Catalog
Your path from zero finance knowledge to complete expert — every course, in order.
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- 🏛️Beginner
A History of Money
BeginnerHow money went from cattle and gold coins to pure code — the 20th-century journey through the gold standard, Weimar hyperinflation, Bretton Woods, the 1971 Nixon shock, electronic money, and the 2008 crisis that birthed Bitcoin.
0/6 lessons
- 🏦Beginner
Economics for Finance
BeginnerThe economics a finance learner actually needs — scarcity and trade-offs, how supply and demand set prices, what inflation really is, GDP and the boom-and-bust business cycle, how central banks move interest rates, and what governments do with taxes, spending and trade. Plain English, worked numbers, interactive charts.
0/7 lessons
- ⏳Beginner
The Time Value of Money
BeginnerWhy a dollar today beats a dollar tomorrow — present value, future value, compounding and discounting explained with analogies, worked numbers and interactive charts.
0/1 lessons
- 🌱Beginner
Investing Basics
BeginnerThe bridge from saving to investing — what an asset really is, why investing differs from stashing cash, the risk-and-return trade-off, what stocks, bonds and funds are, and what "a return" actually means. Zero jargon assumed, worked numbers and interactive charts throughout.
0/6 lessons
- 🔗Beginner
Crypto, From Scratch
BeginnerWhat a blockchain actually is — blocks, hashes and chains; keys, wallets and signatures; how transactions and fees work; and why Bitcoin and Ethereum track your money in two completely different ways.
0/5 lessons
- 🧠Beginner
Investment Psychology
BeginnerThe behavioural finance a real investor needs — Kahneman and Tversky's two-system mind, prospect theory, loss aversion, the disposition effect, overconfidence and overtrading, anchoring, framing, base-rate neglect, herding and bubbles, survivorship bias, and a practical toolkit to debias your own decisions. Zero psychology assumed, with mechanisms, evidence, honest caveats, worked numbers and interactive visuals.
0/11 lessons
- 🏛️Intermediate
Stock Markets & Funds
IntermediateHow the stock market actually works — exchanges and brokers, what happens when you place an order, market vs limit vs stop orders, the bid–ask spread, indices like the S&P 500, ETFs vs mutual funds vs index funds, fees and expense ratios, dividends, buybacks, splits, and IPOs. Worked numbers and interactive order books throughout.
0/8 lessons
- 🧩Beginner
Mental Models for Finance
BeginnerThe thinking toolkit before the math — the core economics, risk, and behavioural mental models that turn money decisions from guesswork into reasoning. Zero finance background assumed; every term defined on first use, with worked everyday examples and interactive visuals.
0/6 lessons
- 📈Beginner
Interest & Yield
BeginnerWhat your money actually earns — simple vs compound interest, APR vs APY, and nominal vs real returns. The difference between the rate on the label and the rate in your pocket, with worked numbers and interactive charts.
0/4 lessons
- ΞIntermediate
Ethereum
IntermediateHow Ethereum actually works — the world computer and the EVM, accounts vs Bitcoin's UTXO, gas and fees under EIP-1559, smart contracts and tokens (ERC-20 and ERC-721), proof-of-stake and staking, and Layer-2 rollups — all from zero.
0/8 lessons
- 🪙Intermediate
Stablecoins
IntermediateHow crypto holds the value of a dollar. Pegs and the arbitrage that defends them; fiat-backed coins (USDT, USDC) and the reserves behind them; crypto-backed, over-collateralized dollars (DAI); the algorithmic death spiral that killed Terra's UST; and how stablecoins depeg, break and get regulated.
0/6 lessons
- ₿Intermediate
Bitcoin
IntermediateHow Bitcoin actually works — the public ledger and mining, proof-of-work, the 21-million cap and halvings, keys and wallets, sending a transaction and its fee, full nodes, and the Lightning Network — all from zero.
