In 2001 security agencies in the United Statesproposed using prediction markets to assess the likelihood of a terroristattack. That government program was cancelled in 2003 due to criticism from USCongress. Put forward a case for or against the use of markets to predict thelikelihood of this type of event.Prediction markets are a platform for participants to trade in futures contracts where the payoff is dependent on an event rather than a value. This essay explores how neoclassical and behavioural economics support the use of this tool as a better predictor than traditional methods of polls and surveys. Using these markets to predict terrorist attacks in theory would retrieve information more easily from disparate sources (Wolfers and Zitzewitz, 2004)1: both within security agencies and from the general public. Different design and participants created the moral argument against these markets. I will explore how they can be controlled and beneficial in contributing to anticipating terrorist attacks, especially cyber-terrorism.As technology and social media is nowsuch a large part of western society there is another method of security threatthrough the huge amount of data available. Although they monitor for key words,prediction markets could be another means of picking out vital information fromthe public domain. A lot of what is available could however be opinion as opposedto informed knowledge (Tabarrok, 2002)2, so a perfect market with traderslooking to make profit would ‘de-bias’ this information (Berg and Gruca, 2007)3.The public informationmay be a good contributor for topics that security agencies do not have indepth knowledge of or it may just inform what the public is more interested in (Yeh, 2006)4.A market needs uninformedparticipants to form trades. If the market was formed, for example, of securityofficers all from the same department then they would have common posteriorbeliefs, not disagree and not want to take alternate sides of a trade (Aumann,1976)5. It is therefore necessary for the market to at least beacross teams with different insider information. Yet these may still have thesame beliefs, so including the public could be a way to ensure a market isdiversified with those that are overconfident and speculating and those usingit for entertainment purposes. In the latter case, terrorism is a topic thatwill attract a lot of interest from those looking to trade on new instruments(Wolfers and Zitzeweitz, 2006)6. However, the US proposal forprediction markets to test policy ideas and for geopolitical risks would not haveattracted much interest (Wolfers and Zitzewitz, 2004)1. Therefore, a subsidy may have been used toacquire participants. This generated public concern of people profiting in amarket (Hanson and Oprea, 2007)7 whichhas negative moral implications.Making a trade on a prediction market is with regards toa specific event that may occur, but with cyber-terrorism there are thousandsmore possible scenarios. Thus, it is a big challenge to speculate and formclear and simple contracts to trade. However, it can be argued that marketswill do this more quickly and efficiently than the systems security unitsalready have. Also, once the platform and contracts are established they can bereplicated easily for many scenarios. A first use of prediction markets aroundcyber-terrorism could be looking at the likelihood of a defence agency beingsuccessfully penetrated (Yeh, 2006)4. This is a narrower and larger eventthan the thousands of other possibilities across institutions, locations andmethods. There may be more knowledge on this already too because of the highlysophisticated systems which need to be implemented and controlled, as well asthe interconnectivity of security and defence.The Efficient Market8 and the Hayek hypotheses9 arethe main theories behind prediction markets aggregating information in asustainable manner. These tools allow the model to accurately price knowledgefrom different individuals, as well as on the environment. From these come therandom walk theory. This is a caveat to the use of prediction markets, statingthat: because information is reflected instantaneously it cannot predict thefuture movements, rather tomorrows price will simply reflect tomorrowsunpredictable news (Yeh, 2006)4.  Despite this, prediction markets that arealready in use have a high success rate. This is possibly because movements inprices reveal events occurring, (Yeh,2006)4 even if they have no contribution as a predictor forfuture movements. Despite the confidence intervals from random walk projectionsincreasing over a longer time horizon, they can be argued to be more accuratethan the margins of error from a poll (Berg,Nelson, and Rietz, 2003)10. Therefore, prediction markets are still beneficialin measuring the degree of (un)certainty. There aren’t many experts on computer programs and hacking so theprediction market created around cyber-terrorism would be thinner than thosewhich back up the Efficient Capital Market hypothesis (Grady and Parisi, 2006)11.In this case, there would be less speculation and more price volatility becausethe number of buyers for contracts and price they are looking for does notmatch the (number of) sellers (Hanson andOprea, 2007)7. It is important for security agencies to understand if bubbleswill occur in these prediction markets on terrorism contracts because it coulddamage their forecasts. As with asset markets, they should be equipped todecide whether it is better to burst the bubble or respond after to limitnegative effects on the structure of the market (Yeh,2006)4. Any attempt to