Market Crashes and Informational Avalanches

This paper analyses a security market with transaction costs and a sequential trading structure. Transaction costs may prevent many traders from revealing their private information if they trade in a sequential fashion. Due to the information aggregation failure, hidden information gets accumulated in the market which may be revealed by a small trigger, yielding a high volatility in the absence of an accompanying event. The paper first characterizes the optimal trading strategy of the agent which constitute the unique equilibrium. Further properties of the price sequence are obtained using the concepts of informational cascade and informational avalanche.
The results are applied to the explanation of market crashes. In particular, the dynamics of market crashes are illustrated as evolving through the following four phases: (1) boom; (2) euphoria; (3) trigger; and (4) panic; where the euphoria corresponds to the informational cascade and the panic corresponds to the informational avalanche.     

Volatility and Market Risk of Rubber Price in Malaysia: Pre- and Post-Global Financial Crisis

The volatility in rubber price is a significant risk to producers, traders, consumers and others who are involved in the production and marketing of natural rubber. Such being the case, forecasting the rubber price volatility is desired to assist in decision-making in this uncertain situation. The 2008 Global Financial Crisis caused some disruptions and uncertainties in the future supply or demand for natural rubber and thus leading to higher rubber price volatility. Using ARCH-type models, this paper intends to model the dynamics of the price volatility of Standard Malaysia Rubber Grade 20 (SMR 20) in the Malaysian market before and after the Global Financial Crisis. Additionally, Value-at-Risk (VaR) approach is implemented to evaluate the market risk of SMR 20. Our empirical result denotes the existence of volatility clustering and long memory volatility in the SMR 20 market for both crisis periods. Leverage effect is also detected in the SMR 20 market where negative innovations (bad news) have a larger impact on the volatility than positive innovations (good news) for post-crisis period. When tested with Superior Predictive Ability (SPA) test, FIGARCH model is the best model across five loss functions for short- and long-term forecasts for pre-crisis period. Meanwhile, over post-crisis period, FIGARCH and GJR GARCH indicate the superior out-of-sample-forecast results and better forecasting accuracy over short- and long-term horizons, respectively. In terms of market risk, the short trading position encounters higher risk or greater losses than the long trading position at both 1 and 5 % VaR quantile for pre-crisis period. In contrast, over post-crisis period, long traders of rubber SMR 20 tend to face limited gains but unlimited losses.

     

Price Limits, Information Acquisition, and Bid–ask Spreads: Theory and Evidence

A number of futures markets use price limits which, in effect, preclude trade from occurring at prices outside certain exogenous bounds. Noting that such markets are characterized by heterogeneously informed traders, whereas previous work on price limits assumes symmetrically informed traders, we examine the effects of price limits in a setting where market participants are asymmetrically informed. We find that imposing price limits generally lowers the quality of information acquired in equilibrium, but lowers bid–ask spreads as well. Thus, depending on the relative weights placed by society on liquidity versus price efficiency, there may exist a set of price limits that are most efficient in achieving a trade-off between liquidity and informational efficiency. We perform empirical tests of some implications of the model using cross-sectional data on price limits. We find that price limits are strongly negatively related to both price volatility and trading volume. Though other explanations for our empirical findings cannot be ruled out, these results are not inconsistent with the model's implication that price limits should be tighter for contracts which offer greater profit potential for informed traders.     

The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method

A recent strand in the literature emphasizes the role of news-based economic policy uncertainty (EPU) and equity market uncertainty (EMU) as drivers of oil price movements. Against this backdrop, this paper uses a kth-order nonparametric quantile causality test, to analyse whether EPU and EMU predict stock returns and volatility. Based on daily data covering the period of 2 January 1986 to 8 December 2014, we find that, for oil returns, EPU and EMU have strong predictive power over the entire distribution barring regions around the median, but for volatility, the predictability virtually covers the entire distribution, with some exceptions in the tails. In other words, predictability based on measures of uncertainty is asymmetric over the distribution of oil returns and its volatility.     

Two-sided competition with vertical differentiation

This paper studies duopoly in which two-sided platforms compete in differentiated products in a two-sided market. Direct competition on both sides leads to results that depart from much of the current literature. Under some conditions the unique equilibrium in pure strategies can be computed. It features discounts on one side and muted differentiation as the cross-market externality intensifies competition. Less standard, that equilibrium fails to exist when the externality is too powerful (that side becomes too lucrative). A mixed-strategy equilibrium always exists and is characterized. These results are robust to variations in the extensive form. The model may find applications in the media, internet trading platforms, search engine competition, social media or even health insurance (HMO/PPO).     

Volatility–volume co-movements: evidence from China metal markets

This article investigates the interactional relationship between price volatility and futures trading activity for three heavily traded metal products on the Shanghai Metal Exchange and the Shanghai Futures Exchange. Using models based on vector autoregression and generalized method of moments, we show, in particular, that futures trading activity has a strong impact on both spot and futures price volatility in copper and aluminium markets. Futures trading activity leads spot market volatility in copper and aluminium markets which suggests that futures markets have a destabilizing effect. In order to disentangle the effect of different traders’ types on asset price movements, we decompose futures trading into speculators’ and hedgers’ trading and investigate their contributions to volatility. As a robustness check, we investigate the impact of endogenous structural breaks on the interactional relationship between price volatility and futures trading.     

