|
on Financial Markets |
|
Issue of 2017‒03‒19
five papers chosen by |
| By: | Hiroshi Toyoizumi |
| Abstract: | A combination of a priority queueing model and mean field theory shows the emergence of traders' swarm behavior, even when each has a subjective prediction of the market driven by a limit order book. Using a nonlinear Markov model, we analyze the dynamics of traders who select a favorable order price taking into account the waiting cost incurred by others. We find swarm behavior emerges because of the delay in trader reactions to the market, and the direction of the swarm is decided by the current market position and the intensity of zero-intelligent random behavior, rather than subjective trader predictions. |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1703.01291&r=fmk |
| By: | Erwan Morellec (EPFL and Swiss Finance Institute); Alexei Zhdanov (Pennsylvania State University) |
| Abstract: | Most firms face some form of competition in product markets. The degree of competition a firm faces feeds back into its cash flows and affects the values of the securities it issues. We demonstrate that, through its effects on stock prices, product market competition also affects the prices of options on equity and naturally leads to an inverse relationship between equity returns and volatility, generating a negative volatility skew in option prices. Using a large sample of U.S. equity options, we provide empirical support for this finding and demonstrate the importance of accounting for product market competition when explaining the cross-sectional variation in option skew. |
| Keywords: | Product market competition, Investment, Leverage effect, Option skew |
| JEL: | G13 G31 G32 |
| Date: | 2017–02 |
| URL: | http://d.repec.org/n?u=RePEc:chf:rpseri:rp1707&r=fmk |
| By: | Elyasiani, Elyas (Temple University); Keegan, Jason (Federal Reserve Bank of Philadelphia) |
| Abstract: | We investigate the association between the yields on debt issued by U.S. systemically important banks (SIBs) and their idiosyncratic risk factors, macroeconomic factors, and bond features, in the secondary market. Although greater SIB risk levels are expected to increase debt yields (Evanoff and Wall, 2000), prevalence of government safety nets complicates the market discipline mechanism, rendering the issue an empirical exercise. Our main objectives are twofold. First, we study how bond buyers reacted to elevation of SIB-specific and macroeconomic risk factors over the recent business cycle. Second, we investigate the degree to which the proportion of variance in yields explained by SIB and macroeconomic risk factors changed across the phases of the cycle. Our data include over 8 million bond trades across 26 SIBs. We divide our sample period into the pre-crisis (2003:Q1 to 2007:Q3), crisis (2007:Q4 to 2009:Q2), and post-crisis (2009:Q3 to 2014:Q3) sub-periods to contrast the findings. We obtain several results. First, bond buyers do react to changes in the SIB-specific risk factors (leverage, credit risk, inefficiency, lack of profitability, illiquidity, and interest rate risk) by demanding higher yields. Second, bond buyers’ responses to risk factors are sensitive to the phase of the business cycle. Third, the proportion of variance in yields driven by SIB-specific and bond-specific risk factors increased from 23 percent in the pre-crisis period to 47 percent and 73 percent, respectively, during the crisis and post-crisis periods. These findings indicate that the force of market discipline improved greatly during the crisis and post-crisis periods, at the expense of macroeconomic factors. The strengthening of market discipline in the crisis and post-crisis periods, despite the unprecedented regulatory intervention in the form of quantitative easing programs, the Troubled Asset Relief Program, large bail outs, and generally accommodative fiscal and monetary policies adopted during these periods, demonstrates that regulatory intervention and market discipline can work in tandem. |
| Keywords: | Bank Risk; Financial Crisis; U.S. Bank Holding Companies; Risk Management; Market Discipline |
| JEL: | G01 G2 G21 G28 |
| Date: | 2017–03–10 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpwp:17-5&r=fmk |
| By: | Oskar Kowalewksi (IESEG School of Management (LEM-CNRS-UMR 9221)); Piotr Spiewanowski (Institute of Economics of the Polish Academy of Science, Poland) |
| Abstract: | We examine the stock market reaction to natural and man-made disasters in potash mines. We use a sample of 44 mining accidents worldwide over the period 1995-2016. A quarter of the accidents were the result of a natural disaster, such as flooding, that often ended in the closure of the potash mine. The remaining accidents were caused mainly by human error, and almost 50% were work accidents often associated with serious injury or death. On average, mining firms experience a drop in their market value of 0.89% on the day of a disaster. However, we observe a significantly stronger response of the stock market to natural events. Indeed, the regression analysis confirms that the firm’s market loss is significantly related to the seriousness of the accident. On the other hand, we do not find any other micro- or macro-level factors that determine the stock market reaction following a disaster. |
| Keywords: | potash mine, disasters, event study, working accident, catastrophe |
| JEL: | G14 Q27 Q51 |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:ies:wpaper:f201702&r=fmk |
| By: | Cheteni, Priviledge |
| Abstract: | This study looks into the relationship between stock returns and volatility in South Africa and China stock markets. A Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model is used to estimate volatility of the stock returns, namely, the Johannesburg Stock Exchange FTSE/JSE Albi index and the Shanghai Stock Exchange Composite Index. The sample period is from January 1998 to October 2014. Empirical results show evidence of high volatility in both the JSE market, and the Shanghai Stock Exchange. Furthermore, the analysis reveals that volatility is persistent in both exchange markets and resembles the same movement in returns. Consistent with most stock return studies, we find that movements of both markets seem to take a similar trajectory. |
| Keywords: | GARCH, ARCH effect, JSE index, Shanghai Stock Exchange Composite Index |
| JEL: | G0 G1 G10 G17 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:77355&r=fmk |