increase market participation to limit volatility as well as acquire more information should be done so with discretion due to the argument that potentially terrorists could enter, influence and even profit from the market changes. They could manipulate what the markets are formed from (coding in websites or software programs for example), thus changing prices reflected in the markets or simply by speculating in the market (Wolfers and Zitzeweitz, 2006)6. However, studies around this have shown that a trader whose target is uncertain and is trying to manipulate the market will not be successful in doing so because this extra noise (biases discussed earlier) gives more opportunity for profit making (Hanson and Oprea, 2007)7. This will bring prices to their correct equilibrium. In other words, trade reveals objectives of participants that are trading against or changing the market which in the case for terrorism can be supporting evidence. There is a trade-off between allowing the public to participate for added insight then recognising when a market manipulation is of any significance (i.e. how much the share price needs to deviate by before being an indicator of terrorist activity) and limiting participation which could just make the market more complicated with unknown benefits in prediction. It can be argued however that limiting participation is also not worthwhile because if it was terrorist’s intention to fund operations through the market they would manipulate a related market. This may have been seen pre-9/11 with unusual trading in airline stock but it is unclear whether adverse profits were made from this (Wolfers and Zitzewitz, 2004)1.Behavioural economics also introduces biases which could result inprices being reflected incorrectly in prediction markets. They are based oncontracts on future events so, prices which arise are typically interpreted asprobabilities an event will occur, which has been discussed by Manski (2006)12to be unsound reasoning because therewould need to be more insight into why the trade has happened (Yeh, 2006)4. Nonetheless,according to Kahneman and Tversky’s Prospect theory (1979)13 theseprobabilities will be over-weighted when calculating rare vents such asterrorism (Wolfers and Zitzeweitz, 2006)6. Yet, cyber-terrorismis becoming much more frequent so this argument may reverse soon and studiesshow this has little influence on the reliability of these instruments anyway(Wolfers and Zitzewitz, 2005)14.Similarly to how many of the publicthink it is unethical thatbankers place large bets on financial markets, it has also been shown they viewprediction markets as a novel idea (Hanson and Oprea, 2007)7.They may think it is a waste of taxpayer’s money (Yeh, 2006)4 tocreate similar models. Increased education for the public on how markets workwill make the potential process less obscure. One view of prediction markets for terrorism is thatthey are putting values on people’s lives and a profit can be made, even by theattackers, which is immoral. Understandingof how to control the use and misuse should also reduce opposition toprediction markets. If a profit is made but results in detection of the threat (Wolfers andZitzewitz, 2004)1 and lives being saved this will beworthwhile. It should also be questioned whether it differs from the wide spread use of lifeinsurance. In fact, the UK has a market for insurance against cyber-terrorismwhich is effectively pricing the likelihood, very similar to a predictionmarket. The possibility and scale ofpotential cyber-attacks is a relatively new and obscure concept compared to thevisible consequences of a physical terrorist attack. An awareness of the benefitsof an extra resource for security in this new area could reduce opposition toprediction markets. Perhaps trialling these markets with a different name tosee the participation and success rates could be a good start for introducingprediction markets but this is ethically dubious.In conclusion, I support the use ofprediction markets as another security measure. There needs to be a lot morepersuasion of the value of results as they are relatively new tool generally.Then they may be accepted in the security industry and senior officers will aidtheir effectiveness (Yeh, 2006)4. With gaps in our abilities as humansto process data (Tabarrok, 2002)2, prediction markets supplementsolutions such as surveys and consultants. Theycould be extremely useful in aggregating and updating information over the longterm (Yeh, 2006)4 where this workis cumbersome and time consuming.This will allow expert judgement to be put to better use on deeper analysis.Bibliography Wolfers, J., and Zitzewitz, E. 2004. “Prediction Markets” Journal of Economic Perspectives. Volume 18, Number 2. 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Pages 425-429. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.159.7574&rep=rep1&type=pdf Kahneman, Daniel and Tversky, Amos. 1979. “Prospect Theory: An Analysis of Decision under Risk”.  Econometrica, 47(2), pp263-291 https://www.princeton.edu/~kahneman/docs/Publications/prospect_theory.pdf Wolfers, Justin and Zitzewitz, Eric. 2005. “Interpreting Prediction Market Prices as Probabilities” Discussion Paper Series IZA DP No. 2092. http://ftp.iza.org/dp2092.pdf Rhode, Paul and Strumpf, Koleman. 2004 “Historical Presidential Betting Markets” Journal of Economic Perspectives. Volume 18, Number 2. Pages 127-142. https://pubs.aeaweb.org/doi/pdf/10.1257/0895330041371277Get Help With Your EssayIf you need assistance with writing your essay, our professional essay writing service is here to help!Find out more