The effects of interest rate volatilities on the demand of Turkish money - Essay Example

?Econometrics Assignment The aim of this study is to examine the effects of interest rate volatilities on the demand of Turkish money. The Turkish money is Lira. The period that has been taken for analysis is 1990 – 2000. Interest rates are predicted on time deposits and treasury bills. Time deposits are term deposits. The volatility of interest rate on treasury bills is positive, but it is statistically not significant while the volatility of interest rate on time and term deposit is negative but has a very high statistical significance. This theory of the effect of interest rate volatility on Turkish money demand can be established only through the Garch model. This theory needs to be established using the E-view software by using the Garch model. Introduction: The main aim of this study is to understand the effect of interest rate volatility on the Turkish money demand. Interest rate volatility is a very important factor in determining a healthy monetary policy for the economy. It is important to identify the factors that create the demand for money. The period of 1990s saw the banking sector in Turkey highly dominated by public banks, which were inefficient in its activities. The Turkish bank sector had a large number of serious discrepancies and deficiencies such as large risks in foreign currency, interest rates and liquidity in the banking sector. During the decided investigation period of 1990-2000s, the increase in GDP was only 2.5 per cent in Turkey. The banking sector in Turkey was deficient of good governance and the economic environment in which the banks existed brought severe economic losses to the bank. “The credits-to-total assets ratio declined from 47 percent to 32.8 percent between 1990 and 2000” (Policy Research Working Paper 2011). There was also a decrease of around 50 – 80% in the credits to deposit ratio in the Turkish banks. The Turkish banking sector was regulated and supervised by the coordination and cooperation of two authorities, the treasury and the central bank of Turkey. “Turkish Bank Ltd is authorized and regulated by the Financial Services Authority” (Turkish Bank n.d.). During this financial period, the Turkish banks financed public deficits due to very high real interest rates, which were charged by the banks. The high volatility in the interest rates also had its consequence on the demand of money in the Turkish economy. It is important to identify the determinant, which increases the demand for money in the economy in order to create and conduct a healthy monetary policy which suits the Turkish economy. The increase in interest rate volatility is accompanied by an effect in demand for money. Investigating the determinant of the demand for money is significant to make and conduct a healthy financial policy, which is directly connected to whole economy. For instance, a factor that raises the demand for cash may unfavorably affect financial performance by rising velocity of money and nominal income circulation. This study aims to look at, particularly the possessions of interest rate volatilities in case of Turkey along with customary factors influencing the demand for money. Because the raise in interest rate volatility is probable to lead structural variations in the formation of behavioral dealings which defines economic sector. It will also really influence the demand for cash. Other than, it must be strained here that the nominal interest rate contains two parts: Expected rate of inflation and an expected real rate of return. While, nominal interest rate volatility can reflect the volatility of each one or both of these parts, it can be said that the influence of interest rate volatility can be happened in two-ways. Even though, there is an agreement between economists that the volatility of actual interest rate enhances money demand, the result of the volatility of price increases is debatable. But, empirical evidences specify that there is a negative connection among the demand for money and volatility of inflation. The explanation: an increase in the volatility of inflation makes all nominal assets containing money riskier to hold because their value in terms of services and goods turns to be unpredictable. The greater risk will cause some depositors to move part of their possessions out of nominal assets into tangible assets for instance product inventories. Consequently, to the extent that volatility of nominal interest rate reveals volatility of nominal interest rates, volatility of inflation could have a harmful result on money demand. While the theoretical viewpoint reveals many-sided effects, issues connecting to empirical studies have exposed conflicting findings. In the study, firstly we described the theoretical methods to the effects of the interest rate volatility on the demand for cash. Secondly, we assembled the empirical studies examining connection among the demand for money and interest rate volatility on the basis of countries. After that, the fourth section contains methodology. Under this section, we utilized parts to explain the variables that are utilized in the empirical model and money demand model that we used in evaluating Turkish money demand and the outcomes of our analysis. In the conclusion part, we discussed and explained our findings about the interest rate volatilities and the Turkish money demand. Literature Review: In the book  ‘ Turkey’ by the OECD economic surveys, the authors are of the view that from the period of 1980s only Turkey saw a less stable macroeconomic performance, and the real GNP was characterized by slowdowns in its economic activity. The inflation also increased in that period and reached