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Forex Strength Investing

Greetings Traders!

I'm Pablo, a seasoned trader with over 12 years of experience in stocks, forex, and indices. I mainly trade on the eToro platform, but I also have coding expertise in creating expert advisors for MT4. Understanding the challenges traders face, I've developed an expert advisor designed to ease market analysis and improve trading success.

Trading Signal:

High Risk : Click Here Low Risk : Click Here

Rental and Pricing:

The current price of the FSI is $1,300 USD. Soon, the price will increase to $1,500 USD, so take advantage of the current pricing while it lasts.

The primary strategy of the Forex Strength Investing EA is a less aggressive Martingale approach combined with various indicators and semi-AI to automatically trade based on market analysis. It includes pattern detection, support/resistance levels, and risk management to handle high market volatility effectively.

  • Indicators and Semi-AI: Utilizes various indicators and semi-AI for automated trading.
  • Pattern Detection: Identifies harmonic patterns and support/resistance levels.
  • Martingale Strategy: Employs a less aggressive Martingale strategy based on market analysis.
  • Risk Management: Includes drawdown control and recovery mode.
  • Volatility Handling: Operates effectively in high market volatility without a news filter.

Recommended Settings:

  • Timeframe: M15
  • Currency Pairs: AUDCAD, AUDNZD, NZDCAD
  • Minimum Capital: $3,000 to $10,000 (Higher capital increases profit potential)

Easy Setup:

  • Attach the EA to the M15 chart for AUDCAD.
  • Use settings: 1000 for high risk or 2000 for low risk.
  • Recommended leverage: 1:500.
  • Use a low spread account (e.g., Exness).

Performance:

  • Drawdown: Backtests show a maximum of 45% for high risk and 25% for low risk.

Installation:

  • Simple installation with minimal input parameters.
  • Restart MT4 three times for optimal performance.

Final Notes:

