Inspirations

Bonds have always been considered a hedge against stocks. I introduce a strategy from the Monthly Mover category, this time focusing on US Treasury bonds. We are exploring the observation that this instrument owes practically all of its returns to the last part of the month.

From the perspective of an international investor, the American bond market seems quite complicated. This is due to the specific naming of bonds.

The entire American bond market is referred to as "Bonds." However, it is important to know that it is internally divided into three categories:

• Short-term, called Treasury Bills (T-Bills), with a maturity period of less than a year. Popular ETF - TBIL (3M)

• Medium-term, called Treasury Notes (T-Notes), with a maturity period of 2 to 10 years. Popular ETF - IEF (7-10Y)

• Long-term, called Treasury Bonds (T-Bonds), with a maturity period of 20 to 30 years. Example ETFs - TLT (20Y)
  

Today, we will focus on exploring a pattern on long-term bonds, specifically on TLT.

Why even bother with bonds? For decades, they have been cited as an example of an instrument that stabilizes a stock portfolio, acting as a low or even negatively correlated instrument to stock prices. Just read about the 60/40 portfolio.

We won't delve into the details of treating bonds as an investment here. Statistically, it is an investment with much lower returns compared to stocks, and as shown in the years 2020-2023, this stable haven turned out to be a nightmare for many financial institutions (with a price drop of over 48%), contributing to the banking crisis in the USA in early 2023.

However, since we are looking for instruments and strategies that are low or negatively correlated with stocks, today we are focusing on TLT. Let's get to work!

Is it true that there is a negative correlation between TLT and S&P500 (SPY)?

The chart below shows that in the long term - YES, although in the last few years the correlation was positive.

Daily correlation:

Source: portfoliovisualizer.com

In general of 2003-2022, bonds were inversely correlated with stocks. The year 2022 was exceptional because stocks and long-term bonds were falling at the same time, which was painfully felt by investors using the 60/40 model. Last few years are more correlated then usual.

Key Components of the strategy

• Exploration of the monthly pattern on TLT.

• The strategy includes two simple filters to improve its effectiveness.

  
  

Backtest 1, Fixed $ Money Management

In this variant, we invest a constant amount of $100k. We test the period of the last 22 years from July 2002 to May 2024.

• Invested capital: $100,000

• Test period in years: 22

• Tested years: 07.2002 - 05.2024

• Tested Instrument: TLT

Equity Chart for this test:

Basic statistics and results month by month:

Examples of transactions on the chart:

Backtest 2, % Money Management

In this backtest, we are investing in a strategy that constantly uses 100% of the current capital (starting with $100'000 capital). This means that as the capital grows or decreases, the value of the position changes proportionally. The rest of the parameters remain unchanged.

The equity chart for this test looks as follows:

Basic statistics resulting from the test:

Additional information about the strategy

Net Profit and CAGR

The net profit above $125'137 in the analyzed strategy is significantly lower than the Benchmark (Buy & Hold SPY marked in yellow on the chart), which is above $792'729, translating to a CAGR of 3.90% vs 11.00%. This means that the analyzed strategy achieves a much lower net profit and lower average annual return, indicating its lower effectiveness in generating profits over the long term.

Exposure

The exposure in the analyzed strategy was 20.8% vs 100% in the benchmark. This means that the analyzed strategy was only "in the market" for 1/5 of the month. This makes it less exposed to market risks, yet it achieved relatively good results, highlighting its effectiveness under conditions of lower market exposure. Click for more about exposure.

Drawdown and Return/Drawdown Ratio

The Max Drawdown in the analyzed strategy was 7.00% vs 55.20% in the benchmark, resulting in a much better Return/Drawdown ratio of 9.70 vs 4.1. This means that the analyzed strategy is less risky and more stable because the maximum capital drawdown is smaller, leading to better risk management compared to the benchmark.

Winning Percent

The Winning percent in the analyzed strategy was 59.4%. This indicates that this percentage of transactions resulted in profit, emphasizing the strategy's effectiveness in generating positive results and giving the user greater confidence in the frequency of profit generation.

