Compare Strategies Side by Side

When you have two candidate strategies with different instruments, different signals, or different parameter sets, the right question is not "which one has the higher Sharpe?" It's "which one is more robust, more consistent, and better suited to your risk tolerance?" The comparison view lets you answer that question without leaving the chat.

1. Running multiple backtests in one conversation

The Quant agent retains context across your conversation. Run two backtests in the same session and both are available for comparison:

"Backtest a 20/50 EMA crossover on RELIANCE NSE:RELIANCE for the last 3 years."

Then:

"Now backtest the same EMA crossover on HDFCBANK NSE:HDFCBANK for the same period."

After both are complete:

"Compare the two backtests side by side: equity curves, Sharpe, max drawdown, win rate, and profit factor."

The comparison view appears with both equity curves overlaid on the same chart and a metrics table below.

2. What the comparison view shows

Equity curve overlay: Both equity curves are normalised to the same starting capital and plotted together. The divergence between them tells you which instrument gave the strategy a better ride.

Metrics table:

A higher Sharpe on RELIANCE NSE:RELIANCE tells you the signal worked better there. The lower max drawdown confirms it was a smoother ride. But you need more evidence before concluding the signal itself is better on RELIANCE NSE:RELIANCE, since the test period may have favoured one stock.

Trade log comparison: Side-by-side trade logs for both instruments, with the ability to drill into any trade and see the indicator context at entry (via the Diagnostician).

3. Comparing signal variants on the same instrument

A common use case is testing multiple variations of the same strategy on the same instrument:

"Backtest three variants of EMA crossover on NIFTY:

• 10/30 EMA
• 20/50 EMA
• 20/50 EMA with RSI > 60 filter Test all three on the last 2 years and compare."

The Quant agent runs all three and returns a 3-way comparison. You'll see clearly which parameter set dominates and whether the RSI filter helps or hurts.

4. Comparing strategy types on the same instrument

Different strategy types produce very different equity curve shapes:

"On BANKNIFTY, compare:

1. A short iron condor on weekly options (theta decay strategy)
2. A momentum strategy on BANKNIFTY futures Which has a better risk-adjusted return over the last 18 months?"

The two strategies have fundamentally different risk profiles:

• The options strategy profits from time decay and low movement
• The futures strategy profits from sustained directional moves

Their equity curves will have very different drawdown patterns. A comparison shows you which regime dominated the test period and whether you're comparing apples to oranges.

5. Using the Strategies library for comparison

The Strategies tab stores all your saved backtests. You can compare any two saved strategies from your library:

"Compare my RELIANCE NSE:RELIANCE EMA crossover strategy with the HDFCBANK NSE:HDFCBANK RSI mean-reversion strategy I saved last week. Which had better out-of-sample performance?"

The platform pulls both strategy records (including the full backtest result) and renders the side-by-side view without needing to rerun the backtests.

The Strategies tab also shows a Similar Strategies panel for any selected strategy: strategies in your library that had similar entry rules or instruments, so you can compare against your own historical research.

6. Comparing across test periods

The same strategy on the same instrument can look very different across different market regimes. Use comparison to test period sensitivity:

"Backtest my NIFTY momentum strategy on two non-overlapping periods:

• Jan 2022 to Dec 2023 (bearish/sideways regime)
• Jan 2024 to Dec 2025 (recovery and bull regime) Compare the results."

If Sharpe collapses in one period but holds in the other, you've discovered a regime dependency. This is important context before deploying to paper.

7. Deciding which strategy to deploy

Use the comparison as a decision tool. A useful framework:

Prefer the strategy with:

• Higher Sharpe across both in-sample and (if walk-forward tested) out-of-sample
• Lower max drawdown: you have to be able to stomach the worst case in practice
• Fewer total trades: lower transaction cost drag, easier to monitor manually
• Consistent win rate across years: not one great year and several bad ones

Flag for further investigation:

• Sharpe differences less than 0.2: likely noise, not real edge
• Max drawdown difference greater than 5%: the risk profile is meaningfully different
• Very different trade counts: comparing an intraday strategy with a swing strategy on the same Sharpe scale is misleading

8. Exporting comparison results

The comparison view has a Share button that generates a public link to the comparison result, useful for sharing with a colleague or saving for reference.

Individual backtests can also be saved to the Strategies library with a custom name so you can find them later for ongoing comparison as you refine your research.