Portfolio Backtesting Tool
Portfolio Strategy Simulator — Five-Year Illustrative Model
Add stocks, set allocations, and compare two modeled strategy paths over five illustrative years. The current browser fallback does not use verified historical closing prices. No signup is needed.
What is portfolio backtesting?
A true backtest uses historical market prices to calculate what a stated strategy would have done. The interactive tool currently uses a browser-generated model instead, so its figures are illustrative scenarios rather than observed market returns.
Why backtest a portfolio?
Patterns that hold across every reporting season. The specific numbers change, the structure does not.
Portfolio Backtester
Explore an illustrative five-year portfolio scenario
Enter each stock’s ticker (e.g. AAPL for Apple) and what percentage of your money goes into it. They do not need to add up to 100 as the tool will balance them for you.
Buy and Hold: Put your money in on day one and leave it for five years.
Trend-Following: Automatically buys when prices are rising and sells when they start falling.
Compare Both: Shows the two modeled strategy paths side by side.
This is your starting amount, split across your stocks based on the percentages above.
Preparing illustrative scenario…
Add your stocks, pick a strategy, enter your starting amount, then click Run Illustrative Model.
Educational content only. Current model results are illustrative and do not establish past or future returns. This tool does not provide personal financial, trading or investment advice.
A historical backtester requires verified price data. This page currently takes your stocks and weights and compares two strategies through a five-year illustrative model. Its numbers are not observed investment returns.
How to use the Portfolio Backtesting Tool — written walkthrough
A four-stage written walkthrough — how to enter tickers, set weights, run the illustrative model and read its hypothetical returns and drawdowns.
How a beginner should approach this tool
Each chapter below maps to a stage of using this tool — work through them in order.
- Step 1Adding stocks and allocations
- Step 2Choosing the test period or strategy
- Step 3Reading modeled return and drawdown
- Step 4Common backtesting mistakes
Why should you backtest a portfolio?
Clear beginner outcomes for this specific tool.
Test allocation ideas before using money
This model helps you see how changes to allocations and assumptions affect an illustrative result.
Understand risk, not just return
Drawdowns and volatility show how uncomfortable the journey may have been.
Compare strategies side by side
Change weights and tickers to compare modeled concentration and strategy outcomes.
What is portfolio backtesting and how does it work?
A genuine backtest can help examine how a stated strategy behaved during a past period when it uses verified historical prices and accounts for its assumptions. This page currently demonstrates those ideas with an illustrative model, so the displayed paths are hypothetical.
- The current tool compares modeled paths; a true historical backtest would require verified price data.
- The tool displays five illustrative years, including a modeled downturn and recovery.
- Two strategies are tested: buy-and-hold (no trading) and trend-following (sell when the trend breaks).
- Neither historical returns nor modeled paths forecast future returns.
- Use the modeled downturn to discuss risk tolerance; it does not show an actual investor outcome.
Total read time: about 8 minutes. Each section can stand on its own.
What is portfolio backtesting? 1 min read
A true historical backtest uses verified past prices and stated trading rules. This page currently uses an illustrative browser model, so its figures show a possible path under assumptions rather than the actual returns of your selected tickers.
Use this model to examine assumptions and risk, then use verified market data if you need a historical reconstruction.
- Modeled paths — current results use illustrative returns, not verified daily prices
- Modeled volatility — a simulated shock helps discuss risk but is not a past market event
- Strategy comparison — two simplified rules applied to the same modeled path
The model neither predicts future returns nor verifies past ones. Changing a ticker, weight, or assumption can change its illustrative output; check actual prices separately before drawing historical conclusions.
How to run a backtest 1 min read
Step 1: Add your stocks. Type each ticker (e.g. AAPL for Apple). You can add up to 10 stocks in one portfolio.
Step 2: Set allocation percentages. Decide how much of your money goes into each stock. The tool rebalances them to sum to 100%, so you do not need to be exact.
