sapm-background materials-jims-2010

8/7/2019 SAPM-Background Materials-JIMS-2010

1/48

SECURITY ANALYSIS ANDPORTFOLIO MANAGEMENT

FACULTY: DR. S. K. CHAUDHURI

1


2/48

SECURITY ANALYSIS AND PORTFOLIO MANAGEMENT

Instructor: Dr. S K Chaudhuri

Email: [email protected]

Course Objectives

The course is designed to provide a perspective on modern portfolio management of financialassets and derivatives. The students will learn basic tools and techniques of security analysisand portfolio management and their practical applications including applications based on Excelspread sheet and other available packages.

In particular, they will be exposed to technical analysis, stock and bond valuation (includingsimulation models), portfolio construction (based on no-linear programming techniques), andportfolio performance evaluation.

Pedagogy

The course will be delivered through lecture, exercises, and available empirical studies. Aboutone-third of the sessions will be devoted to analysis of real life data in the computer lab, whichwill facilitate learning by doing.

The students will be required to undertake individual assignment on stock analysis andvaluation. This will help develop their analytical skills for empirical research.

Course Contents

See next page

Evaluation

Components Weight (%)

Individual Assignment* 10

Quiz I 5

Quiz II 5

Practical Test I 10

Practical Test II 10

Term-End Examination Written exam: 25

Computer based exam: 35

* No assignment will be accepted for evaluation beyond the scheduled date.

2
mailto:[email protected]:[email protected]


3/48

Study Materials

The study materials will consist of select papers/exercises. In addition, the students may refer tothe following text books:

1. Fisher and Jordon, Security Analysis and Portfolio Management2. Zvi Bodie, Alex Kane and Alan J. Marcus, Investments

3. E. J. Elton and M. J. Grubber, Modern Portfolio Theory and Investment Analysis

4. Gordon J. Alexander and William F. Sharpe, Fundamentals of Investments

Course Contents

Sessions 1 - 8 Main themes of security analysis and portfolio management

Return-risk concepts and measurement*

Securities Market - organisation, operations and emerging trends(self study)

Stock market indices and derived series

Efficient market hypothesis - concepts, evidence and implication

Sessions 9 - 13 Technical analysis - basic tools and applications*

Sessions 14 - 17 Investment in equity shares basic analysis including industry &company analysis

Share valuation models (including a simulation model)*

Sessions 18 22 Debt instruments pricing, yield measurement and yield curves*

Price-yield relationship - duration and convexity*

Bond portfolio management*

Sessions 23 27 Modern portfolio theory - Markowitz Model/CAPM/APT

Construction of optimal portfolios using optimization techniques*

Estimation of share beta*

Sessions 28 - 30 Mutual Funds

Portfolio performance measurement*

* Requires working in comp lab.

3


4/48

Individual Assignment (Weight: 10%)

You are required to prepare an analytical report on a corporate stock, which must contain, interalia, the following components:

1. Brief industry analysis as a backdrop to appreciate the companys business performance

2. Brief background of the company

Products/business portfolio

Market structure and competitive profile of the company (key factors)

Future prospects

3. Financial performance analysis

Analysis of recent trends (3-year) in financial performance (develop an appropriateformat for the purpose)

Projected financials for next 3-year period

4. Valuation of the stock (use different approaches including simulation model)

5. Technical analysis

6. Investment arguments and recommendations

7. Design a front page to present the executive summary of your report

Mention clearly the sources of all data and information. Also note that cut-paste from availablereports will be penalized heavily. It might even lead to rejection of the report.

4


5/48

INVESTMENT VS SPECULATION

Features Investment Speculation

Return Seeks returns that commensurate with theinvestment risk including the risk of

inflation

Seeks abnormal returns without regard forinvestment risk

Risk Limits risk exposure Sets no limit to risk exposure

Time Spans over longer time horizon Operates over a shorter time interval

Process Follows rigours of investment process,acts on market opportunities, showspatience of a hunter, involves actualdelivery of securities

Acts on market sentiments and insideinformation, tries to manipulate prices,always on run for a killing, does notinvolve actual delivery of securities

THE PROCESS OF PORTFOLIO MANAGEMENT

Five logical steps to follow:

1. Setting investment policies in terms of (a) objectives (e.g., stability of income,growth in income, capital appreciation) and (b) constraints (e.g., restrictions oninvestment, diversification constraints, liquidity constraints, taxation issues)

