Why Quantitative Strategies Prefer Liquid Markets
Summary
The document explains several reasons a quantitative trading strategy may restrict itself to liquid, publicly traded assets that can be modeled. Low transaction costs matter when expected profits come from small pricing anomalies: trading costs can erase returns that are only a fraction of a percent. Combining many securities may help diversify the randomness in individual opportunities, while liquidity helps keep execution costs manageable.
Liquidity also tends to mean deeper order books, less price impact for larger trades, and a greater ability to exit positions promptly. Another response points to data availability: markets with more trading activity can provide larger datasets for model training. For a large investor, trading in illiquid assets may also change market liquidity and make positions harder to exit, complicating both returns and modeling. These are general rationales rather than quantified findings; the document does not define liquidity thresholds or show that every liquid market has low costs, deep depth, or suitable data.
Key ideas
- Low transaction costs are important when a strategy targets small pricing anomalies.
- Combining opportunities across securities may reduce the effect of randomness in individual returns.
- Deeper markets can reduce price impact and make it easier to exit positions.
- Active markets may provide more observations for training quantitative models.
- A large investor’s activity in an illiquid asset can affect liquidity and complicate execution and modeling.
Tags
Full text
# Why James Simons trades it only if it is liquid? # Why James Simons trades it only if it is liquid? On the website https://25iq.com/2014/07/09/a-dozen-things-ive-learned-from-jim-simons/ (mirror), James Simons cited “We have three criteria. If it’s publicly traded, liquid and amenable to modeling, we trade it.” Why liquid? ## Answer by Alex C (score 6, accepted) https://quant.stackexchange.com/a/35589 Liquid => low transactions costs. When you are trying to take advantage of small anomalies you need transaction costs to be low. [Added 2017-08-13] Simons does not believe there are big price inefficiencies; he does not think you can buy for 10 something that is worth 20 tomorrow. He thinks there are many small anomalies where a security is mispriced by a fraction of a percent. To profit from this you need: to combine many securities (so the randomness washes out) and to concentrate on securities with low transaction costs (if an illiquid security is "10 bid 11 ask" that is a 10% round trip transaction cost, no way you can overcome that with a fraction of a percent per month price appreciation). ## Answer by python_enthusiast (score 5) https://quant.stackexchange.com/a/35611 A market being liquid also means that the books are deeper. This implies that you can trade larger volumes without moving the market prices as much. A liquid market also allows you to reverse your position quickly and avoid being stuck with unwanted assets. ## Answer by python_enthusiast (score 3) https://quant.stackexchange.com/a/35673 A third interesting reason why the markets should be liquid is volume of data. If the models being used demand a lot of data to have a small error (as is the case in Deep Learning models), then liquid markets give you a large enough dataset to train your models. ## Answer by michaelcarniol (score 2) https://quant.stackexchange.com/a/35628 When the market for a security is highly liquid, a large, sophisticated investor can assume that his presence in the market for the security does not affect liquidity. When the market for a security is illiquid, a large, sophisticated investor must consider how his presence in the market for the security affects liquidity. To understand this intuition, start with a standard Kyle (1985) model, and suppose that an additional informed investor is deciding whether to trade the risky asset given an exogenous internal cost of capital. RenTech is large and sophisticated, and likely has a short-term investment horizon and a high IRR. If its presence in the market for the security affects liquidity, it might not be able to exit positions easily, and the returns process is likely to be less "amenable to modeling."
Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.