TickRun learning center

Understand the test before trusting the result.

Plain-language guides to the strategies, assumptions, controls, and risks behind a historical backtest.

Beginner guide

Technical indicators explained simply

Learn what trend, momentum, volatility, and volume indicators measure—and what they cannot tell you.

Learn the indicator families → Strategy concepts

Trend following versus mean reversion

Compare two major strategy styles, the market conditions they prefer, and the different ways they can fail.

Compare the approaches → Reading results

How to read a backtest equity curve

Recognize drawdowns, flat periods, concentrated gains, benchmark differences, and suspicious jumps.

Read the curve → Research workflow

From backtest to paper trading

Freeze a rule, define forward execution, keep a decision log, and understand what paper fills still leave out.

Plan the next stage → Performance metrics

Sharpe ratio explained for backtests

Understand TickRun’s exact formula, √252 annualization, the zero risk-free assumption, sampling uncertainty, and where the ratio fails.

Interpret Sharpe correctly → Market data

Adjusted stock data: the hidden foundation

See how splits, dividends, OHLC consistency, volume adjustments, missing sessions, and data revisions can alter a backtest.

Audit the data → Execution semantics

Signal timing and look-ahead bias

Follow the exact information timeline from a closing indicator through position state, delayed events, costs, and the next return.

Trace the timeline → Optimization research

Parameter sensitivity and robustness

Evaluate response surfaces, neighboring configurations, search budgets, multiple testing, and stability beyond one winning setup.

Test parameter stability → Performance evaluation

Choosing the right backtest benchmark

Compare Buy & Hold responsibly by accounting for exposure, cash returns, warm-up periods, risk, costs, and investability.

Choose a benchmark → Backtesting methodology

How to backtest a trading strategy properly

Turn an idea into an auditable rule, align signals with execution, model costs, choose benchmarks, and separate exploration from evidence.

Read the methodology guide → Research quality

12 backtesting mistakes that create false confidence

A technical examination of look-ahead, survivor selection, same-bar fills, data snooping, metric errors, and hidden model assumptions.

Audit a backtest → Execution realism

Transaction costs and slippage in backtests

Understand commissions, spreads, market impact, turnover, fill assumptions, and exactly what TickRun’s basis-point cost model captures.

Examine trading friction → Strategy validation

In-sample, out-of-sample, and walk-forward testing

Design chronological validation without leaking future information, repeatedly tuning the holdout, or confusing a fitted result with evidence.

Learn the validation workflow → Risk metrics

Maximum drawdown explained

Calculate peak-to-trough loss correctly, interpret path dependence, compare strategies, and understand what one drawdown number leaves out.

Understand maximum drawdown → Backtesting fundamentals

Overfitting in backtesting: why the best result can be misleading

Learn how repeated testing finds historical luck, how to recognize fragile results, and how to make strategy research more disciplined.

Learn about overfitting → Strategy reference

All 40 TickRun strategies explained

What each indicator measures, the precise entry and exit interpretation used by TickRun, and the default parameters.

Read the strategy guide →