A strategy based on real estate-related ETFs has been developed as a way to diversify from the stock market. The Monthly Mover series strategies utilize the best trading periods of the month for selected instruments.
A strategy based on an ETF operating in real estate was developed as part of the search for instruments that provide a break from the stock market. The strategies from the Monthly Mover series utilize the best periods of the month for trading selected instruments.
Real Estate Investment Trusts (REITs) are undoubtedly a different class of instrument compared to stocks. To gain exposure, we can use a variety of instruments. We have chosen the ETF VNQ, which is a very liquid asset with management costs of only 0.13% annually, making it a negligible cost in our trading.
However, is VNQ an instrument worth considering for trading? Let's analyze this together using a ready-made strategy.
About REITs
REITs (Real Estate Investment Trusts) are companies that invest in income-generating properties, operating similarly to investment funds. They own various types of real estate and are required to distribute 90% of their income in the form of dividends. The benefits of investing in REITs include diversification, liquidity, and a steady income from dividends, but there are also risks associated with interest rates, market conditions, and specific properties.
VNQ is issued by Vanguard. Here is the portfolio composition of VNQ as reported by the issuer as of June 2024, which effectively shows the asset classes we are investing in by purchasing this ETF.
As we can see, VNQ provides us with broad exposure and a comprehensive overview of various types of REITs.
Now it's time to present the strategy.
Strategy Conditions
In the Monthly Mover series strategies, we utilize the best periods of the month for trading selected instruments.
Here we explore an interesting pattern, which is easiest to analyze by comparing these charts:
As we can see, there is a clear situation where the last few days of the month make the entire profit on this instrument, while the rest of the month is usually loss-making.
Entry rules
Opening a position is purely time-based and occurs on the 24th day of each month, with a market order at market close.
The strategy takes into account one more factor - seasonality.
Real estate is subject to fairly strong seasonal trends. February, April, and October are statistically very weak months, which is why they have been eliminated from trading.
Exit rules
The exit takes place on the first working day of the month. An emergency exit after 7 bars is implemented.
Backtest 1, Fixed $ Money Management
In this variant, we invest a fixed amount of $100k.
We test the period of the last 20 years from October 2004 to May 2024 (all data available).
Invested capital: $100'000
Test period in years: 20
Tested years: 10.2004 - 05.2024
Tested Instrument: VNQ
Equity chart for this test:
Basic statistics and results month by month:
Backtest 2, % Money Management
In this backtest, we invest in a strategy that constantly uses 100% of the current capital (starting with $100'000). This means that as the capital grows or decreases, the position value changes proportionally. The rest of the parameters remain unchanged.
The equity chart for this test looks as follows:
Basic statistics resulting from the test:
Trading Strategy Analysis
Net Profit and CAGR
The net profit of $275'000 in the analyzed strategy is significantly lower than the Benchmark (Buy & Hold SPY marked in yellow on the chart), which is above $570'802, translating to a CAGR of 7.21% vs 10.50%. This means that the analyzed strategy achieves a lower net profit and a lower average annual return.
Drawdown and Return/Drawdown Ratio
The Max Drawdown was 21.5% vs 55.20% in the benchmark, resulting in a better Return/Drawdown ratio of 6.36 vs 3.94. This indicates that the analyzed strategy was less risky and more stable, leading to better risk management compared to the benchmark.
Exposure
The Exposure was only 16.45% vs 100% in the benchmark. This means that the analyzed strategy was significantly less exposed to market risk, yet still achieved relatively good results, providing the opportunity for it to be sensibly incorporated into a portfolio of other strategies.
Winning Percent
65% of trades were profitable, highlighting the effectiveness in generating positive results and providing comfort 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 (see why). Instead, the strategy has one exit signal or additional safety exit after X bars (time-based stop loss). Diversification within the portfolio of various strategies serves as protection against the strong impact of a single stock price change on the entire portfolio.