0/9 lessons
- 🏠Intermediate
Loans & Mortgages
IntermediateHow borrowing actually works from the customer's side — principal and interest, amortization schedules, fixed vs variable rates, APR vs APY, term trade-offs, the total cost of credit, down payment and loan-to-value, fees and closing costs, early repayment, refinancing, and what happens in default and foreclosure.
0/6 lessons
- 📉Intermediate
Bonds & Rates
IntermediateBonds demystified from the ground up — what a bond really is (a loan you can sell), how its price and yield trade on a see-saw, what the yield curve says about the future, and how duration and convexity measure interest-rate risk. Worked numbers, the bond-price see-saw, and interactive charts throughout.
0/6 lessons
- 📜Intermediate
History of Finance
IntermediateWhere financial products actually came from — ancient interest and the Code of Hammurabi, double-entry bookkeeping, the first government bonds, the Amsterdam joint-stock company, tulip mania, Dojima rice futures, insurance, central banks, and the road to index funds and ETFs.
0/6 lessons
- 🤝Intermediate
Futures & Forwards
IntermediateThe first derivatives, demystified — what a forward contract is, why its payoff is a straight, symmetric line, how exchange-traded futures differ from private forwards, margin and daily mark-to-market, basis, contango and backwardation, hedgers versus speculators, cost-of-carry pricing, and how to roll contracts forward. Worked numbers, payoff diagrams, and a margin-call simulator throughout.
0/7 lessons
- ⚖️Intermediate
Automated Market Makers (AMMs)
IntermediateHow decentralized exchanges price a trade with no order book and no counterparty — just a pool and a formula. The constant-product invariant x·y=k, liquidity pools and LP tokens, slippage and price impact, and the impermanent loss that decides whether providing liquidity actually pays.
0/6 lessons
- 🏦Advanced
Company Financials and Valuation
AdvancedHow to read a business and price it. The three financial statements (balance sheet, income statement, cash-flow statement) and how they lock together, margins and ratios (ROE, debt/equity, ROIC), earnings and EPS, valuation multiples (P/E, EV/EBITDA, P/B), discounted cash flow step by step, growth versus value, and the accounting red flags that separate real earnings from cosmetics.
0/9 lessons
- ⚖️Advanced
DeFi Lending & Borrowing
AdvancedHow decentralized lending really works — money markets run by smart contracts. Suppliers, borrowers and pooled liquidity; interest-bearing receipt tokens (aTokens/cTokens); over-collateralization, loan-to-value, the health factor and liquidation — the machinery under Aave, Compound and MakerDAO/Sky.
0/6 lessons
- 📈Advanced
Investment Metrics
AdvancedThe numbers investors actually live by — ROI, CAGR, volatility, drawdown, Sharpe, Sortino, alpha, and beta — explained in plain language with worked examples.
0/6 lessons
- 📖Advanced
Market Microstructure
AdvancedHow prices actually form, one order at a time. The limit order book, the bid–ask spread and why it exists, makers versus takers, liquidity and depth, slippage and price impact, tick sizes, market makers and inventory risk, adverse selection, and a tour of fragmentation and dark pools. Live order books, walk-the-book simulators, and worked numbers throughout.
0/8 lessons
- 🛡️Intermediate
Zcash
IntermediateFrom a public Bitcoin ledger to fully private payments — learn how Zcash hides sender, receiver, and amount using zero-knowledge proofs.
0/8 lessons
- 🎟️Advanced
Options Basics
AdvancedThe grammar of options — calls and puts as the right, not the obligation, to trade at a fixed price. Payoff and profit diagrams, breakeven, intrinsic vs time value and moneyness, theta decay, the six inputs that drive a premium, and the first real strategies (covered call, protective put, spreads, straddles).
0/6 lessons
- 📊Advanced
Statistics for Finance
AdvancedThe statistics that underpins quantitative finance — probability and random variables, the distributions returns actually follow (normal, lognormal, fat-tailed), expectation, variance and higher moments, covariance, correlation and regression, the Central Limit Theorem and estimation, and hypothesis testing with its finance-specific traps. Worked numbers and interactive charts throughout.
