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Financial Integration and Firm Performance

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Michael Jennings

International Financial Management

Master Thesis:

University of Groningen

Uppsala University

#S1621254

Supervisor: Dr. W.

Westerman

Financial Integration and Firm

Performance

:

A Time Series Country Analysis of American &

Canadian Financial Firm Performance During the

2008 Crisis.

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Abstract

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Background ... 4

Research Question ... 4

Influential Determinants of the Financial System ... 6

The Conceptual Model ... 6

Chapter 2: Firm Performance and the Crisis ... 9

Firm Productivity ... 9

Influential Factors on Firm Specific Components ... 10

Financial Harmonization and Diversification ... 10

Cross Country Integration ... 10

Internal Factors ... 13 Variables ... 17 Hypothesis ... 20 Chapter 3: Methodology ... 21 Time Series ... 21 Chapter 4 Results ... 23

Fluctuations and Trends of Variables ... 24

Correlation and Regression Analysis ... 32

Chapter 5 Conclusion and Discussion ... 35

Potential for Further Research ... 37

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Background

Over the past decade, inefficient corporate governance (Aguilera & Jackson, 2010), poor managerial practices (Contugno & Stefanelli, 2007) and the inability of institutions to prevent the spread of contagion (Adrian & Shin, 2008) led to the late 2000’s global financial crisis. Studies have shown that this crisis was caused by a deficiency in financial institutions along with excessive capital lending that lacked borrowing requirements (Steil, 2009; Rose & Spiegel, 2009). Several large institutions had unresolvable issues which severely impacted financial firms (Steil, 2009) and reduced their ability to perform well in both the short term and the long term. This created various kinds of threats in the financial system.

The threats of contagion and risk exposure need to be reduced and mitigated with effective managerial practices on firm-specific levels (Amenc et al, 2011) and on broad national and systematic levels (Aguilera & Jackson, 2010). Then firms will be able to diversify effectively and mitigate risks (Adrian & Shin, 2008) even in times during a crisis (Contugno & Stefanelli, 2012). In theory this helps firms operate more efficiently. When risks can’t be mitigated managers must find a way to minimize the consequences of the damage that can occur afterwards. Managerial practices tend to mimic other mechanisms involving risk assessment on operational activities and as a result their practices sometimes become inefficient on a wide scale and that leads to actions that destabilize the financial system (Pollin, 2008).

Rose (2012) pointed out that this crisis was systematically originated in the US and created widespread contagion with various effects extending to multiple financial markets. Some studies show how financial firms in the US were severely hit, more so than other financial firms in Canada and the UK which both have a similar Anglo Saxon model of capitalism (Martin, 2010). If this is true then this leads us leads us to the question of why did highly integrated financial firms with high connections in the US market have less exposure than other financial firms that were less integrated? To answer this, it’s important to examine the core characteristics of financial governance systems and how crises are linked with integration (Rose, 2012) and also its relationship with firm performance. With this research we’ll be using several components from previous conceptual models to get a more thorough understanding of how these components effect firms during times of a crisis and hopefully provide some solutions as to how to successfully counter contagion during a financial crisis. Financial crisis in my model will be defined as a decrease in asset prices leading to the failures of financial and non-financial firms (Mishkin, 2011). The model will be composed of several financial components and firm-level financial indicators that will be used to provide quantitative evidence to show how firm performance is influenced by integration during the crisis period. Financial indicators are primarily composed of independent variables such investment cash flows, debt to assets, debt to equity, financial cash flows and operational efficiency and asset management. These indicators are chosen because they pertain to several environmental changes in the financial system that can have direct and indirect impacts on firm performance as they’re affected by various non-indicator components in the conceptual model. This leads us to the research question.

Research Question

Which financial types of financial variables (or indicators) are most important for firms’ protection in order to minimize their exposure during a global financial crisis?

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Financial openness in theory should work as a gateway for strengthening integrated policies and risk mitigation where firms can independently choose their methods for diversifying risk more adequately. However during a financial downturn, risk mitigation becomes more difficult as there are fewer options to choose from because the crisis could be systemic.

2b) Which managerial practices are most important to influencing financial indicators that effect their ability to

counter contagion?

Since we’re using large Canadian and American financial firms which are both similar in terms of markets and financial systems, it’s important to analyze the differences of the firms’ reactions to contagion, financial integration, managerial risk and its effect on firm performance. There are several components pertaining to firm reaction listed in tables one, two and three which differ from the variables and will explained throughout the chapters. This brings me to the next question.

2c) Does financial liberalization lead to stronger counter-risk productive techniques where firms adapt well to

environmental changes and counter exposure effectively?

One problem could be that one set of firms are in an industry or market where contagion is being created and on some occasions these firms themselves contribute to a great deal contagion within their own environment. At the same time other firms are able to cope with the volatility in the market in a more responsible way.

Other areas of this research will lightly examine further questions such as:

2d) Is firm integration beneficial towards diversification (in policy and practice)? And if so then to what extent did

this difference have on affecting the level of exposure from the crisis?

2e) How much does manager expertise and managerial practices effect the level of risk that occurs during a

time of crisis?

Skilled managers provide practices for their firms more efficiently and can acquire stronger skills on evaluating productive options and conducting the most attainable methods for assessing their firm’s performance. This involves analyzing their investment activities while using resources efficiently to develop more assets (Stockhammer, 2010). This pertains to both the degree of investment risks and also the level of profitability. This can be done by applying financial indicators and also by assessing the risks and liabilities (Cicea & Hincu, 2009).

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increasing firm productivity and growth (Bishop & Burleton, 2009). Also, there are external legal and political institutions that affect the efficiency of corporate governance (Aguilera & Jackson et al, 2010).

Influential Determinants of the Financial System

The financial system is impacted by various factors such prudential regulation on micro and macro-levels (Eyzaquirre & Vinals, 2010) including consumer behavior and innovative initiatives (Bunea-Bontas et al 2009). There are several areas that influence the degree to which the financial system is efficient and attractive toward financial firms and their institutions. Before and during the crisis, poor regulation and practices became a detriment to these factors. Factors that hampered the US financial system during the crisis include:

 The asset and capital structure of the local and regional banks, especially those pertaining to real estate loans.

 The debt of small business owners, especially in relation to commercial real estate holdings.

 The debt of households resulting from home mortgages, student loans, and consumption-related debt.

 Sub-prime mortgage issues with resulting from poor contracts, poor lending standards and a high degree of home foreclosures (Kregel, 2008).

