3 Long-Term Strategies That Work

At Quantified Strategies, we focus on strategies that are simple, practical, and backed by data.

In this post, we’ll walk you through three long-term trading strategies that aim to reduce drawdowns, ride bull markets, and potentially outperform buy-and-hold with less stress. These are the 3 long-term strategies that work:

Table of contents:

1. The 200-Day Moving Average Strategy

Paul Tudor Jones, one of the most successful hedge fund managers of all time, once said that the 200-day moving average is the first indicator he looks at. Why is this simple line so powerful?

Let’s break it down.

The 200-day moving average (200DMA) is a trend-following indicator. It smooths out price action by averaging the past 200 days of closing prices. When the price is above this average, the market is in an uptrend. Below it? That often signals trouble. Historically, the average has kept you out of major bear markets (that’s why Tudor Jones uses it).

Basic Strategy:

Buy when the S&P 500 closes above its 200-day moving average.
Sell when it drops below.

Backtested results (since 1960):

Annual return: 6.6%
Max drawdown: 28%
Time in market: ~70%
Compare that to buy-and-hold: 7.1% annual return, but with a 56% drawdown.

This strategy helped you avoid major downturns, such as the 2008 financial crisis. You would have exited before the crash and re-entered after the market bottomed in 2009, avoiding a 55% loss.

Bonus: Use It as a Filter

The 200DMA also works well as a filter for short-term strategies. For example, in a simple RSI(5) mean-reversion setup:

Buy when RSI(5) < 35
Sell when RSI(5) > 50

Adding the 200DMA as a filter—only taking trades when price is above the 200DMA—improves performance:

Drawdown drops from 31% to 14%
Equity curve becomes smoother
New equity highs occur more frequently

On the other hand, using the same strategy below the 200DMA leads to erratic performance and higher volatility, about twice as high.

2. The Golden Cross Strategy

The Golden Cross is a classic trend-following setup. It occurs when the 50-day moving average crosses above the 200-day moving average. The reverse—called a Death Cross—signals a potential bear market.

Basic Rules:

Buy when the 50-day MA crosses above the 200-day MA (Golden Cross).
Sell when the 50-day MA crosses below the 200-day MA (Death Cross).

Long-Term Results (since 1960, S&P 500):

Total trades: 33
Win rate: 79%
Average gain per trade: 15.7%
Annual return: 6.7%
Max drawdown: 33%
Time in market: ~70%
Risk-adjusted return: 9.6%

While this strategy underperforms buy-and-hold in raw returns, it shines in risk-adjusted terms and smoother equity growth.

A recent example: a Golden Cross in July 2020 followed by a 32.4% gain held until March 2022.

3. The 2-ETF Strategy: TQQQ and BTAL

This strategy combines aggressive growth with crash protection—perfect for those looking for a hands-off, once-a-year rebalance approach.

Related reading: –A simple 2 ETF strategy that beats Nasdaq

The Ingredients:

TQQQ: A 3x leveraged ETF tracking the Nasdaq-100.
BTAL: An anti-beta ETF that tends to rise when high-beta stocks fall.

The Rules:

In January each year, rebalance to:
- 33% TQQQ
- 67% BTAL

That’s it. No monthly tweaks. No market timing.

Why it works:

TQQQ gives explosive upside when the Nasdaq rallies.
BTAL hedges against volatility and crashes.
Annual rebalancing minimizes volatility drag.

Performance (2012–present):

Annual return: 18%
Max drawdown: 28%
Outperformed the Nasdaq in 8 of the last 13 years

Caution: TQQQ is leveraged and carries significant risk. It’s designed for short-term trading, not long-term holding. Make sure to factor in fees, taxes, and your own risk tolerance.

Final Thoughts

These three strategies each offer different strengths:

The 200DMA strategy focuses on reducing risk while staying aligned with long-term trends.
The Golden Cross gives you a classic signal for entering and exiting long bull markets.
The TQQQ/BTAL combo provides an elegant, high-performing portfolio with minimal effort.

Whichever you choose, having a rules-based, data-driven approach can help reduce stress and improve long-term results.

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