2. Performing security analysis, both (a) fundamental analysis and (b) technicalanalysis

3. Portfolio allocations to assets (optimization models) and time-to-time rebalancing

4. Hedging portfolios

5. Evaluation of portfolio performance

TYPES OF INVESTMENT RISK

5

Total risk = systematic risk (non-diversifiable risk) +unsystematic risk (diversifiable risk)

Economy/marketrisk Financial risk

Interest rate risk

Inflation risk

Exchange risk

Liquidity risk

Investment risk

Systematic risk Unsystematic riskCountry/politicalrisk Industry/business

risk


6/48

CALCULATION OF MONTHLY RETURN FROM DAILY SENSEX DATA

HISTORICAL RETURNS ON SENSEX

6

Year

N

R

1979-8

Sensex Return Cumulative

Day pt rt = pt / pt-1 - 1 (1 + rt) Product

0 3244.80

1 3226.10 -0.58% 0.9942 0.9942

2 3190.35 -1.11% 0.9889 0.98323 3153.06 -1.17% 0.9883 0.9717

4 3125.88 -0.86% 0.9914 0.9633

5 3154.91 0.93% 1.0093 0.9723 Monthly Return based on Equation 1.3

6 3110.08 -1.42% 0.9858 0.9585 = .9397 - 1 = -0.0603 or -6.03 %

7 3108.24 -0.06% 0.9994 0.9579

8 3084.91 -0.75% 0.9925 0.9507 Monthly Return based on poin-to-point data

9 3121.18 1.18% 1.0118 0.9619 = (3048.72 / 3244.80) - 1 = -0.0604 or -6.04 %

10 3192.93 2.30% 1.0230 0.9840

11 3200.15 0.23% 1.0023 0.9863

12 3218.73 0.58% 1.0058 0.9920

13 3140.36 -2.43% 0.9757 0.9679

14 3140.42 0.00% 1.0000 0.9679

15 3143.58 0.10% 1.0010 0.9689

16 3116.79 -0.85% 0.9915 0.960717 3115.44 -0.04% 0.9996 0.9603

18 3048.72 -2.14% 0.9786 0.9397


7/48

CUMULATIVE WEALTH

DESCRIPTIVE STATISTICS OF RETURN DISTRIBUTIONS (1979-80 TO 2003-04)

Day-to-day movement of Sensex and Nifty

7

6.40

1

10

100

1979-80

1980-81

1981-82

1982-83

1983-84

1984-85

1985-86

1986-87

1987-88

1988-89

1989-90

1990-91

1991-92

1992-93

1993-94

1994-95

1995-96

1996-97

1997-98

1998-99

1999-00

2000-01

2001-02

2002-03

2003-04

ValueofRe.1Investme Stock (Sensex)

GOI-Security

91-Day T-Bills

Inflation

2.97

15.33

9.86

6.09

4.51

Gold

18.21

Series

Ar

BSE Sensex 1


8/48

STOCK PRICE INDEX

S&P CNX Nifty (NSE Futures Index)

Comprises of 50 stocks

Selection criteria:

Market capitalization: each share with market capitalization of Rs.5 bn(US$111m) or more

Liquidity: each share should have traded 85% of trading days at animpact cost of less than 1.5%

Impact cost: percentage mark up suffered while buying/selling a desiredquantity of the share compared to its ideal price, which is the average ofbest bid and best ask price

Example: Order book (of a broker)

Bid (Buy) Ask (Sell)

Calculate Impact cost to buy 1500 share

Ideal Price= (99+98)/2 = Rs.98.50

Qty. Price (Rs.) Qty. Price (Rs.)

100020001000

98.0097.0096.00

100015001000

99.00100.00101.00

Actual Buy Price = (1000 * 99 + 500*100) / 1500 = Rs.99.33Impact cost = {(99.33 98.50) / 98.50} * 100 = 0.84%Buy price for an investor is the selling price of a broker.

