scholarly journals Measuring Tail Risks at High Frequency

2018 ◽  
Vol 32 (9) ◽  
pp. 3571-3616 ◽  
Author(s):  
Brian M Weller
Keyword(s):  
Stock Returns ◽  
High Frequency ◽  
Trading Volume ◽  
Extreme Event ◽  
Open Market ◽  
Federal Open Market Committee ◽  
Tail Risk ◽  
Market Risks ◽  
Jump Risks ◽  
Liquidity Shock

Abstract I exploit information in the cross-section of bid-ask spreads to develop a new measure of extreme event risk. Spreads embed tail risk information because liquidity providers require compensation for the possibility of sharp changes in asset values. I show that simple regressions relating spreads and trading volume to factor betas recover this information and deliver high-frequency tail risk estimates for common factors in stock returns. My methodology disentangles financial and aggregate market risks during the 2007–2008 financial crisis; quantifies jump risks associated with Federal Open Market Committee announcements; and anticipates an extreme liquidity shock before the 2010 Flash Crash. Received April 27, 2016; editorial decision August 10, 2018 by Editor Andrew Karolyi. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online

Hot and Cold Strategies: Australian Evidence

2011 ◽  
Vol 14 (02) ◽  
pp. 271-295 ◽  
Author(s):  
Vikash Ramiah ◽  
Tafadzwa Mugwagwa ◽  
Tony Naughton
Keyword(s):  
Stock Returns ◽  
Asset Allocation ◽  
High Frequency ◽  
Trading Volume ◽  
Stock Exchange ◽  
Short Selling ◽  
Investment Strategies ◽  
Tactical Asset Allocation ◽  
Momentum Trading ◽  
The Relationship

The main purpose of this paper is to explore a high-frequency tactical asset allocation strategy. In particular, we investigate the profitability of momentum trading and contrarian investment strategies for equities listed on the Australian Stock Exchange (ASX). In these two strategies we take into consideration the short-selling restrictions imposed by the ASX on the stocks used. Within our sample portfolios we look at the relationship between stock returns and past trading volume for these equities. This research also investigates the seasonal aspects of contrarian portfolios and observes weekly, monthly and yearly effects. We report significant contrarian profits for the period investigated (from 2001 to 2006) and show that contrarian profit is a persistent feature for the strategies examined. We also document that contrarian portfolios earn returns as high as 6.54% per day for portfolios with no short-selling restrictions, and 4.71% in the restricted model. The results also support the view that volume traded affects stock returns, and show that market imperfections such as short-selling restrictions affect investors' returns.

The ‘Even Keel’ Decisions of the Federal Open Market Committee

1970 ◽  
Vol 26 (6) ◽  
pp. 105-117 ◽  
Author(s):  
William P. Yohe ◽  
Louis C. Gasper
Keyword(s):  
Open Market ◽  
Federal Open Market Committee

scholarly journals Diffusion approximations for randomly arriving expert opinions in a financial market with Gaussian drift

2021 ◽  
Vol 58 (1) ◽  
pp. 197-216 ◽  
Author(s):  
Jörn Sass ◽  
Dorothee Westphal ◽  
Ralf Wunderlich
Keyword(s):  
Stock Returns ◽  
Financial Market ◽  
Discrete Time ◽  
High Frequency ◽  
Utility Maximization ◽  
Limit Theorems ◽  
Approximate Solutions ◽  
Diffusion Approximations ◽  
Expert Opinions ◽  
Arrival Intensity

AbstractThis paper investigates a financial market where stock returns depend on an unobservable Gaussian mean reverting drift process. Information on the drift is obtained from returns and randomly arriving discrete-time expert opinions. Drift estimates are based on Kalman filter techniques. We study the asymptotic behavior of the filter for high-frequency experts with variances that grow linearly with the arrival intensity. The derived limit theorems state that the information provided by discrete-time expert opinions is asymptotically the same as that from observing a certain diffusion process. These diffusion approximations are extremely helpful for deriving simplified approximate solutions of utility maximization problems.

scholarly journals Effect of auditing: Evidence from variability of stock returns and trading volume

2014 ◽  
Vol 7 (4) ◽  
pp. 223-245 ◽  
Author(s):  
Charles J.P. Chen ◽  
Bin Srinidhi ◽  
Xijia Su
Keyword(s):  
Stock Returns ◽  
Trading Volume

Does time-varying illiquidity matter for the Indian stock market? Evidence from high-frequency data

2021 ◽  
pp. 031289622110102
Author(s):  
Mousumi Bhattacharya ◽  
Sharad Nath Bhattacharya ◽  
Sumit Kumar Jha
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
High Frequency ◽  
Jel Classification ◽  
Exogenous Shock ◽  
Intraday Data ◽  
Day Of The Week ◽  
Holiday Effects ◽  
Indian Stock Market ◽  
The Impact

This article examines variations in illiquidity in the Indian stock market, using intraday data. Panel regression reveals prevalent day-of-the-week, month, and holiday effects in illiquidity across industries, especially during exogenous shock periods. Illiquidity fluctuations are higher during the second and third quarters. The ranking of most illiquid stocks varies, depending on whether illiquidity is measured using an adjusted or unadjusted Amihud measure. Using pooled quantile regression, we note that illiquidity plays an important asymmetric role in explaining stock returns under up- and down-market conditions in the presence of open interest and volatility. The impact of illiquidity is more severe during periods of extreme high and low returns. JEL Classification: G10, G12

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