Asset Portfolio Investment Strategies Based on Econometric Models

Abstract

In order to provide traders with a daily trading strategy for gold and bitcoin, a price forecasting model was first developed. After performing ADF stationarity tests and LM tests on returns, the ARMA (3,7) and ARMA (4,5) models are estimated using THE PERTUR (3,7) and ALM (5) models with perturbation terms GARCH (1,1) and vt following a t-distribution. The second step is to build a risk judgement model that considers the impact of the special bull and bear market quotes, sets the bull score and determines its weight as 0.333. The third step is to build a decision model that introduces a purchase score and builds a planning equation based on the fact that gold is only traded on trading days to obtain the final decision. With this model, a principal of $1,000 could end up with an asset of $164,080. MCM/ICM: Procedures and techniques for a great experience. Proving that the model used is the optimal strategy is done in two parts: an accuracy test and an analysis of investment behavior. The accuracy test introduces the regression evaluation metrics MSE and RMSE and the results show that the portfolio investment model is the most accurate. The analysis of investment behavior demonstrates the failure of one-way investments by comparing complete bitcoin investments or gold investments with the information reviewed.