  • Be patient for trades to occur.
  • Avoid using other EAs simultaneously.
Could you please add me to my business Facebook account? My FB link: fb.com/business-profile
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The Multi Strategy Trading Robot This automated trading robot always uses stop loss. Big Hunter is specially designed to trade gold , but you can test it on other pairs since you have the access to the parameters. The robot uses different strategies like swing trading ,  momentum trading , position trading and more. It's backtested for the last 10 years under the harshest, simulated market conditions. Each trade has  unique SL, TP, Trailing stop, and breakeven. These parameters are variabl
Trading robot Sniper (Sniper). Die in der Arbeit der 7 Trading-Indikatoren und eine Vielzahl von verschiedenen Mechanismen, die Trading-Prozess! Alle verwendeten Signal-Indikatoren bekannt ist Parabolic SAR, MACD, MA, Envelopes, CCI, RVI, Alligator ! Berater ständig analysiert und unter Kontrolle hält jede Marktsituation. Konzipiert für den vollständig automatisierten Handel! Jeder Auftrag unterstützt Dual sichere Netz mit sehr glatten Martingal. Um Risiken zu reduzieren, versuchen Sie nicht set
Smart Advisor Calculation is designed for a very interesting method that is able finally to give the martingale a new positive way! At startup the Expert Advisor sets virtual orders and trades like the real deal. As soon as the drawdown of virtual orders reaches the set number, the robot immediately enters the market for real orders! Thus the price is going without setbacks such as 30-70 pips, with great probability will kick back at the entrance to the market! This is used by a robot! If the pr
Octopus Stability
Aleksandr Shurgin
After a thorough work and search for the optimal values of each of the Expert Advisor's parameters, the most stable settings of the algorithms have been selected, which do not require over large history periods. The robot uses a universal trading strategy, allowing the use of the currency pairs EURUSD, GBPUSD, USDCHF, USDJPY and other pairs with low spread. The EA trades on a 5-minute timeframe , it uses levels defined automatically on the bases of multiple parallel price movement calculation me
Forebot
Marek Kvarda
This robot uses a custom hidden oscillating indicator and also analyzes the market response. It traded mostly at the time of higher volatility. It works with several pending orders with different size of volume and their position actively modifies. It uses advanced money management. TradingMode setting can also meet the conditions FIFO. It is successful in different markets and different timeframes. Best results are achieves with a broker with the spread to 5 points on EURUSD. Is necessary a b
Avato
Nikolaos Bekos
The Avato is one of our standalone tools. (A Signal based on it will also be provided on Mt4 Market in the future). It is designed around a combined form of hedging and martingale techniques and uses sophisticated algorithms and filters to place the trades. It uses Stop loss and Take profit levels while Lot size is calculated automatically following the according multiplier settings. We consider it a toolbox for every seasoned trader. Made with Gold market in mind, it can be tested in other inst
AreaFiftyOne
Valeri Balachnin
Area 51 EA generiert Signale für verschiedene Strategien. Hat verschiedene Money-Management-Strategien und dynamische Losgrößenfunktion. Wenn eine Position eröffnet wird, ist sie mit einem Take Profit und einem Stop Loss ausgestattet. Wenn die Position rentabel wird, wird ein dynamischer Stop-Loss basierend auf den angegebenen Werten (TrailingStep und DistanceStep) festgelegt und ständig nachgeführt. Auf diese Weise können Sie immer Positionen mit Gewinn schließen. Wenn Sie möchten, dass Ihre ma
Note : the spread value,  the broker's slippage and the VPS speed affect the Expert Advisor trading results. Recommendations: gold with spread up to 3, USDJPY with spread up to 1.7, EURUSD with spread up to 1.5. Results will be better with better conditions. The Ping value between VPS and the broker server should be below 10 ms. In addition, the smaller the broker's stop-level requirement, the better; 0 is the best. The Expert Advisor is based on a breakthrough system and carefully controls all
Milch Cow Extra
Mohamed Nasseem
EA is primarily a Hedging and Multiples Strategy. It support to seize every opportunity in any direction as MILCH COW MIX but with multiple profit results without increasing the risk. Milch Cow Mix EA starts to open Hedge at first level only But EA opens Hedge at every level Not just opens the deals, but chooses the right time to close the open positions to begin trading again. We recommend the use of an expert with a pair of high volatility for the currency, such as GBPAUD, AUDCAD Experts inter
Milch Cow Turbo
Mohamed Nasseem
MILCH COW Turbo EA is primarily a multi-currency strategy. It supports 9 or 10 pairs as collection of currencies (GBPJPY, GBPUSD, EURCHF,EURGBP, EURJPY, EURUSD, USDCAD, USDCHF, USDJPY). If you choose Trade_Calc = false, only one pair is turned on. The EA depends on a special indicator to set Buy stop, Buy limit, Sell stop and Sell limit orders Note: If enabled Pendingorders = false, the EA will use the prices shown on the chart in live orders (buy and sell). In this case, the EA uses stop loss a
News Hedging Pro  is a unique robot that allows you to trade during the most critical news announcement periods by your predefined strategy. You can preset the strategy to trade, and then it will trade that news automatically when the news comes. News release gives opportunity to have pips since the price usually has big move at that time. Now with this tool, trading news become easier, more flexible and more exciting than ever. No waiting, no confusing anymore. Product Links Fully  Descripti
Weitere Produkte dieses Autors
Trading Signal: High Risk :  Click Here   Low Risk :  Click Here Rental and Pricing: The current price of the Orion is $600 USD. Soon, the price will increase to $5,600 USD, so take advantage of the current pricing while it lasts. Orion Intelligence System Overview: The Orion Intelligence System integrates multiple indicators and semi-AI technology for automated trading. It identifies harmonic patterns , support, and resistance levels to determine trade execution, utilizing a martingale
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Version 4.0 2024.08.12
What's new:

double RSI_m5 = iRSI(Symbol(), 5, RSI_Period, PRICE_CLOSE, 0);
double RSI_m15 = iRSI(Symbol(), 15, RSI_Period, PRICE_CLOSE, 0);
double RSI_m30 = iRSI(Symbol(), 30, RSI_Period, PRICE_CLOSE, 0);