SL & TP

The strategy does not use typical stop-loss and take-profit orders, although there are no obstacles to implementing them. According to our tests, for most ETF/stock strategies, these settings worsen results. Diversification within the portfolio of various strategies serves as protection against the strong impact of a single stock price change on the entire portfolio. Go to the stop loss order page.

Market Regime

The strategy has been tested in all basic market regimes and includes filters implemented based on this analysis.

Trading Costs

Trading costs and slippage were taken into account in the backtests, which occurred in real account tests for the Alpaca broker. With a diversified portfolio of stocks and strategies, transaction costs can determine your profit or loss, so take the time to thoroughly test and choose a broker.

Robustness

The number of historical transactions, 165, is significantly lower than that of Stockpicker-type strategies, which can provide even over 100'000 transactions in stress tests. This is the negative side of this strategy.

The strategy has in general 3 parameters factors to entry and one for Exit. We adhere to the principle that the fewer parameters, the greater the robustness of the strategy. Therefore, we make efforts to ensure that our strategies have as few parameters as possible and to select only those parameters that have a significant impact on the strategy's effectiveness while also aligning with its character.

Recommended Instruments

The recommended primary instrument for this strategy on Algocloud is TLT, which has shown the best historical results.

• Primary Instrument: TLT
  

Pattern Day Trader

The strategy statistically did not close any trades on the same day, so it does not meet the Pattern Day Trader (PDT) criteria. This means it can also be used on smaller accounts.

Correlation

The strategy is inversely correlated with most other strategies, which means it should balance a stock strategy portfolio well. This is a significant advantage. To check the correlation of the strategy with others, visit the correlation page.

Summary & Strengths and weaknesses of the strategy

Over the course of 22 years, the analyzed strategy had 5 losing years, which is a relatively good result for this type of strategy. The Max Drawdown was 7.00%, which is a relatively low level in the context of long-term investment strategies.

Strengths of the strategy:

• Reverse correlation to other strategies: The correlation to most other strategies is negative, which means it should balance a stock strategy portfolio well.

• Low Drawdown: The Max Drawdown in the analyzed strategy was 7.00% compared to 55.20% in the Benchmark. This shows that the strategy was less risky and more stable.

• No same-day transactions: A plus of the strategy is the ability to apply it to smaller accounts.

• Low capital commitment: The strategy offers relatively low capital commitment with an Exposure of 20.8% vs Benchmark 100%, meaning it can be successfully used in a portfolio alongside other strategies.
  

Weaknesses of the strategy:

• Profit Stability: In the analyzed strategy, Net Profit was above $125'137, while the Benchmark achieved above $792'729. The CAGR was 3.90%, which is significantly lower than 11.00% for the Benchmark.

• Robustness: The strategy has significantly fewer transactions than other Stockpicker-type strategies, which should be considered a weakness in terms of robustness. The strategy, therefore, requires closer monitoring and integration into a portfolio of more robust strategies.

• Moderate Winning Percent ratio: 59.4% of transactions ended in profit, which is lower than our average.
  

Summary

Bonds are not, and never will be growth leaders. Compared to other stock strategies, the annual return of this strategy is not overwhelming. The strategy provides a return of only about 4% annually, but using capital for only about 20% of the time, resulting in approximately 21% annualized return.

However, the main advantage of this strategy is its reverse correlation to stocks statistically provided by bonds, as seen in the test results. While bond and stock price declines were exceptionally parallel in 2022, as shown in the longer history, this is more of an exception than a rule. The demonstrated strategy emerged defensively from this period, showing positive results in all turbulent years.

If you want to include bonds in your portfolio, this strategy is definitely worth considering as an alternative to a simple buy and hold approach.

What you get in the package for this strategy:

• .SQX file ready to use on the Algocloud and StrategyQuant platforms.

• Pseudocode that describes all the rules in an easy-to-understand way.
  

If you need the code for this strategy in formats such as Tradestation (easylanguage), Multicharts, MT4, or MT5 (MQL), please contact us on this topic.