0/7 lessons
- 💱Advanced
FX & Currency Markets
AdvancedThe biggest market on Earth, from scratch — how currency pairs are quoted (base/quote, pips, bid/ask, cross rates), spot settlement versus forward FX and FX swaps, covered and uncovered interest parity, the carry trade and why it blows up, central banks and intervention, fixed pegs and the impossible trinity, currency crises, and how currency risk shows up in a global portfolio (hedged versus unhedged). Worked numbers, parity diagrams, and a carry-unwind simulator throughout.
0/7 lessons
- 🛢️Advanced
Commodities & Real Assets
AdvancedThe markets where you can take delivery of a physical thing — barrels, bushels, and bars. How commodity futures actually work, the cost-of-carry that prices them (storage plus financing minus convenience yield), why curves sit in contango or backwardation, the roll yield that makes or breaks a passive long, seasonality, commodity indices, gold as a monetary asset, the structure of the oil market, and why real assets are the classic inflation hedge. Worked numbers, curve diagrams, a roll-yield ladder, a seasonality sweep, and an inflation-shock chart throughout.
0/7 lessons
- 🎯Advanced
Portfolio Theory
AdvancedWhy a basket of risky assets can be safer than any one of them — the mathematics of diversification. Correlation and covariance, how combining assets bends the risk–return curve, the efficient frontier and the minimum-variance portfolio, the Capital Market Line, and CAPM's beta and Security Market Line.
0/7 lessons
- 🥪Expert
MEV & Transaction Ordering
ExpertWhy the order of transactions inside a block is worth money — and who fights to control it. Maximal Extractable Value (MEV) from the mempool up: how ordering is auctioned, front-running and back-running, sandwich attacks on AMMs, arbitrage and liquidation MEV, and how Proposer-Builder Separation (PBS), MEV-Boost and private orderflow try to tame it.
0/7 lessons
- 🌀Expert
Stochastic Processes
ExpertThe math of how prices wander through time — random walks, martingales, Markov chains, Brownian motion, Itô's lemma intuition, geometric Brownian motion, mean reversion (Ornstein–Uhlenbeck), and jump-diffusion — and what a stochastic differential equation actually says.
0/7 lessons
- 📉Expert
Value at Risk
ExpertHow banks and funds turn a whole portfolio's risk into a single number — Value at Risk (VaR) and its sharper cousin Expected Shortfall (CVaR). The three ways to compute them (historical, parametric, Monte Carlo), how to scale across time, how to backtest them, and exactly where they lie to you.
0/7 lessons
- 🧮Expert
Options Pricing
ExpertHow an option's fair premium is actually computed — from no-arbitrage and replication, through the risk-neutral binomial tree, to the Black–Scholes formula, the Greeks (delta, gamma, theta, vega, rho), and implied volatility with its smile and skew.
0/6 lessons
- 🎲Expert
Kelly & Geometric Growth
ExpertThe mathematics of bet sizing and long-run compounding — why the geometric mean, not the average return, is what actually grows your money. Arithmetic vs geometric mean, volatility drag and the variance penalty, the Kelly criterion (f* = edge/odds), full vs fractional Kelly, continuous Kelly (f* = μ/σ²), the drawdown-vs-growth trade-off, multi-asset Kelly, and the ruin that waits past twice Kelly.
0/6 lessons
- 🔬Expert
Bayesian Finance
ExpertProbability as degree of belief, and the machinery for updating it with evidence — prior, likelihood and posterior; Bayes' rule and the base-rate fallacy; conjugate priors and sequential updating; precision-weighted return and volatility estimates; shrinkage and the Black–Litterman model; credible intervals versus confidence intervals; and MCMC for posteriors no formula can express.
0/7 lessons
- 📈Expert
Time-Series Finance
ExpertHow to model returns as they unfold through time — stationarity and unit roots, autocorrelation and the ACF/PACF, AR/MA/ARIMA models for the mean, volatility clustering and ARCH/GARCH for the variance, EWMA and RiskMetrics, and the backtesting pitfalls (look-ahead bias, overfitting, data-snooping) that make a strategy lie.
