The Monday Effect in the US Stock Market06 June 2022
The Monday effect is another popular stock market calendar anomaly, along with the turn-of-the-month effect discussed earlier. In addition to the name “the Monday effect”, this phenomenon is also referred to as “the weekend effect”.
The Monday effect suggests that the worst day of the week in the stock market is Monday. Attempts to explain this phenomenon come to several hypotheses:
- The companies' tendency to publish bad news on Friday after the closing of the markets subsequently leads to a decline in the stock prices on Monday.
- The closing short positions effect. Before the weekend, in order to minimize risks, traders close their short positions, which leads to a Friday market growth. On Monday, positions are restored, and this puts pressure on prices.
- Psychology of market participants: supposedly investors and traders are more optimistic before the weekend, and on Mondays pessimism prevails.
Using the Monday effect to trade US stocks is profitable.
Historical quotes of the S&P 500 index and stocks of the Dow Jones index.
Timeframe - D (daily).
Period - from 1990 to November 2021
A total of 1,519 working Mondays.
Opening a position - selling an index/stock at the close of trading on Friday
If Friday is a holiday, opening a position is on Thursday at the close of trading
Closing a position - buying an index/stock at the close of trading on Monday
If Monday is a holiday, then Tuesday is not taken into account instead
Analysis of the obtained results
We will evaluate the results according to the following criteria:
- The average rate of return reflects the relative change in quotations of financial instruments in percentage. A positive value of the average rate of return indicates the profitability of the strategy, a negative one indicates a loss.
The rate of return (R) of a financial instrument is given by the formula:
R = Σ P (%) / n,
n is the number of transactions;
P (%) = ((position opening price - position closing price) / position opening price) * 100%
- The total rate of return (TD) is the sum of the returns from all transactions. The greater the value of the total rate of return, the greater the profit brought by the signal during its testing period.
- Maximum drawdown (MaxDD) is the maximum loss in percentage terms from fixing losing trades for the entire testing period. The smaller the value of the maximum drawdown, the better the trading signal works.
MaxDD = | min ( DD1 : DDn ) |
DDn = TDn – max ( TD1 : TDn )
n - the number of transactions;
D - rate of return;
TDn - total rate of return of n transactions;
DDn – drawdown at the time of closing the nth transaction;
MaxDD – max drawdown.
According to the results of calculations, only 4 out of 30 stocks of the Dow Jones index have shown a positive average rate of return: Visa (V), Salesforce (CRM), Honeywell (HON) and Boeing (BA).
The S&P 500 index shows a negative average rate of return of 0.039%.
Apple (AAPL), Caterpillar (CAT), IBM and Intel (INTC) stocks have demonstrated the worst average rates of return.
On average, for all the considered instruments, the average rate of return turns out to be negative: - 0.07%.
The total rate of return parameters reflect a picture similar to the average rate of return, with only Visa, Salesforce, Honeywell and Boeing in the positive zone.
The outsiders are Apple, Caterpillar, IBM and Intel.
The largest maximum drawdown has been demonstrated by the stocks of Apple, Caterpillar, IBM and Intel. In terms of average and total rates of return, these stocks have performed as the worst.
The lowest maximum drawdown values have Visa, Dow, Travelers and Salesforce stocks.
Only 7 out of 31 considered instruments have shown a maximum drawdown value of less than 100%.
Using the Monday effect to sell stocks has shown low efficiency. Only 4 out of 30 stocks of the Dow Jones index achieve a positive value of return.
But even in these cases, the rate of return of the strategy does not reach a significant level of 0.3%.
The effectiveness of using the Monday effect for trading US stocks has not been identified.
Detailed results are shown in the Appendix: