50/200 SMA crosslongBacktest Results @ TSLA • 1 Hour
The Moving Average Crossover strategy uses two moving averages of different periods to generate buy and sell signals. It appoximates the idea of a trending market by using 2 SMAs, one short fast SMA(50) and another slow longer SMA(200). It buys whenever a short SMA(50) crosses up a long SMA(200), thereby implying that the direction of the market has changed. It sells once a short SMA(50) crosses down a long SMA(200). These are fairly long MAs, which means that this strategy is naturalyl meant to capture bigger moves, and thereby might not be a good fit for short time frames. But assumptions like that do not mean anything, because we've backested it! See youself.
Equity Curve
Backtest covers 5.7 years of TSLA • 1 Hour (Tesla, Inc.) data, from October 25, 2019 to July 11, 2025.
Equity curve is the strategy's performance over time. You should compare it to the asset's Buy & Hold performance. In general, you want the blue area to be well above the gray area.
Drawdown is how much losses (realized or unrealized) the strategy has had if compared to the highest equity peak. Compare this to the asset's drawdown to see whether your strategy does a decent job of isolating you from downside volatility. In general, the red area must be well within the gray area.
So, we have backtested 50/200 SMA cross on 5.7 years of TSLA • 1 Hour candles. This backtest resulted in 27 positions, with the average win rate of 56% and reward-risk ratio of 6.04. If you assume that 6.04 reward-to-risk ratio holds, you need a minimum win rate of 14.2 to be profitable. So you're looking good so far. However, 27 positions is a small sample size, so take the results with a huge grain of salt. The key metrics are as follows:
- Total Return: Total Return: 2930.20% vs 1395.50% for the asset
- Max Drawdown: Max Drawdown: -38.70% vs -75.10% for the asset
- Exposure: Exposure: 54.60% time in the market
- Win Rate: Win Rate: 56.0%, vs 14.2% minimum
- Reward/Risk Ratio: Reward/Risk Ratio: 6.04
With that exposure in mind, you can tell that for 55% time-in-market, you get 209.97% of the asset upside potential, and 51.53% of the asset downside potential.
50/200 SMA cross: enter a position when
All of the following: # "Papa" 60min Simple Moving Average (50, 0, close) Crosses ↗ 60min Simple Moving Average (200, 0, close)
50/200 SMA cross: exit a position when
All of the following: # "India" 60min Simple Moving Average (50, 0, close) Crosses ↘ 60min Simple Moving Average (200, 0, close)
50/200 SMA cross @ TSLA • 1 Hour (2930.2%) backtest results explained by Alex C, Sarah
Alex C
AuthorThe backtest results for the 50/200 SMA cross strategy on TSLA look mathematically promising, but I have some concerns about the statistical significance.
The strategy shows impressive net profit of 2930.2% over 5.7 years, outperforming buy & hold by more than 2x. The risk metrics are decent - Sharpe ratio of 1.09 indicates acceptable risk-adjusted returns, although the max drawdown of 38.7% is quite substantial. What worries me most is the low sample size of only 27 trades over 5.7 years (0.8 trades per month). This makes the statistical validity questionable, since we need more trades to prove the edge is not just luck.
The win rate of 56% combined with the excellent risk/reward ratio of 6.04 suggests the strategy is mathematically viable, given the minimal required win rate is only 14.2%. However, the average time in position of 201 candles (about 8.4 days) means high exposure to overnight risk. I would recommend running Monte Carlo simulations with different market conditions to test robustness. Also, the strategy performance seems to deteriorate in recent periods based on the CAGR numbers, which could indicate the edge is weakening.
Sarah
AuthorMadre mía, what a mess of a strategy! Let me tell you exactly why this is problematic.
First of all, only 27 trades in 5.7 years? That's ridiculously low - we're talking about less than 1 trade per month! This is not a strategy, this is basically waiting for Godot. The sample size is so small that any statistical conclusion is about as reliable as my ex-boyfriend's promises.
Yes, the numbers look fancy - 2930% profit, 56% win rate, impressive R/R ratio of 6.04. But let's be real here - with such few trades, these metrics are basically meaningless. One or two random trades could completely change everything. The strategy is basically gambling with extra steps.
The most concerning thing is that 38.7% drawdown. Do you have the stomach to watch your account drop by almost 40%? And this is during a backtest - in real life, it could be much worse! The volatility metrics are through the roof too - 40.23% realized volatility? That's not trading, that's riding a mechanical bull blindfolded.
Look, if you want to throw your money away, there are more entertaining ways to do it. This strategy needs serious work - either find a way to generate more signals or go back to the drawing board. And por favor, don't tell me you're planning to trade this with real money!
