Which backtesting strategy has always given confirmed predictions?

<p id="isPasted">There are a few ways one could approach. One would be to just start trading it, perhaps small size and increase as you gain confidence.</p><p>The other is to “forward test” it. That is, continue to paper trade it with fake money to verify that a strategy which works on historical data will work on live data.</p><p>There are advantages and disadvantages to each and by assessing how you went about developing your strategy and what questions might remain, you can try to decide the best way to go forward.</p><p>Did you factor in order slippage and transaction costs in your backtesting? If not, you won’t learn the impact of these by forward testing, but it will be obvious with real, live orders.</p><p>Did you tune the parameters of your strategy (like adjusting indicator settings for the best return, etc.)? If so, forward testing can help validate whether or not you have over-fit the settings and just found a some parameters which are unusually good on backtest results but hard to reproduce. If the results for the parameters you chose on backtesting are significantly better than with other parameters, this could be a worry.</p>

<p id="isPasted">There is no backtesting strategy that can always give confirmed or guaranteed predictions of future market performance. Backtesting is a valuable tool for evaluating a strategy's potential based on historical data, but it has inherent limitations, and past performance is not a reliable indicator or guarantee of future results.&nbsp;</p><p><strong>Key reasons why no backtesting strategy can offer confirmed predictions:</strong></p><ul><li>Past Performance is Not Indicative of Future Results: Market conditions are dynamic and constantly evolving due to various factors like economic events, geopolitical changes, and shifts in trader sentiment, which may not repeat in the same way.</li><li>Overfitting (Curve Fitting): A strategy can be overly optimized to fit historical data perfectly, leading to excellent backtest results but poor performance in live trading.</li><li>Ignoring Real-World Costs: Many backtests fail to account for real-world transaction costs, such as slippage (the difference between the expected price and the actual execution price), broker commissions, and liquidity issues, which can significantly impact profitability in live trading.</li><li>Historical Bias/Data Dredging: Strategies are often developed based on the same data used for testing (in-sample data), leading to a bias that makes the strategy seem more successful than it is. Testing on out-of-sample data helps mitigate this, but does not eliminate all risks.</li><li>Unforeseen Events: Backtesting cannot account for truly unexpected, black swan events or sudden market shocks that have no historical precedent.</li><li>Emotional Factors: Backtesting removes emotion from the process, but live trading involves real money and psychological pressures that can lead to impulsive decisions and deviations from the strategy. </li></ul>