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.     

Futures Trading Activity and Commodity Cash Price Volatility

Abstract:   This paper examines the lead‐lag relationship between futures trading activity (volume and open interest) and cash price volatility for major agricultural commodities. Granger causality tests and generalized forecast error variance decompositions show that an unexpected increase in futures trading volume unidirectionally causes an increase in cash price volatility for most commodities. Likewise, there is a weak causal feedback between open interest and cash price volatility. These findings are generally consistent with the destabilizing effect of futures trading on agricultural commodity markets.     

Futures-Trading Activity and Stock Price Volatility

We examine whether greater futures-trading activity (volume and open interest) is associated with greater equity volatility. We partition each trading activity series into expected and unexpected components, and document that while equity volatility covaries positively with unexpected futures-trading volume, it is negatively related to forecastable futures-trading activity. Further, though futures-trading activity is systematically related to the futures contract life cycle, we find no evidence of a relation between the futures life cycle and spot equity volatility. These findings are consistent with theories predicting that active futures markets enhance the liquidity and depth of the equity markets.     

From pit to electronic trading: Impact on price volatility of U.S. Treasury futures

This paper investigates the dynamics of price volatility and trading volume of 10-year U.S. Treasury note futures within the context of transition from pit to electronic trading. The analysis is conducted over four discernible phases of futures trading evolution: the pit-only phase, the leap to electronic trading, and the electronic trading dominant phase, which is divided further into two periods, the before and after the financial crisis of 2007/2009. Generalized autoregressive conditional heteroskedasticity with in-mean conditional variance and generalized error distribution parameterization (GARCH-M-GED) tests are conducted to examine the conditional volatility of total returns index as a function of trading volume. The empirical results show a consistently negative relationship between the trading volume and price volatility for all four analyzed phases. They also show decreasing leptokurtosis (except for the direct effects of the recent crisis), continuously high persistency in volatility, as well as a weakening impact of unexpected ARCH-type shocks during the most recent analyzed period. Overall, the shift to electronic trading entails a substantial increase in trading volume, but not in price volatility of Treasury futures.     

Volatility and trading activity following changes in the size of futures contracts

This paper has two purposes. First, we examine the relationship between daily price volatility and trading activity one year before and after a change in contract size by examining the results of contract splits in the Australian share price index futures and the U.K. FTSE-100 futures contracts and a reverse contract split in the Australian Bank Bill Acceptance futures contract. Second, we evaluate the effect of the change in contract size on the use of the particular futures market. We find that after a contract size change, the change in total trading frequency has the power to explain the change in daily price volatility. Specifically, after a contract split, trading frequency increased, resulting in increased daily price volatility, and vice versa after a reverse contract split. Most of the average trade size variable has an immaterial impact on price volatility. However, decomposing the total trading frequency into four trade size classes, we find that the trading frequency for small and large trade size categories are highly significant in explaining changes in daily price volatility after the contract splits. Finally, we find the change in contract size for each futures market was successful because within three years following the change, the adjusted trading volume and open interest surpassed the levels prior to the change and have continued to increase thereafter.     

Options and earnings announcements: an empirical study of volatility, trading volume, open interest and liquidity

In this paper we study the impact of earnings announcements on implied volatility, trading volume, open interest and spreads in the stock options market. We find that implied volatility increases before announcement days and drops afterwards. Also option trading volume is higher around announcement days. During the days before the announcement open interest tends to increase, while it returns to regular levels afterwards. Changes in the quoted spread largely respond to higher trading volume and changes in implied volatility. The effective spread increases on the event day and on the first two days following the earnings announcement.     

引入国债期货合约能否发挥现货市场稳定效应?——基于中国金融周期的研究视角

我国国债期货市场能否发挥稳定现货市场功能,金融周期风险是否会改变国债期货市场对现货市场波动的影响,是投资者实施风险管理和监管部门构建市场稳定机制的重要依据。本文通过信息传递机制和交易者行为两个维度探析国债期货市场发挥稳定功能的微观机理,分析金融周期风险对衍生工具稳定功能的影响,解析引入国债期货合约能否缓解金融周期波动对国债市场冲击,同时关注我国国债期货交易机制改进与现券波动关系。研究发现:(1)我国国债期货市场已实现抑制现货市场波动的功能,金融周期风险会引发现货价格波动,国债期货市场能够降低金融周期的波动冲击;(2)改善现货市场深度和套保交易是国债期货市场发挥稳定功能的微观路径,国债期货市场增进国债预期交易量流动性、减弱非预期交易量干扰,金融周期低波动区间套保交易稳定作用受到抑制;(3)国债期货投机交易和波动溢出效应助长现货市场波动,正负期现基差对国债波动影响具有非对称特征。     

The relationship between futures trading activity and exchange rate volatility,revisited

This paper examines the relationship between trading activity in currency futures and exchange rate volatility. In order to measure trading activity, the paper uses both volume and open interest to distinguish between speculators/day traders and hedgers. The study uses three different measures of volatility: (1) the extreme value estimator that measures intra-day volatility; (2) historical volatility; and (3) conditional volatility from the GARCH (1, 1) process. Main finding is that speculators and day traders destabilize the market for futures. Whether hedgers stabilize or destabilize the market is inconclusive. The results suggest that speculators’ demand for futures goes down in response to increased volatility. Meanwhile, the demand from hedgers shows mixed results, depending on the method used to measure volatility.     

