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I'll just add that with Interactive Brokers you have to be aware of their cancel fees. Remember, Interactive Brokers owns Timber Hill, a very large and active market maker. They will discourage you from competing with Timber Hill through monetary disincentives, among other things.
For example, if you send a directed order (i.e., you don't allow IB to SMART ...
22
I'll take a stab at it, but this is a really broad question.
A direct answer: Bayesian models often use "probability that the counter-party is informed."
Indirect answers:
I think your assumption is that the algorithm operates on each stock individually, and has no knowledge of what it's doing in any other stock. But, it is likely that the algorithm is ...
22
The lead paper in the January 2011 Journal of Finance (Hendershott, Jones, and Menkveld) addresses algorithmic trading (AT). In short, they find that AT improves liquidity as measured by bid-offer spreads. Taking the econometrics as correct (it is in the Journal of Finance) the next question is if bid-offer spreads are a sufficient statistic for measuring ...
22
Hah! There is no such thing as the “rigorous mathematical underpinning” of high frequency trading - because HFT, like all trading, is not primarily a mathematical endeavour.
It’s true that many people who work in HFT have a mathematical background, but that’s because the tools of applied math and statistics are useful when analysing the large amounts of ...
21
It seems that your question refers to the microstructure noise defined in papers about intraday volatility estimates.
Originally, it comes from the bid-ask bounce, i.e. the fact that even if the volatility is zero, you have buyers and sellers at this price and consequently you observe prices at Bid or Ask prices, and not at mid-price. Because of that, if ...
19
The main issue measuring intraday volatility is called "signature plot": when you zoom in, the volatility measure (i.e. empirical quadratic variations) explode.
Similarly you have the "Epps effect" for correlations: when you zoom in, the correlations collapse (it is at least a mechanical effect).
For the volatility a lot of models can correct this:
- first ...
18
All HFTs are event driven. In the most basic sense, they have some model that is a function of order book events. For every order book event the model calculates some micro price that is the HFTs perceived fair value. This is often a function of the current bid, ask, depth, last n trade prices, inventory, etc. Given the most up to date view of fair value, ...
17
The term has a different meaning to different people.
to econometricians, microstructure noise is a disturbance that makes high frequency estimates of some parameters (e.g. realized volatility) very unstable. Generally this strand of the literature professes agnosticism as to the its origin;
to market microstructure researchers, microstructure noise is a ...
17
Some cynical but functional definitions:
It's what you can't model if you're not using tick by tick data
It's what proper quant pricing theory doesn't know how to model yet
It's information (order book behavior) that reflects momentary fluctuations in the supply/demand of a given contract, rather than its underlying value (eg an arbitrage free price)
The ...
16
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 more ...
14
The expression you have is fine. But more generally, for the intraday volatility, I don't think there "the correct definition". More like, whatever works in the given context. I found the following notes by Almgren pretty useful:
http://cims.nyu.edu/~almgren/timeseries/notes7.pdf
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There are few things to consider.
Trading moves the price, to minimize market impact and maximize return it is generally optimal to split an order in several child orders. See the Kyle model.
Splitting optimally dependents on specific assumptions that you make. The simplest (and first) approach is that of Berstsimas and Lo (Optimal Control of Execution ...
14
There are many specialised products for HF tick data. In addition to KDB which you mentioned, there is OneTick, Vertica, Infobright, and some open-source ones like MonetDB etc. (see http://en.wikipedia.org/wiki/Column-oriented_DBMS).
My experience is that Column Oriented Databases are overrated when it comes to tick data, because very often you request the ...
13
This answer is my ongoing attempt to consolidate some recent commentary on this hot topic.
A good place to start for anyone thinking about this question is the Economists's Buttonwood: Not So Fast, which mentions recent research by Biais and Woolley (2011) and Dichev, Huang, and Zhou (2011).
Does Algorithmic Trading Improve Liquidity? This paper claims yes....
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IMO transaction data is a better approach, because you have both sides of the trade agreeing that the price is "right." The literature tends to decompose the transaction price $P$ into a true/efficient price $P^e$ plus micro-structure noise, which I think originates from Hasbrouck '93 in the Review of Financial Studies. So you end up with something like $$P^...