Shares bear a weight in the index in proportion of their market capitalization

Example:

Base Period Index = 1.000 x 1000 = 1000

Share Price (Rs.) Issue Size Capitalization Weight

A 20.00 4,000 80,000 0.098

B 60.00 5,000 3,00,000 0.366

C 145.00 2,000 2,90,000 0.354

D 15.00 10,000 1,50,000 0.0183

Total 8,20,000 1.000

Current Period Market Capitalization (only prices changed) = Rs.8,80,000

Current Index = (Current capitalization / Base capitalization) * 1000

= 1.073 x 1000

= 1073

(Index Maintenance replacement of shares) index should remain constant

8


9/48

It = (Mt / M0) x I0

M0 = Mt x (I0 / It)

M0 = Mt x (I0 / It)

M'0 (New Base Capitalization) = M0 + M0

= M0 + Mt x (I0 / It)

Example:

On 5 April

M0 = Rs. 1,95,000 crores and

Mt = Rs.1,97,500 crores

It = (Mt / M0) x I0 = (1,97,500/1,95,000) x1000 = 1012.8205

Scrip A with capitalization of Rs.1000 crores being replaced by Scrip B withcapitalization of Rs.900 crores

M'0 (New Base Capitalization) = M0 + Mt x (I0 / It)

= 1,95,000 + (900 1000) x (1000 / 1012.8205)

= Rs.1,94,901 crores

Mt = 1,97,500 100 = 1,97,400

It = (1,97,400 / 1,94,901) x 1000 = 1012.82

S&P CNX Nifty

Base period selected: close prices of Nifty shares on 03 Nov. 1995(Date marks the completion of one year of operations of NSE)

Hedging Effectiveness: Exhaustive calculations have been carried out todetermine the hedging effectiveness of the 50-security index against numerousrandomly chosen equally-weighted portfolios of different sizes varying from 1 to100 of smallcap, madcap and largecap companies as well as many industryindices/sub-indices provided by CMIE. It was observed that R2 for variousportfolios and indices using monthly returns data on the NSE-50 vis--vis otherindices was significantly higher indicating that the NSE-50 had higher hedgingeffectiveness

9


10/48

EFFICIENT MARKET HYPOTHESIS

EMH states that:

Security prices incorporate all past/new information in a rapid and unbiasedmanner

Investors will not be able to systematically outperform the market by followingconventional approaches (like using chart/trend analysis or searching formispriced securities

Refers to only informational efficiency

Three forms of EMH

Information associated with different forms of EMH

Weak form of

market efficiency

Semi-strong form of

market efficiency

Strong form of

market efficiency

Weak form:

successive price movements are independent

also known as Random Walk Hypothesis common testable form of random walk model

lnPt = lnPt-1 + et where E(et) = 0 & cov. (et, et s) = 0 for all s = 0

or, ln (Pt/Pt-1) = et

model considers only the linear independence - meaning thereby thatinvestors immediately react to new information, investors do not react in acumulative fashion to a series of events

stock process follows Brownian motion

Semi-strong form: security prices reflect fully all publicly available information

not possible to consistently outperform market by analysing published data Strong form: security prices not only reflect fully the published information but

also privileged information even insiders cannot consistently beat the market

Traditional Tests of RWH

Serial Correlation test

Runs test

Filter test

10

All public information

Past price &volume

information

All available informationincluding private information

All public information

Past price &

volume

informationPast price &

volumeinformation


11/48

MARKET ANOMALIES

P/E effectThe portfolios consisting of stocks with low price-earningsratios have a higher average return than portfolios with higher

price-earnings ratios.

Small-firm effect

The risk-adjusted returns of small size (or small capitalisation)firms tend to exceed the returns of large size (or, large cap)stocks; that is returns tend to diminish as the size of the firmrises.

Neglected-firm effect

The stocks of small firms that are neglected by institutionalinvestors (mutual funds, insurance companies, pension funds,etc.) tend to generate higher returns than stocks of those firmsin which the institutional investors put money.

January effectMean monthly return in January exceeds the mean returns ofthe other months.

Week-of-the-month effect

Positive market advances occur in the first part of the month

and almost never in the second half

Day-of-the-week effect Stocks do poorer on Monday than any other days.

Daily returns on Sensex for different week days (June 1998 January 1991)

Monday Tuesday Wednesday Thursday Friday

Mean -0.114 -0.170 -0.029 0.110 0.175

% Days Positive 45.6 45.2 48.5 52.6 50.6

Standard Dev. 0.176 0.145 0.113 0.126 0.131

Kurtosis 6.1 5.8 3.9 12.4 3.6

Skewness 0.941 -0.114 -0.511 1.892 0.227

H (KRUSKAL WALLIS) = 10.57

Correlations between returns of different days (June 1988 January 1991)