Share price volatility with the introduction of individual share futures on the Sydney Futures Exchange

This paper examines a recent innovation in financial derivative securities—individual share futures contracts traded on the Sydney Futures Exchange. We investigate changes in the volatility of the underlying shares in the cash market using an asymmetric exponential ARCH model. The overall evidence suggests that the introduction of futures trading has had very little impact on cash market volatility. Trade in the futures market has less of an effect on cash market volatility than cash market trading for most shares.     

The microstructural foundations of leverage effect and rough volatility

We show that typical behaviors of market participants at the high frequency scale generate leverage effect and rough volatility. To do so, we build a simple microscopic model for the price of an asset based on Hawkes processes. We encode in this model some of the main features of market microstructure in the context of high frequency trading: high degree of endogeneity of market, no-arbitrage property, buying/selling asymmetry and presence of metaorders. We prove that when the first three of these stylized facts are considered within the framework of our microscopic model, it behaves in the long run as a Heston stochastic volatility model, where a leverage effect is generated. Adding the last property enables us to obtain a rough Heston model in the limit, exhibiting both leverage effect and rough volatility. Hence we show that at least part of the foundations of leverage effect and rough volatility can be found in the microstructure of the asset.     

Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis

The relationship between trading volume and volatility in foreign exchange markets continues to be of much interest, especially given the higher than expected volatility of returns. Allowing for nonlinearities, this paper tests competing hypotheses on the possible relationship between volatility and trading volume using data for three major currency futures contracts denominated in US dollars, namely the British pound, the Canadian dollar and the Japanese yen. We find that trading volumes and return volatility are negatively correlated, implying a lack of support for the mixture of distributions hypothesis (MDH). Using linear and nonlinear Granger causality tests, we document significant lead-lag relations between trading volumes and return volatility consistent with the sequential arrival of information (SAI) hypothesis. These findings are robust and not sample-dependent or due to heterogeneity of beliefs as proxied by open interest. Furthermore, our results are insensitive to the modeling approach used to recover volatility measures. Overall, our findings support the contention that short- to medium-term currency relationships may be dominated by trading dynamics and not by fundamentals.     

期货市场的交易量与价格波动

本文检验了美国期货市场WTI原油、S＆P500指数和10年期国债品种的日内、日间价格波动与日内交易量、隔日交易量之间的关系,发现预期的日内和隔日交易量都有平抑期货市场价格波动的作用,非预期的隔日交易量与期货价格波动之间有正相关关系,非预期的目内交易量对价格波动的影响不显著。从信息对称性的角度分析,预期的交易量中含有更多信息,能抑制期货价格的偏离;非预期的交易量主要由信息反馈者提供,他们往往对期货价格的变动做出过度反应,从而加剧价格波动。     

Samuelson Hypothesis & Indian Commodity Derivatives Market

Samuelson (1965) devised that futures price volatility increases as the futures contract approaches its expiration. The relation amid the volatility and time to maturity has significant inference for hedging strategies. Interestingly, so far the empirical evidence in favor of the Samuelson Hypothesis (maturity effect) is mixed in various markets. Considering no significant work to examine the relationship is so far carried out in commodity derivative markets of India, this paper ordeal the Samuelson Hypothesis on 8 commodities traded on Multi-Commodity Exchange (MCX), India. We have examined the issue by applying different regression techniques to test the hypothesis for 8 commodities (Aluminium, Nickel, Copper, Gold, Silver, Natural Gas, Crude Oil and Wheat) using inter-day data on MCX India. In order to test the Samuelson’s hypothesis, tests have been conducted using a series of GARCH, EGARCH and TGARCH models by including trading volume, open interest and time-to-maturity in the conditional variance equation. From our results, it is concluded that Samuelson’s hypothesis does not hold true for majority of commodity contracts considered. Our results also find that volatility series depend on the trading volume, compared to the time-to-maturity or open interest. As Samuelson hypothesis does not hold true for majority of commodity contracts, traders in Indian commodity derivative markets should not bias their decisions solely based on the time-to-maturity, but should also consider trading volume and open interest as they are an important determinant of price volatility. They should also consider the possibility of leverage effect while predicting future price volatilities, and the associated margin requirements.     

When noise trading fades,volatility rises

We hypothesize and test an inverse relation between liquidity and price volatility derived from microstructure theory. Two important facets of liquidity trading are examined: volume and noisiness. As represented by the expected turnover rate (volume) and realized average commission cost per share (noisiness) of NYSE equity trading, both facets are found negatively associated with the ex post and ex ante return volatilities of the NYSE stock portfolios and the NYSE composite index futures. Furthermore, the inverse association between noisiness and volatility is amplified in times of market crisis. The negative noisiness–volatility relation is also supported by our analysis on the effects of trade size on price volatility. The overall results demonstrate that volatility increases as noise trading declines.     

