Monetary Policy Process: Introduction And Construction Of A Portfolio

The Four Asset Classes

Discuss about the Monetary Policy Process.

The four asset classes in Table I are Australian shares, Australian Bonds, Cash rate and International stocks. The first asset class is the Australian shares. This consist the companies listed on ASX and the returns are the year on year return on these stocks. The next asset class is the Australian Bonds which are the bonds issued by the Australian Government. The next asset class is the Australian cash rate also called the official cash rate (OCR). This is the Australian base rate. Banks pay this interest rate when they take out a loan with a maturity of 1 day from another bank. (RBA, 2016) The next asset class is the international stocks which are scrips listed on exchanges all over the world other than Australia. Using the data from the table which is the 25-year year on year return on these asset classes Arithmetic mean, Geometric Mean and Standard deviation has been calculated. A spreadsheet has been used to calculate the various measures. The table below summarises the results.

Asset class	Australian Shares	Australian Bonds Save Time On Research and Writing Hire a Pro to Write You a 100% Plagiarism-Free Paper. Get My Paper	Cash Rate	International Stocks
Arithmetic Mean	15.98571429	11.51429	9.257143	14.88571
Geometric Mean	14.38	10.14	8.32	13.14
Standard Deviation	21.4592035	6.855883	4.332224	22.08374

Arithmetic mean of returns is simply the average of returns over a given period of time. While it is a simple and handy tool for calculating average returns the problem arises when there are negative returns in a given year. In that case arithmetic mean doesn’t necessarily give the best estimate of a risk-return on an asset. Geometric mean on the other hand is a better estimate of a risk return on an asset. Arithmetic mean would tend to overstate the growth and not give a fair estimate of risk return, it does provide an average performance measure over multiple holding periods. Well-known in statistics, AM is more sensitive to outliers than is GM and as such GM may be preferred in such cases. From the perspective of risk averseness, AM might not be preferred. (Yang, Hung, & Zhao, 2013)If we consider an asset with returns of 10%,20% and 6% over three years, the AM would be 12% whereas the GM would be 10.62%. Hence we observe that AM across all asset classes is more than the geometric mean. Standard deviation is the square root of the variance which in turn is the difference between the mean and the actual return. Hence standard deviation is a good tool to measure the volatility of an asset. (New York University, 2013) Generally, a stable asset would have less standard deviation compared to a risky and a volatile asset.

Construction of A Portfolio

AM for Australian shares is roughly 16% while the GM is 14.4% and the standard deviation is 21.45 from the Arithmetic Mean. This would indicate a highly volatile asset.

AM for Australian Bonds is 11.5 and the GM is 10.14 and the standard deviation is 6.85 from the mean. This would indicate a relatively stable asset.

AM for cash rate is 9.25 and the GM is 8.32 while the deviation is 4.33 indicating that across all assets this is the most stable.

AM for international stocks is 15 whereas GM is roughly 13 whereas the SD is 22 indicating that this is the most volatile asset.

Fiscal Vs Monetary Policy

Fiscal policy refers to the government policies regarding expenditures and tac levels through which it monitors and controls a nation’s economy. Summing it up it can be described as the framework for tax rates and government expenditures. Through the means of these the government can change(increase or decrease) aggregate demand and level of economic activity. It can also bring about changes in savings and investment patterns.

When the economic growth is slow, government can use the fiscal policy to decrease the tax rate thereby increasing aggregate demand and conversely use it to the opposite effect as well to slow down the pace of strong economic growth and stabilise prices. (Caballero, 2013)

On the other hand, Monetary policy is the process through which the monetary authority of a country, generally a central bank controls the supply of money in the economy by its control over interest rates in order to maintain price stability and achieve high economic growth. By controlling the supply of money to the economy the central banks can either induce increased demand or slow up an economy growing at a pace faster than anticipated in order to stop inflationary trends.

