Topicality of the monograph. For hundreds of years gold has been playing a unique role in human societies. Since the times of ancient Egypt up to these days there have been very few metals which have played such an important role in mankind history as gold. Appreciation of gold is as old as the written history of mankind. Although the accurate data on when a human for the first time picked up a golden nugget is hard to obtain, golden remnants are found in paleontological caves, which, according to the archaeological findings, appeared 40000 BC (Hur, 2017).
Although nowadays gold has stopped being used as a tool for daily settlements, its role in global economies remains very significant. The evidence that proves the significance of gold in economics is the balance sheet data provided by central banks and other reputable financial institutions, such as International Monetary Fund (Balarie, 2017): the above-mentioned institutions accumulate gold reserves and generate approximately one-fifth of the global demand for gold.
One of the characteristics possessed by gold is the ability to maintain the value of assets through thousands of mankind generations. The same, however, cannot be said about paper money. If, for instance, in 1970, an investor had decided to hold gold (back to then, gold was traded for 35 US dollars) instead of holding 35 US dollars in cash, today this investor could still buy a new qualitative suit, which would not be affordable for 35 US dollars. Gold has preserved its value in the course of time, while the value of paper money has been reduced by inflation. The analysis of the London Bullion Market prognosticate that by the end of 2017, the average gold price will rise by 5.3 percent in comparison to the price captured in 2016, and will approximately reach 1244 US dollars per ounce (i.e. gold price will vary in the interval from 1101 to 1379 US dollars per ounce) (the London Bullion Market, 2017a). It is considered that in 2017, investors in gold will have to go through the variety of hardly predictable events caused by great global political uncertainty, nationalist views of the US President Donald Trump, potentially hard exit negotiations between the UK and the EU, the results of elections in France and Germany and the growing tension between the USA and China.
The main aim of this research is not only to highlight the historical uniqueness of gold, but also to disclose the significance of gold as of an investment asset. This monograph proposes that the choice of gold as of a measure of an investment portfolio diversification must be based on the estimations substantiating which share of an investment portfolio should be composed of gold to make the portfolio properly balanced over different periods of investment. The monograph presents the comprehensive analyses which provide the answers to the questions on when gold becomes a measure enabling to protect the value of particular assets from undesirable changes. In any case, it should not be forgotten that the ability of gold to serve as a “safe heaven” highly depends on specificities of the market.
The first section of the monograph introduces the history of gold as of a monetary - financial instrument. The second section highlights the role of gold as of an alternative investment tool while forming an investment portfolio. The third section presents and compares different scientific research methodologies which disclose the benefits of investment in gold and reveal the links between gold and other asset classes. The methodological analysis has disclosed that the results of different scientific studies in some cases are contradictory due to the differences in the methods applied for the research. The fourth section presents the comparative analysis of the values of the investment in agricultural products and gold. The fifth section of the monograph introduces the methodological requirements applied for the selected research and provides the results of the empirical research. For the first stage of the empirical research, time series model with prognostication was selected. For the second stage of the empirical research, multiple regression model, which allows to prognosticate the dynamics of gold price, was selected. As the research required a full data set, composition of the model was based on the statistical data for the period from August, 1997 to December, 2015 inclusive. Gold price (Gold) was the only dependent variable in this model. The determinants which were included in the initial model presuming that they have an impact on gold price covered silver price (Silver), platinum price (Platinum), palladium price (Palladium), Federal Funds Rate (FFR), Euro Area Inflation Rate (EAIR), money supply (M3), AAR and EUR.
The empirical research allowed to identify the major gold price determinants which include Platinum, M3, Euro Area Inflation Rate (EAIR) and Federal Funds Rate (FFR). It was found that an increase in the value of EAIR by 1 determines an increase in the value of the main determinant (Gold) by 46.18; an increase in the value of Platinum by 1 determines and increase in the value of the main determinant (Gold) by 0.447, and so forth. A very strong correlation, which was captured between gold price and M3 (r = 0.85), can be linked to an increase in money supply in the market, i.e. the growth of M3 determines the growth of gold price. In the initial stage of the research, the correlations between the variables representing all the precious metals and gold price were found to be strong and positive. Nevertheless, verification of the presumptions of the model revealed that platinum price fluctuations affected gold price fluctuations during the period under research. The exact reasons of the links between precious metals and gold prices could be established only by conducting a more comprehensive investigation.
The autoregressive process explains time series observations by consideration of the historical observations. ARIMA’s (1,1,1) MAPE indicator, estimated for the continuous data of 2015, is equal to 3.93 percent, i.e. it does not exceed 4 percent and is lower than the same indicator estimated for ARIMA (0,1,1) with drift, which proposes that ARIMA (1,1,1) can be treated as the model suitable for prognostication of gold price future trends. Nevertheless, it should be noted that ARMA/ARIMA models are suitable only for identification of comparatively insignificant data fluctuations in the short term, while sudden data fluctuations are hard to detect. This feature inevitably reduces the efficiency of the models. For more accurate prognostications, it would be purposeful to include a larger number of variables, to conduct more comprehensive mathematical calculations and to employ a wider variety of multiple regression models, which would allow to identify close correlations between particular determinants and gold price fluctuations.
Gasparėnienė, L.; Sadeckas, A. 2017. Investavimo į auksą raida, strategijos ir priemonės : monografija. - Vilnius : Lietuvos agrarinės ekonomikos institutas. 142 p. (online) ISBN 978-9955-481-64-5.