Over-reliance on Predictive Quantitative Models - Article Example

Over reliance on predictive quantitative models is a dangerous commercial practice. and Section # of Introduction: Quantitative models are used by various individuals, organizations, researchers, analysts, in various different fields of study. The one thing that is most intriguing about the use of quantitative models is the fact that all quantitative models, whether financial, marketing, or general in nature are based on certain assumptions. These assumptions help analysts and researchers evaluate their field of data, statistics and draw certain almost predictable evaluations. These quantitative models are perceived differently in various different fields of study. Literature Review Why use quantitative models in the first place? There can be many conditions differing from situation to situation which could justify the use of a quantitative model. Generally in most cases, there are certain three distinct states that can generally require the usage of a quantitative model. 1. By the side of the selected intensity of aggregation, almost each and every one of the important characteristics or attitudes of the structure have got to be effectively measured. In a case where we are unable to observe such a stipulation not being contented then every model that is being considered will have to be forced to ascribe mathematical values for the incompetent characteristics or attitudes , that can ultimately guide to distortions in several conclusions that are consequently obtained from each of the models Still, wherever all of the significant issues are quantified, there can exist other issues those that are linked with the information and data that may prevent the exploitation of a quantitative model. If for instance the specific data are undependable or in some cases are exceedingly pricey in terms of the time it may require to be collected in or the funds it would cost to assemble, then in the above cases the use of a quantitative model might not be appropriate feasible. 2. The rationale ought to rivet a certain intensity of prejudice or delineation which can only be attained through certain specific mathematical and quantitative comparisons. Some examples of these maybe : Which is mainly efficient intercession? When is this performance expected to evolve into a patent? How many cases of a certain specific situation can be expected each month of the year by any organizational setup? It is said by researchers and analysts that if the chief rationale seems to be achievable devoid of the use of a certain specific quantitative model, it is then advised to inquire about the response in a non-quantitative manner. The rationale behind this being, the fact that the utter intricacy and information congregation essential for nearly all of the quantitative models know how to be factually reasonable if it is vital. 3. An occurrence wherein the scheme of significance encompasses an important amount of responses on the intensity of aggregation necessary. This is most commonly a situation wherein the behavior and effect of a certain variable X tends to affect a certain variable Y, and vice versa. If we observe all the definitions of almost all the quantitative models that exist, we would be able to comprehend the fact that in some cases they would not be required to evaluate the response. On the other hand if the performance of the aim is seemingly directly proportional or directly related to the feedback it would be advisable to use a certain quantitative model for the purpose1. Most of the Quantitative models are based on the assumptions that are simple and not too intricate at all. It is also observed that most of the most quantitative funds managers hold on to the ground rules of contemporary group theory. The fundamental concepts of this issue consist of the capital asset pricing model also famously known as the CAPM model , the Central Value Theory by the famous Graham & Dodd who also named the model after them , the dividend discount model the DDM this is the discounted cash flow model and many more . There are quite a lot of quantitative funds managers who have been able to have evolved certain knots in the conventional portfolio theory. For instance, Stephen Ross, who was the principal investment officer at the of Roll and Ross Asset Management, publicized his pricing theory in the year 1976. This asset pricing model presented by Stephen Ross came out to one of the very first key challenge onto the capital asset pricing model (CAPM). Critiquing Quant Models The Quantitative techniques and the quantitative models have earned themselves much broad approval in the field of asset management. This is because of the sole reason that they tend to make available several detailed facts and figures which evolve into great opportunities which would not be accessible otherwise. The ever evolving conditions and situations tend to alter the response and result received within the due course of time. The nonexistence of or an inadequate coverage to genuine trading is perceived as their furthermost drawback but this may turn out to be their utmost vigor. If we want a model to be valuable in generating surplus proceeds, the use would not be extensive. An investigation of the quantitative models refers to the fact that they formulate logic mutually in perception and in function. There are various stages that can be adopted to guarantee that a certain quantitative model would be the exact fit with the objectives of the specific organization or team. The main objective ought to be to imply exertion with as a small amount of variables as would be possible. Furthermore these should have the guarantee that the contribution being made is dependable. Also in addition, a superior model ought to take into account, the procedures that would eventually reduce the deficit after the execution. 2 Two of the most famous quantitative models are given below: Capital Asset Pricing Model (CAPM) The capital asset pricing model is described as the direct relationship or association between the risk and the expected return. This is basically used in the costing of risky securities. The formula being   The basic idea that is based behind the shell of the capital asset pricing model is that the investors have to be remunerated in two distinct behaviors: 1) By the time value of money and the risk involved. Herein the e time value of money is basically denoted by the (rf) rate i.e. the risk free rate  in the formula above and then subsequently it tends to supplement the investors for keeping the money in any specific form of investment in a specific period of time .It is noticeable that the rest of the formula denotes certain specific kind of risk .This formula also aids in calculating and evaluating The total reimbursement that the investor would eventually in order for him to be able to bare extra risk . The CAPM actually explains the fact that the expected return of a portfolio will be equal to the rate of any risk-free security additional to the risk premium. It further helps decide another crucial matter whether or not the investment should be made? To be able to comprehend this it is upon the user to be able to asses that if the return that is being calculatedly expected is not come over the required rate of return the investment does not sound feasible and thus should not be undertaken. By employing the Capital asset pricing Model in general under the above assumptions it is possible for us to calculate the return that can be expected. It has been observed by analysts that no matter how hard a business tries to diversify in different genres, it is not possible, and the risk element cannot be eliminated at all. All the investors when they intend to invest try and forecast some sort of return in order to compensate themselves on the risk element of the project. The inventor of the Model A financial economist by the name of William Sharpe as the mind behind the invention of this capital asset pricing Model .CAPM. It was in the year 1970 that William Sharpe also wrote a book by the name of "Portfolio Theory and Capital Markets". What he tried to explain via the assumptions and workings of his models was the fact that the investment that is made by any certain specific individual, tends to entail two specific kinds of risk . 