Volatile Markets: How to Quickly Find Trade Systems That Work

Market volatility can shake even the most seasoned traders. In uncertain conditions, the challenge isn’t just surviving—it’s adapting. Jeremy Tang and Zach White from SharkIndicators unpacked how traders can rapidly test and refine systems that fit today’s changing market dynamics using their tools, BloodHound and BlackBird.

 

Understanding the current market context

 

Over the past few years, traders have experienced whiplash—from sharp drops during the pandemic to extended periods of uncertainty influenced by inflation, supply chain disruption, and interest rate decisions. The days of stable uptrends have given way to more complex, sideways movements. In these environments, traditional trend-following strategies may falter.

 
Tang and White proposed that going forward, traders could see choppier, more consolidation-heavy markets. That shift demands a different approach—one rooted in flexibility and quick adaptation.
 

Why backtesting still matters

 

Whether you’re rebuilding a system or starting from scratch, backtesting is essential. It allows traders to assess how a strategy might have performed under past market conditions. But traditional backtesting—manually analyzing charts and recording trades—is tedious and time-consuming.

 
Here’s where technology helps. With tools like BloodHound and BlackBird, traders can visually build systems and automate the backtesting and optimization process without needing to write a single line of code.
 

Creating and optimizing a system

 

White showed how to build a mean-reversion strategy designed for volatile conditions using three classic indicators: a simple moving average (SMA), stochastics, and the percent oscillator (PO), a normalized version of the MACD. The setup focused on long entries when the market was below the SMA, with stochastics in oversold territory and the PO below zero.

 
Using BloodHound, he constructed the entry logic visually, plugging in the indicators and logic blocks to generate entry signals. Once defined, those signals fed into BlackBird, which handles trade management (e.g., entries, exits, stop-loss logic). But the real value came with optimization.
 

Turning hundreds of tests into insights

 

Through NinjaTrader’s Strategy Analyzer, the team demonstrated how to run large-scale optimizations. By testing various values for indicator thresholds and stop-loss/profit target settings, traders can identify configurations that align best with the market’s behavior.

 
For example, their test results showed that tighter stochastics thresholds (e.g., oversold levels closer to 5 rather than the conventional 20) and more conservative profit targets worked better in a sideways market. Meanwhile, some variables, like the SMA length, showed little impact, highlighting the importance of knowing which elements truly matter.
 
Optimization can also help surface consistent trends across instruments. The team tested the system across the Dow 30 stocks and found similar patterns, reinforcing confidence in the system’s logic and robustness.
 

The value of rapid iteration

 

The takeaway? Traders don’t need to settle for outdated strategies or start from zero each time the market shifts. With tools like BloodHound and BlackBird, system creation and refinement can be fast, visual, and driven by data.

 
By quickly iterating on ideas and automating optimization, traders can stay agile, adapting to market conditions with systems built for today, not yesterday.

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