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on Financial Markets |
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Issue of 2014‒02‒08
eleven papers chosen by |
| By: | Durham, J. Benson (Federal Reserve Bank of New York) |
| Abstract: | A small but ambitious literature uses affine arbitrage-free models to estimate jointly U.S. Treasury term premiums and the term structure of equity risk premiums. Within this approach, this paper identifies the parameter restrictions that are consistent with a simple dividend discount model, extends the cross-section to Germany and France, averages across multiple observable-factor and market prices of risk specifications, and considers alternative samples for parameter estimation. The results produce intuitive trajectories for both sets of premiums given standard samples starting from July 1993. However, the decomposition of nominal U.S. Treasury yields, but not long-run equity risk premiums, is sensitive to data beyond 2008, which raises some questions about the net effects of unconventional monetary policy measures. Nonetheless, the rotation from sharp inversion during the financial crisis to an upward-sloping term structure of equity risk premiums more recently, with modest readings at the front end, is not inconsistent with some net moderation in required compensation for equity risk in the United States. |
| Keywords: | equity risk premium; Treasury term premium; affine arbitrage-free models |
| JEL: | G10 G12 G13 G15 |
| Date: | 2013–12–01 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fednsr:656&r=fmk |
| By: | Yavni Bar-Yam; Marcus A. M. de Aguiar; Yaneer Bar-Yam |
| Abstract: | Why do a market's prices move up or down? Claims about causes are made without actual information, and accepted or dismissed based upon poor or non-existent evidence. Here we investigate the price movements that ended with Apple stock closing at \$500.00 on January 18, 2013. There is a ready explanation for this price movement: market manipulation by those who sold stock options, who stood to directly benefit from this closing price. Indeed, one web commentator predicted this otherwise unlikely event publicly. This explanation was subsequently dismissed by press articles that claim that stock prices end near such round numbers based upon legitimate hedging activity. But how can we know? We show that the accepted model that points to hedging as the driving cause of prices is not quantitatively consistent with the price movement on that day. The price moved upward too quickly over a period in which the hedgers' position would require selling rather than buying. Under these conditions hedgers would have driven the price away from the strike price rather than toward it. We also show that a long published theory of the role of hedging is incomplete mathematically, and that the correct theory results in much weaker price movements. This evidence substantially weakens the case of those who claim hedging as cause of anomalous market price movements. The explanation that market manipulation is responsible for the final close cannot be dismissed based upon unsubstantiated, even invalid, hedging claims. Such proffered explanations shield potential illegal activity from further inquiry even though the claims behind those explanations have not been demonstrated. |
| Date: | 2014–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1402.0910&r=fmk |
| By: | Ovidiu Racorean |
| Abstract: | It seems to be very unlikely that all relevant information in the stock market could be fully encoded in a geometrical shape. Still,the present paper will reveal the geometry behind the stock market transactions. The prices of market index (DJIA) stock components are arranged in ascending order from the smallest one in the left to the highest in the right. In such arrangement, as stock prices changes due to daily market quotations, it could be noticed that the price of a certain stock get over /under the price of a neighbor stock. These stocks are crossing. Arranged this way, the diagram of successive stock crossings is nothing else than a permutation diagram. From this point on the financial and combinatorial concepts are netted together to build a bridge connecting the stock market to a beautiful geometrical object that will be called stock market polytope. The stock market polytope is associated with the remarkable structures of positive Grassmannians . This procedure makes all the relevant information about the stock market encoded in the geometrical shape of the stock market polytope more readable. |
| Date: | 2014–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1402.1281&r=fmk |
| By: | Ferreira Filipe, Sara; Grammatikos, Theoharry; Michala, Dimitra |
