ASIC Financial Investment - Report Example

INVESTMENT MANAGEMENT ASSIGNMENT By (Students’ Name) Professor’s Name Course Name+ City Due Date 1 Introduction The report looks at ASIC financial investment; it focuses on the daily short sales, and the most sorted stocks. It `considers stock pricing and the adjustments made for dividends and splits. Finally, the report gives findings in terms of weights at the end of the analysis. 2) Stocks Analyzed Stock code Company name Relevant industry sector Average return Standard deviation of the return FXJ. AX Fairfax Media limited ordinary Media 0.033383956 0.131536917 MYR. AX Myer holdings limited ordinary Financial 0.003625911 0.101558895 MND. AX Monadelphous group ordinary Engineering -0.016021289 0.073553054 DJS. AX David Jones limited ordinary Distribution service 0.015695083 0.099435724 CBA. AX Common wealth Bank ordinary banking -0.010417671 0.046713263 COH. AX Cochlear limited ordinary Health care (cochlear implants) 0.002639528 0.121230999 BHP. AX BHP Billiton limited ordinary Resource services 0.00503127 0.057648073 RCH. AX Ramsey health care ordinary healthcare -0.028201176 0.045271831 Stocks that is likely to be inefficiently priced. 1) FXJ. AX 2) MYR. AX 3) MND. AX 4) DJS. AX The reasons for inefficient pricing are due to under pricing the assets and market crash and spikes at a magnitude different from the point of efficiency. Besides, from task 2 and task 3 we have been shown that the four most sought stocks are CBA.AX, COH.AX, BHP.AX, and RCH.AX (Hafer & Hein 2007). 1) Data And Risk Free Asset Treasury bills have been used as the risk free assets. The report has used both split and dividend multipliers. The adjusted close is used to provide the requested day’s closing price. Also, it avails the closing balances as requested for the week or even month. The closing results given are adjusted for the applicable dividend distribution and splits. The split multiplier is suitable as it is indicated by the resultant split ratio. For example, in the case of a 2 to 1 split, the data to be split will be multiplied by 0.5. This ensures accuracy of the split data. The dividend multiplies are calculated on the basis of dividends given as a percentage of the price. This is suitable as it avoids the possibility of any negative historical pricing. For example, in distributing $0.08 cash dividend and the closing price of a given date is 24.96, then the before dividend data is determined as; (1-0.08)/24.96 = 0.9968 (Hafer & Hein 2007). 2) A Single Factor Model A single index model can be defined as a statistical model that of an investment return. The single index model gives two uncertainty sources for an investment. The systematic and unique sources. The systematic is represented by the single index of an investment while the unique is represented by a specific random component of a security. Components of the model The basic idea The casual observation: investments that are driven by the same market forces tend to move together. The model of generating returns for an asset j can be given as: r j = α j + β j r I + e j where r I is the index’s random return e j = random return component that is firm specific, given that covariance (e j, r I )= 0 and E(e j) = 0 α j = expected return where the index is neutral and E ( r I) = 0 β j = sensitivity of r I from r j, β j = covariance (r j, r I) / variance (r I) Assume that covariance (e j, e i) = 0 and therefore, α j is the part of return that is independent of the return index and β j r I is the part of return due to index fluctuations (Sornette, 2003). A factor model that only considers the effects emanating from only one factor from a group of stocks is called a single factor model. It is a mathematical calculation that determines the extent to which a single macroeconomic factor impacts stocks within any given portfolio. The single factor model makes an attempt and accounts for such contingencies as inflation and interest rates. The single factor model will usually determine how the market return impacts the return on portfolio (Sornette, 2003). Definition of Terms Stocks; this is a security that represents owners claim in a corporation’s assets and earnings. Portfolio; this refers to a collection of assets that are financial in nature for example bonds and stocks. 