ianzeng123
🤖 这不是普通的定投，这是会思考的定投机器人！
你知道吗？大部分人做定投都是”无脑买买买”，但这个策略就像给你配了个超级聪明的投资助手！它会根据市场情况调整每次买入的金额，从初始的5%逐步递增到最高100%。就像你去菜市场买菜，便宜的时候多买点，贵的时候少买点，简单粗暴但超级有效！
📊 四大技术指标组合拳，市场趋势一目了然
划重点！这个策略用了四个技术指标的组合： - 快慢EMA均线：像市场的”心电图”，告诉你趋势方向 - MACD：市场动量的”晴雨表”，判断买卖时机 - RSI：超买超卖的”温度计”，避免追高杀跌 - 布林带：价格波动的”安全区域”，判断支撑阻力
这四个指标配合起来，就像组了个”复仇者联盟”，各司其职但配合默契！
💡 越跌越买的智能加仓逻辑
避坑指南！普通定投最大的问题是不会控制仓位，这个策略就聪明多了： - 首次买入用5%的资金试水 - 每次加仓增加2.5%的投入 - 价格跌得越多，加仓间隔越大（2%、6%、10%…） - 最多单次投入不超过总资金的100%
就像打游戏升级一样，越到后面投入越大，但风险控制得死死的！
🎯 聪明的止盈止损，让利润奔跑让亏损止步
这个策略的卖出逻辑超级人性化： - 最低2%利润才考虑卖出：不做”辛苦一场白忙活”的冤大头 - 趋势转弱及时止盈：见好就收，落袋为安 - 价格大跌2%触发卖出：保护利润不回吐 - 可设置止损线：虽然默认100%（基本不触发），但你可以根据风险承受能力调整
简单来说，这个策略就是”会赚钱的时候绝不手软，该跑路的时候绝不恋战”！
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🤖 This Isn’t Ordinary DCA - It’s a Thinking DCA Robot!
You know what? Most people do dollar-cost averaging like mindless “buy-buy-buy” machines, but this strategy is like having a super-smart investment assistant! It adjusts the purchase amount based on market conditions, starting from 5% and gradually increasing up to 100%. It’s like shopping at a farmers market - buy more when it’s cheap, buy less when it’s expensive. Simple, brutal, but incredibly effective!
📊 Four Technical Indicators Working as a Team
Key point! This strategy uses a combination of four technical indicators: - Fast/Slow EMA: Like the market’s “heartbeat monitor,” showing trend direction - MACD: The market momentum “barometer” for timing entries and exits - RSI: The overbought/oversold “thermometer” to avoid chasing highs and selling lows - Bollinger Bands: Price volatility “safety zones” for support and resistance
These four indicators work together like assembling the “Avengers” - each has their role but they coordinate perfectly!
💡 Smart Pyramiding Logic: Buy More as It Drops
Pitfall alert! The biggest problem with regular DCA is poor position sizing control. This strategy is much smarter: - Initial purchase uses 5% of capital to test the waters - Each additional purchase increases by 2.5% - The more price drops, the larger the spacing between purchases (2%, 6%, 10%…) - Maximum single investment never exceeds 100% of total capital
It’s like leveling up in a video game - the investment gets bigger as you progress, but risk is tightly controlled!
🎯 Smart Take-Profit and Stop-Loss: Let Profits Run, Cut Losses Short
This strategy’s exit logic is super user-friendly: - Minimum 2% profit before considering sale: No more “working hard for nothing” - Exit when trend weakens: Take profits while you can, secure the gains - 2% price drop triggers sell signal: Protect profits from giving back - Configurable stop-loss: Though default is 100% (basically never triggered), you can adjust based on risk tolerance
Simply put, this strategy is “ruthless when making money, decisive when it’s time to run”!
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// This Pine Script™ code is subject to the terms of the MPL 2.0 at https://mozilla.org/MPL/2.0/
// © MTB by Neurodoc
// By Nicolás Astorga
//@version=5
strategy("Master Trading Bot by Neurodoc",
shorttitle="MTB Adaptation",
overlay=true,
initial_capital=10000,
pyramiding=100,
commission_value=0.1,
commission_type=strategy.commission.percent,
default_qty_type = strategy.cash)
// —————— CONFIGURATION (Based on ve.env) ——————
// Purchase and DCA Percentages
var GRP_DCA = "DCA Configuration"
start_percentage = input.float(5.0, "Initial Buy Percentage (%)", group=GRP_DCA)
increment_percentage = input.float(2.5, "DCA Increment per Buy (%)", group=GRP_DCA)
max_percentage = input.float(100.0, "Maximum Buy Percentage (%)", group=GRP_DCA)
min_profit_percent = input.float(2.0, "Minimum Profit Percentage for Sell (%)", group=GRP_DCA)
// Stop Loss and Drop Signal
var GRP_RISK = "Risk Management"
stop_loss_percent = input.float(100.0, "Stop Loss (%)", group=GRP_RISK, tooltip="A value of 100 means there is effectively no stop loss, as the price would have to go to zero.")
