Successful investors are often depicted as instinctive – we speak of “playing the stock market” and assume they watch the market move and use a sixth sense to decide when to buy or sell. In reality, though, intelligent investing is a highly mathematical process that relies on extensive data, and now the growth of big data presents new ways of assessing stock performance and developing a strategic investment plan.
If you’re seeking a better way to organize your stock portfolio, these three tools can help clarify market movements, assess trends and help make smarter investments. Whether you have a limited number of stocks or a sprawling portfolio, you can attain greater profits through data.
Smarter stock selection
One of the first key functions of data for portfolio building is its ability to maximize profits, specifically by building a concentrated portfolio. The idea behind a concentrated portfolio is that, when you identify stocks that are “winners” – that are making big gains, it’s better to put more money into a few stocks than to over diversify in an attempt to guard against risk. Tools like MarketSmith can help you identify industry leaders, stocks that you can then “force feed” or buy increasing amounts of, while culling stocks with less robust returns.
Though diversification is often viewed as the smartest approach to investment, experts like Warren Buffett (Trades, Portfolio) don’t think the data bears this out. Rather, according to Buffett, “wide diversification is only required when investors do not understand what they are doing.” Smart investors don’t dilute their portfolios with weaker stocks when they could be building onto their top performers.
Charting the path
For small investors with a few stocks to track, basic programs can provide sufficient information to differentiate between winners and losers. But for companies managing larger portfolios, these tools may not provide enough data. Rather, more complex software solutions provide visualizations, identify individual stock and overall portfolio performance and manipulate different graphs and data selections, providing both big picture and detailed views of stock performance.
Independent investors looking for this type of solution can see similar kinds of data using more basic programs, like the portfolio gain system from GuruFocus. This system helps paint a complete picture of your portfolio, demonstrating not just holistic growth, but also percentile and dollar growth. This allows you to see which stocks are contributing most significantly to your portfolio’s growth, which stocks are lagging in comparison to other holdings and helps you assess where to force feed, where to sell and when diversification is working against your best interests.
The big data angle
Of course, if you aren’t skilled at reading and manipulating data, analytics apps aren’t sufficient for managing investments, but skill isn’t the only factor at play in the modern marketplace. Rather, as big data connects with the stock selection process, machine learning-based assessments will inevitably outpace human decision-making. Though there will always be some “instinctual” investors who believe they can make better decisions independently, the average investor – even at the corporate level – can’t be expected to spot the kinds of slight variation or big picture trends that machines can.
Regarding machine learning, this new technology may be especially powerful when it comes to trading commodity futures. Because many commodities follow general seasonal patterns, as well as trends dictated by weather activities, machine learning’s ability to analyze and digitally track these trends can lead to increased earnings. While prediction is less reliable for typical stocks, the patterns related to futures are much more responsive to machine learning protocols.
The investment process is changing – though online trading is hardly new, the digital component has reached a new level through big data and advanced software. If you’re playing the market, it’s time to consider what role technology can play in that process. If you’re not digitizing your holdings data, you’re not earning up to your potential.
Disclosure: I do not own any of the stocks mentioned in this article.
