By Kelvin Lye(賴光隆）

» Introduction » The Malaysian Food & Beverage industry» Five featured companies» Application of Theory»Methodology» Research Results » Conclusion and Suggestion

Research Objective»To compute all the necessary variables for each individual stock and for the investment portfolio»To determine the optimal portfolio by obtaining the cut-off rate using single-index model and evaluate the value at risk of the optimal portfolio»To analyze and conclude the optimal portfolio involving stocks of beverage companies in Malaysia

About the country»Region: Southeast Asia»Population: 28 million»Ethnics: Malay and Bumiputra (70%), Chinese (23%), Indians (7%)»Currency: Ringgit Malaysia (RM)»Currency exchange: RM1 9.6NTD

Items Price in Taiwan Price in MalaysiaCoca-cola (0.33 liter bottle) 0.71 USD 0.60 USDMineral water (1.5 liter bottle) 1.02 USD 0.72 USDGasoline (1 liter) 1.07 USD 0.65 USDVolkswagen Golf 1.4 90 kW Trendline 34,476.68 USD 48,024.29 USD1 minute of Prepaid Mobile Tariff (no plans/discounts)

0.13 USD 0.12 USD

Composition of Food and Beverage Sector

Food

Beverage

Food and beverage in

malaysiaDrinking water

Alcoholic drinks

Dairy products

Soft drinks

Traditional drinks

Bakery

Processed foods

Dairy products

Snacks

Staple foods

Instant food

Specials features of the sector»Predominantly owned by Malaysian companies»Contributes 2-3% of Malaysia economy»Domestic retail market of F&B US$11 billion»24% spent on retail purchase of food in Malaysian households

Exports of Malaysian Processed Food and Beverage Products2006-2010

Source: UN Comtrade

Future of Malaysia’s Future of Malaysia’s Beverage IndustryBeverage Industry

» Manufacturer of dairy products in Malaysia since 1950s

» Manufacturing plant in Petaling Jaya» Operations: HACCP, ISO9001, ISO14001,

Malaysian Halal Certification» Partners with the Malaysian

Government on supporting local industries and communities

Finance Performance (2012)Revenue: RM 882.18 million

Operating income: RM 170.74 million

Net income: RM 123.38 millionTotal assets: RM 382.77 millionTotal equity: RM 216.13 million

» Oldest dairy product and beverage company in Malaysia

» Products include dairy products and soft drinks

» Manufacturing plan in Selangor» Operations: HACCP, ISO9001, ISO14001,

Malaysian Halal Certification» Awards: Reader’s Digest Trusted Brand

2006-2008, Superbrands Asia 2006

Finance Performance (2012)Revenue: RM 3239 millionOperating income: RM 887 millionNet income: RM 274 millionTotal assets: RM 2606 millionTotal equity: RM 1555 million

Finance Performance (2012)Revenue: RM 4556 million

Operating income: RM 1553 million

Net income: RM 505 millionTotal assets: RM 1905 millionTotal equity: RM 751 million

» An established dairy product, coffee and nutritional products manufacturer in Malaysia since 1912

» Products include dairy products, coffee, ice cream, cereals and confectionary

» Manufacturing plan in Kuala Lumpur» Operations: HACCP, ISO9001, ISO14001,

Malaysian Halal Certification» Awards: Most Admired Company in Malaysia

2008 and 2009

Finance Performance (2012)Revenue: RM 279.36 million

Operating income: RM 121.24 million

Net income: RM 34.38 millionTotal assets: RM 281.47 millionTotal equity: RM 205.98million

» A relatively new beverage company founded in 1999

» Products include herbal energy drinks, coffee and chocolate beverage

» Manufacturing plan in Johor Bahru» Operations: HACCP, ISO9001, ISO14001,

Malaysian Halal Certification» Focuses on R&D on local mainforest traditional

herbs-based (Tongkat Ali and Kacip Fatimah)

Finance Performance (2012)Revenue: RM 178.21 millionOperating income: RM 62.35

millionNet income: RM 10.59 million

Total assets: RM 272.08 millionTotal equity: RM 150.21 million

» Malaysia’s largest bottled water manufacturer

» Products include mineral water, RO drinking water, carbonated and flavoured water

» Manufacturing plan in Taiping, Perak» Operations: HACCP, ISO9001, ISO14001,

Malaysian Halal Certification» Notable award: Asia Pacific Bottled Water

Company of Year 2010

» Important consumer goods » Steady growth in domestic market» Huge room for improvement: international

market expansion, especially halal market (Bohari, 2013) and value enhancement (Ong, Yeoh & Teh, 2011)

» Active promotion of Malaysian food and beverage by the Malaysian Government

» Steadily strong performance of companies

» Originally known as Kuala Lumpur Stock Exchange (KLSE)

» Renamed in 2004 as Bursa Malaysia» Consists of: Main Board, Second

Board and MESDAQ» Total market capitalization: RM700

billion.

