Growth/Value Style Selection research pack

An aggressive-tier strategy that reads each month whether growth or value leads the 11 sector ETFs and, in a confirmed bull market, holds one 3x index ETF (TQQQ, UPRO or SPXL), otherwise Treasuries, gold or T-bills. The numbers that mean luck cannot be ruled out (a deflated Sharpe ratio below 0.95) and its recent underperformance are disclosed in full below. It has not been verified in live trading; its AI league paper record is in progress. The pack holds the research report, the backtest source that re-runs every number below, and the strategy pack for the free AvalonQuant app, which runs it on an Alpaca Paper account.

Price

99 USDT. Paid in USDT on BNB Smart Chain (BEP-20) or TRON (TRC-20). Sign in, start an order, send the exact amount shown, and the download unlocks on this page once the payment confirms.

Tier: Aggressive

Uses leverage and carries higher risk. Luck has not been ruled out, and the AI league paper record is still in progress.

Risk disclosure

Deflated Sharpe ratio (DSR): 0.766
This strategy was selected from many backtested candidates. Its deflated Sharpe ratio is below the 0.95 confidence level, so the backtest result may be luck and cannot be ruled out as such.
2018Q4 bear market (2018-10-01 to 2018-12-31): strategy max drawdown -21.64%, S&P 500 (SPY) -19.20%
2020 Feb-Mar bear market (2020-02-01 to 2020-03-31): strategy max drawdown -19.81%, S&P 500 (SPY) -33.72%
2022 bear market (2022-01-01 to 2022-12-31): strategy max drawdown -22.54%, S&P 500 (SPY) -24.50%
Leverage: declared leverage 3x, SPXL 3x, TQQQ 3x, UPRO 3x
Max drawdown: -33.95%
Holdout window (2022-12-30 to 2026-10-05): strategy CAGR +29.74%, risk-adjusted 1.05; buy-and-hold S&P 500 (SPY) CAGR +22.16%, risk-adjusted 1.18
In this holdout window it trailed buy-and-hold S&P 500 (SPY) on a risk-adjusted basis.
AI league paper record: in progress — not a live-trading verification.

Backtest you can reproduce

CAGR	+33.42%
Max drawdown	-33.95%
Sharpe	1.06
Total return	+1664.2%
S&P 500 (SPY), same period	+324.0%
Period	2016-10-21 – 2026-10-05
Universe	11 SPDR sector funds (signal), TQQQ/UPRO/SPXL 3x index ETFs, TLT/GLD/SHY
Re-run	2026-10-06 · stock-style-selection-research-pack-0.1.1.zip

These numbers come from running the backtest source shipped in this pack, unchanged. The window is the latest 2,500 SPY sessions on the day it runs, with a 0.05% cost on every traded leg (at 0.10% it still compounds 32.75% a year). A later re-run covers a later window, so its numbers move.

How the strategy works (sample)

Every month, on completed closes and executed at the next open, it ranks the 11 SPDR sector funds by 11-month momentum (skipping the latest month), drops the weak-and-volatile ones and picks the leading style (growth: XLK, XLY, XLC; value: the rest). In a confirmed bull market (SPY above its 200-day average, no −8% week) it holds one 3x index fund — growth may pick TQQQ, UPRO or SPXL, value UPRO or SPXL — chosen by multi-horizon momentum and sized so the selected sectors' volatility targets 18% a year (never above 1x of the account, the rest in SHY). Otherwise, or when a guard trips (portfolio −15% from peak, −20% for the year, the held fund −16% from its high, SPY −8% in five sessions), it moves to the strongest of TLT, GLD and SHY.

What is inside

File	What it is	Size
START-HERE.md	Start here: get the app, set it up, reproduce the backtest	2.6 KB
stock-style-selection-0.1.1.zip	Strategy pack for the AvalonQuant app	33.7 KB
research/style_selection_strategy/README.md	Folder overview	848 B
research/style_selection_strategy/SOURCE.json	Source record	1.3 KB
research/style_selection_strategy/_shared/backtest_engine.py	Backtest engine (fills, costs, equity)	42.6 KB
research/style_selection_strategy/_shared/crypto_perp_data.py		7.7 KB
research/style_selection_strategy/_shared/perp_book.py		2.6 KB
research/style_selection_strategy/_shared/point_in_time_universe.py		6.4 KB
research/style_selection_strategy/assumptions-and-risks.md	Assumptions and risks	1.2 KB
research/style_selection_strategy/backtest/backtest.py	Backtest source (downloads its own data)	17.1 KB
research/style_selection_strategy/parameters.json	Full parameter set	664 B
research/style_selection_strategy/research-report.md	Research report, with the measured risk disclosures	2.9 KB

The report, the full parameter set (24 values), the backtest source and the strategy pack for the free AvalonQuant app. The app itself stays free and is provided as is.

Risks (from the pack)

Provided as is, without warranty. Not investment advice. You decide whether and how much to trade; losses are yours.
Aggressive tier. It passed Avalon's methodology checks but not every luck check. Deflated Sharpe 0.766 (< 0.95): the backtest result may be luck.
Leveraged ETFs. It holds TQQQ, UPRO or SPXL (3x daily). They decay in choppy markets and can fall about three times as fast as the index in a crash.
Recent lag. From 2023 to 2026 it trailed buy-and-hold SPY on a risk-adjusted basis (1.05 vs 1.18).
Drawdowns. Backtest maximum drawdown −33.95%; −22.54% in 2022, −21.64% in Q4 2018, −19.81% in Feb–Mar 2020.
No live verification. The AI paper league record is in progress; nothing here has been verified with real money.
Costs. The backtest assumes 0.05% per traded leg; at 0.10% it earned 32.75% a year.
Price data. Signals assume split- and dividend-adjusted daily prices. Keep the app updated; an older app version that reads unadjusted prices can mis-read a fund that just split.
Paper first. The app runs every pack in paper mode until you switch it to live yourself.

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Disclosure. Backtests are hypothetical simulations on historical data. They do not include every real-world cost, are not live results, and do not guarantee future returns. Educational research only, not investment advice.