RSI_m5 = NormalizeDouble(RSI_m5, 2);
RSI_m15 = NormalizeDouble(RSI_m15, 2);
RSI_m30 = NormalizeDouble(RSI_m30, 2);

bool isOverbought = RSI_m5 > 70 && RSI_m15 > 70 && RSI_m30 > 70;
bool isOversold = RSI_m5 < 30 && RSI_m15 < 30 && RSI_m30 < 30;

if (isOverbought) {
Global_22_a_168_ko[Para_0_in].bo_6 = true;
} else if (isOversold) {
Global_22_a_168_ko[Para_0_in].bo_5 = true;
} else {
Global_22_a_168_ko[Para_0_in].bo_5 = false;
Global_22_a_168_ko[Para_0_in].bo_6 = false;
}

Global_22_a_168_ko[Para_0_in].bo_5 &= Global_22_a_168_ko[Para_0_in].do_9 < Local_49_do && Local_49_do > 0.0;
Global_22_a_168_ko[Para_0_in].bo_6 &= Global_22_a_168_ko[Para_0_in].do_9 > Local_48_do && Local_48_do > 0.0;
tmp_in_10 = 0;
Version 3.7 2024.08.10
What's new:

double RSI_m5 = iRSI(Symbol(), 5, RSI_Period, PRICE_CLOSE, 0);
double RSI_m15 = iRSI(Symbol(), 15, RSI_Period, PRICE_CLOSE, 0);
double RSI_m30 = iRSI(Symbol(), 30, RSI_Period, PRICE_CLOSE, 0);

RSI_m5 = NormalizeDouble(RSI_m5, 2);
RSI_m15 = NormalizeDouble(RSI_m15, 2);
RSI_m30 = NormalizeDouble(RSI_m30, 2);

bool isOverbought = RSI_m5 > 70 && RSI_m15 > 70 && RSI_m30 > 70;
bool isOversold = RSI_m5 < 30 && RSI_m15 < 30 && RSI_m30 < 30;

if (isOverbought) {
Global_22_a_168_ko[Para_0_in].bo_6 = true;
} else if (isOversold) {
Global_22_a_168_ko[Para_0_in].bo_5 = true;
} else {
Global_22_a_168_ko[Para_0_in].bo_5 = false;
Global_22_a_168_ko[Para_0_in].bo_6 = false;
}

Global_22_a_168_ko[Para_0_in].bo_5 &= Global_22_a_168_ko[Para_0_in].do_9 < Local_49_do && Local_49_do > 0.0;
Global_22_a_168_ko[Para_0_in].bo_6 &= Global_22_a_168_ko[Para_0_in].do_9 > Local_48_do && Local_48_do > 0.0;
tmp_in_10 = 0;
Version 3.6 2024.08.09
What's new:

double RSI_m5 = iRSI(Symbol(), 5, RSI_Period, PRICE_CLOSE, 0);
double RSI_m15 = iRSI(Symbol(), 15, RSI_Period, PRICE_CLOSE, 0);
double RSI_m30 = iRSI(Symbol(), 30, RSI_Period, PRICE_CLOSE, 0);

RSI_m5 = NormalizeDouble(RSI_m5, 2);
RSI_m15 = NormalizeDouble(RSI_m15, 2);
RSI_m30 = NormalizeDouble(RSI_m30, 2);

bool isOverbought = RSI_m5 > 70 && RSI_m15 > 70 && RSI_m30 > 70;
bool isOversold = RSI_m5 < 30 && RSI_m15 < 30 && RSI_m30 < 30;

if (isOverbought) {
Global_22_a_168_ko[Para_0_in].bo_6 = true;
} else if (isOversold) {
Global_22_a_168_ko[Para_0_in].bo_5 = true;
} else {
Global_22_a_168_ko[Para_0_in].bo_5 = false;
Global_22_a_168_ko[Para_0_in].bo_6 = false;
}

Global_22_a_168_ko[Para_0_in].bo_5 &= Global_22_a_168_ko[Para_0_in].do_9 < Local_49_do && Local_49_do > 0.0;
Global_22_a_168_ko[Para_0_in].bo_6 &= Global_22_a_168_ko[Para_0_in].do_9 > Local_48_do && Local_48_do > 0.0;
tmp_in_10 = 0;
Version 3.5 2024.07.31
What's new:

double RSI_m5 = iRSI(Symbol(), 5, RSI_Period, PRICE_CLOSE, 0);
double RSI_m15 = iRSI(Symbol(), 15, RSI_Period, PRICE_CLOSE, 0);
double RSI_m30 = iRSI(Symbol(), 30, RSI_Period, PRICE_CLOSE, 0);