Instruments: 1.Securities market (Main & Ace)2.Derivatives market (Futures)3.Islmaic offerings (Sukuk, Shariah compliant securities)4.Others (Bond market, offshore market)

( 1) ( )

( )

( 1)

( )

Daily return, 100% ,

where stock price on current day

stock price on previous day

i t i ti

i t

i t

i t

P PR

P

P

P

1Expected return, ,

where number of period; th security; th period (day)

N

ijj

i

R

RN

N j j i i

Daily Returns and Expected Returns of Individual Stocks

Standard deviation and Covariance of Individual Stocks

1

( )( )

Covariance, ,

where number of period; th security; th period (day)

daily return; = expected return

N

Aj A Bj Bj

AB

R R R R

NN i i j j

R R

Coefficient of correlation,

where covariance between securities and ;

, standard deviation of securities and respectively

ABAB

A B

AB

A B

A B

A B

Single-Index Model: Cut-off Rate Calculation

Adapted from •Elton, Gruber and Padberg (1976)•Campbell, Huisman and Koedijk (2001)

CASES:»Short sales disallowed»Standard definition of short sales»Lintner’s definition of short sales

Ci versus Cut-off rate

Optimal Portfolio: Short Sales and No Short Sales Criteria

CASES:»Short sales disallowed»Standard definition of short sales»Lintner’s definition of short sales

Adapted from •Elton, Gruber and Padberg (1976)•Campbell, Huisman and Koedijk (2001)

Value-at-Risk: Description and Computations

Parametric Value-at-

Risk

Historical Value-at-

Risk

Monte-Carlo

Value-at-Risk

Using overall expected return

and standard deviation

Using daily/weekly/monthly expected return

and standard deviation

Using projected expected return

and standard deviation

Value-at-risk

Adapted from •Kaplanski and Kroll (2002)•Campbell, Huisman and Koedijk (2001)

Value-at-Risk: Description and Computations

Parametric Value-at-

Risk

Analytical

•Individual•Portfolio

Value of Z-score based on the confidence interval based on

normal distribution

Variance-covariance •Portfolio

Optimal portfolio weightsAdapted from •Kaplanski and Kroll (2002)•Campbell, Huisman and Koedijk (2001)

Value-at-Risk: Description and Computations

Historical Value-at-

Risk

1. Calculate daily stock returns and standard deviations for individual stocks

2. Calculate the daily portfolio returns and standard deviations based on the optimal portfolio weights

3. Compute a histogram4. Determine the percentile (or percentage) of the

lowest returns at confidence interval (99%/95%/90%), corresponding to significance level (1%/5%/10%)

Lowest return at significance level

Adapted from •Elton, Gruber and Padberg (1976)•Campbell, Huisman and Koedijk (2001) Use “normsinv”

function in Excel

Comparison: Historical, Parametric and Monte Carlo VaR

Aspects Historical Parametric Monte Carlo

Data type Historical data No data Future data

Strength Easy to implement

Easy to implement

Use projection instead of past data

Weakness• No

distribution required

• Not great for non-linear payoffs

• Harder to implement

• Time-consuming

Historical Individual Daily Stock Prices

Research Process Flow

Historical Daily Indices of KLCI

Data Collection

•Datastream•Bank Negara

Calculation (Microsoft

Excel)

Risk-free return in Malaysia

Expected Returns and Standard Deviations for Stocks and Market

Cut-off Rate and Optimal Portfolio

Value-at-Risk for Stocks and Portfolio

Analysis of results Value-at-Risk

Optimal Portfolio

» Samples: Dutch Lady, Fraser and Neave (F&N), Nestle Malaysia, Power Root and Spritzer

» Sample period: 20 May 2008 – 20 May 2013» Sample Size: 1304 observations per company» Market return rate: KLSE index» Risk-free rate in Malaysia: 3-month interbank offer

rate (3.21% per annum)» Assumption: Returns are equally weighted

Research Sample Setting and Assumptions

Company Expected Return (%)

Standard Deviation (%)

