OPEN-SOURCE SCRIPT
Institutional Risk Engine v3

//version=6
strategy(
"Institutional Risk Engine v3",
overlay=true,
initial_capital=100000,
pyramiding=0,
default_qty_type=strategy.percent_of_equity,
default_qty_value=10,
calc_on_order_fills=true)
// ==========================================================
// 1️⃣ MULTI-ASSET DATA
// ==========================================================
btc = request.security("BINANCE:BTCUSDT", timeframe.period, close)
eth = request.security("BINANCE:ETHUSDT", timeframe.period, close)
es = request.security("CME_MINI:ES1!", timeframe.period, close)
// Returns
btc_ret = math.log(btc/btc[1])
eth_ret = math.log(eth/eth[1])
es_ret = math.log(es/es[1])
// Volatility
btc_vol = ta.stdev(btc_ret, 50)
eth_vol = ta.stdev(eth_ret, 50)
es_vol = ta.stdev(es_ret, 50)
// Correlations
corr_be = ta.correlation(btc_ret, eth_ret, 50)
corr_bs = ta.correlation(btc_ret, es_ret, 50)
corr_es = ta.correlation(eth_ret, es_ret, 50)
// ==========================================================
// 2️⃣ VOL PARITY WITH CORRELATION ADJUSTMENT
// ==========================================================
inv_btc = btc_vol != 0 ? 1/btc_vol : 0
inv_eth = eth_vol != 0 ? 1/eth_vol : 0
inv_es = es_vol != 0 ? 1/es_vol : 0
sum_inv = inv_btc + inv_eth + inv_es
w_btc = inv_btc / sum_inv
w_eth = inv_eth / sum_inv
w_es = inv_es / sum_inv
// Approx portfolio variance
portfolio_var = (
w_btc*w_btc*btc_vol*btc_vol +
w_eth*w_eth*eth_vol*eth_vol +
w_es*w_es*es_vol*es_vol +
2*w_btc*w_eth*corr_be*btc_vol*eth_vol +
2*w_btc*w_es*corr_bs*btc_vol*es_vol +
2*w_eth*w_es*corr_es*eth_vol*es_vol
)
// ==========================================================
// 3️⃣ 12-MONTH SHARPE TARGETING (252 trading days proxy)
// ==========================================================
ret = math.log(close/close[1])
mean_ret = ta.sma(ret, 252)
vol_ret = ta.stdev(ret, 252)
sharpe = vol_ret != 0 ? (mean_ret / vol_ret) * math.sqrt(252) : 0
target_sharpe = 1.5
sharpe_scale =
sharpe > target_sharpe ? 1 :
sharpe > 1 ? 0.7 :
0.4
// ==========================================================
// 4️⃣ RISK OF RUIN
// ==========================================================
wins = strategy.wintrades
loss = strategy.losstrades
total = strategy.closedtrades
p = total > 0 ? wins / total : 0.5
q = 1 - p
risk_per_trade = 0.01
capital_units = strategy.equity * risk_per_trade
risk_of_ruin =
p > q ? math.pow(q/p, capital_units) : 1
// ==========================================================
// 5️⃣ PROP FIRM SURVIVAL MODEL
// ==========================================================
var float peak_equity = na
peak_equity := na(peak_equity) ? strategy.equity : math.max(peak_equity, strategy.equity)
trailing_dd = (strategy.equity - peak_equity) / peak_equity
// Daily
var float day_start = na
new_day = ta.change(time("D")) != 0
if new_day
day_start := strategy.equity
daily_pnl = strategy.equity - day_start
daily_loss_limit = day_start * 0.03
trailing_limit = -0.10
prop_ok =
daily_pnl > -daily_loss_limit and
trailing_dd > trailing_limit
// Near violation compression
prop_scale =
trailing_dd > -0.05 ? 1 :
trailing_dd > -0.08 ? 0.6 :
0.3
// ==========================================================
// FINAL CAPITAL SCALING
// ==========================================================
base_alloc = 0.6
final_scale = base_alloc * sharpe_scale * prop_scale
