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Ethereum Algotrader
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1. Description ⚠️ Please read the following CAREFULLY before investing money in my strategy (especially the [Risks](https://app.binance.com/uni-qr/cpos/8453380496338?l=en&r=241478881&uc=web_square_share_link&uco=MRgaMKoSdObaFbd7mSwlvA&us=copylink) section) ⚠️ I'm trading with crypto robot on Binance futures. It has the following properties: 🔵 Trend following system that trades #ETHUSDT in whatever direction the price goes. 🔵 Independent from market direction, bull or bear. I make money when crypto goes to the moon. I make the same money when crypto is falling like a stone. 🔵 No grid, no martingale, not holding loss positions for a long time. 🔵 Each deal has a short stop loss —> no chance of losing all at once. 🔵 Uses trailing SL to maximize profit from big trends. 🔵 Shows stable historical results during both bull and bear crypto trends, high and low volatility, from 2018 to 2024 (see the [Test results](https://www.binance.com/en/square/post/8762850482417) section). 🔵 Shows historical performance (rec.factor=29.5 with a fix.lot) compared to the best grid systems without dangerous trading methods (see the [Test results](https://www.binance.com/en/square/post/8762850482417) section). 🔵 Demonstrates live performance similar to test results (see Monitoring). 💻 Historical result: from 8000$ to 1 804 594$ with 18% drawdown within 6 years. 💰 Current live result: 125% ROI with 22% max drawdown within 88 days (risk mode is higher than in history tests). #COPYTRADING #algotrading #RiskManagement

1. Description

⚠️ Please read the following CAREFULLY before investing

money in my strategy (especially the Risks section) ⚠️

I'm trading with crypto robot on Binance futures. It has the following properties:

🔵 Trend following system that trades #ETHUSDT in whatever direction the price goes.

🔵 Independent from market direction, bull or bear. I make money when crypto goes to the moon. I make the same money when crypto is falling like a stone.

🔵 No grid, no martingale, not holding loss positions for a long time.

🔵 Each deal has a short stop loss —> no chance of losing all at once.

🔵 Uses trailing SL to maximize profit from big trends.

🔵 Shows stable historical results during both bull and bear crypto trends, high and low volatility, from 2018 to 2024 (see the Test results section).

🔵 Shows historical performance (rec.factor=29.5 with a fix.lot) compared to the best grid systems without dangerous trading methods (see the Test results section).

🔵 Demonstrates live performance similar to test results (see Monitoring).

💻 Historical result: from 8000$ to 1 804 594$ with 18% drawdown within 6 years.

💰 Current live result: 125% ROI with 22% max drawdown within 88 days (risk mode is higher than in history tests).

#COPYTRADING #algotrading #RiskManagement

Algo_Hedge
1 / 200
7D PNL
-1243.94
7D ROI
-17.29%
AUM
$14150.77
MDD
17.96%
Win Rate
10
Copy trading is high risk. Be careful and see Risk Warning.
Disclaimer: Includes thrid-party opinions. No financial advice. May include sponsored content. See T&Cs.
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5. Risks ⚠️ Please read the following CAREFULLY before investing money in my strategy (especially the Risks section - that's why we start from it) ⚠️ All historical tests were done with the risk 0.5 lots for every 1000 of balance (fix.lot=4). A more aggressive option is now being used in trading. It trades from 0.6 to 1 lot for every 1000 of balance. But the lot is increased only in drawdowns which decreases risk significantly. (technical information, not crucial) If you use absolutely passive investing strategy and enter the trading at the high of the profit curve your risk in the case of repeat of the maximal historical drawdown is ❗️55%❗️of your deposit (but this drawdown can be exceeded; there are 5 drawdowns of the similar size within 6 years of history). That's why I highly recommend using partial investing strategy. 🟣 Conservative strategy (the one that I use) 🟣 Divide your bot budget into 3 equal parts: ➡️Deposit 1st part immediately. ➡️Deposit 2nd part when the drawdown on my deposit will reach 800$ (see screenshot below how to find it on Monitoring). ➡️Deposit 3rd part when the drawdown on my deposit will reach 2440$. In this case repeat of the maximal historical drawdown will result in a ❗️43%❗️ drawdown on your account. Your account will recover faster. 🔴 Aggressive strategy 🔴 Divide your bot budget into 2 equal parts: ➡️Deposit 1st part immediately. ➡️Deposit 2nd part when the drawdown on my deposit will reach 800$ (see screenshot below how to find it on Monitoring. In this case repeat of the maximal historical drawdown will result in a ❗️51%❗️ drawdown on your account. Your account will recover faster. (see drawdowns($) in 6 years (blue line is month number) for the lead trader account below) #COPYTRADING #RiskManagement #algotrading #InvestingSafety #BuytheDips
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3. My algorithm ⚠️ Please read the following CAREFULLY before investing money in my strategy (especially the Risks section) ⚠️ Main properties of the expert: 🟢 Trend following system on $ETHUSDT futures. 🟢 No grid, no martingale, not holding loss positions for a long time. 🟢 Trades only 1 deal at a time. Next deal can be opened only after the 1st one was closed. 🟢 Each deal has a fixed SL that can only be shortened. 🟢 Uses trailing SL to maximize profit from big trends. ➡️ On the one hand, it uses some adaptive conditions to enter the trend with a relatively short SL, follow that trend with trailing SL and exit or reverse at the end of the trend. These conditions adapt to the market situation. ➡️ On the other, it has some filters to avoid multiple losses during the flat phase, which were tuned based on my original technique that I call "an optimization without optimization". It was inspired by several research articles ([1], [2], [3]) where I found the answer why most of the optimization techniques used in algotrading are fail. This approach allows to reduce an overfitting to minimum. Examples of deals: see screenshot. References: [1] D. Bailey, J. Borwein, M. López de Prado and J. Zhu, The probability of backtest overfitting, 2013, working paper. [2] D. Bailey and M. López de Prado, The Sharpe ratio efficient frontier, Journal of Risk 15(2) (2012), 3–44. [3] Bailey, D., J. Borwein, M. L´opez de Prado and J. Zhu, “Pseudo-mathematics and financial charlatanism: The effects of backtest over fitting on out-of-sample performance,” Notices of the AMS, 61 May (2014), 458–471. #COPYTRADING #ethereum #algotrading #InvestingSafety #RiskManagement
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