Algorithmic Trading Robots Without Programming (17 Hrs) MT5

This lecture defines black box algorithmic trading, where preprogrammed rules automatically generate buy and sell signals and execute trades without human input, covering high-frequency trading and cost and risk minimization.

Explore how much algorithmic trading and high-frequency trading shape today’s markets, with profitability examples, liquidity implications, and the need to learn algo trading to stay competitive.

Learn how to download MT5 easily from the website, available on Windows, iPhone, iPad, and Android, and how to find codes for MT5 trading.

Explore how technical indicators use math calculations from price and volume history to signal future price movement, and examine display styles—price charts and separate panels—backed by historical data.

Learn how TRIX uses exponential moving averages and smoothing to measure momentum and indicate trend direction, with zero-crossings signaling potential trades.

Build and configure a TRIX-based MT5 trading robot by selecting the triple exponential average, applying stop-loss strategies, and testing and compiling inputs to optimize risk and performance.

Discover how the TRIX algorithmic trading robot for MT5 generates six buy and sell signals, including divergences, and learn testing, stop-loss, and take-profit strategies to maximize profits.

Learn how to test TRIX-based algorithmic trading robots, set signals and thresholds, apply moving average rules, manage orders with stop loss and take profit, and optimize inputs for best performance.

Learn to test the TRIX algorithmic trading robot, analyze single trades, and use optimization to choose the best inputs for consistent profits in backtests.

Explore the adaptive moving average, a low-sensitivity, low-lag indicator that adjusts to recent prices rather than treating all days equally, helping detect uptrends and downtrends.

Build an adaptive moving-average algorithmic trading robot on MT5 by configuring an expert advisor, setting stop loss, trailing stop, parabolic SAR, and fixed risk or volume, then test and optimize.

The lecture shows how an adaptive moving average signals buys when the line points up and sells on breaks or closes below the line, guiding trend-based trading.

Test and refine adaptive moving average based algorithmic trading robots on MT5, adjusting signals, stop-loss, take-profit, and execution settings to optimize performance in historical testing.

Explore adaptive moving average testing for MT5 algorithmic trading robots, optimize inputs for max profit, balance, and stop conditions, and interpret optimization results to select profitable signals.

Discover the William% volume percentage indicator, interpret price near highs or lows, and apply volume-based signals within a trading range to enhance MT5 algorithmic trading.

Discover how the William percentage oscillator drives an MT5 algorithmic trading robot, generating buy and sell signals through divergence and the value accelerator, with automated trade execution and testing.

Test and customize the William oscillator algorithmic trading robot in MT5 by editing signals, importing inputs, and adjusting delay, stop loss, and take profit settings.

Optimize the William oscillator algorithmic trading robot through testing, settings, and inputs. Highlight trailing stop loss, margin calls, and risk management.

Define tema as the triple exponential moving average introduced by Patrick Tremblay in 1994, reducing lag and serving as a leading indicator for algorithmic trading on MT5.

Learn to create a TEMA-based algorithmic trading robot in MT5 without programming, configure signal properties, stop-loss rules, and money management, then compile and test.

Learn how a tema-based algorithmic trading robot generates buy and sell signals from open, close, and line relationships, and how input changes affect trades, profits, and stop losses.

Explore how to test and optimize MT5 algorithmic trading robots, using moving-average signals, fixed risk, and stop-loss and take-profit rules. Learn input setup and testing scenarios to gauge profitability.

Test and optimize the TEMA algorithmic trading robot in MT5, selecting inputs to maximize profit factor and minimize losses. Use optimization graphs to compare periods and export configurations for testing.

See how small input differences and money management techniques elevate profits in TEMA algorithmic trading robot testing on MT5. The session demonstrates optimization and backtest results that show rising profitability.

Learn how the stochastic oscillator uses support and resistance to gauge trend and predict turning points by comparing price to its range, producing a 0 to 100 percentage from high-low.

Create and own a stochastic-based expert advisor on MT5, choose stochastic signals, set stop-loss and risk options, compile changes, and test inputs in the strategy tester for optimization.

Demonstrates how the stochastic oscillator generates buy and sell signals through signal line crossovers and divergences, illustrated with practical two-trade examples and testing insights.

Test a stochastic trading robot using drag-and-drop signals, adjustable thresholds, and open-high-low-close data in the strategy tester to optimize inputs across market conditions.

Explore stochastic testing and input optimization for trading robots, identifying recurring top inputs like 13:21 entry to maximize profits through single tests and input comparisons.

Learn to build an rvi-based algorithmic trading robot in MT5 by creating a new expert advisor, configuring symbol, timeframe, period, stop loss, take profit, and volume, then compile for testing.

learn how the rvi trading robot generates buy and sell signals via signal-line crosses and moving-average inputs, and test parameters to identify the best performing setup with stop-loss rules.

Explore setting up and testing the RVI robot on MT5, adjust inputs, run backtests with history and forward testing, optimize signals, and maximize profit without programming.

Explore RVI robot testing on MT5, learning how input settings and 60-day backtests shape profit and risk, and how to run single tests to identify robust buy-sell setups.

Explore how the relative strength index (RSI) gauges momentum on a 14-day 0–100 scale, flags 70/30 overbought and oversold levels, and signals divergences indicating potential trend reversals.

Create an RSI-based trading robot in MT5 without coding, using the export advisor, configure RSI and time frame, and apply stop-loss and money-management rules for reliable automation.

Discover how a RSI trading robot on MT5 uses oversold and overbought RSI levels, divergences, double divergences, and head-and-shoulders patterns to generate automatic buy and sell signals without programming.

Test an RSI robot in MT5 without programming by adjusting signals, stop-loss, take-profit, and price type (open vs. close) to optimize backtests and identify effective thresholds.

Explore RSI robot testing on MT5 with a default trading board, evaluating inputs, signals, and take-profit stop-loss at 50 pips, without optimization, to assess performance across assets.