# Using Financial Instruments to Transfer the Information Security Risks
## 8 Evaluation
### Carry out Evaluation
#### 8.3.1 Improved Information Aggregation  
The ISDs are designed to be traded at ISPM, to provide a risk hedging/management mechanism that facilitates incorporation of any new information available to the traders. The mechanism will allow the traders to dynamically hedge/adjust their positions based on the new information. Thus, the mechanism will provide an efficient aggregation of information related to the underlying event or condition. The implied probability of the possible outcome will be reflected in the market prices. Also, the market prices carry the information from more informed to less informed traders. Thus, the receivers of the new information will revise their positions accordingly. This process leads to the convergence of belief of the trader on the potential outcome of the underlying event. Therefore, the market prices reflect the mean belief of the traders and are interpretable as the probability of the occurrence of the underlying event. For the efficient and effective functioning of ISPM (trading of ISD), it is desired that the traders truthfully and immediately reveal their private information. However, achievement of information elicitation and aggregation goal in ISPM depends on the strategic behavior of self-interested participants. The behavior of market participants is influenced by their private information, their expectation about other's private information, and conflicting incentives between the marketparticipants. Specifically, the pricing mechanism of market acts as a coordinator of traders' actions in the market, leading to the incorporation of the information in the contract prices. The value of the \"new\" information is time-sensitive in nature, _i.e._, the potential of making a profit from the information is only until nobody else has traded on the information and signaled the same to other market participants. This creates an incentive for the traders to \"quickly\" discover new information and trade on that in the market, thus leading to quick aggregation of new information. Slamka _et al._ reported that on average the new information was incorporated in less than ninety seconds, leading to increase in predictive accuracy of the market [114]. Wolfers and Zitzewitz also reported that the markets quickly respond to new information, leaving very few arbitrage opportunities [115]. Chen _et al._ experimentally studied the prediction market equilibrium and reported [116]: (i) prediction markets are guaranteed to converge to an equilibrium price, representing a consensus among the traders; (ii) they converge to equilibrium in at most \"\(n\)\" rounds of trading, where \"\(n\)\" stands for the number of traders; (iii) the best possible predictions it can make is the direct communication equilibrium when contract's market price is equal to the expectation of the value of the function of all the information of all the market participants; but (iv) a prediction market is not guaranteed to converge to the best possible predictions. Thus, by well-established and proven efficient market hypothesis [117], previously discussed literature and numerous other relevant studies, we expect the ISPM to act as an effective and efficient mechanism of information elicitation and aggregation. To the best of our knowledge, currently there are three methods to measure information aggregation efficiency. One model compares the transaction prices with the competitive equilibrium price of the contract [118]. The competitive equilibrium price implies to the reward when all the private information is aggregated and is reflected in the contract price. Therefore, the information aggregation efficiency is higher when there is a small difference between the transaction price and the competitive equilibrium price of the contract. Though, the measurement indicates the robust ability of prediction markets in aggregating the information, it cannot be used in a real business environment.