tremendous heights. In 1990 the “Nominal GNP was 67.8, the real GNP was 9 and the split ratio was 13.3” (OECD Economic Surveys: Turkey 1991, p. 10). The book named ‘the World Bank in turkey, 1993 – 2004: an IEG country assistance evaluation’ by ‘Basil Kavalsky, World Bank states that Turkey experienced high public investments during the late 1980s. In this period there was a mix of public and private infrastructure, which contributed to inflation as well as high interest rates. The volatility in interest rates was also due to the political changes that were taking place in the Turkish economy, which made the economy very less stable. There were fiscal deficits also, which increased the volatility of interest rates and destabilized the money demand in the economy. The book states that Turkey’s economic problems received stability only from the year 2001 and till then its interest rates were highly volatile and this had a negative impact on the Turkish money demand. In the book ‘The impact of contractual savings institutions on securities market’ by ‘Gregorio Impavido, Alberto R. Musalem and Therry Tressel’ states that the “effect of real interest rate is intuitive, the impact of the  volatility of the real interest rate seems counterintuitive” (Impavido et al. 2003, p. 11). The authors are of the opinion that volatility of the interest rates should be always negatively related to the demand for money. Interest rate volatility promotes the demand for money and increases the demand for long term investments untouched by short term volatility. They are of the opinion that volatility in interest rate has a negative impact on the demand for money. They are of the opinion that increase in the volatility of interest rates leads to structural changes in the financial sector of the country and influences the money demand. They stress that volatility of interest rates increases the demand for money. Volatility of interest rate on time deposit affects the demand for money negatively. Similarly the effect of volatility of the interest rate on treasury bills influences the demand for money in a positive manner. Thus literature states that there is a high effect on the demand for Turkish money with the volatility of interest rates. The study of this topic ‘volatility of interest rates on Turkish money demand’ is tested using the Garch model and the E-view software. The goal in intending E-Views was to build it both prevailing and spontaneous. An extensive diversity of statistical and graphical technique had to be ready accessible without involving users to remember complex command syntax or steer layers and layers of menus. The explanation is an inventive object-oriented user edge. “E-view is a statistical program, which make it possible to perform advanced statistical tests. E-View is both compatible with cross-section, time series and panel data. Even though E-Views can perform relative advanced analyzes, it’s still very easy to use” (Eviews n.d.). Empirical Studies about the Effects of the Interest Rate Volatility: According to Baba, Hendry and Starr (1992) in their study called, Review of Economic Studies 59 (198), under the supposition of the lack of capital market, studying the relationship among real M1 and real GNP, bond / treasury bill give way spread, rate of treasury bill in 1month, rate of inflation, rate of deposit and anticipated risk of holding long term debt, which is estimated as the moving standard variation of the long-term bond yields by means of the co integration manner. (Review of Economic Studies by Baba, Hendry and Starr) “It is important to know that interest rates and volatility exert an influence on option prices. When interest rates are higher; call option prices are higher and put option prices are lower. This effect is not obvious and strains the intuition somewhat. When investors buy call options instead of the underlying, they are effectively buying an indirect leveraged position in the underlying” (The Effect of Interest Rates and Volatility 2011). When interest rates are superior, buying the call in its place of a direct leveraged place in the underlying is better-looking. In the study called Exchange Rates and Monetary Dynamics in Sierra Leone: Evidence from a Modified Money Demand Function by David Bartholomew and Santigie Mohamed Kargbo says that “In recent years, the empirical analysis of the relationship between money demand and its determinants and stability of demand for money have received considerable attention in response to the dynamics of the financial environment, characterized by increased financial innovation and integration, financial sector reforms and shifts in exchange rate policy” (Bathalomew & Kargbo n.d.). Payne (1992), in the Journal of Economics and Finance, examined the relations among real M1 and interest rate volatility of 3 month Treasury bill rate for equally pre- and post periods in the year of 1979 by using two alternative ways in dimension of interest rate volatility. The primary measures are 4 and 8 quarter moving standard divergence (deviation) of real interest rate (?i). The 2nd measure is the moving standard divergence of unexpected interest rate (?i-Ei?i). In evaluation, which are made by 4 quarter moving standard divergence, real interest rate volatility and unexpected interest rate volatility are turn into be negative but statistically unimportant for both periods. The evaluations, which are prepared by eight-quarter moving standard divergence the outcome yield statistically unimportant interest rate volatility for pre-1979 period. On the other part, real interest rate volatility is positive and statistically important at the 5 percent at the same time as unexpected interest rate volatility is statistically unimportant