Tag Archives: Paper

Trading Algo in Parallel Environments Paper

Trading Algo in Parallel Environments Paper

Really good research paper

Implementing Randomized Matrix Algorithms in Parallel and
Distributed Environments

http://arxiv.org/pdf/1502.03032v1.pdf

 

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Quantum Mechanics trading ? Research Paper on Quantum Tunneling of Stock Price in Range Bound Market Conditions

Quantum Mechanics trading ? Research Paper on Quantum Tunneling of Stock Price in Range Bound Market Conditions

This was sent over by a newsletter subscriber so thanks to him:

Do you tried Quantum Mechanics trading ?!
http://arxiv.org/abs/1307.6727

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paper on an anomaly detector which does not require user pre set parameters but uses algos to teach itself possible market abuse.

Please feel free to download our white paper on an ‘anomaly detector’ which does not require user pre set parameters but uses algos to teach itself possible market abuse.You can download a free copy from the REMIT group and I’m sure you will find it of great intrest to HFT and algo traders as well as surveillance functions–

Sounds very interesting – would you mind mailing me a copy please?
Many thanks,

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Low-Latency Trading – Paper for quant development and quant analytics

Low-Latency Trading – Paper for quant development and quant analytics

Low-Latency Trading – Paper

http://pages.stern.nyu.edu/~jhasbrou/Research/Working%20Papers/HS10-11-10.pdf

 

 

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One important conclusion of this paper is that:

In the current environment, increased low-latency activity improves traditional market quality measures such as short-term volatility, spreads, and displayed depth in the limit order book.

Abstract:
This paper studies market activity in the “millisecond environment,” where computer algorithms respond to each other almost instantaneously. Using order-level NASDAQ data, we find that the millisecond environment consists of activity by some traders who respond to market events (like changes in the limit order book) within roughly 2-3 ms, and others who seem to cycle in wall-clock time. We define low-latency activity as strategies that respond to market events in the millisecond environment, the hallmark of proprietary trading by a new breed of high-frequency trading firms. We construct a measure of low-latency activity by identifying “strategic runs,” which are linked submissions, cancellations, and executions that are likely to be parts of a dynamic strategy. We use this measure to study the impact that low-latency activity has on market quality both during normal market conditions and during a period of declining prices and heightened economic uncertainty. Our conclusion is that in the current environment, increased low-latency activity improves traditional market quality measures such as short-term volatility, spreads, and displayed depth in the limit order book.
Number of Pages in PDF File: 59
Working Paper Series

 

 

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Brilliant paper defining HFT / Algo Trading / Non-HFT Algo Strategies

Brilliant paper defining HFT / Algo Trading / Non-HFT Algo Strategies.

Must read for any individual looking forward to clear his concepts regarding Algo Trading. Quite an exceptional research which segregates and defines Algo Trading/ High Frequency Trading/ Non-HFT Algorithms.

High Frequency Deutche scribd.com

Peter Gomber, Björn Arndt, Marco Lutat, Tim Uhle Chair of Business Administration, Campus Westend • RuW P.O. Box 69 • D-60629 Frankfurt/Main High-frequency trading (HFT) has recently drawn massive public attention fuelled by…

http://www.scribd.com/doc/53488495/High-Frequency-Deutsche

 

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A downloadable copy is here:

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1858626

 

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Thanks for the link Niraj, reading the article at the moment.

 

Very good summary report, and from European perspective.

 

 

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Quant analytics: Paper for the Black Litterman Model: BLACK, F. (1989): “Universal Hedging: …”

Quant analytics: Paper for the Black Litterman Model: BLACK, F. (1989): “Universal Hedging: …”

For the people involved in the Black-Litterman model, I think the paper written by Black in 1989 is very interesting, talking about equilibrium (applied to forex) one year before the 1990 internal paper in Goldman Sachs. I’d add it to the bibliografy regarding the BLM.

BLACK, F. (1989): “Universal Hedging: Optimizing Currency Risk and Reward in International Equity Portfolios”, Financial Analysts Journal, pages 16-22, July-August 1989.

http://www2.mccombs.utexas.edu/faculty/keith.brown/chilematerial/black%20faj89.pdf

 

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The interesting paper on universal hedging recommended by Carloshttp://www2.mccombs.utexas.edu/faculty/keith.brown/chilematerial/black%20faj89.pdf
is by Black, but it is not specifically on Black-Litterman.

Black was fascinated by the concept of equilibrium, and he used this concept in many of his articles, including in the above paper on universal hedging and in the Black-Litterman paperhttp://faculty.fuqua.duke.edu/~charvey/Teaching/BA453_2006/Black_Litterman_Global_Portfolio_Optimization_1992.pdf

In the Black-Litterman paper, equilibrium is used to set the prior, but the main contribution of Black-Litterman is a methodology to mix the prior, which need not stem necessarily from equilibrium arguments, with a set of subjective views.

In the paper by Black on universal hedging, equilibrium assumptions are made to derive the universal hedge ratios. The formal proofs are contained in yet another paper by Black, “Equilibrium exchange rate hedging”, Journal of Finance 43, 899-908, which I could not find on the web.
However, you can find interesting comments on the subject in this other paper by Jorion and Glen http://merage.uci.edu/~jorion/papers/JorionGlen-1993-JF.pdf, such as “assumptions must be made to obtain the result [by Black]. In particular, the universality of the hedge ratio follows directly from the assumptions that impose homogeneity on world investors. Moreover, the assumptions require foreign investment to be in balance for all countries at all times.”

 

IMO The Black-Litterman model is an attractive way to mix priors with subjective views. Its most attractive properties seem to be that estimates of expected returns ( to which mean variance optimisation is notoriously sensitive ) are not required and that the optimal weights are consistent with the subjective views imposed via the extra-covariance matrix leading to more stable optimal weights through time*. The main weakness though seems to be the assumption that the Market portfolio is always in ‘equilibrium’ i.e. at ‘fair value’. Unfortunately one only has to look at the prices paid per dollar of dividends for the S&P500 over time to see that the consensus opinions as reflected by the market cap weights are not always perfectly rational and that ‘equilibrium’ if it exists at all is fleeting. Other estimation error avoidance methods like Ledoit-Wolf”s shrinkage and random matrix theory methods appear to give better out of sample results.

*See: He and Litterman http://papers.ssrn.com/sol3/papers.cfm?abstract_id=334304

 

Unfortunately, there can’t be a real equilibrium -in the sense of optimun- portfolio, but I guess that eventually, the equilibrium portfolio acts as a benchmark for those benchmark-linked managers. Some investment firms are using it that way: A small strategyc asset allocation group working on the starting point (equilibrium portfolio) and several managers linked to it.

 

 

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