Monday Tuesday Wednesday Thursday Friday

Monday -

Tuesday .152 -

Wednesday .420 .073 -

Thursday .050 .103 .530 -

Friday .174 .501 .013 .239 -

11


12/48

TECHNICAL ANALYSIS

Dow Theory

Dow was a member of NYSE between 1885 and 1891 and during this tenure he formulatedwhat is now knows as Dow theory. This theory is less popular today, but its basic principles

underlie the contemporary approaches to technical analysis. Dow formulated six basic principlesas follows: (1) average prices discount everything; (2) market moves in trends primary,secondary and minor trends; (3) major trends have three phases accumulation, up-trendthrough corrections or pullbacks, and peak; (4) averages (railroad/transportation average andindustrial average) must confirm each other; (5) volume must confirm the trend; and (6) a trendremains in effect until signals confirm reversal. These principles are briefly discussed below.

The essence of Dow theory is that prices subsume every aspect of trading, and that three typesof trend are always at work in the market place. The primary trend, which may last a year ormore, is commonly known as bullish or bearish trend. This reflects the long run direction of themarket. However, the market can depart from its primary direction for limited periods of time,say from a few weeks to a few months. These departures are secondary reactions or trends.

The minor trends are short-term price fluctuations and are often of no real importance.Every trend builds on phases. During initial phase of accumulation, prices move sideways andbuying of securities remain at low ebb. As more investors begin to participate based on analysisand market news, the second phase begins with an uptrend. Even though the trend is up,security prices zigzag reflecting market corrections and pullbacks. After the price movementreaches its peak, another period of accumulation begins when more investors participate sincemarket news become more widely available. This third phase culminates in a downtrend andprice movements return to a period accumulation.

Dow theory also provides signals for changes in the market trends. If one of the averages transportation average and industrial average departs from the primary trend, the pricemovement is viewed as secondary. However, if departure in one is followed by a departure inthe other, then this is taken as a confirmation that the primary trend has changed. The trendreversals are further confirmed by increased volume of trading in the direction of the trend.

It may be noted here that Dow principles are never intended to indicate which specific stocks tobuy or sell, they are meant for identifying the market trends only. As a matter of fact, Dow theorycannot even predict exact beginnings and reversals of trends. Nor can charting the activitypredict the exact duration and extent of trends. Despite these limitations, however, the Dowtheory has been used to give 40 correct signals in the period 1897 1991. During this period,only five incorrect signals were given.

Elliotts wave theory

Ralph Nelson Elliott studied the events in numerous Dow major trends and devised his wave

theory to help explain why and where certain chart patterns develop and what they signalled.Beginning with Dows original three phases of a trend, he considered a repetitive rhythm of fivewaves advancing(bullish) and three waves declining(bearish) as shown in the figure.

Elliotts wave theory suggests that bullish trend forms through a five-wave movementcomprising of: (i) an advancing phase with peaks 1, 3 and 5, which are called impulsive waves;and (ii) troughs at 2 and 4, which are termed as corrective waves. Apparently, two correctiveinterruptions or waves are a prerequisite for overall directional movement to occur. Once the

12


13/48

five-wave movement is complete, the market moves into bearish trend through correctivemovements a, b and c.

Elliotts wave

The wave structure in practice is not as simple as depicted in Fig. There are many complexstructures of Elliott waves.

Support and resistance

Support is the price level where buying interest is strong enough to overcome selling pressure.The result is that the market does not fall below that level. Resistance is the opposite of supportand represents the price level that resists market price action for a period of time. It is the levelwhere selling interest is strong enough to overcome buying pressure so the market does notexceed that level.

Role reversal of support and resistance

13

Resistance

Support level broken-

line becomes resistance

in the next hase

Support

Resistance

Support

Satyam (weekly chart) Nov 2000 - Jan 2003

x/y = 0.6

y/x =1.6


14/48

The effect of support and resistance can be seen in all time frames, with the longer term(weekly) charts showing more solid support or resistance than the shorter term charts. As abasic premise, once a resistance level has developed, it will continue to provide resistance.Similarly, once support has been established, it will continue to provide support. However, oncethese levels are breached, their roles are reversed. That is, once resistance is breached, it willsubsequently provide support; once support is breached, it will provide resistance. Figure 5.9

explains support and resistance role reversals.

Trend Lines

Panels (a) and (b) in the Figure show downtrend and uptrend channels respectively. Anothertype of channel formation is sideways move. Panel (c) in the figure depicts such a channel. Thesideways trend is generally an indication of a temporary pause in the prevailing trend. Longer amarket moves sideways, which is not the case shown in panel (c) in the figure, the more energyit tends to store up. We, therefore, need to analyse sideways moves carefully.

