For last 40 years, the best day of the week on the US stock market has been Tuesday. The next day with the highest return is Wednesday. We present a strategy that skillfully exploits this market behavior by opening positions only on Mondays and cashing in profits in almost 70% of cases over the following days.
Inspirations
The strategy explores this pattern by trading exclusively on Mondays, with additional conditions to increase its effectiveness. This approach allowed for achieving better results than the benchmark over a 30-year period with only 15% capital utilization, while maintaining a low correlation with other strategies.
Key Components
Time restriction - trading only on Mondays.
Additional components used to create a unique strategy profile.
The Stockpicker mechanism searches and automatically selects stocks that meet the entry criteria.
Backtest 1, Fixed $ Money Management
In this variant, we invest a constant amount of $100k, which is divided by the maximum number of open positions (10). This results in a capital commitment of up to $10k per position. We are testing the period of the last 30 years from 1994 to May 2024.
The backtest automatically selects stocks that meet the criteria from the Nasdaq 100 index. It's important to note that the list of stocks in the index changed over the years, which is taken into account in the Stockpicker data (survival bias).
Invested capital: $100k
Test period in years: 30
Test years: 1994 to May 2024
Test Index: Nasdaq 100
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 about $1.98 mln in the analyzed strategy is higher than the Benchmark (S&P 500 Index in the form of SPY ETF marked in yellow on the chart), which is $1.8m, translating to a CAGR of 10.65% vs 10.33%. This means that the analyzed strategy achieves a slightly higher net profit and a higher average annual return rate.
Drawdown and Return/Drawdown ratio
The Max Drawdown in the analyzed strategy was 18.20% vs 55.19% in the benchmark, resulting in a significantly better Return/Drawdown ratio of 12.20 vs 4.35. This translates to better risk management compared to the benchmark.
Exposure
The average exposure in the analyzed strategy was only 15% vs 100% in the benchmark. The study was conducted on the underlying instrument, which is the Nasdaq100 index stocks.
Please consider that in the case of applying to trade the S&P500 index, the exposure would increase to approximately 25% because there will be a lot more signals. Exposure is measured by a dedicated study, which you can read about here. Thanks to low capital usage, it was much less exposed to risk, and the free capital is suitable for use in other strategies.
Winning percent
The Winning percent was 68.3%. This means that the vast majority of transactions were profitable, highlighting the effectiveness of the strategy in generating positive outcomes, 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. According to our tests, for most 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). Position diversification within one strategy and across the strategy portfolio 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.
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 robustness was tested by practically conducting all possible transactions on stocks (max open positions 100) for the period from 1994-05.2024 for the S&P500 index (22'816 transactions) and the Russell 1000 index (33'375 transactions) at %MM. The strategy also passed positively through our manual parameter modification tests. We adhere to the principle that the fewer parameters, the greater the strategy's robustness. 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.
S&P500 max transactions: 22'816
Russell1000 max transactions: 33'375
Recommended Instruments
The strategy has shown very good results on the Nasdaq 100 over the long term. However, recently it had even better results on the S&P 500. We leave the decision to you on which index to trade. Please note that with the S&P 500, there will be greater exposure. The final decision requires your individual tests.
Primary Instrument: S&P 500
Supplementary Instrument: Nasdaq 100
Pattern Day Trader
The strategy statistically closed 2.22% of transactions on the same day, and there have been no cases of PDT being met in 30 years. This means that it can be used on accounts below $25k.
Correlation
To check the correlation of the strategy with others, visit the correlation page.
Summary & Strengths and weaknesses of the strategy
Strengths of the Strategy:
Exposure: The strategy utilizes capital for only 15-25% of the time (depending on the index)! This is very low compared to most strategies of this type.
Profit Stability: In the analyzed strategy, the Net Profit was close to $2M, while the Benchmark achieved above $1.8M. The CAGR was 10.65%, slightly higher than the Benchmark's 10.33%.
Robustness: The strategy was tested on various indices, including S&P 500 and Russell 1000, and its behavior was verified over a 30-year history and more than 50'000 trades.
Low percentage of same-day closed trades: The strategy is suitable for accounts below $25k.
Weaknesses of the Strategy:
It is difficult to find weaknesses in this strategy. One could point to the Max Drawdown of 18% in 2002, which is slightly higher than some other Stockpicker strategies but significantly lower than the index, which experienced a maximum drop of 55%. Over many subsequent years, including several bear markets, the strategy had a Max Drawdown not exceeding 10%.
Summary
A strategy that trades only on Mondays has shown excellent results over 30 years, utilizing only 15% of capital. Backtests have shown higher profit and CAGR than the S&P 500 benchmark, with a significantly lower maximum portfolio value drop. Additionally, 68% of trades were profitable, providing a high level of comfort. The strategy is robust, tested on various indices, and does not require a large capital, making it attractive to investors of various scales.
What you get in the package for this strategy:
An e-book presenting detailed rules and results of the strategy.
SQX file ready to use on platforms Algocloud and StrategyQuant.
Pseudocode describing all rules in an easy-to-understand manner.
If you need the code for this strategy in formats such as Multicharts, MT4, or MT5 (MQL), please contact us on this topic.
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.
BEST STRATEGIES
R2 Turbo Strategy
The R2 Turbo strategy draws inspiration from Larry Connors' experiences. While it is based on the Relative Strength Index (RSI) indicator, it includes a specific way of using this indicator and filters that enhance its effectiveness. It is a trend reversal strategy that waits for a specific pullback in an uptrend.
Week Explorer Strategy
For last 40 years, the best day of the week on the US stock market has been Tuesday. The next day with the highest return is Wednesday. We present a strategy that skillfully exploits this market behavior by opening positions only on Mondays and cashing in profits in almost 70% of cases over the following days.
●
KO Christmas Rally Strategy
The seasonal holiday pattern on Coca-Cola is one fantastic example of how seasons affect stocks. The pattern has a logical justification, which is the association of the brand with holidays built over decades. This consequently influenced consumer and investor behavior before this period.
●
BA Flight to Growth Strategy
Each year, the shares of the aerospace giant The Boeing Company (BA) statistically see an increase from the end of October to the beginning of January. What might drive this trend? Increased air traffic during the holiday season, which reminds investors of the company? Or perhaps government purchases at the end of the year cause Boeing's shares to gain strength?