The Conceptual Model

This conceptual model is provided to show how linking firm performance with financial integration and along with variables associated with them can reveal specific areas of a value chain that need to have adjustments in order to minimize risks. The factors that make up the theoretical framework are asset management and degree of diversification (Bakay et al, 2011) comparative corporate governance (discussed later) and institutional integration (Aguilera & Jackson, 2010; Steil, 2009), systemic exposure and risk mitigation (Steil, 2009) and cross country effects of contagion (Rose, 2011). It’s created in an attempt to find the causes of the differences of firm performance and also to show which types of firms were more sensitive to the crisis in comparison to other firms. The left side of the model represents some of the specific components that would decrease firm performance during the crisis while the right side of the model represents what increases firm performance. There are two sides of contagion, with the upper left side of the model representing how poor institutional integration with varying degrees of value causes a decrease of money supply in the financial system. This can threaten a firms’ liquidity level, balance sheet protection and ultimately the organizational structure. The lower left side of the model deals with risks. These risks are increased when there’s poor management, especially involving hazardous decisions because ultimately that leads to stronger threats of exposure during a crisis. The right side of the model represents the possible characteristics necessary to achieve strong performance in spite of a crisis. It includes all of the dependent variables and independent variables along with the hypothesis because the whole goal is to identify to what extent these variables play a role in achieving stronger performance during a crisis. The variables will be discussed in the following chapter. The upper right quadrant seeks to identify how external factors such as institutional integration and financial openness can give firms more options to mitigate risks which could be very effective during a crisis. The lower right quadrant links institutional efficiency with risk mitigation, which in theory allows firms to diversify more accurately which could be a leading factor to causing strong firm performance even during a crisis. The next chapter follows the conceptual model while providing a more thorough insight on micro-economic factors, along with institutional pressure such as corporate governance can have a role on firm performance during economic downturns.

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Chapter 2: Firm Performance and the Crisis

The conceptual model designed is to provide some insight as to how to achieve stable and positive firm performance despite dealing with a financial crisis. Financial crises typically have three main stages, firstly are the initiation of the financial crisis, secondly are the banking crisis and thirdly are the debt deflation. The internal side of this model mainly uses components of the initiation of the crisis because the components such as financial institution performance, asset price fluctuations and moral hazards which create agency cost (Mishkin, 2011) all have direct or indirect implications on the firm’s equity. The latter stages won’t be covered that much because the time series to be applied doesn’t conduct a measurement long enough.

Bekaert et al (2010) provided similar research by examining how financial openness affects firm productivity, where for example some financial components such as investor behavior and liquidity growth can positively affect the financial system. These types of components are interactive with internal factors such as diversification and institutional efficiency because it involves changing liquidity liabilities and capital accounts which impact the total growth (Kiran, 2009). They’re interactive with external factors which involve financial liberalization and harmonization as they link mitigating risk with manager insight resulting from institutional efficiency, thereby reducing contagion stemming from lack of supply. Both of these factors will be discussed later as we examine how they’re influenced from institutions, firm diversification and financial integration on systemic and firm-specific levels during the 2008 crisis.

Firm Productivity

Though productivity is widely associated with the workforce and their ability to efficiently convert their resources into assets, in the financial industry it also relates to the supply and demand of capital from the financial system (Stockhammer, 2010). Some studies have shown that firms can be more productive because they’re able to allocation their resources more efficiently (Kiran, 2009) and can apply better methods to adapt to economic shocks. This helps them to adjust their operations to the cyclicality of their firm more appropriately (Batini et al, 2010). Bonfiglioli (2007) shows’ that firms can achieve a strong level of financial growth by increasing the total factor productivity and capital accumulation. Total factor productivity is composed of capital input (including investment input and resource input), labor input and technology input. Firms increase their value when their resources and assets are allocated more efficiently (Naciri, 2008) and as a result they should be able to counter contagion and minimize exposure to risk even during time of a crisis. But shortly before and during the crisis, banks were unable to cope with the challenges in the financial markets, they hampered the funding markets and in many cases there had to be changes made to the monetary policies. This included stricter regulation as well as localized and firm specific changes in requirements including diverse changes to policies based on firm specific financial information (Mishkin, 2011).

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the unity between their stakeholders. Managers with sufficient knowledge with technology can adjust to changes and solving issues faster while effectively organizing their tasks and as a result this can lead to another important channel of productivity (Bishop & Burleton, 2009) and can better identify ways to add value to their firm.

Risk Mitigation

The common assumption that diversification reduces a firms’ ability to mitigate risks during a systemic crisis will be reexamined. Notice that one possible unique feature with choosing these countries is that while their financial systems are closely interlinked, the American financial system is supposed to be highly linked to contagion. The American financial system is very diverse and diversity also supports environments that allow more flexibility and self-discipline in the banking industry. This allows managers to assess their exposure to operational risk when it’s systematic with their own measurement approach (Bunea-Bonta et al, 2008). Operational risk can have its origins from technology risks, business model risks and execution risks. Technology risks involve threats as a result of having a lack of competitiveness and uniqueness within a reasonable time period pertaining to the environmental market. Business model risks involve the threats related to lack of repetitive consumer behavior in terms of willingness to purchase again. Also the execution risks involve the threats relating to a firms inability to provide the services needed with their consumers within the firms capacity. In theory all of these risks are associated with the firms’ ability to operate efficiently and produce. Firm productivity can be used as a measurement of operational effectiveness (Ussahawanitchakit & Wangcharoendate, 2009).

Influential Factors on Firm Specific Indicators

Financial Harmonization and Diversification

Financial integration and firm diversification have a unique relationship, as some studies have pointed out that diversity in itself hampers financial integration especially in the banking sector because banks must adapt to all of the standards which aren’t always compatible to their own system. This includes adopting practices on a national level such as consumer culture and the preferences of foreign consumers, the incurrence of additional cost of banking services and products, the adaptation to foreign regulations and also adapting to foreign institutional practices. In most cases this interferes with governmental actions and in some cases diversification can lead to less supervision and regulation (Bunea-Bontas et al, 2009). Financial liberalization on a firm level, such as indices and corporate governance codes help foster this financial freedom (Agénor, 2003) while at the same time provide better ways for firms to produce the cost of their governance by allowing them to have an option to choose from.

Cross Country Integration

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influenced from legal and political institutions and can be used as a strong variable to measure social performance which in theory should have a major impact on firm performance, especially during a crisis.

Table 1

US Regulatory Standards

Standards and

Regulations

Original Agenda

How it was applied

The effects afterwards

Glass Steagall Act 1999

Lower abuse and risk

towards investors

Separates institutions

from investment banks,

commercial banks and

insurers

Boosted competition

with banks, securities

companies & insurance

companies

Commodity Futures

Modernization Act 2000

Use derivatives to add

value towards stocks,

bonds, national currency

and commodities

Protect banks against

loan defaults by

mitigating risk involving

derivatives

Protected against

financial lost

Sarbanes Oxley Act

2002

To increase corporate

stability and to minimize

corporate scandals

Increased accounting

standards and

requirements and

corporate responsibility

Costly for firm

structures but better

investor protection

Customized chart with concepts derived from www.isaca.org

The following table above shows the changes and the regulation by acts passed in the American financial system. With the American system being stricter than the Canadian system, monetary intervention in theory had positive effects on certain factors such as minimizing the contagion, stabilizing inflation, reducing volatility and reducing uncertainty. This was done so by increasing the sensitivity of market expectations which reduced the typical cost to build a positive reputation especially for banks (Geraats, 2005). Reavis (2009) contends that deregulation causes agency problems and panic in the financial system. When a large number of investors want to divest all at once, this exacerbates the crisis and fuels spread of contagion into other areas thereby causing a domino effect. Table 1 listed above also provides a brief overview of some of the changes in regulatory standards that in theory would impact large financial firms in the American financial system.

