The wide acceptance and use of the Portfolio theory has drew criticism from its detractors in the basis of the argument of the market efficiency hypothesis. Its utilization as a primary source of assessing risk on a companys and regulators perspectives calls for the ideology that the imperfections of a financial market does not call for the methodology used in risk management.
Perhaps, the systematic assumptions derived from risk management debunks the probabilistic nature of risk its very inception questions the figures derived from Value-at-Risk measures.
The attempts to provide alternative theories surrounding risk measurement and management
MotivationWhy do we care about the problem and the results If the problem isnt obviously interesting it might be better to put motivation first but if your work is incremental progress on a problem that is widely recognized as important, then it is probably better to put the problem statement first to indicate which piece of the larger problem you are breaking off to work on. This section should include the importance of your work, the difficulty of the area, and the impact it might have if successful.
Problem statementWhat problem are you trying to solve What is the scope of your work (a generalized approach, or for a specific situation) Be careful not to use too much jargon. In some cases it is appropriate to put the problem statement before the motivation, but usually this only works if most readers already understand why the problem is important.
ApproachHow did you go about solving or making progress on the problem Did you use simulation, analytic models, prototype construction, or analysis of field data for an actual product What was the extent of your work (did you look at one application program or a hundred programs in twenty different programming languages) What important variables did you control, ignore, or measure
ResultsWhats the answer Specifically, most good computer architecture papers conclude that something is so many percent faster, cheaper, smaller, or otherwise better than something else. Put the result there, in numbers. Avoid vague, hand-waving results such as very, small, or significant. If you must be vague, you are only given license to do so when you can talk about orders-of-magnitude improvement. There is a tension here in that you should not provide numbers that can be easily misinterpreted, but on the other hand you dont have room for all the caveats.
ConclusionsWhat are the implications of your answer Is it going to change the world (unlikely), be a significant win, be a nice hack, or simply serve as a road sign indicating that this path is a waste of time (all of the previous results are useful). Are your results general, potentially generalizable, or specific to a particular case
In every investment being done at a financial market, there is always a certain degree of risk involved. With the advent of the financial crisis, traders has been adamant in dipping into the financial markets with the stability of financial markets such that there is an accepted knowledge that the risk of obtaining the true valuation of an investment may not hold true in the long run. As such, the development of more statistical yet difficult models are done that primarily the reason of their developments are to appease the individuals or organizations to characterize, identify and act upon the financial risks. In a most basic sense, the drive to be successful is attuned to the intention of adopting hopefully more stringent measures to escape the financial risks.
Galichon (year) echoes that the single most used measure of financial risk is the Value -at Risk measure. Furthermore, it is also used as a benchmark measure to budget capital regulatory requirements.
Lozovaia and Hizhniakova (year) discusses the importance of the Portfolio theory as to Value at Risk, such that by its definition, the Portfolio theory attempts to provide reasoning that the concept of diversification can be accomplished to reduce further risk and maximize returns on a portfolio, and that Value at Risk attempts to discuss the loss that can be derived on a particular portfolio.
The applications of the modern portfolio theory with regard to financial risk is still practical. In congruence to an efficient financial market, the behavior and decisions of all interested parties must be attuned to that of an inefficient market.
Purpose of the Study
For a companys management, the practical application of risk to management decisions regarding investment and debt-transfer decisions. For example, the management may consider extending a takeover bid to another company in compliance to their one of their company goals in securing a market share percentage in their industry (Kraft V. Cadbury).
It has also been established that regulators have been vigilant in maintaining an efficient financial market in their scopes such that the financial markets are integrated. In this line of reasoning, the general truth that the financial markets are the compounds of one global market in which every company wishes to penetrate. As such, the inefficiency of the global market will have ripple effects on the aggregate financial markets, and that the effects of market inefficiencies (financial bubbles, The Great Depression) has lead the regulating consensus on not letting history repeating itself.
The prudential regulation of financial institutions requires the maintenance of minimum levels capital as reserves against financial risks. The Basel Committee on Banking Supervision, The US Federal Reserve Bank, The US Securities and Exchange Commission, and regulators in the European Union have converged on VAR as a benchmark risk measure.
