There have been, and always will be, disruptors, new threats and market trends that change the face of investing.
The speed at which information is now transferred around the world, and the accessibility and velocity of trading, have played a role in increased volatility.
The introduction of computer-based algorithm models has added to wider market swings. Economic indicators are driving computer trading activity and built-in buy and sell triggers create exponential highs and lows. A current example is this week's inverted yield curve.
Computer models only take into account Hard Data, which is data in the form of numbers or graphs that can be measured, traced, and validated.
On the other hand, Soft Data is comprised of human intelligence, intuition, and the interpretation of factors that cannot be measured by computers. Soft Data includes political climate, corporate branding, innovation, personnel changes, pending legislation and legal actions, none of which can be captured by algorithms.
For these reasons, we always come back to investing with institutional funds that are actively managed by humans interpreting the impact of both Hard and Soft Data rather than by technology alone.
Increased downside volatility offers portfolio managers opportunities to purchase underpriced stocks with solid fundamentals that are unrecognizable by computer models.
Patience, poise, time, and aligning with seasoned money managers help you remain focused during volatile times.
Fatal mistakes typically arise when outside influences make you deviate from your original plan, or if you never had a plan.
We are here to remind you that you do have a plan and that increased volatility should not change your long-term investment strategy.
Coaching you through up and down markets is the most important aspect of our relationship. If market conditions are giving you anxiety, schedule your coaching call easily and instantly on our virtual scheduler.
Investing involves risk including loss of principal. No strategy assures success or protects against loss.