Financial and Market Risks

Financial risk hampers a managers ability to identify the best decisions regarding choices involving diversification (Amenc et al, 2011), moral-hazards (Berger & Bowman, 2009), integration (Rose, 2011) and volatility (Agénor, 2003). Short term and long term decisions impact may be altered during a crisis. Hillier et al (2008) shows how the duration of a project period is a key element in measuring risks, especially for decision-making on an individual basis. Though there are too many companies for this research to examine the individual level of risk, we’ll still note that firms have their own niches and market specifications in their industry. Broad risks have implications on firm specifications and thereby it becomes a necessity to examine risks on a systematic level.

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inequality, innovation patterns (Meyer, 2000) which affect performance in particular, the return on assets (ROA) and the return on equity (ROE) (Hillier et al 2010). As these variables define firm performance, ROE is highly internal as it’s heavily involved with the firms’ equity and balancing the finances on an internal level. In contrast the ROA is the best component to measure the effects of firm performance as it relates to external factors because with these firms several of the assets are highly associated with the global market. The ROA is determined by dividing the total net income (or loss) by the total assets and this ratio provides a clear picture of how efficient the firms’ assets are being used to generate the level of earnings needed.

Financial System

For many firms, accounting standards such as the GAAP may be beneficial to understand the current value of assets and risks on an immediate short-term level. However for other firms that involve more risky decisions which have long term implications, it’s necessary to have other methods such as a counter-risk balance sheet statement that focus more on long-term opportunities and issues that theaten finances. When financial standards are unified they create more integration as financial systems create diversified characteristics globally (McLeay et al, 1999) and when risk are involved, in theory this makes the spread of contagion more permissible (Resnick, 2007) which hampers protection and monitoring on broad levels. Regulatory agencies are often needed to assist firms with managing systematic risks (Reaves, 2009) and to also reduce agency problems (Amman et al, 2010) and to bring more value to the financial system. The size of the firm often plays a role in which options are available for getting their capital, whether they have the ability to raise it themselves or whether they have to issue debt instead. The financial system can play a role in effecting the minimum requirements to raise capital and it’s influenced by the tax rate and capital allocation as well as the legal frameworks (Ayadi et al, 2010). The financial system also fosters regulations and policies that affect the structures of firms. Firms that are widely held with low ownership concentration and poor investor protection help facilitate an environment of a high liquidity market and high anti-takeover policies. In high liquidity markets shareholders can sell their equity stakes quicker but in lower liquidity markets shareholders can’t sell them as fast which can hinder them especially during times of a crisis. Hopefully this study will help responsible firms attract wiser investors on a wide scale level. Yet, does this responsibility which stems from corporate governance bring more efficiency to the financial system by forcing the agents to act more responsible? It is widely perceived that the Anglo-Saxon type financial system is the most effective type of system because it focuses on strengthening and balancing the capital market while influencing positive social interactions with financial institutions and investors along with pressuring corporate structures to be reshaped with more transparency. This should be the best method to achieve success and create a competitive edge in the global market (Guellen, 2006). Competition and innovation are always vital for financial firms in the banking sector and financial system because they enhance them in two main ways: (1) it pressures financial firms to create more added values to their services and products and building (or coordinating) them with higher technology in order to maintain positive returns: (2) it helps facilitate a system where most efficient producers in the market are the external variables and these factors reap the benefits on returns and therefore develop a high proportion of the market share and comparative advantage (Bishop & Burleton, 2009). Managerial Expertise

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sector (Bonfliglioli, 2007). Strong managerial expertise is coordinated with financial integration, risk mitigation and their ability to obtain and share knowledge (Ussahawanitchakit & Wangcharoendate, 2009) which is all useful for utilizing firms’ assets efficiently. That’s why debt-to-assets is used to help show whether or not if bank debt has a strong negative impact on the ROA. This variable pertains to the ROA but it could also pertain to the ROE based on the fact that high levels of debt could show a higher degree of risks and poor investor perceptions of the firm (Angelon & Wolff, 2012). Effective managers talented in understanding the firms’ specified niche and valuable characteristics as they’re able to coordinate this to the firm’s own agenda within their industry (Nimalathanson, 2008). These skills are particularly useful on the internal side of the model and these characteristics include effectiveness and efficiency of the firms operations, firm reliability on financial reporting (as it relates to investment cash flows) and their compliance with their regulations. For managers this is especially the case if they have designated corporate codes or principles for their own firm (KPMG, 1995).

Homogeniety and Heterogeniety Factors between American and Canadian Firms

Both Canadian and American financial systems are impacted by asset-dependent trends and fluctuations, where a typical firms’ income and their financial needs fluctuate and affect their stocks. The stocks are used by these firms as financial equity and minimize the necessity of borrowing (Lavoie, 2005). Though these two financial systems are very similar, Lavoie (2005) argues that there are distinct differences within these systems including the complexity of the US institutions, the higher transparency and zero-reserve requirements or low reserve requirements in the Canadian system (which have led it to be more feasible with their firms as a result of their monetary policy). This study argues that in theory, several institutions create policies that would favor having the capital supply remain internally in the financial system, which could minimize financial restraints during a crisis. This is typically done by simultaneously monitoring the control cost of holding reserves versus exercising advances, thereby maintaining stability in the liquidity market. Perhaps this plays a role in Canadian firms allegedly having a higher success rate in comparison to US firms as their policy would be less restrictive on a firm level but somewhat more efficient on the national level by emphasizing protecting capital on a broad level.

Internal Factors

Managerial Practices and Quantitative Implications

Banks typically have policies where they know who they could lend to and which customers should be considered as their most valuable, how much can they afford to lose from a borrowers default or forbearance and also how much are their risks for loaning to others. This helps them increase their ROA (Alkhatib, 2012). During previous times shortly before the crisis many banks decided not to key in their assets in the book but to rather hold on them until they felt that the value would increase later in the future (Reavis, 2009). In theory this proved to be detrimental to performance as this type of concealment of finances created a moral hazard (Meyer, 2000) and reduced accurate forecasts.

