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Hold bitcoin above 100 day

Hold bitcoin while it’s above its 100 day average. Move to cash when it drops below.

Prepared dataBTC 1d · 1,462 candles

Wrote strategy.pyComplete

1import pandas as pd2import numpy as np345def run_backtest(df):6    """BTC 100 Day Trend. Hold bitcoin while it closes above its7    100 day moving average; move to cash on a close back below."""8    initial_capital = 10000.09    fee = 0.001  # 0.1% taker fee, charged on every fill1011    close = df["close"]12    sma100 = close.rolling(window=100).mean()1314    # Long when the prior close sits above the 100-day average.15    # Shift one bar so a bar never decides its own trade (no lookahead).16    long = (close > sma100).shift(1).fillna(False)1718    cash = initial_capital19    units = 0.020    equity_curve = []21    trades = []2223    for i in range(len(df)):24        price = float(close.iloc[i])25        ts = int(df["ts"].iloc[i] // 1000)2627        if long.iloc[i] and units == 0.0:28            units = (cash * (1 - fee)) / price29            cash = 0.030            trades.append({"time": ts, "side": "buy", "price": price})31        elif not long.iloc[i] and units > 0.0:32            cash = units * price * (1 - fee)33            units = 0.034            trades.append({"time": ts, "side": "sell", "price": price})3536        value = round(cash + units * price, 2)37        equity_curve.append({"time": ts, "value": value})3839    curve = np.array([p["value"] for p in equity_curve])40    returns = np.diff(curve) / curve[:-1]41    sharpe = np.sqrt(365) * returns.mean() / returns.std()42    peak = np.maximum.accumulate(curve)43    max_drawdown = ((curve - peak) / peak).min() * 10044    return {

Ran backtestComplete

Return+42.3%

Buy & hold+29.9%

Max drawdown−8.2%

Sharpe1.34

Trades24

Equity curve Strategy Buy & hold

20212024

Illustrative backtest · hypothetical results

Strategy saved — BTC 100 Day Trend · BTC 1dview file ❯

Example backtest · 42% · running in background

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Trend following
Hold while price stays above its own average, step aside when it doesn't.
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Buy the stretch away from fair value, sell the snap back.
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Review the assumptions behind my BTC 100 day trend strategy. What should I check before trusting the result?

I’ll check how the rule is evaluated, what the data contains, and which costs the backtest includes.

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Three checks for the next run

Timing. Evaluate the signal on a completed daily candle. The next fill must occur after the signal is known.

Coverage. Check the market, date range and missing candles before comparing results.

Costs. Include fees and slippage, and compare against buy and hold over the same period.

Sources reviewed

Strategy rules · BTC 100 day trend

Kraken API documentation · OHLC data

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Long bitcoin while price holds above its 100 day moving average; move to cash on a close below.

I built BTC 100 day trend and opened its current backtest in the workspace.

Wrote strategy code Code v1Running backtest 68.4%btc_100d_trend.pyBacktest · BTC 1d

Which rules is it actually trading?

Both rules read off the same daily close.

EntryClose crosses above the 100 day moving average.ExitClose falls back below the 100 day moving average.Testing on 1,462 daily candlesRules · BTC 100 day trend

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I built Take profit ladder and opened its current backtest in the workspace.

Wrote strategy code Code v1Running backtest 14.6%take_profit_ladder.pyBacktest · BTC 1d

Which rules is it actually trading?

Both rules read off the same daily close.

EntryAn open position is up 25% from its entry price.ExitSell half at +25%, the rest at +50% or on a close back at entry.Testing on 1,462 daily candlesRules · Take profit ladder

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The backtest is still running. I’ll review the results and trade log once it finishes.

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