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on Financial Markets |
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Issue of 2016‒06‒25
eleven papers chosen by |
| By: | Kurz-Kim, Jeong-Ryeol |
| Abstract: | Using a simple sign test, we report new empirical evidence, taken from both the US and the German stock markets, showing that trading behavior substantially changed around Black Monday in 1987. It turned out that before Black Monday investors behaved more as in the momentum strategy; and after Black Monday more as in the contrarian strategy. We argue that crashes, in general, themselves are merely a manifestation of uncertainty on stock markets and the high uncertainty due to globalization is mainly responsible for this change. |
| Keywords: | Trading behavior,Momentum,Contrarian,Black Monday,Globalization,Uncertainty |
| JEL: | C12 G02 G11 |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdps:182016&r=fmk |
| By: | Thesmar , David; Bouchaud , Jean-Philippe; Stefano , Ciliberti; Landier , Augustin; Simon , Guillaume |
| Abstract: | This note investigates the causes of the quality anomaly, which is one of the strongest and most scalable anomalies in equity markets. We explore two potential explanations. The "risk view", whereby investing in high quality firms is somehow riskier, so that the higher returns of a quality portfolio are a compensation for risk exposure. This view is consistent with the Efficient Market Hypothesis. The other view is the "behavioral view", which states that some investors persistently underestimate the true value of high quality firms. We find no evidence in favor of the "risk view": The returns from investing in quality firms are abnormally high on a risk-adjusted basis, and are not prone to crashes. We provide novel evidence in favor of the "behavioral view": In their forecasts of future prices, and while being overall overoptimistic, analysts systematically underestimate the future return of high quality firms, compared to low quality firms. |
| Keywords: | Quality anomaly; financial analysts misplaced focus; behavioral biases |
| JEL: | G00 G14 |
| Date: | 2016–06–15 |
| URL: | http://d.repec.org/n?u=RePEc:ebg:heccah:1134&r=fmk |
| By: | Roman Frydman (New York University); Joshua R. Stillwagon (Trinity College) |
| Abstract: | Behavioral finance views stock-market investors’ expectations as largely unrelated to fundamental factors. Relying on survey data, this paper presents econometric evidence that fundamentals are a major driver of investors’ expectations. Although expectations are also in part extrapolative, this effect is transient. The paper’s approach underscores the central importance of opening models to structural change and imposing discipline on econometric analysis through specification testing. Our findings support the novel hypothesis that rational market participants, faced with unforeseeable change, base their forecasts on both fundamentals - the focus of the REH approach - and the psychological and technical considerations underlying behavioral finance. |
| Keywords: | Behavioral finance, REH, Knightian uncertainty, survey expectations, structural change, model specification, automated model selection. |
| JEL: | G12 G14 G02 C22 |
| Date: | 2016–05 |
| URL: | http://d.repec.org/n?u=RePEc:thk:wpaper:44&r=fmk |
| By: | G. Marandola; R. Mossucca |
| Abstract: | This paper studies the stock market response to corporate downgrades by S&P, Moody's and Fitch between 1999 and 2011. The empirical evidence shows that cumulative abnormal returns around downgrades become significantly smaller (in absolute value) after the release in 2003 of the Securities and Exchange Commission’s Report on credit rating agencies. The Report addresses concerns related to the agencies and marks a turning point in the attitude of U.S. regulators towards a more critical approach. This has a strong impact on investors that respond by reacting less to downgrades. |
| JEL: | G14 G24 G28 |
| Date: | 2016–05 |
| URL: | http://d.repec.org/n?u=RePEc:bol:bodewp:wp1066&r=fmk |
| By: | Mihaly Ormos; Dusan Timotity |
| Abstract: | This paper discusses a novel explanation for asymmetric volatility based on the anchoring behavioral pattern. Anchoring as a heuristic bias causes investors focusing on recent price changes and price levels, which two lead to a belief in continuing trend and mean-reversion respectively. The empirical results support our theoretical explanation through an analysis of large price fluctuations in the S&P 500 and the resulting effects on implied and realized volatility. These results indicate that asymmetry (a negative relationship) between shocks and volatility in the subsequent period indeed exists. Moreover, contrary to previous research, our empirical tests also suggest that implied volatility is not simply an upward biased predictor of future deviation compensating for the variance of the volatility but rather, due to investors systematic anchoring to losses and gains in their volatility forecasts, it is a co-integrated yet asymmetric over/under estimated financial instrument. We also provide results indicating that the medium-term implied volatility (measured by the VIX Index) is an unbiased though inefficient estimation of realized volatility, while in contrast, the short-term volatility (measured by the recently introduced VXST Index representing the 9-day implied volatility) is also unbiased and yet efficient. |
| Date: | 2016–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1606.03597&r=fmk |
| By: | Nicol\'o Musmeci; Vincenzo Nicosia; Tomaso Aste; Tiziana Di Matteo; Vito Latora |
| Abstract: | We propose here a multiplex network approach to investigate simultaneously different types of dependency in complex data sets. In particular, we consider multiplex networks made of four layers corresponding respectively to linear, non-linear, tail, and partial correlations among a set of financial time series. We construct the sparse graph on each layer using a standard network filtering procedure, and we then analyse the structural properties of the obtained multiplex networks. The study of the time evolution of the multiplex constructed from financial data uncovers important changes in intrinsically multiplex properties of the network, and such changes are associated with periods of financial stress. We observe that some features are unique to the multiplex structure and would not be visible otherwise by the separate analysis of the single-layer networks corresponding to each dependency measure. |
| Date: | 2016–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1606.04872&r=fmk |
