Corporate Finance: Investment Strategies and Risk-Weighted Assets

This report delves into key aspects of corporate finance, beginning with an examination of standard deviation as a measure of investment portfolio volatility and its relationship to risk assessment. It discusses the role of financial dispersion in understanding investor behavior and the use of normal distribution in portfolio optimization for balancing risk and return. The report further analyzes diversification strategies, emphasizing the importance of covariance and correlation coefficients in reducing portfolio volatility. It explains how diversifiable risks can be mitigated through correlation analysis, highlighting the challenges of achieving zero correlation in real-world scenarios. Finally, the report addresses risk-weighted assets (RWA) and their significance in determining capital adequacy, particularly focusing on the impact of risk-free assets on overall portfolio risk, concluding that even a single risk-free asset can nullify the overall risk contribution in RWA calculations. Desklib offers this report as a valuable resource for students studying finance, alongside a wealth of other solved assignments and study materials.

Running head: CORPORATE FINANCE
Corporate Finance
Name of the Student
Name of the University
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Table of Content

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s
Answer to Question 1.................................................................................................................2
Answer to Question 2.................................................................................................................3
Answer to Question 3.................................................................................................................4
References..................................................................................................................................6

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Answer to Question 1
The computation SD is commonly seen in statistic for measurement of dispersion.
This is considered as a simple procedure for investment in volatility of the portfolio. The
lesser is the amount of SD, lesser is the volatility. Dispersion is considered as a statistical
term which describes the range of values which are related to particular variables. The
financial dispersion is further used to study the effects associated with the investors and
analysis of the beliefs pertaining trading of securities. These are further seen to be depicted in
terms of variability of returns as a result of a particular trading strategy. The risk
measurement beta is considered with measures of dispersion as per the security’s return
which relative to the market or benchmark. In case the dispersion is seen to be greater than
the benchmark, the security is considered to be riskier in compared to benchmark. On the
hand, a security is regarded as less risky in case the dispersion is seen to be less risky than
benchmark1.
Normal distribution is considered as the probability distribution for plotting of the
values in a symmetrical manner considered with the mean of the probability. The
optimization of the portfolio is seen to be based on considering the lowest possible value for
the risk and highest value for returns. Therefore, the use of normal distribution aids in the
process of mean for returns and standard deviation for risk. For example, in real situation the
share price may go up by 1.5% on a daily basis, this means that the expected value has strong
significance as per the expected value2.
The expected return as per the probability distribution has been further depicted as the
function which shows all possible value during the evaluation for the expected return from a
1 Bessis, Joel. Risk management in banking. John Wiley & Sons, 2015.
2 DeAngelo, Harry, and René M. Stulz. "Liquid-claim production, risk management, and bank capital structure:
Why high leverage is optimal for banks." Journal of Financial Economics116, no. 2 (2015): 219-236.

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portfolio. This analysis is further seen to be confined with the range of derived statistical
possibility of selecting the range of discrete and continuous inputs of the share prices3.
Answer to Question 2
The consideration of adding the new shares is mainly identified with the dependence
on diversification strategy. Covariance aids in the process of diversification and reducing the
volatility in the portfolio. This is considered as the measure for determining how two assets
move corresponding to each other. Positive value of the covariance suggests how the assets
vary in similar manner. On the other hand, the negative value in the covariance indicates that
the assets move in the opposite directions. However, covariance is identified with certain
limitations which depicts the direction among the two assets. It cannot provide the specific
relation between the process. This gap needs to be filled with the determination of the
correlation coefficient between the assets for measuring the strength among the same. The
risks which are diversifiable in nature can be reduced with the use of coefficients of
correlation of the assets. This measures the degrees of correlation ranging from -1 from a
perfectly negative correlation of +1 depicted with a perfectively positive correlation4.
As the correlation is identified as the statistical measure of perfectly uncorrelated pair
of investments the possibility of zero correlation coefficient is rarely possible in real practice.
In general, even the most diversified portfolio will bear the greatest negative correlation.
Even for a portfolio of uncorrelated assets there may be higher degree of risk, which is less
than the positively correlated investment decisions. It needs to be understood that a positive
correlation in the portfolio is identified with less risk when compared with single assets or
investments which are completely positively correlated. It needs to be however determined
3 Olson, David L., and Desheng Dash Wu. Enterprise risk management. Vol. 3. World Scientific Publishing
Company, 2015.
4 McNeil, Alexander J., Rüdiger Frey, and Paul Embrechts. Quantitative Risk Management: Concepts,
Techniques and Tools-revised edition. Princeton university press, 2015.

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that there is no scope of reducing the overall risk even with the combination of assets with
positive correlation.
The application of the SD is applied to the investment returns which are based on the
quantitative statistical measure pertaining to the variation for the specific returns as per the
average of the returns. The risk is generally represented by SD of the expected returns of an
asset which is equal to the square of the variance. The calculation of the variances using the
SD for two assets are depicted with the probability of multiplying the return for the state less
the square of the expected return5.
Answer to Question 3
The risk weighted assets (RWA) are represented as the bank’s assets pertaining to the
off-balance sheet exposures which are weighted as per the risk. This asset is useful in
determining the capital requirement or CAR as per the financial situation. In practical terms
this computation is depicted to be useful in terms of determining comparison of rate of return
among banks. In addition to this, the off-balance sheet exposure exposures can be easily
considered for the capital adequacy determinations. The different classes of assets are
determined with different risk weights associated to them. Such assets are typically inferred
with debentures which has higher risk associated in compare to others6.
As per the given statement it has been asked what the implication of combination of
two assets in case of the two assets would be was risk free during the computation of
weighted risk of two assets. It needs to be discerned that if even one of the asset is risk free
the net impact on the overall risk will be zero. As per the formula of RWA, the risk rate is
multiplied with the expected rate of return. Therefore, even if there is decrease in the risk
5 Chance, Don M., and Roberts Brooks. Introduction to derivatives and risk management. Cengage Learning,
2015.
6 Lam, James. Enterprise risk management: from incentives to controls. John Wiley & Sons, 2014.

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rates the added result for the overall risk will be zero. This is mainly due to the fact the risk of
the portfolio is multiplied with the expected rate of the return for one asset and further added
with the same rate to other assets. As the rates are multiplied all along the computation of
RWA, even if the risk-free rate is 1, the net impact on the overall risk of the portfolio will be
nil7.
7 Wolke, Thomas. Risk Management. Walter de Gruyter GmbH & Co KG, 2017.

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References
Bessis, Joel. Risk management in banking. John Wiley & Sons, 2015.
Chance, Don M., and Roberts Brooks. Introduction to derivatives and risk management.
Cengage Learning, 2015.
DeAngelo, Harry, and René M. Stulz. "Liquid-claim production, risk management, and bank
capital structure: Why high leverage is optimal for banks." Journal of Financial
Economics116, no. 2 (2015): 219-236.
Lam, James. Enterprise risk management: from incentives to controls. John Wiley & Sons,
2014.
McNeil, Alexander J., Rüdiger Frey, and Paul Embrechts. Quantitative Risk Management:
Concepts, Techniques and Tools-revised edition. Princeton university press, 2015.
Olson, David L., and Desheng Dash Wu. Enterprise risk management. Vol. 3. World
Scientific Publishing Company, 2015.
Wolke, Thomas. Risk Management. Walter de Gruyter GmbH & Co KG, 2017.