Wealth Management Portfolio - Report Example

2.1.1 Alpha for the long Term Investment

2.1.2. Portfolio Characteristics

7 – Conclusion and Recommendations

1 – Introduction

1.1. Overview

The asset management for high net worth individuals is undergoing a shift period. Some Private family funds are separated based on the knowledge of the customers and their asset management sections. There are so many activities, so the focus in this project is portfolio and asset management. At the same time, the mutual fund indicates massive transformation in the asset management industry (Koijen, Brandt & Binsbergen, 2008). New funds have been introduced and they demand difficult choices between the investors because the asset management sector shifted from the focal point of the wise investment groups from long term portfolio management to ‘star’ funds or speculations on short term investments.

• • Background

This portfolio in this study is for a high net worth individual who intends to choose between wealth based asset investment and the non wealth based assets. The results of the performance of the two portfolios will guide the choice of the investor.

1.3. Problem definition

As it is clearly evident in the previous section, there is a likelihood that a significant driver of the increase in the level of assets being managed is the outstanding performance that they produced as opposed to the large asset portfolios. Tis raises two fundamental questions as shown below:

• Are the assets asset management performing better than the Non-asset funds asset management?
• What drives the out-performance in the asset asset management?

1.4. Relevance

This study is essential as it gives rare attention to the study of out-performance in the general asset funds. The capacity of the mutual fund sector is also demonstrating the relevance of this assessment. Since the asset management manage by manage very large amount of wealth and portfolio, they require special skills to benefit special investors such as the retirees. It is therefore essential to allocate money according to the information about the customers (KYC - know your customers, the qualification of customer, the knowledge about the customer’s profile of risk against returns. The investment mandate is to provide the classes of wealth and portfolios, the equities, bonds, the commodities, and foreign exchange deals, real estate, ETF, HF Funds of Funds strategies / styles, long-short, trading and the emerging market.

1.5. Results

There are three types of asset management investments in this study, long term, medium term and short term. The expectation is that the medium term will show better performance of the asset investment funds, than the Non-asset funds investment funds. The short term investments present more random results. When shorter investments are estimated depending on the definite period under the research. There is no steady persistence in the asset fund management studied over the periods being evaluated. Many driving factors of the performance have no statistical evidence that there can be an out-performance. Still, it is apparent that the turnover ratio is an exceptional factor in generating greater values of alpha. The asset funds are found to be charging higher costs compared to the Non-asset funds fund investments.

2 - Implementation / Strategy

This study measures the variations in performance of the asset investment and the Non-asset funds funds using a model of three parameters. The model is sufficient not only for assessing the wealth returns from the funds, but also in the consideration of whether the asset fund performance was adequate and justified the risk that the wealth manager takes. The model show the that the mutual funds are outperformed by most of the short term funds. The model appropriately captures the time value of money as a representative of the risk free rate (Rf(t), which compensates the returns on the wealth investments. The model uses the CAPM method, part of which represents the risk reward as desired by the investors for having decided to invest in the wealth (Goyal & Wahal, 2008). The added risk is computed by the risk value (βmi), which does comparison of the return on the wealth and portfolio against the market-based premium (Rm(t) – Rf(t)) within a given period. The real CAPM formula is stated as shown below:

Ri(t) = βmi(Rm(t) – Rf(t)) + Rf(t) ------------------EQ 1

The model in EQ 1 above is extended after an observation that the empirical average returns on the wealth in short term asset funds had high market equity than the forecast equities by the CAPM model. The observations leading to the equation suggested that the capacity of the ratios exposed the asset funds to systematic risks, which the CAPM beta did not show. It means the value stocks performed better than the growth stocks and the small wealth stocks did better than the large wealth stocks on a standard occasions.

2.1. Investment Mandate

This study aims at building a portfolio, suitable for a wealth management client. The focus of this study is the management of wealth portfolio. It therefore selects 12 asset asset management and 12 Non-asset funds asset management. This selection is principally conducted from the investigation on the information about assets on the on line media. The asset and non asset funds management were chosen due to the availability of information about the assets. In that case, it is possible to re-evaluate the structure of wealth ownership for the the high net worth individuals, family offices and standard private client, with a portfolio of between £1m and £20m.