RSI_m5 = NormalizeDouble(RSI_m5, 2);
RSI_m15 = NormalizeDouble(RSI_m15, 2);
RSI_m30 = NormalizeDouble(RSI_m30, 2);

bool isOverbought = RSI_m5 > 70 && RSI_m15 > 70 && RSI_m30 > 70;
bool isOversold = RSI_m5 < 30 && RSI_m15 < 30 && RSI_m30 < 30;

if (isOverbought) {
Global_22_a_168_ko[Para_0_in].bo_6 = true;
} else if (isOversold) {
Global_22_a_168_ko[Para_0_in].bo_5 = true;
} else {
Global_22_a_168_ko[Para_0_in].bo_5 = false;
Global_22_a_168_ko[Para_0_in].bo_6 = false;
}

Global_22_a_168_ko[Para_0_in].bo_5 &= Global_22_a_168_ko[Para_0_in].do_9 < Local_49_do && Local_49_do > 0.0;
Global_22_a_168_ko[Para_0_in].bo_6 &= Global_22_a_168_ko[Para_0_in].do_9 > Local_48_do && Local_48_do > 0.0;
tmp_in_10 = 0;
Version 3.0 2024.07.25
What's new:

double RSI_m5 = iRSI(Symbol(), 5, RSI_Period, PRICE_CLOSE, 0);
double RSI_m15 = iRSI(Symbol(), 15, RSI_Period, PRICE_CLOSE, 0);
double RSI_m30 = iRSI(Symbol(), 30, RSI_Period, PRICE_CLOSE, 0);

RSI_m5 = NormalizeDouble(RSI_m5, 2);
RSI_m15 = NormalizeDouble(RSI_m15, 2);
RSI_m30 = NormalizeDouble(RSI_m30, 2);

bool isOverbought = RSI_m5 > 70 && RSI_m15 > 70 && RSI_m30 > 70;
bool isOversold = RSI_m5 < 30 && RSI_m15 < 30 && RSI_m30 < 30;

if (isOverbought) {
Global_22_a_168_ko[Para_0_in].bo_6 = true;
} else if (isOversold) {
Global_22_a_168_ko[Para_0_in].bo_5 = true;
} else {
Global_22_a_168_ko[Para_0_in].bo_5 = false;
Global_22_a_168_ko[Para_0_in].bo_6 = false;
}

Global_22_a_168_ko[Para_0_in].bo_5 &= Global_22_a_168_ko[Para_0_in].do_9 < Local_49_do && Local_49_do > 0.0;
Global_22_a_168_ko[Para_0_in].bo_6 &= Global_22_a_168_ko[Para_0_in].do_9 > Local_48_do && Local_48_do > 0.0;
tmp_in_10 = 0;
Version 2.6 2024.07.01
What's new:

double RSI_m5 = iRSI(Symbol(), 5, RSI_Period, PRICE_CLOSE, 0);
double RSI_m15 = iRSI(Symbol(), 15, RSI_Period, PRICE_CLOSE, 0);
double RSI_m30 = iRSI(Symbol(), 30, RSI_Period, PRICE_CLOSE, 0);

RSI_m5 = NormalizeDouble(RSI_m5, 2);
RSI_m15 = NormalizeDouble(RSI_m15, 2);
RSI_m30 = NormalizeDouble(RSI_m30, 2);

bool isOverbought = RSI_m5 > 70 && RSI_m15 > 70 && RSI_m30 > 70;
bool isOversold = RSI_m5 < 30 && RSI_m15 < 30 && RSI_m30 < 30;

if (isOverbought) {
Global_22_a_168_ko[Para_0_in].bo_6 = true;
} else if (isOversold) {
Global_22_a_168_ko[Para_0_in].bo_5 = true;
} else {
Global_22_a_168_ko[Para_0_in].bo_5 = false;
Global_22_a_168_ko[Para_0_in].bo_6 = false;
}

