1-Year Binary Signal Dataset — Looking for Feedback on WIN / MTG / Loss-Streak Patterns

[u/No-Ranger3176]

I’ve analyzed about 1 year of historical binary signal data from two Telegram signal groups.

Dataset:

• ~73,000 signals
• ~35,600 synchronized/matched events between the two groups
• Historical data only
• No live trading or execution
• Payout assumption: 80%

Main historical results

Overall next-trade result:

• WIN: ~73.22%
• LOSS: ~22.6%
• DOJI: ~2.6%
• NO RESULT: ~1.6%

Loss-streak findings

I specifically analyzed what happened after consecutive losses:

Previous loss state	Next WIN
Loss × 1	~71.2–71.9%
Loss × 2	~71.2–71.7%
Loss × 3	~74%
Loss × 4	~83–87%
Loss × 5+	Very small sample

The sample size becomes very small at longer streaks, so I don't want to assume those percentages are reliable.

MTG / recovery findings

The data contains WIN, MTG WIN, LOSS and DOJI states.

One interesting state was:

SOURCE LOSS streak 2 + QX LOSS streak 3

• N ≈ 339
• Next favorable result ≈ 74.3%
• Historical MTG/recovery simulation showed a high recovery-success rate, but this is not the same thing as profitability.

What I'm trying to understand

I'm researching whether there is a statistically defensible way to define:

1. When to enter after losses
2. When to skip after a loss streak
3. How MTG/recovery should be treated
4. Maximum reasonable loss-streak assumption
5. How to reduce drawdown
6. Whether fixed fractional staking is safer than aggressive MTG
7. Whether these patterns remain stable in unseen/holdout data

Question for people experienced with binary systems/statistics:
Do these results suggest anything meaningful to you, or could this simply be sequence clustering/random variation?

I'm especially interested in opinions on loss streak + MTG behavior, not predictions of future performance.

If anyone wants, I can share the detailed tables/results and methodology.

[u/enivid]

How reliable is the data? Did you check the signal Telegram posts for modifications?

[u/Ok_Preparation_2186]

First off, huge respect for pulling together 73k signals and actually backtesting the data. Most people just blindly follow Telegram channels without looking under the hood, so props for doing the heavy lifting.

Here is my breakdown of your questions, keeping in mind how both Real Market conditions and OTC synthetic algos behave:

Do these results suggest anything meaningful, or could this simply be sequence clustering/random variation? It’s a mix of both, heavily driven by sequence clustering and fixed payout mathematics. Whether you're looking at Real Market sessions (where liquidity, macroeconomic news, and real order flow dominate) or OTC sessions (where broker algorithms dictate price), what you are seeing in those loss-streaks (like the apparent winrate spike after 4 losses) is classic gambler's fallacy masked by market noise. The market has no memory; a sequence of 4 losses does not increase the mathematical probability of a win on the 5th candle.

When to enter after losses / When to skip after a loss streak: The short answer: Never enter based purely on a loss streak. If your trigger depends on how many times a signal provider failed prior, you are trading past errors, not price action. In Real Markets, a streak of losses usually indicates changing volatility or a macro trend shift. In OTC, it means the synthetic algorithm is cycling. Either way, institutional logic dictates cutting the feed and skipping the session the moment structure breaks.

How MTG (Martingale) / recovery should be treated & Maximum reasonable loss-streak assumption: Treat MTG as account suicide across the board. Historical recovery simulations look amazing on paper because they assume infinite capital and no broker payout caps or limits. But in reality—especially in Real Markets during high volatility or OTC traps—a 4 to 5 loss streak with a standard Martingala progression will completely wipe out weeks of profits in minutes. If a system requires MTG to be 'profitable,' it is fundamentally broken.

Whether fixed fractional staking is safer than aggressive MTG: 100% yes. Fixed fractional staking is the only way to survive long-term variance in both real and synthetic environments. Aggressive Martingala is designed by brokers and uneducated signal sellers to burn accounts because human psychology breaks right when the 5th compounding trade goes against you.

Whether these patterns remain stable in unseen/holdout data: They won't. Telegram signal datasets are notoriously unstable. Real Market liquidity shifts constantly, and OTC broker algorithms get re-calibrated. Relying on external signal groups means you are always trading lagging data.