments?
  • What Makes Switzerland's Regulatory Approach Unique?
  • Digital Risk Management
  • How Is Technology Shifting Risk Management from Reactive to Real-Time?
  • Why Is Cyber Risk the Fastest-Growing Threat to Banks?
  • Summary
  • Summary
Why Manage and Regulate Risk?Types of Financial Risk (Detail)Statistical Foundations for Risk MeasurementRisk MeasurementStress TestingBasel FrameworkEuropean and Swiss RegulationDigital Risk ManagementSummary
ExtendedCybersecurity
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • The Financial Threat Landscape
  • Who Is Actually Attacking Financial Institutions -- and What Do They Want?
  • How Have the Primary Attack Vectors Evolved Over the Past Decade?
  • Why Does a Data Breach Cost Financial Firms More Than Almost Any Other Industry?
  • How Do You Classify Cyber Threats by Motive, Capability, and Persistence?
  • Attack Vectors \& Incident Response
  • How Long Does It Actually Take to Detect, Contain, and Recover From a Breach?
  • Is Paying the Ransom a Rational Business Decision -- or a Systemic Mistake?
  • Why Does Phishing Still Work After Two Decades of Security Awareness Training?
  • What Does a Financial Institution's Incident Response Playbook Actually Contain?
  • Can You Map Every Stage of a Financial Cyber Attack to a Defensive Control?
  • Zero Trust \& Defence-in-Depth
  • How Far Along Are Financial Institutions in Adopting Zero Trust Architecture?
  • Where Are the Gaps in a Typical Financial Institution's Security Posture?
  • What Are the Five Pillars of Zero Trust Architecture in Financial Services?
  • What Does the Distribution of Vulnerabilities Tell Us About Where to Focus Patching?
  • How Many Layers of Defence Must an Attacker Penetrate to Reach Core Banking Data?
  • DORA \& Regulatory Frameworks
  • What Are the Five Pillars of DORA and Why Does Each One Matter?
  • How Wide Is the Gap Between Current Practice and DORA Requirements?
  • How Does DORA Compare to Existing Cybersecurity Frameworks?
  • What Does a Realistic DORA Implementation Timeline Look Like?
  • Third-Party Risk \& Cyber Insurance
  • Where Does Concentration Risk Hide in the Financial Vendor Ecosystem?
  • How Do You Score and Prioritise Third-Party ICT Risk Under DORA?
  • Is Cyber Insurance Becoming Unaffordable -- or Just Properly Priced?
  • What Does a Financial Cyber Insurance Policy Actually Cover -- and What Does It Exclude?
  • What Is the Difference Between a Vulnerability Scan and a Full Red Team Engagement?
  • Should You Pay the Ransom -- and What Does Game Theory Say?
  • How Do You Measure Whether Your Security Programme Is Improving Year Over Year?
  • Can You Put a Dollar Value on Cyber Risk -- and Should You?
  • Which Emerging Cyber Threats Will Reshape Financial Security in the Next Five Years?
  • What Are the Five Key Takeaways From Financial Cybersecurity?
(Introduction)The Financial Threat LandscapeAttack Vectors \& Incident ResponseZero Trust \& Defence-in-DepthDORA \& Regulatory FrameworksThird-Party Risk \& Cyber Insurance
MiniCybersecurity
10 slides
  • (Slides)
  • Why Does Making Banking More Convenient Also Make It More Dangerous?
  • How Many of Your Financial Accounts Could Be Reached Through a Single Stolen Password?
  • What Types of Cyber Threats Actually Hit Financial Institutions?
  • Follow One Ransomware Attack from First Click to Last Recovery Step
  • Should a Bank Defend at the Perimeter, Inside the Network, or Both?
  • What Happens When Your Cloud Provider Goes Down and Takes Half the Banking System With It?
  • How Does the Cost of a Single Cyber Incident Cascade Through a Financial Institution?
  • Who Wins and Who Loses When a Major Financial Institution Is Breached?
