Liquidity flows, drawdowns and trading networks in order driven markets: An application to Borsa Istanbul

We empirically analyze the agent based relationship between liquidity flow and downside price formation based on the individual trading network topologies of 20 equities in Borsa Istanbul between 2009/01-2013/12. We apply PageRank Algorithm to extract daily centrality degree in liquidity demand of domestic financial institutions classified as informed traders and use intraday maximum drawdown to capture intraday liquidity shocks. We find evidence that 1) Maximum cumulative loss for a given day, deepens with the increasing liquidity demand of informed traders. 2) The uncertainty in the centrality degree of informed trading is overtime positively related with the uncertainty regarding the intraday maximum drawdown. 3) Time Patterns are significant: Drawdown depth is highest on Thursdays and lowest on Mondays. Highest (lowest) drawdowns on May (March) indicate the existence of Sell-in-May effect and earnings announcement effect, respectively.