# Tag Info

22

In fact you have three papers available to go further: The Avellaneda-Stoikov one, with proper model and an approximate solution The Bayraktar-Ludvkosli one, with a solution for the linear utility function The L-Guéant-Fernandez one, with a full solution for a generic utility function I prefer the last one ;{)}

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 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 ...

17

Flow trading is in spirit very similar to market making - such firms make a profit by earning a spread. There are 3 common ways this is done. Suppose a client wants to buy 100k shares of XYZ, which is publicly quoted at 1M@10.01 bid, 1M@10.03 ask. For sake of simplification, assume sub-penny pricing is not accepted in the jurisdiction where XYZ is listed. ...

15

An interesting starting point is The Cost of Latency by Moallemi and Saglam. After setting up a simple order execution problem --- in which a trader must chose between a market order and a limit order and guarantee execution over a fixed interval $[0,T]$, they proceed to derive a (complex) close form solution for the optimal strategy and evaluate the impact ...

13

There are hundreds of different market making strategies that exist. I'm going to change "market making" into liquidity provision and try to give you some areas to begin your research. 1) Arbitrage. Basically you are going to be quoting in one market using limit orders so that you when you get filled you can spread it into another market where you will ...

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

You need to differentiate between OTC and listed options in order to appreciate the fact market makers are still active and relevant in either segment: Listed Options: Actually most listed options market making is governed by market making algorithms, however, most such algorithms are implemented with manual overlays. Something very similar goes on in the ...

11

The way market makers mark their volatility curves is by using models which 'fill in the gaps', i.e. they will make a price for a given option even if they do not believe this option is going to get a lot of volume. They are still willing to go long/short because they have a strategy to hedge their overall position (i.e. by managing their greeks and expiries)...

11

A good place to start learning about option market making using quantitative techniques is Euan Sinclair's Option Trading (chapter 10 is devoted to market making techniques). He also gives a decent introduction to a more sophisticated quantitative market making technique which he calls information-based market making. Specifically, he explains how to apply ...

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

Most organized markets have intermediaries to match buyers and sellers who may arrive at different rates. These intermediaries are typically called market makers because they "make markets" by buying from people who want to sell and selling to people who want to buy. Since market makers take on risk to provide liquidity, they generally need to be ...

10

I didn't quite understand your objection. Most theories of market making are derived from a famous paper by Jack Treynor (The Economics of the Dealer Function). In the theory, there are initially no market makers, but there is a backstop seller (in this case someone willing to sell large amounts at 10.10) and a backstop buyer (a Warren Buffet ready to buy ...

9

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 ...

9

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 Bonds/...

9

The paper "High Frequency Trading and The New-Market Makers" by Menkveld will likely have information that will be interesting to you. The paper breaks down the activity of one HFT in a European market. It provides statistics such as the # of trades, capital required, average profit, loss, etc. You can judge for yourself whether you trust the numbers based ...

9

Pete's seven year old answer is just as relevant now as it was in 2011. None of the limiting factors of their API has changed since then, so this is essentially an extensive reiteration. The Interactive Brokers API is not suitable for high frequency trading execution. However the main reason that this is the case is not necessarily what would come to mind ...

8

There is a paper of mine answering To this question: Dealing with the Inventory Risk. A solution to the market making problem by Olivier Guéant, Charles-Albert Lehalle, Joaquin Fernandez Tapia.

8

At the risk of stating the obvious: market gaps are a problem only when the market maker is holding a position and the market gaps against them. So the gap problem is really an instance of a more general problem: inventory management. The market maker's goal is to profit from the bid-ask spread. They prefer to be flat, but at any given moment, they could be ...

8

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 ...

8

I found this power point and this paper to be an excellent source on this topic. Here is a quote from the paper: A square-root singularity for small traded volumes is highly non-trivial, and certainly not accounted for in Kyle’s classical model of impact [11], which predicts a linear impact ∆ ∝ Q. A concave impact function is often thought of as a ...

7

Volatility Trading by Euan Sinclair is a good book to get you started.

7

My favorite culprit is quote stuffing, which can be used for a lot of things, including mapping the topology of the exchange servers themselves. The general idea is to look for bottlenecks which can then be lagged with more targeted quote-stuffing to create arb opportunities. Nanex's flash crash analysis covers this to some extent: http://www.nanex.net/...

7

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 EMM ...

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 of ...

6

There is no way to calculate returns here. Let me stop you right there. You didn't open a brokerage account with zero dollars. The money you put-up for margin is your starting position. After a year of trading, you have a stopping position represented by a different amount of money in your account. The change from your starting position to your stopping is ...

6

This is a very difficult question. First of all you should read Almgren's slides on the topic: Using a Simulator to Develop Execution Algorithms. First you need to backtest your strategy against a "replayer". Ok it is not perfect, but it gives you information anyway. Provided you add some "sanity limitation" to this simulator (i.e. do not allow you ...

6

My understanding (devoid of any mathematical grounding) is as follows. v = Turnover PER UNIT TIME n = Shares you need to execute therefore n/v = Number of units of time required to execute your size at the normal turnover rate Realized vol follows a SQRT(T) heuristic. Given that we can now rewrite the transaction cost formula purely in terms of vol ...

5

For single stock options against index options, this may be of interest: Dispersion -- A Guide for the clueless

5

Assuming that: limit prices of Long and Short orders are equally pre-calculated in all 3 strategies; there is no risk-free return; strategies 1 and 2 have equal quality, and strategy 3 is slightly better. However, the only advantage that strategy 3 takes over 1,and 2, is better location of the orders in the price level queue. In case of FIFO (price-time ...

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