Since all the asset and non – asset funds were traded on the exchange, it is possible to generate the share prices using Blomberg as shown in table 1 below.

Table 1: Descriptive statistics

Group

Number of funds

Mean Return / week

St. Dev

Max

Min

Asset Funds

140

0.000937

0.025971

0.082688

-0.147607

Non-asset funds

2300

0.000338

0.021047

0.077492

-0.157379

All

2440

0.001275

0.047018

0.078241

-0.204986

As it is evident from table 1 above, the return per week for the asset fund is 0.000937%, while the return per weak for the Non-asset funds 0.000338%. The descriptive statistics are assessed over the overall sample, in the range between 2000 and 2010. The table shows the return per week for the asset funds being of better performance than the Non-asset funds. This is in agreement without previous prediction. Nevertheless, the asset returns are exposed to greater risks owing to the greater standard deviation in stead of the asset funds. The drawback risk in the asset funds is also larger due to the minimum in the asset funds being -0.147607%. at the same time, the advantage and the benefit of the asset funds is greater owing to the maximum of 0.082688% against the the maximum for the non asset funds of 0.77492%. table 2 below shows the other relevant information not captured in the previous analysis.

Table 2: Other relevant statistics

Fund size

Fund-age

Manager tenure

Manager’s Fee

Exposure ratio

Turnover ratio

Asset Funds

Mean

£ 602,000,000

7.8

4.1

1.44

2.08

167.33

StdDev.

£ 2,060,000,000

5.7

3.4

0.33

1.13

188.04

Max

£ 20,200,000,000

25.2

21.6

2.02

6.37

952.73

Min

£ 483,224

1.2

0.4

0.36

0.00

0.00

Non-

Mean

£ 277,000,000

9.5

4.7

1.08

1.37

126.10

asset Funds

StdDev.

£ 617,000,000

7.6

4.5

0.55

0.64

155.91

Max

£ 12,000,000,000

80.0

39.6

4.55

6.67

1596.86

Min

£ 68

1.4

0.0

0.00

0.00

0.00

All

Mean

£ 290,000,000

9.5

4.6

1.17

1.46

129.13

StdDev

£ 830,000,000

7.4

4.6

0.57

0.75

162.43

Max

£ 24,200,000,000

80.0

39.8

4.30

6.47

1595.83

Min

£ 68

1.0

0.0

0.00

0.00

0.00

Table 2 above presents an impression of the relevant statistics. From a quick view of the table, there is a significant result, which is the mean size of the wealth (funds) for the asset funds of £ 602,000,000. From our previous projection, the assets provide less funds than the Non-asset funds on normal occasions. In this section, we have produced the analysis of the fund size for the asset funds in greater details.

2.1.1 Alpha for the long Term Investment

Table 3 below provides the outcome of the long term wealth investment for a ten year period. We consider this period as a time series analysis for the long term portfolio management.

Table 3: Alpha for Long term Investment

Table 3: Comparing the alpha for the ten years’ period

Testing for Equity in Means within the Series

Sample: 12344

Included observations: 2344

Method

df

Value

Probability

T - test

1638

-27.16258

0.0000

Category Stat

Variables

Count

Mean

Std. Dev.

Std. Err. of Mean

ALPHA-10YRS-ASSET

140

-0.032307

0.021000

0.0017640

ALPHA - 10YRS - NONASSET

1400

-0.048243

0.002695

0.0000697

All

1540

-0.080550

0.023095

0.0018337

From a quick view of table 3 above, it is clearly evident that the asset funds had better performance during the ten years compared to the non asset funds for the same period. The mean alpha during the period is negative for both the asset funds and the non asset funds. However, the mean for asset funds is less negative when compared with the negative alpha of the Non-asset funds funds. The variance in the performance is statistically significant. This implies that in the long term investment in asset funds, there is a better performance compared to the Non-asset funds. In the same way, when the high net worth individuals will want establish a longterm investment, it is extremely fascinating to think about certain asset funds for the wealth investment portfolio.