13
This question has been re-opened again after (rightly) being closed as too broad for the purpose of clearing some misconceptions regarding one of the answers here.
The main idea that is to be stressed here is this: When it comes to high frequency trading, biggest or "as many as you can get" is rarely true.
Not only is it false, it is impossible in terms of ...
13
There are rigorous econometric definitions, as has already been eluded to by others. For practical purposes, microstructure noise is a component of a price process that exhibits mean reversion on some (possibly time-varying) frequency.
This reversion is particularly attractive to liquidity provisioners, who seek to profit from this noise component (along ...
13
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 ...
12
HFT seems to be the big money making mystery machine these days.
That's not correct. By its very nature, HFT can only produce a limited amount of revenue. The big money makers are still the large hedge funds that charge 2-and-20 on their \$10B worth of assets.
There are not too many players there at the moment so markets are not completely efficient?
...
12
There are typically two important metrics:
Order to Accept. This measures the round-trip time it takes your application to send an order to the exchange and get an accept, cancel, or execute back. Think of it as the minimum amount of time required for you to ask the market to do something and know whether it's been done. This plays an important role when ...
12
The best explanation/theory that I have heard about Knight's erratic trading was put forth by Nanex. I have pasted their summary of findings below.
We believe Knight accidentally released the test software they used to verify that their new market making software functioned properly, into NYSE's live system.
In the safety of Knight's test laboratory,...
12
"quote spam", "book colouring", "quote stuffing", etc encompass any mechanism to modify the shape of the orderbook by a market participant who does not intend to really buy or sell shares thanks to these orders.
It means that someone fills the bid side of the book with 10,000 shares at different levels of price and does not want to buy at all, or only 100 ...
11
Market makers place quotes on both sides (ie, the bid and the ask). Depending on the market, the MM might even be contractually obligated to provide liquidity within some threshold. NYSE's designated market makers (who replaced the specialists a few years back) are an example. Even when there is no explicit requirement, the MM will quote both sides and ...
11
Why not just use the weighted mid-market price, quoted as (Bsize * Aprc + Asize * Bprc) / (Asize + Bsize)? This measure doesn't suffer a bounce per se and allows you to directly take moving or exponential moving averages.
11
This answer summarizes some of my comments.
HFT is certainly a very hot topic these days, but it's hard to point to any one reason. A large part of it is the mystery and the profits, but also part of it is the relative novelty. Note that there is no lack of papers about medium and low frequency strategies, it's just that they are not labeled as such. Medium ...
11
Using months of proprietary data that labels participants by their participant ID, it has been found that during periods of significant volatility, the composition of HFT participants in the book remains mostly constant as a fraction of the total BBO composition.
What really changes, it was found, was that the fraction of low-frequency traders aggressing on ...
10
Intraday seasonality is a major factor in comparing volatility at different times of day. Most time series display significantly higher volatility in the morning EST than mid-day. For US exchange-traded products, volatility picks up again just before 4:00 PM EST. This is known as the u-shaped volatility pattern for exchange-traded products. A proper ...
10
Joel Hasbrouck (imho, a leading expert in market microstructure) has a paper on this:
http://people.stern.nyu.edu/jhasbrou/Research/Working%20Papers/HS10-11-10.pdf
From the abstract:
Our conclusion is that increased low-latency activity improves traditional market quality measures such as short-term volatility, spreads, and displayed depth in the limit ...
10
I can think of an application in options pricing. I came across the following paper a long time ago but think it explains FT very eloquently as applied to pricing options under BS:
http://maxmatsuda.com/Papers/2004/Matsuda%20Intro%20FT%20Pricing.pdf
The fun starts on page 112 but it relies on the 1998 paper by Madan and Carr.
What I like about the paper ...
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The "price protection" refers to RegNMS in the US. A stock exchange that does not have the best price must route all order flow to the exchange that does. The SIP in the figure is a consolidated feed that lists the best price among all exchanges.
Consider this example: a broker sends a market order to buy JNJ to NYSE where the best offer is \$86.97. However,...
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