0/7 lessons
- 🧬Expert
Factor Models
ExpertFrom CAPM's single market factor to the modern multi-factor zoo — size, value, momentum, profitability and investment. How factor-mimicking portfolios are built, how to estimate loadings and premia by regression, why most "alpha" is really hidden factor beta, and how published factors decay once everyone trades them.
0/7 lessons
- 📐Expert
Fixed-Income Analytics
ExpertBonds at practitioner depth — price a bond from its cash flows, measure its rate sensitivity with duration (Macaulay, modified, DV01) and convexity, bootstrap the yield curve into spot and forward rates, glimpse the term-structure models (Vasicek, CIR) that drive rates, decompose credit spreads into expected loss and risk premium, and immunize and hedge a whole rate book.
0/8 lessons
- 🎢Expert
DeFi Derivatives & Perpetuals
ExpertHow derivatives moved on-chain and why perpetual futures came to dominate crypto trading. The funding-rate mechanism that anchors a never-expiring contract to spot, leverage and the liquidation engines that enforce it, insurance funds and auto-deleveraging, the three perp-DEX architectures (order book, vAMM, oracle/pool), on-chain options and power perps, and the cash-and-carry basis trade that turns the funding premium into market-neutral yield.
0/8 lessons
- 🎲Expert
Monte Carlo in Finance
ExpertHow quants replace impossible math with brute-force randomness — Monte Carlo simulation. The law of large numbers, sampling from return distributions, geometric Brownian motion price paths, simulating retirement and portfolio outcomes, pricing path-dependent options, convergence and standard error, and the variance-reduction tricks that buy accuracy without melting your laptop.
0/7 lessons
- 🎯Expert
Portfolio Optimization
ExpertFrom theory to weights — the mechanics of mean-variance optimization, the covariance matrix and its conditioning, why optimizers are "error maximizers", weight instability out of sample, shrinkage estimators (Ledoit–Wolf), the minimum-variance and maximum-Sharpe (tangency) portfolios, risk parity, and real constraints with transaction costs.
0/7 lessons
- 🎛️Expert
Greeks & Hedging
ExpertManaging a live options book — delta, gamma, theta, vega and rho in depth, delta-neutral hedging, the discrete-rebalancing tradeoff, gamma scalping, the volatility surface, vega risk, and daily P&L attribution.
0/6 lessons
- 🎲Expert
Polymarket & Prediction Markets
ExpertTrading real-world outcomes on-chain — what a prediction market is and why its price IS a probability, how Polymarket works end-to-end (USDC on Polygon, $1 YES/NO share pairs, the CLOB order book, minting and merging), how markets resolve through UMA's optimistic oracle, calibration and the favorite–longshot bias, binary arbitrage, Kelly-sized bets on a binary, and the real risks.
0/6 lessons
- 🤖Expert
Algorithmic Trading & Execution
ExpertHow large orders actually get worked — the hidden cost of trading, implementation shortfall, the square-root law of market impact, the TWAP/VWAP/POV/IS execution algos, optimal execution and the Almgren–Chriss frontier, transaction-cost analysis, and the execution-aware backtesting traps (and HFT) that decide whether an edge survives contact with the market.
0/8 lessons
- 🔁Expert
Swaps & Rate Derivatives
ExpertThe biggest derivatives market on earth, taught from first principles to desk-grade practice. Build an interest-rate swap out of a fixed leg and a floating leg, see why only the net changes hands, decompose a swap into a strip of FRAs and value it as one bond minus another, derive the par swap rate, build the swap curve and discount on OIS, live through the death of LIBOR and the rise of SOFR, read swap spreads (even negative ones) and asset swaps, glance at caps, floors and swaptions, and hedge a whole rate book to a near-zero DV01. Worked numbers, cash-flow diagrams, a swap curve with implied forwards, a two-bond valuation bridge, and a swap-spread chart throughout.