for post -1979 periods. All together, according to this study, the interest rate volatility does not influence the demand for cash in a meaningful method. (Journal of Economics and Finance by Payne.) Halil Fidan, in his study Impact of the Real Effective Exchange Rate (Reer) on Turkish Agricultural Trade sates that “exchange rate is an important economic variable influencing the export, import, and prices of Turkish agricultural products world wide. While stronger Turkish Lira makes Turkish Exports more expensive in other countries, it also reduces the cost of imported products, resulting in lower prices for Turkey” (Fidan 2006, p. 1). According to Saglam (2005), in his study, the relations among real money demand and real Gross Domestic Product are the interest rate volatility on deposits time, exchange rate, the volatility of interest rate on treasury bills, and finally the rate of inflation for Turkey for the duration of 1987:1-2005. Interest rate volatility is a very significant factor in determining a healthy monetary policy for the financial system. It is important to identify the factors that generate the demand for money. The period of 1990s saw the banking sector in Turkey highly dominated by public banks, which were incompetent in its activities (Saglam) The Effects of the Interest Rate Volatility on Turkish Money Demand: Volatility is the measure of fluctuations in a given time period. Volatility involves the task of first measuring and secondly the estimation of the measured. Interest rate volatility affects the economic performance of a country by influencing the monetary policy of demand for money. “Volatility is defined as the standard deviation of the return over time T. (For technical reasons, volatility is usually computed based on log return rather than return.) Volatility must be stated for a specific period of time, such as a day or a year” (Volatility 2004). Interest rate is the rate which is received from time deposit and also the treasury bills. The volatility of interest rate on treasury bills is always and usually positive but the volatility of interest rate on time deposit have been stated as negative in previous researches and are statistically very important. The significance of interest rate volatility for money demand has been a study, which had drawn tremendous attention and needs to be carefully evaluated through empirical studies. The period that has been taken for the purpose of this study is 1990-2000. The Variables Used in the Model: For the purpose of this study, the dependent variable is the money aggregates while the independent variable chosen is the income of the state, the interest rate, the inflation and the exchange rate. It is very difficult to obtain an actual data related to the demand associated with money; therefore the dependent variable chosen is money aggregates. The independent variables chosen here are also the scale variables. The traditional monetary aggregates are defined as M0, M1, and M2 etc. The income of the state comprises of the Gross domestic product (GDP), gross national product (GNP) and the national income. The Garch model is the proposed model, which is used to test the volatility of interest rate on the Turkish money demand. The effect of interest rate volatility on the Turkish money demand can be studied only with the study of the two other components involved in the interest rate which are the expected real rate of return and the expected rate of inflation in the country. Economists have stated both the views that volatility in the interest rates affects the money demand as well as does not affect the money demand. “Volatility is a measure of the fluctuations over a period of time” (Veredas p. 6). GARCH model implies the Generalized Autoregressive Conditional Heteroscedastic model. According to the Garch model, it is necessary to understand that “innovations are stationery, zero mean, unrelated and the conditional volatility is a random variable defined in terms of present and past innovations and conditional volatilities” (Conditional Heteroscedasticity and Garch Models n.d.). The volatility forecasting technique used in this appear is Garch (1,1) method and the Garch (1,1) + implied volatility method. For the volatility forecast to be made, it is important to calculate the mean and variance specifications. “Kroner acknowledge that GARCH forecasts seem to provide the best forecasts of Volatility (based on evidence from literature) but also that implied volatility based forecasts can still be used to explain some of the forecasting error from the GARCH models” (Laws & Gidman n.d., p. 4). The n step forecast for Grach process is ht+n = ??[ 1 + ( ??+ ??) +…+ ( ??+ ??)n-2 ] + ??+ ???2t +??ht While the one step ahead volatility forecast for the Garch (1,1) + implied volatility model is given using the following formula: ht = ??+ ???2t-1 + ??ht-1 + ??IMPt-1 The Garch (1,1) process is given by the following formula : ht = ??