Global_22_a_168_ko[Para_0_in].bo_5 &= Global_22_a_168_ko[Para_0_in].do_9 < Local_49_do && Local_49_do > 0.0;
Global_22_a_168_ko[Para_0_in].bo_6 &= Global_22_a_168_ko[Para_0_in].do_9 > Local_48_do && Local_48_do > 0.0;
tmp_in_10 = 0;
Version 2.5 2024.06.05
What's new:

double RSI_m5 = iRSI(Symbol(), 5, RSI_Period, PRICE_CLOSE, 0);
double RSI_m15 = iRSI(Symbol(), 15, RSI_Period, PRICE_CLOSE, 0);
double RSI_m30 = iRSI(Symbol(), 30, RSI_Period, PRICE_CLOSE, 0);

RSI_m5 = NormalizeDouble(RSI_m5, 2);
RSI_m15 = NormalizeDouble(RSI_m15, 2);
RSI_m30 = NormalizeDouble(RSI_m30, 2);

bool isOverbought = RSI_m5 > 70 && RSI_m15 > 70 && RSI_m30 > 70;
bool isOversold = RSI_m5 < 30 && RSI_m15 < 30 && RSI_m30 < 30;

if (isOverbought) {
Global_22_a_168_ko[Para_0_in].bo_6 = true;
} else if (isOversold) {
Global_22_a_168_ko[Para_0_in].bo_5 = true;
} else {
Global_22_a_168_ko[Para_0_in].bo_5 = false;
Global_22_a_168_ko[Para_0_in].bo_6 = false;
}

Global_22_a_168_ko[Para_0_in].bo_5 &= Global_22_a_168_ko[Para_0_in].do_9 < Local_49_do && Local_49_do > 0.0;
Global_22_a_168_ko[Para_0_in].bo_6 &= Global_22_a_168_ko[Para_0_in].do_9 > Local_48_do && Local_48_do > 0.0;
tmp_in_10 = 0;
Version 2.4 2024.03.10
double RSI_m5 = iRSI(Symbol(), 5, RSI_Period, PRICE_CLOSE, 0);
double RSI_m15 = iRSI(Symbol(), 15, RSI_Period, PRICE_CLOSE, 0);
double RSI_m30 = iRSI(Symbol(), 30, RSI_Period, PRICE_CLOSE, 0);

RSI_m5 = NormalizeDouble(RSI_m5, 2);
RSI_m15 = NormalizeDouble(RSI_m15, 2);
RSI_m30 = NormalizeDouble(RSI_m30, 2);

bool isOverbought = RSI_m5 > 70 && RSI_m15 > 70 && RSI_m30 > 70;
bool isOversold = RSI_m5 < 30 && RSI_m15 < 30 && RSI_m30 < 30;

if (isOverbought) {
Global_22_a_168_ko[Para_0_in].bo_6 = true;
} else if (isOversold) {
Global_22_a_168_ko[Para_0_in].bo_5 = true;
} else {
Global_22_a_168_ko[Para_0_in].bo_5 = false;
Global_22_a_168_ko[Para_0_in].bo_6 = false;
}

Global_22_a_168_ko[Para_0_in].bo_5 &= Global_22_a_168_ko[Para_0_in].do_9 < Local_49_do && Local_49_do > 0.0;
Global_22_a_168_ko[Para_0_in].bo_6 &= Global_22_a_168_ko[Para_0_in].do_9 > Local_48_do && Local_48_do > 0.0;
tmp_in_10 = 0;
Version 2.3 2024.03.03
Version 2.3 Fixed

-No errors and Warnings
Version 2.2 2024.02.17
Version 2.2 Fixed

-No errors and Warnings
Version 2.1 2024.02.09
Version 2.1 Fixed and is Mandatory.
Version 2.0 2024.01.31
Version 2.0 Fixed and is Mandatory.
Version 1.9 2024.01.31
Version 1.9 Fixed and is Mandatory.
Version 1.8 2024.01.31
Version 1.8 Fixed and is Mandatory.
Version 1.7 2024.01.28
Version 1.7 Fixed and is Mandatory.
Version 1.6 2024.01.27
Version 1.6 Fixed and is Mandatory.
Version 1.5 2024.01.26
Version 1.5 Fixed and is Mandatory.
Version 1.4 2024.01.25
Version 1.4 Fixed
Version 1.3 2024.01.24
Version 1.3 Fixed
Version 1.2 2024.01.09
Version 1.2 Fixed
Version 1.1 2023.12.30
Version 1.1 Fixed