  • Four Questions That Reveal Any Financial Institution's True Cyber Resilience
  • Your Challenge: Evaluate a Financial Institution's Cyber Resilience
(Slides)
LGRegulatory Frameworks
10 slides
  • (Slides)
  • Why Is Every Major Financial Regulation Named After a Crisis It Failed to Prevent?
  • How Many Regulatory Requirements Touched Your Bank Account This Morning?
  • What Do PSD2, MiFID~II, and Basel Actually Regulate?
  • How Would Basel~III Capital Requirements Have Prevented Lehman's Collapse?
  • Who Makes the Rules, Who Enforces Them, and How Do Banks Comply?
  • When Does Regulation Itself Become the Problem?
  • How Long Does It Take for Financial Regulation to Go from Adoption to Enforcement?
  • Who Wins and Who Loses When a New Regulation Takes Effect?
  • Four Questions That Reveal Whether Any Financial Regulation Actually Works
  • Your Challenge: Does the EU AI Act Adequately Address Algorithmic Trading Risks?
(Slides)
ExtendedOperational Resilience
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Operational Risk Taxonomy
  • How Do You Model Operational Losses When Both Frequency and Severity Are Random?
  • What Shape Does an Operational Loss Distribution Actually Take?
  • Can You Simulate a Full Operational Loss Distribution in 18 Lines?
  • Which Categories of Operational Loss Actually Cost the Most?
  • Why Do Standard Distributions Fail in the Tail -- and What Replaces Them?
  • How Do Basel's Seven Risk Categories Map to Modern Digital Threats?
  • Scenario Design \& Reverse Stress Testing
  • How Does Stress Re-Rank the Risks You Thought You Understood?
  • Can You Generate Internally Consistent Stress Scenarios in 18 Lines?
  • Why Does the Choice of Copula Determine Whether Your Stress Test Is Realistic?
  • Which Scenarios Are Both Plausible and Catastrophic?
  • How Wide Is the Uncertainty in Cumulative Operational Losses?
  • What Is the Difference Between Asking ``How Bad?'' and ``What Kills Us?''
  • Monte Carlo Simulation for Loss Estimation
  • Where Are the Blind Spots in Your Stress Test Programme?
  • How Do You Convolve Frequency and Severity Into a Single Capital Number?
  • Can You Find the Scenario That Kills the Bank Using Binary Search?
  • How Fast Must Each Business Process Recover -- and Which Ones Fail the Target?
  • How Long Does It Actually Take to Detect, Contain, and Resolve a Cyber Incident?
  • Automated Stress Test Infrastructure
  • How Does Basel III Calculate Operational Risk Capital Without Internal Models?
  • How Ready Is Each Institution Type for Operational Resilience Regulation?
  • Can You Calculate Recovery Objectives from a Dependency Graph?
  • Where Does Concentration Risk Hide in Your Vendor Network?
  • How Do You Measure the Average Loss in the Worst Scenarios?
  • What Does an End-to-End Automated Stress Test Architecture Look Like?
  • Regulatory Frameworks \& DORA
  • How Does a Single Vendor Failure Cascade Through the Financial Network?
  • Can You Fit a GPD to Operational Loss Tails in 18 Lines?
  • How Do Different Institution Types Compare on DORA Readiness?
  • Where Does Operational Risk Capital Actually Go?
  • What Does a DORA Compliance Roadmap Look Like for a Mid-Size Bank?
(Introduction)Operational Risk TaxonomyScenario Design \& Reverse Stress TestingMonte Carlo Simulation for Loss EstimationAutomated Stress Test InfrastructureRegulatory Frameworks \& DORA
MiniOperational Resilience
10 slides
  • (Slides)
  • Why Did the 2023 Banking Crisis Hit Exactly the Risks That Stress Tests Ignored?
  • What Happens to Your Savings When Your Bank's IT System Crashes for a Week?
  • What Is the Difference Between Business Continuity, Disaster Recovery, and Operational Resilience?
