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Author: Joseph Chen
Publisher:
ISBN:
Category : Financial crises
Languages : en
Pages : 66
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Book Description
This paper is an investigation into the determinants of asymmetries in stock returns. We develop a series of cross-sectional regression specifications which attempt to forecast skewness in the daily returns of individual stocks. Negative skewness is most pronounced in stocks that have experienced: 1) an increase in trading volume relative to trend over the prior six months; and 2) positive returns over the prior thirty-six months. The first finding is consistent with the model of Hong and Stein (1999), which predicts that negative asymmetries are more likely to occur when there are large differences of opinion among investors. The latter finding fits with a number of theories, most notably Blanchard and Watson's (1982) rendition of stock-price bubbles. Analogous results also obtain when we attempt to forecast the skewness of the aggregate stock market, though our statistical power in this case is limited.
Author: Joseph Chen
Publisher:
ISBN:
Category : Financial crises
Languages : en
Pages : 66
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Book Description
This paper is an investigation into the determinants of asymmetries in stock returns. We develop a series of cross-sectional regression specifications which attempt to forecast skewness in the daily returns of individual stocks. Negative skewness is most pronounced in stocks that have experienced: 1) an increase in trading volume relative to trend over the prior six months; and 2) positive returns over the prior thirty-six months. The first finding is consistent with the model of Hong and Stein (1999), which predicts that negative asymmetries are more likely to occur when there are large differences of opinion among investors. The latter finding fits with a number of theories, most notably Blanchard and Watson's (1982) rendition of stock-price bubbles. Analogous results also obtain when we attempt to forecast the skewness of the aggregate stock market, though our statistical power in this case is limited.
Author: Joseph Chen
Publisher:
ISBN:
Category :
Languages : en
Pages : 47
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Book Description
This paper is an investigation into the determinants of asymmetries in stock returns. We develop a series of cross-sectional regression specifications which attempt to forecast skewness in the daily returns of individual stocks. Negative skewness is most pronounced in stocks that have experienced: 1) an increase in trading volume relative to trend over the prior six months; and 2) positive returns over the prior thirty-six months. The first finding is consistent with the model of Hong and Stein (1999), which predicts that negative asymmetries are more likely to occur when there are large differences of opinion among investors. The latter finding fits with a number of theories, most notably Blanchard and Watson's (1982) rendition of stock-price bubbles. Analogous results also obtain when we attempt to forecast the skewness of the aggregate stock market, though our statistical power in this case is limited.
Author: Lois Flynn
Publisher:
ISBN:
Category :
Languages : en
Pages : 108
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Book Description
Author: Ian Martin
Publisher:
ISBN:
Category : Assets (Accounting)
Languages : en
Pages : 0
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Book Description
We introduce a framework that uses option prices to deliver upper and lower bounds on the probability of crash in an individual stock, and argue based on a priori considerations that the lower bound should be close to the true crash probability. Empirical tests support this prediction in and out of sample. We horse-race the lower bound against a range of characteristics proposed by the prior literature. The lower bound is highly statistically significant, with a t-statistic above five, and is an order of magnitude more economically significant than any of the characteristics, in the sense that a one standard deviation increase in the lower bound raises the predicted probability of a crash by 3 percentage points, whereas a one standard deviation change in the next most important predictor (a measure of short interest) moves the predicted probability of a crash by only 0.3 percentage points.
Author: Daehyun You
Publisher:
ISBN:
Category : Traffic safety
Languages : en
Pages : 470
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Book Description
Author: Esther Del Brio
Publisher:
ISBN:
Category :
Languages : en
Pages : 6
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Book Description
The current research examines the capacity of the Edgeworth-Sargan density on forecasting market crashes. Focusing on the 1987 stock market crash the performance of this distribution is compared to the Student's t concluding that the latter overestimates the risk. In contrast, and due to its flexible parametric structure, the Edgeworth-Sargan density is capable of more accurately forecasting the risk of highly volatile scenarios, especially when intraday data is available. We use daily data from the FTSE and Dow Jones indices (continuously compounded returns).
Author: Didier Sornette
Publisher: Princeton University Press
ISBN: 1400885094
Category : Business & Economics
Languages : en
Pages : 449
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Book Description
The scientific study of complex systems has transformed a wide range of disciplines in recent years, enabling researchers in both the natural and social sciences to model and predict phenomena as diverse as earthquakes, global warming, demographic patterns, financial crises, and the failure of materials. In this book, Didier Sornette boldly applies his varied experience in these areas to propose a simple, powerful, and general theory of how, why, and when stock markets crash. Most attempts to explain market failures seek to pinpoint triggering mechanisms that occur hours, days, or weeks before the collapse. Sornette proposes a radically different view: the underlying cause can be sought months and even years before the abrupt, catastrophic event in the build-up of cooperative speculation, which often translates into an accelerating rise of the market price, otherwise known as a "bubble." Anchoring his sophisticated, step-by-step analysis in leading-edge physical and statistical modeling techniques, he unearths remarkable insights and some predictions--among them, that the "end of the growth era" will occur around 2050. Sornette probes major historical precedents, from the decades-long "tulip mania" in the Netherlands that wilted suddenly in 1637 to the South Sea Bubble that ended with the first huge market crash in England in 1720, to the Great Crash of October 1929 and Black Monday in 1987, to cite just a few. He concludes that most explanations other than cooperative self-organization fail to account for the subtle bubbles by which the markets lay the groundwork for catastrophe. Any investor or investment professional who seeks a genuine understanding of looming financial disasters should read this book. Physicists, geologists, biologists, economists, and others will welcome Why Stock Markets Crash as a highly original "scientific tale," as Sornette aptly puts it, of the exciting and sometimes fearsome--but no longer quite so unfathomable--world of stock markets.
Author: Armin Bunde
Publisher: Springer Science & Business Media
ISBN: 3642562574
Category : Science
Languages : en
Pages : 472
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Book Description
This book tackles these questions by applying advanced methods from statistical physics and related fields to all types of non-linear dynamics prone to disaster. It gives readers an insight into the problems of catastrophes and is one of the first books on the theories of disaster. Based on physical and mathematical theories, the general principles of disaster appearance are explained.
Author: Eric Engstrom
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Stock market gyrations are notoriously hard to predict, and not for lack of effort by legions of investors, market commentators and academics.
Author: Manmohan S. Kumar
Publisher: International Monetary Fund
ISBN:
Category : Business & Economics
Languages : en
Pages : 44
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Book Description
This paper assesses the extent to which crashes in emerging market currencies are predictable using simple logit models based on lagged macroeconomic and financial data. To evaluate our model, we calculate trading strategies in which an investor goes long or short in the currency depending on whether crash probabilities are low or high. When we estimate the model on part of the data and then use the parameter estimates to generate predictions for the remainder of the sample, we find that substantial profits may be made. Furthermore, the model correctly forecasts major crashes even on an out-of-sample basis.
