Computing the market price of volatility risk in the energy commodity markets

In this paper, we demonstrate the need for a negative market price of volatility risk to recover the difference between Black–Scholes [Black, F., Scholes, M., 1973. The pricing of options and corporate liabilities. Journal of Political Economy 81, 637–654]/Black [Black, F., 1976. Studies of stock price volatility changes. In: Proceedings of the 1976 Meetings of the Business and Economics Statistics Section, American Statistical Association, pp. 177–181] implied volatility and realized-term volatility. Initially, using quasi-Monte Carlo simulation, we demonstrate numerically that a negative market price of volatility risk is the key risk premium in explaining the disparity between risk-neutral and statistical volatility in both equity and commodity-energy markets. This is robust to multiple specifications that also incorporate jumps. Next, using futures and options data from natural gas, heating oil and crude oil contracts over a 10 year period, we estimate the volatility risk premium and demonstrate that the premium is negative and significant for all three commodities. Additionally, there appear distinct seasonality patterns for natural gas and heating oil, where winter/withdrawal months have higher volatility risk premiums. Computing such a negative market price of volatility risk highlights the importance of volatility risk in understanding priced volatility in these financial markets.     

Local investors,price discovery,and market efficiency

This study examines the effect of locally informed investors on market efficiency and stock prices using large power outages, which are exogenous events that constrain trading. Turnover in stocks headquartered in an outage area with 0.5% of U.S. electrical customers drops by 3–7% on the first full day of the outage, and bid–ask spreads narrow by 2.5%. Firm-specific price volatility is 2.3% lower on blackout dates. This effect is larger for smaller, lesser-known stocks and in higher income areas. Consistent with a valuation discount and higher expected returns for stocks with more informed traders, firms with a one-standard-deviation higher local trading propensity have market-to-book values that are 5% lower, Tobin's Q that is 6% lower, annualized four-factor alphas that are 1.2% higher, and average spreads that are 6.5% higher. Together, the evidence suggests that informed investors contribute disproportionately to both liquidity and price discovery, and that these contributions are reflected in valuations and expected returns.     

The price discovery of day trading activities in futures market

Access to information is necessary for market transparency. However, contrary to trading volume and open interest, information related to day trading activities is rarely available. By incorporating unexplored day trading volume in the literature, this paper demonstrates that both the expected open interest and expected day trading volume are consistently and positively correlated with returns, but that one-lagged day trading volume is negatively correlated with futures returns. Meanwhile, both expected and unexpected day trading volume are negatively correlated with volatility, suggesting that arbitrage activities related to unexpected day trading volume may accelerate the movement of futures prices to a new equilibrium. Moreover, open interest provides liquidity but increases volatility. Finally, we strongly suggest that day trading transaction information be released by futures exchanges to achieve greater transparency.     

Macroeconomic announcements and price discovery in the foreign exchange market

This study shows that the dominance of the overlapping trading hours of London and New York in the price discovery of the EUR/USD and USD/JPY markets only applies on days with U.S. announcements. Different from Cai et al. (2008) and Wang and Yang (2011), we highlight the informational advantage of local traders at the arrival of macroeconomic announcements in the local market, and find that macroeconomic announcements affect the pattern of price discovery across different markets, consistent with Chen and Gau (2010) and Jiang et al. (2012). We also examine changes in information shares before and after the announcement. A significant increase in price discovery before the announcement suggests the possibility of information leakage, while enhanced price discovery efficacy after the announcement suggests that prices gradually adjust to new information, not just immediately respond to the arrival of announcements.     

A structural analysis of price discovery measures

We analyze the structural determinants of two widely used measures of price discovery between multiple markets that trade closely related securities. Using a structural cointegration model, we show that both the information share (IS) and component share (CS) measures account for the relative avoidance of noise trading and liquidity shocks, but that only the IS can provide information on the relative informativeness of individual markets. In particular, the IS of one market is higher if it incorporates more new information and/or impounds less liquidity shocks. Use of the CS in conjunction with the IS can help sort out the confounding effects of the two types of shocks. Furthermore, we find that the IS only accounts for the immediate (one-period) responses of market prices to the news innovation, which implies that the IS estimates based on high sampling frequencies may be distorted by transitory frictions and may miss important price discovery dynamics.     

The role of market expectations in commodity price dynamics: Evidence from oil data

This paper examines the contribution of market expectations to commodity price dynamics. It proposes a dynamic competitive storage framework with an explicit expectations shock along with concurrent shocks to study the commodity price movements. This allows for a refined analysis of the expectations’ effect on price and inventory and the estimation of the expectations. Applied to the world crude oil market, it finds that the contribution of market expectations to the crude oil spot price movements is limited from 1987 to 2014.     

