Behavioral Finance- Microeconomics Theories - Literature review Example

Behavioral Finance- Microeconomics Theories Behavioral Finance- Microeconomics Theories Absence of a body of positive micro economic theory relating to risk condition has beset those attempting to predict the behaviour of capital markets. Traditional models have given insights of investment considering certain conditions of certainty though many prefer the method of price behaviour. Economics is a science due to the complications in the subject matter and complications, in the mechanism of prices and production. There has been an analysis of the behaviour of individuals constituting the economic community to illustrate the development of economics. Capital asset prices undergo description carefully, the individual preferences and physical relationships and their interactions for the determination of an equilibrium pure interest rate. The assertion is that a market risk premium has adjusting asset prices to account for risk differences. The consumer desires to obtain maximum utility and satisfaction while getting maximum profits for the entrepreneur. The aim of all participants in the economic system- that is consumers and entrepreneurs- is a single monetary commodity. The theory of individual’s choices regarding to indifference curve analysis revolves around the same facts but uses a superior mathematical method. The view of capital markets can be shown as follows; Risk Capital market line 0 Pure interest rate Expected rate of return At equilibrium, capital asset prices have an adjustment such that the investor using primary diversification which attains the desired point along the capital market line. Incurring of additional risk helps attain high rates of return. The market presents two prices that are; the price of time and the price of risk. There has been a proposal relating to the utility maxim and the general solution for the portfolio selection problem (Von Neumann and Morgenstern, 2007). The process of making an investment choice includes; choosing a unique optimum combination of risky assets and separate choice regarding to the allocation of funds. For maximum satisfaction, there is consideration of the assumptions relating to numerical character of utility which depends on the number of variables and the nature of the maximized function. The simplified model of the isolated individual for the social exchange economy does not represent an individual exposed to the manifold influences of the society (Von Neumann and Morgenstern, 2007). To obtain a maximum resulting satisfaction, there is combination and application of certain wants and commodities. The weakness of this model is it’s cumbersome to separate the purely technical from the ones in the conceptual nature. In classical mathematics, there is an emphasis on the pedantic risk which explains that there is no conditional maximum problem relating to calculus of variations and functional analysis. In behavioural finance, there is consideration of the greatest possible good for the greatest possible number. There has been a suggestion by Hirshleifer “the mean-variance approach is a unique case of a general formulation due to Arrow” (Markowitz, Miller & Sharpe, 1991). According to Mr. Jack Treynor, the total utility function can be given by U = f (E, a) illustrating the meters of distribution and the expected value and the standard deviation, where E indicates the future wealth and a shows the standard deviation under prediction (Markowitz, Miller & Sharpe, 1991). There is the preference of a high expected future wealth to a value which is low; this is known as ceteris paribus illustrated as (dU/dEw > 0). This leads to an upward slope as seen in the earlier graph of risk against the expected rate of return. For a simpler analysis, there is an assumption that an investor decides to commit an amount (W) of their wealth to investment. By letting R be the rate of return and W as the terminal wealth, then; R= (Wt- Wi)/Wi. Thus, Wt= R Wi + Wi The above relationship helps to express the investor’s utility in terms of R. this is because the terminal wealth has a relation to the rate of return. U=g (E, a). The mean-variance under certain conditions leads to unsatisfactory predictions of behaviour. A model based on semi-variance is preferable basing on standard deviation and variance (Markowitz, Miller & Sharpe, 1991). There is an assumption that the curves can diminish marginal rates of substitution between E and α, from the earlier equations. There is a derivation of indifference curves from the assumption that the investor wishes to maximise the expected utility and thus, the total utility can be represented by a quadratic function of R indicative of a decreasing marginal utility. The difference between Crusoe aspect of the economy and that of participants is that Crusoe gets a number of data which are unalterable physical background of the situation (Mishan, 2007). There is the use of variables where every participant gets a set of variables describing the actions. This creates the partial sets of variables. The total number of variables got by the number of participants and the number of variables in every partial set. Every participant gets influence by the foreseeable reactions of another to his own measures regarding to the sellers that are in the classical resolutions of oligopoly and duopoly. According to the current economic theory unlike the traditional theory, many branches of the exact physical sciences having influential figures are easy to handle comparing to those with medium sizes. This leads to the idea of free competition where the solutions are uniquely and sharply determined. In my opinion, free competition is between vendors for the provision of services and products where price tends to decrease while the quality increases. The topic in discussion avoids the real complexity and deals with a vocal problem which is an empirical one (Von Neumann & Morgenstern, 2007). There is the conception of utility as a quantitatively measurement, taken as a number. According to this theory, a numerical utility is dependent due to the possibility of making a comparison between the differences in utilities. Two alternatives are mutually exclusive such that no probability of complementarities exists. That is by getting the probability of events A, B and C which are two mutually exclusive events. Considering an accepted standpoint, there is a criterion that is in use in comparing the preference of the variables A, B or C, well known that