Liquidity has long been a great interest to investment professionals as well as academic researchers. The estimation of illiquidity premium for infrequently traded asset classes, such as real estate and private equity, presents a challenge to the industry because of opaque information and sporadic trading activities. We propose to use autocorrelations of return series as a tool to estimate the transaction costs and illiquidity premium of private assets. This tool can also be used to adjust the risk of illiquid asset classes so that private and illiquid assets can be reasonably compared with public and liquid assets. We also show that this metric could have implications for understanding the delay between transaction decision and transaction execution, known to market participants as time-on-market.