trade


 

Content Generation

 

Different predictions and estimations are published in the media. TV Newscast and printed news describe the public opinion and experts opinions in, different subjects, such as: politics, economics and business.

 

Traditionally, predictions were based on survey results among statistical sample. The prediction was determined according to the majority of participants who answered in a similar way. Not infrequently, such surveys attracted serious criticism, due to biased questionnaire wording or sampling quality.

Another methodology is when predictions are set according to an expert opinion and estimation.

 

Nimanix arenas are innovative method for predictions and evaluations generation. Predictions are presented, at each point of time, as the results of the trade session in the arena. The traders form a group of members who were previously rated according to their knowledge or ability to conduct quality predictions in the relevant subject. The predictions are derived from the trade transactions, based on the participants' status, the trade volume, the transactions time stamps etc. Hence, these predictions are more qualified and encompass much more information. Nimanix predictions, in many cases, are superior to survey results, and as well, superior to a single expert estimation, since they represent a group of 'experts' consensus – the 'experts' that the platform spotted.

 

Another important advantage of the Nimanix arenas, comparing to traditional surveys and experts estimations, is the ability to present the prediction in a continuous manner. Surveys are conducted at a certain point of time, and represent opinions which may become irrelevant, shortly. This characterizes specially situations in which information frequently changes, for example, politics, economics or social events. Surveys conducted very frequently are not sensitive for such changes. On the other hand, the trade in Nimanix arenas is continuous, ensuring updated predictions which are sensitive to volatile events.