+ ???2t-1 + ??ht-1 In the garch model any number of lags on the squared error term and variance can be included. The garch model leverage effect with asset prices whereby a positive shock has very less effect on the conditional variance as compared to negative shock. Garch model is the most appropriate model used for measuring the volatility of interest rates and its effect on the money demand in a market. The money market consists of narrow and broad money. Narrow money are those assets which are readily and easily available in everyday transactions, while broad money consist of a broad range of assets which provide portfolio chance to the asset holders. In order to get the real money measurement from the nominal value of money, the method to be followed is to divide the nominal balances by an appropriate price index. The independent variables are the GDP, GNP and the inflation in the country for determining the effect of interest rate volatility on money demand in turkey. The chart below states the inflation and the GDP. 1990 – 2000 Inflation chart, GDP Year inflation GDP 1990 60.36% 9.25 1991 65.69% 0.926 1992 70.62% 5.98 1993 65.64% 8.042 1994 103.17% -5.456 1995 92.44% 7.19 1996 80.37% 7.007 1997 84.46% 7.528 1998 86.66% 3.092 1999 64.76% -3.365 2000 56.43% 6.774 This data is according to the world data report. The chart below states the volatility or the fluctuations in the interest rates in the Turkish economy. (Turkey Interest Rate 2011, para. 1). Garch models are used for filtering, forecasting and the estimation of the volatility in interest rates. “Garch filters perform under controlled conditions and then daily currency and equity index returns is evaluated to understand how the model performs in a risk management application” (Fleming & Kirby 2003, p. 1). In order to understand the Garch model it is necessary to first develop a linear model and to study the conditional variance and the time structure. Garch model has been a revision to the arch model. The advantage of the Garch model over the arch model is that in the Garch model it is possible to capture the serial correlation with just a few parameters. The Garch model develops a very statistically significant relationship between the volatility of interest rate and the money demand in the Turkish economy. When the GDP in a country increases, then income of individuals in the country increases. This, in turn, increases the demand for money in the economy. When there is volatility of interest rate on treasury bills, there is an individual demand more money. Thus, there is a relationship between the volatility of interest rates and the money demand in the Turkish economy. Heteroscedasticity test using the data provided above Heteroscedasticity is tested by using the Spearman rank correlation test H0: Homoscedasticity Vs H1: restricted Heteroscedasticity Nonparametric Correlations Correlations GDP real interest rate Spearman's rho GDP Correlation Coefficient 1.000 .509 Sig. (2-tailed) . .110 N 11 11 real interest rate Correlation Coefficient .509 1.000 Sig. (2-tailed) .110 . N 11 11 Conclusion: Here the Spearman rank correlation coefficient r =0.509 which indicates a positive correlation between GDP and real interest rate. It suggests that there is relationship between GDP and real interest rate. A high correlation coefficient suggests the presence of heteroscedasticity. This indicates that there is a positive correlation of interest rate volatility on the Turkish money demand. Methodology: The economic markets are receptive to the time dependent data flows. For that cause, financial data must be parameterized with Autoregressive Conditional Heteroskedastic (ARCH) models. The general method for a Garch model includes three steps. The opening is to approximation a best-fitting autoregressive model; secondly, calculate autocorrelations of the mistake term and finally, test for importance. Garch models are utilized by economic professionals in various fields containing investing, trading, dealing and hedging. Two other broadly -used approaches to predicting and estimating financial volatility are the common historical volatility method and the exponentially weighted affecting average volatility method. ARCH method models a time- varying restrictive variance as a linear purpose of past squared residuals and of its past charges. ARCH models are established by Engle and generalized as by Bollerslev. Engle constructs ARCH model to clear the time-varying variance. (Product Documentation: Time Series Modeling 1984). In the above the equation, it is the time-varying conditional variance. In the model, the amount of i >0 and must be 1. Bollerslev constructs Generalized Garch for approximating the model with negative difference. The Garch model captures the conditional variance and linear variance of the past. Garch models create well-fit explanations for both out-of-sample and in-sample volatility parameter estimates. This paper tests The Effects of the Interest Rate Volatility on Turkish Money Demand by GARCH model with choice symmetric normality assumptions. In the methodology, we justify the variables that are utilized in money demand function one by one. Then we make the empirical model and observe the connection among real monetary total M2Y as real gross domestic product (GDP), and money demand volatility of interest rate on reserves bills, instability of interest rate on time deposit, exchange rate and inflation rate. Variables Used in Money Demand Model: Monetary aggregates are utilized as the dependent variable in empirical studies, whereas scale variable which is in use as income (Gross National Product, Gross Domestic Product, permanent income or Net National Product) and opportunity price of holding money, which could be exchange rate or inflation rate, interest rate, are all utilized as independent variables. Dependent Variable: Monetary Aggregates: Since there is no data connected to the quantity of demand for money, monetary aggregates data or money supply are used in empirical research so as to symbolize the demand for money by affecting from the statement that the money market is in equilibrium. On the other hand, there is no agreement among economists about the definition of money supply or monetary aggregates. Some researchers described the money as the time deposits collection of demand and deposits, while the traditional view describes the money as the aggregate of currency in circulation and demand deposits. Scale Variable: In assessment of the demand for funds, the scale variable is utilized