24

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 ;{)}


22

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. 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 ...


18

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. ...


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 ...


12

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 ...


11

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

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 ...


11

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 ...


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

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 ...


10

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 ...


9

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 ...


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

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

The market-maker makes a bid-ask spread $\delta$ around the reservation price $r$. So at any time, the market-maker quotes the bid price $$ p_b = r - \delta/2, $$ and the ask price $$ p_a = r + \delta/2. $$ Bid price is hence always below the reservation price and ask price is always above the reservation price. The reservation price $$ r = s - q\gamma\...


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 ...


7

Your question is twofold How a market maker should adjust its quotes on a vol surface with respect to his inventory? How to adjust the vol surface when a new trade is observed on the markets? Let me focus on the market making question, and that for you need to be familiar with optimal trading and optimal market making literature: A breakthrough has been ...


7

If you are market making equities or futures you tend to make your profits over the short term by flipping your inventory. So if I'm showing 3.00 bid at 3.01 ask on a stock I'm going to tend to flip it pretty quickly for 0.01 profit. The guys that bought and sold from me may make/lose money depending on the length of their holding period and market direction....


7

You could also look at how each price level is made up. For example how is the 18 lot on the bid price 0.0995 collated. Is it a 5 lots, 5 lots, 7 lots and 1 lot. You can do this on certain exchanges as they have an enhanced order book where you can see every insert, modification, delete and trade. This may require you to recreate the order book, which ...


6

The best options AMM guys are rumored to capture roughly 1/3tick per round trip, net of transaction costs + implementation shortfalls. I had worked for a regional index options MM. With the growth of competition in the recent years, expected returns are actually much lower than that today. So realistically, in today's environment, you could net maybe 1/...


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

I'm doing this from memory, but as I recall $q_{\text{max}}$ is the maximum inventory on any side that you wish to take (otherwise you might build up a huge position if you are adversely selected). Later papers such as this one https://arxiv.org/pdf/1105.3115.pdf helped my understanding. As it actually happens, I implemented these algorithms and had a go ...


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

I used to work in OTC, many of the deals would be so individual I can't imagine an algorithm being able to cope. In addition there were some extra factors like how we feel towards a counterparty and sometimes the broker over whether we would step in or not. I now work in exchange traded futures and options (listed options), and I can say the number one ...


5

The primary way ECNs determine if a liquidity taker's flow is 'toxic' or not is by looking at aftermath charts. The aftermath chart shows the average mark-to-market profit of trades done by the liquidity taker as a function of either time or number of top-of-book updates (optionally broken down by currency pair). The trade profit is usually viewed from the ...


5

Yes, it is. There is plenty of information about it online. E.g. here's a related very recent article: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2874957, here's a link to a discussion on Barclays lawsuit with nice liquidity charts: https://jackgavigan.com/2014/06/30/barclays-smoking-chart/ You can also find related discussions on http://tabbforum....


5

When trading options it is most useful to think in terms of implied volatilities, rather than option prices. For vanilla options, there is a one-to-one relationship between implied volatility and price, and the Black-Scholes formula gives the conversion between the two. Since price and implied volatility are interchangeable, you can convert both the bid and ...


5

Your question is too broad to give anything but a very general answer. Data mining in the raw form won't do any good. At the minimum, you will pick up thousands of spurious correlations. You cannot go from data to a solution. You have to work in the opposite direction, you have to posit some model of the world and then test it. You must have an existing ...


5

The real reason for the literature you're seeing is that constrained optimization problems are often much easier to solve and give rise to simpler, more elegant results or tractable analytical solutions. It's entirely a mathematical motivation, not a practical one. The "cop-out" reason (which is not completely invalid) they give to justify the terminal ...


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