What exactly is a backtest?
A backtest uses real historical price data to check 'what would have happened if I'd used this strategy back then.' This tool computes the past return, max drawdown, and CAGR of investing a fixed monthly amount (DCA) into a given ticker. It lets you validate a strategy after the fact without real trades — useful for stress-testing investing ideas — but always keep in mind that past performance does not guarantee the future.
What's the data source and how accurate is it?
It uses Yahoo Finance adjusted close prices, cached every 24 hours. Adjusted prices reflect both dividend reinvestment and stock splits, giving the most accurate picture of long-term performance. However, Yahoo data is unofficial and may have gaps or errors for some tickers/periods, and delisted or merged tickers won't load. For precise analysis, cross-check with broker or official data.
How do DRIP ON/OFF change the result?
ON computes with 'adjusted prices' (dividends and splits included), showing total return with dividends auto-reinvested. OFF values positions at plain 'close' prices and accumulates received dividends separately as cash. High-yield tickers like SCHD or O show a large gap between the two; near-zero-dividend tickers like QQQ show little. To see realistic long-term performance, reinvest ON is usually closer to reality.
What is max drawdown (MDD) and why does it matter?
MDD (Maximum Drawdown) is the largest drop from a prior peak during the period. For example, if value rises to ₩100M then falls to ₩60M, the MDD is −40%. Even with identical CAGR, a strategy with a large MDD is psychologically hard to hold through a downturn, raising the risk of capitulating mid-way. Leveraged ETFs (e.g., TQQQ) can exceed −80% MDD, so it's a risk metric you must check alongside return.
Why do leveraged ETFs lag their multiple over the long run?
Leveraged ETFs like TQQQ and QLD track 2–3× the 'daily' return. The higher the volatility, the more volatility decay accumulates, so long-term performance can fall below 'index return × multiple.' Conversely, in a strong, steady uptrend they can far exceed the nominal multiple. In short, they favor trending markets and hurt in choppy or crashing ones — understand they're short-term trading instruments.
If past returns were good, will the future be good too?
No. The biggest pitfall of backtesting is 'overfitting to the past.' A ticker or strategy that performed best in a given window has no guarantee of repeating, and high past returns often came with proportionally large volatility and risk. Results also shift dramatically with small changes to the start/end dates (timing bias). A backtest is a tool to understand a strategy's character (volatility, drawdown, compounding), not to predict future returns.
Why does the start date change results so much?
Even with DCA, the start and end dates strongly drive results. Starting just before the 2000 dot-com bubble or the 2008 crisis would have left the same ticker underwater for a while. This is 'timing bias,' and you shouldn't generalize from one window. Comparing several start years, or using a long contribution period (10+ years), reduces it. Use this tool to vary the period and check how sensitive the results are.
Can I compare Bitcoin or individual stocks?
Yes. Select BTC-USD for Bitcoin, or enter tickers like Tesla, Nvidia, or Apple to compare individual stocks against ETFs under the same conditions (up to 5 tickers). Note Bitcoin is extremely volatile and individual stocks carry higher concentration risk than indexes. Tickers with a short listing history have limited comparable data, so align the start date for a fair comparison.
Are taxes and trading costs reflected?
No. This backtest is a 'pre-tax, pre-cost' result — it excludes capital gains tax (22% foreign), dividend tax, FX conversion fees, and trading commissions. A Korean resident's net return is lower than shown, and the 22% capital gains tax matters significantly when sale gains are large. So the results are best for 'relative comparison' between strategies; estimate your actual take-home by separately deducting taxes and costs.
Are you recommending high-risk products like TQQQ?
No. This tool is an informational simulation and does not recommend any specific security. Leveraged ETFs are generally considered unsuitable for long-term accumulation due to volatility decay and drawdowns approaching −80%. Even if a backtest shows high past returns, you must view the underlying max drawdown and volatility alongside them and judge for yourself whether they fit your own risk tolerance.