position_pct = final_scale * 100
// ==========================
// ENTRY
// ==========================
long_signal = close > ta.ema(close, 20) and ta.crossover(ta.rsi(close, 6), 50)
// Prop condition default (avoid empty block issues)
if strategy.position_size == 0 and prop_ok
if long_signal
strategy.entry("LONG", strategy.long)
// ==========================================================
// EXIT
// ==========================================================
if strategy.position_size != 0
avg = strategy.position_avg_price
strategy.exit("EXIT",
limit = avg * 1.01,
stop = avg * 0.995)
// ==========================================================
// DASHBOARD
// ==========================================================
var table dash = table.new(position.top_right, 2, 8)
if barstate.islast
table.cell(dash, 0, 0, "Portfolio Vol")
table.cell(dash, 0, 1, "Sharpe")
table.cell(dash, 1, 1, str.tostring(sharpe,"#.##"))
table.cell(dash, 0, 2, "Risk of Ruin")
table.cell(dash, 1, 2, str.tostring(risk_of_ruin,"#.#####"))
table.cell(dash, 0, 3, "Trailing DD")
table.cell(dash, 1, 3, str.tostring(trailing_dd*100,"#.##")+"%")
table.cell(dash, 0, 4, "Prop OK")
table.cell(dash, 1, 4, str.tostring(prop_ok))
table.cell(dash, 0, 5, "Sharpe Scale")
table.cell(dash, 1, 5, str.tostring(sharpe_scale,"#.##"))
table.cell(dash, 0, 6, "Prop Scale")
table.cell(dash, 1, 6, str.tostring(prop_scale,"#.##"))
table.cell(dash, 0, 7, "Position %")
table.cell(dash, 1, 7, str.tostring(position_pct,"#.##"))
strategy(
"Institutional Risk Engine v3",
overlay=true,
initial_capital=100000,
pyramiding=0,
default_qty_type=strategy.percent_of_equity,
default_qty_value=10,
calc_on_order_fills=true)
// ==========================================================
// 1️⃣ MULTI-ASSET DATA
// ==========================================================
btc = request.security("BINANCE:BTCUSDT", timeframe.period, close)
eth = request.security("BINANCE:ETHUSDT", timeframe.period, close)
es = request.security("CME_MINI:ES1!", timeframe.period, close)
// Returns
btc_ret = math.log(btc/btc[1])
eth_ret = math.log(eth/eth[1])
es_ret = math.log(es/es[1])
// Volatility
btc_vol = ta.stdev(btc_ret, 50)
eth_vol = ta.stdev(eth_ret, 50)
es_vol = ta.stdev(es_ret, 50)
// Correlations
corr_be = ta.correlation(btc_ret, eth_ret, 50)
corr_bs = ta.correlation(btc_ret, es_ret, 50)
corr_es = ta.correlation(eth_ret, es_ret, 50)
// ==========================================================
// 2️⃣ VOL PARITY WITH CORRELATION ADJUSTMENT
// ==========================================================
inv_btc = btc_vol != 0 ? 1/btc_vol : 0
inv_eth = eth_vol != 0 ? 1/eth_vol : 0
inv_es = es_vol != 0 ? 1/es_vol : 0
sum_inv = inv_btc + inv_eth + inv_es
w_btc = inv_btc / sum_inv
w_eth = inv_eth / sum_inv
w_es = inv_es / sum_inv
// Approx portfolio variance
portfolio_var = (
w_btc*w_btc*btc_vol*btc_vol +
w_eth*w_eth*eth_vol*eth_vol +
w_es*w_es*es_vol*es_vol +
2*w_btc*w_eth*corr_be*btc_vol*eth_vol +
2*w_btc*w_es*corr_bs*btc_vol*es_vol +
2*w_eth*w_es*corr_es*eth_vol*es_vol
)
// ==========================================================
// 3️⃣ 12-MONTH SHARPE TARGETING (252 trading days proxy)
// ==========================================================
ret = math.log(close/close[1])
mean_ret = ta.sma(ret, 252)
vol_ret = ta.stdev(ret, 252)
