Intraday Data (intraday + data)

Distribution by Scientific Domains
Distribution within Business, Economics, Finance and Accounting

Selected Abstracts

Are Momentum Profits Robust to Trading Costs?

Robert A. Korajczyk
We test whether momentum strategies remain profitable after considering market frictions induced by trading. Intraday data are used to estimate alternative measures of proportional and non-proportional (price impact) trading costs. The price impact models imply that abnormal returns to portfolio strategies decline with portfolio size. We calculate break-even fund sizes that lead to zero abnormal returns. In addition to equal- and value-weighted momentum strategies, we derive a liquidity-weighted strategy designed to reduce the cost of trades. Equal-weighted strategies perform the best before trading costs and the worst after trading costs. Liquidity-weighted and hybrid liquidity/value-weighted strategies have the largest break-even fund sizes: $5 billion or more (relative to December 1999 market capitalization) may be invested in these momentum strategies before the apparent profit opportunities vanish. [source]

Modeling and Forecasting Realized Volatility

ECONOMETRICA, Issue 2 2003
Torben G. Andersen
We provide a framework for integration of high,frequency intraday data into the measurement, modeling, and forecasting of daily and lower frequency return volatilities and return distributions. Building on the theory of continuous,time arbitrage,free price processes and the theory of quadratic variation, we develop formal links between realized volatility and the conditional covariance matrix. Next, using continuously recorded observations for the Deutschemark/Dollar and Yen/Dollar spot exchange rates, we find that forecasts from a simple long,memory Gaussian vector autoregression for the logarithmic daily realized volatilities perform admirably. Moreover, the vector autoregressive volatility forecast, coupled with a parametric lognormal,normal mixture distribution produces well,calibrated density forecasts of future returns, and correspondingly accurate quantile predictions. Our results hold promise for practical modeling and forecasting of the large covariance matrices relevant in asset pricing, asset allocation, and financial risk management applications. [source]

Price Movers on the Stock Exchange of Thailand: Evidence from a Fully Automated Order-Driven Market

Charlie Charoenwong
G12; G14; G15 Abstract This study examines which trade sizes move stock prices on the Stock Exchange of Thailand (SET), a pure limit order market, over two distinct market conditions of bull and bear. Using intraday data, the study finds that large-sized trades (i.e., those larger than the 75th percentile) account for a disproportionately large impact on changes in traded and quoted prices. The finding remains even after it has been subjected to a battery of robustness checks. In contrast, the results of studies conducted in the United States show that informed traders employ trade sizes falling between the 40th and 95th percentiles (Barclay and Warner, 1993; Chakravarty, 2001). Our results support the hypothesis that informed traders in a pure limit order market, such as the SET, where there are no market makers, also use larger-size trades than those employed by informed traders in the United States. [source]

Forecasting realized volatility: a Bayesian model-averaging approach

Chun Liu
How to measure and model volatility is an important issue in finance. Recent research uses high-frequency intraday data to construct ex post measures of daily volatility. This paper uses a Bayesian model-averaging approach to forecast realized volatility. Candidate models include autoregressive and heterogeneous autoregressive specifications based on the logarithm of realized volatility, realized power variation, realized bipower variation, a jump and an asymmetric term. Applied to equity and exchange rate volatility over several forecast horizons, Bayesian model averaging provides very competitive density forecasts and modest improvements in point forecasts compared to benchmark models. We discuss the reasons for this, including the importance of using realized power variation as a predictor. Bayesian model averaging provides further improvements to density forecasts when we move away from linear models and average over specifications that allow for GARCH effects in the innovations to log-volatility. Copyright 2009 John Wiley & Sons, Ltd. [source]

The Effects of Unanticipated Macroeconomic News on Debt Markets

Rohan Christie-David
Abstract We examine the effects of unanticipated macroeconomic news on two interest rate futures using intraday data. The surprises are identified on the basis of their potential effects on debt markets (positive or negative) and by their size (large, medium, or small). The results show distinct ex-post return patterns associated with different categories of news surprises. For example, large surprises have the strongest immediate effects whereas negative surprises have the longest persisting effects. Tests that examine the separate effects of each announcement suggest that debt responses vary with the size and potential effect of the news surprise in each announcement. [source]

Forecasting volatility: Roles of sampling frequency and forecasting horizon,

Wing Hong Chan
This study empirically tests how and to what extent the choice of the sampling frequency, the realized volatility (RV) measure, the forecasting horizon and the time-series model affect the quality of volatility forecasting. Using highly synchronous executable quotes retrieved from an electronic trading platform, the study avoids the influence of various market microstructure factors in measuring RV with high-frequency intraday data and in inferring implied volatility (IV) from option prices. The study shows that excluding non-trading-time volatility produces significant downward bias of RV by as much as 36%. Quality of prediction is significantly affected by the forecasting horizon and RV model, but is largely immune from the choice of sampling frequency. Consistent with prior research, IV outperforms time-series forecasts; however, the information content of historical volatility critically depends on the choice of RV measure. 2010 Wiley Periodicals, Inc. Jrl Fut Mark [source]

Do futures lead price discovery in electronic foreign exchange markets?

