代写L1094 Applied Finance Project Spring Term 2024/2025代做留学生SQL语言程序

List of Project Topics

L1094 Applied Finance Project

Spring Term 2024/2025

Students are required to read the research topics of Applied Finance Project that are listed below and choose three topics in order of their preferences, then submit the topic preference form available on the Units view on the Canvas site for this module by the following deadline:

12pm Monday in Week 2 (3^th February 2025)

Preferences are respected on a first come first served basis. Note that more than one student can do the same topic title if, for instance, it is applied to another case study or context. The projects will be allocated once we receive the topic preference forms, and each student will then be allocated a supervisor and notified to this effect by the end of Week 2 of the Spring Term.  

Each topic has a title, a short description, suggestions on how to conduct research, and a short list of key references. This is meant to provide an introduction to the topics only and students may want to go beyond these core reading. Students can identify additional reading using, for example, the Library’s on-line searching facilities or Google. In consultation with project supervisors, students may focus their research on a particular direction and/or exploit different sources of data.  

In the topic list there are often several topics which are related (e.g., doing the same project but for different datasets which may be different countries or time periods). It might be useful to cross-reference to the related topics as there may be useful suggestions on methods, data and readings in broadly similar topics.

1. Are Chinese Stock Markets Efficient?

Outline: There are three major stock markets now active in China: Hang Seng (Hong Kong), Shenzhen and Shanghai. The purpose of this project is to determine whether the stock markets are efficient. In other words, do the returns follow a random walk?

Methodology: The project will require use of a variety of unit root tests and cointegration econometric techniques. A good paper that describes the background to the stock markets in China is Chan et al. (2007), and the empirical methodology to be used is described in Liu et al. (1996).    

Data: The period of interest and the frequency of the data (e.g., daily, weekly time intervals) can be determined in consultation with you supervisor. Data is available on we sites of stock exchanges or Yahoo Finance.

Reading

Chan, K., H. Fung and S. Thapa, 2007. “China Financial Research: A Review and Synthesis.” International Review of Economics and Finance 16 (3): 416-428.

Liu, X., H. Song and P. Romilly, 1996. “Are Chinese Stock Markets Efficient? A Cointegration and Causality Analysis,” Applied Economics Letters 4 (8): 511-515.

2. Does Activity on the Hang Seng Stock Market Lead the Shanghai and Shenzhen Stock Markets?

Outline: There are three major stock markets now active in China: Hang Seng (Hong Kong), Shenzhen and Shanghai. The project will investigate whether the movements in the Hang Seng market determine or lead the activity in the others.

Methodology: This will involve use of causality testing techniques from econometrics. A good paper that describes the background to the stock markets in China is Chan et al. (2007), and part of the empirical methodology to be used is described in Liu et al. (1996).    

Data: The period of interest and the frequency of the data (e.g., daily, weekly time intervals) can be determined in consultation with the supervisor. Data is available on the stock markets website or Google Finance.

Reading:

Chan, K., H. Fung and S. Thapa, 2007. “China Financial Research: A Review and Synthesis.” International Review of Economics and Finance 16 (3): 416-428.

Liu, X., H. Song and P. Romilly, 1997. “Are Chinese Stock Markets Efficient? A Cointegration and Causality Analysis,” Applied Economics Letters 4 (8): 511-515.

3. Is there a Relationship between Stock Market Returns and Consumer Confidence in China? 

Outline: Stock markets have become an increasingly important part of China’s economy over the last two decades.  The re-opening of the Shanghai stock market and the inauguration of the Shenzhen stock market in the early 1990s was partly motivated by China’s need for private capital.  There is a literature on the relationship between the stock market and consumer confidence.  There is the possibility of a causal relationships operating in both directions: consumer sentiment influencing stock returns, and stock returns influencing consumer confidence (and hence consumers’ expenditure through either a traditional wealth effect or as an indicator of favourable future economic conditions). This project investigates whether or not there is a short-run relationship between Hang Seng stock market returns and changes in consumer confidence in China. The econometric analysis will use causality testing, among other approaches, to determine and interpret the direction of the relationship.

Data: Data regarding consumer confidence can be collected from the Organisation for Economic Development (OECD), comprised of values from the Westpac-MNI China Consumer Sentiment Index.  Data on the Hang Seng (or Shanghai) stock market can be found on Yahoo Finance or other financial databases.

Reading

Jansen, W. K. and N. J. Nahuis, 2003. “The Stock Market and Consumer Confidence: European Evidence,” Economics Letters 79 (1): 89-98.

Otoo, M. W., 1999. “Consumer Sentiment and the Stock Market,” Finance and Economics Discussion Series, Federal Reserve Board.

