Circuit Breakers,Trading Collars,and Volatility Transmission Across Markets: Evidence from NYSE Rule 80A

The NYSE's Rule 80A attempted to delink the futures and equity markets by limiting index arbitrage trades in the same direction as the last trade to reduce stock market volatility. Rule 80A leads to a small but statistically significant decline in intraday U.S. equity market volatility. In addition, the results are asymmetric: volatility is dampened more in a rising market than in a declining one. These results suggest that, to a limited extent, rule restrictions on trading can sufficiently delink the futures and equity markets enough to reduce the transmission of volatility.     

Stock Market Crashes and the Performance of Circuit Breakers: Empirical Evidence

This study examines the behavior of a small stock market with circuit breakers and with a one-hour preauction order imbalance disclosure, during the October 1987 crash. The crash and its aftershocks lasted for a week and selling pressure was concentrated in higher beta, larger capitalization, and lower leverage firm stocks. Circuit breakers when implemented reduced the next-day opening order imbalance and the initial price loss; however, they had no effect on the long-run response. Some price overreaction and reversal phenomena also are documented.     

The Dark Side of Circuit Breakers

Market-wide circuit breakers are trading halts aimed at stabilizing the market during dramatic price declines. Using an intertemporal equilibrium model, we show that a circuit breaker significantly alters market dynamics and affects investor welfare. As the market approaches the circuit breaker, price volatility rises drastically, accelerating the chance of triggering the circuit breaker—the so-called “magnet effect,” returns exhibit increasing negative skewness, and trading activity spikes up. Our empirical analysis supports the model's predictions. Circuit breakers can affect overall welfare negatively or positively, depending on the relative significance of investors' trading motives for risk sharing versus irrational speculation.     

Stock Market Volatility and Learning

We show that consumption‐based asset pricing models with time‐separable preferences generate realistic amounts of stock price volatility if one allows for small deviations from rational expectations. Rational investors with subjective beliefs about price behavior optimally learn from past price observations. This imparts momentum and mean reversion into stock prices. The model quantitatively accounts for the volatility of returns, the volatility and persistence of the price‐dividend ratio, and the predictability of long‐horizon returns. It passes a formal statistical test for the overall fit of a set of moments provided one excludes the equity premium.     

What Makes Circuit Breakers Attractive to Financial Markets? A Survey

After the stock market crash of October 1987, the Brady Report (1988) and several academic researchers suggested the imposition of "circuit breakers" to prevent the market from fluctuating excessively. Most financial markets in the world have imposed circuit breaker systems, in the form of price limits and trading halts, in an attempt to reduce excessive market volatility. Similar to any other regulations, circuit breakers have proponents and opponents. In this survey, we analyze the benefits and costs of each type of circuit breaker, provide existing theoretical models and predictions related to each type of circuit breaker, and present findings from empirical studies to justify or disqualify the existence of circuit breakers. In addition, we synthesize existing studies and offer directions for further research in this area.     

Circuit Breakers and the Tail Index of Equity Returns

Using the tail index of returns on U.S. equities as a summarymeasure of extreme behavior, we examine changes in the equitymarkets surrounding the development of program trading for portfolioinsurance, the crash of 1987, and the subsequent introductionof circuit breakers and other changes in market architecture.Recently-developed tests for the null of constancy of the tailindex, versus the alternative of a change at an unknown date,permit inference on changes in extreme behavior over a longtime period while allowing for second-moment dependence in thereturn data. We find strong evidence of a decrease in the tailindex (increase in the probability of extreme events) aroundthe beginning of large-scale program trading, and weaker, butstill substantial, evidence of further significant change inthe tail index following the introduction of circuit breakers.Point estimates of the tail index suggest that the tail indexmay have roughly regained pre-program trading levels. More generally,the results tend to suggest that long samples of U.S. equityreturns should not be treated as samples from a single distributionfunction, particularly in examining extremes.     

Understanding Housing Market Volatility

The Campbell–Shiller present value formula implies a factor structure for the price–rent ratio of housing market. Using a dynamic factor model, we decompose the price–rent ratios of 23 major housing markets into a national factor and independent local factors, and we link these factors to the economic fundamentals of the housing markets. We find that a large fraction of housing market volatility is local and that the national factor has become more important than local factors in driving housing market volatility since 1999, consistent with the findings in Del Negro and Otrok (2007). The local volatilities mostly are due to time variations of idiosyncratic housing market risk premia, not local growth. At the aggregate level, the growth and interest rate factors jointly account for less than half of the total variation in the price–rent ratio. The rest is due to the aggregate housing market risk premium and a pricing error. We find evidence that the pricing error is related to money illusion, especially at the onset of the recent housing market bubble. The rapid rise in housing prices prior to the 2008 financial crisis was accompanied by both a large increase in the pricing error and a large decrease in the housing market risk premium.     

