Wall Street is an Investment in the Future
Wall Street is an investment in the future. Wall Street primarily focuses on the financial markets, which offer sustainable investment opportunities as long-term investments. The stock market is controlled by randomness and uncertainty over a short period. However, randomness and chaos in the short-term reveal patterns that can govern investments in the future. Analysts can employ different neural networks and chaos theory to forecast the stock index and mitigate risk (Dhanalaxmi Chakradhar, Sreedhar, 2016). Wall Street presents an opportunity for long-term investment. For instance, Microsoft's stocks have grown from $55.48 at the start of 2016 to $212.65 on January 15, 2021 (MSFT Advanced Charting, 2021). Microsoft's stocks have grown significantly over five years. Similarly, Wall Street can be considered an investment in the future since stocks' value tends to increase over an extended period, making them lucrative investment opportunities.
The Fear about Wall Street and Investing in the Stock Market
My biggest fear of Wall Street and investing in the stock market is losing money in the short term. The stock market experiences unprecedented fluctuations. High volatility increases the stock market's risk and uncertainty, which is damaging to normal operations of the stock market (Bhowmik & Wang, 2020). Volatility is directly related to market uncertainty and impacts the investment behavior of individuals and enterprises. The fear of losing money on an investment is connected to the high risk and unpredictability of the stock market, especially in the short term. The monetary markets are controlled by randomness within the short term, which makes the markets unpredictable. Wall Street uses different models and techniques to forecast market volatility. However, forecasting perfect market volatility is challenging, which makes it hard to mitigate risk. The high levels of risk increase fear about Street Wall and make investing in stock markets unappealing to investors who fear losing money.
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References
Bhowmik, R., & Wang, S. (2020). Stock market volatility and return analysis: A systematic literature review. Entropy, 22(5), 522.
Dhanalaxmi, M., Chakradhar, B., Sreedhar, B. (2016). Time series prediction of stock market data by using chaos theory and neural network. International Journal of Scientific & Engineering Research , 7(3), 144.
MSFT Advanced Charting . (2021, January 16). NASDAQ, https://www.nasdaq.com/market-activity/stocks/msft/advanced-charting
