In the US, the defense budget, is announced by the President and the Congress at the beginning of the year. The beneficiaries of the defense budget are mostly American defense companies, such as Lockheed Martin. This strategy allows you to leverage creation of the US defense budget to defend your personal budget.
Inspiration
In the United States, the federal budget, including the defense budget, is announced by the President and presented to Congress usually at the beginning of the calendar year. Traditionally, the federal budget for the next fiscal year is presented in February. This process involves the President submitting a budget proposal to Congress, which then discusses and makes decisions regarding various expenditures, including the defense budget.
Who is a major beneficiary of the defense budget? Of course, American defense companies.
LMT, or Lockheed Martin, is an American defense and aerospace company and one of the world's largest suppliers of defense equipment and technology related to the defense industry.
The company's "products" that most of us may be familiar with include:
Fighter jets: F16, F22 Raptor, F35 Lightning.
Multi-purpose aircraft C-130 Hercules
HIMARS systems
and many, many others.
In this article, you will learn how to utilize the period of creating the US defense budget to defend your personal budget :)
Key components
Exploration of seasonal patterns in LMT stocks.
The strategy is based on specific dates. We completely ignore trends, news, company valuation, and the overall market situation.
Entry Rules
Entry occurs in mid-December, with a Market order to close the market.
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Exit rules
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The exit occurs "On Bar Close" at the beginning of May.
Backtest 1, $ Money Management
In this variant, we invest a constant amount of $100k.
We have been testing for the last 28 years*:
Capital chart for this test:
Test results:
The average annual result was over 10%, which, when using capital for 37% of the year, gives an annualized return of approximately 28%.
*The pattern was successfully tested on an earlier period from 1977 to 1994, during which the Win rate was 72%, the average return was 13.35%, and the Annualized Return was 38.87%. The total period of both tests is therefore 45 years. Unfortunately, SQX does not have LMT data before 1995.
Backtest 2, % Money Management
In this backtest, we invest in a strategy that constantly allocates 100% of the current capital (with an initial capital of $100k). This means that as the capital increases or decreases, the value of the position changes proportionally. The rest of the parameters remain unchanged.
The capital chart for this test looks as follows:
Basic statistics resulting from the test:
The maximum open drawdown is shown on the chart and was 31% during the Covid crash in 2020. However, holding onto this position until the proper closing date reduced the loss in this exceptional year to about 1%. In the case of hypothetically applying a stop loss, for example, at 25%, the loss in that year would have been 25% instead of the actual 11%. This is an example that stopping losses usually does not improve strategy results.
Applying risk management and reinvesting all profits in the next transaction results in a 5x increase in strategy earnings over the years. The total profit from the initially invested $100k amounted to $1.23M.
Additional information about the strategy
SL & TP
The strategy does not use typical stop loss and take profit levels, although they can potentially be implemented. According to our tests, for most ETF and stock strategies, SL settings worsen the results (see why). The diversification within the strategy portfolio serves as protection against the strong impact of potential price changes on individual stocks. However, the company LMT is considered not only as a defensive company but also as a defensive stock in turbulent times.
Market regime
The strategy has been tested in all major market regimes and has performed well in different periods, despite its simplicity.
Trading costs
The backtests include trading costs and slippage typical for the strategy, which were observed in real account tests with the Alpaca broker (detailed study). With a diversified portfolio of stocks and strategies, transaction costs can significantly impact your profit or loss, so take the time to thoroughly test and choose a broker.
Robustness
The strategy was not generated automatically or optimized automatically to fit historical data (read why).
The main concern with seasonality strategies is the low number of trades. We cannot directly compare it to the number of trades obtained in backtests of stockpicker-type strategies.
Seasonal patterns, by their nature, will never have a large number of trades.
Recommended instruments
The primary instrument is LMT.
Pattern Day Trader
The strategy is suitable for use on smaller accounts as well. The holding period is over 95 business days, which does not meet the PDT requirement.
Correlation with other strategies
The strategy aligns with trends related to the first half of the year. It can be correlated with other trading systems during this period. But we can assume that also has a different driver than most of them. Results show that LMT, a defensive type of company is less correlated with most stocks. Visit the correlation page.
Below is the general correlation of LMT with the S&P500 index:
Summary & Strengths and weaknesses of the strategy
The strategy provides an opportunity for you to benefit from the US defense budget, with LMT being the beneficiary. The defense business, due to conflicts around the world, probably (unfortunately) has a bright future ahead.
The pattern has been successfully tested since 1977, with a win rate of about 76% and an average return of 11.04% over those 90 working days, which is a very good result for such a "defensive" company like LMT.
The presented strategy is very easy to implement, even manually. If you value your time, we suggest entrusting this work to simple and effective algorithms, so you don't have to worry about keeping track of deadlines. Especially since by using capital precisely for only part of the year, you can use multiple systems simultaneously.
The main concern one may have with a seasonality strategy is the number of transactions. Seasonal patterns, by their nature, will never have a large number of transactions. What matters more in them are:
The pattern's alignment with nature, business patterns, or consumer behavior patterns.
A representative number of years - we consider a minimum of 15-20 years.
A longer pattern period. We use patterns that last at least a few weeks, preferably months.
There have been many interesting scientific studies on seasonal patterns in financial markets. They confirm that seasonality can often have more power than trends. We enjoy studying and exploring them for you. However, we acknowledge that patterns can evolve. That's why we review and make any necessary adjustments to our seasonal strategies once a year. The subsequent published versions will be available to you on this website.
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What you get 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.
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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