0/9 lessons
- 💀Expert
Risk of Ruin
ExpertThe math of survival — risk of ruin, expectancy and the per-trade edge, R-multiples, the classic risk-of-ruin formula, drawdown depth and duration distributions, sequence-of-returns risk, Monte Carlo ruin curves, and stop-loss position sizing — so a positive-expectancy system survives long enough to pay off.
0/7 lessons
- 🌋Expert
Extreme Value & Tails
ExpertModeling the part of the distribution that actually bankrupts people — fat tails versus the Gaussian, power laws and the tail index, Extreme Value Theory (block maxima/GEV and peaks-over-threshold/GPD), expected shortfall beyond VaR, copulas and tail dependence, and stress testing.
0/7 lessons
- 🎢Expert
Volatility Trading
ExpertTreat volatility itself as the asset and learn to trade it like a desk. Separate realized from implied vol and price the gap, build variance and vol swaps and see why long variance is long convexity, read the VIX and its term structure (and why long-vol products bleed in contango), harvest the volatility risk premium without getting steam-rollered, put on straddles and strangles as direction-agnostic bets on movement, run a dispersion trade that sells index vol against single names to short correlation, and engineer a convex tail hedge that floors a crash. Worked numbers, payoff diagrams, a VIX term-structure curve, an implied-vs-realized premium chart, a variance-convexity plot, dispersion bars and a tail-hedge convexity curve throughout.
0/8 lessons
- 🧨Expert
Credit Derivatives & Securitization
ExpertTrade default risk and manufacture bonds out of pools of loans, taught from first principles to desk-grade practice. Build a single-name CDS from its premium and protection legs, price it with hazard rates and the credit triangle, read CDX and iTraxx and the index basis, pool loans into an SPV and slice them into tranches with a cash-flow waterfall, see how subordination turns BBB collateral into AAA bonds — and how default correlation and the Gaussian copula turned "safe" senior tranches into the wreckage of 2008. Finish on the modern CLO and the OC/IC coverage tests that make it the structure that survived. Worked numbers, a CDS cash-flow diagram, a survival-curve credit triangle, an index-basis chart, a securitization pipeline, a loss waterfall, a correlation-vs-tranche-loss model, and a CLO coverage-test gauge throughout.
0/8 lessons
- ⚛️Expert
Quantum Computing for Finance
ExpertThe frontier-hardware bet: where quantum algorithms might actually help finance, and where it is pure hype. Amplitude estimation for a quadratic Monte-Carlo speedup in option pricing and risk, QAOA and quantum annealing for portfolio optimization, quantum-inspired methods you can run on classical hardware today — and a clear-eyed audit of the noise, qubit-count, and data-loading walls between the promise and a real edge.
0/7 lessons
- 🔗Expert
Systematic & Statistical Arbitrage
ExpertMining relative value at scale — pairs trading and cointegration, the z-score spread trade, mean-reversion versus momentum signals, building a market- and factor-neutral book, combining alphas and fighting signal decay, the capacity and crowding ceiling, and the cautionary tale of the August 2007 quant quake.
0/7 lessons
- ⚡Expert
High-Frequency Market Making
ExpertQuoting both sides of the book for a living. The market-making P&L (spread capture minus adverse selection minus inventory risk), the Avellaneda–Stoikov optimal-quoting model, the reservation price and inventory skew, the Glosten–Milgrom view of adverse selection, queue position and fill probability, the latency arms race, and maker-taker rebate economics. Live quoting simulators and worked numbers throughout.
0/8 lessons
- 🎰Expert
Exotic Options & Structured Products
ExpertGo beyond vanilla calls and puts into the engineered payoffs that banks actually sell. Price digital (binary) options and replicate them with a tight call spread, meet barrier options (knock-in/knock-out) and the discontinuous-delta hedging nightmare they create, average the path with Asians and lock in the extreme with lookbacks, decode autocallables and cliquets observation by observation, then take a structured note apart to reveal it is just a zero-coupon bond plus an option strip — and learn to count the hidden costs, the issuer credit risk, and the sold put you didn't know you owned. Worked numbers, payoff and path diagrams, an interactive barrier explorer and an autocall ladder throughout.
