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| bio | website | citeulike.org/user/lehalle/… |
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| location | ||
| age | ||
| visits | member for | 1 year, 1 month |
| seen | May 21 at 8:18 | |
| stats | profile views | 380 |
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Feb 27 |
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Why do high frequency traders use rapidly cancelled limit orders? You will find some generic knowledge about these kind of topics in this paper: Market Microstructure Knowledge Needed for Controlling an Intra-Day Trading Process - arxiv.org/abs/1302.4592 |
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Feb 5 |
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Position management and market-making techniques @Freddy of course you are right. The fact is that market making loose money in case of unexpected jump. Of course in the model of the paper you can obtain some robustness to jump (if you compensate it on the intensity of the flow). But you will post quotes very far away from the mid point, thus beging out of the market more often. |
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Feb 5 |
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Position management and market-making techniques @Serg: this assumption is commonly used, to avoid it, you should have a "passive market impact model". Nobody have one. The only other possible viewpoint (according to me at least), is to be 100% non parametric. I develop such a viewpoint in "Optimal posting price of limit orders: learning by trading" with S Laruelle et G Pagès ( arxiv.org/abs/1112.2397 ). Very good question about testing the optimal policy against the 'theoretical model', it is the usual first step and we implemented it. It works as soon as the volatility is not too high (as expected). |
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Feb 4 |
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Position management and market-making techniques yes I am one of the authors of the paper, @Freddy, the assumptions we made are realistic in the sense that when the market is not "stressed", they are reasonable. When the market is stressed, no model will work... |
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Sep 1 |
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Strategy Risk and Portfolio Allocation Model (copy from nuclear phynance) welcome at quant.se |
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Aug 31 |
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Strategy Risk and Portfolio Allocation Model (copy from nuclear phynance) it is not "my" question, so I will eventually post answers... |
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Aug 30 |
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Switching from Matlab to Python for Quant Trading and Research I would just add few points on the matlab side: (1) if you buy the compiling toolkit, then you can redistribute your code everywhere without paying more license fees. (2) matlab statistical tools are very good and properly coded. |
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Aug 23 |
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How to normalize different instruments by volatility? @Freddy, please do not think that formalizing answers to try to be clear is academic arrogance. I try to be as concise as possible, we have the chance to share the formalism of stochastic calculus, I just use it. |
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Aug 23 |
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How to normalize different instruments by volatility? @Freddy, the question was about normalization and not volatility definition. your generic remark about "there is no single answer" should be on renormalization and not volatility, don't you think? your answer is out of the scope of the question I think. |
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Aug 17 |
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How to normalize different instruments by volatility? @Freddy volatility of the price is the multiplier of the normalized random part of the returns. What do you call "returns volatility"? |
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Aug 8 |
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Reference request: Survey article on GPU in Finance @chrisaycock sorry for the naming "hardware programming", but FPGA and GPU are very similar in the mind of a lot of people. And in fact they are not that different. DSP, GPU and FPGA are ways to delegate to hardware some of your computations; that is why I put a tag "hardware-programming". What is a better name for a tag to group questions about "is GPU better than FPGA?", "should I use GPU to accelerate my softs?", etc. We have a lot of questions like this here. Please choose a tag so that we could group them and write a "wiki" summary on it. |
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Aug 6 |
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Analyzing an incomplete set of trades I tried to modify my answer to be more accurate: you need to use your knowledge of this market and the real constraints to find full sequences (or sequence that are most probably full). Then identify the gaps in terms of joint variables (price/quantity/duration/etc). Perform statistics on these joint variables to be able to compute likelihoods for each of them (Bayesian models are good that for). And then you can fill the gaps with the most probable values. |
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Aug 6 |
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How to choose a data center for deploying high frequency trading strategies? yes: it is a well-known effect. I tried to modify my answer, @RYogi. |
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Jul 16 |
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Multilayer Perceptron (Neural Network) for Time Series Prediction I modified my point on the hidden layer to answer to (A). For (B): the biais are also adjusted thanks to a gradient descent. My recommendation is: use regular perceptrons first, then if you discover than by averaging you seem to improve their performance, use a TDNN (they embadded a sliding window by construction). |
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Jun 10 |
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How to get an analytic result for option price based on this model? do you means that you would like to price under semi-martingale assumptions (and especially jumps)? you should look at Financial modelling with Jump Processes ( Chapman & Hall / CRC Press) by Rama CONT and Peter TANKOV cmap.polytechnique.fr/~rama/Jumps . |
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Jun 6 |
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What latency should I use for backtesting a high-frequency strategy? I mean: to arbitrage bid-ask crosses between two trading destinations. |
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May 8 |
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cointegration applied to Portfolio Construction & Risk management There is a generic page about cointegration, some answers to your question can be found on it: quant.stackexchange.com/tags/cointegration/info |
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Apr 30 |
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application of lie groups in finance It underlines the relationship between Lie groups and infinitesimal generators. Any tool that can be of use on Lie groups could be on SDE. |
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Apr 30 |
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application of lie groups in finance I like the second one: Boonlert Srihirun, Sergey V. Meleshko, Eckart Schulz, On the definition of an admitted Lie group for stochastic differential equations, Communications in Nonlinear Science and Numerical Simulation, Volume 12, Issue 8, December 2007, Pages 1379-1389. |
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Apr 30 |
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Real time stock volatility I already answered to a very similar question about computing high-frequency volatility |