sharpe = vol_ret != 0 ? (mean_ret / vol_ret) * math.sqrt(252) : 0
target_sharpe = 1.5
sharpe_scale =
sharpe > target_sharpe ? 1 :
sharpe > 1 ? 0.7 :
0.4
// ==========================================================
// 4️⃣ RISK OF RUIN
// ==========================================================
wins = strategy.wintrades
loss = strategy.losstrades
total = strategy.closedtrades
p = total > 0 ? wins / total : 0.5
q = 1 - p
risk_per_trade = 0.01
capital_units = strategy.equity * risk_per_trade
risk_of_ruin =
p > q ? math.pow(q/p, capital_units) : 1
// ==========================================================
// 5️⃣ PROP FIRM SURVIVAL MODEL
// ==========================================================
var float peak_equity = na
peak_equity := na(peak_equity) ? strategy.equity : math.max(peak_equity, strategy.equity)
trailing_dd = (strategy.equity - peak_equity) / peak_equity
// Daily
var float day_start = na
new_day = ta.change(time("D")) != 0
if new_day
day_start := strategy.equity
daily_pnl = strategy.equity - day_start
daily_loss_limit = day_start * 0.03
trailing_limit = -0.10
prop_ok =
daily_pnl > -daily_loss_limit and
trailing_dd > trailing_limit
// Near violation compression
prop_scale =
trailing_dd > -0.05 ? 1 :
trailing_dd > -0.08 ? 0.6 :
0.3
// ==========================================================
// FINAL CAPITAL SCALING
// ==========================================================
base_alloc = 0.6
final_scale = base_alloc * sharpe_scale * prop_scale
position_pct = final_scale * 100
// ==========================
// ENTRY
// ==========================
long_signal = close > ta.ema(close, 20) and ta.crossover(ta.rsi(close, 6), 50)
// Prop condition default (avoid empty block issues)
if strategy.position_size == 0 and prop_ok
if long_signal
strategy.entry("LONG", strategy.long)
// ==========================================================
// EXIT
// ==========================================================
if strategy.position_size != 0
avg = strategy.position_avg_price
strategy.exit("EXIT",
limit = avg * 1.01,
stop = avg * 0.995)
// ==========================================================
// DASHBOARD
// ==========================================================
var table dash = table.new(position.top_right, 2, 8)
if barstate.islast
table.cell(dash, 0, 0, "Portfolio Vol")
table.cell(dash, 0, 1, "Sharpe")
table.cell(dash, 1, 1, str.tostring(sharpe,"#.##"))
table.cell(dash, 0, 2, "Risk of Ruin")
table.cell(dash, 1, 2, str.tostring(risk_of_ruin,"#.#####"))
table.cell(dash, 0, 3, "Trailing DD")
table.cell(dash, 1, 3, str.tostring(trailing_dd*100,"#.##")+"%")
table.cell(dash, 0, 4, "Prop OK")
table.cell(dash, 1, 4, str.tostring(prop_ok))
table.cell(dash, 0, 5, "Sharpe Scale")
table.cell(dash, 1, 5, str.tostring(sharpe_scale,"#.##"))
table.cell(dash, 0, 6, "Prop Scale")
table.cell(dash, 1, 6, str.tostring(prop_scale,"#.##"))
table.cell(dash, 0, 7, "Position %")
table.cell(dash, 1, 7, str.tostring(position_pct,"#.##"))
오픈 소스 스크립트
트레이딩뷰의 진정한 정신에 따라, 이 스크립트의 작성자는 이를 오픈소스로 공개하여 트레이더들이 기능을 검토하고 검증할 수 있도록 했습니다. 작성자에게 찬사를 보냅니다! 이 코드는 무료로 사용할 수 있지만, 코드를 재게시하는 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.
오픈 소스 스크립트
트레이딩뷰의 진정한 정신에 따라, 이 스크립트의 작성자는 이를 오픈소스로 공개하여 트레이더들이 기능을 검토하고 검증할 수 있도록 했습니다. 작성자에게 찬사를 보냅니다! 이 코드는 무료로 사용할 수 있지만, 코드를 재게시하는 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.