Jorion (year) further added that the contribution of VAR measures lies in the imposition of a structured methodology for critically thinking about risk. Though there are studies that provides a clear grasp and measure on risk, organizations are then reprimanded by restrictive impositions by regulatory bodies by implementing the judicious function of VAR.
Since the modern portfolio theory assesses the asset valuation (or asset-pricing), regulators act as protectants to financial crisis in markets and instigators of ethical behavior and practices in stock market transactions of companies. The independent regulator also has forwarded the cause of companies implementing self-regulation policies in the company s core values and framework.
Rationale of the Study
The basis for this study perhaps is to take a studied look at the ethical considerations of valuation and risk in companies.
In the modern times, we have yet to learn from the historical events regarding the catastrophic events of incorrect valuation that is mostly derived from greed.
Though it is a company s core to earn profit (by reducing debt), we have yet to learn from the Japanese, that the concept of achieving profit is merely a benefit, as the concept of being in the business is the major key of success.
In a world were money is still power, it is a hard concept for profit-driven companies to integrate the attitude of a true businessman much demonstrated by the Japanese.
Liker (year) quotes Jim Press, Executive Vice President and C.O.O of Toyota Motor Sales in North America
The purpose of the money we make is not for us as a company to gain, and it s not for us as associates to see our stock portfolio grow or anything like that. The purpose is so we can reinvest in the future, so we can continue to do this. That is the purpose of our investment. And to help society and to help the community, and to contribute back to the community that we re fortunate enough to do business in. I ve got a trillion examples for that. (72)
It is to note that he is one of the two American Managing Directors of Toyota. As such, the philosophy is not just limited to the Japanese.
Literature Review
Financial risk management is a process to deal with the uncertainties resulting from financial markets (Horcher, year, p. 3). Considering the volatility of financial markets, it is essential that risks must be identified and addressed for management to develop strategies in managing a company through the financial markets at minimum risk.
A company s framework of company goals evolves in the success of the company in its capability to achieve its company objectives. As such the efficiency of risk measures must be at optimum such that it balances the success in achieving company objectives as accepted by the management, and the amount or value of risk that the company can tolerate with such undertaking of corporate strategies.
The emphasis of valuation of a company lies in the company s interest to be attractive to the people of interest investors, financing institutions, and stakeholders alike.
In a stock market, valuation is as important such that a company will be exposed to a variety of opportunities to be competitive and strong in such a volatile market. The volatility of the market presents opportunities of a company to be financially attractive to these persons of interest. Investors, for one, will likely apply themselves in the long run as present andor future stakeholders, which may also present capitalization opportunities for the company to expand and grow bigger. On the other hand, financing institutions will present opportunities as well, somewhat the same as the investors, by way of financing capital expenditures and other management decisions by the company due to its attractive credit ratings.
On the other hand, information might as well spell power in a ever-changing world. In a stock market, the valuation of a company is correlated to the exchange of information taking place in the financial market.
Portfolio theory
The beginnings of the portfolio theory were derived from Harry Max Markowitz, an American economist who was notable with his then eventual development of the theory today.
Elton and Gruber (year, p. 25) observes
Markowitz (1952, 1959) formulated the portfolio problem as a choice of mean and variance of a portfolio of assets. He proved that the fundamental theorem of mean variance portfolio theory, namely holding constant variance, maximize expected return, and holding constant expected return minimize variance. These two principles led to the formulation of an efficient frontier from which the investor could choose his or her portfolio, depending on individual risk preferences.
Value at Risk
Value at risk is a method of assessing risk that use statistical techniques that measures the worst expected loss over a given horizon under normal market conditions at a given confidence level (Jorion, year). As such, these risk measures provide interested users a summary measure of market risk.
Furthermore, the use of these measures provides a total insight of a portfolio s risk that accounts for leverage, correlations, and current positions. In a nutshell, Value at Risk measures provide a formidable future of the effects of management decisions with the considerations of risks being identified. It would also allow interested parties to look into the efficiency of management strategies and regulatory statutes in a financial market.