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to build an organizational structure. With this they can better coordinate with a counterpart to work more and to produce more efficiently. A manager of firm a can either short hedge by selling a futures contract in order to buy a specific asset that may prove to add value or have great potential in the long run. In contrast, they can long hedge a contract by buying a future contract to reduce the risk and having a transaction confirmed in the future at a fixed sales price for the assets involved (Hiller et al 2010). I argue that this pertains especially to large non-bank financial firms because it reduces their risk of exposure and therefore they can better handle their debt and maintain their competitive edge internationally through skilled diversification (Aybar & Gonenc, 2006). Banks on the other hand face risks that stem directly from exogenic factors such as unfavorable rate changes, changes in the monetary policy and external (financial) systematic changes (Geraats, 2012). Banks influence capital within an industry by raising or lowering their lending standards and when they increase lending standards, firm’s capital cost become more heterogeneous (Batini et al, 2010). As a result they must allocate their capital based upon their cost-opportunity tradeoffs. When this occurs, cost opportunity tradeoffs go from internal to external because the firms first use their capital for internal purposes and then transfer it over to the ROA side of the model to try to maintain more external growth. We argue that managerial practices and internal firm activities focus on utilizing resources effectively to obtain positive synergies and on systematical levels effects international activities through isomorphism. Market returns during a crisis normally creates negative synergies and imbalanced trade-offs in the market which lead to lower profits, reduced stakeholder wealth and a decline in investments (Bellavance et al, 2008).

Adding value is associated with risk mitigation, institutional efficiency and diversification which are key factors that draw investors and can boost the ROE value as it can be influenced by their decisions on how to budget capital. This includes understanding how managers are able to detect and minimize unwanted features on the services that they offer to their consumers and strengthen their services. Also, to identify ways to provide the same level of productivity or better compared to their competitors and doing so at a lower cost. Being innovative also plays a role in building more cutting edge products that create new specifications for market niches (Hillier et al, 2010) and increase asset value which increase liquidity (Pollin, 2008). Also, effective budget structures focus on creating growth opportunities and operating activities could provide residual income during the crisis and counter threats. Residual income and profit maximization can best be achieved by having accounting standards based on precise transactions that would show marginal revenues, marginal profit, marginal cost and opportunity cost. Budget structures have mechanisms which include the structural development of revenues, productivity and capital activity integrated in a symmetrical balance sheet and this can be done through economic value activities (EVA) and activity based cost (ABC) budgeting methods. This help firms save cost and the the sufficiency their technology can play a role to saving cost in this area (Anctil et al, 1997; Mondria & Wu, 2011).

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Table 2 Major Financial Institutions: Sources and Uses of Funds

Referred from Siklos 2001

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Davis and Stone (2004) argue how financial systems go through four stages as listed below to develop and maintain success (See Table 3). Even though market oriented systems such as the Canadian and American system may be considered stronger than based bank system, this may not always be beneficial in times of a crisis. Mainly because they don’t have the same type of legal protection in comparison to bank oriented systems and there can be occasions where they have many industries that are dependent on external finance (in contrast to bank based systems).

Table 3: Stages of Financial System

1. Corporate sources of finances are

mainly internal (internal)

2. Banks increases as a result of

information symmetry on collection

efficiencies

3. Equity issuances increase as a result

of more diversity

4. Bonds increase as a result of a

decreasing cost of information

When financial services companies work efficiently they work as an effective intermediary between various parties and they should provide more transparency in the financial system. Financial transparency shows that while issues involving disinformation with financial assets and liabilities increase agency risks, these issues can be minimized when transparency is enforced. Therefore firms can still maintain their ability to increase productivity and produce efficiently with their operations (Backus et al, 2005) despite the agency cost. The risks from agency cost create costly obligations that involve the necessity to monitor managers and the necessary stakeholders for their protection. When this cost is reduced, by default it should also reduce contagion. Investor opportunity, when pertaining to portfolio diversification is a key factor to increasing the need for more open capital markets, providing quicker rates of return and preventing high levels of capital account imbalances which can pose sudden risk of exposure (Agénor, 2003).

Variables

Considering the contents in the conceptual model, use the ROA as the independent variable to account for the external factors and the ROE as the independent variable to account for the internal factors. The variables listed below in Table 4 represent the same variables in the conceptual model in the previous chapter. It’s important to note that in the following sections, the variables were combined where necessary. For example, in the test models, the return on assets for Canadian banks would be written as ROACB, combining ROA and with CB.

Table 4

List of Variables Canadian Banks CB American Banks AB Canadian Non-Bank Financial Firms CF American Non-Bank Financial Firms AF Return on

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Management Income)/(Total

Assets) which could be considered their potential earnings; different from that asset turnover which can use net

sales instead

chosen as the numerator because it measures the companies income based upon

current operations, Operating

Profit Margin OPM = Income)/(Revenues) (Operating

measures the profitability of a firm and provides an insight of how profitable it is in comparison with other firms in the same

industry Debt-to-Asset

Ratio DA = (Total Debt)/(Total Asset)

measures how much debt a company uses to cover its assets, which typically affects their ability to borrow capital because it

influences their financial flexibility Investment

Cash Flows ICF = varies by firms components

Net Cash

Flows NCF = varies by firms components; commonly listed as (Net Income)+(Non-cash expenses) or (OCF)+(FCF)-(ICF) Return on

Equity ROE = (Net Income after tax)/(Shareholder Equity) Operation

Efficiency OE = (Total Operating Expense)/(Net Interest Income) Net Profit

Margin NPM = (Net Income)/(Revenues)

Debt-to-Equity

Ratio DE = (Total Debt)/(Total Common Equity)

Operation

Cash Flows OCF = varies by firms components

Financial Cash

Flows ICF = varies by firms components

Total Common Shareholders

Equity TE = (Total Stockholders Equity)-(Preferred Stockholders Equity)

The operating profit margin (OPM) was added to the ROA as a primary independent variable because it’s associated with comparing profitability with other firms and is comprised of the external factors. This association includes variable cost, interest expense and gross revenues which are affected by external factors (Purdue, 2010). The OPM equals the operating income divided by the revenue and is useful for determining how successful a firm is in terms of profit in comparison to other similar firms within the same industry. The net profit margin as explained in the previous section is mainly used a replacement variable for operational efficiency for non-bank financial firms.

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Financial performance is associated with certain components from their accounting data, such as the ROA, ROE and TE, which are all characteristics of their performance as it relates to contagion (Bellavance et al, 2008). This method will be chosen because Chan et al (2010) used it in a similar research related firm performance and the advantages and disadvantages of entering foreign markets through acquisitions.

The total debt as a percentage of common equity (DE) is a variable that’s used because it helps provides a strong insight of investments and inventory. It’s important to minimize certain problems that stem from a financial crisis that are associated with a decrease in investments and inventory because managers would have had the ability to finance their debt more effectively. The DE variable is chosen pertaining to common equity shareholders instead of preferred equity shareholders because common equity shareholders direct absorb risk and loss in the firms. Companies with high liquidity may be able to cover their expenses stronger than those with low liquidity during periods of shock. Also companies that are linked with government supported industries most likely receive bonds and government subsidies which would be help cover their expenses (Davis & Stone, 2001).

