Based On The Gray Markov Gold Price Adjustment Model Prediction Research

For a long time, gold has caught a global attention for its functions as a measure of value, means of circulation, payment instruments, reserve assets and the world’s monetary. It has become a major project of the theoretical and empirical research that how to effectively predict the price of gold. The changes in the price of gold appear both the uncertainty of the macro trends and the randomness of the microscopic fluctuations, how to predict the price of gold accurately has been an important research task for financial institutions. This article is going to introduce you the historical changes of the gold and the world’s four largest gold markets. In addition, you are going to read the review of the predicting model used in previous studies, such as the ARMA model, ARIMA model, adaptive filtering prediction models, varying coefficient regression model, BP neural network model and so on. Moreover, we will analyze the merits and demerits of predicting methods in terms of the relationship between supply and demand, the inflation rate, the dollar index, the stock market, crude oil market and geopolitical factors; Furthermore, different factors has an influence on the price of gold in different ways, also the effect changes with time and environment; sometimes,these factors may interact each other, resulting in the complexity of the quantitative study of influencing factors. It is difficult to establish a model of predicting the price of gold by analyzing the variation of impact factors, therefore there is a necessity to breakthrough the limitations of impact factors research to establish predicting models through the analysis of historical data of the gold price, taking the impact of some individual factors on the price of gold into account at the same time.The formation of the gold price is a complex economic process of combined action of many factors, thus this process can be regarded as a gray system containing both the known and unknown information, excavating information according to the variation law of time-series data of gold price and analyzing by establishing the Grey predicting model GM (1,1). In the view of large stochastic volatility of time-series data of gold price, the traditional Grey Predicting Model GM (1,1) fits the large random volatility of time-series data less effectively. While MARKOV CHAIN has strong adaptability to the predicting problem of large random volatility, which is precisely the inadequacy of Grey Predicting Model GM (1,1). On the other hand, Markov chain requests time-series data for Markov property and Stationary. When processing the time-series data in the use of Grey Predicting Model GM (1,1) to figure out the development trend of time-series data, the inadequacy of MARKOV CHAIN can be made up. We can effectively improve the prediction accuracy of time-series data regardless of its large random volatility, when we combine the Grey Predicting Model GM (1,1) and MARKOV CHAIN into MARKOV Predicting Model. Also we can further reduce the predictive value of the error ratio when we establish the Grey MARKOV Adjustment Model on the basis of Grey Predicting Model, taking the impact of U.S. CPI index, dollar index, and the international gold reserves of the gold on gold price into consideration, which also can provide reliable basis for the medium-and long-term investment. Gold are widely used in various fields due to its unique monetary property, goods property, financial property and other features, having always got the worlds’ much attention. The price of gold is affected not only by its supply-demand relations, but also rather sensitive to changes in the economic environment and geopolitics; what’s more, the impact of stock market, money market and oil market can also cause violent volatility of gold market. To accurately predict the price of gold is necessary for both the country’s macro-control and common investors thus effectively expanding activities and investment behavior. The deep study of predicting the price of gold can help us better understand the objective laws, make investment decisions, control financial risks, which also has great theoretical significance and practical value.