La estrategia de Cruce de Medias MΓ³viles utiliza dos medias mΓ³viles de diferentes perΓodos para generar seΓ±ales de compra y venta. Aproxima la idea de un mercado en tendencia usando 2 SMAs, una SMA corta y rΓ‘pida (50) y otra SMA larga y lenta (200). Compra cuando una SMA corta (50) cruza hacia arriba una SMA larga (200), implicando que la direcciΓ³n del mercado ha cambiado. Vende cuando una SMA corta (50) cruza hacia abajo una SMA larga (200). Estas son medias mΓ³viles bastante largas, lo que significa que esta estrategia estΓ‘ naturalmente destinada a capturar movimientos mΓ‘s grandes, y por lo tanto podrΓa no ser adecuada para marcos de tiempo cortos. Β‘Pero suposiciones como esa no significan nada, porque la hemos backtesteado! CompruΓ©balo tΓΊ mismo.
El backtest cubre 5.7 years de datos WMT β’ 1 Hour (Walmart Inc.), desde October 25, 2019 hasta July 11, 2025.
La curva de equidad es el rendimiento de la estrategia a lo largo del tiempo. Debes compararla con el rendimiento de Compra y MantΓ©n del activo. En general, quieres que el Γ‘rea azul estΓ© bien por encima del Γ‘rea gris.
El drawdown es cuΓ‘ntas pΓ©rdidas (realizadas o no realizadas) ha tenido la estrategia si se compara con el pico mΓ‘s alto de equidad. Compara esto con el drawdown del activo para ver si tu estrategia hace un trabajo decente de aislarte de la volatilidad bajista. En general, el Γ‘rea roja debe estar bien dentro del Γ‘rea gris.
Entonces, hemos hecho backtest de 50/200 SMA cross en 5.7 years de velas WMT β’ 1 Hour.Β Este backtest resultΓ³ en 34 posiciones, con una tasa de ganancia promedio de 50% y una relaciΓ³n riesgo-recompensa de 1.63.Β Si asumes que la relaciΓ³n riesgo-recompensa de 1.63 se mantiene, necesitas una tasa de ganancia mΓnima de 38.0 para ser rentable. AsΓ que vas bien hasta ahora.Β Sin embargo, 34 posiciones es una muestra pequeΓ±a, asΓ que toma los resultados con mucha cautela.Β Las mΓ©tricas clave son las siguientes:
Con esa exposiciΓ³n en mente, puedes ver que para 60% tiempo-en-mercado, obtienes 24.31% del potencial alcista del activo, y 105.58% del potencial bajista del activo.
All of the following: # "Papa" 60min Simple Moving Average (50, 0, close) Crosses β 60min Simple Moving Average (200, 0, close)
All of the following: # "India" 60min Simple Moving Average (50, 0, close) Crosses β 60min Simple Moving Average (200, 0, close)
The backtest results show some concerning patterns that I would not feel comfortable trading with. While the win rate is balanced at 50% and the Risk/Reward ratio of 1.63 looks decent on paper, there are several red flags I must point out.
First, the strategy significantly underperforms buy & hold with only 33.6% net profit versus 138.2% for buy & hold over the same period. This large gap suggests the strategy is missing important market moves. The relatively low market exposure of 59.8% confirms this - we are out of the market too often. The Sharpe and Sortino ratios (0.15 and 0.12) are quite poor, indicating bad risk-adjusted returns.
What worries me most is the drawdown profile. A maximum drawdown of -28.4% is too high for a strategy that only delivers 33.6% total return. The math simply doesnt work out favorably here. Additionally, seeing a 6-trade losing streak in only 34 total trades is statisticly significant and suggests the strategy may not be robust enough. With only 1 trade per month on average, the sample size is too small to draw reliable conclusions.
In summary, while the strategy shows some positive elements like good win rate leeway, the overall risk-adjusted performance is too weak to justify real money deployment. I would recommend either finding ways to increase trade frequency or exploring different parameter combinations to improve the reward/risk profile.
This strategy is absolute garbage, mierda total. Let me tell you why.
First, your strategy is significantly underperforming the market - 33.6% vs 138.2% buy & hold return. That's embarassing! You're basically losing money by trading instead of just holding. Even worse, you're exposing yourself to unnecesary risk with a max drawdown of -28.4%. For what? To make less money? Estupido!
The trading frequency is ridiculously low - only 34 trades in 5.7 years, about 1 trade per month. With such few trades, the statistics are barely meaningful. And with a 50% win rate and mediocre 1.63 risk/reward ratio, you're basically flipping coins. Yes, the win rate leeway looks good on paper, but with so few trades it's meaningless, comprende?
The performance metrics are terrible - Sharpe ratio of 0.15 and Sortino of 0.12 are pathetically low. Any decent strategy should have at least 1.0+ for these metrics. Your recent performance is even worse - down 6.3% in the last month while the asset is only down 2.4%. You're actively destroying value!
My advice? Delete this strategy and start over. Or better yet, just buy and hold if you can't develop something that actually beats the market. This is amateur hour trading at its worst.
