Asset Pricing Learning Mechanism On Signal’s Divergent Expectation

Financial asset’s information price theory is an important branch of financialresearch in nowadays. Mainly focusing on price’s learning process, cleaning out andinformation spreading, information price theory developed rapidly in recent severaldecades with diffusion into other financial field such as behavioral fiancé andexperimental fiancé, which incite widespread concern of researchers. In recent years,researchers have tried to expand this theory with discussing price mechanism, investors’behavior and market quality under different trade models, which formed several factionsinclude rational expectation, market microstructure and etc.This paper developed an information price’s leaning model with basis of investors’behavior analysis under signal’s divergent expectation, which also discussed tradingamount’s structure. The existing research have achieved a certain amount ofachievement and formed several theory frame. Comparing with the existing research,this paper divide investors in market into “self-believer” and “market-follower” anddiscussed their invest strategy separately. In the meanwhile, this paper separated tradeprocess into signal’s trading period and leaning period and discussed price and tradingamount structure. This research method admits the risk asset price’s variation is causedby information and investor’s mutual leaning process, which is different with the otherresearch. This method could combine the reality market’s microstructure and be benefitto the related price and trade amount research.The main content includes the following several parts:(1) In enumerating the related price theory under risk assets value signal, theresearch introduced the latest related research categories which include the rationalexpectation theory, the microstructure theory, the public signal’s price theory and etc.By presenting the core and basic research achievements of these theories, the researchpossessed a complete theory source and builds its own theory frame from their research.(2) The research discussed the special financial market’ microstructure of Chinawhich especially mean the financial asset trading market in Shanghai and Shenzhen. Bystatistical research of market asset and inventors’ structure, the research gave apreliminary result of financial market’s trading mechanism and inventors’ divergentstructure which have great influence of assets’ price variation. By the way, because ofgreat usefulness of price yield research for the description of inventors’ divergent structure, we put the mainland’s market yield research into this chapter.(3) By dividing investors in order market into two types:“market-follower” and“self-believer”, we analyzed investors’ asset position strategy facing market price whichis caused by public information’s divergent expectation. We then discussed themovement of trade volume and the market price’s equilibrium process. It is shown thattrade volume remains under one-period equilibrium price and investors withdraw frommarket with persistent equilibrium prices and a larger price precision. In addition,equilibrium price could be achieved in both single and multi-investor market while alarger ratio of “market-follower” would delay the equilibrium period in a multiinvestors’ market.(4) With the basis of one-period signal’s equilibrium price model, we discussed theprice and trading volume’s alternation structure under multi signals of risk asset’s valueand the market have signal and price’s friction. It is shown that the two signal period’svalue differences take great part in price alternation, in which the pre-latest signal valuehave reverse pulling power and the signal of current standing for the value of asset havethe same direction of price alternation. The trading volume fluctuates with the pricesignal’s value and has significant relationship with price yield rate. By the way, the“self-believer” rate in market disturbs the cleaning up of price and strength the latestsignal’s effect. The market friction which includes signal and trading friction willincrease the market’s trading volume and price yield rate’s fluctuation.(5) Based on the one-period and multi-signals’ price model, the research had anumerical example analysis with the help of data analysis software such as Matlab andetc. By variable assignment of theory model, we fit several different price and tradingvolume model and it shown great coincidence with theory result, which provided datasupport for the theoretical model.