Investors often seek out patterns and trends to guide their trading decisions, and one such approach that captures attention is the seasonality of stocks. Seasonal trends can provide a strategic edge, illuminating periods of potential outperformance or underperformance. Today, we dive into the intriguing world of seasonal trading strategies, focusing on the historical performance of American Tower Corporation (AMT) through the lens of a backtested monthly seasonality strategy. This analysis aims to offer retail investors a clearer understanding of how such strategies could impact their trading decisions.
Company Overview
American Tower Corporation is a global player in the real estate investment trust (REIT) sector, specializing in wireless and broadcast communications infrastructure. Their extensive portfolio includes communication towers, which are leased to various wireless service providers. AMT’s business model is grounded in providing the necessary backbone for modern communication, which includes cell towers and other structures essential for wireless technology. As the world grows ever more connected, the demand for such infrastructure is expected to remain robust, making AMT an integral player in the telecommunications landscape.
Strategy Overview
The strategy in focus is a long-only monthly seasonality trading approach applied to AMT, without including commissions or the potential impact of slippage. Initiated with a starting capital of $10,000, the strategy involves entering long positions at the close of February, March, April, June, and September, and exiting them at the end of the respective months. The backtest spans two decades, from the beginning of 2003 to the end of 2022, covering 7302 days. During this period, the strategy was active for approximately 43.59% of the time, selectively engaging in the market during months historically favorable for AMT.
Key Performance Indicators
The strategy culminated in a final equity of $261,369.11, attaining a peak of $275,540.54. This translates to a remarkable return of 2513.69%, contrasted with a substantial 6701.80% buy & hold return over the same duration. Annually, the strategy delivered a 17.74% return, with the buy & hold approach yielding a higher 23.89% annual return. These figures highlight the robust growth of AMT but also point to the strategy’s conservative nature compared to a passive investment approach.
| Strategy | Buy and Hold | |
|---|---|---|
| Start Date | 2003-01-02 | 2003-01-02 |
| End Date | 2022-12-30 | 2022-12-30 |
| Duration | 7302 days | 7302 days |
| Exposure Time [%] | 43.59 | 99.96 |
| Equity Final [$] | 261369.11 | 722557.99 |
| Equity Peak [$] | 275540.54 | 980776.83 |
| Return [%] | 2513.69 | 7125.58 |
| Return (Ann.) [%] | 17.74 | 23.89 |
| Volatility (Ann.) [%] | 24.23 | 37.7 |
| Sharpe Ratio | 0.73 | 0.63 |
| Sortino Ratio | 1.38 | 1.21 |
| Calmar Ratio | 0.62 | 0.42 |
| Max. Drawdown [%] | -28.81 | -56.54 |
| Avg. Drawdown [%] | -3.49 | -3.88 |
| Max. Drawdown Duration | 735 days | 982 days |
| Avg. Drawdown Duration | 40 days | 30 days |
| # Trades | 60 | 1 |
| Win Rate [%] | 75.0 | 100.0 |
| Best Trade [%] | 91.04 | 7126.68 |
| Worst Trade [%] | -10.18 | 7126.68 |
| Avg. Trade [%] | 5.59 | 7126.68 |
| Max. Trade Duration | 92 days | 7300 days |
| Avg. Trade Duration | 52 days | 7300 days |
| Profit Factor | 8.43 | nan |
| Expectancy [%] | 6.22 | 7126.68 |
| SQN | 4.19 | nan |
Risk Management
Risk assessment is paramount in evaluating trading strategies. The annualized volatility of the strategy stood at 24.23%, compared to the buy & hold’s 37.70%, indicating a smoother equity curve. The Sharpe Ratio, a measure of risk-adjusted return, was 0.73 for the strategy, suggesting a decent but not exceptional excess return over a risk-free asset. The strategy experienced a maximum drawdown of 28.81%, significantly less severe than the buy & hold’s 56.54%, with the strategy’s average drawdown being -3.49% and drawdowns typically lasting around 40 days.
Trade Analysis
The backtest included 60 trades with a substantial 75% win rate, showcasing the strategy’s effectiveness. The best trade soared with a 91.04% gain, while the worst trade saw a manageable loss of 10.18%. On average, trades yielded a 5.59% return, and positions were held for an average of 52 days, with the longest trade duration being 92 days. The Profit Factor stood at 8.43, and the expectancy was an impressive 6.22%, demonstrating the strategy’s ability to capitalize on the seasonality of AMT’s stock.
Conclusion
This backtested monthly seasonality strategy provides a compelling narrative on AMT’s historical performance, demonstrating periods of consistent gains. While not outperforming a buy & hold approach, the strategy offers reduced volatility and drawdown, which might appeal to risk-averse investors. As with any strategy, backtesting is merely a simulation and cannot predict future results. However, it can provide valuable insights into potential seasonal trends that investors may consider when crafting their trading plans.
“Make the invisible visible. My goal is to shine a light on the subtle seasonal signals in the stock market, providing investors with the insight needed to make informed decisions. By breaking down the complexities of seasonality, I strive to empower our audience with knowledge and foresight, turning data into action.”