Market’s Up- and Downswings and Customers Satisfaction

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Market’s Up- and Downswings and Customers Satisfaction

Market oriented economies are characterized by unpredictable fluctuations in aggregate eco-nomic activities, which are called market’s up- and downswings (Long and Plosser, 1983). Upswings and downswings involve fluctuations over time between periods of relatively rapid economic growth, booms, and periods of relative stagnation or decline, recessions (Long and Plosser, 1983). During booms, a shift in demand can raise markets output, lower its price and raise income (Rotemberg and Saloner, 1986). Price wars are common in booms. This can be explained by the fact that when demand is high, a firm can lower a bit its prices and take the whole demand (Rotemberg and Saloner, 1986). The benefit from this is higher than the pun-ishment of not collude1 (Rotemberg and Saloner, 1986). So, even though the total income ris-es, a frequent phenomenon during booms is the price wars. In recessions, on the contrary, a decline in demand can reduce the output. Demand outplaces supply and the prices remain constant, may even rise, but the total income declines and the market falls (Rotemberg and Saloner, 1986).
The effects of market’s up- and downswings are more intensive in the case of homogeneous products or services as in this case the customers are more price-sensitive (Singh and Vives, 1984). From the customers’ perspective, the product is a combination of value satisfactions (Levitt, 1980). When customers perceive a product or service as homogeneous the price be-comes the differentiated strategy (Levitt, 1980). A fractionally lower price then, gets the whole demand (Levitt, 1980). These fluctuations and their effects are especially relevant to up- and downswings in securities’ markets. Companies, therefore, need strategies in order to differentiate their product or service from the competitors, create value for the customer, fore-cast more accurate the demand and protect themselves from these fluctuations and their mac-roeconomic effects. In that way they can remain long term viable and profitable.
A definition of marketing suggests that based on the customers’ view, the marketing purpose is “to establish, develop and commercialise long term customer relationships, so that the ob-jectives of the parties involved are met. This is done by mutual exchange and keeping of promises” (Grönroos, 1989). I am using this definition because by including the term “long term customer relationships” it is more relevant to my topic. Based on marketing theories and researches, marketers are developing and implementing efficient marketing strategies in order to increase customers’ satisfaction and to protect the company from the consequences of mar-ket’s up- and downswings. They support that by differentiating their product or service, the benefits and the satisfaction, that customers receive, increase. Therefore, by increasing cus-tomers’ satisfaction and loyalty and by strengthening the business and the product respective-ly service image, the company will be long-term profitable and will not be affected, or at least will be affected less, from market’s fluctuations (Yu and Dean, 2001).
Moreover, as price wars are common in booms and as companies have realized that price is not an advantage weapon anymore, the companies which have loyal customers will be more profitable. A loyal customer will buy more, will make recurring purchases, will talk more about the firm (word of mouth strategy) and will not try to find a substitute (a competitor’s firm) (Berthon, Hulbert and Pitt, 1999). All these strategies will help the company to be fi-nancially improved without getting involved in the price war. Price wars are common in the business world because managers see them as an easy action to gain market share and tempo-rary profits. An increase in expected future profit reduces the initiatives for price-wars and markups staying in a higher level (Rotemberg and Woodford, 1991). In order to gain market share in the future without reducing the prices the companies can create efficient marketing strategies, differentiate their product or service, increase customers satisfaction and build “glamorous” brands and create a competitive advantage (Dutta, Zbaracki and Bergen, 2003).
In downswings or recessions, when the total market declines, companies tend to compete more in order to keep their customers. In this case too, companies with loyal customers will have competitive advantages. Highly satisfied customers are more loyal and less likely to give in to other firms’ offers (Heide and Weiss, 1995). Consequently, remaining loyal to the firm makes the firm less vulnerable to market’s declines and more attractive to investors.
The value of customer retention is especially high in the banking sector (Reichheld and Ken-ny, 1990-1991). As they mention, the two main strategies of cost reduction or price increase, can cause only short-term profits. On the other hand, customers’ retention and loyalty cause growth and margins for several reasons. Balances raise through time as interest accrues, many accounts are consolidated and the economic situation of the customer is superior (Reichheld and Kenny, 1990-1991). The cost of keeping a customer is approximately fixed but the cost of attracting new customers is high and includes increased promotion and advertising expendi-tures and rate escalation (Reichheld and Kenny, 1990-1991). The cost of gaining a new cus-tomer is incurred only the first year, which means that the older the relationship is, the lower the amortised cost (Reichheld and Kenny, 1990-1991). Loyal customers could expand their purchasing manner also to other products/ services (Reichheld and Kenny, 1990-1991). A bank with loyal depositors has the advantage that its competitors will not react fast and this is because retention it is not easily measured (Reichheld and Kenny, 1990-1991). With all these arguments and some examples they are suggesting customers’ satisfaction as a comparative advantage against their competitors from one hand and market’s economic fluctuations from the other. A measurement of the yearly market value is the Gross Domestic Product (GDP). The graph shows the gross domestic product of the countries and through the period tested, Sweden, Denmark and Norway. A downswing can be considered around 2008 and an up-swing around 2010.
The question now is: Can marketing, by increasing customers’ satisfaction, protect the firm from the market fluctuations? Can we count this strategy in financial/ economical results? Some theoretical marketing studies posit that customers’ satisfaction lowers the stock’s re-turns risk (Srivastava, Shervani and Fahey, 1998). However, very little empirical research has verified this relationship (Tuli and Bharadwaj, 2009).