| Abstract: | While the empirical literature has often documented a “default anomaly”, i.e. a negative relation between default risk and stock returns, standard theory suggests that default risk should be priced in the cross-section. In this paper, we provide an explanation for this apparent puzzle using a new approach. First we calculate monthly physical probabilities of default (PDs) for a large sample of European firms. Second we decompose these estimated PDs into systematic and idiosyncratic components; we measure the systematic part as the sensitivity of the physical PD to an aggregate measure of default risk. While sorting stocks based on physical PDs confirms a possible default anomaly, we find that the relation between the systematic default risk and stock returns is in fact positive. Our results therefore suggest that risker stocks, as measured by the physical PDs, will tend to underperform because they have on average lower exposures to aggregate default risk. Their riskiness is mostly idiosyncratic and can be diversified away. |
| Keywords: | Default Risk, Merton model, Default Anomaly, Idiosyncratic Risk |
| JEL: | G11 G12 G15 G33 |
| Date: | 2014–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:53373&r=fmk |
| By: | Sebastian Poledna; Stefan Thurner |
| Abstract: | Financial markets are exposed to systemic risk (SR), the risk that a major fraction of the system ceases to function and collapses. Since recently it is possible to quantify SR in terms of underlying financial networks where nodes represent financial institutions, and links capture the size and maturity of assets (loans), liabilities, and other obligations such as derivatives. In particular it is possible to quantify the share of SR that individual nodes contribute to the overall SR in the financial system. We extend the notion of node-specific SR to individual liabilities in a financial network (liability-specific SR). We use historical, empirical data of interbank liabilities to show that a few liabilities in a nation-wide interbank network contribute to the major fraction of the overall SR. We propose a tax on individual transactions that is proportional to their contribution to overall SR. If a transaction does not increase SR it is tax free. We use a macroeconomic agent based model (CRISIS macro-financial model) with a financial economy to demonstrate that the proposed Systemic Risk Tax (SRT) leads to a self-organized re-structuring of financial networks, that are practically free of SR. This is because risk-increasing transactions will be systematically avoided when a SRT is in place. Systemic stability under a SRT emerges due to a de facto elimination of system-wide cascading failure. ABM predictions agree remarkably well with the empirical data and can be used to understand the relation of credit risk and systemic risk. |
| Date: | 2014–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1401.8026&r=fmk |
| By: | David E. Allen (Centre for Applied Financial Studies, UniSA University of South Africa, and, visiting, School of Mathematics and Statistics, University of Sydney); Michael McAleer (National Tsing Hua University, Taiwan, Econometric Institute, Erasmus University Rotterdam, the Netherlands, and Complutense University of Madrid, Spain); Abhay K. Singh (School of Business, Edith Cowan University, Perth, Australia) |
| Abstract: | This paper features an analysis of the relationship between the volatility of the Dow Jones Industrial Average (DJIA) Index and a sentiment news series using daily data obtained from the Thomson Reuters News Analytics (TRNA) provided by SIRCA (The Securities Industry Research Centre of the Asia Pacic). The expansion of on-line financial news sources, such as internet news and social media sources, provides instantaneous access to financial news. Commercial agencies have started developing their own filtered financial news feeds, which are used by investors and traders to support their algorithmic trading strategies. In this paper we use a sentiment series, developed by TRNA, to construct a series of daily sentiment scores for Dow Jones Industrial Average (DJIA) stock index component companies. A variety of forms of this measure, namely basic scores, absolute values of the series, squared values of the series, and the first differences of the series, are used to estimate three standard volatility models, namely GARCH, EGARCH and GJR. We use these alternative daily DJIA market sentiment scores to examine the relationship between financial news sentiment scores and the volatility of the DJIA return series. We demonstrate how this calibration of machine filtered news can improve volatility measures. |
| Keywords: | DJIA; Sentiment Scores; TRNA; Conditional Volatility Models |
| JEL: | C58 G14 |
| Date: | 2014–01–23 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:uvatin:20140014&r=fmk |
| By: | Durham, J. Benson (Federal Reserve Bank of New York) |
| Abstract: | The consensus suggests that subdued nominal U.S. Treasury yields on balance since the onset of the global financial crisis primarily reflect exceptionally low, if not occasionally negative, term premiums as opposed to low anticipated short rates. Depressed term premiums plausibly owe to unconventional Federal Reserve policy as well as to net flight-to-quality flows after 2007. However, two strands of evidence raise questions about this story. First, a purely survey-based expected forward term premium measure, as opposed to an approximate spot estimate, has increased rather than decreased in recent years. Second, with respect to the time-series dynamics of factors underlying affine term structure models, simple econometrics of recent data produce not only a more persistent level of the term structure but also a depressed long-run mean, which in turn implies an implausibly low expected short rate path. Strong caveats aside, an implication for central bankers is that unconventional monetary policy measures may have worked in more conventional ways, and an inference for investors is that longer-dated yields embed meaningful compensation for bearing duration risk. |