| By: | Esin Cakan (Department of Economics, University of New Haven, USA); Rangan Gupta (Department of Economics, University of Pretoria and IPAG Business School, Paris, France) |
| Abstract: | This article analyzes the impactof US macroeconomic announcement surprises on the volatility of the South African equity market. We employ the asymmetric GJR-GARCH model that that allows for both positive and negative surprises about inflation and unemployment rate announcements in the U.S. By examining daily data on South African stock market returns from 31 May 1994 to 8 March 2016, we find that shocks to volatility are persistent and asymmetric. While bad news about US inflation does not affect the volatility of South African stock returns, good news tend to increase the volatility. Further, the South African stock market becomes more risky with an unexpected increase in the US unemployment rate and less risky with the an unexpected decrease in the US unemployment rate, with the latter effect being stronger than the former. Our findings demonstrate that US economic conditions may have an impact on the risk profile of the South African equity market. |
| Keywords: | Asymmetric GARCH, US macroeconomic news, surprises, South Africa |
| JEL: | C22 G1 |
| Date: | 2016–06 |
| URL: | http://d.repec.org/n?u=RePEc:pre:wpaper:201646&r=fmk |
| By: | Chong, Terence Tai-Leung; Liu, Xiaojin; Zhu, Chenqi |
| Abstract: | This paper examines the causes of herd behavior in the Chinese stock market. Using the non-linear model of Chang, Cheng and Khorana (2000), we find robust evidence of herding in both the up and down markets. We contribute to the existing literature by exploring the underlying reasons for herding in China. It is shown that analyst recommendation, short-term investor horizon, and risk are the principal causes of herding. However, we cannot find evidence that relates herding to firm size, nor can we detect significant differences in herding between state-owned enterprises (SOE) and non-SOEs. |
| Keywords: | A-share market; Herd behavior; Return dispersion; Systemic risk. |
| JEL: | G15 |
| Date: | 2016–06–19 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:72100&r=fmk |
| By: | Marco Bianchetti; Davide Galli; Camilla Ricci; Angelo Salvatori; Marco Scaringi |
| Abstract: | We applied the Johansen-Ledoit-Sornette (JLS) model to detect possible bubbles and crashes related to the Brexit/Bremain referendum scheduled for 23rd June 2016. Our implementation includes an enhanced model calibration using Genetic Algorithms. We selected a few historical financial series sensitive to the Brexit/Bremain scenario, representative of multiple asset classes. We found that equity and currency asset classes show no bubble signals, while rates, credit and real estate show super-exponential behaviour and instabilities typical of bubble regime. Our study suggests that, under the JLS model, equity and currency markets do not expect crashes or sharp rises following the referendum results. Instead, rates and credit markets consider the referendum a risky event, expecting either a Bremain scenario or a Brexit scenario edulcorated by central banks intervention. In the case of real estate, a crash is expected, but its relationship with the referendum results is unclear. |
| Date: | 2016–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1606.06829&r=fmk |
| By: | Adam Marszk (Gdansk University of Technology, Gdansk, Poland); Ewa Lechman (Gdansk University of Technology, Gdansk, Poland); Harleen Kaur (Faculty of Management and Information Technology, Hamdard University, Hamdard, India) |
| Abstract: | Exchange traded funds (ETFs) are one of the most influential financial innovations, reshaping the investment funds market in many countries, including Mexico. Due to their similar investment objectives, ETFs are considered substitutes for mutual funds. This paper examines the changes of the investment funds (ETFs and mutual funds) in Mexico over 2002-2012 using a category of the innovation diffusion models, i.e. logistic growth models in order to explore the key development patterns. Descriptions of the selected categories of investment funds are provided in the first section of the article, together with the advantages of ETFs as opposed to mutual funds. Next section presents data sources and methodological framework, with detailed description of the innovation diffusion models applied in the research (based on 3-parametric logistic curve). Sum of assets under management of ETFs and mutual is considered as the size of the total investment funds market. Empirical findings indicate the significant development of the ETF market, both in terms of assets under management and market share. According to the presented estimations, Mexican ETF market development can be described with the logistic growth models, and three characteristic phases of the logistic curve were clearly observable. Predicted ETF market development patterns point towards further increase of market share of ETFs over the next 3-5 years yet the probability of exceeding the level of ca. 20-30% seems low |
| Keywords: | exchange traded funds, mutual funds, diffusion models, financial innovation, Mexico |
| JEL: | G11 G23 O16 |
| Date: | 2016–06 |
| URL: | http://d.repec.org/n?u=RePEc:gdk:wpaper:34&r=fmk |
| By: | Santiago Gamba-Santamaria; Jose Eduardo Gomez-Gonzalez (Banco de la República de Colombia); Luis Fernando Melo-Velandia (Banco de la República de Colombia); Jorge Luis Hurtado-Guarin (Banco de la República de Colombia) |
| Abstract: | We extend the framework of Diebold and Yilmaz [2009] and Diebold and Yilmaz [2012] and construct volatility spillover indexes using a DCC-GARCH framework to model the multivariate relationships of volatility among assets. We compute spillover indexes directly from the series of asset returns and recognize the time-variant nature of the covariance matrix. Our approach allows for a better understanding of the movements of financial returns within a framework of volatility spillovers. We apply our method to stock market indexes of the United States and four Latin American countries. Our results show that Brazil is a net volatility transmitter for most of the sample period, while Chile, Colombia and Mexico are net receivers. The total spillover index is substantially higher between 2008Q3 and 2012Q2, and shock transmission from the United States to Latin America substantially increased around the Lehman Brothers’ episode. Classification JEL: G01, G15, C32 |
| Keywords: | Volatility spillovers, DCC-GARCH model, Stock market linkages, financial crisis |
| Date: | 2016–05 |
| URL: | http://d.repec.org/n?u=RePEc:bdr:borrec:943&r=fmk |