scholarly journals The adaptive market hypothesis and high frequency trading

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260724
Author(s):  
Ke Meng ◽  
Shouhao Li
Keyword(s):  
High Frequency ◽  
High Efficiency ◽  
High Frequency Trading ◽  
Order Book ◽  
Lower Efficiency ◽  
Processing Information ◽  
Low Efficiency ◽  
Exchange Traded Fund ◽  
The Relationship ◽  
Over Time

This paper uses NASDAQ order book data for the S&P 500 exchange traded fund (SPY) to examine the relationship between one-minute, informational market efficiency and high frequency trading (HFT). We find that the level of efficiency varies widely over time and appears to cluster. Periods of high efficiency are followed by periods of low efficiency and vice versa. Further, we find that HFT activity is higher during periods of low efficiency. This supports the argument that HFTs seek profits and risk reduction by actively processing information, through limit order additions and cancellations, during periods of lower efficiency and revert to more passive market-making and rebate-generation during periods of higher efficiency. These findings support the argument that the adaptive market hypothesis (AMH) is an appropriate description of how prices evolve to incorporate information.

scholarly journals DOES SPEED MATTER? THE ROLE OF HIGH‐FREQUENCY TRADING FOR ORDER BOOK RESILIENCY

2020 ◽  
Vol 43 (4) ◽  
pp. 933-964
Author(s):  
Benjamin Clapham ◽  
Martin Haferkorn ◽  
Kai Zimmermann
Keyword(s):  
High Frequency ◽  
High Frequency Trading ◽  
Order Book

scholarly journals Body composition and implications for heat production of Angus steer progeny of parents selected for and against residual feed intake

2001 ◽  
Vol 41 (7) ◽  
pp. 1065 ◽  
Author(s):  
E. C. Richardson ◽  
R. M. Herd ◽  
V. H. Oddy ◽  
J. M. Thompson ◽  
J. A. Archer ◽  
...  
Keyword(s):  
Body Composition ◽  
Chemical Analysis ◽  
Feed Intake ◽  
High Efficiency ◽  
Residual Feed Intake ◽  
Whole Body ◽  
Lower Efficiency ◽  
Fat Depots ◽  
The Difference ◽  
Low Efficiency

Yearling Angus steer progeny of parents selected for low residual feed intake (RFI; high efficiency) or high RFI (low efficiency) were evaluated for feed intake, growth and differences in body composition. RFI is the difference between actual feed intake and expected feed intake based on an animal’s size and growth over a test period. Individual intakes of a high grain content ration and growth rates were recorded for 140 days and then the steers were slaughtered for measurement of body composition. All internal organs and non-carcass fat depots were removed, weighed and ground for chemical analysis. Carcasses were kept overnight in the chiller and the left half of every carcass physically dissected into retail cuts, and then into total fat, lean and bone. Carcass fat and lean were then combined and ground for chemical analysis. Steers from low RFI parents ate less (P<0.05) than the steers from high RFI parents, for similar rates of growth. Improvement in RFI was accompanied by small changes in body composition towards greater lean and less fat in the progeny of low RFI parents. Correlations of sire estimated breeding values for RFI with end of test whole body chemical protein, chemical fat and a principal component that condensed information on fat and lean body composition at the end of the test, were statistically significant. These confirmed there was a genetic association between body composition and RFI, with fatness being associated with higher RFI (i.e. lower efficiency). However, the correlations were small and suggested that less than 5% of the variation in sire RFI was explained by variation in body composition of their steer progeny. There was no evidence that a difference in the chemical composition of gain over the test explained the greater intake of metabolisable energy (ME) by the high RFI steers. The results suggest that the difference in ME intake following a single generation of divergent selection for RFI was due to metabolic processes rather than to changes in body composition.

scholarly journals Realized Measures to Explain Volatility Changes over Time

2020 ◽  
Vol 13 (6) ◽  
pp. 125
Author(s):  
Christos Floros ◽  
Konstantinos Gkillas ◽  
Christoforos Konstantatos ◽  
Athanasios Tsagkanos
Keyword(s):  
High Frequency ◽  
Realized Volatility ◽  
High Frequency Data ◽  
Leverage Effect ◽  
Frequency Data ◽  
Specific Group ◽  
Volatility Feedback ◽  
Changes Over Time ◽  
The Relationship ◽  
Over Time

