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12

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, ...


12

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 ;{)}


11

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 ...


11

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 ...


9

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 ...


8

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 ...


8

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 ...


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: ...


7

Market makers covers a broad range of shops, from large investment banks to small proprietary trading firms. So working capital can be in the millions or the billions, and leverage can be anywhere from 2x to 30x. This is no different from buy-side firms, which includes a variety of both asset managers and retail investors. There is tons of diversity among ...


7

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 ...


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

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 ...


6

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


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

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.


5

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 ...


5

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


5

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 ...


5

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

Your friend might be right, if, for example, he was talking about making a market in a set of low liquidity stocks. But that usually requires a market-making model where you're inventorying shares, for longer periods of time, which adds risk. Returns can be 'good' though. There are other scenarios, that are exchange-model dependent, that would also ...


4

The problem with this question is that the real world answer is probably different than any theoretical answer. Below is my stab at some "real world" nonsense. 1) Assuming that both Foo and Bar have the same market capitalization and no debt, their market caps would be co-integrated (over time, they wouldn't stray too far from each other). 2) Because of ...


4

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 ...


4

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 ...


4

All things being equal, stocks with the highest bid-ask spread present the greatest opportunity for the market maker The size of the opportunity (i.e. revenue expectation) can be represented as Volume * Bid-Ask Spread. Your algorithm should rank-order that revenue expectation Stocks with high current market values will tend to have narrower spreads and be ...


3

Update via Bloomberg Knight Capital Group Inc. (KCG)’s $440 million trading loss stemmed from an old set of computer software that was inadvertently reactivated when a new program was installed, according to two people briefed on the matter. Once triggered on Aug. 1, the dormant system started multiplying stock trades by one thousand, according to the ...


3

There are two excellent choices for implementing prediction markets: (1) Use book orders that stand until filled, just as intrade.com does. (2) Use an automated market maker (like Robin Hanson's) that stands ready to make trades. The book orders model is very simple to implement, but can suffer from very wide Bid/Ask spreads. And, it can be tough to bet ...


3

I don't know about an algorithm, but you probably want to pick the stocks that have the most ways to hedge, or the ones with the least idiosyncratic risk.


3

It sounds like you're trying to filter your input event stream so as to reduce noise. By reducing noise you'll reduce the number of cancel/replace's you're doing and, hopefully, have a better order-to-fill ratio. I would investigate algorithms from control theory, in particular dynamic linear models like Kalman. The problem with denoising is you want to ...


3

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 ...


3

This differs from exchange to exchange but in Toronto (TSX) the rule is that the unfilled amount becomes a limit order at the last sale price. A market priced order is an instruction to trade the order at prices currently established by the opposite side of the market. Such orders have no trader defined limit on the potential trade price but these orders ...



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