Due Date Essay Example

6Investment Management

INVESTMENT MANAGEMENT ASSIGNMENT

By (Students’ Name)

  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

Relevant industry sector

Average return

Standard deviation of the return

Fairfax Media limited ordinary

0.033383956

0.131536917

Myer holdings limited ordinary

Financial

0.003625911

0.101558895

Monadelphous group ordinary

Engineering

-0.016021289

0.073553054

David Jones limited ordinary

Distribution service

0.015695083

0.099435724

Common wealth Bank ordinary

-0.010417671

0.046713263

Cochlear limited ordinary

Health care (cochlear implants)

0.002639528

0.121230999

BHP Billiton limited ordinary

Resource services

0.00503127

0.057648073

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).

  1. 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.

  1. 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

Fairfax Media limited ordinary

0.033383956

0

0.183383956

Myer holdings limited ordinary

0.003625911

0

0.143625911

Monadelphous group ordinary

0.016021289

0

0.146021289

David Jones limited ordinary

0.015695083

0

0.125695083

Common wealth Bank ordinary

0.010417671

0

0.020417671

Cochlear limited ordinary

0.002639528

0

0.102639528

BHP Billiton limited ordinary

0.00503127

0

0.17503127

Ramsey health care ordinary

0.028201176

0

0.208201176

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.

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

Average return

Standard deviation of the return

Fairfax Media limited ordinary

0.033383956

0.131536917

Myer holdings limited ordinary

0.003625911

0.101558895

Monadelphous group ordinary

-0.016021289

0.073553054

David Jones limited ordinary

0.015695083

0.099435724

Common wealth Bank ordinary

-0.010417671

0.046713263

Cochlear limited ordinary

0.002639528

0.121230999

BHP Billiton limited ordinary

0.00503127

0.057648073

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