High frequency trading - page 10

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The flow of information between futures and spot prices may vary over time, in particular during periods of stress. This article analyses the information content of the Bund Future and German government bonds during 1998 and test whether it is constant over time. The use of high-frequency data permits us to capture possible imperfections in the information flows between the two markets. We measure the contributions of trading on the spot and futures markets to price discovery using the information shares approach by Hasbrouck (1995) as well as a recently proposed approach based on the Gonzalo-Granger decomposition. A state-space approach is used to estimate the underlying VECM in the presence of missing values. We test for structural breaks in the pricing relationship between the spot and futures markets and estimate break dates. Although most information is incorporated into prices in the futures market, this does not mean that the spot market is irrelevant for prices discovery. Under normal market conditions, the underlying bonds contribute to 19 to 33 % of the variation in the efficient price. The informational role of the spot market vanishes during episodes of stress. For example, during the two weeks after the recapitalization of LTCM (September 24th to October 8th, 1998), the information share of the spot market dropped to virtually zero and futures prices did not respond to movements in bond prices. All adjustment towards equilibrium took place in the spot market.

Der Informationsfluss zwischen Kassa- und Terminmärkten kann, insbesondere in Zeiten turbulenter Märkte, zeitlich variieren. Dieser Beitrag analysiert den Informationsgehalt im Bund Future und in den zugrundeliegenden Bundesanleihen für das Jahr 1998 und testet auf zeitliche Konstanz. Unsere Analyse basiert auf Hochfrequenzdaten und erlaubt daher die Untersuchung möglicher Unvollkommenheiten im Informationsfluss zwischen beiden Märkten. Wir messen den Beitrag der Handelstransaktionen auf dem Kassa- und Terminmarkt zum Preisbildungsprozess mit Hilfe des Informationsanteil Ansatzes von Hasbrouck (1995) sowie eines Ansatzes basierend auf der Gonzalo-Granger Zerlegung. Um das zugrundeliegende Fehler-Korrektur-Modell schätzen zu können, wenn Datenlücken vorliegen, wird ein Zustands-Raum-Modell verwendet. Wir testen auf Strukturbrüche im Preisbildungsprozess der Märkte und schätzen die Zeitpunkte der Strukturbrüche. Obwohl die meiste Information in den Preisen der Terminkontrakte enthalten sind, liefert der Kassamarkt einen nicht unerheblichen Beitrag zum Preisbildungsprozess. Unter normalen Marktbedingungen trägt die Bundesanleihe mit 19 bis 33 Prozent zur Bestimmung des Effizienzpreises bei. Der Informationsbeitrag des Kassamarktes verschwindet jedoch während Zeiten mit Marktturbulenzen. Zum Beispiel brach der Informationsanteil des Kassamarktes während der LTCM Rekapitalisierungsphase völlig zusammen. Der Terminkurs reagierte in dieser Phase nicht mehr auf Preisbewegungen am Kassamarkt und die Anpassung an das Arbitragegleichgewicht erfolgte ausschließlich durch den Kassakurs.
 
This paper analyses the informational role of the trading activity when jumps occur in the US Treasury market. As jumps mark the arrival of new information to the market, we explore the contribution of jumps in reducing the informational asymmetry. We identify jumps using a combination of jump detection techniques. For all maturities, the trading activity is more informative in the proximity of jumps. For the 2- and 5-year maturities, there is a lower level of information asymmetry before the jump, followed by a high level during the jump window and up to 20 minutes after the jump occurs. Thus, the incorporation of new information in prices is not instantaneous but several transactions are needed for the market to completely acknowledge the new information. Finally, we propose the use of the estimated integrated volatility as an exogenous predictor of jump occurrence in addition to announcement surprises.
 
In this paper we present a simple closed form stock price formula, which captures empirical regularities of high frequency trading (HFT), based on two factors: (1) exposure to hedge factor; and (2) hedge factor volatility. Thus, the parsimonious formula is not based on fundamental valuation. For applications, we first show that in tandem with a cost of carry model, it allows us to use exposure to and volatility of E-mini contracts to estimate dynamic hedge ratios, and mark-to-market capital gains on contracts. Second, we show that for given exposure to hedge factor, and suitable specification of hedge factor volatility, HFT stock price has a closed form double exponential representation. There, in periods of uncertainty, if volatility is above historic average, a relatively small short selling trade strategy is magnified exponentially, and the stock price plummets when such strategies are phased locked for a sufficient large number of traders. Third, we demonstrate how asymmetric response to news is incorporated in the stock price by and through an endogenous EGARCH type volatility process for past returns; and find that intraday returns have a U-shaped pattern inherited from HFT strategies. Fourth, we show that for any given sub-period, capital gains from trading is bounded from below (crash), i.e. flight to quality, but not from above (bubble), i.e. confidence, when phased locked trade strategies violate prerequisites of van der Corput's Lemma for oscillatory integrals. Fifth, we provide a taxonomy of trading strategies which reveal that high HFT Sharpe ratios, and profitability, rests on exposure to hedge factor, trading costs, volatility thresholds, and algorithm ability to predict volatility induced by bid-ask bounce or otherwise. Thus, extant regulatory proposals to control price dynamics of select stocks, i.e., pause rules such as ''limit up/limit down" bands over 5-minute rolling windows, may mitigate but not stop future market crashes or price bubbles from manifesting in underlying indexes that exhibit HFT stock price dynamics.
 