We studied (i) the volatility feedback effect, defined as the relationship between contemporaneous returns and the market-based volatility, and (ii) the leverage effect, defined as the relationship between lagged returns and the current market-based volatility. For our analysis, we used daily measures of volatility estimated from high frequency data to explain volatility changes over time for both the S&P500 and FTSE100 indices. The period of analysis spanned from January 2000 to June 2017 incorporating various market phases, such as booms and crashes. Based on the estimated regressions, we found evidence that the returns of S&P500 and FTSE100 indices were well explained by a specific group of realized measure estimators, and the returns negatively affected realized volatility. These results are highly recommended to financial analysts dealing with high frequency data and volatility modelling.

scholarly journals The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response *

2015 ◽  
Vol 130 (4) ◽  
pp. 1547-1621 ◽  
Author(s):  
Eric Budish ◽  
Peter Cramton ◽  
John Shim
Keyword(s):  
High Frequency ◽  
Market Design ◽  
Limit Order Book ◽  
Theory Model ◽  
Arms Race ◽  
High Frequency Trading ◽  
Continuous Limit ◽  
Order Book ◽  
Limit Order ◽  
Arbitrage Opportunities

Abstract The high-frequency trading arms race is a symptom of flawed market design. Instead of the continuous limit order book market design that is currently predominant, we argue that financial exchanges should use frequent batch auctions: uniform price double auctions conducted, for example, every tenth of a second. That is, time should be treated as discrete instead of continuous, and orders should be processed in a batch auction instead of serially. Our argument has three parts. First, we use millisecond-level direct-feed data from exchanges to document a series of stylized facts about how the continuous market works at high-frequency time horizons: (i) correlations completely break down; which (ii) leads to obvious mechanical arbitrage opportunities; and (iii) competition has not affected the size or frequency of the arbitrage opportunities, it has only raised the bar for how fast one has to be to capture them. Second, we introduce a simple theory model which is motivated by and helps explain the empirical facts. The key insight is that obvious mechanical arbitrage opportunities, like those observed in the data, are built into the market design—continuous-time serial-processing implies that even symmetrically observed public information creates arbitrage rents. These rents harm liquidity provision and induce a never-ending socially wasteful arms race for speed. Last, we show that frequent batch auctions directly address the flaws of the continuous limit order book. Discrete time reduces the value of tiny speed advantages, and the auction transforms competition on speed into competition on price. Consequently, frequent batch auctions eliminate the mechanical arbitrage rents, enhance liquidity for investors, and stop the high-frequency trading arms race.

scholarly journals High-frequency trading in a limit order book

2008 ◽  
Vol 8 (3) ◽  
pp. 217-224 ◽  
Author(s):  
Marco Avellaneda ◽  
Sasha Stoikov
Keyword(s):  
High Frequency ◽  
Limit Order Book ◽  
High Frequency Trading ◽  
Order Book ◽  
Limit Order

scholarly journals The Relationship between Environmental Regulations and Green Economic Efficiency: A Study Based on the Provinces in China

2021 ◽  
Vol 18 (3) ◽  
pp. 889
Author(s):  
Gongli Luo ◽  
Xiaotong Wang ◽  
Lu Wang ◽  
Yanlu Guo
Keyword(s):  
Economic Efficiency ◽  
High Efficiency ◽  
Negative Impact ◽  
Environmental Regulations ◽  
National Level ◽  
Critical Value ◽  
Eastern Region ◽  
Low Efficiency ◽  
The Impact ◽  
The Relationship

This study examined the relationship between environmental regulations (ER) and green economic efficiency (GEE) based on the panel data of 30 provinces in China from 2008 to 2017. Firstly, GEE was calculated and evaluated using the super-efficiency SBM model with undesirable outputs. Secondly, the impact of ER on GEE was studied with the Tobit model. Finally, this article draws conclusions based on the above analysis and offers some suggestions for government and enterprise. The results show that the GEE of China is generally low. The GEE of the eastern region is much higher than that of the middle and western regions, with the western region performing slightly better than the middle. From west to east, there is a V shape, with high efficiency in the west and east and low efficiency in the middle. The impact of ER on GEE has the characteristics of nonlinearity and spatial heterogeneity. At the national level, as well as in the middle and western regions, the impact of ER on GEE shows an inverted U shape that first rises and then falls. ER are currently within the range conducive to the development of GEE. If the intensity of ER exceeds the critical value, they will have a negative impact on GEE. In the eastern region, the impact of ER on GEE is shown as a U shape that first falls and then rises. At present, the ER are not of sufficient intensity to contribute to the improvement of GEE. Only when the intensity of the ER exceeds the critical value will they have a positive influence on the GEE.

