Asset Management and Portfolio Formation: Syndicate assignment, Q2 and Q4

Transcription

1 Asset Management and Portfolio Formation: Syndicate assignment, Q2 and Q4 August 2014 Hugh Napier ( N) Motlodi Charles Ntjana (303921) Similo ### Priya Garg (956738)

2 Question 2: a) Ferreira, Keswani et al. (2013) examine what factors influence openend managed mutual fund performance. Historic research on understanding fund performance has focused on fund characteristics such as size, age, fees and expenses, loads, turnovers (liquidity), flows and historic returns, management structure and domestic vs international diversification. The rationale being that older and larger funds should have purchasing power (bulk orders) and scale (management overheads and expertise), which should reduce total expense ratios and allow for better returns to end consumers. The overall trading and legal environment allow for trading efficiencies and ensure high liquidity and investor protection. Interesting current literature provides both supportive and contradictory findings to the above logic to predicting mutual fund performance. For example (Chen, Hong et al. 2004) suggest that fund performance in fact worsens as fund size increases. Several arguments have been made relating to large funds not being able to invest as actively in small market cap stocks as larger funds and also that their purchasing activities are easily tracked in the market based on the large trade volumes. Thus smaller funds are potentially more agile than larger funds and may outperform them for this reason. This paper examines all of the above factors as well as country specific factors and examines whether they influence or predict mutual fund performance better than the classic fund specific characteristics listed above. The non country specific factors are listed below, with Table 1 below describing in more detail the country specific factors and the associated findings. Non-country specific factors (Findings of Ferreira, Keswani et al. (2013)): 1 P a g e

3 Fund size: Performance has a negative correlation with fund size Fund family size: Performance has a positive correlation with fund family size Age: No relation found in US markets, but newer funds perform better than older funds outside the USA Expenses: No consistent correlation with fund performance Loads: No relation between loads and performance Flows: Smart money effects are not correlated with flows Past performance: Positive correlation between past performance and future performance, but country specific actors could explain this better Management structure: Team managed funds perform worse than individually managed funds Number of countries where fund is sold: Weak evidence for funds selling in multiple countries performing better TABLE 1: Country specific factors influencing mutual fund performance (Ferreira, Keswani et al. 2013) Element Description Finding Economic development Financial development Investor protection and legal More developed economies will include investors with greater financial education and awareness. This should exert pressure on mutual fund managers to perform better for the fees that they charge More developed financial economies should have higher liquidity (turnover), lower transaction costs and greater information flow and transparency. Investor protection is a fundamental starting Broad economic development is not a statistically significant factor in predicting mutual fund performance Trading costs are negatively correlated with fund performance and increased share turnover improves fund performance (1 std dev improvement in turnover equates to a 38 basis point improvement in performance) Common law countries demonstrate positive 2 P a g e

4 infrastructure Mutual fund industry development and concentration point for any investment decision and activity. This is best captured by the legal frameworks and infrastructure More mature mutual fund markets should have greater experience and thus generate better returns correlations to fund performance relative to civil law countries. Indicators for shareholder rights and the securities market regulations also show positive correlations to fund performance. No correlation between the age and maturity of mutual markets, with their performance was found b) I. Ferreira, Keswani et al. (2013) employed a four factor CAPM model in order to understand and model mutual fund performance. They combined the three factor Fama and French (1992) model with that of Jegadeesh and Titman (1993) (Fama and French 1992, Jegadeesh and Titman 1993). The additional factors include factors that track the impact of market capitalisation, market to book value and the impact of historic performance (momentum) on fund performance. They thus ended up with a CAPM model as below: Where: β 0 Market beta from standard CAPM β 1 Small market cap to large market cap beta β 2 High book to market vs low book to market beta β 0 Market momentum beta This model has greater explanitory power than the classic CAPM model used by Malkiel (1995). This is best shown in Table II, where the coefficients for these additional factors are shown to be sttaistically significant and non zero, particulatrly in the USA market. Of interest is the focus of Malkiel (1995), was in the USA market. 3 P a g e