The debt capacity is invisible to the model but debt levels are still useful for examining the effects of internal managerial decision making (Owens & Temesvary, 2012) and also how severe the level of risks impact the equity (Cardinal et al, 2000; Adrian & Shin, 2008). They’re highly associated with the independent variables associated with the ROE. Furthermore debt can be used for key factors in showing how much leverage a firm can handle (Adrian & Shin, 2008; Bullard et al, 2009).

Net cash flow is part of a set of variables used in this model that link diversification to both operational efficiency and asset management. Previous research has shown that net cash flows are vital to bringing stronger control to cash balances and more visibility to the financial value chain which improves financial forecasts and provide a better optimization of cash management (SAP Executive Insight, 2009; Cardinal, et al 2000; Amenc, et al 2010). Net Cash flows are subdivided into three different categories, operating cash flows, investment cash flows and financial cash flows, where investment cash flows pertain to the managerial practices and asset management while the other two pertain to operational efficiency and diversification. In theory cash flows would maintain their stability during the crisis because under good governance firms could retain their cash at ease in comparison to poor governance. This would lead to higher interest rate or level of dividends which would play a stronger role in the firms profit (Amman et al, 2010).

Since previous studies show that Canadian financial system is more liberalized than the American financial system, we should find that the firms labor market and capital markets are more flexible which would allow them to have greater access to information, leading them to allocate their resources more efficiently (Cardinal et al, 2010; Saldías, 2011). The debt to asset (DA) ratio is an independent variable useful for determining the firms’ capacity to finance asset through their debt. If a firm has a high DE ratio such as 1 or higher that means that the firm is highly leveraged which would be dangerous during a crisis

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If the models independent variables are significant to influencing the firm performance and can show how sensitive performance is to external factors (such as financial liberalization) and internal factors (such as diversification and institutional efficiency). Perhaps it would provide us an illustration on what it would take for the factors on the right side of the model associated with strong performance are more influential to performance. If not, then it should at least show how the independent variables (financial indicators) to lead the dependent variables (representing firm performance) lead to a strong performance, shifting the firm performance further to the right.

Hypothesis

The first hypothesis (H1) is associated with the external factors and both types of corresponding variables that are

located on the upper side of the model. The null and alternative hypotheses are stated below in Table 5.

Table 5

List of Hypothesis

H0, there exist an insignificant impact with the asset management and operating profit margin on financial performance (in terms of return on assets) during the series.

H1, there exist a significant impact with the asset management and operating profit margin on financial performance (in terms of return on assets) during the series.

The second pair of hypothesis follows as:

2H0, there exist an insignificant impact with the operational efficiency and net profit margin on financial performance (in terms of return on equity) during the series.

2H1, there exist a significant impact with the operational efficiency and net profit margin on financial performance (in terms of return on equity) during the series

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Chapter 3: Methodology

Time Series

Previous studies that are similar to this one such as Alkhatib (2012) and Demirguc-Kunt et al (2010) used research that is categorized under a time-series approach. The following sections will use a set of time series tables that provide a more in-depth illustration of the variables by showing their trends and how they fluctuated shortly before, during and after the financial crisis. Using Datastream and Excel Macros, we’re able to test the data and develop a thorough understanding of its implications on the model and on managerial principles. The following section will also show the calculations of the descriptive statistics, correlation matrixes, model summaries and the correlation coefficients for both the dependent and independent variables. The correlations for the variables in these models r are defined by what’s in table 6 and the level of significance for these variables are defined in table 7.

This study is conducted over the years that span from 2006 to 2010, because in the US and Canada the peak of the crisis occurred in 2008 and this time span is chosen in to show the type of fluctuations that occurred during the different stages of the crisis. In the equation, yit = ai +bxit + βxit + …. + eit, yit which is derived from Schmidheiny (2012 ). The yit represents the dependent variables, where a = the intercept (constant unstandardized beta), t = time interval, X represents the independent variables while b = first independent variable and β represents the second and remaining independent variable and e represents the standard error. This process pertains to all the models in the study. This equation best supports the variables in the model because several of these components could best be categorized under firm-specific micro-panels according to Eberhardt (2011). This study examines if these independent variables are highly sensitive to both contagion and integration as it performance. For example, if the ICF variable is exogenous to the ROA in this model as a result of being highly associated with how changes in the external market can influence investor decisions, then the level of changes should show some degree of changes to the ROA as a result of the change.

Table 6

Levels of strength measuring for Betas and Univariate Correlations

Value of r =

Level of Strength

Value of r =

Level of Strength

-1 to -0.8

Very Strong, Negative

0.0 to 0.2

Very weak , Positive

-0.8 to -0.6

Strong, Negative

0.2 to 0.4

Weak, Positive

-0.6 to -0.4

Medium Negative

0.4 to 0.6

Medium, Positive

-0.4 to -0.2

weak, Negative

0.6 to 0.8

Strong, Positive

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Table 7

Measurements for Validity on Alternative Hypothesis

P value =

Level of Significance

0.00 to 0.01

Very Strong level of significance

0.01 to 0.05

Strong level of significance

0.05 to 0.10

Medium level of significance

The coefficients for the ROA are set in 3 levels to account for the internal factors and internal factors. Based upon previous research it’s reasonable to set the level of significance at 0.01, 0.05 and 0.10 respectively. At any time the p-value falls at or below the number shows the strength of the level of significance as strong, somewhat strong or medium. These measurements are to be used to show whether the values should be accepted or rejected under the hypothesis.

Financial service firms are separated from banking companies because different changes in the financial system can affect them differently than from banks. Banks act as key roles in being mediators in the financial system, which includes using a variety of financial services to work as linkages between the banks and companies as well as institutional investors and corporate investors (Murdoch, 2006). In contrast, financial companies often act as protective monitors that bring more transparency to the financial system and make performance indicators more accurate and reliable. This becomes effective in determining where contagion is at an early stage. Despite having a small sample of only 60 total firms, these firms are chosen because they are within the top largest firms of their countries. The model consists of 14 of the largest Canadian Banks and American Banks a piece and 16 of the largest Canadian non-bank financial firms and 16 American non-bank financial firms.