Research Methodology and Proposed Approach
It is appropriate for management and regulators to acknowledge the exposure of a company to such risks (Horcer, year, p. 205).
For our study, we can adopt the ARIMA model. Considering that stock valuations are affected by random walks , random-walk and random-trend are apt as statistical methods for forecasting sample data of time series variables.
The basis of using the ARIMA model is under the presumption that stock prices evolve according to its randomness. The correlation of the randomness of stock prices is with the degree of efficiency of a financial market.
To measure the pract
A nonseasonal ARIMA model is classified as an ARIMA(p,d,q) model, where
p is the number of autoregressive terms,
d is the number of nonseasonal differences, and
q is the number of lagged forecast errors in the prediction equation.
To identify the appropriate ARIMA model for a time series, you begin by identifying the order(s) of differencing needing to stationarize the series and remove the gross features of seasonality, perhaps in conjunction with a variance-stabilizing transformation such as logging or deflating. If you stop at this point and predict that the differenced series is constant, you have merely fitted a random walk or random trend model. (Recall that the random walk model predicts the first difference of the series to be constant, the seasonal random walk model predicts the seasonal difference to be constant, and the seasonal random trend model predicts the first difference of the seasonal difference to be constant--usually zero.) However, the best random walk or random trend model may still have autocorrelated errors, suggesting that additional factors of some kind are needed in the prediction equation.
ARIMA(0,1,0) random walk In models we have studied previously, we have encountered two strategies for eliminating autocorrelation in forecast errors. One approach, which we first used in regression analysis, was the addition of lags of the stationarized series. For example, suppose we initially fit the random-walk-with-growth model to the time series Y. The prediction equation for this model can be written as where the constant term (here denoted by mu) is the average difference in Y. This can be considered as a degenerate regression model in which DIFF(Y) is the dependent variable and there are no independent variables other than the constant term. Since it includes (only) a nonseasonal difference and a constant term, it is classified as an ARIMA(0,1,0) model with constant. Of course, the random walk without growth would be just an ARIMA(0,1,0) model without constant
Perhaps, the systematic assumptions derived from risk management debunks the probabilistic nature of risk its very inception questions the figures derived from Value-at-Risk measures.
The attempts to provide alternative theories surrounding risk measurement and management
MotivationWhy do we care about the problem and the results If the problem isnt obviously interesting it might be better to put motivation first but if your work is incremental progress on a problem that is widely recognized as important, then it is probably better to put the problem statement first to indicate which piece of the larger problem you are breaking off to work on. This section should include the importance of your work, the difficulty of the area, and the impact it might have if successful.
Problem statementWhat problem are you trying to solve What is the scope of your work (a generalized approach, or for a specific situation) Be careful not to use too much jargon. In some cases it is appropriate to put the problem statement before the motivation, but usually this only works if most readers already understand why the problem is important.
ApproachHow did you go about solving or making progress on the problem Did you use simulation, analytic models, prototype construction, or analysis of field data for an actual product What was the extent of your work (did you look at one application program or a hundred programs in twenty different programming languages) What important variables did you control, ignore, or measure
ResultsWhats the answer Specifically, most good computer architecture papers conclude that something is so many percent faster, cheaper, smaller, or otherwise better than something else. Put the result there, in numbers. Avoid vague, hand-waving results such as very, small, or significant. If you must be vague, you are only given license to do so when you can talk about orders-of-magnitude improvement. There is a tension here in that you should not provide numbers that can be easily misinterpreted, but on the other hand you dont have room for all the caveats.
ConclusionsWhat are the implications of your answer Is it going to change the world (unlikely), be a significant win, be a nice hack, or simply serve as a road sign indicating that this path is a waste of time (all of the previous results are useful). Are your results general, potentially generalizable, or specific to a particular case
In every investment being done at a financial market, there is always a certain degree of risk involved. With the advent of the financial crisis, traders has been adamant in dipping into the financial markets with the stability of financial markets such that there is an accepted knowledge that the risk of obtaining the true valuation of an investment may not hold true in the long run. As such, the development of more statistical yet difficult models are done that primarily the reason of their developments are to appease the individuals or organizations to characterize, identify and act upon the financial risks. In a most basic sense, the drive to be successful is attuned to the intention of adopting hopefully more stringent measures to escape the financial risks.