  • Follow One Bank Through a Coordinated Cyber-Attack -- Minute by Minute
  • How Do You Automate Stress Testing When the Scenarios Are Infinite?
  • What Happens When the Stress Test Itself Becomes a Source of Systemic Risk?
  • Where Are the Gaps in Current Stress Test Coverage?
  • Who Owns Operational Risk -- the CRO, the CIO, or the Board?
  • The Resilience Assessment Framework: Beyond Check-the-Box Compliance
  • Your Challenge: Design a Reverse Stress Test for a Digital Bank
(Slides)
ExtendedRisk Management
28 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Quantitative Risk Modeling
  • How Do You Model the Full Distribution of Losses in a Credit Portfolio?
  • What Shape Does the Loss Distribution Actually Take -- and Why Does It Matter?
  • Can You Simulate 100,000 Credit Portfolios in 15 Lines of Python?
  • Why Do Correlations Lie About Tail Dependence -- and What Replaces Them?
  • How Does the Choice of Copula Change What You See in the Tails?
  • Which Risk Factors Drive the Most Variation in Portfolio Loss?
  • VaR \& ES Mathematical Framework
  • How Do You Derive VaR from a Return Distribution -- and What Happens When It Is Not Normal?
  • How Many VaR Breaches Are Too Many -- and What Happens When You Cross the Line?
  • Can You Calculate VaR and ES Three Different Ways in Python?
  • Why Is VaR Not a Coherent Risk Measure -- and Why Does That Matter?
  • How Much More Does ES Reveal Than VaR -- and When Does the Gap Explode?
  • When Do VaR Breaches Cluster -- and What Does Clustering Tell You?
  • Stress Testing \& Model Validation
  • What Scenario Would Actually Kill the Bank -- and How Do You Find It?
  • How Do Different Stress Scenarios Compare in Severity and Plausibility?
  • Can You Build a Multi-Factor Stress Test Engine in Python?
  • How Do You Measure the Risk of the Risk Model Itself?
  • How Much Do Different Risk Models Disagree -- and What Does the Disagreement Mean?
  • Capital Adequacy \& FRTB
  • How Do You Calculate Risk-Weighted Assets -- and Why Does the Method Matter?
  • How Is a Typical Bank's Risk Capital Allocated Across Risk Types?
  • Can You Build a Basel III Capital Adequacy Calculator in Python?
  • How Much More Capital Will FRTB Require -- and Which Banks Are Hit Hardest?
  • Digital Risk \& RegTech
  • How Do You Prove That a Machine Learning Credit Model Is Better Than a Human?
  • How Rapidly Is RegTech Replacing Manual Compliance -- and What Functions Lead?
  • Can You Quantify Operational Risk Using the Loss Distribution Approach?
  • What Have We Learned -- and What Remains Unsolved?
  • Key Takeaways
  • References and Further Reading
(Introduction)Quantitative Risk ModelingVaR \& ES Mathematical FrameworkStress Testing \& Model ValidationCapital Adequacy \& FRTBDigital Risk \& RegTech
MiniRisk Management
10 slides
  • (Slides)
  • Why Do Risk Models Fail Precisely When We Need Them Most?
  • What Did Lehman Brothers' Risk Dashboard Look Like the Morning Before It Collapsed?
  • What Is the Difference Between Risk You Can Measure and Risk That Measures You?
  • How Did a Fund Run by Nobel Laureates Lose \$4.6 Billion in Six Weeks?
  • How Much Do VaR, Expected Shortfall, and Stress Tests Disagree When Markets Break?
  • What Happens When Every Bank's Risk Model Tells It to Sell at the Same Moment?
  • Where Is Risk Measurement Heading When AI and Climate Change Rewrite the Historical Record?
  • What Changes When Every Systemically Important Bank Uses the Same Risk Model?
  • Has Regulation Kept Pace With the Risks It Cannot Fully Measure?