Step 3: Choose a strategy. Buy-and-hold remains invested along the modeled path. The simplified trend option responds to recent modeled returns and may shift into cash. Compare the two illustrative paths, not historical strategy performance.
Step 4: Pick a starting amount. Default is $10,000. The result scales linearly, so a $50,000 starting amount gives a result 5 times the size of a $10,000 one.
Buy-and-hold vs trend-following 1 min read
The two strategies the tool supports
Which one wins? It depends on assumptions and the generated path. Compare the two model outputs to see how the chosen rule affects this illustration; do not infer which would have won in actual markets.
How allocation percentages work 1 min read
Allocation percentages decide how much of your starting amount goes into each stock. A 30% allocation to Apple on a $10,000 starting amount means $3,000 of Apple shares on day one.
Common allocation approaches
| Approach | How it works | Example | When to use |
|---|---|---|---|
| Equal weight | Same percent for each stock | 5 stocks × 20% | You have no strong view on which will outperform |
| Conviction weight | More to the names you believe in | 40% AAPL, 30% MSFT, etc. | You have research-backed views on relative quality |
| Market cap weight | Bigger companies get more | Like an index | You want index-like behavior with fewer names |
| Inverse cap weight | Smaller companies get more | Equal $ each, smaller % to mega caps | You believe smaller names will outperform |
The tool does not rebalance the allocation over time. The percentages reflect day-one weights. By the end of the period, the actual weights will have drifted based on each stock’s performance.
Common mistakes when backtesting 2 min read
Picking stocks that already won. Backtesting Nvidia and Apple looks brilliant. But you only know they were the winners because you have hindsight.
→ Fix: Test the portfolio you would have actually picked five years ago, not the one that obviously worked.
Confusing 5-year returns with annual returns. In an illustrative example, 138% total growth over five years is roughly 19% compounded annually; those figures are not this portfolio’s verified return.
→ Fix: Always check the annualized return, not just the total return. Annualised is the fairer comparison.
Ignoring drawdowns. A portfolio that returned 100% but lost 60% along the way is much harder to hold than one that returned 80% with only a 30% drawdown.
→ Fix: Always read the max drawdown number alongside the return. They both matter.
Treating the result as a forecast. A strong modeled result is neither a prediction nor proof of past performance.
→ Fix: Use the current model to discuss assumptions, not to forecast returns or claim historical performance.
Optimizing on one period. Tweaking allocations until the backtest looks great is called “overfitting”. The portfolio is now perfect for the past and probably wrong for the future.
→ Fix: Pick a portfolio you would hold for reasons beyond the backtest. Use the test to check it, not design it.
Reading the backtest result 1 min read
A backtest result shows you four key numbers. All four matter, not just the headline return.
Total return: the percent change from day one to today. Easy to understand but can be misleading on its own.
Annualised return: the return expressed per year, adjusted for compounding. Fairer for comparing periods of different lengths.
Max drawdown: the biggest peak-to-trough fall during the test. A 35% drawdown means the portfolio at one point lost 35% of its value before recovering.
Strategy comparison: if you ran both buy-and-hold and trend-following, see which one had the better risk-adjusted result (return divided by drawdown), not just the higher total return.
Worked example: two-stock strategy model 2 min read
Compare a two-stock model
The tool starts with a hypothetical $10,000 split equally between AAPL and MSFT. Run the model once, then change only one weight. Compare the buy-and-hold and simplified trend results and note how the concentration changes.
The browser fallback generates a repeatable five-year scenario from assumptions. Its displayed dollar totals, model years, benchmark and drawdowns are not AAPL, MSFT, or S&P 500 historical performance.
The lesson: A modeled path can show how assumptions affect an outcome, but it cannot tell you what actually happened. Use verified price and total-return data for a historical analysis.
References
- For a real historical test, obtain dated price and corporate-action data from an exchange or licensed market-data provider. This browser model does not retrieve those prices.
- Faber, “A Quantitative Approach to Tactical Asset Allocation” (2007), describes historical trend research. The current browser model does not implement its 200-day price rule.