Trend lines and some continuation patterns

Continuation patterns occur during periods of consolidation when prices are moving sidewaysfollowing an up or down trend. The patterns are not always easy to recognise and do not alwayshave the regular shapes as will be described now. Continuation patters have names based on

geometric shapes such as: (a) triangles; (b) rectangles; (c) flags and pennants; (d) wedges; and(e) rounding bottoms/tops. The names pretty well describe how the formations look like.

Market players use continuation patterns to determine a target price for their trading strategy.This target price is the level they expect the market to reach following breakout of theconsolidation and resumption of the continuation trend. We would not get into details of targetprice calculations, but certainly endeavour understanding different patterns.

14

(e)

(b)

(d)

(a)

(c)


15/48

Head and shoulders

The first or the left shoulder represents the penultimate advance in the bull market to reach ahead, and the second or the right shoulder is, in effect, the first bear market rally. Tradingvolume is normally heaviest during the formation of left shoulder and head. The traders oftenstretch to see a head and shoulders pattern but the real tip-off that such a pattern is developingcomes with the formation of the right shoulder, which is invariably accompanied by distinctlylower volume.

The line joining the bottoms of the two shoulders is called the neckline. The breaking of aneckline tends to provide a good indication the market will follow through in the direction of thebreak out. In the above, as prices move down from the right shoulder and penetrate below theneckline we get a strong indication that prices will now trend downwards. Thus, breaking ofneckline is generally a signal to sell. Some analysts measure the distance from the top of the

head to the neckline and project that the bottom will be the same distance below the neckline.We also find formation of head and shoulders in down trends. Such formation is called inversehead and shoulders.

Inverse head and shoulder

15

MTNL (daily chart) Feb - Oct 2003

Neckline

Head

Left shoulder

Right shoulder

Neckline

H

LSRS

Head

Left shoulderRight shoulder

Neckline

Hero Honda (weekly chart) Oct 2001 - Oct 2003


16/48

Simple & Exponential Moving Average

Buy and sell signals: We get buy signals when any of the following occurs:

The price line moves up through MA, which itself is rising.

The price line moves down towards MA, fails to go through, and then bounces off as ittouches MA. This could be a strong bullish indicator.

The price line temporarily falls through MA, which itself is rising, and then bounces backthrough it. This is often a strong buy signal.

The sell signals work in exactly the same way as buy signals but in reverse. Thus, we get sellsignals when any of the following occurs:

The price line moves down through MA, which itself is falling.

The price line moves up towards MA, fails to go through, and then bounces off as ittouches MA. This could be a strong bearish indicator.

The price line temporarily rises through MA, which itself is falling, and then bouncesback through it. This is often a strong sell signal.

However, close observations of any price and MA chart will usually reveal a number ofwhipsawor false signals.

16

1

2

A

Da

04/02/200

04/03/20004/04/200


17/48

Moving averages on a daily chart for SBI stock

In general, 10-day and 30-day moving averages are applied for short-term trend analysis; andfor intermediate period, it is quite common to use 100-day (20 week) or 200-day (40-week)moving average.

SBI stock entered into correction phase after attaining the peak (at Rs 674.50) it received bothsupport and resistance from 10-day and 30-day MAs. Another interesting point to note is that100-day MA has so far provided support to SBI stock whenever price reactions movedsouthward in the uptrend. Usually, when price line crossovers longer moving average, such as100-day MA or 200-day MA, it indicates a change in the major trend. Since southward stockprice movement of SBI has not yet crossed 100-day MA, we do not expect a major bearishtrend to set in; rather, the stock is likely to gain when the market rises.

Use of two moving averages When shorter and longer MAs crossover and both point upward, with shorter MA rising

above longer MA from below, then this a strong buy indicator, known as golden cross.

Similarly, when shorter and longer MAs crossover and both point downward, with shorterMA falling below longer MA from above, then this is a strong sell indicator, known asdead cross.

17

700

Daily cl


18/48

Computation of MACD and signal line

MACD shows the difference between two exponential moving averages, one with short and theother one with long time intervals. Though 12-day and 25-day EMAs are commonly used, anyother combination of time intervals may be used in the calculation of MACD.