drop_percent_signal = input.float(2.0, "Price Drop Signal (%)", group=GRP_RISK)
// Indicator Parameters
var GRP_INDICATORS = "Indicator Parameters"
ema_fast_period = input.int(3, "Fast EMA", group=GRP_INDICATORS)
ema_mid_period = input.int(7, "Medium EMA", group=GRP_INDICATORS)
ema_slow_period = input.int(18, "Slow EMA", group=GRP_INDICATORS)
bb_length = input.int(20, "Bollinger Bands Length", group=GRP_INDICATORS)
bb_stddev = input.float(2.0, "Bollinger Bands Std Dev", group=GRP_INDICATORS)
macd_fast = input.int(52, "MACD Fast", group=GRP_INDICATORS)
macd_slow = input.int(200, "MACD Slow", group=GRP_INDICATORS)
macd_signal = input.int(3, "MACD Signal", group=GRP_INDICATORS)
rsi_length = input.int(14, "RSI Length", group=GRP_INDICATORS)
rsi_oversold_threshold = input.int(25, "RSI Oversold (for divergence)", group=GRP_INDICATORS)
// —————— INDICATOR CALCULATIONS ——————
// EMAs
ema_fast = ta.ema(open, ema_fast_period)
ema_mid = ta.ema(open, ema_mid_period)
ema_slow = ta.ema(open, ema_slow_period)
// Bollinger Bands
[bb_middle, bb_upper, bb_lower] = ta.bb(close, bb_length, bb_stddev)
bb_width = (bb_upper - bb_lower) / bb_middle * 100
is_bb_expanding = bb_width > bb_width[1]
// MACD
[macd_line, signal_line, _] = ta.macd(close, macd_fast, macd_slow, macd_signal)
// RSI
rsi = ta.rsi(close, rsi_length)
// Price drop signal from recent highest price (equivalent to `cummax` in Python)
highest_price = ta.highest(high, 500) // 500-bar lookback as an approximation of all-time high
price_drop_percent = ((highest_price - close) / highest_price) * 100
is_price_drop_signal = price_drop_percent >= drop_percent_signal
// —————— TRADING LOGIC ——————
// Trend Conditions
is_bullish = ema_fast > ema_slow and macd_line > signal_line and close > bb_middle
is_bearish = ema_fast < ema_slow and macd_line < signal_line and close < bb_middle
is_weakening = rsi < rsi[1]
// Strategy state variables
var bool just_sold = false
var int dca_step = 0
// Determine the capital percentage for the next buy
dca_buy_percentage = start_percentage + (dca_step * increment_percentage)
if dca_buy_percentage > max_percentage
dca_buy_percentage := max_percentage
avg_buy_price = strategy.position_avg_price
// Long Entry Condition
// Initial Buy (no open position)
long_signal_initial = strategy.position_size == 0 and is_bullish and macd_line > signal_line and rsi < 65
// DCA (if already in position)
price_drop_from_avg = ((avg_buy_price - close) / avg_buy_price) * 100
dca_required_drop = 2.0 + (dca_step * 4.0) // Logic equivalent to DCA_PRICE_DROP_START and INCREMENT
long_signal_dca = strategy.position_size > 0 and is_bearish and close < avg_buy_price and price_drop_from_avg >= dca_required_drop
// Manage `just_sold` state
if strategy.position_size > 0
just_sold := false
if strategy.position_size == 0 and strategy.position_size[1] > 0
just_sold := true
// Avoid immediate rebuying after selling unless strong bullish condition
long_signal = (just_sold and is_bullish) ? long_signal_initial : (not just_sold ? (long_signal_initial or long_signal_dca) : false)
// Sell/Close Condition
current_profit_percent = ((close - avg_buy_price) / avg_buy_price) * 100
has_min_profit = current_profit_percent >= min_profit_percent
stop_loss_price = avg_buy_price * (1 - stop_loss_percent / 100)
is_stoploss_triggered = close <= stop_loss_price
short_signal = strategy.position_size > 0 and has_min_profit and ((is_bearish and is_weakening) or is_price_drop_signal or is_stoploss_triggered or (macd_line < signal_line))
// —————— ORDER EXECUTION ——————
if (long_signal)
// Calculate how much money (e.g., USDT) to invest in this trade
cash_to_invest = (strategy.equity * dca_buy_percentage / 100) / close
strategy.entry("Buy", strategy.long, qty=cash_to_invest) // "qty" represents a cash-based position
dca_step := dca_step + 1
if (short_signal)
strategy.close_all(comment="Sell")
dca_step := 0 // Reset DCA counter upon selling
// —————— CHART VISUALIZATION ——————
// Background color by trend
bgcolor(is_bullish ? color.new(color.green, 90) : is_bearish ? color.new(color.red, 90) : na)
// Plot EMAs and Bollinger Bands
plot(ema_fast, "Fast EMA", color.blue)
plot(ema_slow, "Slow EMA", color.orange)
p1 = plot(bb_upper, "Upper BB", color=color.gray)
p2 = plot(bb_lower, "Lower BB", color=color.gray)
fill(p1, p2, color=color.new(color.gray, 90))
// Plot average buy price if position is open
plot(strategy.position_size > 0 ? avg_buy_price : na, "Average Buy Price", color.yellow, style=plot.style_linebr, linewidth=2)
// Plot take-profit target
plot(strategy.position_size > 0 ? avg_buy_price * (1 + min_profit_percent / 100) : na, "Sell Target (TP)", color.aqua, style=plot.style_linebr, linewidth=2)
// Plot stop loss level
plot(strategy.position_size > 0 ? stop_loss_price : na, "Stop Loss", color.fuchsia, style=plot.style_linebr, linewidth=2)