5 II. III. A time lag is necessary to allow the fund managers time to respond to the information presented in the various indicators. Mutual fund managers will also adjust portfolios on the basis of trends emerging and this will take time to establish. The quarterly interval is used based on the reporting intervals of indicators such as GDP and various confidence indices. Most data sets that are used to evaluate mutual fund performance only track the performance of current funds (Malkiel 1995). Thus in evaluating fund performance, all non performing funds that are closed would be excluded from analysis. This introduces a survivorship bias / phenomenon, in which mutual fund returns are over stated. This is most likely to be the reason behind the independent variables having limited (5%) predictive power in explaining fund excess returns in Ferreira, Keswani et al. (2013). Not only are non performing funds dropped from reporting records, but fund managers often create incubator funds, where only the best performing funds are ultimately reported on and marketed (Malkiel 1995). Thus in order to account for this the four factor CAPM model created by Ferreira, Keswani et al. (2013), could be extended to include a fifth factor which would be a dummy variable to track any changes to a fund. For example a value of zero could be ascribed to funds, which have no investment strategy changes, no merges with other funds and have been in existence throughout the data review period (time interval of analysis); whereas a value of 1 could be ascribed to funds which undergo any change relating to investment strategy, merging with other funds or those that are newly created in the period under review. This approach could determine the 4 P a g e

6 survivorship impact on fund performance anmd determine if it is a major factor in explaining mutual fund excess returns. c) According to chen et al.( 2004), evidence has been found that small funds perform better than large ones in the USA. The findings revealed that liquidity constraints play an important role in explaining why fund size erodes fund returns. This association was most prominent among funds that invest in small and illiquid stocks (small Caps), suggesting that these adverse scale effects are related to liquidity. The negative Size effect in the USA is economically significant as a one standard deviation increase in fund size yields a 0.15% decline in the next quarter s fund return. This striking difference on diseconomies of scale is unique to the USA, as fund size does not seem to hurt the performance of funds that invest overseas. d) Empirical researchers do not know the true model. Neither theory nor intuition, neither the scientific tests nor data mining can give empirical researchers sufficient guidance to specify a Scientific/econometric model which exactly mirrors the true datagenerating process. If the model differs from the true datagenerating process, estimates are biased and standard errors do not reveal the true level of uncertainty, as a consequence inferences maybe unreliable. A test is claimed as robust if it still provides insight to a problem despite having its assumptions altered or violated. In general, being robust means a system can handle variability and remain effective. Importance Robustness tests were introduced to avoid problems in interlaboratory studies and to identify the potentially responsible factors The robustness test examines the potential sources of variability in one or a number of responses of the method being studied. Help Identify the system suitability test (SST) limits can be defined (e.g. resolution, tailing factors, capacity factors, column efficiency in a chromatographic method) can be evaluated Another Aim of a robustness test may be to predict reproducibility or intermediate precision estimates 5 P a g e

7 Question 4: Text d) The Investment Committee of Actis (China) is involved with accepting the investment opportunities that are presented to them from the Investment Principals, such as Joseph Li in this case. The main aim of IC is to approve the projects that conform to the investment policy of the company. This being said, Actis is a private equity firm and not a venture capital company. The clear distinction between the two lies on many factors such as the return on investment criteria, target industry, investment size, investment horizon, the use of leverage and different options for financing etc. However, the most important differentiation factor is the type of target companies they aim to invest in: venture capital companies aim to provide funding to companies that are either in their infancy stage or still in the process of developing their idea/product. In line with that, these start-ups are have either no revenues or are operating at losses due to the initial cost of setting up operations or researches carried out and hence carry high risk and low liquidity. Venture capital companies base their decisions on the growth potentials of the company itself, and hence require a high rate of return to offset the high risk (Fenn, 1995). On the other hand, private equity firms focus on companies that are relatively mature. These firms perform on their proven technology or strategy, in the case of 7 Days Inn. They are generally earning accounting profit, which makes them less risky investments and with a 6 P a g e

