Excess Volatility Research Articles

The Effect of KRX Halts on Overheated Short-selling Stocks

Korea Exchange (KRX) has adopted several measures to ease temporary overheating of short-selling stocks in the market since March 27, 2017. These measures aim to curb excessive volatility and unfair trade, promoting efficient price discovery. This study examines the effect of overheated short-selling halts using the sample data from these KRX measures during the period of September 2017 to October 2019. The major empirical results are: first, the drop in prices of overheated short-selling stocks on a downward trend slows significantly after KRX announcement. Moreover, the stock price rise on the triggering day shows no additional increase in the period after the trigger. Second, for the stocks so triggered, the volatility in the period after the halt announcement shows no significant difference from the pre-halt period. This can be attributed to the resolution of the information asymmetry by calling investors’ attention to overheated short-selling. Third, the ratio of short-selling to trading after halt suggests no statistically significant difference from the period before the trigger. These results imply that the measures to ease overheated short sale of stocks in KRX are effective in controlling excessive temporary volatility and unfair trading.

What to expect when everyone is expecting: Self-fulfilling expectations and asset-pricing puzzles

We study an economy without bubbles in which expectations about future discount rates can become self-fulfilling because asset valuations redistribute wealth across different investor cohorts. For such redistribution to take place, the wealth of arriving and existing cohorts must react differently to discount rates, and in addition only the existing agents are marginal in financial markets. The self-fulfilling nature of discount rate expectations means that the economy can address several well-documented empirical asset-pricing facts (excessive volatility, return predictability, low interest rate level and volatility), while all real quantities (aggregate consumption and dividend growth) are smooth.

Heterogeneous speculators and stock market dynamics: a simple agent-based computational model

We propose a simple agent-based computational model in which speculators’ trading behavior may cause bubbles and crashes, excess volatility, serially uncorrelated returns, fat-tailed return distributions and volatility clustering, thereby replicating five important stylized facts of stock markets. Since each speculator bets on his own (technical and fundamental) trading signals, stock prices are excessively volatile and oscillate erratically around their fundamental value. However, speculators’ heterogeneity occasionally vanishes, e.g. due to panic-induced herding behavior, yielding extreme returns. Lasting regimes with high volatility originate from the fact that speculators extract stronger trading signals out of past stock price movements when stock prices fluctuate strongly. Simulations furthermore suggest that circuit breakers may be an effective tool to combat financial market turbulences.

An empirical examination of investor sentiment and stock market volatility: evidence from India

Understanding the irrational sentiments of the market participants is necessary for making good investment decisions. Despite the recent academic effort to examine the role of investors’ sentiments in market dynamics, there is a lack of consensus in delineating the structural aspect of market sentiments. This research is an attempt to address this gap. The study explores the role of irrational investors’ sentiments in determining stock market volatility. By employing monthly data on market-related implicit indices, we constructed an irrational sentiment index using principal component analysis. This sentiment index was modelled in the GARCH and Granger causality framework to analyse its contribution to volatility. The results showed that irrational sentiment significantly causes excess market volatility. Moreover, the study indicates that the asymmetrical aspects of an inefficient market contribute to excess volatility and returns. The findings are crucial for retail investors as well as portfolio managers seeking to make an optimum portfolio to maximise profits.

DATA MANAGEMENT AS A TOOL FOR ECONOMIC SUSTAINABILITY: APPLICATION TO CURRENCY RISKS OF TECHNOLOGY ENTERPRISE

The global economy is entering into recession and markets excessive volatility. Market disruptions implications would be liquidity loose of enterprises’ balances, eroding assets and turning to losses, supply chains, and operational instability, outplacements, etc. Moreover, exchange rates will fluctuate unpredictable and currency risks will rise. Consequently, these tendencies will lead to the volatility of the currency market as one of the most sensitive parts of the modern economic system. Therefore, it drives a need for looking at the possibilities to apply data management to constant and frequent analysis of distress factors for enterprise economies, such as currency risks, to ensure their sustainability.

