Investment Intel by Jakub Krivan #1: MAKING DECISIONS WITH THE GREATEST POSSIBLE ACCURACY

I’m not exactly a big fan of guesswork. Especially when dealing with high-level investment decisions, where the mistakes get, well, costly.

That’s why I’ve always respected solid mathematical simulations as a way to reliably back up all kinds of investment decisions. Algorithmic market predictions lie at the very heart of the financial business for a reason: Forecasts help investors decide when, where and how much to invest, and the more accurate these models are, the better the profits in the end.

It’s important, however, that the accuracy of financial forecast mechanisms relies in large part on the amount of data available to them. It’s rather unsurprising then, that small data pools lead to unreliable prediction models.

Not enough data = not enough accuracy

The problem with most financial market algorithms is that they only work with ‘tip of the iceberg’ data, making world-wide predictions based on listed companies only.

While the mathematical models behind them might be great, this only gives the investor access to the numbers of as little as 70 000 corporates. And these, importantly, make up only a tiny fraction of the complete global financial data. Which – you guessed it – you need to make really accurate predictions.

Not enough accuracy = costly mistakes

In the end, working with listed data only leaves the you as the investor with much to guess, predict and evaluate on your own. And where there’s not enough data, guesswork takes over. And where guesswork takes over investment decisions, costly mistakes are made.

Global data PLUS the right algorithm = significantly greater accuracy

Imagine that instead of the tip of the iceberg, you could take advantage of data from more than 42 million unlisted global companies and use it to make informed, data-based investments. After all — data from 70 000 companies vs. data from 42 000 000 companies — there's no comparison. So far, having this kind of data has only been an investor's dream, but now that we've launched a new prediction model developed by our friends at Quantic Risk Solutions, this is exactly what you can do.

The Quantic prediction model processes the full scale of global financial data including 42+ million unlisted global companies. This means you can make predictions about the future development of the financial market with accuracy which was never available before.

On top of the algorithm itself, a handy digital toolbox from Quantic helps you apply these insights in various daily tasks from risk analyses through stress testing to trading strategies. And this is not theory – several leading financial institutions have already started using the model with proven, long-term success.

The Quantic prediction model at C-Quadrat:

• Collects information beyond the iceberg tip and includes unlisted corporates
• Analyzes sheet data from over 42+ million corporates worldwide
• Predicts future with very high reliability and accuracy
• Applies these predictions to dynamic trading
• Is already in use by leading financial institutions

The Takeaway:

Having a tool able to predict results with the greatest possible reliability so far improves your long-term investment outcome by eliminating human factor faults.

I don’t know about you, but knowing that my investments are backed by insights based on hard data rather than intuition really sounds like a good idea.

And it might be a good idea for you as well to visit Quantic website to learn more.