Galichon (year) echoes that the single most used measure of financial risk is the Value -at Risk measure. Furthermore, it is also used as a benchmark measure to budget capital regulatory requirements.
Lozovaia and Hizhniakova (year) discusses the importance of the Portfolio theory as to Value at Risk, such that by its definition, the Portfolio theory attempts to provide reasoning that the concept of diversification can be accomplished to reduce further risk and maximize returns on a portfolio, and that Value at Risk attempts to discuss the loss that can be derived on a particular portfolio.
The applications of the modern portfolio theory with regard to financial risk is still practical. In congruence to an efficient financial market, the behavior and decisions of all interested parties must be attuned to that of an inefficient market.
Purpose of the Study
For a companys management, the practical application of risk to management decisions regarding investment and debt-transfer decisions. For example, the management may consider extending a takeover bid to another company in compliance to their one of their company goals in securing a market share percentage in their industry (Kraft V. Cadbury).
It has also been established that regulators have been vigilant in maintaining an efficient financial market in their scopes such that the financial markets are integrated. In this line of reasoning, the general truth that the financial markets are the compounds of one global market in which every company wishes to penetrate. As such, the inefficiency of the global market will have ripple effects on the aggregate financial markets, and that the effects of market inefficiencies (financial bubbles, The Great Depression) has lead the regulating consensus on not letting history repeating itself.
The prudential regulation of financial institutions requires the maintenance of minimum levels capital as reserves against financial risks. The Basel Committee on Banking Supervision, The US Federal Reserve Bank, The US Securities and Exchange Commission, and regulators in the European Union have converged on VAR as a benchmark risk measure.
Jorion (year) further added that the contribution of VAR measures lies in the imposition of a structured methodology for critically thinking about risk. Though there are studies that provides a clear grasp and measure on risk, organizations are then reprimanded by restrictive impositions by regulatory bodies by implementing the judicious function of VAR.
Since the modern portfolio theory assesses the asset valuation (or asset-pricing), regulators act as protectants to financial crisis in markets and instigators of ethical behavior and practices in stock market transactions of companies. The independent regulator also has forwarded the cause of companies implementing self-regulation policies in the company s core values and framework.
Rationale of the Study
The basis for this study perhaps is to take a studied look at the ethical considerations of valuation and risk in companies.
In the modern times, we have yet to learn from the historical events regarding the catastrophic events of incorrect valuation that is mostly derived from greed.
Though it is a company s core to earn profit (by reducing debt), we have yet to learn from the Japanese, that the concept of achieving profit is merely a benefit, as the concept of being in the business is the major key of success.
In a world were money is still power, it is a hard concept for profit-driven companies to integrate the attitude of a true businessman much demonstrated by the Japanese.
Liker (year) quotes Jim Press, Executive Vice President and C.O.O of Toyota Motor Sales in North America
The purpose of the money we make is not for us as a company to gain, and it s not for us as associates to see our stock portfolio grow or anything like that. The purpose is so we can reinvest in the future, so we can continue to do this. That is the purpose of our investment. And to help society and to help the community, and to contribute back to the community that we re fortunate enough to do business in. I ve got a trillion examples for that. (72)
It is to note that he is one of the two American Managing Directors of Toyota. As such, the philosophy is not just limited to the Japanese.
Literature Review
Financial risk management is a process to deal with the uncertainties resulting from financial markets (Horcher, year, p. 3). Considering the volatility of financial markets, it is essential that risks must be identified and addressed for management to develop strategies in managing a company through the financial markets at minimum risk.
A company s framework of company goals evolves in the success of the company in its capability to achieve its company objectives. As such the efficiency of risk measures must be at optimum such that it balances the success in achieving company objectives as accepted by the management, and the amount or value of risk that the company can tolerate with such undertaking of corporate strategies.
