Understanding the downsides in of trading in smaller exchange

External question — Quantitative Finance Stack Exchange Author: Kimmo Hintikka Original post: https://quant.stackexchange.com/questions/33756 License: CC BY-SA 3.0 — https://creativecommons.org/licenses/by-sa/3.0/ Adaptation: HTML converted to plain text; contact email addresses removed. I've been algo trading a small portfolio within NYSE for about a year now. And while do end up running positive P/L results are far from spectacular. I ran a test using my strategy in OMX Stockholm with much better results even with higher commissions/slippage. Beeing from Finland indices traded there are much more familiar for me as well. I am really keen on starting proper backtests & paper trading with a real-time data feed, but I would like to understand what I need to take into account trading in a much smaller less liquid environment? My list of worries: Slippage Risk hedging challenges due to low derivate/options trading volume Market manipulation. Few market makers are responsible for more than 50% of the volume in quiet trading days. Complex forex management, Nordic OMX has listings in 4 currencies. Is there something else I need to take into account compared to trading in larger more liquid exchange?

External answer — Quantitative Finance Stack Exchange Author: misantroop Original post: https://quant.stackexchange.com/a/33794 License: CC BY-SA 3.0 — https://creativecommons.org/licenses/by-sa/3.0/ Adaptation: HTML converted to plain text; contact email addresses removed. Keep in mind the selection is much smaller. US exchanges have thousands of relatively liquid listings, OMX Helsinki has less than 50. If you factor in correlation then on any given week you might only have a few good opportunities (vs. hundreds in a large, liquid exchange). Currency conversion isn't an issue with a broker like IB as it's done on-the-fly. Some brokers might require you to only trade in your base currency. The positive side is that exchanges which don't get as much attention might have better opportunities as there's fewer players and you might be trading against big, slow pension funds. The more liquid the market, the bigger the fish you're competing with.

External answer — Quantitative Finance Stack Exchange Author: David Addison Original post: https://quant.stackexchange.com/a/33802 License: CC BY-SA 3.0 — https://creativecommons.org/licenses/by-sa/3.0/ Adaptation: HTML converted to plain text; contact email addresses removed. I think you've nailed down the main points. I will only add two thoughts based on my experience with OTC trading: Volatility The flip side of inefficiency Slippage versus impact The volatility on smaller, lesser known exchanges could be more intense due to greater inefficiencies. By volatility, I don't mean just day-to-day noise, but long-term dislocations and extreme swings in both price and fundamental drivers of price. Anyway, I presume inefficiencies are what you're after in the first place. ...which leads to bullet two: "markets can remain irrational for longer than you can remain solvent". Presuming you're entering an inefficient market because the long term expectancy from identifying inefficiencies is greater, there is also a darker side of inefficiency which may be hidden from plain view. The flip-side of inefficiency implies that price and expected value of price can diverge for quite some time resulting in large losses even if you are "right". But then again again, the market is always right. Because implementing said strategy in an illiquid market could fundamentally change the expectation, I believe that is is important to think about the difference between slippage and impact. First, slippage does not equal impact . I define slippage as the realized transaction price in relation to the published transaction price. For example, if my market on close order was filled at \$100.1, when the the published closing price was \$100, my order experiences slippage of 10 bps (.1%). On the other hand, market impact is an estimate for how an order changes both the short and long-term equilibrium price. As a result, impact cannot be directly observed. For example, if I had not submitted my market on close order, how would that have affected the market price? In all likelihood, the published closing price would have been less than \$100. But we cannot directly observe this, so we must infer it based on the observed instantaneous and residual relative (i.e., excess) drift in prices after such an order is placed and filled. The net result of slippage and impact are the same: an implicit cost not included in direct transaction costs. But I think that untangling this conflation is important when dealing with smaller exchanges where smaller orders can drive a huge wedge between your expectancy in some backtest versus reality. In practical-speak, I would think it extremely wise to implement said strategy with close regard to impact. In reality, we cannot change the fact that impact happens, but we can improve our price realizations by never attempting to remove liquidity from an already illiquid market.