Strategy Leaderboard

Strategy Leaderboard is the discovery surface for strategies. Use it to inspect curated strategy families and their ranked variants, then copy the ones you want into your Library for reuse.

Open Strategy Leaderboard →

Core Concepts

Every strategy is built from a small set of composable pieces:

Building Block	What It Does
Condition	A named allocation rule. A strategy has one or more conditions (for example "Risk-On" and "Risk-Off"). Each condition has its own set of asset positions with target weights.
Signal	A boolean rule that decides which condition is active on any given day. Signals are evaluated daily; the first condition whose signal is true wins. The last condition must be a fallback (no signal); it's the default when nothing else fires.
Position	A single asset position within a condition: a ticker, an allocation weight (positions within a condition sum to 100%), and optional modifiers (leverage, expense ratio, etc.).
Rebalance Policy	Controls when the strategy rebalances its internal positions back to target weights, by time, by drift threshold, or both. See the Rebalancing guide for details.

A one-position buy-and-hold strategy still uses the same model: one condition, one position, and no signal.

Strategy Types

The Strategy Builder supports three common patterns:

Buy & Hold (single ticker): hold one asset permanently. One condition, one position. Example: 100% SPY.
Buy & Hold (multi-ticker / asset allocation): hold multiple assets at fixed weights with internal rebalancing. One condition, multiple positions. Example: 60% SPY / 40% AGG rebalanced monthly.
Signal-based (tactical / LFLR): switch between conditions based on a signal. Two or more conditions, the first with a signal, the last as the fallback. Example: hold UPRO when SPY > 200-day SMA, otherwise hold SHY.

Signal Types

Signals are the rules that trigger condition switches. Each signal evaluates a condition on each trading day and produces a true/false result.

Signal	Parameters	When It Fires
SMA	Period (days)	Price is above the simple moving average
EMA	Period (days)	Price is above the exponential moving average (more responsive to recent data than SMA)
MA Hysteresis	Entry MA, exit MA, MA type	Price re-enters above the faster entry moving average and stays on until it breaks below the slower exit moving average
VIX Threshold	Threshold level	CBOE Volatility Index is below the threshold (low fear = risk-on)
RSI	Period, threshold	Relative Strength Index is above the threshold (momentum is positive)
Momentum	Lookback (days)	Price is higher than N days ago (positive trend)
Drawdown	Threshold (%)	Current decline from all-time high is less than the threshold

All signals are evaluated with a 1-bar lag to prevent lookahead bias. A signal computed on Monday's close becomes tradable on Tuesday's open. See the Signals documentation for detailed explanations of each signal type and their parameters.

Composite Signals

Combine multiple atomic signals into a composite signal tree using logic operators:

AND: all child signals must be true.
OR: at least one child signal must be true.
NOT: inverts a child signal.

Example: price > 200-day SMA AND VIX < 25 keeps the condition active only when both rules are true.

Condition Evaluation Rules

When a strategy has multiple conditions, the engine evaluates them in order:

Conditions are checked in the order they appear in the strategy (first-match wins).
The first condition whose signal is true becomes active.
The last condition must have no signal; it's the fallback that activates when no other signal fires.
When the active condition changes, the engine forces an immediate rebalance to the new condition's target weights.

Position allocations within each condition must sum to 100%. Different conditions can hold completely different assets (for example, a risk-on condition with 100% UPRO and a risk-off condition with 100% SHY).

Strategy Leaderboard, Library, and Workspace

Strategy Leaderboard is the browsing surface for curated strategy families and their ranked variants.

Leaderboard ranks are computed over the shared window shown on the page. Expanded rows also show the full backtest window when it differs from the ranking interval, so metrics and longer history are not conflated.

Library is the ownership surface. After you copy or save a strategy, manage it from Workspace and reuse it in backtests and tactical workflows.

Workspace is where you reopen analyses and manage the reusable items you own.

Example: Classic 60/40

Example of a two-asset allocation with monthly rebalancing:

Type: Buy & Hold (multi-ticker)
Condition: 1 condition (fallback, no signal)
Positions: SPY at 60%, AGG at 40%
Rebalance: Monthly, time-based

Example: Leveraged Trend-Following (LFLR)

Example of a signal-based strategy with a leveraged risk-on state:

Type: Signal-based (2 conditions)
Risk-On condition: Signal = SPY > 200-day SMA. Position: 100% UPRO (3x leveraged S&P 500)
Risk-Off condition: Fallback (no signal). Position: 100% SHY (short-term treasuries)
Rebalance: Monthly

Use .SIM tickers (e.g. UPRO.SIM) for extended history that goes back further than the ETF's listing date.

Using Strategies in Portfolios

Once saved, a strategy becomes a reusable building block. In the Portfolio Backtest, each strategy occupies an "allocation" (an independently-managed sub-portfolio with its own allocation weight). Allocations rebalance internally according to their own policy, then the portfolio rebalances across allocations.

Each allocation manages its own internal positions. Portfolio-level rebalancing then manages the split across allocations.

Ticker Modifiers

Each ticker input has a gear icon that opens the modifier modal. Modifiers let you apply leverage, expense ratios, fill-backward history, return/volatility targets, and other transforms to individual tickers within a strategy, all using testfol.io-compatible expressions.

See the full Ticker Modifiers documentation for the complete reference, expression syntax, and examples.