> ## Documentation Index
> Fetch the complete documentation index at: https://www.questforedge.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Research

> Explore trading risk experiments and simulations covering drawdowns, losing streaks, compounding, correlation, and Monte Carlo analysis.

Trading outcomes are shaped by distributions, sequences, and compounding—not by a single trade. This section uses simulations and structured examples to make those behaviors easier to see.

## Risk experiments

> [card] [The mathematics of drawdown](https://www.questforedge.io/research/risk-experiments/the-mathematics-of-drawdown-and-why-it-matters.md)
>
> Understand how losses compound and why recovery becomes progressively harder.

> [card] [How losing streaks behave](https://www.questforedge.io/research/risk-experiments/how-losing-streaks-actually-behave.md)
>
> Explore why normal variance can produce uncomfortable sequences of losses.

> [card] [Risking 1% vs 5% per trade](https://www.questforedge.io/research/risk-experiments/what-happens-if-you-risk-1-vs-5-per-trade.md)
>
> Compare account survival and drawdown behavior under two risk levels.

> [card] [Accounting for correlated risk](https://www.questforedge.io/research/risk-experiments/accounting-for-correlated-risk-in-trading.md)
>
> See how several positions can create one concentrated exposure.

## Simulations

> [card] [Monte Carlo simulation](https://www.questforedge.io/research/simulations/monte-carlo-simulation-in-trading-explained-simply.md)
>
> Use repeated random paths to estimate the range of plausible system outcomes.

> [card] [Can a 40% win rate be profitable?](https://www.questforedge.io/research/simulations/can-you-be-profitable-with-a-40-win-rate.md)
>
> Test how payoff size changes the meaning of win rate.

> [card] [Random entry and risk control](https://www.questforedge.io/research/simulations/random-entry-+-good-risk-management-what-happens.md)
>
> Separate loss control from the positive expectancy required for profitability.

## Data insights

> [card] [Why accounts blow up](https://www.questforedge.io/research/data-insights/the-real-reason-accounts-blow-up.md)
>
> Examine leverage, escalation, concentration, and missing limits.

> [card] [Compounding gains and losses](https://www.questforedge.io/research/data-insights/how-compounding-works-against-you-and-for-you.md)
>
> Understand asymmetric recovery after percentage drawdowns.

> [card] [Consistency vs prediction](https://www.questforedge.io/research/data-insights/why-consistency-beats-prediction.md)
>
> See why stable execution is necessary to measure a strategy.

## How to read the research

Worked examples expose their assumptions and are designed to teach mechanisms. They are not forecasts. For publication standards and sourcing, see the [editorial methodology](https://www.questforedge.io/reference/editorial-methodology.md).

> [!NOTE]
>
> Simulations explain ranges and probabilities. They do not predict the exact path of a live trading account.


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