8 slightly higher liquidity than start-ups. Private equity firms also base their decisions on the growth potential of the company. In line with the above, 7 Days Inn falls between the categories of earlystage ventures that venture capitals fund and the later-stage ventures that private equity firms fund. At the time of consideration, the Inn was incurring losses at the time of consideration, even though the EBITDA is generally improving over the years, suggesting both growth potential and validation of the company s business plan. However, it is relatively less mature than later-stage ventures and still faces losses: though this can be explained by costs incurred due to the rapid expansion of the franchises, it still raises a red flag for the IC. e) There are three general valuation approaches that can be adopted: discounted cash flows, comparable transactions and opportunity cost method. The discounted cash flow method involves the adjusted present value method and weighted average cost of capital method. The comparable transactions method involves comparing key accounting ratios of the venture being considered to that of similar companies in its industry. Lastly, the opportunity cost method involves evaluation of different methods available to the investor. As 7 Days Inn is in the service sector and hence comparable transactions would apply more aptly as the valuation method. Lin s pitch to the IC is that the budget hotels sector in the lodging industry has high growth potential and hence comparing 7 Days Inn to other budget hotels will provide a good view of where it stands versus other budget hotels and how its customer acquisition and retention strategies fare. Due to the nature of the sector, the European Private Equity & Venture Capital Association (EVCA) suggests various comparative criteria: Price/ Earnings Ratio Price/ EBITDA Ratio Price/ turnover Ratio 7 P a g e

9 Other criteria that are specific to the lodging industry should also be applied, such as: Room yield Rental costs Maintenance costs Agent fees Occupancy rate f) There are several factors that impact the lodging industry: the macroeconomic standing of the economy, technological advancements that allow better advertisement and customer acquisition as well as for service delivery, competition from similar lodging facilities, changing demographics of travellers, the presence of well-known hotels versus new domestic start-ups and finally the changing travelling trends. The Lehman Bankruptcy will have a direct impact on China s macroeconomic standing and the travelling trends of 7 Day Inn customers. Firstly, the Bankruptcy impacts the flow of international travellers to the country, both those that travel for leisure and those that travel for business purposes. Due to the Bankruptcy, forecasts of recession imply that the foreign traveller, especially those that travel for leisure, will face two options: downgrading from their current lodgings to cheaper ones, if they wish to continue their vacations, or in the adverse situation, cancelling trips altogether. Leisure foreign travellers also may then choose to plan their vacations domestically rather than internationally. In the case of 7 Days Inn, since it is a budget hotel chain that attracts mainly domestic business and leisure travellers, this can lead to higher sales forecasts: international travellers from high-end hotels will seek more affordable, standardized service for a lower cost than those that they incur at four- and five-star hotels. 8 P a g e

10 In contrast to that, there will be an economy-wide impact on the Bankruptcy: the recession in the United States of America will impact China s economy as well. Some industries in China will be directly impacted, e.g. the exported goods sector: closing down of firms in these sectors or even slashing of wages results has a two-fold implication: depending on the impact of business activity, the budget hotels will see a drop in business travellers and lower wages implies immediate termination of luxury expenditure, e.g. travelling for leisure. There are two opposing impacts of the Bankruptcy: downgrading of travellers from expensive, higher-end hotels to budget hotels and the loss of the existing customer base. The decision to invest in 7 Day Inn will then be derived from whether the incoming new customers will offset the loss of the already acquired customers. From the information given, since the business already has a very lean business model, e.g. low variable costs, smaller rooms leading to low maintenance costs, low staff to room ratio, low rental costs, etc., and a high level of adaptability, e.g. introducing the IT and ecommerce platform for bookings Actis should invest to 7 Days Inn. However, due to the macroeconomic impact of Lehman Bankruptcy, the strategy for 7 Days Inn will need to be changed from rapid expansion through franchises in new locations to sustainability. The focus should then be on the smooth running of existing hotels to not incur any new fixed costs from leasing new locations that may, eventually, lead to losses on current hotels and their ultimate closedown. 9 P a g e

11 References Chen, J., H. Hong, M. Huang and J. D. Kubik (2004). "Does Fund Size Erode Mutual Fund Performance? The Role of Liquidity and Organization." American Economic Review 94(5): Fama, E. F. and K. R. French (1992). "The Cross-Section of Expected Stock Returns." The Journal of Finance 47(2): Ferreira, M. A., A. Keswani, A. F. Miguel and S. B. Ramos (2013). "The Determinants of Mutual Fund Performance: A Cross-Country Study." Review of Finance 17(2): Jegadeesh, N. and S. Titman (1993). "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency." The Journal of Finance 48(1): Malkiel, B. G. (1995). "Returns from Investing in Equity Mutual Funds 1971 to 1991." The Journal of Finance 50(2): European Private Equity & Venture Capital Association. (2007). Guide on Private Equity and Venture Capital for Entrepreneurs. Brussels: EVCA. Fenn, G. W., Liang, N., & Prowse, S. (1995, December). The Economics of the Private Equity Market. Washington DC. 10 P a g e