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financial harmonization on the financial systems and the isomorphic pressures on institutions affect all four different types of firms with some impacts stronger than others. Asset management can tell us that during the financial crisis, there is (or is not) a strong relationship between the firm performance and strong managerial expertise. It can do this more so than during times of a crisis and the assumption would be that firm performance and pressure from external financial governance played a stronger role in hampering efficient managerial activities with their usages of assets. There also could be some implications that are internal with asset management, such as portfolio diversification, protecting and monitoring covenants when necessary and the ability to maintain stable long-term relationships with their clients (Geraats, 2012). Yet the asset management variable is still suitable for this area of the model as a measurement because the crisis was largely a result of declining asset prices along with the failure of various firms and institutions which had contagious affects (Geraats, 2012). The model shows that these asset management variables would be best suitable to measure the effects of ROA with external factors impacting firm performance. The panel regression test shows how the ROA are affected by the changes from fluctuations of asset management. The variables included need to be examined and tested in the hypothesis to see if there’s a correlation with firm performance (return on equity) and productivity growth (return on assets) (Davis & Stone, 2004; Bonfiglioli, 2007). These variables are used best to fulfill the other variables which could have been used such as return on foreign sales, because they’re still influential enough to have a strong prediction of the outcomes of the ROE (Dissanayake, 2012).

It will be necessary to see what their expenses were during the crisis and also whether or not their governments provided them subsidies to help cover expenses. This will be taken into account when we run the test and different control variables for the hypothesis. The TE variable is used to examine a firms’ ability to cover a high degree of expenses, return on capital providers and equity holders (Ioannou & Serafeinn, 2010).

Chapter 4: Results

This chapter will show the activity for all of the variables and thereby reveal how sensitive they were to the changes in the environment. While every variable has their own components that could affect their sensitivity to the crisis, it’s important to examine them individually and then put them in the model. By doing so we can get a better understanding of what it would take to bring the dependent variables closer to the right side of the model to provide a stronger performance during a crisis. The subsections will show a Pearson correlation on a univariate level. This is done to show how strong or weak each independent variable has on each other only on an individual basis and how significant their impact with would be on the dependent variable on an individual basis. Afterwards there will be a more detailed explanation of the regression analysis because this is where we find out if the hypotheses are rejected Then there will be a set of limitations to follow.

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Fluctuations and Trends of Variables

Figure 1 shows that the ROA was somewhat volatile for both Canadian Banks and Canadian non-bank financial service firms. This most likely means that these two are strongly impacted by the crisis and are highly sensitive to the market. At the same time the American banks and American non-bank financial firms showed a more stable trend, but both ended 2010 lower than when the series begin in 2006. Also, all types of firms ended the series lower than they began except for the Canadian Banks.

Figure 1

The External Factors on Performance as a Measurement of Return on Assets

Figure 2 shows that the AM was very volatile for the AM American non-bank financial firms (AMAF) but for all remaining sectors it was more stable. The AMAF showed a slight increase in 2007 followed by a major decrease in 2008 and a major increase almost to the same level that immediately followed. The AM for American banks show a relatively stable but slight decreasing trend throughout the time series, followed by a slight increase at the end of 2010. The AM for American non-bank financial firms show a steady decrease throughout the entire period. The AM for Canadian banks had a steady decrease just before the crisis followed by a steeper decrease during the crisis but then rose strongly right afterwards. What’s unique about the AM variable is that for both American non-bank financial firms and Canadian non-bank financial services firms, they don’t mimic each other while Canadian banks have very similar trends with each other. In the table, both showed steady to gradual decrease heading into the crisis and during the crisis. While Canadian banks were more volatile in this aspect, they still ended the series with a strong increase. This could indicate that their ability to manage their assets as it is strongly influenced by external factors provides a strong enough impact to affect these variables in general ways. For example, fewer restrictions in the financial system could provide more optimization for asset allocation which would lead to a higher return on asset management in comparison to the American firms which have stricture rules.

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Figure 2

Asset Management (listed as the first variable for the hypothesis)

Figure 3 shows the operating profit margin (OPM) for both the Canadian banks and for Canadian non-bank financial firms, with strong decreases in 2007 and 2009 respectively followed by resilient years afterwards. The American firms in contrast had a relatively stable trend, with their banks having a decrease from 21.9% to 5.2% during the crisis, before rebounding to 18.5 closer to the levels in 2006. American non-bank financial firms were the most stable with the OPM rates maintaining a range of 24-29% during the series. During the end of the series both the Canadian bank firms and non-bank firms both had stronger margins than the American firms with Canadian non-bank financial firms having a very resilient year for 2010 ending at a OPM rate at almost 60%.

Figure 3

Operating Profit Margin (listed as the second hypothesis variable for firm performance)

Figure 4 shows that the both American banks and American non-bank financial firms have a much higher debt to asset ratio and in some cases the range is twice as high as the Canadian firms. American banks show a slight increase trend up until the peak of the crisis followed by a somewhat sharp decrease, followed by a much milder decrease. The American non-bank financial firms show a trend that’s almost the opposite of the American banks firms. A similar trend is for Canadian banks and Canadian non-bank financial firms. Both Canadian Banks and Canadian non-banks financial firms have trends that are nearly identical for the American firms, however their debt to

2006 2007 2008 2009 2010 AMCB 3.86% 1.61% -0.33% -3.96% -0.19% AMAB 1.87% 1.58% 0.28% 0.29% 1.07% AMCF 8.81% 10.63% -7.55% 10.99% 11.35% AMAF 10.85% 7.48% 6.33% 4.36% 4.22% -10.00% -5.00% 0.00% 5.00% 10.00% 15.00%

A

M

R

ati

o

Asset Management

2006 2007 2008 2009 2010 OPMCB 8.11% -68.56% 1.71% 21.25% 29.41% OPMAB 25.34% 21.91% 5.21% 5.23% 18.52% OPMCF 27.12% 25.50% 28.57% -49.77% 59.86% OPMAF 28.69% 25.07% 24.16% 24.30% 28.49% -80.00% -60.00% -40.00% -20.00%0.00% 20.00% 40.00% 60.00% 80.00% OP M as a %

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asset ratio’s are much lower. Towards the end of the series, the Canadian banks debt to asset ratio is lower than the Canadian non-bank financial firms’ debt to asset ratio which is in contrast to the beginning of the series. Though the American firms have a similar trend that matches the Canadian firms’ trends, the American banks end the series with a debt to asset ratio slightly lower than the American non-bank financial firms. Perhaps this shows that while the Canadian banks may have had a stronger impact of exposure from the crisis, their methods for managing their assets while controlling their debt were very effective which led to a strong reduction of debt after the crisis.

Figure 4

Total Debt to Assets (as an independent variable for Return on Assets)

Figure 5 shows that investment cash flows (ICF) had similar trends throughout the whole time series with a strong decrease in 2009 mostly likely shows the aftermath of exposure from the 2008 peak of the crisis. The ICF for Canadian non-bank financial firms remained very low throughout the whole series with an average of $56 million for the year 2009. However this segment of firms never fell below 0, unlike both types of American firms in 2009 which both saw ICF go well below 0.