Hi

Some example of EA High Frequency?

Regards,

Rogério

 
We propose an inventory-based model of market making where a strategic high frequency trader exploits his speed and informational advantages to place quotes that interact with low frequency traders. We characterize the optimal market making policy analytically, illustrate that it generates endogenous order cancellations, and compute the long-run equilibrium bid-ask spread and other liquidity measures. The model predicts that the high-frequency trader provides more liquidity as he gets faster and shies away from it as volatility increases due to a higher risk of his stale quotes being picked by arbitrageurs. Competition with another liquidity provider increases improves the overall liquidity. Finally, we provide the first formal, model-based analysis of the impact of four widely discussed policies designed to regulate high frequency trading: imposing a transactions tax, setting minimum-time limits before quotes can be cancelled, taxing the cancellations of limit orders, and replacing time priority with a pro rata or random allocation. We find that these policies are largely unable to even out the speed and informational advantages of high frequency market makers.
 
borgesr:

Hi

Some example of EA High Frequency?

Regards,

Rogério

You can not HF using MT
 
borgesr:

Hi

Some example of EA High Frequency?

Regards,

Rogério

google high frequency trading first & u will see it's not a tool for retail trader !
 
How stocks are traded in the United States has been totally transformed. Gone are the dealers on NASDAQ and the specialists at the NYSE. Instead, a company’s stock can now be traded on up to sixty competing venues where a computer matches incoming orders. A majority of quotes are now posted by high-frequency traders (HFTs), making them the preponderant source of liquidity in the new market.

Many practices associated with the new stock market are highly controversial, as illustrated by the public furor following the publication of Michael Lewis’s book Flash Boys. Critics say that HFTs use their speed in discovering changes in the market and in altering their orders to take advantage of other traders. Dark pools – off-exchange trading venues that promise to keep the orders sent to them secret and to restrict the parties allowed to trade – are accused of operating in ways that injure many traders. Brokers are said to mishandle customer orders in an effort to maximize the payments they receive in return for sending trading venues their customers’ orders, rather than delivering best execution.

In this paper, we set out a simple, but powerful, conceptual framework for analyzing the new stock market. The framework is built upon three basic concepts: adverse selection, the principal-agent problem, and a multi-venue trading system. We illustrate the utility of this framework by analyzing the new market’s eight most controversial practices. The effects of each practice are evaluated in terms of the multiple social goals served by equity trading markets.

We ultimately conclude that there is no emergency requiring immediate, poorly-considered action. Some reforms proposed by critics, however, are clearly desirable. Other proposed reforms involve a tradeoff between two or more valuable social goals. In these cases, whether a reform is desirable may be unclear, but a better understanding of the tradeoff involved enables a more informed choice and suggests where further empirical research would be useful. Finally, still other proposed reforms are based on misunderstandings of the market or of the social impacts of a practice and should be avoided.
 
We propose a local adaptive multiplicative error model (MEM) accommodating time-varying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time. Analysing 1-minute cumulative trading volumes of five large NASDAQ stocks in 2008, we show that local windows of approximately 3 to 4 hours are reasonable to capture parameter variations while balancing modelling bias and estimation (in)efficiency. In forecasting, the proposed adaptive approach significantly outperforms a MEM where local estimation windows are fixed on an ad hoc basis.
 
Aim. High Frequency Trading poses a large number of ethical questions. The purpose of this study is to examine the ethical perceptions of those who work inside the HFT industry.

Method. The research consisted of a case study. Participants (N=30) were high frequency traders, algorithm developers, consultants, quant analysts, quantitative strategists, ultra low-latency data scientists, or managers of HFT companies. Participation involved an interview (N=27) or a completion of a questionnaire (N=3). HFT actors were asked to report what ethical considerations are involved in their work.

Results. Participants’ answers showed that many HFT actors considered legal and regulatory issues a central component of their ethical conduct. However, a proportion of the participants was concerned with the social contribution of their practice and with the public image of HFT. In particular, perceiving HFT as having neutral or negative effect on the market was related with sense of meaninglessness.

Conclusions. Ethics perceptions of HFT actors are characterised by a personal nature. Beyond the overlap between the notions of ethics and legality, they reflect the human tendency to search for meaning and the need to have a positive image.
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