  • Your Challenge: Diagnose the Measurement Paradox in a Real Portfolio Decision
(Slides)
ExtendedVar Es
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Extreme Value Theory \& Tail Modeling
  • Why Does Extreme Value Theory Let You Model Tails Without Knowing the Full Distribution?
  • How Do You Extract More Information from Tail Observations Than Block Maxima Allow?
  • How Stable Is the Tail Index Estimate -- and When Should You Stop Trusting It?
  • Can You Build a Risk Model That Is Nonparametric in the Body but Parametric in the Tails?
  • Can You Fit a Generalized Pareto Distribution to Tail Losses in 20 Lines?
  • How Much Do EVT Estimates Diverge from Gaussian -- and Does It Matter at 99.9\%?
  • Advanced Historical Simulation
  • What If You Could Give Historical Returns a Volatility Adjustment for Today's Regime?
  • How Quickly Did Filtered HS Detect the COVID Crash -- and How Badly Did Plain HS Lag?
  • How Many Observations Do You Need Before Your VaR Estimate Becomes Trustworthy?
  • Does the Square-Root-of-Time Rule Work -- or Does It Systematically Underestimate Multi-Day Risk?
  • Can You Build a Volatility-Aware Historical Simulator in Python?
  • Monte Carlo for Non-Linear Portfolios
  • Why Does a Linear Approximation Fail for Options -- and What Replaces It?
  • How Much Risk Does the Linear Approximation Miss in an Options Portfolio?
  • Can Three Principal Components Capture 90\% of a Multi-Factor Portfolio's Risk?
  • Can You Compute Delta-Gamma VaR for an Options Portfolio in Python?
  • How Does Option VaR Change Across the Strike-Maturity Landscape?
  • What Does the P\&L Distribution Look Like When Payoffs Are Non-Linear?
  • VaR Decomposition \& Risk Attribution
  • How Do You Decompose Portfolio VaR into Pieces That Add Up Exactly?
  • Which Positions Contribute the Most Risk Per Dollar of Capital Invested?
  • Can You Decompose Portfolio VaR into Position Contributions in Python?
  • Why Do Two Different ``Position-Level VaR'' Measures Give Different Answers?
  • Formal Backtesting \& Model Validation
  • How Do You Statistically Test Whether a VaR Model Has the Right Number of Breaches?
  • What If the Breaches Come at the Right Frequency but Cluster Together?
  • Can You Build a Kupiec and Christoffersen Backtest in Python?
  • How Do You Backtest Expected Shortfall When You Cannot Observe the Tail Mean Directly?
  • What Have We Learned -- and What Remains Unsolved?
  • Key Takeaways
  • References and Further Reading
(Introduction)Extreme Value Theory \& Tail ModelingAdvanced Historical SimulationMonte Carlo for Non-Linear PortfoliosVaR Decomposition \& Risk AttributionFormal Backtesting \& Model Validation
MiniVar Es
10 slides
  • (Slides)
  • Why Did Every Major Bank's Risk Model Fail on the Same Day?
  • How Confident Are You in a Number That Has Been Wrong Every Time It Mattered?
  • What Are the Three Approaches to Measuring VaR -- and Where Does Each Break?
  • Follow One VaR Calculation from Raw Returns to Risk Number
  • Why Is Expected Shortfall a Better Risk Measure Than VaR -- and What Did We Sacrifice?
  • What Happens When Your Risk Model Assumes Normality but Reality Has Fat Tails?
  • How Do VaR and ES Compare Across Different Market Regimes?
  • Who Benefits and Who Suffers When Risk Models Underestimate Tail Risk?
  • Three Questions That Reveal Whether a Risk Model Is Trustworthy
  • Your Challenge: Diagnose a Risk Model and Recommend Improvements
(Slides)

L08 Emerging Topics in Digital Finance9 lectures

MainEmerging Topics in Digital Finance
25 slides
  • Foundations for Emerging Topics
  • What Makes Something ``Money'' -- and Is Bitcoin Money?