as a measure of dealings, which are connected to economic actions. Scale variable is generally symbolized by variables which states, wealth or expenditure income concept. The stage of income is frequently used as a proxy for the quantity of dealings in a financial system. Particularly, it has played a significant role in empirical tests of dealings-based theories of the demand for money. Since net national product series, gross national product series and gross domestic product series move rather closely together over time, no significant variation in outcomes is obtained by utilizing one or the other, in computing income variable. Application of GARCH the Model: The model ARCH is firstly introduced by Engle in the year of 1982 and subsequently this model is generalized as GARCH in the year if 1986 by Bollerslev. A GARCH model helps to create extremely well-fit explanations for both in-sample and out-of-sample parameter estimations of the volatility. This paper is mainly tests the Effects of the Interest Rate Volatility on Turkish Money Demand by way of using the GARCH model. The period that has been taken for the purpose of this study is 1990-2000. The effect of interest rate volatility on the Turkish money demand can be studied only with the study of the two other components concerned in the interest rate which are the expected real rate of return and the expected rate of inflation in the country. A category of ARCH models is deemed to model the inflation risk. GARCH (1, 1) was the most suitable measurement for inflation risk. Once the inflation risk is integrated, then both inflation risk and anticipated inflation increase the interest rates. On the other hand, the interest rate enlarges less than inflation. This particular method has a wide variety of capital markets applications. “The model is based on the assumption that forecasts of variance changing in time depend on the lagged variance of capital assets. An unexpected increase or fall in the returns of an asset at time t will generate an increase in the variability expected in the period to come” (Gazda & Vyrost 2003, p. 18). The definition of GARCH model is follows: “?t2= a + ?qb i.e. t2–i + ?p c j? 2t–j + wt” (Gazda & Vyrost 2003, p. 18). From this ‘p’ denotes the degree of GARCH, ‘q’ denotes the degree of procedure of ARCH, ‘wt’ denotes random element with the properties of white noise. While the equation conveys the dependence of the variability of returns in the present period on information from earlier periods, indicate this variability as conditional. The garch model tells us about the implications of the interest rate volatility: Interest rate is one of the most significant and basic parameters in monetary market. It plays a primary position in risk management, asset pricing and macro-economy study. Volatility is viewed as one of the most significant ideas in the field of Finance. It is considered as the variance of returns or standard deviation. It is frequently used to calculate of total risk on fiscal assets. GARCH model is the one of the method that used develop with the aim of determining and estimating level of volatility. “By applying a GARCH model, it is possible to interpret the current fitted variance as a weighted function of a long term average value, information about volatility during the previous period and the fitted variance from the model during the previous period” (Gutierrez 2008, 46). This particular model is better and more commonly used since this type of models are more economical and keep away from over fitting. So; the model is less probable to infringe non-negativity constraints. Conclusion: This project studied, particularly the consequences of interest rate volatilities of Turkish Money Demand for the period of 1990-2000. For the completion of the study, quarterly statistics of all variables were mainly used. In calculating interest rate volatility Kenen and Rodrik proposed one of the method i.e., moving-sample standard deviation method that is also used in this study. According to the outcome, the coefficient of the real GDP is positive and statistically important as expected. There is statistically irrelevant relationship among money demand and the volatility of the interest rate on treasury bills though the symbol of the coefficient is positive as hypothetically expected. The Garch model builds up a very statistically significant relationship among the volatility of interest rate and the money demand in the Turkish financial system. When the GDP in a state increases then income of persons in the country also increases. This in turn increases the demand for money in the financial system. Peoples in Turkish hold real domestic assets rather than money in periods of inflationary. On the other face, the negative and significance exchange rate coefficient specifies that when exchange rate enlarges, the expected return from holding overseas money enlarges, too. So Turkish people substitute overseas currency in place of domestic currency and this roots the demand for money to decrease. Reference List Bathalomew, D. & Kargbo, SM. n.d. Exchange Rates and Monetary Dynamics in Sierra Leone: Evidence from a Modified Money Demand Function. [Online] Available at Accessed on 20, December 2011. Conditional Heteroscedasticity and Garch Models. n.d. [Online] Available at Accessed on 20, December 2011. Eviews. n.d. Aarhus School of Business. [Online] Available at Accessed on 20, December 2011. Fleming, J. & Kirby, C. 2003. A Closer Look at the Relation between GARCH and Stochastic Autoregressive Volatility. Journal of Financial Econometrics. Oxford University Press. Vol. 1. [Online] Available at Accessed on 20, December 2011. Fidan, H. 2006. 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