among researchers capture liquidity effectively and, if they do, which of the proxies measures liquidity best. We carry out a comprehensive analysis using tick data that covers 1,183 stocks from 21 emerging markets. The use of tick data allows us to compare various low-frequency liquidity proxies with various high-frequency transaction cost and price impact measures. We have several important findings. We find rich dispersion in transaction costs and price impacts across emerging markets. We also find that most of the spread proxies, including Roll’s spread, LOT, and Zeros, perform relatively well in emerging markets. But when it comes to price impact proxies, the Amihud measure is clearly the most effective. Finally, it is important to recognize that there is no one universal proxy that captures liquidity best across different emerging markets. One that works best in most of the markets does not necessarily perform best in a specific market. Hence, it is important to know which proxy is the best liquidity proxy in a specific emerging market. Finally, it appears that there are some countries where none of the proxies can be reliably employed.