公允价值会计与市场波动

2008年金融危机的爆发,使得公允价值会计倍受关注。一个焦点问题是:公允价值会计是否会加剧市场波动。我们针对2007—2011年中国A股市场的情况对这一问题进行了实证研究,主要结论如下:1)股价能够反应公允价值会计信息,且在市场波动期比平稳期反应更显著;2)公允价值会计信息与波动率之间的正相关关系在市场波动期比在平稳期更加显著;3)波动率与公允价值会计信息的正相关性主要出现在长周期上。     

Stock Market Volatility and Economic Factors

This paper examines the ability of rational economic factors to explain stock market volatility. A simple model of the economy under uncertainty identifies four determinants of stock market volatility: uncertainty about the price level, the riskless rate of interest, the risk premium on equity and the ratio of expected profits to expected revenues. In initial tests these variables have significant explanatory power and account for over 50 per cent of the variation in market volatility from 1929 to 1989. When the regression coefficients are allowed to vary over time using cluster regression, the four factors explain over 90 per cent of the variation in market volatility. The results are useful in explaining the past behavior of stock market volatility and in forecasting future volatility.     

Imperfect Information and Stock Market Volatility

The purpose of this paper is to (1) develop a model to show how imperfect information can create excess volatility in asset returns and (2) provide empirical evidence consistent with the model. In this framework, variations in information quality cause the market prices to fluctuate more than the corresponding economic fundamentals. Using high‐frequency data from 1988 to 2002, the empirical evidence supports the predictions of the model by showing that economic volatility, defined as squared deviations of the quarterly gross domestic product (GDP) growth rate from its long‐run trend, can explain about half of the variation in S&P 500‐stock index quarterly volatility.     

Margin Regulation and Stock Market Volatility

Using daily and monthly stock returns we find no convincing evidence that Federal Reserve margin requirements have served to dampen stock market volatility. The contrary conclusion, expressed in recent papers by Hardouvelis (1988a , b ), is traced to flaws in his test design. We do detect the expected negative relation between margin requirements and the amount of margin credit outstanding. We also confirm the recent finding by Schwert (1988) that changes in margin requirements by the Fed have tended to follow rather than lead changes in market volatility.     

Accounting for Intangibles: A Theoretical Perspective

This paper uses a transactions theory approach to analyse some of the measurement and disclosure issues involved in accounting for goodwill and other intangibles. The recent professional and academic literature is reviewed and the traditional economic theory approach to interpreting accounting issues in these areas is criticised. A form of transactions theory called ‘Statistical Transactions Theory’ is then used to investigate several conceptual problem areas, notably: the definition of goodwill and fair values; the distinction between goodwill and other intangibles; and capitalisation, amortisation and valuation issues. The authors conclude that the most fruitful course of action in dealing with these issues would be a substantial research effort designed to investigate the distributional properties of accounting numbers relating to the subject of intangibles measurement, including goodwill as defined in this paper. They call for more analytic and empirical work in this field.     

Market Structure and Return Volatility: Evidence from the Hong Kong Stock Market

There is no consensus about the cause for higher volatility at the market open than at the market close in the U.S. market. As an order–driven, nonspecialist market, the Hong Kong stock market provides a useful setting for an examination. If halt of trade were the major cause of higher open–to–open volatility, the open–to–open volatility in the Hong Kong market would be higher. However, this is not observed. The autocorrelation of the open–to–open return series also indicates that the temporary price deviation at the market opening is not significant. We view these findings as consistent with the specialist argument.     

波动溢出网络视角下全球股市风险传染研究

为刻画全球股票市场风险传染的动态路径特征,从波动溢出网络视角分析全球股票市场的风险传染机制.首先,采用DCC-GARCH动态溢出指数框架来捕捉全球股市波动溢出的动态联动性和风险传染效应;然后,基于方差分解构建信息溢出复杂网络,从网络视角分析全球股票市场的风险传染特征.研究发现,在整个样本期间,全球股票市场高度相互关联,并依赖于极端经济事件;从次贷危机到欧债危机期间全球股市溢出整体呈现减弱态势;近年来国际资本流动、金融开放与国际贸易往来等推动我国股市进程走向新阶段,风险溢出与吸收水平有上升趋势.     

