A Trend-Alignment Signal for Polymarket's BTC Up/Down Markets

Polymarket is a prediction market platform where every trade is public - you can see exactly what any wallet bought, at what price, and when. Some of these markets ask a simple question: will Bitcoin be higher or lower five minutes from now? Most bots trading these markets look at one signal at a time - momentum on a short timeframe, or comparing the market price to a live Bitcoin price feed. Traders in other markets, like leveraged futures, often do something different: they check whether multiple timeframes agree before trusting a move. A longer timeframe tells you the overall trend, a medium one confirms the current move still has room, and a short one times the entry. I wanted to see if that same idea - checking several timeframes before acting - could work for Polymarket's short Bitcoin markets. It mostly does, but only once you strip out the parts built for a different kind of trading. Why the full version doesn't transfer The original version of this idea comes from futures trading, where a trader holds one open position that can be adjusted for hours: adding to it if the price moves the wrong way, trailing a stop once it moves the right way, letting a winning trade run. None of that fits Polymarket. Each Bitcoin market - 5 minutes, 15 minutes, or 1 hour - is a one-time bet. It resolves to a win or a loss at a fixed time, then it's over. There's no ongoing position to adjust, no stop-loss order to place, and no way to "average in" the way a futures trader would, because the bet doesn't stay open long enough for that idea to make sense. What does work: the agreement check itself The part that survives is simpler than the full strategy: does the long-term trend, the medium-term momentum, and the short-term timing all point the same direction? If yes, that's a stronger signal than any one of them alone. If they disagree, the bot skips the trade rather than guessing. Here's a simplified version of what that looks like in code:

def trend_aligned(price, ema_200_1h, rsi_15m, stoch_rsi_3m, stoch_rsi_3m_prev):
    bullish_trend = price > ema_200_1h
    bearish_trend = price < ema_200_1h

    pullback_recovering = rsi_15m < 40 and stoch_rsi_3m > stoch_rsi_3m_prev
    rally_fading = rsi_15m > 60 and stoch_rsi_3m < stoch_rsi_3m_prev

    if bullish_trend and pullback_recovering:
        return "up"
    if bearish_trend and rally_fading:
        return "down"
    return None
    ...

This isn't a full trading decision by itself — it's a filter. Even when the timeframes agree, the bot still needs to check whether the market's current price actually offers a good deal compared to what it thinks the real odds are:

def combined_decision(trend_signal, model_probability, execution_price, fee, slippage, buffer):
    if trend_signal is None:
        return None

    net_edge = (model_probability - execution_price) - fee - slippage - buffer
    if net_edge <= 0:
        return None

    return trend_signal
    ...

Agreement across timeframes tells you a direction is more likely to continue. It doesn't tell you the market is pricing that likelihood incorrectly. You only have a real edge when both are true. Where this is genuinely useful - and where it isn't This kind of signal works best as a confirmation layer, not the main source of an edge. Since Bitcoin's longer-term trend often doesn't change much over the course of just a few 5-minute windows, this check can end up agreeing with itself several times in a row without adding much new information. It's a tie-breaker, useful alongside other signals rather than instead of them - and like anything else here, it's worth testing carefully in paper-trading mode before trusting it with real money.
I build trading tools for people working on Polymarket - signal design, strategy extraction from wallet history, or full bot builds. Full source, paper-trading validation before anything goes live.