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An Empirical Investigation into the Value of Credit Lines
Access to adequate liquidity to finance future investments is an essential element of financial management. The two main questions that this dissertation attempts to answer are (i) what is the net valuation effect of LoC? and (ii) if LoC create value, what are the sources of this value? To answer these questions, I constructed a sample of 85,232 firm-years spanning from 1993 to 2016, with credit line data obtained from Capital IQ and Bloomberg. I investigated the valuation effects of LoC with a methodology extensively used in the analysis of the valuation implications of cash. I used this methodology because cash and LoC are two alternatives to manage liquidity and estimated the changes in shareholders' value associated with changes in existing LoC undrawn balances and on new LoC agreements. The results from this analysis demonstrates a positive association between increases in LoC capacity and shareholder's value. These findings are also obtained in univariate and event study analyses. The results also suggest that LoC create more value for firms that are rich in cash, indicating the LoC and cash are complementary liquidity management tools. I then focused on the sources of the value created by credit lines. I examined whether information asymmetry plays a role in LoC valuation by analyzing the association between firm value and LoC for firms with high- and low-information asymmetric. I also studied whether LoCs reduce agency problems by comparing firm value and LoC capacity in both poorly and well-governed firms. Furthermore, I examined whether firms benefit from an increase in financial flexibility provided by access to credit lines. I found results consistent with LoC being more valuable for firms with higher levels of informational asymmetries. The analysis also suggests that LoCs with longer maturity create more value than those with shorter maturity. Surprisingly, I find limited …
Impact of Market State on Momentum Portfolio Risk and Performance: A Risk-Based Explanation
The momentum puzzle, i.e., stocks that have performed better in the past tend to perform better in the future, has been a constant challenge to classic finance theory. Prior research has failed to provide valid risk-based explanations because winner portfolios do not exhibit higher risk characteristics. Without a convincing risk explanation, the persistence of momentum profit is a violation of the efficient market hypothesis. Today, the momentum puzzle remains one of the very few major anomalies that cannot be explained by Fama-French factor models. I find prior empirical efforts to measure momentum profits and its sources are contaminated by the state of the market during both formation and holding periods. By looking into different market states, classified by both traditional and non-traditional bull and bear market definition, I find the key to at least partially solve the momentum mystery. Momentum stocks are riskier when formed in bull market, and momentum profit is much higher in continuation of market than reverses of market condition, lending empirical support to a risk-based explanation. My definition of market states is essentially based on the risk premium of major risk factors. When market risk is considered a risk factor, if realized market risk premium is positive, it is a bull market; when size is considered a proxy for risk factor, if SMB (small minus big risk premium) is positive, it is a bull market; when valuation (book-to-market) ratio is a proxy for risk factor, if HML (High-minus-Low risk premium) is positive, it is a bull market. This paper also explores simulations using models based on the positive relationship between risk and return. The simulation result confirms that at least part of the momentum profit can be explained by risk.
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