- Drawdown in the current model is calculated from its simulated path, not verified daily closing prices.
- CFA Institute, “Quantitative Investment Analysis” — reference for return calculations and risk-adjusted metrics.
- The current browser fallback uses a deterministic illustrative model when the historical-price service is unavailable.
Backtesting terms, defined in one line
Bookmark this. Every term you will see on the tool or in backtest commentary.
A true backtest applies stated rules to verified historical prices; the current interactive model does not do that.
A strategy where you buy on day one and never sell. Captures full upside and full downside.
A rule-based strategy that sells when price falls below a moving average and buys back when it rises above.
The biggest peak-to-trough fall during a period. A 35% drawdown means the portfolio fell 35% from its high.
The return expressed per year, adjusted for compounding. Fairer than total return for comparing different periods.
When a backtest only includes companies that still exist today. Inflates results because failures are missing.
Portfolio backtester: frequently asked questions
Quick answers before running your first backtest.
Is the backtester free?
Does a good backtest mean my portfolio will do well?
Can I backtest more than 5 years?
What strategies can I test?
Can I include ETFs?
What about dividends?
What is the trend-following rule used?
Why would a real result differ from this model?
Deepen your understanding
This tool is one research step. These articles teach the concepts behind it.
How to build a stock portfolio
Asset allocation basics for beginners
Buy and hold vs market timing
The research behind each approach
What is a moving average?
The 200-day SMA explained
Understanding portfolio drawdown
Why max drawdown matters more than average return
What is rebalancing?
When and why to reset your allocations
Diversification for beginners
How many stocks is enough?
Reading risk-adjusted returns
Sharpe ratio and what it means
Common backtest pitfalls
Survivorship bias, overfitting, look-ahead bias
Keep researching
Use these tools to connect scenario thinking with portfolio planning.
Sources & methodology
The interactive tool currently runs a deterministic five-year browser model when a historical-price service is unavailable. It uses assumptions and synthetic shocks rather than verified closing prices. A true backtest would require dated price and corporate-action data plus fully specified trading rules.
Authoritative outbound sources:
- Yahoo Finance, Historical closing price reference
- Nasdaq Historical Data, Official exchange price archive
- CFA Institute, Return calculation methodology
- FINRA, why back-tested results do not predict future performance
- SSRN, Academic research on tactical strategies and backtesting
- The browser fallback generates illustrative monthly returns for the entered tickers; it does not fetch verified historical prices.
- The model starts with the entered amount and weights, then compounds its generated monthly returns.
- The buy-and-hold scenario stays invested along the generated path.
- The simplified trend scenario reacts to the generated monthly path; it is not a historical 200-day moving-average test.
Ready to test a portfolio?
Add tickers, set allocations, and compare illustrative strategy scenarios before researching verified historical performance.
Check your understanding
Answer each question, then open the explanation.
1. Does this lesson’s five-year illustrative model establish a portfolio’s actual historical return?
Show answer and why
Answer: No. It shows a result under model assumptions.
Why: The current lesson labels the activity as illustrative; do not relabel it as a measured historical backtest.
2. What should remain consistent when comparing two runs of the model?
Show answer and why
Answer: The period and other assumptions apart from the input you intend to compare.
Why: Changing several inputs at once obscures the reason for a difference.
3. What should you check before using a model result in planning?
Show answer and why
Answer: Its assumptions and how it treats fees, taxes and cash flows.
Why: An internally correct calculation can omit costs or circumstances that matter to a real portfolio.
AI responses are for educational purposes. Always verify with official course materials.
This lesson teaches a concept. It is general education, not advice about your money. Before you act on anything you learn here, speak to someone licensed.
AI responses are for educational purposes. Always verify with official course materials.
This lesson teaches a concept. It is general education, not advice about your money. Before you act on anything you learn here, speak to someone licensed.
This lesson teaches a concept. It is general education, not advice about your money. Before you act on anything you learn here, speak to someone licensed.