  • Is FinTech Creating Value or Just Redistributing It?
  • Why Do Platform Markets Produce Winner-Take-Most Outcomes?
  • Learning Objectives
  • Decentralized Finance (DeFi)
  • Can Smart Contracts Replace Banks Entirely?
  • How Does DeFi Solve the Same Problems Differently?
  • What Does a TVL Crash from \$180B to \$40B Reveal About Algorithmic Trust?
  • What Happens When There's No Customer Support?
  • Central Bank Digital Currencies
  • If Cash Went Digital, What Would Change?
  • Why Is There No Single Optimal CBDC Design?
  • Why Did Small Countries Launch CBDCs First?
  • Why Is Switzerland Leading Wholesale CBDC Innovation?
  • AI in Financial Services
  • Is AI One Thing in Finance -- or Many?
  • Can Machines Find Signal in Financial Noise?
  • What Happens When an Algorithm Denies Your Loan?
  • How Is Generative AI Different from Traditional ML in Finance?
  • Sustainable Finance and ESG
  • Why Do Different Raters Give the Same Company Different ESG Scores?
  • Is Climate Change the Ultimate Unpriced Externality?
  • Embedded Finance and Platform Models
  • What Happens When Financial Services Become Invisible?
  • Will Tech Platforms Dominate Finance -- or Will Banks Build Super-Apps?
  • Why Is Insurance Especially Ripe for Disruption?
  • How Did the Minimum Investment Fall from \$100,000 to \$1?
  • Frontier Technologies
  • When Will Quantum Computers Break Financial Encryption?
  • Can You Verify Your Identity Once and Use It Everywhere?
  • Summary and Course Wrap-Up
  • Course Summary: Digital Finance in Perspective
Foundations for Emerging TopicsDecentralized Finance (DeFi)Central Bank Digital CurrenciesAI in Financial ServicesSustainable Finance and ESGEmbedded Finance and Platform ModelsFrontier TechnologiesSummary and Course Wrap-Up
ExtendedCbdc
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Monetary Policy Transmission \& Seigniorage
  • How Does a CBDC Destroy the Most Profitable Product in Central Banking?
  • How Sensitive Is Seigniorage to CBDC Remuneration and Substitution?
  • How Much Will Depositors Flee Banks for CBDC Safety?
  • At What CBDC Rate Do Bank Deposits Collapse?
  • Can You Find the CBDC Rate That Maximizes Welfare Without Killing Banks?
  • Where Is the Sweet Spot Between Inclusion and Stability?
  • Privacy Engineering \& Cryptographic Design
  • How Can You Prove a Transaction Is Valid Without Revealing Its Details?
  • What Is the Computational Price of Privacy in CBDC Transactions?
  • Can You Measure How Much Privacy Leaks from Aggregate CBDC Statistics?
  • How Do Anonymity Vouchers Create Cash-Like Privacy with Digital Audit Trails?
  • How Do Different Voucher Designs Distribute Privacy Across the Population?
  • Cross-Border mCBDC \& Currency Substitution
  • How Does Atomic PvP Settlement Eliminate Herstatt Risk in mCBDC?
  • How Much Does Each Extra Intermediary Cost in Cross-Border Payments?
  • Can You Simulate a Multi-Currency Atomic Swap on mBridge?
  • When Does a Foreign CBDC Replace Your Domestic Currency?
  • Which Countries Face the Highest Risk of Digital Dollarization?
  • How Fast Is mBridge Compared to SWIFT and Correspondent Banking?
  • Technology Architecture \& Offline Payments
  • Why Can't a Blockchain Process Visa-Level Transaction Volume?
  • How Do Real CBDC Platforms Compare on Throughput, Latency, and Finality?
  • How Do Hardware Wallets Prevent Double-Spending Without Connectivity?
  • How Long Can a Wallet Stay Offline Before Double-Spend Risk Becomes Unacceptable?
  • What Can -- and Should -- Programmable CBDC Money Actually Do?