ADAPTIVE EXPECTATIONS AND STOCK MARKET CRASHES*

A theory is developed that explains how stocks can crash without fundamental news and why crashes are more common than frenzies. A crash occurs via the interaction of rational and naive investors. Naive traders believe that prices follow a random walk with serially correlated volatility. Their expectations of future volatility are formed adaptively. When the market crashes, naive traders sell stock in response to the apparent increase in volatility. Since rational traders are risk averse as well, a lower price is needed to clear the market: The crash is a self‐fulfilling prophecy. Frenzies cannot occur in this model.     

Timing under individual evolutionary learning in a continuous double auction

The moment of order submission plays an important role for the trading outcome in a Continuous Double Auction; submitting an offer at the beginning of the trading period may yield a lower profit, as the trade is likely to be settled at the own offered price, whereas late offers result in a lower probability of trading. This timing problem makes the order submission strategy more difficult. We extend the behavioral model of Individual Evolutionary Learning to incorporate the timing problem and study the limiting distribution of submission moments and the resulting offer function that maps submission moments to offers. We find that traders submit different offers at different submission moments the distribution of which uni-modal with a peak moving from late to early as the market size increases. This behavior exacerbates efficiency loss from learning. If traders evaluate profitability of their strategies over longer history, orders are submitted later with the same effect of market size.     

Order aggressiveness and order book dynamics

In this paper, we study the determinants of order aggressiveness and traders’ order submission strategy in an open limit order book market. Applying an order classification scheme, we model the most aggressive market orders, limit orders as well as cancellations on both sides of the market employing a six-dimensional autoregressive conditional intensity model. Using order book data from the Australian Stock Exchange, we find that market depth, the queued volume, the bid-ask spread, recent volatility, as well as recent changes in both the order flow and the price play an important role in explaining the determinants of order aggressiveness. Overall, our empirical results broadly confirm theoretical predictions on limit order book trading. However, we also find evidence for behavior that can be attributed to particular liquidity and volatility effects.

Taxation and the sustainability of collusion: ad valorem versus specific taxes

Assuming constant marginal cost, it is shown that a switch from specific to ad valorem taxation that results in the same collusive price has no effect on the critical discount factor required to sustain collusion. This result is shown to hold for Cournot oligopoly when collusion is sustained with Nash-reversion strategies or optimal-punishment strategies. In a Cournot duopoly model with linear demand and quadratic costs, it is shown that the critical discount factor is lower with an ad valorem tax than with a specific tax that results in the same collusive price. However, in contrast to Colombo and Labrecciosa (J Public Econ 97:196–205, 2013) it is shown that the revenue is always higher with an ad valorem tax than with a specific tax.     

Market for Information and Identity Disclosure in an Experimental Open Limit Order Book

This paper analyses the effects of pre‐trade transparency on market quality in an experimental open limit order book preceded by a market for information. The design of the trading game is akin to the system in use in an increasing number of financial markets. We find that the disclosure of traders' identities reduces the incentive to acquire information, liquidity and volatility. We also show that a positive relation exists between the proportion of traders buying information and liquidity. The results are consistent with a standard model of price formation where the number of informed traders is endogenous .     

Rational panics and stock market crashes

This paper offers an explanation for stock market crashes which focuses on the role of rational but uninformed traders. We show that uninformed traders can precipitate a price crash because as prices decline, they surmise that informed traders received negative information, which leads them to reduce their demand for assets and drive the price of stocks even lower. The model yields several implications, such as that crashes can occur even when the fundamentals are strong, and that the magnitude of the crash depends on the fraction of uninformed investors and the amount of unsophisticated passive investing present in the market.     

Order Flows,Investor Sentiments and Feedback Trade in Index Futures Market

This paper examines the presence of feedback trading, and investor sentiment drove feedback trading by traders in the Nifty 50 index futures contract in India. The results of the study using high-frequency data sampled at 10 min interval using VAR and contemporaneous VAR model as applied to market microstructure settings reveals negative evidence of feedback trade and investor sentiment-driven feedback trade in Nifty 50 futures contract. Further, consistency with noise trading hypothesis, order flows in Nifty 50 futures contract is less informative when traders are overly optimistic.

     

Short-term investment and equilibrium multiplicity

I study the effects of the heterogeneity of traders’ horizons in a 2-period NREE model where all traders are risk averse. Owing to risk premia, short-termism generates multiple equilibria. In particular two distinct patterns arise. Along the “low trading intensity equilibrium,” short termists anticipate a thinner second period market and, owing to risk aversion, scale back their trades. This reduces both risk sharing and information impounding into prices, enforcing a high returns’ volatility-low price informativeness equilibrium. Along the “high trading intensity equilibrium,” the opposite happens and a low volatility-high price informativeness equilibrium arises. Thus, in the presence of short-term behavior and traders’ risk aversion, periods of high volatility are a signal of poor price informativeness.     

