Strategy Archetypes + Backtesting
Trend-following, mean-reversion, stat-arb, event-driven — flashcard drills on entry/exit logic, regime filters, and backtest pitfalls. Start drilling →
Algorithmic Trading Education — Strategy Archetypes, Backtesting Concepts, and Risk Tools
AlgoDrill is a flashcard-style platform for building rigorous algorithmic-trading knowledge. Unlike every other "algo trading course" that hand-waves the hard parts, AlgoDrill's agentic-AI module (in development) will teach you to build LLM-driven paper-trading agents from scratch — state machines, prompt design, data pipelines, and feedback loops — before you risk a single dollar. The Kelly, Sharpe, drawdown, and expectancy tools are live calculators you keep open while you build.
Start Flashcard Drill →What's Inside
Build LLM-Driven Trading Agents
The module nobody else builds. Coming soon — will cover agent architecture: data ingestion, LLM signal generation, paper-trade execution loop, and performance eval.
Kelly + Sharpe + Drawdown Tools
Live calculators for the four numbers every systematic trader watches: Kelly fraction, Sharpe ratio, max drawdown, and expectancy. Paste your returns and get instant risk-adjusted feedback.
Live Tools
Kelly Criterion + Expectancy
Enter your historical win rate and average win/loss to compute optimal position sizing.
Sharpe Ratio + Max Drawdown
Paste a comma- or space-separated list of periodic returns (e.g. daily P&L as decimals).
Max Drawdown Analyzer
Paste your equity curve (account value, NAV, or any positive series) to get peak, trough, and max drawdown with recovery status.
Trade Expectancy Batch Calculator
Paste your trade P&L values (positive = win, negative = loss) to get win rate, expectancy, payoff ratio, and profit factor across your full trade history.
Backtest Health Check
Enter your backtest summary metrics to flag common red flags — overfitting, poor risk-adjusted returns, thin edge, and small sample size.
How to Think About Algorithmic Trading Risk
Most retail algo traders fail not because their signals are wrong, but because their position sizing destroys the account before the edge can compound. The four numbers below are the minimum viable dashboard for any systematic strategy:
- Kelly Fraction: The maximum fraction of capital to risk per trade that maximizes long-run geometric growth. A positive Kelly means you have positive expected value; negative Kelly means stop trading the setup immediately. Most pros use half-Kelly (50% of the output) to reduce variance and path risk.
- Expectancy: Average profit per dollar risked across many trades. A strategy with $0.10 expectancy earns 10 cents for every dollar risked on average. Below zero: the strategy is a net drain regardless of position sizing.
- Sharpe Ratio: Risk-adjusted return. Measures how much excess return you earn per unit of volatility, annualized (×√252 for daily returns). Values below 0.5 are weak; 1.0+ is respectable; 2.0+ is exceptional (and worth scrutinizing for look-ahead bias or overfitting).
- Max Drawdown: The largest peak-to-trough decline in the equity curve. This is the number you actually feel psychologically — a 40% drawdown requires a 67% recovery just to break even. Know your drawdown before you trade real money.
The Kelly and Sharpe calculators above work entirely in your browser — no data leaves the page.
What the Agentic AI Module Covers
Coming soon — director-authored deck in progress.
The agentic-AI module will be the differentiating content on AlgoDrill — it will be the only structured curriculum that teaches you to build LLM-driven paper-trading agents, not just use them as chatbots. The architecture has five layers:
- Data ingestion: Streaming price data from broker APIs (paper accounts only), normalizing tick data into feature vectors an LLM can interpret.
- Signal generation: Prompt engineering for trading decisions — structured outputs, chain-of-thought for market-regime classification, and tool use for accessing indicators in real time.
- Execution loop: A paper-trade state machine that processes LLM decisions, applies position sizing (Kelly-constrained), and logs fills to a local ledger.
- Feedback loop: Automated performance evaluation that feeds back Sharpe, drawdown, and expectancy metrics to the agent as context, enabling iterative improvement without human intervention.
- Guardrails: Hard constraints enforced at the code level — max position size, daily loss limit, and circuit breakers — so the agent cannot exceed risk parameters even if the LLM generates a rogue signal.
Every lesson is a flashcard drill, not a video. You read the concept, recall the structure, and verify against the answer. The goal is retention, not passive consumption.
Frequently Asked Questions
- What is AlgoDrill?
- AlgoDrill is a free flashcard-style educational platform for algorithmic trading. It covers strategy archetypes and backtesting concepts today, with an agentic AI module (LLM-driven paper-trading agents) in development. It also includes live Kelly Criterion, Sharpe Ratio, drawdown, and expectancy calculators.
- Does AlgoDrill execute trades or manage my money?
- No. AlgoDrill never executes trades, never holds API keys, and never connects to your brokerage. It is a purely educational platform. We teach the architecture; you wire your own broker on your own account.
- What is the Kelly Criterion?
- The Kelly Criterion is a formula for optimal position sizing: given your win rate, average win, and average loss, it computes the fraction of capital to risk per trade that maximizes long-run portfolio growth. Many practitioners use half-Kelly (50% of the output) to reduce variance.
- What is the Sharpe Ratio?
- The Sharpe Ratio measures risk-adjusted return: average excess return divided by standard deviation of returns. Above 1.0 is good; above 2.0 is excellent. Below 0.5 suggests the strategy does not compensate for its volatility.
- What is an agentic AI trading agent?
- An agentic AI trading agent uses an LLM to reason about market data, generate trading signals, and paper-trade in a feedback loop. AlgoDrill will teach the full architecture: data ingestion, LLM signal generation, paper-trade execution, and performance evaluation — all before risking real capital. The dedicated deck is in development.
- What is Sortino Ratio?
- The Sortino Ratio is a variation of the Sharpe Ratio that penalizes only downside volatility (returns below the target or risk-free rate), not upside volatility. A strategy with frequent small gains and rare large losses will score higher on Sortino than Sharpe. Sortino above 1.0 is generally considered good; below 0.5 is weak.
- What is Calmar Ratio?
- The Calmar Ratio is the annualized geometric return divided by maximum drawdown. It measures how much annual return you earn per unit of worst-case drawdown risk. A Calmar above 1.0 means you earn more than your worst drawdown in a given year — a useful bar for trend-following and CTA-style strategies.
- What is profit factor in trading?
- Profit factor is the ratio of gross profit (sum of winning trades) to gross loss (sum of losing trades). A profit factor above 1.0 means the system is net profitable; below 1.2 the edge is so thin that commissions and slippage can easily flip it negative. Above 2.0 is strong; above 3.0 warrants scrutiny for overfitting.
- Is AlgoDrill free?
- Yes, completely free. No account, no subscription, no credit card. All tools run in your browser — no data leaves the page.