3) Regression Results In this the regression equation to use is R I t =  i R m t +e I t This regression result will give us the security characteristic line (SCL), this defines an intercept this defines the slope and e i t are the deviations from the returns. Stock code Company name   i R m t e i t R I t Б2 FXJ. AX Fairfax Media limited ordinary 0.033383956 0.15 0 0.183383956 0.01 MYR. AX Myer holdings limited ordinary 0.003625911 0.14 0 0.143625911 0.01 MND. AX Monadelphous group ordinary 0.016021289 0.13 0 0.146021289 0.01 DJS. AX David Jones limited ordinary 0.015695083 0.11 0 0.125695083 0.01 CBA. AX Common wealth Bank ordinary 0.010417671 0.01 0 0.020417671 0.002 COH. AX Cochlear limited ordinary 0.002639528 0.1 0 0.102639528 0.02 BHP. AX BHP Billiton limited ordinary 0.00503127 0.17 0 0.17503127 0.003 RCH. AX Ramsey health care ordinary 0.028201176 0.18 0 0.208201176 0.002 The quality of the regression is guaranteed by the accuracy of the data given and the splits and dividend instruments used. The alpha and the beta are not the same because of the formula difference; the betas have been calculated as a percentage. Stock X1 Y1 FXJ. AX 0.15 3.3 MYR. AX 0.4 0.4 MND. AX 0.13 0.1 DJS. AX 0.11 1.5 CBA. AX 0.01 1 COH. AX 0.1 0.2 BHP. AX 0.17 0.5 RCH. AX 0.18 3 There are 8 stocks, hence the n=8, to determine the values of a and b, the following summations are necessary. SX = ∑xi = 1.25 SY = ∑ y i = 10 SXX = ∑ xi2 = 0.2829 SXY = ∑xi y i =1.488 SYY = ∑y12 =23.6 b= (n s x y –s x s y) / (n s x x –s x) =-113 / 1.01 =-111.9 a= (1/n) s y – b (1/n) s x = 1.25 + 17.5 = 18.73 6) Trade Idea Statistical Arbitrage This is a situation whereby profit arises from inefficiencies in pricing between securities in the market. Market investors can identify this arbitrage situation by the use of mathematical modeling methods. Statistical arbitrage has a risk; it heavily depends on the market price ability to get back to a predicted normal or historical cost (Fuller, 2006). Risks Associated with this Trade Statistical arbitrage in general sense can only be demonstrated correctly as the trading time amount approaches the liquidity and infinity, or allowable bet size approaches infinity. Heavy short term losses can be imposed by a lower probability series of events. This can take place over any given finite period of time. If the liquidity available to the affected trader is less than the short term losses, then default is likely to occur. For example, cases of management of long term capital management assets (Fuller, 2006). Statistical arbitrage suffers model weaknesses like stock or security specific risk. Due to return distribution from the underlying assets, the model may easily break down. Sometimes the model might not take into consideration some of the factors that it might not be aware of. These factors might be the drivers of the market price action. The investment done might also change in an unexpected manner due to newer entrants into the market (Fuller, 2006). Investment Weights for the Eight Stocks Stock code Company name Average return Standard deviation of the return FXJ. AX Fairfax Media limited ordinary 0.033383956 0.131536917 MYR. AX Myer holdings limited ordinary 0.003625911 0.101558895 MND. AX Monadelphous group ordinary -0.016021289 0.073553054 DJS. AX David Jones limited ordinary 0.015695083 0.099435724 CBA. AX Common wealth Bank ordinary -0.010417671 0.046713263 COH. AX Cochlear limited ordinary 0.002639528 0.121230999 BHP. AX BHP Billiton limited ordinary 0.00503127 0.057648073 RCH. AX Ramsey health care ordinary -0.028201176 0.045271831 References Cootner, P. H. (N.D.). Stock prices: random vs. systematic changes. The Random Character of Stock Market Prices / [Edited by] Paul H. Cootner Osborne, M. F. M. (N.D.). Brownian motion in the stock market. The Random Character of Stock Market Prices / [Edited by] Paul H. Cootner Hafer, R. W., & Hein, S. E. (2007), The stock market, Westport, Conn, Greenwood Press Fuller, D. J. (2006), The stock market, Minneapolis, MN, Lerner Publications Sornette, D. (2003). Why stock markets crash: critical events in complex financial systems. Princeton, N.J., Princeton University Press Read More