Pregled bibliografske jedinice broj: 830087
Does bargaining dynamics inherently cause market bubbles and crashes?
Does bargaining dynamics inherently cause market bubbles and crashes? // 7th General Advanced Mathematical Methods in Finance and Swissquote Conference
Lausanne, 2015. (poster, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 830087 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Does bargaining dynamics inherently cause market bubbles and crashes?
Autori
Kostanjčar, Zvonko ; Begušić, Stjepan ; Stanley, H. Eugene ; Podobnik, Boris
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
7th General Advanced Mathematical Methods in Finance and Swissquote Conference
/ - Lausanne, 2015
Skup
7th General Advanced Mathematical Methods in Finance and Swissquote Conference
Mjesto i datum
Lausanne, Švicarska, 07.09.2015. - 10.09.2015
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Cooperative game theory ; Feedback ; Market crash
Sažetak
Estimating a current stock price requires estimating future cash flows and cost of capitals. The accuracy of estimates can then be checked against the actual data, which emerge with the passage of time. Bad predictions are time-limited and in case of overestimation can induce abrupt adjustments in the form of market crashes. The question is: Can we predict the time of market crashes? Here, we propose a bargaining model based on a complex networks, where agents on the supply side of the market cooperate with agents on the demand side of the market, but agents who are on the same side of the market compete with each other. We demonstrate that the competition clustering in the networks directly affects the bargaining outcome, where bargaining dynamics strongly influence the emergence of market bubbles and the occurrence of market crashes. We propose a dynamical free cash flow model to estimate the intrinsic (fundamental) value of a financial index. When a bargaining process pushes market values to levels that are above intrinsic values, the uncertainty in market dynamics increases, and this increase in uncertainty could be used as an early warning indicator for market crashes. We illustrate the applicability and forecasting power of the network model for the S&P500 index by estimating a probability of market crash occurrence in period from April 2015 to December 2016. We demonstrate how our market crash predictions are in good agreement with the S&P500 index market crashes in the past.
Izvorni jezik
Engleski
Znanstvena područja
Matematika, Fizika, Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Građevinski fakultet, Rijeka