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« Created by: Co0olCat on: 06/24/08 at 09:55:33 »

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White papers on Algo (Read 91809 times)
qroach
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Re: White papers on Algo
Reply #45 - 12/17/08 at 15:12:54
 
Marco Vangelisti, March 2006

The Capacity of an Equity Strategy: Defining and Estimating the Capacity of a Quantitative Equity Strategy
http://www.qwafafew.org/filestore/download/469
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« Last Edit: 12/19/08 at 00:30:13 by Co0olCat »  
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qroach
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Re: White papers on Algo
Reply #46 - 01/29/09 at 15:22:43
 
Failure of Genetic-Programming Induced Trading Strategies: Distinguishing between Efficient Markets and Inefficient Algorithms
2007

http://www.loria.fr/~nnavet/publi/SHC_NN_Springer2007.pdf

Over the last decade, numerous papers have investigated the use of Genetic Programming (GP) for creating financial trading strategies. Typically, in the literature, the results are inconclusive but the investigators always suggest the possibility of further improvements, leaving the conclusion regarding the effectiveness of GP undecided. In this paper, we discuss a series of pretests aimed at giving more clear-cut answers as to whether GP can be effective with the training data at hand. Precisely, pretesting allows us to distinguish between a failure due to the market being efficient or due to GP being inefficient. The basic idea here is to compare GP with several variants of random searches and random trading behaviors having well-defined characteristics. In particular, if the outcomes of the pretests reveal
no statistical evidence that GP possesses a predictive ability superior to a random search or a random trading behavior, then this suggests to us that there is no point in investing further resources in GP. The analysis is illustrated with GP-evolved strategies for nine markets exhibiting various trends.
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statstrader
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Re: White papers on Algo
Reply #47 - 02/02/09 at 23:57:58
 
When do informed traders arrive in foreign exchange markets?

Gencay, Gradojevic, Selcuk †April 2008

http://economics.ca/2008/papers/0027.pdf

-----------------------------------------------
Abstract
This article examines the implications of the existence of private information in the spot foreign
exchange market. Our framework is a high-frequency version of a structural microstructure
trade model that measures the market makerís beliefs directly. We find that the underpinnings
for the time-varying pattern of the probability of informed trading are rooted in the strategic
arrival of informed traders on a particular hour-of-day, day-of-week, and geographic location
(market). Specifically, we document that informed traders not only pick the low activity hours,
but also attach the largest market weight to a particular market. The distributions of the
estimated arrival rates confirm the commitment of the informed traders to strategic trading
activities. In our framework, we acknowledge that an expected loss of informed trading to the
market maker is a function of both the probability of informed trading and its likely impact on
the price. The impact of the uninformed tradersí arrival on the daily foreign exchange price
volatility is about twice the magnitude of the one for informed traders. These effects are in
stark contrast to the findings from the hourly data that indicate dominance of informed traders.
Finally, the results relate the informational content of trading to the trade size and suggest
that the probability of the informed large trading is significantly higher than the probability of
uninformed large trading.
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Re: White papers on Algo
Reply #48 - 10/28/09 at 17:01:10
 
Erik Anderson and Paul Merolla and Alexis Pribula, JOURNAL OF STELLAR MS&E 444 REPORTS

Adaptive Strategies for High Frequency Trading
http://www.stanford.edu/class/msande444/2008/OrderBook.pdf

Abstract.

In this report, we discussed adaptive strategies for high frequency trading. We showed that use of the order book can increase profitability of trading strategies over first-order approaches. Moreover, we proposed a method to help reduce the impact of market shocks which uses Support Vector Machines and Independent Component Analysis. Although further back-testing is still warranted, these methods show promise. Further research directions include optimizing the trading rule to be used in conjunction with the price predictor and to incorporate additional risk-management above and beyond a predictor of market shocks. Moreover, the Support Vector Machine method could be optimized (tweaking the input data, varying the training window, etc.).
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sidharth
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Re: White papers on Algo
Reply #49 - 05/17/10 at 15:24:39
 
Jedrzej Pawel Bialkowski, Serge Darolles, GaŽlle Le Fol

Improving VWAP Strategies: A Dynamical Volume Approach  
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=932699

Abstract:    
In this paper, we present a new methodology for modelling intraday volume which allows for a reduction of the execution risk in VWAP (Volume Weighted Average Price) orders. The results are obtained for the all stocks included in the CAC40 index at the beginning of September 2004. The idea of considered models is based on the decomposition of traded volume into two parts: one reflects volume changes due to market evolutions; the second describes the stock specific volume pattern. The dynamics of the specific part of volume is depicted by ARMA, and SETAR models. The implementation of VWAP strategies imposes some dynamical adjustments within the day.
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Re: White papers on Algo
Reply #50 - 09/05/10 at 07:09:45
 
it give me great help .  thank you.
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Thought is already is late, exactly is the earliest time.
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Re: White papers on Algo
Reply #51 - 11/10/12 at 10:27:34
 
Does anyone have this paper : Dissertation Title: "Forecasting and Trading the GBP/USD Exchange Rate using a Nonlinear Dynamical Approach" †by Jose Antonio Ortiz Contreras ?Thanks.
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