Table 4: Alpha in Medium Term

Comparing the values of alpa for the five years period between 2005 and 2010

Testing Equity of Means in the Series

Sample: 1 2340

Included observations: 2340

Method

df

Value

Prob

T - test

1815

18.113

0.0000

Category Stat

Variable

Count

Mean

StdDev.

StdErr. of Mean

ALPHA - 5YRS - ASSET

140

-0.034561

0.022624

0.001897

ALPHA - 5YRS - NONASSET

1670

-0.049355

0.007206

0.000174

All

1810

-0.083916

0.029830

0.002071

Table 4 above gives the outcome of comparing the alpha for the five years between the two categories. The table presents the asset funds having performed better for the 10 years than the Non-asset funds for the same period. The alpha for the two categories of funds, the assets and the Non-asset funds are of negative values. However, the mean for the asset funds investment is negative but less in the during the chosen time frame. The variation between the means is statistically considerable. The results show that for the medium term assets and the investment in the asset funds had better advices. The high net worth individuals can consider investing in the asset funds, as opposed to the Non-asset funds.

To do an advanced analysis on the performance of the asset and non-asset funds in the medium term, we take the values of the three year performance of the funds as shown in table 5 below.

Table 5: Comparing the alpha for three years

Testing for Equity of the Means in the Series

Sample: 1 2340

Observations: 2340

Method

df

Value

Probability

T - test

2053

8.490797

0.0000

Category Stat

Variable

Count

Mean

StdDev.

StdErr. of Mean

ALPHA - 3YRS - ASSET

140

-0.014731

0.009222

0.0007720

ALPHA - 3YRS - NONASSET

1910

-0.018309

0.004340

0.0000994

All

2050

-0.022040

0.013562

0.0008714

From the results in results in table 5 above, the asset funds have again indicated better performance compared to the outcome of the Non-asset funds by the look of the means. The outcome shoes the statistical variation in the three years performance. Additionally, for the shorter period, the asset fund and the non asset funds in the wealth portfolio management show negative alpha for the chosen period. The outcome for the Non-asset funds are poorer in performance than the asset funds. The Non-asset funds exhibit an alpha with more negativity (Ferris & Yan, 2009). When the investor consider an investment in the shorter term, like the three years, then the asset funds ought to be of essence in the distribution of the asset. This is because we have demonstrated better advanced performance in the asset funds for this period of three years.

2.1.2. Portfolio Characteristics

In this section, we study the possible drivers of the alpha, not mentioned in the previous sections. These aspect are excluded from the the cross-sectional assessment, due to the various drivers of alpha. The chosen drivers are assessed for every per wealth manager in stead of per fund. We therefore do the additional regressions using the fund level.

Other feature that can be linked to each individual fund characteristics also shows a control on the performance of funds (Eggins, 2008). Consequently we have gathered the individual information concerning the size or the capacity of the funds, the age of the funds, team management, the service term (tenure) of the manager and the earnings ratio. This study also collected details about the costs of a fund considering the expenditure ratio and the asset or wealth management charges.

Table 6: Cross-Sectional Analysis of Alpha for the period of 10 Years

Dependent Variable: ALPHA – 10 - YRS

Method Used: Least Squares

Sample: 1 2364

Observations: 551

Coefficient

Std. Error

t-Statistic

Prob.

C

-0.045153

0.003117

-14.50445

0.0000

LOG_FUND SIZE

-0.000245

0.000164

-1.476368

0.145

FUND-AGE – IN - YEARS

-0.000107

0.0000394

-2.725154

0.0065

TEAM - DUMMY

-0.000349

0.000543

-0.64245

0.5203

MANAGER - TENURE

0.000034

0.000032

0.559155

0.572

TURNOVER - RATIO

0.0000043

0.000037

2.415056

0.0163

EXPENSE - RATIO

0.002068

0.000664

3.11083

0.0022

MANAGEMENT - FEE

-0.00038

0.00083

-0.47713

0.6335

R-squared

0.059955

Mean dependent var

-0.04755

Adjusted R-squared

0.0478337

S.Ddependent var

0.00624

Fund Size

The fund size provides the positive as well as the negative connection with the alpha. The outcome of the fund size is not statistically important. A greater fund size possibly leads to greater economy of scale, due to the transaction cost being relatively low. On the other hand a larger fund suffers from lack of flexibility. From these results, it is not easy to decide on the effect for decision.

