OST's Blog

Trading insights, market analysis, and swing trading strategies.

What “Better Stock” Means for Breakout Swing Traders

What “Better Stock” Means for Breakout Swing Traders

An explainer on what “better stock” means for breakout swing trading—why liquidity, structured volatility, crowded reference levels, and clean price action matter more than being a “good company.”

Why your market breadth dashboard gives false risk signals

Why your market breadth dashboard gives false risk signals

A practical troubleshooter for market breadth dashboards that throw off false risk signals—validate your universe and timestamps, fix A/D line and volume-breadth math, de-mirage 52‑week highs, and rebuild moving averages and thresholds so indicators match reality.

Why your relative strength stock screener misses winners

Why your relative strength stock screener misses winners

A practical troubleshooter for fixing relative strength stock screeners that miss the biggest winners — diagnose failure symptoms, audit benchmark/universe fit, correct return math and corporate actions, tune lookback windows, and upgrade ranking methods for cleaner signals.

Build sector theme strength ranks in 15 minutes

Build sector theme strength ranks in 15 minutes

A fast, repeatable guide to building sector theme strength ranks in 15 minutes—define a universe and strength lens, pull and validate price data, compute normalized relative returns, apply a trend filter, and combine windows into a composite score you can rank.

Episodic pivot results: 50 breakouts, win rate

Episodic pivot results: 50 breakouts, win rate

A data-backed case study on episodic pivot breakouts—define the setup and benchmarks, document entry/exit and cost assumptions, summarize 50 breakout outcomes, and translate win rate into expectancy with regime filters and failure-pattern risk controls.

William O'Neil Explained for Breakout Swing Traders

William O'Neil Explained for Breakout Swing Traders

An explainer for breakout swing traders on William O’Neil’s method—understand the breakout premise, apply CAN SLIM as a decision lens, spot bases/pivots/handles, read volume tells, and execute entries with 7–8% stops plus sizing and pyramiding rules.