Fast and Slow Arbitrage: Fund Flows and Mispricing in the Frequency Domain

We document that hedge-fund and mutual-fund flows drive much of anomaly-return dynamics by, respectively, correcting and amplifying anomalies, and doing so slowly. Indeed, their contributions to the autocorrelation and volatility of anomaly returns add up to 57% over horizons longer than one year, vs. a few percent over shorter horizons. Thus, flows cause long-horizon factor momentum and stock excess volatility, not transient fluctuations. This effect is more pronounced for hedge funds, helmed by fund managers rather than fund investors, and linked to frictions. We address endogeneity concerns and propose a model highlighting the horizon-dependent effects of capital on anomaly-return dynamics.

Stock Characteristics and Individual Herding

Individuals who invest stocks in a market with excess volatility generally end up selling or holding the stocks at losses. The purpose of this study was to examine individual herding as it related to three comprehensible stock characteristics, market capitalization, price-to-book ratio, and industry affiliation. The target population was the individual investors who traded in Taiwan Stock Exchange in 2016. Data were collected through subscription. Based on Lakonishok, Shleifer, and Vishny's measure, individual herding was significant. The three stock characteristics were separately and as a whole related to individual herding. The findings confirmed sell-herding higher than buy-herding, more serious herding in high market capitalization stocks, and broad industry herding. The findings also extended knowledge to comparable herding levels with 8 to 10 years ago, more linearity between log market capitalization and log odds of herd occurrence, and less herding in P/B ratio stocks with other independent variables controlled.

Marketing and financial issues in Iran

Objective: When a financial crisis occurs, speculators typically get the blame whereas fundamentalists are presented as the safeguard against excessive volatility. Methodology: This paper consider two types: speculators and fundamentals who have the same information. Results: In this paper, excess volatility not only exists, but is actually fueled by fundamental trading. Conclusion: Consequently, efficient markets are more volatile with a few speculators than with many speculators and Existence of fundamentals ruins market’s liquidity and this may pose problems for traders, who intend to undertake frequent transactions.

A Counterfactual Economic Analysis of COVID-19 Using a Threshold Augmented Multi-Country Model

This paper develops a threshold-augmented dynamic multi-country model (TGVAR) to quantify the macroeconomic effects of COVID-19. We show that there exist threshold effects in the relationship between output growth and excess global volatility at individual country levels in a significant majority of advanced economies and in the case of several emerging markets. We then estimate a more general multi-country model augmented with these threshold effects as well as long term interest rates, oil prices, exchange rates and equity returns to perform counterfactual analyses. We distinguish common global factors from trade-related spillovers, and identify the Covid-19 shock using GDP growth forecast revisions of the IMF in 2020Q1. We account for sample uncertainty by bootstrapping the multi-country model estimated over four decades of quarterly observations. Our results show that the Covid-19 pandemic will lead to a significant fall in world output that is most likely long-lasting, with outcomes that are quite heterogenous across countries and regions. While the impact on China and other emerging Asian economies are estimated to be less severe, the United States, the United Kingdom, and several other advanced economies may experience deeper and longer-lasting effects. Non-Asian emerging markets stand out for their vulnerability. We show that no country is immune to the economic fallout of the pandemic because of global interconnections as evidenced by the case of Sweden. We also find that long-term interest rates could fall significantly below their recent lows in core advanced economies, but this does not seem to be the case in emerging markets.

Deconstructing Wheat Price Spikes: A Model of Supply and Demand, Financial Speculation, and Commodity Price Comovement

In 2008, wheat futures prices spiked and then crashed along with prices for other agricultural and nonagricultural commodities. Market observers offered several theories to explain this common movement, or comovement, in prices, and have proposed policies to address the perceived problem of excessive price volatility. The design of an appropriate policy response would benefit from a better understanding of the cause of the observed price movements. This study uses an econometric model to decompose observed wheat prices into a set of economic factors and measure the relative contribution of each factor to observed price changes. Findings show that market-specific shocks related to supply and demand for wheat were the dominant cause of price spikes in the three U.S. wheat futures markets. Fluctuations in the global macroeconomy associated with broadbased demand shocks were relatively less significant for wheat than for other commodities like crude oil and corn. Finally, little evidence suggests commodity index trading contributed to recent price spikes.

