Bottom 300 (Lowest Price Buckets)

Overview

This strategy ranks all stocks by price (ascending) and buys the lowest-priced bucket(s)—e.g. top 10, top 50, top 100, or top 300. The goal is to test whether extremely low-priced stocks (often ignored or distressed) generate systematic returns after rebalancing.

Critical constraints: Low-price names tend to have weak liquidity and, in India, frequent upper/lower circuits. Backtests must include liquidity filters, execution caps, and a circuit execution model (e.g. no trade on circuit days, or a penalty assumption).

Strategy logic

• Ranking: Sort universe by price ascending; assign rank 1 to the cheapest.
• Buckets: Define buckets by rank ranges (e.g. 1–300, 301–600). "Bottom 300" = ranks 1–300.
• Rebalance: At each rebalance date, hold the selected bucket(s). Rebalance frequency (e.g. quarterly, annual) must match data and execution assumptions.
• Portfolio construction: Equal weight within bucket, or cap-by-liquidity with a max single-stock weight.
• Execution: Apply liquidity and circuit constraints so backtested returns reflect realistic tradability.

Parameters (knobs)

• Bucket definition: Preset (Top 10 / 50 / 100 / 300) or custom rank range; multi-select for comparing buckets.
• Rebalance frequency: Quarterly (3M), Semiannual (6M), Annual (1Y), 2Y, 3Y. If data is annual, rebalancing >1Y aggregates over multiple years.
• Liquidity filter: Minimum average daily traded value (₹) or volume; max % of ADTV allowed to trade per rebalance (e.g. 5% / 10% / 20%). If Excel lacks this, use as simulation parameters.
• Circuit execution model: Ignore circuits (naive); delay execution until tradable day; or apply slippage penalty on circuit events.
• Portfolio construction: Equal weight vs cap-by-liquidity; max single-stock weight.

Backtest design checklist

• Survivorship bias and delistings: Include dead/delisted stocks in the historical universe.
• Corporate actions: Use split/bonus-adjusted price series.
• Bid-ask spread and impact: Microcaps are expensive to trade; model costs.
• Circuit locks: Execution uncertainty when buy signal on upper circuit or sell on lower circuit; model delay or penalty.
• Stale last traded price: Illiquid names may have stale LTP; adjust or flag.
• Pump-and-dump / governance: Penny stocks carry event risk; consider filters or caveats.
• Portfolio turnover and tradability: Assess whether strategy is executable at target AUM.

Common failure modes

• Liquidity: Cannot execute at assumed prices; backtest overstates returns.
• Circuits: In stress, many names lock; assumed exits may be impossible.
• Survivorship bias: Ignoring delistings inflates historical returns.
• Costs: Spread and impact erase edge in thin names.
• Regime: Low-price edge may be period-specific (e.g. small-cap rallies).

Our notes & suggestions

Upload your own backtest table (Excel) to see bucket returns by year and cumulative returns. Use the parameter controls to explore bucket choice, rebalance frequency, and liquidity/circuit assumptions. When data lacks liquidity or circuit fields, treat those as modeled impact only.