Autonomous self-evolving forecasting models for price movement in high frequency trading: Evidence from Taiwan

2020 ◽  
Vol 24 (5) ◽  
pp. 1175-1206
Author(s):  
Chien-Feng Huang ◽  
Hsiao-Chi Wu ◽  
Po-Chun Chen ◽  
Bao Rong Chang
Keyword(s):  
High Frequency ◽  
Prediction Models ◽  
Time Series Data ◽  
Financial Time Series ◽  
Supply And Demand ◽  
High Frequency Trading ◽  
Series Data ◽  
Order Book ◽  
Price Movement ◽  
Increasing Demand

Among FinTech research and applications, forecasting financial time series data has been a challenging task because this kind of data is typically quite noisy and non-stationary. A recent line of financial research centers around trading through financial data on the microscopic level, which is the holy grail of high-frequency trading (HFT), as the higher the data frequency, the more profitable opportunities may appear. The advancement in HFT modeling has also facilitated more understanding towards price formation because the supply and demand of a stock can be comprehended more easily from the microstructure of the order book. Instead of traditional statistical methods, there has been increasing demand for the development of more reliable prediction models due to the recent progress in Computational Intelligence (CI) technologies. In this study, we aim to develop novel CI-based methodologies for the forecasting task of price movement in HFT. Our goal is to conduct a study for autonomous genetic-based models that allow the forecasting systems to self-evolve. The results show that our proposed method can improve upon the previous ones and advance the current state of Fintech research.

scholarly journals LLC and CLLC Resonant Converters Based DC Transformers (DCXs): Characteristics, Issues, and Solutions

2021 ◽  
Vol 6 (4) ◽  
pp. 332-348
Author(s):  
Yuqi Wei ◽  
Keyword(s):  
Resonant Frequency ◽  
High Frequency ◽  
High Efficiency ◽  
Industrial Applications ◽  
Resonant Converters ◽  
Frequency Tracking ◽  
Main Work ◽  
Small Footprint ◽  
Low Efficiency ◽  
Voltage Conversion

Conventional line frequency transformers have the disadvantages of large volume and low efficiency. The medium or high frequency transformers based on power converters can achieve high power conversion with small footprint have drawn popularity in numerous industrial applications. Unregulated resonant converters, LLC and CLLC resonant converters, with fixed voltage conversion ratio operating at resonant frequency, which are also known as DC transformers (DCXs), are attractive owning to their high efficiency characteristic. Nevertheless, there are issues associated with DCXs in real applications. Regulation capability and automatic resonant frequency tracking capability are the two most important issues for DCXs. The main work of this paper is to characterize the resonant converters based DCXs, and overview the issues and solutions associated with DCXs. Guidelines can be provided for researchers and engineers when designing the resonant converters based DCXs.

Research on Negative Pressure Wall Climbing Absorption System Based on SMA

2013 ◽  
Vol 423-426 ◽  
pp. 1790-1793
Author(s):  
Fang Dai ◽  
Gao Hua Liao
Keyword(s):  
Power Consumption ◽  
Negative Pressure ◽  
High Efficiency ◽  
Experimental Result ◽  
Utilization Rate ◽  
Climbing Robot ◽  
Absorption System ◽  
Working Pressure ◽  
Low Efficiency ◽  
The Relationship

This paper presents a negative pressure absorption system of climbing robots. Based on the utilization rate of the negative pressure climbing robot, the impacts of locomotion system adsorption forces allocation were studied. In order to solve the problems of sliding wall climbing robot's great power consumption and low efficiency design, a negative pressure generator of the low power consumption and high efficiency was investigated. After the analysis of robot's pressure needed and flow leakage fluid dynamics, the relationship between negative working pressure was established.Through the thermo dynamic analysis of the component process of state changes in suctions flow field was described, and the principles of the adsorption system were revealed. The results show that negative pressure can be stably generated and the system realize firmly adsorbing on wall. The theoretical and experimental result of wall climbing robot contributes to further perfecting the performance of robot.

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