From location quotient geography formula to AI (Artificial Intelligence) investing, leveraging technology to generate higher returns is one of the best ways to ensure your investment efforts result in success.
Driving top investment returns by leveraging the latest tech tools isn’t exactly a new way to earn from investing. Hedge funds were the initiators of data-driven investing that heavily relied on technology to make better and more lucrative investment decisions.
This investment model quickly became popular among both private and institutional investors. Although there’s a big difference between data-driven and model-driven investing methods, the former helps an investor by offering access to the power of data to recognize patterns that traditional investment models simply couldn’t provide.
The best way to describe data-driven investing is to say that it combines alternative data and traditional information to provide an investor with the latest, most up-to-date investment insights.
Data helps avoid risks, identify top investment opportunities by location, and make better investment decisions. Let’s talk about how data-driven methods can help to improve your investment decision-making.
AI investing or big data investing is a new way to make smarter, more lucrative investment decisions. It’s a strategy that relies on the latest technology and data science to help investors make better decisions based on the alpha metric.
The term alpha refers to two essential driving factors:
- Completing a successful investment cycle.
- Gathering various metrics to measure the active ROI (return on investment);
AI relies on gathering vast quantities of data from the web to help investors enhance alpha. In addition, corporate investors rely on AI to track various metrics, such as security management and risks, business operations, social sentiment, etc.
In the past, investors used to rely on traditional investment strategies that involved using publicly available data, such as market data (returns, volumes, prices, etc.), financial statements, public investment records, etc.
However, data-driven investing relies on incorporating unconventional data, such as the right location quotient, social media, satellite images, and internet web traffic, to help private and institutional investors make better investment decisions.
They gather this information for analysis to get a more detailed picture of the current market situation, trending events, and best opportunities across different regions and industries.
Unconventional data gives an investor a competitive advantage by providing current and up-to-date information on the best investment opportunities at the moment. That’s why this data-driven investment technique is currently so popular among investors.
Using new data
While modern computing devices come with great abilities regarding data analysis, they require quantifiable or structured data to perform their magic. Data-driven investing, on the other hand, relies on raw, unstructured data, such as images, speech recognition, language, etc., to provide investors with valuable business valuations.
Thanks to new data, private and corporate investors can perform massive analyses of entire regions and identify top events and trends in the market to adjust their investment strategies accordingly. Investors can easily incorporate the insights from the analyses into value creation and business valuation abilities.
Social media sentiment analysis
Sentiment analysis is probably one of the most important trends in the data-driven investing industry. This method refers to performing detailed research and analysis on consumer reactions to a particular brand, market, and industry.
Modern customers are used to posting their thoughts and opinions on brands on social media networks. Their posts are an abundant source of top-grade data that can provide investors with all the insights they need to decide whether investing in a brand or industry promises high returns.
However, it won’t be enough to amass simple mentions and comments online. The data-driven method implies that an investor must tap into customers’ opinions and general emotions toward a particular brand.
Let’s say that you want to invest in the car industry in Norway.
You can feel the pulse of the local market by checking what people are saying on social media to get a better perspective of the things to expect. Conducting such analysis allows you to create not one but several strategies.
For instance, if customers have complaints about a particular industry and their opinions on the matter are mostly negative, that’s a clear sign that you shouldn’t invest in that industry.
Data gives investors a competitive advantage
One of the most significant benefits of data-driven investing is eliminating human error, irrationality, and bias. Having top information on the best investment factors makes it easier to ensure higher returns as data opens countless possibilities.
Data-based decisions allow investors to improve the selection process and select the best investment opportunities. More importantly, it solves the leading causes of risks and mispricing across emerging markets, such as lack of transparency, volatility, and uncertainty.
Data-driven investing provides investors with invaluable insights regarding top investment opportunities for investing in emerging markets. Through analyzing centralized and alternative data, investors can also eliminate the need to spend their budgets on hiring various investment specialists, such as business environment analysts.
Instead, they can rely on the latest advanced technology to gather and analyze data from various data sources to discover the latest investing trends in both traditional and new markets. In other words, data-driven investing is a sure way to improve your investment decision-making process.