0/7 lessons
- 🦢Expert
Taleb & Uncertainty
ExpertActing under fat-tailed uncertainty the way Nassim Taleb's Incerto teaches it — being fooled by randomness, black swans and Extremistan, fragility and antifragility, convexity and the barbell, skin in the game, ergodicity, and the Lindy effect.
0/8 lessons
- 🧠Expert
Machine Learning for Alpha
ExpertML done right in markets — financial features and labeling, the leakage trap and why ordinary k-fold fails on time series, purged and embargoed cross-validation, the multiple-testing backtest-overfitting problem and the deflated Sharpe ratio, tree ensembles versus linear models, MDI/MDA feature importance, and folding ML signals into the stat-arb pipeline. Overfitting is the enemy throughout.
0/7 lessons
- 🌀Expert
DeFi Options & On-chain Volatility
ExpertVolatility goes on-chain — how options moved onto the blockchain, the DeFi option vaults that sell covered calls and cash-secured puts for yield and the structural short-vol risk baked into them, how implied volatility is quoted and oracle-fed on-chain, reading perp funding and basis as a live volatility and skew signal, and the settlement, gas, and liquidity frictions that separate an on-chain options market from a TradFi desk. Worked payoffs, a vault P&L diagram, a stale-oracle vol chart, funding-rate signals, and a graded final exam.
0/7 lessons
- 🤝Expert
Counterparty Risk & XVA
ExpertThe cost of who you trade with, taught from first principles to desk-grade practice. See why a derivative is a two-way credit relationship that loans never are, measure counterparty exposure through time with current exposure, expected exposure (EE/EPE) and potential future exposure (PFE), and read the hump-shaped profile of a swap against the rising profile of an FX forward. Then crush that exposure with close-out netting and a CSA — variation margin, initial margin, thresholds, minimum transfer amounts and haircuts — and learn to price what is left: CVA (the charge for their default), DVA (the benefit of your own), and the whole post-2008 XVA family (FVA funding, MVA margin, KVA capital, ColVA). Finish with wrong-way risk, and the great migration from bilateral trading to central clearing, default waterfalls and SA-CCR. Worked numbers, exposure-profile and XVA-waterfall islands, and a graded final exam throughout.
0/7 lessons
- 🔀Expert
On-chain Arbitrage & Cross-DEX MEV
ExpertStatistical arbitrage meets the blockchain: cross-DEX and triangular arb, atomic bundles, the cost stack, and the searcher–builder economics that bid most of the profit away. The relative-value mindset, ported to a venue with no shorting and atomic settlement.
0/7 lessons
- 🤖Expert
Reinforcement Learning for Trading
ExpertMarkets as a sequential decision problem — framing trading as a Markov decision process, why supervised ML is the wrong frame for execution and sizing, reward design and its pitfalls, value-based (Q-learning/DQN) versus policy-gradient (PPO/actor-critic) methods, optimal execution and market-making as RL, and the brutal sim-to-real gap that makes RL backtests even easier to overfit than supervised ones.
0/7 lessons
- 📡Expert
Order-Flow Auctions & MEV Redistribution
ExpertThe frontier of taming MEV: instead of letting searchers and builders keep the value your transaction creates, route it back to you. Order-flow auctions and backrun refunds, intent-based trading with competing solvers (UniswapX, CoW Protocol), MEV-Share's programmable privacy, the SUAVE decentralized-sequencing vision, and the mechanism design that decides whether 'give it back to the user' is real or marketing.
0/7 lessons
- 🔮Expert
Deep Learning for Market Data
ExpertSequence models on the hardest data there is — why plain MLPs over- and under-fit low-signal returns, recurrent models (RNN/LSTM/GRU) and the vanishing-gradient story, temporal convolutional networks, attention and transformers for returns and the limit-order book, embeddings for categorical and alternative data, and the tiny-effective-sample-size problem with aggressive regularization, purged/embargoed evaluation, and a deflated Sharpe — plus a sober answer to "when does deep learning actually beat gradient boosting in finance?"
