As a financial advisor, I work closely with my clients to help them intentionally plan, save, and invest. While these are essential components of financial health, it’s equally important to examine how our attachment to control over our finances can sometimes become an obstacle to our well-being.
No one can predict market movements with absolute certainty—my crystal ball is still in the shop🔮! What I do know is that missing just a few days of strong returns can drastically affect your overall performance, which is why it’s crucial not to abandon a well-planned investing strategy when the market gets rocky.
Let's face it—life can be incredibly stressful. Between demanding work schedules, chaotic commutes, and the pressures of family and social obligations, it often feels like we're constantly being pushed off balance. However, even on the busiest and most overwhelming days, there are simple practices we can use to manage our stress and regain a sense of equilibrium.
I’ve had countless conversations with people about money, and one theme consistently emerges: anxiety. Everyone has a vision of their ideal financial life, but few have a concrete plan to achieve it. After many discussions on this topic, I’ve developed a strategy that might help.
Many of us repeatedly make the same financial mistake: buying high out of greed and selling low out of fear, despite knowing intellectually that it's a terrible idea. This behavior is most evident in market cycles. When sectors are booming, people pour money into markets to chase performance. But when sentiment changes, and investments plummet, investors rush to escape.
Humans don't fit into an algorithm. This is particularly true when we’re talking about humans and their money. Because “Humans + Money” is a messy little cocktail that economists refer to as a complex adaptive system. “Humans + Money” is complex because cause and effect can only honestly be identified with the benefit of hindsight, and it’s adaptive because our interaction with the system changes it. Try cramming that into an algorithm.