Since MACD represents the absolute difference between two EMAs and, therefore, could beeither positive, negative or zero values. The zero line, also known as equilibrium line, shows thecomplete convergence of the two EMAs and, thus, lies at the centre of the chart. On the other

18

1

23

4

5

A

Day08/12/2003

08/13/2003

08/14/2003

08/18/2003

08/19/2003


19/48

hand, MACD line with positive or negative values reflects divergence between the two EMAsand, hence, it oscillates above and below the zero line.

A positive, rising momentum indicates that the price is not only rising but that it is alsoaccelerating. This is bullish and indicates that the prices are ensconced in a strong up trend. Afalling MACD in the positive area, however, indicates that the price trend is still rising but at a

decelerating rate. It is during this phase that momentum warns us that prices are ready to fall.A negative, falling momentum value indicates that the price trend is not only falling but that it isfalling at a faster rate. This reflects a strong bearish trend. A rising momentum in the negativearea indicates that the price trend is still falling but at a decelerating rate. It is during this phasethat momentum tells us that prices are ready to rise.

MACD is also used to determine buy/sell signals. For that purpose, a second line, designated asslow MACD orsignal line, is commonly displayed in the chart. This line is an exponential movingaverage of MACD values. The 9-day EMA is often used as signal line. We get buy signalwhenthe fast MACD line crosses from below toabove the signal line and when both have negativevalues. Similarly, we get sell signalwhen the fast MACD line crosses from above to belowthesignal line and when both have positive values.

MACD on a daily chart

It can be seen from Fig. 5.24 that HDFC stock is currently in the negative territory and has comeinto buy mode. The crossover of MACD and 9-day EMA (signal line) gives this buy signal.

19

H

Price l


20/48

Computation of ROC

When ROC is above the equilibrium line (i.e., 100) and rising, it indicates a bullish trend. In caseROC starts falling while still in the area above the 100 line (i.e., in the positive area), it indicatesthat market is advancing but more slowly than before. Similar kind of interpretations applies inreverse when ROC is below the equilibrium line and reflects bullish trend.

The current position of the stock in the figure shows a sign of possible revival because priceshas crossed 20-week moving average; so long this moving average has acted as a resistanceline. Besides, the 12-week ROC that has so long hovered around the equilibrium line has nowmoved into positive zone after showing positive divergence.

20

1

2 D

09/14/200109/21/2001

09/28/200110/05/2001

10/12/2001

Rs 27


21/48

Overbought/oversold lines in ROC chart

Relative Strength Index

J. Welles Wilder, Jr. introduced the most commonly known momentum indicator, namely relativestrength index (RSI). RSI formula is so designed that its absolute value ranges between 0 and

21

SBI

(May2003 - March 2004)

70

80

90

100

110

120

130

140

Overbought line

Oversold line

12-day ROC

1

2

34

5

6

78

A B

Pr

Date Sl. no. close

04/09/2003 0 204/10/2003 1 2

04/11/2003 2 2

04/15/2003 3 2

04/16/2003 4 2

04/17/2003 5 2

04/21/2003 6 234.70

04/22/2003 7 233.00

04/23/2003 8 233.10


22/48

100. As a thumb rule, when RSI goes above70/80 the underlying stock is consideredoverbought and one would expect a downturn soon. Similarly, when RSI goes below 30/20 theunderlying stock is labeled as oversold and one would expect prices to move up. There isnothing sacrosanct about this 70-30 or 80-20 rule; typical stock overbought or oversold linesmay appear at different values. In the BPCL chart shown in the figure, the 70-30 rule for definingoverbought and oversold zones seem to have worked.

RSI in daily chart

22

400


23/48

Computation of Williams %R

Williams %R in daily chart

23

1234

567

A B

Date Sl. no. Hi

26-Dec-03 1 37

29-Dec-03 2 38

30-Dec-03 3 39

31-Dec-03 4 39

01-Jan-04 5 39

500

525

Price


24/48

Putting the indicators together

It is now appropriate to undertake an integrated technical analysis putting all the indicatorstogether that we have learnt so far1. For that purpose, we consider the recent movement of BSESensex. All the technical charts, both daily and weekly, are summarised in the figures.

EMA and MACD for Sensex

Daily price chart clearly shows that Sensex has broken the support level (ranging from 5,568 to5,621) giving a strong bearish signal. The signal is strong because the price line has not only

penetrated the short-term moving average (10-day EMA) but has just crossed long-term movingaverages (10-week and 20-week EMAs). It appears that the bulls are on the back-foot andSensex would continue to stay under pressure. The support line that Sensex has just broken isgoing to become a tough resistance line.

