Investors can employ a combination of quantitative analysis, technical indicators and machine-learning algorithms to effectively analyse historical data. Photo: Pexels.com
The stock market trading environment abounds with cautionary tales and sage advice, among them being the reminder that “past performance is not a failproof indicator of future returns”. But while over-reliance on historical data can be a pitfall, the past can provide valuable insights into future market cycles and may even help local investors in mitigating the inherent uncertainty that is part of the ever-evolving investment world.
This is according to Kamogelo Mosime, the partnership manager at Tickmill, who refers to historical stock market data as a “treasure trove of information”. He explains: “When looking at history as traders and investors, what we’re going in search of are patterns and trends that can provide a foundation for informed predictions. In a sense, history provides an anchor, a source of grounding during periods of turbulence and volatility.
“By understanding patterns which tend to repeat over time, we can, to a certain extent, factor in unexpected geopolitical events and economic shifts. While we cannot rely entirely on historical events as indicators of what lies ahead, we can use the data, along with other tools and methods, to build robust portfolios.”
Mosime offers the following three insights:
History is replete with instances where specific patterns and trends have repeated across multiple stock market cycles. A prime example is the tech boom-and-bust cycle, or the “dot.com bubble” of the late 1990s. Now, at the dawn of the Fourth Industrial Revolution, tech stocks and innovations, such as Bitcoin, have seen similar peaks and troughs in response to underlying dynamics related to investor confidence market exuberance and subsequent corrections.
Another example can be seen in real estate market cycles, where, for instance, during the mid-2000s, there was a notable upsurge in real estate prices, fuelled by speculative buying and ease of access to credit. Following closely on the heels of the boom was the 2008 financial crisis, which saw a substantial correction in real estate values. Most recently, the market has seen a resurgence of the trend, with a significant increase in real estate price in certain regions, driven by low interest rates and growing demand.
Therefore, historical data suggests that these types of rapid price increases can sometimes be unsustainable and lead to future correction. By studying the examples provided by history, investors can develop a more balanced approach that weighs up historical data with real-time context – striking this balance and resisting making impulsive choices based on fear or greed, is crucial to building a successful portfolio.
One would be remiss to rely wholly on history and past performance when making investment decisions. In fact, mastering the ability to use history as a yardstick, rather than a surety, is vital to achieving long-term investment success.
For example, the “bull” and “bear” market cycle is a metaphor that has become an ingrained part of how analysts and traders approach decision-making. “Bull” markets are typically characterised by prolonged periods of rising stock prices, often driven by strong economic fundamentals and investor optimism.
Conversely, “bear” markets involve sustained declines, typically driven by economic downturns or negative sentiment. The cycles can span several years and while the specific triggers may vary, the underlying psychology of investor behaviour and sentiment remains a constant.
Hasty investors may make the mistake of basing their decisions on these indicators and, as a result, become over-invested in certain asset classes and unprepared when the market takes an unexpected turn. On the other hand, traders also need to avoid falling into the trap of “recency bias” or the human tendency to give greater credence to recent events when making judgements or decisions.
For instance, during periods of sustained market growth, investors might assume that the trend will continue indefinitely, ignoring the cyclical nature of markets. This can result in a distorted view of market cycles, as it may neglect longer-term patterns and trends.
This bias can hinder accurate predictions by neglecting historical context and failing to anticipate shifts in market sentiment. Recognising and mitigating recency bias is crucial for a more balanced interpretation of historical data, ensuring a broader perspective is considered when predicting future market cycles.
It is for this reason that local investors need to rely on a combination of approaches, tools and methods to effectively analyse their decisions against historical data and recent events. Fortunately, trading platforms like Tickmill are powered by technology that can counteract human error and assist investors in making decisions that are based on fact rather than feelings.
Investors can employ a combination of quantitative analysis, technical indicators and machine-learning algorithms to effectively analyse historical data and enhance their predictive abilities. Quantitative models help identify statistical relationships and correlations within historical data, while technical indicators offer insights into market momentum and sentiment.
On the other hand, machine-learning algorithms can uncover complex patterns that might be imperceptible to human analysis. However, it’s always important to note that no method can eliminate uncertainty entirely, and a multidimensional approach that integrates quantitative analysis and qualitative judgement is optimal.
“While history provides a guide, the interplay of investor emotions and biases can either reinforce historical trends or challenge them, underscoring the importance of a balanced and adaptive investment approach,” says Mosime.
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