0/7 lessons
- 🌉Expert
Cross-Chain Arbitrage & Bridge MEV
ExpertArbitrage after atomicity dies: bridging assets across chains, the inventory and finality risk it reintroduces, bridge-hack tail risk, shared sequencers, and where MEV reappears in a multi-chain world. The on-chain arb playbook, ported to a venue where settlement is no longer all-or-nothing.
0/7 lessons
- 🤖Expert
Deep RL for Execution & Market Making
ExpertWhere deep learning meets reinforcement learning on the order book — deep value and policy networks pointed at the two canonical control problems, optimal execution and market making. DQN and its instability on financial state, policy gradients and actor–critic for continuous quoting, reward shaping that silently rewrites the policy, the sim-to-real gap, and the honest evaluation that compares a learned agent against Almgren–Chriss and Avellaneda–Stoikov instead of against doing nothing.
0/7 lessons
- 🕸️Expert
Graph Neural Networks for Financial Networks & Systemic Risk
ExpertMarkets are not a table of returns — they are a graph: banks lending to banks, firms wired into supply chains, assets co-moving, wallets transacting on-chain. Learn graph neural networks — message passing, node/edge/graph tasks — and aim them at the problems a flat table cannot see: contagion, systemic risk, fraud rings, and relational alpha.
0/7 lessons
- 🎯Expert
Causal Inference for Alpha & Execution
ExpertThe discipline that separates 'my signal predicts returns' from 'my signal causes returns': potential outcomes, confounding, natural experiments, instrumental variables and double machine learning — aimed squarely at trading signals and the true cost of your own trades.
0/8 lessons
- 🛡️Expert
Adversarial Machine Learning & Model Robustness in Trading
ExpertMarkets are adversarial: other agents probe, spoof, and trade against your model, and the data shifts the instant you deploy. Learn adversarial examples and data poisoning aimed at trading models, distribution shift and concept drift, and the robustness toolkit — adversarial training, robust optimization, and honest stress evaluation — for systems that must survive an opponent, not a benchmark.
0/7 lessons
- 🌀Expert
Generative Models for Synthetic Market Data
ExpertManufacturing more market when you have too little — the data-scarcity problem behind deep learning in finance, the stylized facts every generator must reproduce (fat tails, volatility clustering, slow absolute-return autocorrelation, the leverage effect), the classical Monte-Carlo baselines (GBM, block bootstrap, regime-switching), and the modern learned generators (GANs and the QuantGAN/TimeGAN lineage, variational autoencoders, diffusion/score-based models) — plus the hard, under-taught problem of evaluating synthetic data without fooling yourself, where a memorizing generator silently leaks the future into every downstream backtest.
0/8 lessons
- 🐜Expert
Agent-Based Models & Market Simulation
ExpertGrow a market from the bottom up. Instead of learning a generator from your one history, build the market mechanistically as a swarm of interacting agents — zero-intelligence traders, market makers, momentum and value players, and the learned RL bots from earlier courses — and let the price path emerge. Watch stylized facts (fat tails, volatility clustering, autocorrelations) fall out of interaction rather than being programmed in, learn to calibrate an ABM to real data and validate it without fooling yourself, and use it as a sandbox the historical tape can never give you — counterfactual market structure, flash-crash stress tests, and a non-stationary training ground that pushes back on your RL agents.
0/8 lessons
- 🧠Expert
Foundation Models for Financial Time Series
ExpertThe pretrain-and-adapt playbook walks into markets — large time-series foundation models (the TimesFM / Chronos / Moirai / Lag-Llama lineage), how they tokenize continuous returns, zero-shot and few-shot forecasting and whether scaling laws even hold on financial data, LLMs as research tools and as multimodal price-plus-text signals, the leakage minefield of pretraining on the future, and an honest, deflated-Sharpe audit of whether any of it survives an efficient, non-stationary market.
0/7 lessons