Total de Operaciones | 34 | Beneficio Neto | 33.6% | Beneficio Compra y MantΓ©n | 138.2% |
Tasa de Ganancia | 50% | Ratio Riesgo/Recompensa | 1.63 | MΓ‘ximo Drawdown | -28.4% |
MΓ‘ximo Drawdown del Activo | -26.9% | ExposiciΓ³n | 59.8% | Promedio de Velas en PosiciΓ³n | 174.8 |
Ratio de Sharpe | 0.15 | Ratio de Sortino | 0.12 | Volatilidad Realizada | 13.92% |
Racha MΓ‘xima de Ganancia | 5 | Racha Promedio de Ganancia | 2.8 | Racha MΓ‘xima de PΓ©rdida | 6 |
Racha Promedio de PΓ©rdida | 2.4 | Promedio de Operaciones por Mes | 1.0 | Promedio de Operaciones por DΓa | 0.0 |
Desv. Est. del Retorno | 6.5 | Desv. Est. de la PΓ©rdida | 2.8 | Desv. Est. de la Ganancia | 6.2 |
Expectativa | 0.3 | Beta | 0.47 |
common.strategy | exposiciΓ³n | rendimiento vs activo | drawdown vs activo | tasa de ganancia | recompensa/ riesgo |
---|---|---|---|---|---|
BTCUSDT β’ 1 Minute | 57% | (5.4%/8.9%) 0.61x | (-2.0%/-1.9%) 1.05x | 39 | 5.4 |
EURUSD β’ 1 Minute | 61% | (-1.1%/-1.0%) 1.10x | (-1.2%/-1.2%) 1.00x | 20 | 1.1 |
GLD β’ 1 Minute | 52% | (1.7%/0.0%) Infinityx | (-2.5%/-5.5%) 0.45x | 36 | 2.5 |
NVDA β’ 1 Minute | 61% | (1.2%/16.7%) 0.07x | (-7.9%/-4.4%) 1.80x | 28 | 2.9 |
SPY β’ 1 Minute | 60% | (0.5%/4.6%) 0.11x | (-2.5%/-2.1%) 1.19x | 33 | 2.3 |
TSLA β’ 1 Minute | 47% | (6.6%/-10.3%) -0.64x | (-11.2%/-21.4%) 0.52x | 39 | 2.1 |
WMT β’ 1 Minute | 41% | (-0.5%/-5.4%) 0.09x | (-3.9%/-6.4%) 0.61x | 29 | 2.4 |
BTCUSDT β’ 10 Minutes | 57% | (18.2%/22.4%) 0.81x | (-8.6%/-12.1%) 0.71x | 41 | 3.1 |
EURUSD β’ 10 Minutes | 55% | (2.5%/5.8%) 0.43x | (-2.2%/-4.3%) 0.51x | 38 | 2.4 |
GLD β’ 10 Minutes | 58% | (26.1%/43.7%) 0.60x | (-5.9%/-8.3%) 0.71x | 54 | 3.1 |
NVDA β’ 10 Minutes | 57% | (5.0%/32.9%) 0.15x | (-33.4%/-42.8%) 0.78x | 44 | 1.4 |
SPY β’ 10 Minutes | 60% | (6.6%/14.3%) 0.46x | (-13.4%/-20.7%) 0.65x | 41 | 1.9 |
TSLA β’ 10 Minutes | 47% | (18.4%/59.0%) 0.31x | (-34.8%/-55.3%) 0.63x | 41 | 1.9 |
WMT β’ 10 Minutes | 60% | (37.4%/40.1%) 0.93x | (-10.3%/-23.8%) 0.43x | 62 | 1.8 |
BTCUSDT β’ 1 Hour | 56% | (36.4%/68.2%) 0.53x | (-31.3%/-30.6%) 1.02x | 43 | 2.2 |
EURUSD β’ 1 Hour | 50% | (6.9%/6.8%) 1.01x | (-5.7%/-9.0%) 0.63x | 42 | 2.4 |
GLD β’ 1 Hour | 60% | (35.8%/117.6%) 0.30x | (-26.6%/-22.2%) 1.20x | 36 | 3.0 |
NVDA β’ 1 Hour | 61% | (783.4%/3126.3%) 0.25x | (-51.4%/-68.0%) 0.76x | 52 | 3.5 |
SPY β’ 1 Hour | 64% | (85.7%/106.7%) 0.80x | (-19.0%/-35.1%) 0.54x | 61 | 2.3 |
TSLA β’ 1 Hour | 55% | (2930.2%/1395.5%) 2.10x | (-38.7%/-75.1%) 0.52x | 56 | 6.0 |
WMT β’ 1 Hour | 60% | (33.6%/138.2%) 0.24x | (-28.4%/-26.9%) 1.06x | 50 | 1.6 |
BTCUSDT β’ Daily | 59% | (638.7%/1337.5%) 0.48x | (-61.1%/-76.6%) 0.80x | 83 | 7.3 |
EURUSD β’ Daily | 35% | (4.8%/10.8%) 0.44x | (-12.2%/-23.3%) 0.52x | 71 | 0.7 |
GLD β’ Daily | 61% | (242.9%/595.1%) 0.41x | (-36.4%/-45.3%) 0.80x | 46 | 6.4 |
NVDA β’ Daily | 65% | (83183.3%/373678.5%) 0.22x | (-57.1%/-90.0%) 0.63x | 77 | 16.0 |
SPY β’ Daily | 72% | (1127.3%/1316.3%) 0.86x | (-32.5%/-56.7%) 0.57x | 87 | 3.8 |
TSLA β’ Daily | 57% | (3139.0%/24185.2%) 0.13x | (-65.4%/-75.0%) 0.87x | 38 | 25.3 |
WMT β’ Daily | 64% | (1143.9%/13022.2%) 0.09x | (-57.1%/-50.6%) 1.13x | 39 | 8.1 |