Juan Cabrera
Using intraday data, this study investigates the contribution to the price discovery of Euro and Japanese Yen exchange rates in three foreign exchange markets based on electronic trading systems: the CME GLOBEX regular futures, E-mini futures, and the EBS interdealer spot market. Contrary to evidence in equity markets and more recent evidence in foreign exchange markets, the spot market is found to consistently lead the price discovery process for both currencies during the sample period. Furthermore, E-mini futures do not contribute more to the price discovery than the electronically traded regular futures. 2008 Wiley Periodicals, Inc. Jrl Fut Mark 29:137,156, 2009 [source]

How potent are news reversals?: Evidence from the futures markets

Arjun Chatrath
A theoretical model is presented, which predicts a heightening in return volatility following a news reversal. A reversal occurs when a value of an economic indicator that is larger than the forecasted value is followed in the following month by a value smaller than the forecasted value, or vice versa. The model also suggests that the effects of a news reversal will be more pronounced early in the monthly macroeconomic news cycle. The predictions of the model for trading activity are less clear. The main predictions of the model were tested employing intraday data for the nearby Treasury bond futures contract. Consistent with the model, the data show significantly greater responses in volatility per standard-deviation surprise when there is a news reversal, than otherwise. Further, the increased sensitivity in volatility is especially perceptible early in the announcement cycle. 2008 Wiley Periodicals, Inc. Jrl Fut Mark 29:42,73, 2009 [source]

A test of the Samuelson Hypothesis using realized range

Petko S. Kalev
This study examines the Samuelson Hypothesis, which postulates that futures price volatility increases as the futures contract approaches its expiration. Investigating intraday data and drawing on the recently developed concept of realized range, this study provides empirical evidence regarding the Samuelson Hypothesis for 14 agricultural, metal, energy, and financial futures markets in six futures exchanges. While utilizing a nonparametric test, a simple linear regression model and a system of seemingly unrelated regressions, the study finds strong support for the Samuelson Hypothesis in agricultural futures. In contrast, no support for the Samuelson Hypothesis is observed in any of the metal and financial futures. 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:680,696, 2008 [source]

Information transmission in electronic versus open-outcry trading systems: An analysis of U.S. equity index futures markets

Aysegul Ates
In this article the intraday price discovery process between regular index futures (floor trading) and E-mini index futures (electronic trading) in the S&P 500 and Nasdaq 100 index futures markets is examined, using intraday data from the introduction of the E-mini index futures to 2001. Using both information shares (Hasbrouck, J., 1995) and common long-memory factor weights (Gonzalo, J., & Granger, C. W. J., 1995) techniques, we find that both E-mini index futures and regular index futures contribute to the price discovery process. However, since September 1998, the contribution made by E-mini index futures has been greater than that provided by regular index futures. Based on regression analysis, we have also found direct empirical evidence to support the hypothesis that the joint effects of operational efficiency and relative liquidity determine the greater contribution made towards price discovery by electronic trading relative to open-outcry trading over time. 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25: 679,715, 2005 [source]

Index futures leadership, basis behavior, and trader selectivity

Arjun Chatrath
Employing intraday data for futures and cash values for the S&P 500 over the 1993,1996 period, we attempt to characterize the lead,lag relationship between these two markets and their basis behavior. Our findings show evidence of pronounced futures leadership when markets are rising, with no feedback from the cash market. However, when markets are falling, futures leadership is less evident and significant feedback from the cash market is noted. We also provide evidence of a positive relationship between the basis and return volatility. We offer an explanation, based on trader selectivity, for the leadership-asymmetry and the basis,volatility relationship. 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:649,677, 2002 [source]

The Price Premium of China A-Shares over Hong Kong H-Shares: A Further Visit of the Liquidity Hypothesis,

Hing-Wah Lee
Abstract I examine the price premium between A-shares and H-shares using a sample of Hong Kong, Shenzhen, and Shanghai stock market intraday data in 2004. Following the market-microstructure approach, I reinvestigate the liquidity hypothesis by incorporating spread and depth. The study generates two important results. First, China A-shares on average provide better market liquidity than their Hong Kong H-share counterparts do. Second, after controlling for traditional liquidity measures and variables related to competing hypotheses, the percentage differences in quoted spread and depth between A-shares and H-shares still explain significantly the price premium. Endogeneity between spread and depth does not affect the major findings. [source]