1) The systematic risk , which tends to outline the market risks which cannot be avoided or altered away. Interest rates are a famous example of systematic risk. 2) Unsystematic Risk: which is also known as the "specific risk", this pertains to the risk involved in individual stocks . These can be avoided or diversified if needed so by the investor. in order to do this the investor needs to increase the number of stocks existent in the portfolio . there are certain modern ,and contemporary portfolios which represent the fact there are certain specific risks that can be avoided or in other words diversified . The CAPM is usually used to calculate the systematic risk What CAPM basically denotes for an Investor : the rationale behind this model is fairly simple and easy to deliver . The reason that an investor would earn more by one stock than the other would be that one of the stocks would be riskier to invest in. Hence it would not be wrong to conclude the fact that this capita asset pricing model is the one in which it cannot be said entails a perfect theory . A perfect theory in the terms of risk and the return for the investor. All it tends to provide is a very practical manner of calculating ho much risk an investor would have to bare, in order to achieve a certain specific amount of return . 3 The user of the model judging the value of the use of a quantative model It is a very vital and essential question as to how would any potential user who intends to use any quantitative model would be able to differentiate between the real and the face value of its use? The person who has invented one of these many quantitative models may not be able to answer this question in the right manner. As, it would be real rare in these model builder cases that they would evaluate this concept initially. A Framework for Evaluation The users of these models need to realize that the effectiveness of any quantitative model majorly rests on both "suitability" and "excellence." Suitability refers to the acceptance by individuals in organizations who seriously tend to use the model while excellence would refer to the aptitude to make available improved forecasts and decisions. A quantitative model has to be a high scorer on both the attributes only and only if the model scores high enough in both the attributes can it be deemed as advantageous for the user. Habitually, a few adjustments need to be made between suitability and excellence. In order for the quantitative model to fulfill the practical reason of its implementation, it is essential that the true meaning of the terms suitability and excellence be reviewed and understood in order to be sure of the implication of these on the user and the results. For this purpose to be fulfilled a comparative study of the other existing quantitative models would also be an essential , the present model would be considered good and favorable if upon comparison it would not entail the weaknesses of the other alternative models viewed . 4 The Quantitative models are desirable for an assortment of management responsibilities, which include: (a) The recognition of vital variables to make use of for the monitoring, (b) anticipating service level violations by using predictive models. And (c) continuing optimization of configurations. regrettably, the structuring of quantitative models require certain specialized skills that are usually in diminutive supply. Still shoddier, swift alterations in contributor configurations and the development of business demands stand for that quantitative models must be rationalized on an continuing base. 5 Analysis: What we are able to derive and deduce off of the above line under the literature review are the facts that the Capital asset pricing model which has been described as an example of a quantitative model. Describes and outlays certain assumptions upon which it is based. Like wise there are other quantitative models which are used in various fields of study and our daily lives. All are based on certain assumptions. These assumptions we as individuals need to comprehend that are only true in some cases. The variable that are defined along with the se models are fixed in certain situations. They would not stand true in all the cases. Even if in the occurrence of one of the assumptions not being satisfied in the real application of the model, the model would not be able to deduce the expected or forecasted results. It is true though, that in the fast paced world of today we cannot deny the fact that there are more than one instances in the commercial business world, where these quantitative models are used in order to calculate evaluate, certain data that is gathered, certain information that is collected. But yet it is true that these commercial organizations should not rely wholly n these models. If due to one reason or the other the model and its assumptions are not satisfied they will fail and not produce the required results. Also when these models are used commercially this means, they are being used to deduce and also forecast, certain risk and return elements. These models help investors make vital decisions in life regarding their businesses. One wrong decision might mean a loss of a year’s long profit. Conclusion: It would not be wrong to conclude the fact that, these models though are very useful in the sense that they can provide their organizations or even themselves individually of all the probable forecasts of the risk elements and the returns involved. Over reliance on these models can cause severe damage and loss to organizations and individuals in the long run. It is quiet dangerous for commercial as well as individual use, for that matter. And it is also true at this point that over reliance on any one of the models would be dangerous. Bibliography 1) Its Mostly Fundamental: Basics Form Backbone of Quantitative Models. Berkovitz hanks Chicago’s 21 1987 . Vol. 15, Iss. 20; pg. 18, 2 pgs. 2) Glass Richard DChicago: August 8th 1988 . Vol. 16, Iss. 17; pg. 13, 2 pgs 3) By Ben McClure Investopedia advisor Ben is director of McClure & Co., an independent research and consulting firm that specializes in investment analysis and intelligence. Before founding McClure & Co., Ben was a highly-rated European equities analyst at City of London-based Old Mutual Securities. 4) . Analyzing Quantitative Models J. Scott Armstrong and Alan C. Shapiro Reprinted with permission from Journal of Marketing, Vol. 38, No. 2, (1974), 61-66. 5) Generic on-line discovery of quantitative models for service level management Yixin Diao   Eskesen, F.   Froehlich, S.   Hellerstein, J.L.   Keller, A.   Spainhower, L.F.   Surendra, M.   IBM TJ Watson Res. Center, Yorktown Heights, NY, USA; Read More