On the momentum charts, the indicators are now showing weakness. MACD on daily chart ismoving southward in the negative territory reflecting sell mode. Though the long-term MACD isstill in the positive zone, it has started showing weakness with its southward movement andthereby confirms sell mode.

The 12-day ROC has given a bearish signal. It is currently placed in the negative territory andmoving southward after repeated failures to crossover the equilibrium line into positive territory.The long-term ROC is also showing similar kind of weakness. The 12-week ROC has alreadymoved into negative territory and the 5-week has followed the suit after a few failed attempts tocrossover to positive zone.

The 14-day RSI is placed near the oversold territory but is still far from giving a buy signal. The14-week RSI, however, continues to be in sell mode as it moves southward in the equilibriumterritory. Both the 14-day and 14-week Williams %R are currently reflecting oversold position buthave not yet given buy signals.

1 The analysis presented here is based on one of the regular technical items of Economic Times.

24

(1 Oc

6500

Price


25/48

On the whole, Sensex is likely to stay under pressure for some more time before it tries to makean attempt to move upward in a range.

ROC, RSI and Williams %R for Sensex

25

(1 Oc

110115

120


26/48

POPULAR STOCK SELECTION MODELS

Stock selection attributes

Sales-to-Price Ratio= sales per share / price per share

Dividend Yield = dividend per share / price per shareEarnings Yield = earnings per share / price per share

Book Value-to-Price Ratio= book value per share / price per share

Free Cash Flow Ratio = (cashflow / share- capex/share) / price per share

Cash Flow-to-Capex Ratio = (cash flow/capex) / price per share

Rank stocks on each attribute and then determine combined rank order of individual stocks

Stock may be combined into portfolios based on combined rank order (e.g. top-ranked stocksmay form the most "attractive" portfolios)

Does Model Indexation provide a useful alternative to select and manage portfolios?

(Ref: Allan Twark & James P D'Mello, "Model Indexation: A Portfolio Management Tool",Journal of Portfolio Management, 1991)

Dividend Discount Model (DDM)

Constant dividend growth model (Contd.)

If k >g and n (perpetuity), xn+1 0

P = D0x / (1 x)

P = D0 (1 + g) / (k g) = D1 / (k g)

Discount rate may be estimated using CAPM

k = rf + (rm rf)

Growth rate may be estimated using the following relationship:

g = (1 b) x ROE, where b = payout ratio, ROE = return on equity capital

A simulation model

One-period investment horizon

P = {D1 + EPS x (P/E)} / (1 + k)

EPS = {S0 (1 + g) x M} / N

Assign probability to five variable: D, g, M, N, P/E

(Use relevant probability distribution)

Carryout large no. of trials estimate mean, std. Deviation and confidence limit

26


27/48


28/48

BOND PRICING FUNCTIONS IN EXCEL

Day Count Basis: "30/360" = 0; "Actual/Actual" = 1; "Actual/360" = 2; "Actual/365" = 3; "European 30/360" = 4Bond pricing at spot rates

1

A

6.65%

CouponBasi

Bond yield function in Excel

28

2 BOND PRI


29/48

29


30/48

70

80

90

100

110

120

130

140

6% 8% 10% 12% 14%

Price(Rs.)

Required Yield

Price - Yield Relationship(As on 6 August, 2002)

Price-Yield Relationship - An Illustration

As on 6 August, 2002

Required Change in10.25% GOI

202111.19%

GOI 2005

YieldBasisPoints Price % Change Price % Change

7.0 -300 135.5660 30.41% 116.6245 7.55%

7.5 -250 129.3494 24.43% 115.2045 6.24%

8.0 -200 123.5529 18.86% 113.8073 4.95%

8.5 -150 118.1438 13.65% 112.4326 3.68%

9.0 -100 113.0918 8.79% 111.0798 2.44%

9.5 -50 108.3695 4.25% 109.7486 1.21%

9.9 -10 104.8120 0.83% 108.6989 0.24%

10.0 0.00 103.9516 0.00% 108.4385 0.00%10.1 10 103.1025 -0.82% 108.1790 -0.24%

10.5 50 99.8149 -3.98% 107.1493 -1.19%

11.0 100 95.9383 -7.71% 105.8804 -2.36%

11.5 150 92.3022 -11.21% 104.6316 -3.51%

12.0 200 88.8887 -14.49% 103.4025 -4.64%

12.5 250 85.6815 -17.58% 102.1926 -5.76%

13.0 300 82.6655 -20.48% 101.0016 -6.86%

30


31/48

PRICE VOLATILITY OF BONDS: DURATION AND CONVEXITY

Price volatility depends on duration and convexity

P = f (y) , y = YTM (discount rate)

dp = .....3

.(dy)3

dy

p3d

6

1)dy.(

dy

Pd

2

1dy.

