4 Strategies
Strategies
Four rules-based models with defined allocations, backtests, and continuing paper journals.
Explore collectionModel library
Paper Trade
A hands-on lab for testing investment ideas before real money is involved. Explore rules-based strategies, follow their simulated journals, and compare each result with a clear benchmark. The goal is not to predict the future; it is to make every assumption visible.
Simulation only
This is an educational paper portfolio, not investment advice or a record of real trades. Past or simulated results do not guarantee future returns.
3 Experiments
Experiments
Focused research questions where the point is to show the full evidence, including the inconvenient parts.
Explore collectionPortfolio foundations
Why do so many of these paper trades use SPY and QQQ?
They are familiar, liquid index ETFs that make a useful learning laboratory. SPY is a broad slice of large U.S. companies. QQQ holds 100 large non-financial companies listed on Nasdaq and gives the portfolio a noticeably stronger growth-and-technology tilt. They are tools for comparing ideas here, not a claim that either one belongs in every portfolio.
SPY
The broad U.S. stock starting point
It tracks the S&P 500, so one purchase spreads money across many large American companies and sectors. That is broader than buying a few stocks, but it is still mostly large U.S. companies.
QQQ
A larger bet on Nasdaq growth
It tracks the Nasdaq-100. It includes many household-name innovators, but it excludes financial companies and can be much more influenced by a small group of large technology and growth names.
A 50/50 SPY-QQQ mix is not two completely separate baskets. Many of QQQ's largest companies are already inside SPY. The mix keeps broad-market exposure, then deliberately turns the dial up on the Nasdaq-100 names that appear in both funds.
Why start here
- Easy to understand: a broad market reference plus a clear growth tilt.
- Easy to compare: buy-and-hold SPY, QQQ, and a 50/50 mix give each paper model honest benchmarks.
- Easy to trade in a simulation: the funds are widely followed, priced every trading day, and have long enough records for repeatable tests.
- Easy to diagnose: when a model wins or loses, we can separate the effect of the rules from the effect of simply owning more Nasdaq growth.
What this leaves out
- Both funds are U.S. large-cap equities, so neither adds much exposure to international stocks, small companies, or bonds.
- QQQ increases concentration. A few giant companies and the technology sector can have an outsized effect on the result.
- Broad diversification reduces single-company risk; it does not stop a market-wide decline.
- A clean historical backtest can hide the hard part: staying with a plan when it is temporarily losing.
Four useful history lessons
The 2000-02 technology unwind
The dot-com bubble is the hard reminder: QQQ fell by roughly 80% from its 2000 peak to its 2002 low and did not regain a prior high until around 2015. Leadership can reverse for years, not just days; a portfolio tilted toward the previous winners can feel excellent before the reversal and painfully concentrated afterward.
The 2008 global selloff
Owning many companies is helpful, but it is not the same as owning different asset classes. In a broad panic, stock funds can fall together.
The 2020 shock and rebound
Markets can fall very quickly and recover surprisingly quickly. A rule that reacts late can miss part of either move; a rule that reacts too often can create its own damage.
The 2022 rate reset
When interest rates rise, investors often pay less for profits expected far in the future. That makes growth-heavy exposure especially sensitive to the price of money.
That is why this library does not treat SPY and QQQ as the answer. Strategies 01-03 use them as a transparent stock-market test bed, with different ways of managing risk. Strategy 04 deliberately changes the ingredients toward dividend funds. Future experiments can add international stocks, small caps, bonds, real assets, or simpler balanced portfolios when there is a clear question worth testing.