The three factors that would determine how sensitive a firm’s earnings are to the business cycle are:

• Nature of product: The sale of non necessary goods such as show pieces, collectibles will decline whereas that of necessary items such as groceries etc would be stable.
• Operating leverage: A company having a low ratio of fixed costs to variables costs will be more flexible in adjusting to price cuts as compared to a company with high fixed costs.
• Debt-equity ratio: A firm having more debt in its capital structure is said to be leveraged. Debt although decreases the WACC(Weighted Average Cost of Capital) and increases profitability when the firm is in high growth phase, but it also increases the burden of fixed expenses. Hence having the leverage of debt in a capital structure is a two edged sword as it makes the firm less sensitive to recessionary trends.

The value of a call option in the Black-Scholes model can be written as a function of the five variables:

S = Current stock price; in this case 39

K = Strike price of the option; in this case 35

t = Life to expiration of the option; in this case given as 6 months or ½ year

r = Riskless interest rate corresponding to the life of the option which is given as 5.3% in the given scenario

σ ^2= Variance in the ln(value) of the underlying asset; in this case given as square of 0.3

Fiscal Vs Monetary Policy

Value of call = S N (d1) – K e-rt N(d2) where d1 = ln(S/K) + (r + σ^2/2 ) t/ σ*t^1/2

Note that e-rt is the present value factor and reflects the fact that the exercise price on the call option does not have to be paid until expiration.

N(d1) and N(d2) are probabilities, estimated by using a cumulative standardized normal distribution and the values of d1 and d2 obtained for an option. (Damodran, 2005)

Using the values on a spreadsheet d1 is obtained as 1.86 and d2 is obtained as 1.66. Using the normal distribution table from the prescribed textbook then N(d1) and N(d2) is obtained as 0.9686 and 0.9515 respectively. Using the formula then value of the call is obtained as $8.83.

Similarly, value of put option is given by P=Xe^-rT[1-N(d2)]-S[1-n(d1))] (Damodran, 2005)

Putting the values in the formula the put option valuation is arrived at $1.01.

The daily mark-to-market settlements for each contract held by the long position has been calculated and tabulated as follows. The values in the second column obtained by subtracting that day’s price with the starting price and the total proceeds calculated by multiplying the total quantity with the second column which in this case is 100 ounces.

Day		profit/loss per ounce	Total proceeds
0	1197.9
1	1198.7	0.8	80
2	1194.7	-3.2	-320
3	1247.9	50	5000
4	1239.1	41.2	4120
5	1239.1	41.2	4120
6	1207.9	10	1000
7	1211.1	13.2	1320
8	1226.1	28.2	2820
9	1230.4	32.5	3250
10	1209.5	11.6	1160

Basis is the difference between the spot price and the future price. For example, if the spot price for a ounce of gold is $195 and the future price for delivery after 10 days is $198. In that case the basis is 3 dollars. Suppose the next day the spot price decreases to 193 dollars and the future price for delivery becomes 195. In that case the basis reduces to 3 dollars from 2 dollars.

In any hedging strategy there is a risk that the two investments used to offset each other won’t move in the same direction. This exposes the investor to a position wherein he/she can make excess gains or losses arising from the fluctuations. This risk is called the basis risk. (Ankirchner, Kratz, & Kruse, 2013) For example an investor hedges a two-year bond with purchase of govt bills. The risk that the two won’t move in the same direction is always there and forms the foundation for the basis risk.

Futures and options are financial contracts and both are examples of derivatives as their value is derived from that of an underlying asset. Future is an example of a financial contract Futures are much similar to forwards but are a more evolved product in the sense that they are flexible and give the option of removing the “obligation” before the expiry of the contract. Future contracts are widely used by the banks to hedge currency risks. (Meera, 2002) Options are similar financial contracts but the main point wherein they differ from futures is that entering into an option contract gives the buyer of the option right but not the obligation to buy or sell an asset. A call option is for buy, whereas a put option is for sell.