Shareholder Value – Risk

There are two ways to increase shareholder’s value: high expected stock’s returns or low stock’s returns systematic risk (Brown, Martin and Gruber, 2010).
From the asset pricing theory, the basic model for pricing risky securities, which describes the relationship between risk and expected return, is the Capital Asset Pricing Model (CAPM) (Fama and French, 2004). CAPM suggests that the equilibrium return on any risky security is equal to the sum of the risk-free rate of return and a risk premium measured by the product of the market price of risk and the security’s systematic risk. The general idea behind CAPM is that investors need to be compensated in two ways: time value of money and risk (Fama and French, 2004). According to Brown, Martin, and Gruber (2010) the time value of money compensates the investors for placing money in any investment over a period of time and represented with on the equation one below; (beta), risk premium, in the formula represents the systematic risk and calculates the amount of compensation the investor needs for taking on additional risk. Beta measures the sensitivity of the asset’s returns to variation in the mar-ket return (Fama and French, 2004).
In simple words, when investors are evaluating a company, they are interested in the tradeoff between returns and systematic risk in minimum variance portfolios: the more systematic risk a security has, the higher the rate of return should be and the beta (systematic risk) is the only parameter which affects this relationship (graph two). Many researchers showed that some of the variation in expected returns is unrelated to market beta (Basu, 1977; Banz 1981). There-fore, accounting factors like earnings, size, etc add to the explanation of expected stock re-turns, explained by market beta and have been used as proxies for the latent risk factors. Therefore, market beta is not a complete description of asset’s systematic risk – high standard error (ei), not normally distributed.
The risk of the asset can be divided in two different kinds of risks: systematic and idiosyncrat-ic (Brown, Martin, and Gruber, 2010). Systematic risk is the market risk or the risk associated with the market movements and all securities are affected by the systematic risk (Brown, Martin, and Gruber, 2010). The companies which can protect themselves from the impact of market movements have lower systematic risk. Idiosyncratic risk, on the other hand, is the risk which is unique for every company and is affected mainly from company’s actions (Tuli and Bharadwaj 2009). Idiosyncratic risk can be eliminated in a well diversified portfolio. So, what matters to investors is only the systematic risk of stock’s returns.
As I already argued systematic risk is the risk associated with the market movements. Market is influenced by the different market’s up- and downswings (Long and Plosser, 1983). Mar-ket’s up- and downswings refers to the ups and downs seen somewhat unpredictably and sim-ultaneously in most parts of an economy. These fluctuations have an important effect on secu-rities’ markets. More detailed, in recessions, where the market declines, stocks with high ex-posure in market’s β (beta) will be more vulnerable and insecure. Even in the case of a boom, where the market rises, companies which can prevent to be involved in the price wars as-sumed as more stable in their future earnings without the risk to lose their market share in the future.
Stock’s returns systematic risk is a key component of shareholder value that affects the finan-cial markets (Barber and Odean, 2000). Thus, it makes sense that investors are trying to find factors that can reduce the systematic risk of the stock’s returns and its impact from the up-and downswings. Based on the financial literature, variables that are significant predictors of the systematic risk are: firm size, financial leverage, profitability, and earnings variability (Coles, Daniel and Naveen, 2006). McAlister, Srinivasan and Kim (2007) have shown that advertising/sales and R&D/sales are also important factors in reducing firm’s systematic risk.
A model which adds more factors in order to explain the variability in returns is Fama- French three factors model (equation two) and it is the main model used in portfolio management to measure market returns (Fama and French, 1993; Lin, Wang and Cai, 2012).
Fama-French three factors model predicts company’s systematic risk by using the two non-market risk factors SMB (the difference between the return on a portfolio of small stocks and the return on a portfolio of large stocks) and HML (the difference between the return on a portfolio of high-book-to-market stocks and the return on a portfolio of low-book-to-market stocks) (Brown, Martin, and Gruber, 2010). Taking also these factors into account Fama-French three factors model is considered as more accurate than the CAPM (Fama and French, 1993). Nevertheless, it cannot be assumed as the complete description of the variability in re-turns (Fama and French, 1993).
The financial theory requires that the systematic risks should be net priced. If the CAPM is not misspecified, omit some relevant explanatory variables, means that the expected return is completely captured by β (beta). If this is the case the standard error of the regression is white noise and normally distributed (Chen, 1983). Otherwise, the remaining part must be contained in the standard error (Chen, 1983). Similarly, Fama-French three factors model, although it includes also the size proxy, and the book-to-market equity proxy, possibly is not a complete description of the variability in returns. Thus, the part which is not explained must be included in the standard error. In both cases, there must be some other explanatory factors which can price the remaining part of the expected returns (Chen, 1983). These factors can be used as proxies to the latent risk and should be net priced. Should we expect the “extra satisfac-tion” to be one of them? To verify this, the classical econometric tactic is to run the regression with the error term as dependent variable and the customers’ satisfaction scores as independ-ent and observe if some part of the error term can be priced by the customers’ satisfaction fac-tor.

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1 Introduction
2 Background
2.1 Market’s Up- and Downswings and Customers Satisfaction
2.2 Shareholder Value – Risk
2.3 Customer Satisfaction and Stock Returns Risk
3 Problem and Purpose
4 Research Questions
4.1 Customer Satisfaction and Systematic Risk
5 Methodology – Estimation Procedure
5.1 Dependent Variable
5.2 Customer Satisfaction
5.3 Accounting Measurements
5.4 Lag Dependent Variable
5.5 Final Model for systematic risk
6 Data Collection
7 Results
7.1 Final Model – Fama and French three factor model
7.2 CAPM
8 Conclusion and Limitations
8.1 Conclusion
8.2 Limitations
9 References

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