Article No. 10 STUDY OF VARIOUS FACTORS AFFECTING RETURN ... Dr. Anurag... · STUDY OF VARIOUS...

AIMA Journal of Management & Research, May 2015, Volume 9 Issue 2/4, ISSN 0974 – 497 Copy right© 2015 AJMR-AIMA

Article No. 10

STUDY OF VARIOUS FACTORS AFFECTING

RETURN IN BOND MARKET – A CASE OF INDIA

Dr. Anurag Agnihotri Professor, College of Vocational Studies, Delhi University

Abstract: This paper will study the impact of different macroeconomic factors on the bond Return such as inflation, USD INR spot rate, crude price and RBI cash balance. The paper will give comparative analysis of impact of various factors on bond Return against. Finally, the paper, being based only upon the statistical analysis, gives conclusion based upon the historical analysis of the available data. Along with the above assumption, our study considers that the inflation data are collected on weekly basis. This research has found some kind of relation between these chosen variables and the bond Return of different maturities. While some of the factors have more correlation with the bond prices, others are quite insignificant in affecting the Return. The results of regression model also depicted that the bonds of different maturities generally move together with any given variable i.e. any variable would affect the bond price of shorter maturity same as that of longer maturity.

Keywords: Bond market, Macro Economics, Cash Balance, Comparative Analysis of bonds

Introduction: The movement of return curve is a complicated issue for considering various factors affecting this movement in different ways which varies with respect to time and market conditions. This paper will study the impact of different macroeconomic factors on the bond Return such as inflation, USD INR spot rate, crude price and RBI cash balance. The paper will give comparative analysis of impact of various factors on bond Return against. Statistical tool like multiple regressions is considered for the analysis of three years of data i.e 2011- 12 to 2013-14. It was observed that interest rate risk is connected to maturity of bonds. However, maturity is not a precise mechanism for measuring this risk because there is a significant difference between nominal maturity and effective maturity of bonds. This is especially true when there are intermediate cash flows involved. Duration is one mechanism that helps us at least reduce the problems of maturity matching. In this section researcher will try to measure duration, its use duration to measure interest rate risk exposure.


Duration is the weighted average time over which the cash flows from an investment are expected, where the weights are the relative present values of the cash flows. It is an alternative to maturity for expressing the time dimension of an investment. When you focus on maturity you ignore the fact that cash benefits are received before the maturity date. The value of bond is based on early payments are discounted less than those received later, Differences in discounted value become more pronounced as time increases, effective maturity may differ from contractual maturity. The duration is a measure of effective maturity. Two bonds with the same duration but different maturities have more in common than two bonds with the same maturities but different durations. One can calculate the duration of bond as:

N

tt

N

tt

N

ttt

N

ttt

PV

tPV

DFCF

tDFCFD

1

1

1

1

.

.

..

Where: CFt = cash flow received on the bond at the end of period t DFt = Discount factor = 1/(1 + R)t R = Yield or current market rate PVt = Present value of cash flows at the end of period t. Finally, the paper, being based only upon the statistical analysis, gives conclusion based upon the historical analysis of the available data. Along with the above assumption, our study considers that the inflation data are collected on weekly basis. This assumption eliminates this time mismatch of data in order to conduct the statistical analysis.


REVIEW OF LITERATURE The Return curve, which plots a set of interest rates of bonds of different maturities, describes the relationship among short-term, medium-term, and long-term rates at a given point in time. It has been the subject of much research in the finance literature, because it is the natural starting point for pricing fixed-income securities and other financial assets. Baker (1996) explain that illiquidity to the costs of executing a transaction in the capital markets. A cost of illiquidity exists because buyers and sellers must pay a price concession to execute orders quickly. Illiquidity is a property only of a non-frictionless market related to trading cost where trading costs like direct transaction cost, bid-ask spread, market impact cost, delay and search cost are attributable to illiquidity. Amihud and Mendelson (1991) Hasbrouck and Schwarts, 1988) expressed the similar views. Groth and Dubofsky (1992), and Bernstein (1987) reaffirmed Schwartz by saying that there is no single, unambiguous, theoretically correct measure of liquidity. Despite the difficulties of precisely defining and measuring market liquidity, most researchers prefer some quantitative liquidity measure. Common liquidity proxies include bid-ask spreads, trading volume, and trading turnover. One common measure of immediacy is the bid-ask spread, either absolutely or relative to some base price. It is the price that market makers impose for liquidity services. Roll, (1970) McCulloch, (1987) explained that the bid-ask price can be a proxy for liquidity since the trader, unsure of the true price of an illiquid bond, is prone to require a high margin for error. Also an illiquid bond is difficult to locate and deliver. In both cases, a high bid-ask price indicates a relatively illiquid bond. However, the traders are likely to use larger spreads in volatile periods, since, in such periods, uncertainty about illiquid bonds price is larger. However, the bid-ask spread is more directly a measure of transactions cost than liquidity and suffers from several shortcomings as a liquidity measure. First, spread alone does not capture the ability of the market mechanism to absorb a dollar volume of trading without disturbing price. Sarig and Warga (1989) exclaimed that a bonds liquidity tends to decrease with its age. Seidner (1992) and Graham (1962) explained that a bonds age and time-to-maturity upon issuance are correlated, the illiquid bonds are more prevalent among long-maturity bonds rather than short-maturity bonds. However, inverse relationship between price risk (refinancing risk) and interest risk further complicates the effect of maturity on liquidity. Bonds with distinctive features may be perceived differently by investors. Darst (1975) explained that the issuing firms usually view convertible securities as future common stock rather than debt, and are generally subordinated to other straight debt of the issuer. Pinches (1973) rated the convertible bonds one class below that of a straight debenture issue of the same company. Graham (1962) found out that the coupon rate tended to vary inversely with the ability of the firm to pay it. A strong company borrows at lower coupon rate, although it can afford to pay more than a weak company. Hence, a low coupon rate will not be a poor feature for a bond investment. Fabozzi, (1995) explained that floating rate bonds are complex debt instruments as the benchmark rate and the reset period make the coupon rate fluctuate and thus the bond prices change. The liquidity of floating-rate bond issue is determined by the investors recognition of the floating-rate and


