Autopilot Bitcoin Systems

Explore basic chart features: draw and adjust support and resistance lines and trend lines, measure moves, delete unused elements, and add indicators such as moving averages and RSI.

Explore how candlesticks work, including green and red candles, open-high-low-close relationships, and volume signals, and compare series like heikin-ashi, renko, and point-and-figure for trend analysis.

learn to code a pine script indicator in trading view and plot highs and lows to form a channel. configure yesterday's high/low, highest high, and lowest low over set periods.

Learn to program bullish engulfing and other candle formations in TradingView, building your first trading system that buys after bullish engulfing signals and sells after a set number of days.

Build a trend following system with a simple moving average indicator, then a long/short strategy where close > moving average triggers longs and close < triggers shorts, plus backtest results.

Explore a seven day moving average to improve profit factor and reduce drawdown while tracking net profit, trades, and win rate across long and short positions.

Explore short versus long strategies in autopilot bitcoin systems, toggle allow short to see effects on max drawdown, profit, and equity curves, with buy-and-hold comparisons.

visualize your backtests with a custom period selector to isolate performance during a chosen window, showing bear markets, profit factor, and drawdown for long and short entries.

Evaluate how backtest versus walk-forward validation shapes Bitcoin strategies by adjusting data splits, trade counts, and equity allocation, revealing robust profit factors and manageable drawdown in out-of-sample tests.

Create a market regime indicator using a 200-day moving average to identify bull or bear markets in Bitcoin, coloring the bottom chart green for bull and red for bear.

Experiment with different moving-average lengths to optimize crypto filters. The 165–170 day range shows higher profit factors and more stability than the 200-day benchmark.

Improve the bullish engulfing strategy by adding a volume filter: require volume above the 20-day SMA by 20%, increasing win rate and profit factor.

Explores a 12-period simple moving average with regime length 170, trading long in bull markets and short in bear markets, backtesting 2012–2024 and comparing profit factor, drawdown, and filter.

Explore Richard Dennis's turtle trading system using Donchian channels to trade breakouts. Size positions with percent of equity to compare fast and slow entries against buy-and-hold.

Experiment with Richard Duncan's five- and twenty-day moving average crossover system, compare 14/28 crosses, and explore exponential moving averages to tune signals and evaluate strategy results.

Beware of doctored performance in trading scripts; test across genuine data and avoid switching between versions that inflate win rates, drawdowns, or profit factors.

Explore how to trade Bitcoin using multiple systems and time frames, combining moving average strategies, crossover signals, and volume filters across daily and four-hour charts to beat buy-and-hold.

Explore how altcoins trade against Bitcoin, analyze market dominance and volatility, and use screeners and historical data to spot trailing signals.

Learn to use the cryptocurrency signal finder in trading view to filter altcoins, set alerts, and read oscillator and moving-average signals on daily charts for buy or sell opportunities.

Practice live trading with paper trading in trading view, place market orders, manage positions, and review orders and account history as you prepare for Poloniex or other brokers.

Engage in live bitcoin trading on the biggest exchanges by managing leverage, understanding maker vs taker roles, and minimizing fees with limit and market orders to avoid liquidation.

Learn how a Chrome browser extension links TradingView to 12 exchanges, enabling automated trades via an alert-based indicator, with clipboard export for Excel and live versus simulated checks.

Analyze systems to balance risk and reward, and apply risk management to prevent large drawdowns, choosing appropriate leverage and position sizing for sustainable returns.

Assess risk across your portfolio by normalizing trade size to one contract and exporting performance data to Excel, then compare strategies through returns, correlations, and scatter plots to guide diversification.

Adapt to market changes by using the equity curve feedback tool and moving average to manage trades, assess cumulative returns, and know when to stop trading.

Learn to align with price action by accepting your trades and controlling emotions, emphasizing risk management, discipline, and continuous effort for long-term trading success.

Download the source code from predictive.com for Aldo Dashni workshop 1, backtesting before live trading, walk forward daily, ensure live execution mirrors the simulation, and avoid late entries.