Equity Market Comovement and Contagion: A Sectoral Perspective

This paper takes an asset pricing perspective to investigate the equity market comovement and contagion at the sector level during the period 1990-2004 across the regions of Europe, Asia, and Latin America. It examines whether unexpected shocks from a particular market, or group of markets, are propagated to the sectors in other countries. The results confirm the sector heterogeneity of contagion. This implies that there are sectors that can still provide a channel for achieving the benefits of international diversification during crises despite the prevailing contagion at the market level. In addition, the results lend support to the importance of financial links in the propagation of contagion.     

Emerging Bond Market Volatility and Country Spreads

Using JPMorgan's emerging market bond index, this paper analyzes how increases in country credit spreads can persist in emerging bond markets. The results of T-GARCH regressions show that, during financial crisis periods, emerging countries' credit spreads may increase persistently as a result of interaction between changes in spreads and volatilities, making emerging bond markets more turbulent. The results suggest that emerging countries should endeavor to develop a stabilization mechanism by enhancing information efficiency in bond markets. In particular, because Asian countries have experienced persistent, overreactive volatility, this paper implies that Asian countries should work together more closely during financial crisis periods.     

从利率市场化改革的角度看货币市场波动

虽然2013年6月份的货币市场波动给市场平稳运行造成了一定的冲击,但中央银行对市场流动性有着完全的控制能力.实际上,这是我国全面放开利率之前一次难得的市场演练,对完善货币市场基准利率体系、实现货币政策向价格调控方式转型、提高金融机构风险管理水平,都具有非常深远的意义.此次货币市场波动的经验表明,中央银行要更加重视市场预期管理和与市场的沟通,加强货币政策的透明度与可信性,逐步明确货币市场利率操作目标,建立存贷款便利安排,完善再贷款(再贴现)浮息制度,加强对中小金融机构流动性的制度安排,从而更好地推进金融深层次改革,完善货币调控手段,提高货币政策的有效性.     

The Effect of Market Transparency: Volatility and Liquidity in the Korean Stock Market

Faced with unprecedented competition, stock markets should have fairness and transparency. The effects of market transparency for the stock market volatility and liquidity will be investigated using the case of the Korean stock market. The evidence from this study indicates that increasing the market transparency makes the price discovery process more efficient than before from the viewpoint of stock market volatility, and increases the stock market liquidity compared with before.     

Forecasting Commodity Market Returns Volatility: A Hybrid Ensemble Learning GARCH-LSTM based Approach

This study investigates the advantage of combining the forecasting abilities of multiple generalized autoregressive conditional heteroscedasticity (GARCH)-type models, such as the standard GARCH (GARCH), exponential GARCH (eGARCH), and threshold GARCH (tGARCH) models with advanced deep learning methods to predict the volatility of five important metals (nickel, copper, tin, lead, and gold) in the Indian commodity market. This paper proposes integrating the forecasts of one to three GARCH-type models into an ensemble learning-based hybrid long short-term memory (LSTM) model to forecast commodity price volatility. We further evaluate the forecasting performance of these models for standalone LSTM and GARCH-type models using the root mean squared error, mean absolute error, and mean fundamental percentage error. The results highlight that combining the information from the forecasts of multiple GARCH types into a hybrid LSTM model leads to superior volatility forecasting capability. The SET-LSTM, which represents the model that combines forecasts of the GARCH, eGARCH, and tGARCH into the LSTM hybrid, has shown the best overall results for all metals, barring a few exceptions. Moreover, the equivalence of forecasting accuracy is tested using the Diebold–Mariano and Wilcoxon signed-rank tests.     

基于变结构Copula模型的股市与汇市间波动溢出效应研究

本文采用变结构Copula模型对我国股、汇市间的波动溢出效应进行研究。利用二元正态Copula函数的时变相关系数得出美元对人民币汇率与沪深300指数间相关关系的变结构点,再利用混合Copula模型分段检验波动溢出效应。实证结果表明,汇改以来,美元对人民币汇率与沪深300指数间存在着长期而显著的波动溢出效应。在次贷危机发生期间,美元对人民币汇率与沪深300指数间相关关系的变结构点增多,尾部相关性增强,两市间的波动溢出效应显著增强。因此,应加强对波动溢出传导中介的管理,减轻波动溢出效应的负面影响。