| Keywords: | Treasury term premium; monetary policy |
| JEL: | E52 G10 |
| Date: | 2013–12–01 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fednsr:658&r=fmk |
| By: | Enrico Onali; John Goddard |
| Abstract: | Fractal analysis is carried out on the stock market indices of seven European countries and the US. We find evidence of long range dependence in the log return series of the Mibtel (Italy) and the PX Glob (Czech Republic). Long range dependence implies that predictable patterns in the log returns do not dissipate quickly, and may therefore produce potential arbitrage opportunities. Therefore, these results are in contravention of the Efficient Market Hypothesis. We show that correcting for short range dependence, or prefiltering, may dispose of genuine long range dependence, suggesting that the market is efficient in cases when it is not. Prefiltering does not reduce significantly the power of the tests only for cases for which the Hurst exponent (a measure of the long range dependence) lies well outside the boundaries of no long range dependence. For borderline cases, the prefiltering procedure reduces the power of the test. On the other hand, the absence of prefiltering does not result in a test that is significantly oversized. |
| Date: | 2014–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1402.1440&r=fmk |
| By: | F. Y. Ouyang; B. Zheng; X. F. Jiang |
| Abstract: | We investigate the spatial and temporal structures of four financial markets in Greater China. In particular, we uncover different characteristics of the four markets by analyzing the sector and subsector structures which are detected through the random matrix theory. Meanwhile, we observe that the Taiwan and Hongkong stock markets show a negative return-volatility correlation, i.e., the so-called leverage effect. The Shanghai and Shenzhen stock markets are more complicated. Before the year 2000, the two markets exhibit a strong positive return-volatility correlation, which is called the anti-leverage effect. After 2000, however, it gradually changes to the leverage effect. We also find that the recurrence interval distributions of both the trading volume volatilities and price volatilities follow a power law behavior, while the exponents vary among different markets. |
| Date: | 2014–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1402.1046&r=fmk |
| By: | El Ghini, Ahmed; Saidi, Youssef |
| Abstract: | The aim of this paper is to investigate the return and volatility linkages among Moroccan stock market with that of U.S. and three European countries (France, Germany and U.K.) before and during the financial crisis. More specifically, we use stock returns in MASI, CAC, DAX, FTSE and NASDAQ as representatives of Moroccan, French, German, British and U.S. markets respectively. The data sample frequency is daily and spans from January 2002 to December 2012 excluding holidays. Using the estimation results of bivariate VAR-BEKK GARCH model, we analyze the return and volatility spillover effects between the Moroccan market and the other considered markets. Moreover, the identification of break point due to the subprime crisis is made by Lee-Strazicich (2003,2004) and Bai-Perron (1998, 2003) structural break tests. The empirical findings provide clear evidence of stronger linkages between the Moroccan market and the four other considered stock markets have been created during the subprime financial crisis period. |
| Keywords: | Return and volatility spillovers; multivariate GARCH model; financial crisis; stock markets; break identification; conditional correlation |
| JEL: | C10 C50 C58 G15 |
| Date: | 2014–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:53439&r=fmk |
| By: | Adrien Nguyen Huu (FiME Lab, IMPA); Nadia Oudjane (FiME Lab) |
| Abstract: | We investigate the problem of pricing and hedging derivatives of Electricity Futures contract when the underlying asset is not available. We propose to use a cross hedging strategy based on the Futures contract covering the larger delivery period. A quick overview of market data shows a basis risk for this market incompleteness. For that purpose we formulate the pricing problem in a stochastic target form along the lines of Bouchard and al. (2008), with a moment loss function. Following the same techniques as in the latter, we avoid to demonstrate the uniqueness of the value function by comparison arguments and explore convex duality methods to provide a semi-explicit solution to the problem. We then propose numerical results to support the new hedging strategy and compare our method to the Black-Scholes naive approach. |
| Date: | 2014–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1401.8271&r=fmk |