differences of utilities are numerically measureable. Probability gets visualisation as a subjective concept which is more or less related to the nature of estimation, finding the probability helps in getting the procedure for a measurement of the utilities of individuals which depends on the hypothesis of completeness of individual preferences, thus use of indifference curves is not plausible. Considering two events A and B, the proportion of the individuals wealth is the event A while the remainder is B; thus the expected return rate of the combination lies between the expected returns of events A and B. given by the equation; ER= αERa + (1-α) ERb To make a comparison between various preferences a graph of variables is as in the following. B aRb A Z CRa ER Era ERb Because ERc and αRc have a linear relationship to the proportions invested in the two plans, thus if there is a perfect correlation, the combinations lie along a straight line between the two points. The standard deviation of any combination is less than the obtained value with perfect correlation if the investments are less than perfectly positive correlation. This makes the combination lie along a curve below the line AB shown in the earlier figure. A point to note, the physic geometrical concepts, which are in, vector form including velocity and acceleration allow for the addition operand. Energy and mass are numbers in mathematical models while position and other vector quantities become coordinates. When using a physical quantity, the system of transformations under description by numbers varies in time and is the stage of development of the subject. Example of such physical quantity is temperature which was initially a number until the monotone transformation (Sharpe, 2007). When dealing with riskless assets, their risks are usually zero while the expected rate of return is equal to the pure interest rate. In equating the quantities in riskless assets, the curvature is essentially the rationale for diversification thus; the problem is a parametric quadratic programming problem (Markowitz, Miller & Sharpe, 1991). Considering the investment possibility, one can borrow at a considerable rate of interest. If an investor borrows to buy more of the available investment plan, then there is a negative value in the equation. When lending, one investment plan, dominate the others when it is possible to borrow, given that the rate of borrowing funds is equal to the rate of lending. The assumptions considered in this are universal, pure rate of interest and homogeneity of the expectations of the investors. For the case where the wholesome rate of interest is zero, there is consideration of the lending situation under comparable conditions but not allowing borrowing. Hick’s analysis assumes independence thus insuring that the solution includes no negative holding of assets which are risky. Further, there is a non-negativity constraint when holding all the assets (Markowitz, Miller & Sharpe, 1991). In my opinion, the authors argue that the probability of an investor not taking an investment plan because the other has failed to take the plan is almost negligible This is because investors have their taste and preferences when it comes to taking investment plans. There is an indicator that the failure of one device does not necessarily exclude the possibility of achieving a corresponding conclusion by another device. The domain of utility has natural operation narrowing the system of transformation to the same extent that the other devices ought to have done. From the previous equation, if investors consider variability of future currency returns which has no relation to present price, both ER and αR fall, this is due to the change in price. The values of ER and αR associated with single assets lie above the capital market line thus creating a reflection of the inefficiency of undiversified holdings. Thus, there is no consistent relationship between the expected return and the total risk (αR). There is a consistent relationship between the expected returns and the systematic risk; as shown in the following graph. αR P ER The graph is an indication of the diagonal model. This is because its portfolio analysis solution comes by reorganising the data such that the variance-covariance matrix becomes oblique. This part of the total risk of the assets is the systematic risk while what remains is the unsystematic component. In my own understanding, the part on the diagram that indicates the magnitude of this risk has a direct relation to the expected returns. There is an arbitral selection of the combinations thus the rate of return from all proficient combination has an entire correlation (Sharpe, 2007). In finding the probability, it is conclusive to state that the probability indicates a plausible explanation for the implication such that, all the efficient combinations have a perfect correlation. This implies that there is useful interpretation of the relationship between the asset’s expected rates of returns including the risks for an individual (Sharpe, 2007). From the theory earlier discussed, it is indicative that the rates of return from efficient combinations are perfectly correlated. This is because of their dependence on the total level of economic activity. Diversification is crucial since it enables the investors escape most risks, this due to the variation in economic activity whereby the risk is always constant even when the combinations are efficient. The responsiveness of an asset’s return rate to the economic activity level is relevant when determining the risk. A linear relationship between the expected returns and the magnitude, come from the adjustment in prices. From the author’s point of view, the rations of a logical framework in the production of vital elements in the traditional financial theory are useful in its right. References MARKOWITZ, H., MILLER, M. H., & SHARPE, W. F. (1991). The founders of modern finance: their prize-winning concepts and 1990 Nobel lectures. [Charlotlesville, Va.], Research Foundation of the Institute of Chartered Financial Analysis. MISHAN, E. (2007). Cost Benefit Analysis. London: Routledge SHARPE, W. F., (2007). Investors and markets: portfolio choices, asset prices, and investment advice. Princeton: Princeton University Press. TREYNOR, J. L. (2011). Toward a theory of market value of risky assets. Princeton: Princeton University Press. VON NEUMANN, J., & MORGENSTERN, O. (2007). Theory of games and economic behavior. Princeton, NJ [u.a.], Princeton Univ. Press. Read More