  • Bank Disintermediation \& Financial Stability
  • How Fast Can a Digital Bank Run Drain the Banking System?
  • How Does a CBDC Bank Run Compare to SVB, Northern Rock, and Classical Panics?
  • Can You Model How Tiered Rates Discourage Excessive CBDC Holdings?
  • What Holding Limit Maximizes Inclusion While Containing Systemic Risk?
  • What Happens to the Central Bank Balance Sheet When Everyone Holds CBDC?
  • Can You Stress-Test a Bank's Balance Sheet Under CBDC Deposit Migration?
(Introduction)Monetary Policy Transmission \& SeignioragePrivacy Engineering \& Cryptographic DesignCross-Border mCBDC \& Currency SubstitutionTechnology Architecture \& Offline PaymentsBank Disintermediation \& Financial Stability
MiniCbdc
10 slides
  • (Slides)
  • What If the Government Could See Every Coffee You Buy?
  • How Would You Feel If Your Money Had an Expiration Date?
  • What Makes a CBDC Different from Everything Else?
  • How Does a Digital Euro Transaction Actually Work?
  • Why Does Every CBDC Design Sacrifice Something?
  • What Goes Wrong When Central Banks Become Retail Bankers?
  • Which Countries Are Closest to a Digital Currency -- and Why?
  • Who Gains Power and Who Loses It in a CBDC World?
  • The Privacy-Control Spectrum -- Where Should Your Country Land?
  • Your Challenge -- Design a CBDC for Switzerland
(Slides)
ExtendedClimate Risk
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • Climate Risk Taxonomy
  • How Do You Compute the Carbon Value-at-Risk of a Portfolio?
  • What Does the Carbon Price Look Like Under NGFS Scenarios?
  • Can You Compute the Carbon VaR of a Four-Asset Portfolio?
  • Which Sectors Face the Largest Stranded Asset Write-Downs?
  • How Do You Value an Asset When Its Cash Flows Depend on Carbon Policy?
  • How Do Physical, Transition, and Liability Risk Interact in a Climate Stress Test?
  • Carbon Pricing \& Stranded Assets
  • Where Is the Gap Between What Markets See and What Climate Delivers?
  • Can You Compute When a Fossil Asset Becomes Stranded?
  • How Sensitive Is Each Asset to the Climate Factor?
  • Which Assumptions Drive the Largest Swings in Transition Risk Estimates?
  • What Does the Climate Loss Distribution Look Like Under Each Scenario?
  • How Do Different Carbon Pricing Mechanisms Create Different Stranding Patterns?
  • Green Bond Verification \& Greenwashing
  • How Has the Green Bond Market Grown -- and Where Is the Money Going?
  • Do Green Bonds Really Trade at a Premium -- and Can You Measure It?
  • Can You Build an Automated Green Bond Verification Score?
  • How Wide Is the Greenium -- and Does It Vary by Sector and Rating?
  • Can You Teach a Machine to Detect Greenwashing?
  • Climate Stress Testing
  • How Do You Combine Six Disagreeing ESG Ratings into One Usable Score?
  • How Do ESG Raters Disagree Across Environmental, Social, and Governance Pillars?
  • Can You Build a Bayesian ESG Aggregator That Flags High-Divergence Companies?
  • How Does Physical Climate Risk Vary Across Asset Classes and Regions?
  • Why Are Compound Climate Events More Likely Than Models Predict?
  • Which NGFS Scenario Should You Use -- and Why Does It Matter?
  • ESG Integration \& Portfolio Construction
  • What Does It Cost to Decarbonize a Portfolio -- Exactly?
  • Can You Interpolate Between NGFS Scenarios for Custom Stress Tests?
  • Where Do Scope 1, 2, and 3 Emissions Hide in a Diversified Portfolio?
  • What Does a Credible Portfolio Decarbonization Glide Path Look Like?
  • Which ESG Integration Approach Actually Reduces Climate Risk?
