This paper derives in closed form the optimal dynamic portfolio policy when trading is costly and security returns are predictable by signals with different mean-reversion speeds. The optimal updated portfolio is a linear combination of the existing portfolio, the optimal portfolio absent trading costs, and the optimal portfolio based on future expected returns and transaction costs. Predictors...

Academia has considerable delves into the investment strategy of stock market. Typically, pairs trading is one familiar strategies. To optimize performance strategy, accurate methods for price prediction should be employed and thesupport vector machine (SVM) a typical one. This passage focuses on China market, demonstrating how SVMclassifiers assist strategy. The time period data from 2020-01-0...

This paper presents two methods for increasing comprehensibility in technical trading rules produced by Genetic Programming. For this application domain adding a complexity penalizing factor to the objective fitness function also avoids overfitting the training data. Using pre-computed derived technical indicators, although it biases the search, can express complexity while retaining comprehens...

In this paper, we derive the optimal boundary for pair trading. This boundary defines the points of entry into or exit from the market for a given stock pair. However, if the assumed model contains uncertainty, the resulting boundary could result in large losses. To avoid this, we develop a more robust strategy by accounting for the model uncertainty. To incorporate the model uncertainty, we us...

Neural networks are good at classification, forecasting and recognition. They are also good candidates of financial forecasting tools. Forecasting is often used in the decision making process. Neural network training is an art. Trading based on neural network outputs, or trading strategy is also an art. We will discuss a seven-step neural network forecasting model building approach in this arti...

With the rapid development of economic globalization, various financial products have appeared in domestic and foreign markets. How to adopt ideal trading strategies meet demands market traders for high returns low risks has become focus investors research goal scholars. In order solve this problem, paper establishes a quantitative strategy based on position management model.First, we performed...

In order to quantify the transactions in investment,this paper establishes a non-subjective transaction strategy model 
 based on Apriori algorithm.The technical analysis index is blurred through triangular fuzzy device,designing decision system with class rule library,a product inference machine Mamdani meaning,and central average device.The structural parameters of are estimated using re...

A deterministic trading strategy can be regarded as a signal processing element that uses external information and past prices as inputs and incorporates them into future prices. This paper uses a market maker based method of price formation to study the price dynamics induced by several commonly used financial trading strategies, showing how they amplify noise, induce structure in prices, and ...