4. What Is the Effect of Good and Bad “News” on Stock Market Prices?

Outline: The recent BP oil spill in the Gulf of Mexico is by far the largest oil spill in the history of the oil industry. Aside from the environmental and economic impacts on people in and around the Gulf of Mexico, what effect did it have on share prices of BP, and other large oil companies? We might expect that the share price was affected by the release of news about the severity of the spill and clean up costs (i.e. new information) and also by public anti-BP statements by Obama and others.  Were other oil companies affected, and by how much compared to BP?  

The effect of good and bad news on share prices is a particular area of study for economists interested in the efficient market hypothesis. How did the SARS outbreak in China in April 2003 affect the Hang Seng? How did the fake powdered milk case in Fuyang in 2004 affect stock market confidence in China and more specifically shares in food processing or food producing companies? What about the ill health and eventual death of Steve Jobs – how was the Apple share price affected?  You could investigate the effect of news of a merger, or collapse of a deal, discovery of a new resource, outbreak of war or peace etc, election of a new party to government etc. Rather than follow an individual firm’s share price, you could examine an overall share price index and examine the effect of “news” on its value.

This topic can potentially be chosen by several students, as long as each student chooses their own firm and news event (or events).

Methodology: A very simple approach would be to regress the daily share price on say, the market interest rate, and one or more dummy variables that capture “news” events.  You will find that the literature on stock market efficiency has more sophisticated models. Start with something simple and then build on that.

Data: Share price data are easily accessible online and if you have relevant cases you can choose a Chinese stock market. You need to decide if you want daily prices or something averaged over a period, or measures of volatility that you will construct form. the raw price data. You need to make sure you cover a sufficiently long period before and after the “events”.  You might also want to access share price data on either the relevant industry as a whole, or of main rivals, to test if the share price you are following moved in line with other firms. You will need to construct 'news' events that might have affected the share price – good and bad news. This may require piecing together lots of info from media coverage. You may find it useful to construct a timeline of events (speeches, press releases, real events) and see if any of those are followed by drops or rallies in the share price. Of course, some news may have been good.

Reading

Cebula, Richard J., James V. Koch and Robert N. Fenili, 2011. “Do Investors Care if Steve Jobs is Healthy?” Atlantic Economic Journal Special Issue: Current Issues in Financial Economics" 39 (1): 59-70.

Copeland, L. S., 1989. “Market Efficiency before and after the Crash,” Fiscal Studies 10(3): 13-33.

Firth, M., 1986. “The Efficient Markets Theory”, in M. Firth and S. M. Keane (eds), Issues in Finance, Philip Allan.

Jackson, P. D. and A. D. O'Donnell, 1985. “The Effects of Stamp Duty on Equity Transactions and Prices in the UK Stock Exchange,” Bank of England Discussion Paper 25.

Thaler, R. H., 1987. “Anomalies”, Journal of Economic Perspectives 1(1)” 197-201 and 1(2): 169-178.

On oil spills (pre-BP Gulf of Mexico):

Alsop, R. J., 2004. “Corporate Reputation: Anything but Superficial – The Deep but Fragile Nature of Corporate Reputation,” Journal of Business Strategy 25 (6): 21-29.

Alli, K., S. Thapa and K. Yung, 1994. “Stock Price Dynamics in Overlapped Market Segments: Intra and Inter-Industry Contagion Effects,” Journal of Business Finance & Accounting 21 (7): 1059–1070.

Anthony, H., J. Marshall and J. Wingender, 1996. “An Analysis of the Stock Market Response to the Exxon-Valdez Disaster,” Global Finance Journal 7(1): 101-114.

5. What are the Determinants of Remittances by Migrants in China?

Outline: For this project the student will investigate what factors determine the proportion (rather than the size) of annual labour market income that male Chinese migrants remit home each year.  

Methodology: The project will require use of OLS regression analysis where the share of annual income remitted home each year will be regressed on a set of individual level demographic and other factors (e.g., age, educational level, sector of work, time spent as a migrant etc.). The project will thus permit an investigation of the key motivations for these transfers. The theoretical issues governing individual remittances are contained in the two readings below and the references cited in them.

Data: Data is available on the module Canvas site.

Reading

Carling, J., 2008. “The Determinants of Migrant Remittances.” Oxford Review of Economic Policy 24 (3): 582-599.

Liu Q. and B. Reilly, 2004. “Income Transfers by Chinese Rural Migrants: Evidence from Jinan.” Applied Economics 36 (12): 1295-1314.

6. The Impact of Oil Prices on Asset Prices

Outline: This project will examine the impact of oil price changes and/or its volatility on asset prices such as stock returns and/or exchange rates.