Tabular metrics of 50/200 SMA cross backtested on TSLA • 1 Hour
| Total Trades | 27 | Net Profit | 2930.2% | Buy & Hold Profit | 1395.5% |
| Win Rate | 56% | Reward/Risk Ratio | 6.04 | Max Drawdown | -38.7% |
| Asset Max Drawdown | -75.1% | Exposure | 54.6% | Avg Candles in Position | 201.1 |
| Sharpe Ratio | 1.09 | Sortino Ratio | 0.67 | Realized Volatility | 40.23% |
| Max Winning Streak | 5 | Avg Winning Streak | 1.5 | Max Losing Streak | 2 |
| Avg Losing Streak | 1.3 | Avg Trades per Month | 0.8 | Avg Trades per Day | 0.0 |
| Return Std Dev | 32.6 | Loss Std Dev | 4.6 | Win Std Dev | 33.8 |
| Expectancy | 2.9 | Beta | 0.5 |
All backtests for 50/200 SMA cross
| backtest | exposure | peformance vs asset | drawdown vs asset | win% | reward/risk |
|---|---|---|---|---|---|
BTCUSDT • 1 Minute | 57% | (5.4%/8.9%) 0.61x | (-2.0%/-1.9%) 1.05x | 39 | 5.4 |
EURUSD • 1 Minute | 61% | (-1.1%/-1.0%) 1.10x | (-1.2%/-1.2%) 1.00x | 20 | 1.1 |
GLD • 1 Minute | 52% | (1.7%/0.0%) Infinityx | (-2.5%/-5.5%) 0.45x | 36 | 2.5 |
NVDA • 1 Minute | 61% | (1.2%/16.7%) 0.07x | (-7.9%/-4.4%) 1.80x | 28 | 2.9 |
SPY • 1 Minute | 60% | (0.5%/4.6%) 0.11x | (-2.5%/-2.1%) 1.19x | 33 | 2.3 |
TSLA • 1 Minute | 47% | (6.6%/-10.3%) -0.64x | (-11.2%/-21.4%) 0.52x | 39 | 2.1 |
WMT • 1 Minute | 41% | (-0.5%/-5.4%) 0.09x | (-3.9%/-6.4%) 0.61x | 29 | 2.4 |
BTCUSDT • 10 Minutes | 57% | (18.2%/22.4%) 0.81x | (-8.6%/-12.1%) 0.71x | 41 | 3.1 |
EURUSD • 10 Minutes | 55% | (2.5%/5.8%) 0.43x | (-2.2%/-4.3%) 0.51x | 38 | 2.4 |
GLD • 10 Minutes | 58% | (26.1%/43.7%) 0.60x | (-5.9%/-8.3%) 0.71x | 54 | 3.1 |
NVDA • 10 Minutes | 57% | (5.0%/32.9%) 0.15x | (-33.4%/-42.8%) 0.78x | 44 | 1.4 |
SPY • 10 Minutes | 60% | (6.6%/14.3%) 0.46x | (-13.4%/-20.7%) 0.65x | 41 | 1.9 |
TSLA • 10 Minutes | 47% | (18.4%/59.0%) 0.31x | (-34.8%/-55.3%) 0.63x | 41 | 1.9 |
WMT • 10 Minutes | 60% | (37.4%/40.1%) 0.93x | (-10.3%/-23.8%) 0.43x | 62 | 1.8 |
BTCUSDT • 1 Hour | 56% | (36.4%/68.2%) 0.53x | (-31.3%/-30.6%) 1.02x | 43 | 2.2 |
EURUSD • 1 Hour | 50% | (6.9%/6.8%) 1.01x | (-5.7%/-9.0%) 0.63x | 42 | 2.4 |
GLD • 1 Hour | 60% | (35.8%/117.6%) 0.30x | (-26.6%/-22.2%) 1.20x | 36 | 3.0 |
NVDA • 1 Hour | 61% | (783.4%/3126.3%) 0.25x | (-51.4%/-68.0%) 0.76x | 52 | 3.5 |
SPY • 1 Hour | 64% | (85.7%/106.7%) 0.80x | (-19.0%/-35.1%) 0.54x | 61 | 2.3 |
TSLA • 1 Hour | 55% | (2930.2%/1395.5%) 2.10x | (-38.7%/-75.1%) 0.52x | 56 | 6.0 |
WMT • 1 Hour | 60% | (33.6%/138.2%) 0.24x | (-28.4%/-26.9%) 1.06x | 50 | 1.6 |
BTCUSDT • Daily | 59% | (638.7%/1337.5%) 0.48x | (-61.1%/-76.6%) 0.80x | 83 | 7.3 |
EURUSD • Daily | 35% | (4.8%/10.8%) 0.44x | (-12.2%/-23.3%) 0.52x | 71 | 0.7 |
GLD • Daily | 61% | (242.9%/595.1%) 0.41x | (-36.4%/-45.3%) 0.80x | 46 | 6.4 |
NVDA • Daily | 65% | (83183.3%/373678.5%) 0.22x | (-57.1%/-90.0%) 0.63x | 77 | 16.0 |
SPY • Daily | 72% | (1127.3%/1316.3%) 0.86x | (-32.5%/-56.7%) 0.57x | 87 | 3.8 |
TSLA • Daily | 57% | (3139.0%/24185.2%) 0.13x | (-65.4%/-75.0%) 0.87x | 38 | 25.3 |
WMT • Daily | 64% | (1143.9%/13022.2%) 0.09x | (-57.1%/-50.6%) 1.13x | 39 | 8.1 |