BREXIT referendum’s impact on the financial markets in the UK

BREXIT might be considered the most paramount event of the past 40 years in modern English history. The present research attempts to examine the impact of BREXIT referendum vote on the British financial markets. The authors examine the impact of money and capital markets on the forex markets in the UK. In their research, they utilize the ECM-Realized-EGARCH model. Their findings support that there is an excess volatility on the GBP after BREXIT vote. In particular, a momentum investing strategy crash led to the excess volatility on the UK financial markets. Finally, they found out that a further devaluation of the GBP is likely, which may lead to an additional decrease of GBP value especially against the euro and the US dollar in the near future after BREXIT.

A Counterfactual Economic Analysis of COVID-19 Using a Threshold Augmented Multi-County Model

This paper develops a threshold-augmented dynamic multi-country model (TGVAR) to quantify the macroeconomic effects of Covid-19. We show that there exist threshold effects in the relationship between output growth and excess global volatility at individual country levels in a significant majority of advanced economies and in the case of several emerging markets. We then estimate a more general multi-country model augmented with these threshold effects as well as long term interest rates, oil prices, exchange rates and equity returns to perform counterfactual analyses. We distinguish common global factors from trade-related spillovers, and identify the Covid-19 shock using GDP growth forecast revisions of the IMF in 2020Q1. We account for sample uncertainty by bootstrapping the multi-country model estimated over four decades of quarterly observations. Our results show that the Covid-19 pandemic will lead to a significant fall in world output that is most likely long-lasting, with outcomes that are quite heterogeneous across countries and regions. While the impact on China and other emerging Asian economies are estimated to be less severe, the United States, the United Kingdom, and several other advanced economies may experience deeper and longer-lasting effects. Non-Asian emerging markets stand out for their vulnerability. We show that no country is immune to the economic fallout of the pandemic because of global interconnections as evidenced by the case of Sweden. We also find that long-term interest rates could fall significantly below their recent lows in core advanced economies, but this does not seem to be the case in emerging markets.

Impact of FOMC Cycle on Market Uncertainty: Evidence From Interest Rate Derivatives

This paper investigates how Federal Reserve (Fed) actions influence market uncertainty. We consider two kinds of Fed events: the day of the Federal Open Market Committee (FOMC) meeting -- which includes a policy statement, press conference and release of a Summary of Economic Projections -- and the day the minutes of the FOMC minutes are released -- which is typically set 3 weeks after the meeting. Unlike related papers focused on the issue, we measure market uncertainty by the implied volatility extracted from interest rate options, specifically swaptions. We use 1-month constant maturity volatility for swaptions over tenors ranging from one up to 30 years as they are reflective of how these volatilities are marked by dealers/market-makers and cover only one FOMC meeting/minutes release at a time. We use an event study approach along with extensive graphical analysis to evaluate the impact of Fed actions. The results show that 1-month constant maturity implied volatility increases marginally going into these events and falls much more significantly afterwards. Remarkably, the increase and reduction in uncertainty around a meeting is not reducing with increasing tenors, showing that the impact of information release has a similar impact over all horizons ranging from 1 to 30 years. If, on one side, this evidence witnesses the capacity of the central bank to control the long end of the curve, on the other it indicates the possibility that overreaction to news may generate the puzzling excess volatility which is observed in long term rates.

On the Price Dynamics of a Two-Dimensional Financial Market Model with Entry Levels

This paper aims to extend the model developed by Tramontana et al. By adding trend followers who pay attention to the most recent observed price trend, we formulate a financial market model driven by a new two-dimensional discontinuous piecewise linear (PWL) map with three branches. The dynamic behavior of the mapping system is studied in two cases according to different trend followers’ expectation of the stock price. The existence and stability conditions of periodic attractors and other bounded attractors are derived by using qualitative and quantitative methods, theoretical analysis, and numerical simulation. When trend followers are neutral on the stock market, we present that the basin of locally attracting fixed points can be determined by the preimages of two borderlines. We also prove that one of its surprising features is that model simulations may appear to be chaotic, although only regular dynamics can emerge. When trend followers are bullish or bearish on the stock market, we present the existence conditions of attracting coexistence fixed point, globally and locally attracting fixed point, and periodic and other bounded attractors. The transversal homoclinic theory of flip saddle periodic point is applied to prove the existence of chaotic attractor. We also give the calculation methods of border collision bifurcation (BCB) curves. This paper advances our knowledge of discontinuous PWL systems and reveals the endogenous evolution of bubbles and crashes and excessive volatility in financial markets from a new perspective with new methods.

