# Tag Info

18

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 ...

15

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 ...

10

Since Quant Cup 1's objective was an efficient price/time matching engine, the data structure of the winning implementation might partly be what you are looking for. Else the setup of LOBSTER is supposed to be quick.

10

I've not yet read it, but Lehalle's recent book is bound to be a goldmine of good micro-structure bits and pieces. Market Microstructure in Practice EDIT: I'm reading the book now, so far it's quite good.

9

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 ...

9

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) ...

8

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 ...

7

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 ...

7

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 ...

7

DSpace@MIT - High frequency trading system design and process management (non-printable) This thesis provides a detailed study composed of high frequency trading system design, system modeling and principles, and processes management for system development. Particular emphasis is given to backtesting and optimization, which are considered the most ...

7

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 ...

7

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 ...

7

There are several. This list is from Giyenko et al (2008)---in their work they compare all these different measures--- and includes spread proxies and price impact proxies. As for spread proxies: "Effective Tick" (Holden 2007, Giyenko et al 2008) "Holden measure" (Holden 2007) "LOT Y-split" (Giyenko et al 2008) "Roll measure" (Roll 1984) "Gibbs measure" ...

7

This paper Dealing with the Inventory Risk. A solution to the market making problem, has a full bibliography and explains the intra day market making mechanism. The model is made of two components: a diffusion of the fair price (to model the market risk) a point process (with an intensity in $A \exp -k \delta$ (where $\delta$ is the distance to the fair ...

7

I recommend reading Cao, Hansch, and Wang (2004) "The Informational Content of an Open Limit Order Book". They present a simple model for an order-book price called the weighted price ($\mbox{WP}$): $$\mbox{WP}^{n_1 - n_2} = \frac{\sum_{j=n_1}^{n_2} (Q_j^d P_j^d + Q_j^s P_j^s)}{(Q_j^d + Q_j^s)}$$ Where: $n$ is the order book level $Q_j$ is the size at ...

6

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

6

i am not a F# expert but when it comes to performance and thread safety try sorted list or hashset. sorted list if the data needs to be sorted (it gets sorted when added to the list) otherwise hashset, no sorting hence better performance. they are both generic. in addition i would think you need thread safety when reading/writing/updating your data in ...

6

Are you after the famous paper from Christie and Schultz? Christie,W., Schultz,P., 1994. Why do NASDAQ market makers avoid odd-eighth quotes? Journal of Finance 49,1813–18 40. From the abstract: On May 26 and 27, 1994 several national newspapers reported the findings of Christie and Schultz (1994) who cannot reject the hypothesis that market makers ...

6

The best paper is probably Relative Volume as a Doubly Stochastic Binomial Point Process - James Mcculloch. In this paper the volume is modelled via a Point Process, and theoretical laws are derived (with confident intervals, etc). And if you can wait few days (it will be available very soon), we put elements about this in Market Microstructure in Practice, ...

5

Additionally I would recommend Evidence-based technical analysis by David Aronson It explains the whole process (including the complete statistical background) of rigorously setting up the basis for your trading system. See for a short summary of important points here: CXO Advisory See for a review here (including some practical advice and programs how ...

5

In addition to Chan's Quantitative Trading, I have also found the description of trading systems in Rishi Narang's Inside the Black Box to be informative and interesting. There are a few chapters there that give some details on system development, but they are very broad overviews.

5

Normally, an order is indeed routed to a different exchange to fill at NBBO. The exchange will then levy a fee for this routing. I'm not sure how the exchange actually chooses where to route in the case of a tie; I suspect that decision is up to the exchange operator so long as the SEC agrees. As for an ISO order, the sender is effectively taking ...

5

I don't know if you can really improve, the point of Market Making is that you don't know when you'll be executed. It also depends a lot on the type of product you're trading, it's not the same business Market Making far from the money options (where you will never be executed but just offer a reference price and answer traders phone calls) and MM on ...

5

You have two ways to estimate your position in an order book: first if you have access to an ITCH feed, you can recognize your order into the ITCH updates, and know exactly where you are, but you will have to build an engine to translate an order-by-order ITCH feed to a limit order book; or you have to use estimates; the easiest way to build one is to ...

5

Your question is very vague (e.g. what are you trying to measure, and what "tick data" do you have), but I'll give you some pointers: In general, when people consider how prices evolve, they will tend to think about things like volatility and correlation dynamics. So I would start by defining exactly what you want to measure. The irregularity of time ...

5

If you're missing ticks, then no technique will get those ticks back. If you have two sources, then designate one source as the primary feed and then fill-in gaps from the secondary feed. Of course, you'll have to mind the timestamps when determining whether the secondary feed can be used properly.

5

Classical book on market microstructure is: Market Microstructure for Practitioners by Larry Harris. It's a bit outdated (2002) and missing few recent market developments like dark pools etc. but the way it currently is it's already highly recommended reading. Personally I'm waiting for the next edition of the same book, and surely many others waiting as ...

4

In terms of system design, I learned the most by reading the developer guides and exchange connectivity specs for various exchanges. You probably won't be connecting to these directly, but understanding how the sessions, book updates, snapshotting works, and what events can occur is very useful. Also, google for the Max Dama automated trading PDF, which ...

4

I just finished "High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems" by Irene Aldridge -- I think it provides a very good overview of HFT, considerations of different aspects of trading systems, and good introductions to many formulas and research.

4

Statistical volatility is the standard deviation of a window of log returns. For example, 30-day statistical volatility is the standard deviation of 30, one-day log returns. The log return comes from the assumption that log stock returns are normally distributed. Statistical volatility differs from implied volatility which is the volatility input to some ...

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