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 (detailed study). 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, 178, is significantly lower than Stockpicker-type strategies, which can provide even over 100'000 transactions in resilience tests. As a result, the strategy has lower resilience scores and requires more vigilant observation in real trading.
Additionally, monthly filters slightly lower the resilience. We adhere to the principle that the fewer parameters, the greater the strategy's resilience. Therefore, we make efforts to ensure that our strategies have as few parameters as possible and to only select parameters that have a significant impact on the strategy's effectiveness while also aligning with its character.
Recommended Instruments
The primary recommended instrument for this strategy in Algocloud is VNQ, which has shown good historical results.
Primary Instrument: VNQ
Pattern Day Trader
The strategy did not close any trades on the same day, so it does not meet the Pattern Day Trader (PDT) criteria. Therefore, it is also suitable for accounts below $25k.
Correlation
To check the correlation of the strategy with others, go to the correlation page.
In correlation tests, the strategy performs well, showing little to no correlation or even negative correlation with most other strategies. The exception is the Emerging Monthly Mover, where we have a correlation of around 0.4-0.5.
Despite the low correlation of the strategy itself, it is important to note that the VNQ instrument is positively correlated with stock indices. In most periods, this is an average correlation, but there are periods of high correlation. The levels of correlation between VNQ and SPY are shown below.
Source: PortfolioVisualizer (https://www.portfoliovisualizer.com/asset-correlations?s=y&sl=1lMQGcwbmagxcfAnHtEFVw)
Summary & Strengths and Weaknesses of the Strategy
Over the course of 20 years, the analyzed strategy had 2 losing years, which is a very good result for this type of strategy. The Max Drawdown was 21.5%, which is relatively low in the context of long-term investment strategies.
Strengths of the strategy:
Low capital commitment: It offers a small capital commitment with an exposure of 16.45%, meaning it can be successfully incorporated into a portfolio with other strategies.
Low correlation with other strategies: This is one of the reasons for its success, especially in real estate as an instrument.
Moderate Drawdown: The Max Drawdown of 21.5% compared to 55.20% in the Benchmark shows that the strategy was less risky.
High Winning Percent ratio: 65% of trades ended in profit, highlighting the psychological comfort of using the strategy.
Percentage of trades closed on the same day: The strategy did not close any trades on the same day, making it suitable for accounts below $25k.
Weaknesses of the strategy:
Profit size: In the analyzed strategy, the Net Profit was $275'060, while the Benchmark achieved $570'802. The CAGR was 7.21%, lower than the Benchmark's 10.50%.
Robustness: The strategy has significantly fewer trades than Stockpicker-type strategies, which may be considered a weakness in terms of robustness. The strategy requires closer monitoring and integration into a portfolio of more resilient strategies.
In summary, this trading strategy shows stable results with a moderate CAGR and relatively low drawdown, and most importantly, very low capital commitment. The lower number of trades and reduced robustness are normal for Monthly Mover types of strategies, but that may require closer monitoring.
Download is free - login required
What you receive in the package for this strategy:
SQX file ready to be used on the Algocloud and StrategyQuant platforms.
Pseudocode that describes all the rules in an easy-to-understand way.
If you need the strategy code in formats such as TradeStation (EasyLanguage), MultiCharts, MT4, or MT5 (MQL), please contact us regarding this matter.
Disclaimer
The results obtained from historical data do not guarantee future outcomes. The effectiveness of a strategy can change over time. Backtesting is a tool that allows for the analysis and evaluation of an investment strategy based on historical data. Various factors, such as market changes or economic conditions, can influence the effectiveness of a strategy over time.
Investing always involves risk. This material is not investment advice. We share our experience and algorithms for educational purposes. We make efforts to ensure that our algorithms are error-free, but neither we nor the tools we use guarantee the absence of technical issues. Any decisions to use a particular strategy are made at your own risk and should be preceded by careful understanding and verification. You should always carefully consider your investment goals and risk tolerance before making investment decisions.
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