
Ini adalah strategi perdagangan berdasarkan SMA (rata-rata bergerak sederhana) yang menganalisis kenaikan dan penurunan dalam tempoh setahun. Strategi ini mengenal pasti isyarat perdagangan yang berpotensi dengan mengira purata bergerak perbezaan jumlah pembelian dan membandingkannya dengan penurunan dan penurunan sejarah. Strategi ini menggunakan tempoh pengulangan yang panjang dan sesuai untuk perdagangan trend jangka panjang.
Logik teras strategi adalah berdasarkan langkah utama berikut:
Ini adalah strategi pengesanan trend jangka menengah dan jangka panjang berdasarkan analisis kuantiti transaksi, untuk menangkap trend pasaran dengan menganalisis perbezaan nilai pembelian dan penjualan. Reka bentuk strategi adalah masuk akal, risiko terkawal, tetapi perlu memperhatikan kesesuaian dan pengoptimuman parameter persekitaran pasaran. Dengan arah pengoptimuman yang dikemukakan, strategi masih mempunyai ruang untuk meningkatkan lagi.
/*backtest
start: 2024-02-20 00:00:00
end: 2025-02-17 08:00:00
period: 2h
basePeriod: 2h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=5
strategy("Delta SMA 1-Year High/Low Strategy", overlay = false, margin_long = 100, margin_short = 100)
// Inputs
delta_sma_length = input.int(14, title="Delta SMA Length", minval=1) // SMA length for Delta
lookback_days = 365 // Lookback period fixed to 1 year
// Function to calculate buy and sell volume
buy_volume = close > open ? volume : na
sell_volume = close < open ? volume : na
// Calculate the Delta
delta = nz(buy_volume, 0) - nz(sell_volume, 0)
// Calculate Delta SMA
delta_sma = ta.sma(delta, delta_sma_length)
// Lookback period in bars (1 bar = 1 day)
desired_lookback_bars = lookback_days
// Ensure lookback doesn't exceed available historical data
max_lookback_bars = math.min(desired_lookback_bars, 365) // Cap at 365 bars (1 year)
// Calculate Delta SMA low and high within the valid lookback period
delta_sma_low_1yr = ta.lowest(delta_sma, max_lookback_bars)
delta_sma_high_1yr = ta.highest(delta_sma, max_lookback_bars)
// Define thresholds for buy and sell conditions
very_low_threshold = delta_sma_low_1yr * 0.7
above_70_threshold = delta_sma_high_1yr * 0.9
below_60_threshold = delta_sma_high_1yr * 0.5
// Track if `delta_sma` was very low and persist the state
var bool was_very_low = false
if delta_sma < very_low_threshold
was_very_low := true
if ta.crossover(delta_sma, 10000)
was_very_low := false // Reset after crossing 0
// Track if `delta_sma` crossed above 70% of the high
var bool crossed_above_70 = false
if ta.crossover(delta_sma, above_70_threshold)
crossed_above_70 := true
if delta_sma < below_60_threshold*0.5 and crossed_above_70
crossed_above_70 := false // Reset after triggering sell
// Buy condition: `delta_sma` was very low and now crosses 0
buy_condition = was_very_low and ta.crossover(delta_sma, 0)
// Sell condition: `delta_sma` crossed above 70% of the high and now drops below 60%
sell_condition = crossed_above_70 and delta_sma < below_60_threshold
// Place a long order when buy condition is met
if buy_condition
strategy.entry("Buy", strategy.long)
// Place a short order when sell condition is met
if sell_condition
strategy.close("Buy")
// Plot Delta SMA and thresholds for visualization
plot(delta_sma, color=color.blue, title="Delta SMA")
plot(very_low_threshold, color=color.green, title="70% of 1-Year Delta SMA Low", linewidth=2)
plot(above_70_threshold, color=color.purple, title="70% of 1-Year Delta SMA High", linewidth=2)
plot(below_60_threshold, color=color.red, title="60% of 1-Year Delta SMA High", linewidth=2)
// Optional: Plot Buy and Sell signals on the chart
//plotshape(series=buy_condition, title="Buy Signal", location=location.belowbar, color=color.new(color.green, 0), style=shape.labelup, text="BUY")
//plotshape(series=sell_condition, title="Sell Signal", location=location.abovebar, color=color.new(color.red, 0), style=shape.labeldown, text="SELL")