Dutch Lady (D) 0.1100 1.2712

F&N (F) 0.0611 1.1199

Nestle Malaysia (N) 0.0633 0.8804

Power Root (P) 0.1128 2.9073

Spritzer (S) 0.1107 2.5496

KLSE 0.0274 0.7596

Expected Return and Standard Deviation of Individual Stocks and KLSE

Variance-Covariance Matrix

D F N P S

D 1.6159 0.1555 0.1084 0.2949 0.0699

F 0.1555 1.2542 0.0771 0.1692 0.0055

N 0.1084 0.0771 0.7751 0.1636 0.0838

P 0.2949 0.1692 0.1636 8.4522 0.6126

S 0.0699 0.0055 0.0838 0.6126 6.5003

Coefficient of Correlation Matrix

D F N P S

D 1 0.1092 0.0968 0.0798 0.0216

F 0.1092 1 0.0782 0.0520 0.0019

N 0.0968 0.0782 1 0.0639 0.0373

P 0.0798 0.0520 0.0639 1 0.0826

S 0.0216 0.0019 0.0373 0.0826 1

Cut-off Rate: Ranking and CalculationRanking(Excess

Return over Beta)

Collection of required

parameters

Calculation of Cut-off

rate

Company Expected Return (%)

Standard Deviation (%)

Beta (Datastream)

Other parameters

Dutch Lady (D) 0.1100 1.2712 1.1060

Risk-free rate, RF

(3.21% annual,0.008% daily)

F&N (F) 0.0611 1.1199 0.5610Nestle Malaysia (N) 0.0633 0.8804 0.4830Power Root (P) 0.1128 2.9073 1.7290Spritzer (S) 0.1107 2.5496 0.8040KLSE 0.0274 0.7596 1.0000

Cut-off Rate: Ranking and CalculationCalculation of Cut-off

rate

Collection of Required

Parameters

Ranking (Excess

Return over Beta)

Cut-off Rate: Ranking and CalculationCollection of

Required Parameters

Calculation of Cut-off rate

Ranking(Excess

Return over Beta)

Optimal Portfolio: Computation

Stock Z values X values Weights (%)S 0.0677 0.3152 31.52N 0.0340 0.1582 15.82F 0.0285 0.1325 13.25D 0.0542 0.2523 25.23P 0.0305 0.1418 14.18

Total 0.2149 1.0000 100.00

Portfolio Expected Return

Portfolio Standard Deviation

0.0967% 1.0448%

NOTE:»All Ci are lower than excess return over Beta»Cut-off rate, C* = 0.0425»No short sales can be done

No Short Sales ONLY

Excel Printscreen: Expected Return, Standard Deviation, Variance-Covariance, Cut-off Rate and Optimal Portfolio

Value-at-Risk Computation: Excel Printscreen

Value-at-Risk Computation: Comparison

MethodConfidence interval

99.00% 95.00% 90.00%

Parametric VaR 2.3338 1.6218 1.2422

Variance-Covariance VaR 2.4306 1.7185 1.3390

Historical VaR 2.6144 1.3912 1.0102

Objectives met?•All variables computed ()•Cut-off rate determined ()•Optimal portfolio computed ()•Value-at-Risks evaluated ()

Analysis:•No short sales can be done•Low portfolio return•Low risk (standard deviation and value-at-risk)

Objectives met?•All variables computed ()•Cut-off rate determined ()•Optimal portfolio computed ()•Value-at-Risks evaluated ()

Analysis:•No short sales can be done•Low portfolio return•Low risk (standard deviation and value-at-risk)

» Benninga, S., & Wiener, Z. (1998). Value-at-risk (VaR). Mathematics in Education and Research, 7(4), 1-8.

» Bohari, A. M., Cheng, W. H., & Fuad, N. (2013). The competitiveness of halal food industry in Malaysia: A SWOT - ICT analysis. Malaysia Journal of Society and Space, 9(1), 1-9.

» Campbell, R., Huisman, R., & Koedijk, K. (2001). Optimal portfolio selection in a value-at-risk framework. Journal of Banking and Finance, 25(9), 1789-1804.

» Elton, E. J., Gruber, M. J., & Padberg, M. W. (1976). Simple criteria for optimal portfolio selection. Journal of Finance, 31(5), 1341-1357. Jusoff, K. (2009). An ARDL approach in food and beverages industry growth process in Malaysia. International Business Research, 2(3), 98-107.

» Kaplanski, G., & Kroll, Y. (2002). VAR risk measures vs traditional risk measures: An analysis and survey. Journal of Risk, 4(3), 1-27.

» Ong, T. S., Yeoh, L. Y., & Teh, B. H. (2011). Intellectual capital efficiency in Malaysian food and beverage industry. International Journal of Business and Behavioral Sciences, 1(1), 16-31.