Table 7: Five Years Cross-Sectional Analysis of the alpha alpha

Dependent Variable: ALPHA – 5 - YRS

Method Used: Least Squares

Sample : 1 2364

Observations: 602

Coefficient

StdError

t-Statistic

Prob.

C

-0.044786

0.00419

-10.89777

0.0000

LOG - FUND SIZE

-0.000312

0.000213

-1.445332

0.143

FUND-AGE – IN - YEARS

-0.0000754

0.0000472

-1.574436

0.114

TEAM - DUMMY

0.000455

0.000713

0.6425507

0.525

MANAGER - TENURE

-0.0000336

0.0000884

-0.374457

0.705

TURNOVER - RATIO

0.0000007

0.0000023

0.364491

0.714

EXPENSE - RATIO

0.002374

0.000873

2.645898

0.0033

MANAGEMENT - FEE

-0.001062

0.001075

-0.99106

0.3245

R-squared

0.029333

Mean dependent var

-0.0489

Adjusted R-squared

0.01744

S.Ddependent var

0.0084

Fund Age

The dependent parameter (fund age) provides a negative and positive alpha values during the five years period of analysis. The statistical significant outcome is the outcome for the ten years, during which the negative relationship is seen. Because the outcome show positive and negative values, it is possible that the age of the fund is not a significant driver of the fund performance.

Table 8: Cross-Sectional Evaluation of the alpha three years period

Dependent Variable: ALPHA – 3 - YRS

Method: Least Squares

Sample: 1 2364

Observations: 691

Coefficient

Std. Error

t-Statistic

Prob.

C

-0.015178

0.00234

-6.9149

0.0000

LOG - FUND SIZE

-0.002181

0.00316

-1.55756

0.126

FUND-AGE – IN - YEARS

0.0000361

0.00043240

0.256137

0.738

TEAM - DUMMY

-0.000428

0.00482

-0.596456

0.5409

MANAGER - TENURE

-0.0005234

0.005469

-0.495529

0.653

TURNOVER - RATIO

0.0000605

0.0005012

0.392259

0.69355

EXPENSE - RATIO

0.001244

0.0003890

2.3322062

0.4197

MANAGEMENT - FEE

-0.000392

0.0002188

-1.622305

0.0524

R-squared

0.013343

Mean dependent var

-0.01572

Adjusted R-squared

0.00322

S.Ddependent var

0.00449

The management tenure for the investment is dependent variable and is negative and very small so the values are not statistically significant.

Table 9: Cross-Sectional Analysis of the alpha for one year

Dependent Variable: ALPHA - 0910

Method: Least Squares

Sample: 1 2364

Obs: 752

Coefficient

Std. Error

t-Statistic

Prob.

C

-0.004494

0.0583

-1.04765

0.3125

LOG - FUND SIZE

0.000305

0.00419

0.973087

0.3313

FUND-AGEIN - YEARS

-0.04030

0.00507

-0.276756

0.782

TEAM - DUMMY

0.00533

0.0039

2.54255

0.01407

MANAGER - TENURE

0.000688

0.003208

1.864166

0.06328

TURNOVER - RATIO

-0.00053

0.000405

-0.666628

0.50346

EXPENSE - RATIO

0.0056478

0.003221

2.166691

0.034509

MANAGEMENT - FEE

-0.006115

0.03265

-0.4351685

0.66561

R-squared

0.026697

Mean dependent var

0.00278

Adjusted R-squared

0.017539

S.Ddependent var

0.003237

Turnover Ratio

The Turnover ratio exhibits positive association with the alpha values in the long term funds investment. This outcome is statistically important, but the outcome is not strong enough. For the moderate and the short term investment, the average also gives a positive association with the alpha (Cremers & Petajisto, 2009). However, th results indicate no statistical consequence. The turnover ratio is an essential driver of the alpha, considering the high value of trading that causes a high turnover ratio. The fund manager that can be classified as a wealth picker and will demonstrate high trading actions.