Time-variations in commodity price jumps

In this paper, we study jumps in commodity prices. Unlike assumed in existing models of commodity price dynamics, a simple analysis of the data reveals that the probability of tail events is not constant but depends on the time of the year, i.e. exhibits seasonality. We propose a stochastic volatility jump–diffusion model to capture this seasonal variation. Applying the Markov Chain Monte Carlo (MCMC) methodology, we estimate our model using 20 years of futures data from four different commodity markets. We find strong statistical evidence to suggest that our model with seasonal jump intensity outperforms models featuring a constant jump intensity. To demonstrate the practical relevance of our findings, we show that our model typically improves Value-at-Risk (VaR) forecasts.     

Understanding international commodity price fluctuations

An overview is provided of recent work on commodity prices, focusing on three themes: (i) "financialization" of commodity markets--commodities being considered by financial investors as a distinct asset class, (ii) trends and forecasts of commodity prices, and (iii) fracking—a shorthand for the emergence of new sources of energy supply. Lessons are drawn on the role of fundamentals and expectations in driving the rapidly changing nature of commodity markets.     

Trading frequency and the efficiency of price discovery in a non-dealer market

The increasing popularity of non-dealer security markets that offer automated, computer-based, continuous trading reflects a presumption that institutionally-set trading sessions are economically obsolete. This theoretical paper investigates the effect of the trading frequency, a key feature of the trading mechanism, on the efficiency of price discovery in a non-dealer market. By tracing the market pricing error to the correlation structures of arriving information and pricing errors of individual traders, the effect of diverging expectations on error-based and overall return volatility is isolated. The analysis reveals that, due to a portfolio effect, an increase in the trading time interval has contradictory effects on the portion of return volatility stemming from pricing errors. The greater accumulation of information increases error-based return volatility, but the greater volume and number of traders per session have the opposite effect. The net effect on overall return volatility can go either way. It is found that the return volatility of heavily traded securities is likely to be minimized under continuous trading, but that of thinly traded securities may be minimized under discrete trading at moderate time intervals. The latter is more likely to occur the greater is the divergence of expectations among traders. These findings challenge the presumption that automated continuous trading in a non-dealer market is more efficient than discrete trading for all securities, regardless of trading volume. The findings are applicable to all economies, but have special importance for developing countries where typically a single market is dominated by small issues and a low volume of trade. As a by-product of the analysis, it is shown how to correct the biased estimate of inter-session price volatility when observations are less frequent than the trading sessions themselves.     

Dynamic price discovery

This article analyzes the dynamic process of price discovery in a competitive securities market where investors are equally informed about the fundamental determinants of an asset's end-of-period value but, because they do not know each other's wealth positions, do not know the equilibrium price of shares at the start of a current trading session. Because a large number of participants is assumed, issues concerning market impact and market manipulation are avoided. As trading progresses, participants update their expectations of an asset's equilibrium value. As they do so, price can either converge to a new level or, following a run, revert back to a previous level. This implies that, in clusters of adjacent prices, price changes are more apt to be predominantly of like sign (positive or negative) than would be the case under random walk with a bid-ask spread. Moreover, reversals, when they do occur, should be larger than continuations. An examination of 1988 transactions data for the 30 Dow Jones Industrial stocks shows that this is indeed the case. With the effect of the bid-ask spread removed, first-order autocorrelation coefficients are found to be positive.     

The complexity of price discovery in an efficient market: the stock market reaction to the Challenger crash

We provide evidence on the speed and accuracy of price discovery by studying stock returns and trading volume surrounding the crash of the space shuttle Challenger. While the event was widely observed, it took several months for an esteemed panel to determine which of the mechanical components failed during the launch. By contrast, in the period immediately following the crash, securities trading in the four main shuttle contractors seemingly singled out the firm that manufactured the faulty component. We show that price discovery occurred without large trading profits and that much of the price discovery occurred during a trading halt of the firm responsible for the faulty component. Finally, although we document what are arguably quick and accurate movements of the market, we are unable to detect the actual manner in which particular informed traders induced price discovery.     

Measuring time-varying financial market integration: An unobserved components approach

We measure the time-varying degree of world stock market integration of five developed countries (Germany, France, UK, US, and Japan) over the period 1970:1–2011:10. Time-varying financial market integration of each country is measured through the conditional variances of the country-specific and common international risk premiums in equity excess returns. The country-specific and common risk premiums and their conditional variances are estimated from a latent factor decomposition through the use of state space methods that allow for GARCH errors. Our empirical results suggest that stock market integration has increased over the period 1970:1–2011:10 in all countries but Japan. And while there is a structural increase in stock market integration in four out of five countries, all countries also exhibit several shorter periods of disintegration (reversals), i.e. periods in which country-specific shocks play a more dominant role. Hence, stock market integration is measured as a dynamic process that is fluctuating in the short run while gradually increasing in the long run.     