Figure 5 Investment Cash Flows (as an independent variable for Return on Assets)

2006 2007 2008 2009 2010 DACB 15.05 13.93 14.20 7.45 6.71 DAAB 23.62 27.13 27.69 22.58 21.21 DACF 13.09 12.43 14.14 18.45 11.90 DAAF 27.00 26.31 26.34 28.35 22.26 5.00 10.00 15.00 20.00 25.00 30.00 D A as a p e rc e n tage

Total Debt to Assets

2006 2007 2008 2009 2010 ICFCB 10,796,856 11,632,203 12,461,994 4,120,193 10,242,846 ICFAB 26,702,981 28,245,591 32,901,351 (16,541,821) (4,365,734) ICFCF 197,832 328,048 197,486 56,136 78,358 ICFAF 3,600,660 6,902,504 8,522,751 (1,557,905) 3,143,635 (20,000,000) (10,000,000) 0 10,000,000 20,000,000 30,000,000 40,000,000 ICF in t er m s of $1, 00

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Figure 6 shows that despite the challenges that American banks faced during the crisis, this segment for firms fared the best in terms of net cash flows (NCF), ending the series with a remarkable average amount of $6.2 billion following a $1 billion deficit. American non-bank financial service firms began the series with an average of $132 million deficit before rising to $1.67 billion in 2008. However this was followed by a very sharp decrease of over $3 billion at the end of the series. In theory, my argument would be that there was most likely major governmental assistance that went to banks but they weren’t available for the American non-bank financial service firms. This would explain why the American banks would have such a sharp increase following a sharp decline right after the crisis in 2009. Furthermore, the Canadian firms NCF remained steady during the crisis with very little fluctuations. In this this study it’s unclear if the NCF will be directly equal with the other cash flow components that normally make up the NCF because all of this data is taken directly from Datastream and there may have been some retroactive adjustments. Furthermore, this study has its adjustments in some areas to make the models more relevant but these adjustments can off-set the original numbers for any addition test directly associated with these numbers.

Figure 6

Net Cash Flows (as an independent variable for Return on Assets)

Figure 7 shows that the ROE was again very volatile for Canadian Banks with a very sharp drop in 2008 followed by a sharp increase and decrease afterwards, but not so volatile for American Banks. American banks had sharp decreases in 2008 followed by two gradual years of increases. Canadian non-bank financial firms showed some volatility for the year along with a sharp decrease in the year 2008, which is a contrast in comparison to the American non-bank financial firms as these firms had the least amount of volatility.

2006 2007 2008 2009 2010 NCFCB $308,939 $256,206 $(263,409) $857,694 $1,922 NCFAB $1,680,776 $418,295 $1,352,299 $(1,070,193) $6,260,380 NCFCF $40,296 $30,496 $29,628 $21,927 $34,564 NCFAF $(132,611) $(128,914) $1,665,600 $3,607,449 $(3,023,559) $(4,000,000) $(2,000,000) $2,000,000 $4,000,000 $6,000,000 $8,000,000 N CF in t e rm s o f $1, 000

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Figure 7

The Internal Factors on Performance as a Measurement of Return on Equity

Figure 8 shows how the OE for both Canadian and American firms experienced a relatively increasing trend before and during the crisis. However for both firms the OE did decrease in the final period of the series. This may be the result of a lag between the peak time of the crisis and the time that the crisis began to affect the firms’ level of efficiency. Furthermore, it shows how the Canadian level of OE was much greater than the American level and just like in many other figures the levels appeared more volatile as there was a sudden sharp decreasing trend in 2010. Figure 8

Operation Efficiency (listed as the first variable for the hypothesis pertaining to the ROE)

Table 9 shows that for the net profit margin (NPM) all firms to some degree had a decline followed by resilience during the series. In contrast from several other tables, this table shows that the Canadian Banks and Canadian non-bank financial firms fluctuated strongly along with a sharp decline during and shortly after the peak of the crisis. This is followed by a very strong increase in the NPM afterwards. What’s unique with this table is that it clearly shows how both types of Canadian firms had a higher NPM in comparison to the US firms and during the crisis, their NPM fell much lower than the American firms NPM. This shows that their ability to control prices and reduce risk was

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minimized at a stronger degree in comparison to the US firms. However, shortly after the crisis, the Canadian firms began to improve and once again they were able to rebound above the level of the American firms. This table shows that not only were these firms very resilient in the OE variable but also that despite their high level of exposure, their strategies for overcoming this contagion were very affective and successful for generating income. Notice how just like in several other tables and models Canadian firms show more volatility than in US firms and also they’re able to rebound faster than the US firms. Both types of American firms were relatively stable but they still ended the series with a net decrease and they both finished much lower than Canada’s NPM. Apparently the effects of the crisis hit the banks first as their declines occur the heaviest in 2008 before rising again. The trend is very similar for the non-bank financial service firms where there drop occurs in 2009.

Figure 9

Net Profit Margin (listed as the second variable for the hypothesis pertaining to the ROE)

Figure 10 shows that the total debt as a percentage of common equity (DE) decreased strongly for the Canadian banks but fluctuated lightly afterwards and ended the series with a relatively high level at 204%. Both types of Canadian firms showed slight increases in debt in the year proceeding the crisis followed by a gradual decrease shortly afterwards. The American banks DE variable fluctuated but stayed in a range of 220% to 397% representing the lowest rate and the final year of the series. The Canadian non-bank financial firms had a relatively low rate of DE in comparison to the other 3 types of firms, perhaps indicating that these institutions have greater access to capital or can achieve greater ways of obtaining financing without relying on debt to finance their operations. American non-bank financial firms in contrary to the Canadian non-non-bank financial firms had a very stable DE ratio throughout the series which fluctuated from 391% in 2006 to 404% in 2010. What’s unique about this is that unlike the Canadian non-bank financial firms, the American non-bank financial firms had a higher DE ratio then the American banks which show a stark contrast of how dependent the two types of firms (American non-bank firms and Canadian non-bank firms) rely on debt to cover operations involving equity. There are two figures that show the adjusted rates because one of the banks had a very strong negative debt to equity ratio which altered the series representing 2008. This table is listed in Appendix B along with the other tables.

2006 2007 2008 2009 2010 NPMCB 64.43% 41.67% -4.36% 43.53% 47.12% NPMAB 18.28% 13.67% -3.13% 5.45% 11.49% NPMCF 29.05% 21.60% 20.16% -43.47% 39.81% NPMAF 21.01% 16.99% 10.09% 6.29% 16.72% -60.00% -40.00% -20.00% 0.00% 20.00% 40.00% 60.00% 80.00% N e t Pr o fi t M ar gi n n as

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Figure 10

Debt to Equity (as an independent variable of Return on Equity)

Figure 11 shows that the operating cash flows (OCF) fluctuated on a relatively independent basis with different trends for each type of firm. The OCF variables for American banks were much more volatile than the other three types of firms. The OCF for both types of American firms rose during the peak of the crisis (2008), but for the American non-bank financial firms there was a dip in 2009 followed by an increase right afterwards. Also, the Canadian non-bank financial service firms saw a relatively low average OCF throughout this series fluctuating from $113 million in 2005 to a high of $181 million in 2010. These low levels seem to have been the case for Canadian non-bank financial firms too.

