 The empirical literature in finance shows that the arbitrage pricing theory is unable to identify risk factors while valuing the risky assets. Now the solution to this problem is the introduction of multi-factor models. A multi-factor model is an empirical model that captures the essence of APT and it relies on the direct specification on form of the relationship that the researcher is interested to estimate. This model allows an investor to choose the exact number and identify the exact risk factors. The equation form of this model is that return of if asset is the function of certain factors like F1, F2 and so on these are the multi-factors that are combined into this empirical model. There are number of multiple factors in practice in the finance literature and these are microeconomic based factor models, microeconomic based factor models and third class is the extension of characteristic based risk factor models. The advantage of this multi-factor model is that an investor can know precisely that how many and what things are needed to be estimated to fit the regression equation. A primary disadvantage of this factor is that it is developed with little theoretical guidance as to the true nature of risk return relationship. If we conclude, we can say that developing a useful factor model is as much as an art form and as a theoretical exercise. The first class in this category is the macroeconomic based factor models. There are two models that are discussed here. These are developed by Role and Rose with Chen in 1986 and Bermister in 1994. In an influential model by Role and Chen, they hypothesized that security returns are governed by the set of broad macroeconomic influences in a equation and that equation is basically carrying certain factors. These factors are RM which is the return on a value weighted index of any recognized stock exchange, MP stands for monthly growth rate in the US industrial production, DEI is the change in inflation measured by US CPI or consumer price index, UI is the difference between actual and expected level of inflation, UPR is the unanticipated change in the bond credit spread like BAA yield minus the risk free rate and finally UTS is the unanticipated term structure shift that is the difference between long term and the short term risk free rate. These are the factors that are described in the equation set by these researchers. There is another model by Role and Rose with Bermister. They analyzed a model based on the different set of macroeconomic factors using the falling characteristics. These are confidence risk, time horizon risk, inflation risk, business cycle risk and market timing risk. Now what these terms are stands for, CR means changes in investors' willingness to take on investment risk, TR is the changes in investors' desired time to get payouts, IR is a mix of unexpected components of short term and long term inflation rates, BR is the unanticipated changes in level of overall business activity whereas MR is the part of the standard and poor's 500 total return not explained by the other four microeconomic factors. The second category in this multiple factor, factor models is the microeconomic based risk factor model. These models focus on relevant characteristics of security itself to specify the risk using proxy variables like a firm size and other financial resources of the firm. In this class there is an approach called as Fama and French approach and that approach is used for valuing the risky assets. This is a basically a three factor model approach where RMT minus RFR is the access market return and that is the dependent variable in their model where SMB is basically the difference between return on small capitalized stock and the large capitalized stock. HML basically is the difference between high book to market portfolio and the low book to market portfolio. As SMB captures the firm's size and HML basically distinguishes between the growth risk from the value risk. The third category in the class of multi factor model is the extensions of characteristic based risk factor models. This class involves the usage of index portfolios as a common factor. Elton Gruber and Blake built a model using certain indices like they use the standard poor 500, the Barclays capital aggregate bond indexes, the potential batch index of the difference between the large capital capitalized and small capitalized stocks. And last is the potential batch index of the difference between value and growth stock. So these are the five factors that these researchers used in their empirical model. Another model is set by Fersen and the Schaath. They developed index using stock and bond indexes as the risk factors. And they also used in this model other public information variables like the shape of yield curve and the dividend payouts. In this line there is an other researcher MSEI Barahu developed the multi factor model using several characteristic risk based variables as the risk factors and the 50 plus industry indices.