Order Imbalance in the FTSE Index Futures Market: Electronic versus Open Outcry Trading

Abstract:  This study examines trading activities before and after the transfer of the FTSE 100 index futures contract from open outcry to electronic trading. Daily order imbalance exhibits strong serial persistence in the electronic limit order market, but not in open-outcry trading. Both excess buying and selling reduce liquidity. In the electronic venue, prior market movements barely affect investors' buying or selling decisions. Excess buy orders do not generate any price impact, but sell orders do. Positive imbalances are more strongly autocorrelated than negative imbalances. No trading elements, such as order imbalance, volume, or open interest, are associated with volatility. Moreover, excess buying decreases volatility. Such evidence suggests that the development and growth of electronic trading has changed the dynamics of trading activities in many important ways.     

Discount rate changes,stock market returns,volatility, and trading volume: Evidence from intraday data and implications for market efficiency

We examine the effect of discount rate changes on stock market returns, volatility, and trading volume using intraday data. Equity returns generally respond negatively and significantly to the unexpected announcements; however, the effect of expected changes on equity returns is insignificant. Furthermore, our results indicate that equity prices respond to announcements within the trading period/hour after the information release. An indication of a return reversal is too small to cover the full transaction costs. Unexpected discount rate changes also contribute to higher market volatility although the volatility is short-lived. Similarly, unexpected changes in discount rates induce larger trading volume while expected changes do not. Abnormal trading volume occurs only in period t. Our results also support the notion that unexpected changes in the discount rates impact market returns irrespective of the Federal Reserve operating procedures.     

Leverage vs. feedback: Which Effect drives the oil market?

This article brings new insights on the role played by (implied) volatility on the WTI crude oil price. An increase in the volatility subsequent to an increase in the oil price (i.e. inverse leverage effect) remains the dominant effect as it might reflect the fear of oil consumers to face rising oil prices. However, this effect is amplified by an increase in the oil price subsequent to an increase in the volatility (i.e. inverse feedback effect) with a two-day delayed effect. This lead-lag relation between the oil price and its volatility is central to any type of trading strategy based on futures and options on the OVX implied volatility index. It is of interest to traders, risk- and fund-managers.     

Futures Commitments and Exchange Rate Volatility

It is commonly suggested that certain groups of futures traders, such as speculators and small traders, exacerbate cash market volatility. Empirical research on the subject has been conducted in context of the relationship between price volatility and futures volume or open interest and fails to satisfactorily resolve such an issue. This paper examines the relationship between exchange rate variability and futures trading activity in the context of disaggregated open interest. The data and techniques employed allow for more specific inferences regarding which group of traders contribute to exchange volatility. The results suggest that while 'typical' levels of futures commitments are not destabilizing, surges in the level of commitments of large speculators and small traders causes exchange rate volatility. The actual release of the commitment-of-traders data, however, has no impact on spot prices.     

The intraday behaviors and relationships with its underlying assets: evidence on option market in Taiwan

In this paper, we use daily data to investigate the information asymmetric effects and the relationships between the trading volume of options and their underlying spot trading volume. Our results reveal that options with higher liquidity are near-the-money and expiration periods with 2 to 4 weeks have higher trading activity. We classify them into two parts with the ARIMA model: the expected trading activity impact and the unexpected trading activity impact. Using the bivariate generalized autoregressive conditional heteroscedasticity (GARCH) model, we investigate the trading activity effect and information asymmetric effect. In conclusion, the trading volume volatility of the spot and options markets move together, and a greater expected and unexpected trading volume volatility of the spot (options) market is associated with greater volatility in the options (spot) market. However, both markets generate higher trading volume volatility when people expect such an impact rather than when they do not. We also find that there are feedback effects within these two markets. Furthermore, when the spot (options) market has negative innovations, it generates a greater impact on the options (spot) market than do positive innovations. Finally, the conditional correlation coefficient between the spot and the option markets changes over time based on the bivariate GARCH model.     

How do economic policy uncertainty and geopolitical risk drive Bitcoin volatility?

We investigate how economic policy uncertainty (EPU) and geopolitical risks (GPR) impact Bitcoin volatility with respect to factors related to type and nationality of uncertainty, investigated period, relationship horizon and extreme conditions. Applying ARDL model and quantile regression for monthly data from August 2010 to September 2021, we reveal that June 2014 corresponds to a key date that marks a reversal in the investigated relationship. Furthermore, we show that the relationship between uncertainty and bitcoin volatility changes according to different factors. US uncertainty has short run effects on Bitcoin volatility, while China’s uncertainty has rather long run effects. Moreover, Bitcoin volatility responds in the same manner to US EPU and GPR, while, it responds differently to China's EPU and GPR. In extreme quantiles, we find that Bitcoin hedges against US EPU and GPR. Further, Bitcoin hedges against either individual or joint effects of US uncertainty, but not both.