Private information flow and price discovery in the U.S. treasury market

Using intraday data, we identify the intensity of private information flow in the U.S. Treasury market. Our results show that the intensity of private information flow is highly correlated with public information shocks and higher for longer maturity bonds. More importantly, we find that bond price changes associated with high intensity of private information flow tend to be persistent, whereas those associated with low intensity of private information flow are more likely reversed. While public information and private information are the main determinants of bond price variations on days with news announcements, private information and liquidity shocks are important determinants of bond price variations on days with no significant events. Finally, we show that the depth of limit order book is inversely related to the intensity of private information flow. Nevertheless, informed dealers do not seem to use hidden orders to disguise their trading intentions.     

商品市场的金融化与油价泡沫

在过去几年中,商品市场发生了巨大的变化。衍生品交易量大幅度超过了实物的产量,而在衍生品市场中,金融机构已经取代了传统的商品买家和卖家,成为了市场的主动性力量。商品市场这种＂金融化＂现象改变了商品价格的形成机制。以油价为例,实证分析表明,自2003年以来油价的暴涨,其系统性的推动因素就在于石油衍生品市场金融机构过于活跃、甚至是投机性质的交易行为。     

Trending time-varying coefficient market models

In this paper we study time-varying coefficient (beta coefficient) models with a time trend function to characterize the nonlinear, non-stationary and trending phenomenon in time series and to explain the behavior of asset returns. The general local polynomial method is developed to estimate the time trend and coefficient functions. More importantly, a graphical tool, the plot of the kth-order derivative of the parameter versus time, is proposed to select the proper order of the local polynomial so that the best estimate can be obtained. Finally, we conduct Monte Carlo experiments and a real data analysis to examine the finite sample performance of the proposed modeling procedure and compare it with the Nadaraya–Watson method as well as the local linear method.     

Adverse selection costs,trading activity and price discovery in the NYSE: An empirical analysis

This paper studies the role that trading activity plays in the price discovery process of a NYSE-listed stock. We measure the expected information content of each trade by estimating its permanent price impact. It depends on observable trade features and market conditions. We also estimate the time required for quotes to incorporate all the information content of a particular trade. Our results show that price discovery is faster after risky trades and also at the extreme intervals of the session. The quote adjustment to trade-related shocks is progressive and this causes risk persistency and unusual short-term market conditions.     

Trading costs and price discovery

The price discovery roles of a set of related markets or securities have been investigated in many different settings where trading costs effect is often commingled with other trading arrangement factors. In Hong Kong, regular futures and mini futures contracts as well as their underlying spot asset are all traded on a same electronic trading platform. The trading arrangements thus provide us with a unique setting where we can isolate the impacts of transaction costs on price discovery. Using Hasbrouck’s (J Finance 50:1175–1199, 1995) information share approach, it is found that in Hong Kong, the regular futures contracts market plays a dominant role in price discovery while the mini futures and cash index markets play minor roles. The results in this paper provide an unequivocal support to the trading costs hypothesis.     

Oil commodity returns and macroeconomic factors: A time-varying approach

This paper analyses the dynamic influence of macroeconomic factors on oil commodity returns (crude oil and heating oil) shown in monthly data over the period of 1990–2013. Using a time-varying parameter model via the Kalman filter, we find that macroeconomic factors are relevant for explaining oil commodity returns. We find that multilateral exchange rates have a negative effect on commodity returns. We confirm the existence of a strong linkage between energy and non-energy commodities. More importantly, we find shifts in global demand and SP500 effects that are not identified through the constant parameter model. These variables have had a progressively positive effect on oil commodity returns, especially since 2008.     

Financial analysts and price discovery

We show that whether or not a bank/brokerage firm has top‐rated financial analysts and high Wall Street Search rankings for their research is significantly related to that firm's contribution to price discovery, the process by which information is incorporated into stock prices. Our study relates cross‐sectional characteristics of the quality of brokerage research, the asymmetric information environment, and order flow volume to a microstructure measure of price discovery developed by Granger and Gonzalo. We measure analysts’ research quality with an industry‐specific ranking by institutional investors, with an opinion survey of trading desk personnel, and with the number of top 3 analysts across all industries employed by the bank/brokerage firm.     

The speed of stock price discovery

We develop closed-form expressions for the path and speed of stock price discovery in a utility-based CAPM with wealth effects. Two investors with uniquely bounded risk-preferences always apply opposite portfolio rebalancing trades. These trades determine the intra-period path and speed of price discovery in a Walrasian, tâtonnement setup. While conditions for maximum speed exist, convergence is rapid over a wide range of endowments and preferences. Convergence to equilibrium is exponential, and its speed depends on endowments, risk-preferences, firm size, and market price for risk. Convergence is not guaranteed, and the conditions for divergence are specified.