“I buy on the assumption that they could close the market the next day and not reopen it for five years.”
— Warren Buffett
The Warren Buffett investment philosophy calls for a long-term investment horizon, where a five year holding period, or even longer, would fit right into the strategy. How would such a strategy have worked out for an investment into General Motors Co (NYSE: GM)? Today, we examine the outcome of a five year investment into the stock back in 2018.
|Average annual return:||0.76%|
The above analysis shows the five year investment result worked out as follows, with an annualized rate of return of 0.76%. This would have turned a $10K investment made 5 years ago into $10,385.82 today (as of 03/13/2023). On a total return basis, that’s a result of 3.88% (something to think about: how might GM shares perform over the next 5 years?). [These numbers were computed with the Dividend Channel DRIP Returns Calculator.]
Dividends are always an important investment factor to consider, and General Motors Co has paid $3.31/share in dividends to shareholders over the past 5 years we looked at above. Many an investor will only invest in stocks that pay dividends, so this component of total return is always an important consideration. Automated reinvestment of dividends into additional shares of stock can be a great way for an investor to compound their returns. The above calculations are done with the assuption that dividends received over time are reinvested (the calcuations use the closing price on ex-date).
Based upon the most recent annualized dividend rate of .36/share, we calculate that GM has a current yield of approximately 1.01%. Another interesting datapoint we can examine is ‘yield on cost’ — in other words, we can express the current annualized dividend of .36 against the original $37.69/share purchase price. This works out to a yield on cost of 2.68%.
Here’s one more great investment quote before you go:
“The whole secret to winning big in the stock market is not to be right all the time, but to lose the least amount possible when you’re wrong.” — William O’Neil