Based On The Technical Analysis To Provide Liquidity And High-frequency Trading Strategy Research

Technical Analysis (TA) is widely used in financial practice, and most of the existing researches on TA are focused on testing the predictability and profitability of TA. In the recent years, with the development of market microstructure theory, some foreign scholars find technical indicators can help to forecast the changes of liquidity provision on market. Using Chinese stock market high-frequency transaction data, this thesis researches the relations between technical indicators and several liquidity indicators, and, tests whether TA is valuable for timing strategies of liquidity providers, moreover, investigates the feasibility of constructing the high-frequency trading strategies base on liquidity change patterns.Firstly, using Chinese stock market high-frequency transaction data, we investigate the relations between resistance (support) levels and several liquidity indicators, and we find that resistance and support levels coincide with peaks in depth on the limit order book, and the Granger causality tests suggest that this relationship stems from resistance and support levels locating depth already in place on the limit order book. Furthermore, we find limit orders placed before the creation of a new level tend to be positioned slightly ahead of the forthcoming technical level, while limit order placement after the technical levels is relatively diffuse, which suggests that liquidity providers try to step ahead of a large position already in place on the book.Secondly, liquidity providers have to consider a tradeoff between executive risk and adverse selection risk, we estimate transaction probabilities of limit sell orders (limit buy orders), where different price intervals below resistance level (above support level), to weight executive risk. Furthermore, we consider market order as benchmark price, because the executive risk of market order is zero, while its adverse selection risk is highest, then we decide the optimal price for submitting limit orders, base on the principle of the maximizing expected gain relative to market order. Base on this method we design our indicator to help liquidity traders decide the optimal price for submitting limit orders.Thirdly, we investigate the feasibility of constructing the high-frequency trading strategies base on liquidity change patterns. We design our high-frequency trading strategy base on the price fluctuation between resistance level and support level. Using Chinese stock market tick-by-tick data, we investigate the profitability of our high-frequency trading strategy.