SeasonAlpha's Plain-Vanilla strategies bundle 24 simple, rule-based seasonal strategies and backtest them on the ticker you choose. Each strategy enters and exits on fixed calendar rules — such as the classic Sell in May (enter on the last trading day of October, exit on the 3rd trading day of May), September avoidance, the turn-of-the-month effect, the January Barometer or the Santa Claus rally. For every strategy the tool builds an equity curve starting from 1,000 euros, lists all individual trades and runs a significance test to check whether the returns differ statistically from zero. At a glance you see how a fixed seasonal plan would have performed historically.
Several metrics help you judge a strategy, and you should read them together. Return appears as CAGR (compound annual growth rate) and as the final value of a 1,000-euro portfolio. The win rate is the share of profitable trades — but it says nothing about the size of the gains. Max drawdown shows the largest peak-to-trough decline and thus the emotionally hardest scenario. The Sharpe ratio (return per unit of risk) and the profit factor (gross profits divided by gross losses; above 1 is profitable) add further quality measures. Optionally you can enable a fixed or trailing stop-loss and watch how it changes the metrics.
Methodologically the tool uses the ticker's real closing prices: entry and exit always happen at the close of the signal day, exactly per the strategy rule. Trading days are counted in an exchange-specific, holiday-aware way — a third trading day of May for a XETRA stock may fall on a different calendar day than for an NYSE stock. There is no optimisation: the rules are fixed and applied identically year after year, which avoids overfitting to the past. The backtest is look-ahead-free — each trade only uses information available on the signal day, for example when the January Barometer decides on a February entry only after month-end. Everything is computed in the browser from SeasonAlpha's maintained price data.
The Plain-Vanilla strategies are a tool for putting seasonal patterns into context, not investment advice and not a guarantee of profit. Backtests look backwards and ignore trading costs, taxes and slippage; real results would be lower. Some strategies rely on just a handful of trades per decade — so check the number of trades and the significance test before reading meaning into a pattern. Seasonal effects can weaken or vanish once they become widely known. Use the analyses as additional context for your own research, not as your sole basis for decisions. Past patterns do not guarantee future results.
Frequently Asked Questions
Are the backtested returns an investment recommendation? No. The strategies are rule-based historical backtests that illustrate seasonal patterns, not investment advice. All metrics are based on past data for the selected ticker. Past results do not guarantee future performance, and backtests ignore trading costs, taxes and slippage.
What does a 70 percent win rate mean? The win rate is the share of trades with a positive return. 70 percent means 7 of 10 historical trades closed in profit. It says nothing about the size of gains or losses — CAGR, profit factor and max drawdown cover that. A high win rate can still come with a few large losses.
How are the metrics calculated? Each strategy follows fixed entry and exit rules (e.g. last trading day of October to the 3rd trading day of May for Sell in May), applied identically every year without optimisation. From the closed trades the tool computes CAGR, win rate, max drawdown, Sharpe ratio and profit factor, plus an equity curve from a 1,000-euro starting capital. Entry and exit always occur at the closing price.