(Introduction)Climate Risk TaxonomyCarbon Pricing \& Stranded AssetsGreen Bond Verification \& GreenwashingClimate Stress TestingESG Integration \& Portfolio Construction
MiniClimate Risk
10 slides
  • (Slides)
  • Why Are Banks Still Financing Coal Plants That Will Be Worthless in 15 Years?
  • What If Your Pension Fund Held Assets That Climate Change Will Make Uninsurable?
  • What Is the Difference Between Physical Risk, Transition Risk, and Liability Risk?
  • Follow One Green Bond from Issuance to Impact Report -- and Spot the Greenwashing
  • How Do You Put a Price on a Risk That Materializes After the CEO Retires?
  • What Happens When Stranded Assets Hit Bank Balance Sheets All at Once?
  • Where Does the Horizon Gap Between Financial Planning and Climate Risk Hit Hardest?
  • Who Bears the Cost of the Climate Transition -- Investors, Consumers, or Governments?
  • The Climate Risk Assessment Checklist: Physical, Transition, and Liability
  • Your Challenge: Compute the Carbon VaR of a Hypothetical Portfolio
(Slides)
ExtendedDefi
29 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • AMM Mathematics \& Market Microstructure
  • How Does a Constant Product Market Maker Set Prices Without an Order Book?
  • How Does Price Impact Scale with Trade Size and Pool Depth?
  • How Does Concentrated Liquidity Multiply Capital Efficiency by 10x -- or 4000x?
  • Can You Simulate an AMM Swap and Measure the Slippage?
  • How Does Concentrated Liquidity Reshape the Capital Efficiency Frontier?
  • What Makes StableSwap Different from Constant Product -- and When Does Each Break?
  • Lending Protocol Mechanics \& Interest Rate Models
  • How Do Lending Protocols Set Interest Rates Without a Committee?
  • What Does the Interest Rate Kink Look Like -- and Why Does It Exist?
  • Can You Model a Liquidation Cascade in Five Lines of Logic?
  • How Do Liquidation Cascades Amplify a 10\% Price Drop into a 40\% Loss?
  • How Does the Health Factor Determine Whether You Get Liquidated?
  • How Does Flash Loan Volume Reveal the Hidden Economy of Atomic Arbitrage?
  • Yield Farming \& Tokenomics
  • Where Does DeFi Yield Actually Come From -- and When Is It Real?
  • How Do Token Emission Schedules Predict the Yield Collapse?
  • Can You Detect a Ponzi-like Protocol from Its On-Chain Cash Flows?
  • How Does Recursive Leverage Amplify Yield -- and Risk -- Simultaneously?
  • Which Yield Sources Survived the 2022 Crash -- and Which Evaporated?
  • Risk Quantification \& Smart Contract Security
  • Why Does Impermanent Loss Follow a Square Root Law?
  • How Does Impermanent Loss Compare to Fee Income Across Price Scenarios?
  • Can You Build a Monte Carlo Simulator for LP Profitability?
  • How Much Value Have Smart Contract Exploits Destroyed -- and What Are the Patterns?
  • How Do You Model Smart Contract Risk as a Jump Process?
  • How Does Protocol Composability Create Hidden Contagion Pathways?
  • Governance \& Regulatory Frameworks
  • How Concentrated Is Voting Power in Decentralized Governance?
  • How Does Voting Power Distribution Compare Across Major DAOs?
  • Can You Compute the Cost of a Flash Loan Governance Attack?
  • What Does MiCA Actually Regulate -- and What Escapes Through the Cracks?
  • Can You Score How Decentralized a Protocol Actually Is?
(Introduction)AMM Mathematics \& Market MicrostructureLending Protocol Mechanics \& Interest Rate ModelsYield Farming \& TokenomicsRisk Quantification \& Smart Contract SecurityGovernance \& Regulatory Frameworks
MiniDefi
10 slides
  • (Slides)
  • What If You Could Be Your Own Bank -- but Nobody Would Help If You Got Robbed?