Figure 11

Operating Cash Flows (as an independent variable for Return on Equity)

Figure 12 shows that financial cash flows (or commonly known as free-cash-flows, FCF) for American banks was very volatile during the series with a strong decrease following the peak of the crisis. Then afterwards there was a

2006 2007 2008 2009 2010 TECB 2261.15% 498.94% -1224.77% 223.62% 204.55% TEAB 242.44% 311.06% 397.15% 253.39% 220.62% TECF 71.92% 47.55% 48.69% 108.56% 80.70% TEAF 391.34% 453.55% 485.61% 430.07% 404.27% -1500.00% -1000.00%-500.00% 0.00% 500.00% 1000.00% 1500.00% 2000.00% 2500.00%

TE

as

a

%

Total Debt to Common Equity (adjusted)

2006 2007 2008 2009 2010 OCFCB $(2,542,447) $1,459,289 $4,006,062 $4,233,239 $(457,057) OCFAB $(1,960,369) $(9,653,855) $10,635,369 $24,249,725 $11,249,203 OCFCF $113,117 $177,576 $143,018 $155,331 $181,683 OCFAF $(2,359,977) $865,142 $5,599,252 $(2,958,663) $4,115,447 $(15,000,000) $(10,000,000) $(5,000,000) $5,000,000 $10,000,000 $15,000,000 $20,000,000 $25,000,000 $30,000,000 OCF in t e m rs o f $1, 000

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would be the result of investors panicking and reducing their investments (Huang, 2002). As a result, this would lead to a sharp decline in cash flows coming from debt, equity and any of the other several components of securities. The remaining 3 types of firms in comparison to the American banks fluctuated but to a much more minimal degree. All four types of firms show a decrease that let their cash flows to be negative in the year 2009, but they all showed signs of resiliency in the final year of the series. The Canadian banks were the only firms that ended the series with positive financial cash flows, perhaps showing a great level of trust with their investors.

Figure 12

Financial Cash Flows (as an independent variable for Return on Equity)

Figure 13 shows that all types of firms had had increase of total common equity (TE). The American banks have a very large share TE throughout the series, most likely because of the size of the banks. They had a slight increase followed by a slight decrease during the peak of the crisis. But afterwards the data shows that these banks then had two periods of sharp increase in comparison to three other types of firms. Throughout the series there was only a decrease in 2009 (the year following the peak of the crisis) and this was for both American and Canadian banks, while all firms on all other occasions experienced an increase in the TE variable. It’s hard to determine in this study why this is the case, but there could be some reasons based upon other studies. Demirguc-Kunt et al, (2010) provides an explanation showing how a bank’s size and quality of capital can attract investors so in theory this could lead to a higher total common equity amount even in terms of a crisis. Furthermore, this study showed that the relationship between stockholders return on investments and firm capital can be stronger depending on how a firm measures its capital. For example, a leverage ratio measurement would most likely be stronger than a risk-adjusted capital ratio measurement.

Figure 13

Total Equity (as an independent variable of Return on Equity)

2006 2007 2008 2009 2010 FCFCB $13,595,509 $9,909,505 $9,313,627 $(111,124) $11,414,054 FCFAB $29,081,645 $39,251,746 $21,195,788 $(34,531,166) $(17,217,308) FCFCF $106,819 $194,108 $59,671 $(61,160) $(39,647) FCFAF $5,836,382 $7,696,236 $6,569,288 $(1,670,063) $(519,721) $(40,000,000) $(20,000,000) $20,000,000 $40,000,000 $60,000,000 FCF i n t e rm s o f $1, 000

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Correlation and Regression Analysis

In reference to the Canadian Banks ROA in Model 1, the equation is as follows: ROACB = Constant (3.1) + AM(65.59) + OPM(-0.0) + NCF(-0.0) + ICF(-0.0) + DA(.03) + e

The univeriate correlation in appendix three shows that on an individual basis, the ROACB had a positive medium correlation at a significant level with the AM variable having an r value equal to 0.48. However, with the exception of the ICF variable, the findings for all other variables were weak and all other remaining variable correlations with the ROACB were very weak as well.

The regression analysis test of the ROA for Canadian Banks can explain 37.3% of the ROACB as an average. There’s a medium positive correlation with an r value equal to 0.475 with AM, with a strong level of significance showing support for rejecting the null hypothesis. However, the cash flows from investment activities has a very weak negative correlation with the ROACB, but a level of significance would be strong enough to reject the null hypothesis if this were to be considered a main variable along with the OE variable. For every 1 unit increase of the AM variable (which is denominated as $1,000 per unit equal at 1 (nominal)%), the ROA variable should increase by $65,590. So for example, if the AM increases by half a percent, or $500 in nominal terms, then this would lead to a $38,750 (65.59/2 = 38.75) per $500 increase of the ROA just as $1,000 is the core number denominated from the data. One of the Canadian Banks, Canada Imperial had total assets estimated at $303 billion in 2006 with a return on assets at a rate of 1.02 which equals $3.09 billion (nominally). The AM ratio of this kind of situation would lead to an increase of the $15.5 million (core number in operating income) which is equal to (0.005) * (3.09 billion). The 15.5 nominal rates would be divided into 2 (because of the half percent rate) which would lead to a rate of $7.725 million. This would coincide with the nominal rate 1.025, adding 0.005 to the original rate of 1.02. The data for the remaining variables show that the other control variables don’t have a significant relationship with the ROACB as their p-values are all greater than 0.1. As a result, the null hypothesis is accepted and the alternative hypothesis is rejected because there’s no reliable evidence that shows that operating profit margin relates significantly to the ROA.

In reference to the American Banks ROA in Model 2 the equation is as follows:

ROAAB = Constant(-0.62) + AM(75.22) + OPM(-0.0) + NFC(-0.0) + ICF(0.0) + DA(0.02) + e

Based upon the adjusted r value of 0.598, at least 59.8% of the ROA for American Banks can be explained by variables in the regression analysis and the F test has a significant p-value of 0. Therefore, if the hypothesis were to include all the variables as a combination then they would collectively have a significant impact on the ROA. But for

2006 2007 2008 2009 2010 TECB $7,495,878 $7,871,408 $9,487,951 $10,652,652 $11,695,156 TEAB $31,767,004 $32,762,254 $29,975,032 $45,638,646 $50,266,480 TECF $736,911 $835,721 $862,516 $924,556 $997,862 TEAF $4,354,417 $6,474,003 $6,915,082 $8,670,873 $9,651,769 $10,000,000 $20,000,000 $30,000,000 $40,000,000 $50,000,000 $60,000,000 TE in t e rm s o f $1, 000

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