Spark Profit Application enters India

Nous Global Markets, a London based company aiming to discover and train the next generation of trading talent, has announced the India entry of its ‘Spark Profit’ application. It is a free to join, free to play and free to earn virtual trading game. Behind its friendly interface is a highly realistic trading simulator that pays actual cash for correctly predicting financial markets (currencies, commodities, stock indices and Bitcoin). As a bonus players will also learn the valuable skills needed to trade as fulltime occupation.

The goal of Spark Profit is to make predictions in financial markets to earn points. Earn enough points, and you start to earn money – the more points you accumulate, the more money you earn! There is no outlay of cash nor investment required. Even more compelling, 95% of the points you earn are carried over each week, to help you earn as much as possible.

The predictions you make are about the real financial markets, with live prices coming straight from those markets. As the price changes after you make a prediction, your points will go up or down. Because the app is so intuitive and graphical however, you don’t need to any prior experience or mathematical skills to use it.  Just point and predict!

According to Short, Spark Profit was very carefully designed to fit any schedule, no matter how busy. Predictions can be made in seconds, and run even when you are not watching; you can limit points lost for incorrect predictions; and you can come back to review or cancel at any time.  After downloading and registering for free, there is even a two minute tutorial to help you make your first prediction.

The company wants to find and nurture natural trading talent from around the world. By making the financial markets accessible to everyone in the world, the company aims to make them more efficient and democratic. The company has already applied for two patents and has more planned. The company is looking to deploy this “crowd-sourced alpha” with financial institutions in UK and US by combining its users’ predictions to forecast actual price movements.