Data and Methodology: Time series of oil prices, stock prices and exchange rates can be obtained from many sources, including Thomson Reuters Eikon and Datastream. The tests and econometrics methods employed in this project include descriptive statistic, correlations, and regression analysis. More advanced time series models such as cointegration analysis and volatility models can also be used.

Reading

Filis, G., S. Degiannakis and C. Floros, 2011. “Dynamic Correlation between Stock Market and Oil Prices: The Case of Oil-Importing and Oil-Exporting Countries.” International Review of Financial Analysis 20 (3): 152-164.

Kilian, L., and C. Park, 2009. “The Impact of Oil Price Shocks on the U.S. Stock Market.” International Economic Review 50 (4): 1267-1287.

Li, S., H. Zhu and K. Yu, 2012. “Oil Prices and Stock Market in China: A Sector Analysis using Panel Cointegration with Multiple Breaks.” Energy Economics 34(6): 1951-1958.

Lizardo, R. and A. Mollick, 2010. “Oil Price Fluctuations and U.S. Dollar Exchange Rates.” Energy Economics 32 (2): 399.408.  

7. What Determines the Price of Gold?

Outline: Gold is an asset that is sometimes interpreted as a long-run ‘hedge’ against inflation and short-run ‘hedge’ against exchange rate movements. The fact that the volume of gold mined is minimal, increases in global real income and the demand for jewellery may also exert an impact on gold prices. In addition, gold prices also respond to extreme economic crises and political risks. Thus, it would be useful to model the relationship between movements in gold prices and US inflation and exchange rates, global income, and any relevant political or other global events that have occurred.

Methodology: The empirical methodology use cointegration techniques and an appropriate specification would be in the form. of an error correction mechanism (ECM) model that allowed an investigation of the short-run and long-run effects  

Data: It is suggested that you use annual data for this project starting as early as possible (e.g., the early 1960s). The gold prices can be downloaded from the London Bullion Market Association homepage. Consult the Oxford Economics Report (2011) in the readings below for information on the data sources for other macroeconomic variables.  

Reading

Oxford Economics Report, 2011. “The Impact of Inflation and Deflation on the Case for Gold,” A Report Commissioned for the World Gold Council, Oxford Economics.  

Sumner, S., R. Johnson and L. Soenen, 2010. “Spill-over Effects between Gold, Stocks and Bonds,” Journal of Centrum Cathedra 3 (2): 106-120.  

8. The Role of Technical Indicators in Forecasting the Crude Oil Price Changes.

Outline: This project will investigate the ability of a variety of technical indicators and macroeconomic fundamentals to forecast crude oil price changes.

Methodology: This will involve the use of linear regression techniques. A good paper that can be used as a background reading is Neely et al. (2014).

Data: Students will have to collect their own data.

Reading

Neely, C. J., D. E. Rapach, J. Tu and G. Zhou, 2014. “Forecasting the equity risk premium: The role of technical indicators.” Management Science 60 (7): 1772-1791.

9. Do Retail Petrol Changes Respond Asymmetrically to Crude Oil Price Changes?

Outline: There is a view by consumers that retail petrol prices at the pump respond asymmetrically to crude oil price changes.  The argument is that retail prices rise like a rocket when crude oil prices increase but fall like a feather when crude oil prices decline. The purpose of this project is to investigate the evidence for this proposition using monthly retail price data from the UK over the last 20 or so years.    

Data: Students will have to collect their own data on their selected country.

Methodology: The basic empirical methodology will be OLS but the analysis is best situated within an error correction mechanism (ECM) model framework.  For example, the template to use to start with could be Reilly & Witt (1998) below.

Reading

Reilly, B. and R. Witt, 1998. “Petrol Price Asymmetries Revisited,” Energy Economics 20 (3): 297-308.

Frey, G. and M. Manera, 2007. “Econometric Models of Asymmetric Price Transmission,” Journal of Economic Surveys 21(2): 349-367.

10. Corporate Governance and Capital Market Responses: Does Good Corporate Governance Affects Market Valuation by Investors?

Outline: This study examines the relationship between corporate governance e and firm performance in the UK pre and during the financial crisis. The rationale for an association between corporate governance and firms’ performance arises because better governance enhances efficiency in the monitoring of managerial activities. This in turn, encourages managers to pursue value-maximizing projects and to avoid expropriation of firms’ resources such as perquisites consumption (Love, 2011). In addition, better governance increases investors’ protection by limiting expropriation of firms’ resources from the majority shareholders (La Porta et al., 2002; Lemmon and Lins, 2003).  

Data: The data covers corporate governance and financial information of a sample of UK non-financial companies listed on London Stock Exchange (LSE) over the period pre and during crisis, or the student will have to collect their own data on their selected country.

