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 32.5 years de datos SPY β’ Daily (SPDR S&P 500), desde January 29, 1993 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 32.5 years de velas SPY β’ Daily.Β Este backtest resultΓ³ en 15 posiciones, con una tasa de ganancia promedio de 87% y una relaciΓ³n riesgo-recompensa de 3.82.Β Si asumes que la relaciΓ³n riesgo-recompensa de 3.82 se mantiene, necesitas una tasa de ganancia mΓnima de 20.8 para ser rentable. AsΓ que vas bien hasta ahora.Β Sin embargo, 15 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 72% tiempo-en-mercado, obtienes 85.64% del potencial alcista del activo, y 57.32% del potencial bajista del activo.
All of the following: # "Papa" D Simple Moving Average (50, 0, close) Crosses β D Simple Moving Average (200, 0, close)
All of the following: # "India" D Simple Moving Average (50, 0, close) Crosses β D Simple Moving Average (200, 0, close)
Yo fam, this 50/200 SMA cross strategy is actually pretty lit! π₯ Looking at those 32.5 years of data, we're seeing some seriously juicy numbers that got me hyped.
The win rate is absolutely bonkers at 87% with a 3.82 risk/reward ratio - that's the kind of setup that makes my Wendy's paycheck look like pocket change! πͺ The average winner brings in 25.45% while the average L is only -6.66%. Plus, with only 15 total trades over this period, you're not getting killed by commission fees or having to watch charts 24/7.
One thing that's keeping me from going full YOLO though is that the strategy slightly underperformed buy & hold (1127% vs 1316%). But here's the big brain play - it only had 71.6% market exposure, meaning you're carrying way less risk during rough patches. That -32.5% max drawdown compared to the market's -56.7% is the kind of protection that helps you sleep at night while holding those diamond hands! ππ The recent performance has been a bit choppy, but looking at those 2-5 year returns got me ready to bet the farm! π
Dios mΓo, this strategy is terrible! 15 trades in 32 years? Are you planning to trade once every two years or what? This is ridiculous!
The win rate looks impressive at first - 87% sounds amazing, no? But with only 15 trades, it's meaningless estadΓstica! You could flip a coin 15 times and get 13 heads - it doesn't make it a reliable system. And look at the market exposure - 71.6% means you're basically following the market like a lost puppy, but doing worse than simple buy and hold! You're underperforming by almost 200 percentage points!
The drawdown of -32.5% is atrocious for such a slow strategy. With this kind of performance, you might as well put your money under the mattres! And look at those recent numbers - -91.6% over 6 months? Β‘Madre mΓa! This is the kind of performance that makes people jump from buildings!
If you're seriously considering trading this estrategia, I suggest you find a new hobby - maybe collecting stamps or feeding pigeons. At least you won't lose money that way. This is not a trading strategy, it's a retirement plan for snails!
Total de Operaciones | 15 | Beneficio Neto | 1127.3% | Beneficio Compra y MantΓ©n | 1316.3% |
Tasa de Ganancia | 87% | Ratio Riesgo/Recompensa | 3.82 | MΓ‘ximo Drawdown | -32.5% |
MΓ‘ximo Drawdown del Activo | -56.7% | ExposiciΓ³n | 71.6% | Promedio de Velas en PosiciΓ³n | 388.7 |
Ratio de Sharpe | 0.63 | Ratio de Sortino | 1.13 | Volatilidad Realizada | 11.15% |
Racha MΓ‘xima de Ganancia | 9 | Racha Promedio de Ganancia | 4.3 | Racha MΓ‘xima de PΓ©rdida | 1 |
Racha Promedio de PΓ©rdida | 1.0 | Promedio de Operaciones por Mes | 0.1 | Promedio de Operaciones por DΓa | 0.0 |
Desv. Est. del Retorno | 31.5 | Desv. Est. de la PΓ©rdida | 3.2 | Desv. Est. de la Ganancia | 31.7 |
Expectativa | 3.2 | Beta | 0.5 |
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 |