The emphasis of valuation of a company lies in the company s interest to be attractive to the people of interest investors, financing institutions, and stakeholders alike.
In a stock market, valuation is as important such that a company will be exposed to a variety of opportunities to be competitive and strong in such a volatile market. The volatility of the market presents opportunities of a company to be financially attractive to these persons of interest. Investors, for one, will likely apply themselves in the long run as present andor future stakeholders, which may also present capitalization opportunities for the company to expand and grow bigger. On the other hand, financing institutions will present opportunities as well, somewhat the same as the investors, by way of financing capital expenditures and other management decisions by the company due to its attractive credit ratings.
On the other hand, information might as well spell power in a ever-changing world. In a stock market, the valuation of a company is correlated to the exchange of information taking place in the financial market.
Portfolio theory
The beginnings of the portfolio theory were derived from Harry Max Markowitz, an American economist who was notable with his then eventual development of the theory today.
Elton and Gruber (year, p. 25) observes
Markowitz (1952, 1959) formulated the portfolio problem as a choice of mean and variance of a portfolio of assets. He proved that the fundamental theorem of mean variance portfolio theory, namely holding constant variance, maximize expected return, and holding constant expected return minimize variance. These two principles led to the formulation of an efficient frontier from which the investor could choose his or her portfolio, depending on individual risk preferences.
Value at Risk
Value at risk is a method of assessing risk that use statistical techniques that measures the worst expected loss over a given horizon under normal market conditions at a given confidence level (Jorion, year). As such, these risk measures provide interested users a summary measure of market risk.
Furthermore, the use of these measures provides a total insight of a portfolio s risk that accounts for leverage, correlations, and current positions. In a nutshell, Value at Risk measures provide a formidable future of the effects of management decisions with the considerations of risks being identified. It would also allow interested parties to look into the efficiency of management strategies and regulatory statutes in a financial market.
Research Methodology and Proposed Approach
It is appropriate for management and regulators to acknowledge the exposure of a company to such risks (Horcer, year, p. 205).
For our study, we can adopt the ARIMA model. Considering that stock valuations are affected by random walks , random-walk and random-trend are apt as statistical methods for forecasting sample data of time series variables.
The basis of using the ARIMA model is under the presumption that stock prices evolve according to its randomness. The correlation of the randomness of stock prices is with the degree of efficiency of a financial market.
To measure the pract
A nonseasonal ARIMA model is classified as an ARIMA(p,d,q) model, where
p is the number of autoregressive terms,
d is the number of nonseasonal differences, and
q is the number of lagged forecast errors in the prediction equation.
To identify the appropriate ARIMA model for a time series, you begin by identifying the order(s) of differencing needing to stationarize the series and remove the gross features of seasonality, perhaps in conjunction with a variance-stabilizing transformation such as logging or deflating. If you stop at this point and predict that the differenced series is constant, you have merely fitted a random walk or random trend model. (Recall that the random walk model predicts the first difference of the series to be constant, the seasonal random walk model predicts the seasonal difference to be constant, and the seasonal random trend model predicts the first difference of the seasonal difference to be constant--usually zero.) However, the best random walk or random trend model may still have autocorrelated errors, suggesting that additional factors of some kind are needed in the prediction equation.
ARIMA(0,1,0) random walk In models we have studied previously, we have encountered two strategies for eliminating autocorrelation in forecast errors. One approach, which we first used in regression analysis, was the addition of lags of the stationarized series. For example, suppose we initially fit the random-walk-with-growth model to the time series Y. The prediction equation for this model can be written as where the constant term (here denoted by mu) is the average difference in Y. This can be considered as a degenerate regression model in which DIFF(Y) is the dependent variable and there are no independent variables other than the constant term. Since it includes (only) a nonseasonal difference and a constant term, it is classified as an ARIMA(0,1,0) model with constant. Of course, the random walk without growth would be just an ARIMA(0,1,0) model without constant
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