Table 10: Cross-Sectional Assesemnt of Alpha one Year

Dependent Variable: ALPHA - 2010

Method: Least Squares

Sample: 1 2364

Included observations: 773 after adjustments

Coefficient

StdError

t-Statistic

Prob.

C

-0.000911

0.00262

-0.72204

0.4705

LOG - FUND SIZE

0.000565

0.0054663

1.00418

0.3161

FUND-AGEINYEARS

0.004057

0.0003138

0.45763

0.656

TEAM - DUMMY

0.004307

0.003216

3.2658554

0.511

MANAGER - TENURE

0.003251

0.000568

0.93556774

0.3592

TURNOVER - RATIO

0.004001

0.006007

0.243438

0.851

EXPENSE - RATIO

0.000313

0.0067282

2.525734

0.517

MANAGEMENT - FEE

-0.04335

0.05339

-0.491

0.3525

R-squared

0.01435

Mean dependent var

0.05144

Adjusted R-squared

0.024356

S.D dependent var

0.00598

As indicated in the assessment in table 10 above, the greater expense ratios in the wealth management and the portfolio optimization is not driven by the many transaction costs in the asset funds. In stead, it can be viewed that in the asset investment, managing the company is easier in the efficient and the cost effective method (Ramos, 2009). At the same time , the larger Non-asset funds wealth management is of benefit when considering the economies of scale as a result of their sizes. Our outcome can not show the cost competent structure in the wealth management and so we expect that the low expenditure ratios of the Non-asset funds asset management is essentially because of the greater economies of scale.

Table 6.18 - Descriptive statistics management fee

MNGMT - FEE - ASSET

MNGMT – FEE – NON - ASSET

Mean

1.45

1.07

Median

1.54

1.13

Max

2.55

4.55

Min

0.35

0.05

StdDev.

0.35

0.55

Skewness

-1.16

0.26

Kurtosis

4.62

3.900674

Jarque-Bera

39.34

66.75

Proba

0.01

0.00

Sum

169.95

1591.56

Sum SqDev.

13.07

453.5617

Obs

117

1484

Table 6.19 - Comparison of management fee

Test for Equality of Means Between Series

Sample: 1 2500

Included observations: 2500

Method

df

Value

Probability

t-test

1599

7.320331

0.0000

Category Statistics

Variable

Count

Mean

Std. Dev.

Std. Err. of Mean

MNGMTFEEASSET

117

1.452222

0.335937

0.031057

MNGMTFEENONASSET

1484

1.07248

0.553029

0.014356

All

1601

1.100231

0.549028

0.013721

Within the documented cross-sectional analysis, there is a documentation of the positive connection between the expenditure ratio and the fund alpha. The time-series study indicated that the overall asset funds were better in performance compared to the Non-asset funds (Benson, Tang & Tutticci, 2008). The comparison of the structure of the expenditure gives a clear impression that the expenditure ratio of the asset funds is generally greater than that of the Non-asset funds. The returns that acts as the foundation of the alpha computation is not covered in the costs as well as the expense ratio and has a great effect on the last return from the portfolio.

7 – Conclusion and Recommendations

The outcome of this study shows that the asset funds (wealth fund) has more efficient performance than the non-wealth funds for the last 10 years. The mean alpha during the 10 years period is negative for the wealth based funds as well as the non-wealth based funds. Nevertheless, the mean of the asset funds was found to be negative but lower in negativity than the negative alpha values of the Non-wealth funds. In that regard, the long term asset funds demonstrated better performance than the Non-wealth (non-asset) funds. At the same time, the short term period gave better better performance as illustrated. In the 3 years period, the the review showed the average performance of the asset and the Non-asset funds funds generating negative alphas. Still in this scenario, the wealth – based fund investment performed better.