  • How Many Safety Nets Did You Use Today Without Knowing It?
  • What Does DeFi Replace -- and What Does It Remove?
  • How Does a DeFi Loan Work When There Is No Loan Officer?
  • How Do Three DeFi Primitives Solve the Same Problems Differently?
  • What Happens When Your Stable Coin Is Not Stable?
  • Where Did All the Money Go -- and Where Is It Coming Back?
  • Who Benefits and Who Bears the Risk in a World Without Banks?
  • The Freedom-Safety Balance: Three Questions Before You Deposit
  • Your Challenge: Evaluate a DeFi Protocol
(Slides)
ExtendedEmerging Topics
30 slides
  • (Introduction)
  • What Will You Be Able to Do After This Lecture?
  • DeFi Mechanisms \& Economics
  • Why Does $x \times y = k$ Make Automated Market Making Possible?
  • Can You Simulate an AMM Pool and Watch Slippage in Action?
  • How Does Pool Depth Protect You from Slippage?
  • How Much Do Liquidity Providers Actually Lose to Impermanent Loss?
  • Where Does DeFi Yield Actually Come From -- and How Much Is Real?
  • When Does Yield Farming Beat Simply Holding?
  • CBDC Architecture \& Monetary Policy
  • How Does a CBDC Change the Way Monetary Policy Reaches You?
  • Can You Simulate Bank Disintermediation from a CBDC Launch?
  • Where Does Money Flow in a Two-Tier CBDC System?
  • How Private Is Your CBDC -- and How Private Should It Be?
  • Can CBDCs Replace SWIFT -- and What Would That Mean for Dollar Hegemony?
  • AI/ML in Financial Services
  • How Do You Turn Text into a Trading Signal?
  • Can You Build a Financial Sentiment Classifier in 20 Lines?
  • How Confident Should You Be in an AI Credit Score?
  • Does Market Sentiment Actually Predict Returns?
  • Why Do the Most Accurate Models Resist Explanation?
  • Sustainable Finance Quantification
  • Why Do Six Raters Give the Same Company Six Different ESG Scores?
  • Can You Build an ESG-Constrained Portfolio Optimizer?
  • How Much Do ESG Raters Disagree -- Company by Company?
  • What Does Climate Risk Look Like in a Portfolio's Loss Distribution?
  • Do Green Bonds Really Cost Less to Issue -- and Can You Prove It?
  • Platform Economics \& Frontier Tech
  • Why Does a Platform with 10x Users Have 100x Value?
  • Can You Predict When a FinTech Platform Reaches Critical Mass?
  • How Do FinTech Platform Ecosystems Overlap?
  • When Exactly Will Quantum Computers Break Financial Encryption?
  • What Is the Quantum Migration Roadmap for Financial Institutions?
  • Can You Demonstrate Why Lattice-Based Cryptography Resists Quantum Attack?
  • What Have We Learned -- and What Remains Unsolved?
  • Key Takeaways
(Introduction)DeFi Mechanisms \& EconomicsCBDC Architecture \& Monetary PolicyAI/ML in Financial ServicesSustainable Finance QuantificationPlatform Economics \& Frontier Tech
MiniEmerging Topics
10 slides
  • (Slides)
  • Why Would a Bank Trust a Machine That Makes Things Up?
  • Have You Already Used AI for a Financial Decision Without Realizing It?
  • What Can Generative AI Actually Do in Finance?
  • Follow a Prompt from Input to Investment Recommendation
  • Human-in-the-Loop or Human-out-of-the-Loop -- Who Decides?
  • What Happens When AI Hallucinates a Financial Fact?
  • How Fast Is the Financial Industry Adopting Generative AI?
  • Who Wins and Who Loses When AI Writes the Analyst Report?
  • The Trust Spectrum: When Should You Rely on AI-Generated Financial Advice?
  • Your Challenge: Evaluate an AI-Generated Financial Analysis
(Slides)
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