ENDOGENOUS PARTICIPATION, RISK, AND LEARNING IN THE STOCK MARKET

A simple asset pricing model with both endogenous stock market participation and subjective risk can explain the negative cross-country correlation between participation rates and the volatility of excess returns, along with the time-varying participation rates in the data. Belief-driven learning dynamics can explain the interplay between participation rates, subjective risk, and stock price volatility. When agents adaptively learn about the risk and return, my model generates 25% of the excess volatility observed in US stock prices, while also matching key moments. With learning about risk, excess volatility of stock prices is driven by fluctuations in the participation rate that arise because agents’ risk estimates vary with prices. I find that learning about risk is quantitatively more important than learning about returns.

The Response of Arab Region to Overcome Global Financial Crisis

The main objective of this study is to analyze the policies adopted by Arab countries to recover from the global financial crisis (GFC) in 2008. The study highlights the fiscal and monetary policies that were applied by Arab countries to maintain economic activity. The study shows that Arab countries primarily relied on a mix of fiscal policies to stimulate the economy. As a result, the accumulated oil revenues enabled them to respond quickly, preventing a deeper deceleration in growth and also supporting a growth rebound. However, for countries with limited fiscal space, macroeconomic and oil revenue management became more challenging. Strategies aimed at increasing non-oil sources of growth are recommended to help reduce the vulnerability of these countries to excessive oil price volatility. JEL Classifications: E520, E620, O40, P470

Multiple subordinated modeling of asset returns: Implications for option pricing

Motivated by behavioral finance, we introduce multiple embedded financial time clocks. Consistent with asset pricing theory in analyzing equity returns, the investors’ view is considered by introducing a behavioral subordinator. Subordinating to the Brownian motion process in the log-normal model results in a new log-price process whose parameter is as important as the mean and variance. We describe new distributions, demonstrating their use to model tail behavior. The models are applied to S&P 500 returns, treating the Chicago Board Options Exchange (CBOE) volatility index (VIX) as intrinsic-time change and CBOE Volatility-of-Volatility Index as the volatility subordinator. We find these volatility indexes fail as time-change subordinators. We employ a double subordinator model to explain the equity premium puzzle and the excess volatility puzzle. The results indicate the puzzles can be explained by fitting a double subordinator model to the historical data.

Duration-Based Stock Valuation

Using a panel of international government bond data, I construct fixed income portfolios that match the duration of the dividend strips of the local aggregate stock market index. I find that these bond portfolios have performed as well as their stock counterparts in the past half century while exhibiting similar (and often higher) levels of volatility. These results provide a novel perspective on both the equity risk premium and excess volatility puzzles (bubbles). I present several potential explanations, and discuss further the implications for macroeconomics, monetary economics, asset pricing, and corporate finance. The results cannot be explained away by net stock repurchases or inflation.

Spontaneous Volatility: Fooled by Reflexive Randomness

We draw a parallel between noise trading and the “readiness potential” in neuroscience. The latter can be explained in terms of neuronal noise accumulation which can tip the scale ahead of voluntary actions, in particular their timing in situations of weak evidence. This principle may apply to trading by technical noise traders. Based on our initial findings we propose that excess volatility, as a measure of price noise, indirectly reflects the signature of collective neuronal noise. In other words, we’ve potentially identified an internal contributor to Black’s “cumulative noise”, with neurons and prices reflexively participating in a joint random walk.

Asset Pricing with Ambiguous Signals: An Experiment

This paper explores how ambiguous signals and ambiguity aversion influence individuals' expectations and the pricing of asset in experimental financial markets. In line with the theory of Epstein and Schneider (2008) we find that subjects' degree of ambiguity aversion is positively correlated with their expectations about the variance of ambiguous signals. These signals matter for the determination of asset prices. We find that the distribution of the excess return of the asset exhibits negative skewness, and that price volatility is significantly larger under ambiguous signals. Our findings provide evidence in support of the idea that ambiguous information and ambiguity aversion may be a source of negative skewness and excess volatility in financial markets.