Reading

Li, C., Li, J., Liu, M., Wang, Y., and Wu, Z., 2016. “Anti-misconduct policies, corporate governance and capital market responses: International evidence”. Journal of International Financial Markets, Institutions & Money 48: 47-60.

Essen, M., Engelen, P. and Carney, M., 2013. “Does ‘Good’ Corporate Governance Help in a Crisis? The Impact of Country‐and Firm‐Level Governance Mechanisms in the European Financial Crisis.” Corporate Governance: An International Review 21(3): 201-224.

Erkens, D., Hung, M. and Matos, P., 2012. “Corporate Governance in the 2007–2008 financial crisis: Evidence from financial institutions worldwide.” Journal of Corporate Finance 18: 389-41.

Leung, S., and Horwitz, B., 2010. “Corporate governance and firm value during a financial crisis.” Review of Quantitative Finance and Accounting 34(4): 459-481.

11. International Trade and Its Impact on Growth

Outline: Globalisation has been one of the most important and controversial issues in the twenty-first century. As an indicator of globalisation, trade remains as a major branch of economics. Students in the past explored growing trade between industrial and developing countries, the effects of globalisation on growth, pollution and poverty, problems of international trade policy.

Data and Methodology: Students are expected to choose countries and time periods of interest. Time series of openness and growth can be obtained from many sources including the World Bank Development Indicators. Time series analysis include descriptive statistics, correlation coefficients, unit root tests.

Reading

Heckscher, E. and Ohlin, B., 1991. Heckscher-Ohlin Trade Theory, translated, edited, and introduced by H. Flam and M. Flanders, Cambridge: MIT Press.

Krugman, P. and Lawrence, R., 1994. “Trade, Jobs and Wages”, Scientific American, 270: 44-49.

Leamer, E., 1980. “The Leontief Paradox, Reconsidered”, Journal of Political Economy, 88: 495-503.

Frankel, J. and Romer, D., 1999. “Does Trade Cause Growth?” American Economic Review 89 (3): 379-399.

12. On the Link between Stock Prices and Exchange Rates

Outline: There are two main types of theoretical models analysing the linkages between exchange rates and stock prices. The traditional approach based on ‘flow-oriented’ models posits that causality runs from the former to the latter, whereas the portfolio approach based on ‘stock-oriented’ models suggests the opposite. This project will examine the linkages between stock prices and exchange rates within national economies to further test these theories.

Data and Methodology: Time series of stock prices and exchange rates can be obtained from many sources, including Thomson Reuters Eikon and Datastream. The tests and econometrics methods employed in this project include descriptive statistic, correlations, and regression analysis. More advanced time series models such as cointegration analysis and volatility models can also be used.

Reading

Caporale, G.M., Hunter, J., and Menla Ali, F., 2014. “On the linkages between stock prices and exchange rates: Evidence from the banking crisis of 2007-2010.” International Review of Financial Analysis 26: 150-170.

Phylaktis, K., and Ravazzolo, F., 2005. “Stock prices and exchange rate dynamics.” Journal of International Money and Finance 24: 1031.1053.

Ülkü, N., and Demirci, E., 2012. “Joint dynamics of foreign exchange and stock markets in emerging Europe.” Journal of International Financial Markets, Institutions & Money 22: 55-86.

13. Football Finance

Outline: The world of football is now replete with high quality financial data at the club level. This includes data on football clubs which are (or have been) quoted on the stock exchange. It also includes many years of club accounts data. It will be possible to take one of the elite clubs which are quoted on the stock exchange to examine the influence of on-field performance on the weekly stock market price. It is also possible to analyse the effect of close competitors in the same league of their rival’s financial performance. Long run financial effects of changes in attendances and TV revenues on club’s profitability can be studied using annual report data from Deloittes.

Possible titles to explore this topic include the following:

1) Stock market share price effects of team performance in elite football.*

2) Team Rivalry and performance on football club share price.*

3) The financial redistributive effects of TV revenue in UK professional football.

4) The effect of financial fair play (FFP) of Premier League football.

5) Stadium capacity as a constraint on the demand for football.

Note that titles marked with an * are most suitable for Finance students who are predominantly interested in a project which involves stock market share price data.

Reading

Szymanski, S. 2015. Money and Football: A Soccernomics Guide, Nations Books.

Dobson S. and J. Goddard, 2001. The Economics of Football, Cambridge University Press.

Maguire, K., 2021. The Price of Football, Agenda Publishing.

Peeters, T. and S. Szymanski, 2014. “Financial fair play in European football,” Economic Policy 29 (78): 343–390.

Bryson, A., P. Dolton, J. Reade, D. Schreyer and C. Singleton, 2021. “Causal effects of an absent crowd on performances and refereeing decisions during COVID 19,” Economics Letters 198.

Deloitte, 2022. “Annual Review of Football Finance 2022”.