dy

dp2

2

2

+++ (Taylor series)

dp/p =2

2

2

(dy).p

1.

dy

pd

2

1(dy).

p

1.

dy

dp

+ (considering only two terms)

Duration weighted average term-to-maturity of a bonds cashflows

= +

=n

ttytCp

1 )1(

= ++

n

tt

y

tCt

y1 )1(

.

)1(1

dy

dp

*D-D.y)(1

1-n

1t p

1x

t)y1(

tC.t

y)(11-

p1.

dydp =

+=

= ++

=

Where D = Macauly Duration , D* = Modified Duration

dp/p = - D*

. dy = approximate percentage change in bonds price

Convexity : measures rate of change of duration as yield changes

= +

=n

1t ty)(1

tC

p 1t)y1(

n

1t t(-t).C

dy

dp

++

==

2t)y1(

n

1tt

1)C(tt

dy

pd2

2

++

=

+

=

pConvexity 1.

dyPd2

2

=

2

2

2

)(dy.1.x0.5convexity)todp/p(due

=

PdyPd

31

Duration

Convexityy


32/48

Immunization of bond portfolio

Principle of immunization:

L,iD

iw

A,iD

iw =

Efficient frontier of bond portfolios

Application of Excel Solver Illustration

32


33/48

x

GOI

x t 3

OI

33


34/48

1A

Monthly Retu

Month

1

2

A

Variance - Cov

PORTFOLIO SELECTION AND DIVERSIFICATION

Return and risk measures for select stocks

Calculation of risk and return of four-asset portfolio

34


35/48

1

23

AMonthly - Ret

Month Ending29-Sep-00

- - Figure 1: Indifference Curves For Risk-Averse Investors

I1

I2

I3

)p(Risk

)pr(Return

Figure 1: Diversification of Portfolio Risk

Number of Assets (n)

DiversifiableRisk

Non-Diversifiable

Risk

)pRisk(Total

Variance-covariance matrix for four-asset portfolio

35


36/48

Figure 2: Indifference Curves For Risk-

Seeking and Risk-Neutral Investors

)p(Risk

)p

r(Return

I1

I2

I3

I1'

I2'

I3'

Risk-Neutral

Risk-Seeking

Figure 3: Efficient Frontier and Selection of

Optimal Risky Portfolio

H

I1I2I3I4

G

F

E

O

Global-Minimum

Variance Portfolio

Optimal Risky

Portfolio

)p(Risk

)pr(Return

36


37/48

12345

678

A

Variance -

Dr. Re

Efficient portfolio for a target return (no short sales)

37


38/48

1

23

4

A

Variance -

Efficient portfolio for a target return (with short sales)

38


39/48


40/48

1

23

4

A

Variance -

HDF

Efficient portfolio for a given risk level (no short sales)

40


41/48

2

34

5

AVariance -

HDF

L &

Efficient portfolio to maximize return-to-risk ratio (no short sales)

41


42/48


43/48

12

3

A

Variance - Covaria

HDFC

Composition of tangency portfolio

43


44/48

44


45/48

12

3

A BSl. MontNo. Endin

1 31-Jan-0

BETA ESTIMATION

45


46/48

12

345

678

91011

AMont

Endin

31-Jan-029-Feb-0

31-Mar-0

28-Apr-031-May-0

30-Jun-0

31-Jul-031-Aug-0

29- -0

Regression analysis to estimate beta

46


47/48

RISK-ADJUSTED PERFORMANCE MEASURES

Sharpes Measure:p

/)

f

r-

p

r( (reward to volatility trade-off)

Treynors Measure: p/)fr-pr( (systematic risk instead of total risk)

Jensens Measure: )]fr-mr(fr[- pprp +=

p > 0 abnormal gain

p < 0 abnormal loss

p = 0 average performance

Appraisal Ratio : )pe(/p (abnormal return per unit of non-systematic risk)

47

(portfolio return compared to

CAPM based return)


48/48

r

Table 1: Sharpe's

Sl.

1 J

sapm-background materials-jims-2010

Documents