Tag Info

Hot answers tagged

6

The primary quant skill needed to make the market is optimal control (a typical paper is Guéant, O., L, and J. Fernandez-Tapia (2013, September). Dealing with the inventory risk: a solution to the market making problem. Mathematics and Financial Economics 4 (7), 477-507), because you need to control your inventory and adjust your quotes accordingly: be ...


4

I have heard of several allegations in the recent days, but they are mostly baseless. However, there are a rare, few trading venues whose matching rules are most often accused of giving unfair order execution advantages to certain firms. These usually arise from violations of the standard price-time priority: IEX's broker priority rule. "All orders will ...


3

Here's a way to think about it: imagine you can do something in an ASIC (i.e. directly in hardware). However, the process of fabrication is in itself expensive, and you get a design that you cannot change afterwards. ASICs make sense for predefined tasks such as Bitcoin mining, well-known data processing algorithms, etc. On the other hand we have ordinary ...


3

Unfortunately, the ability and tools to develop a low latency trading system are extremely commoditized and will be insufficient for you to make a living in this field. An overwhelming majority of electronic market makers are staffed 100% by PhDs because trading experience and research compose their primary differentiators, e.g.: SIG EMM - 100% PhD. DRW ...


3

Well the answer depends on what are you considering a fee? Do you included per trade regulatory fees or just exchange fees? Many exchanges will pay you for being the passive side of a trade, so technically the fees in that case are negative. For the big exchanges, I'm not sure that you can negotiate the fee's. I'll confess I've never tried and the ...


3

Short answer: It offers some degree -- and in many cases, a greater degree -- of comparability between two types of data (different assets, returns, etc.) Long answer: You may already know this, but keep in mind that "normalization" can mean different things (see this question). There are various methods and purposes for normalizing data (financial or ...


3

Successful strategies in both areas can have the same math requirement. It just depends on the algorithm. PhD level mathematics is not a requirement in either area, despite the impression you may get from academic papers (note that a lot of these papers use math to build a sim market, which is completely dislocated from what a researcher needs to do). I feel ...


3

In my experience HFT has to balance the reward of any strategy with risk. In the case of a news-based trading strategy, the risk can be enormous, which means the algo will need a very high expected profit in order to trade the news. After important news events, volatility skyrockets and persists for some time (sometimes even days). If the market were able ...


3

Very interesting question. I am not an expert on the subject, however, I was able to find a collection of papers on the subject that should get you started. Here is a good and very informative paper that walks you through several tick by tick volatility estimators that seek to reduce the volatility imposed by market micro-structure: Efficient estimation of ...


3

Many of the strategies are motivated by objective functions (contour integrals) in the complex plane and the elements of complex linear spaces, so I'd recommend at least for an applied understanding: Saff, E. B., and Snider, A. D. Fundamentals of Complex Analysis with Applications to Engineering, Science and Mathematics. In addition to Saff and Snider, I ...


2

I subscribed recently to ActiveTick, primarily because of the Excel add-in they offer. The ability to feed real time data into Excel equations sounded really promising, but what I have found is a service that is incredibly unreliable. I’ve been sitting here for the last 5 hours watching the add-in try to connect with the server, but no luck. This is about ...


2

The direct filter approach (DFA) is a time series filter which is calculated in Fourier space. DFA minimizes the mean square error of a time series $y_t$ compared to a filter estimate $\hat{y_t}$ $ E[(y_t - \hat{y_t})^2] = \frac{1}{2 \pi} \int_{-\pi}^{\pi} |\Gamma(\omega)- \hat{\Gamma}(\omega)|^2 h(\omega) d\omega $ The minimization is done in the ...


2

In addition to @madilyn's answer, there is one point that needs to be addressed and that is often called an unfair advantage although it is merely a competitive advantage. Take the US Equities market. There are now several venues on which the same symbols are traded. If one HFT acquires information about one symbol in one venue - e.g. due to a limit order ...


2

If I was in your position I would start to research how I can create a web server is C++ and expose calls to create a REST service. In other words, can you make your code status output to HTTP? From there, the rest should be easy. You would just need to create a GUI that can access REST services, which virtually all modern languages can. You could focus on ...


2

I think it will also depend on the amount of the orders you will entering. In FXInside it will also depend if you are just aggregating or using a HUB, and even if you use the HUB it will depend if you are enable to "make liquidity" otherwise you will be only sending an agressive watch order waiting a market move. I don't have any number to share with you, ...