THE DYNAMIC RELATION BETWEEN RETURNS,TRADING VOLUME,AND VOLATILITY: LESSONS FROM SPILLOVERS BETWEEN ASIA AND THE UNITED STATES

This paper investigates the dynamic relationship between index returns, return volatility, and trading volume for eight Asian markets and the US. We find cross‐border spillovers in returns to be non‐existent, spillovers in absolute returns between Asia and the US to be strong in both directions, and spillovers in volatility to run from Asia to the US. Trading volume, especially on the Asian markets, depends on shocks in domestic and foreign returns as well as on volatility, especially those shocks originating in the US. However, only weak evidence is found for trading volume influencing other variables. In the light of the theoretical models, these results suggest sequential information arrivals, with investors being overconfident and applying positive feedback strategy. Furthermore, new information causes price volatility to rise due to differences in its interpretation among traders, but the subsequent market reaction takes the form of adjustment in price level, not volatility. Lastly, the intensity of cross‐border spillovers seems to have increased following the 1997 crisis, which we interpret as evidence of increased noisiness in prices and diversity in opinions about news originating abroad. Our findings might also help to understand the nature of financial crises, to predict their further developments and consequences.     

Loss aversion and market crashes

This study proposes a rational expectation equilibrium model of stock market crashes with information asymmetry and loss averse speculators. We obtain a state-dependent linear optimal trading strategy, which makes the equilibrium price tractable. The model predicts nonlinear market depth and the result that small shocks to fundamentals (e.g., supply or informational shocks) can cause abrupt price movements. We demonstrate that short-sale constraints intensify asset price collapses relative to upward movements. The model also generates contagion between uncorrelated assets. These results are consistent with the main puzzling features observed during market crashes, namely abrupt and asymmetric price movements that are not driven by major news events but coupled with a spillover effect between unrelated markets.     

Market Dynamics,Programmed Traders and Futures Markets: Beginning the Laboratory Search for a Smoking Gun

Recent events have caused a re-examination of the role of programmed traders and futures markets in generating destabilizing price movements. Laboratory experiments provide an ideal environment to isolate their effects on behaviour. In a new series of experiments we find that program traders and futures markets can be crucial for ensuring the informational efficiency of the spot market, even when the former are active participants in bubbles and crashes     

Efficiency of continuous double auctions under individual evolutionary learning with full or limited information

In this paper we explore how specific aspects of market transparency and agents’ behavior affect the efficiency of the market outcome. In particular, we are interested whether learning behavior with and without information about actions of other participants improves market efficiency. We consider a simple market for a homogeneous good populated by buyers and sellers. The valuations of the buyers and the costs of the sellers are given exogenously. Agents are involved in consecutive trading sessions, which are organized as a continuous double auction with order book. Using Individual Evolutionary Learning agents submit price bids and offers, trying to learn the most profitable strategy by looking at their realized and counterfactual or “foregone” payoffs. We find that learning outcomes heavily depend on information treatments. Under full information about actions of others, agents’ orders tend to be similar, while under limited information agents tend to submit their valuations/costs. This behavioral outcome results in higher price volatility for the latter treatment. We also find that learning improves allocative efficiency when compared to outcomes with Zero-Intelligent traders.     

On the Stochastic Properties of Carbon Futures Prices

Pricing carbon is a central concern in environmental economics, due to the worldwide importance of emissions trading schemes to regulate pollution. This paper documents the presence of small and large jumps in the stochastic process of the CO $_2$ futures price. The large jumps have a discrete origin, i.e. they can arise from various demand factors or institutional decisions on the tradable permits market. Contrary to the existing literature, we show that the stochastic process of carbon futures prices does not contain a continuous component (Brownian motion). The results are derived by using high-frequency data in the activity signature function framework (Todorov and Tauchen in J Econom 154:125–138, 2010; Todorov and Tauchen in J Bus Econ Stat 29:356–371, 2011). The implication is that the carbon futures price should be modeled as an appropriately sampled, centered Lévy or Poisson process. The pure-jump behavior of the carbon price might be explained by the lower volume of trades on this allowance market (compared to other highly liquid financial markets).     

卖空机制、股价信息含量与暴跌风险--基于融资融券交易的经验证据

文章利用我国逐步推出融资融券交易的自然实验机会,运用双重差分的研究设计,考察了卖空机制对股价反映负面消息效率的影响。文章以2007-2012年的数据为样本研究发现：相对于非标的股票,融资融券标的股票在成为标的之后,其股价对市场的向下波动及时做出了调整,使得股价对市场正负向波动反应之间的不对称性显著降低,表明标的股票更加及时和充分地吸收了有关公司价值的负面信息;同时,相对于非标的股票,融资融券标的标的股票在成为标的之后,其股价暴跌风险显著降低。文章结果表明,我国股市推出融资融券交易后,卖空机制提高了市场对标的股票负面消息的定价效率。