Valuation of Options

Sharpe ratio was a tool developed by William Sharpe and since its inception has become the most widely used measure for evaluating risk adjusted return. It is given by (Return on the Asset-Risk free rate)/Standard deviation. (Pav, 2016)

For the given example, Sharpe ratio of the portfolio is calculated as (0.12-0.055)/0.33 which is obtained as 0.19 or in other words for every point of return the investor is carrying 0.19 units of risk. Similarly, the Sharpe ratio for the market using the same method is obtained as 0.1. Hence what Sharpe ratio deduces is that the portfolio is giving more return per unit of risk and hence outperforms the market.

Treynor ratio is a tool quite similar to Sharpe ratio in a lot of aspects and again is a widely used measure to evaluate how much return an investor gets per unit of risk. It is given by the formula (Risk premium)/beta. For the given example the risk premium for the portfolio is 6.5% whereas that for the market is 2.5% since the risk free rate is given as 8% and hence the premium is obtained by subtracting this from the average return ion each respective asset. Hence Trey nor ratio for the portfolio is obtained as 0.056 whereas that for the market is obtained as 0.025. Simply put this implies that for every unit of risk the portfolio gives a return of 5,6% whereas the market gives a return of 2.5%. Hence quite alike to the Sharpe ratio Treynor ratio too indicates at a similar result. (Lan, 2012)

The Jensen’s is a risk adjusted performance measure and evaluates the return of a portfolio over and above that as predicted by the CAPM model. It is given by Expected portfolio return-((risk free rate beta(market return-risk free rate)) (Gerber & Hens, 2009)

Hence for the given example the Jensen’s alpha for the portfolio is obtained as 0.03625. The higher the alpha the better performing it is. That for the market is obviously 0.

The information ratio is a variation of the Sharpe ratio and is again used to evaluate from the investors point of view as to how much excess return is generated from the amount of excess risk taken relative to the benchmark. The information ratio measures a portfolio’s excess return relative to its benchmark tracking error. It answers the question of how much reward a manager generated in relation to the risks he or she took deviating from the benchmark. The information ratio is used for measuring active managers against a passive benchmark. (KIDD, 2011)

The information ratio is calculated by dividing the portfolio’s mean excess return relative to its benchmark by the variability of that excess return. For the given portfolio the information ratio is obtained as 0.5. This can be interpreted as an above average result. (Clement, 2009)

The M2 measure also known as the Modigliani Miller risk adjusted performance(RAP) measure is a performance measure for portfolios. It is given by(Rp-Rf)/Beta of the portfolio*benchmark beta+risk free rate. (Scholz & Wilkens, 2005) Using the values from the example M2 measure is obtained as 11.58% or 0.1158.

References

Ankirchner, S., Kratz, P., & Kruse, T. (2013). Hedging forward positions: basis risk versus liqquidity costs.

Bodie, Kane, & Marcus. (2014). Investments. McGraw Hill.

Caballero, G. (2013). Effects of Fiscal and Monetary Policy in the Great Recession.

Clement, C. (2009). Interpreting the Information Ratio.

Damodran, A. (2005). Option Pricing Theory And Models. In A. Damodran, Corporate Finance. New York: Stern.

Gerber, A., & Hens, T. (2009). Jensen’s Alpha in the CAPM with Heterogeneous Models Financial Valuation and Risk Management. National Centre of Competence in Research.

KIDD, D. (2011).Investment Performance Measurement.

Lan, Z. J. (2012). Measuring Risk adjusted return. AAII.

Meera, A. K. (2002). Hedging Foreign Exchange Risk with Forwards, Futures,Options and the Gold Dinar: A Comparison Note.

New York University. (2013). Standard Deviations. In Stern. New York: New York University.

Pav, S. E. (2016). Notes on the Sharpe ratio.

RBA. (2016). Cash rate. Retrieved from RBA: https://www.rba.gov.au/statistics/cash-rate/

Scholz, H., & Wilkens, M. (2005). A Jigsaw Puzzle of Basic Risk-adjusted Performance Measures. The Journal of Performance Measurement.

Yang, C. W., Hung, K., & Zhao, Y. (2013). A Comparison of Risk Return Relationship in the Portfolio Selection Models. ISI World Statistics Congress, 3495-4500.