2

Features could include: Bid-ask spread Bid-ask volume imbalance Signed transaction volume The sign in the Signed transaction volume is positive if the buyer has issued a market order and negative if the seller issued a market order. A great introductory plain English paper on high frequency trading machine learning applications can be found here. A ...


2

First of all, I do not believe the "optimal smoothing" of an estimator (like the mean or the variance) and the "regression case" are the same. The smoothing of an existing estimator (like mean or variance in the blog post), is an univariate problem, where the regression is a multivariate one. In the regression case, you should be able to change the ...


1

Have you considered socket programming? if you need 'real time' control http://www.codeproject.com/Articles/586000/Networking-and-Socket-programming-tutorial-in-C If you only want to reset the parameter periodically(like end of the day), you can setup a service and communicate via http/rest/soap. "fetch order and trade history" should be done in a separate ...


1

Your question really makes not much sense. It's like asking how much of the wiring in trading infrastructure uses optic fiber and how much of it uses copper. The best answer that we can give to you is that an FPGA is not a magic bullet. Vendors like Cisco claim they have achieved the same results with high performance NIC's ...


1

You will find that the level of success you have using Neural Networks (NN) as a tool for financial market prediction is strongly dependent on what initially appear to be some quite subtle factors. In particular: Input data: You mention using "certain technical indicators". I assume that you mean the standard TA set of price-based indicators such as Moving ...


1

Neural networks are a supervised machine learning algorithm. Unlike unsupervised machine learning, the key to supervised machine learning is the selection of input factors and explicit labeling of outputs. Input factors have to be manually selected, such as your combination of technical / fundamental / statistical indicators. Outputs have to be ...


1

FIX has some known deficiencies. Repeating groups is one of them. It can be costly in terms of latency to parse repeating groups inside repeating groups, requiring recursive calls. I prefer protocols that send a first message signaling that N messages will follow with the group info. FIX is also too verbose consuming too much bandwidth. For that they have ...


1

This is a very good observation that I wrote about in my undergrad studies. I also believed that markets were efficient but not precise. I used the example a few years back regarding a tweet (roughly after the Boston bombings). The tweet was regarding terrorist attacks in which markets fell sharply and then recouping all the gains as news later indicated ...


1

KDB is a column oriented database and is optimized for time series. As far as I know there are no libraries available for statistical testing and you pretty much have to write things on your own. This page has tutorials http://code.kx.com/wiki/Main_Page You can download the free version from here http://kx.com/software-download.php The most popular book ...


1

For the question in your title, The mean reversion of the volatility is due to the Moving Average part of the volatility process. The solution would be to set $\beta = 0$. In other words you have to use an AR process for the volatility (so an ARCH model for price). The restriction in p and q come from the estimation process of the parameters. You test ...


1

You're playing against people who would take the opportunities you're going for in microseconds or milliseconds. What kind of latency are you getting with TradeStation? You need to do two things: measure this latency. get tick by tick data and do a real backtest. Probably your opportunities are gone in 10 milliseconds so you need to do this.


1

I know it's not what you want to hear, but the smaller the time-frame the more limit orders should be focused on (which can change the design of a strategy entirely). Due to the nature of the futures markets, having a gap in liquidity can obviously cause discrepancies with market orders, but can guarantee some nature of being filled using limits.


1

Definitely check out Quantopian and Zipline. Quantopian provides a free research environment, backtester, and live trading rig (algos can be hooked up to Interactive Brokers). The algorithm development environment includes really handy collaboration tools and an open source debugger. They provide tons of data (even Morningstar fundamentals!) free of charge. ...


1

Perhaps not the most encouraging answer, but: I would think that it is contingent upon the specific implementation, magnitude, regularity, and transiency of arbitrage available as well as the volatility estimate time-scale. In a very simple case, the existence of arbitrage opportunities would likely result in larger fraction of informed traders (relative to ...


1

If you look at it from a mathematical point of view - presence of arbitrage should not matter for volatility estimates. Absence of arbitrage can be associated with the existence of an equivalent martingale measure for the bank account numeraire. (first fundamental theorem of asset pricing) Let's assume the real world process is something like ...



Only top voted, non community-wiki answers of a minimum length are eligible