the interest rate risk. Wongkomol (1997) found that the sharp rise in the overnight inter-bank rate occurs when most large banks have to hold funds in preparation to meet tax payments and reserve requirements; so with less available funds for bond investment, the bond secondary market liquidity becomes low. Therefore, spread between return on promissory note and fixed-income funds has an influence on the Thai bond market; as with narrow spread, fixed-income fund managers re-evaluate their exposure and shorten the duration of their portfolios in light of continuing uncertainty. Mukherjee and Atsuyuki (1995) explain that exchange rates as one of the macroeconomic factors exhibit a positive relationship between itself and the stock price. The exchange rate fluctuation is a critical factor for the foreign investors in the security market. The secondary security market liquidity increases when foreign currency appreciates. However, the fluctuation of exchange rate also increases the exchange risk of the investment when the foreign investors transfer their investment back. The fluctuation of exchange rate may have a minor impact on secondary bond market liquidity particularly when foreign investors do not play an active role in bond trading. Collin-Dufresne, Goldstein, and Martin (2001) explain that there are positive and negative correlations and Interplay of factors affecting bond Returns. The more volatile high Return bonds have a 20-30% impact in Returns due a change in the credit risk quality of the bond. Research Methodology For this paper, I have used the secondary data which was collected from the website of RBI, money control, IMF, World bank, federal bank. The data which was collected from the above resources was tabulated and put to statistical test. For this paper, I have taken macro economic variables such as inflation, spot rate, interest rate, repo, reverse repo rates and crude oil prices. Then I used the multiple regression models. The results obtained were then analyzed. DATA ANALYSIS The data was studied with the help of correlation and regression between different variables. Bond Returns have positive correlation with all factors except USD INR Spot Rate and Reverse Repo Amount. The positive correlation indicates that the bond Return moves in the same direction as that of these factors if they are considered in isolation. The correlation table explains that inflation has higher positive correlation than that of other variables. Economic growth affects long-term interest rates through inflation expectations. Inflation expectations are generally the main driver of long-term interest rates. The increase in interest rate affects the Return in the similar manner. The increase in Return reduces the bond price. Looking at the output across all maturity bonds, it can also be concluded that inflation has higher positive correlation with the Return for low maturity bonds and it declines gradually when the maturity period increases. This happens due to the sentiments driving the bond market. If the bond market believes that


inflation risks are big enough to prompt the RBI to raise interest rates, short-term interest rates will rise faster than long-term interest rates and thereby flatten the Return curve. Crude oil price have also high positive correlation as per the table. Crude price has indirect impact on the bond Return. Increase in crude price increases the cost of production of goods, resulting a high inflation. That ultimately increases the bond Return. USD-INR Exchange rate has negative correlation on bond Return as per the statistical analysis. Empirical analysis suggests that appreciation of dollar against rupee makes the market unattractive for investments. That reduces the cash inflow into the market and hence the reduction of interest rate. That pushed the bond Return in a negative direction. Reverse Repo Balance with RBI shows strong negative correlation with bond Return. Reverse repo amount shows the deposits of the banks with RBI. An increase in this deposit reduces the liquidity in the market. This in turn reduces the interest rate and ultimately the bond Return.

Table 1: Pearson Correlation of Bond return and Inflation

Pearson

Correlation

Bond Return

1 year 2 year 3 year 4 year 5 year 6 year 7 year 8 year 10 year 11 year

Inflation 0.794 0.741 0.602 0.584 0.684 0.647 0.657 0.646 0.591 0.602

Table 2: Pearson Correlation of Bond return with respect to spot rate, crude oil

price, Repo, reverse repo rate

Pearson

Correlation

Bond Return

1

year

2

year

3

year

4

year

5

year

6

year

7

year

8

year

10

year

11 year

USD INR Spot

Rate

-

0.631

-

0.655

-

0.564

-

0.772

-

0.580

-

0.543

-

0.518

-

0.532

-0.589 -0.564

Crude Prices 0.628 0.681 0.687 0.521 0.698 0.712 0.693 0.741 0.684 0.687


Reverse Repo

Amt

-

0.809

-

0.723

-

0.529

-

0.670

-

0.585

-

0.540

-

0.526

-

0.497

-0.538 -0.529

Repo Amount 0.405 0.387 0.325 0.173 0.352 0.297 0.330 0.350 0.294 0.325

Regression models: The coefficient of determination (R-square) has significantly higher value 0.8 - 0.9 (close to 1) for short maturities (Y1 - Y4). The value of R-square falls into an average of 0.6 - 0.7 for longer maturities. This goes to show that the regression equations obtained from the analysis capture good amount of total variance of data for short maturity bonds. The five market variables contribute to the bond Return fluctuation in a significant manner. This would allow capturing future Return movements for short term bonds in precision. At the same time the comparatively low R-square value for long maturity bonds indicates the availability of other significant factors those impact the bond Return.

Table 3 : Statistical result of bond returns

Bond Return

1

year

2

year

3

year

4

year

5

year

6

year

7

year

8

year

10 year 11 year

R square 0.894 0.836 0.623 0.723 0.704 0.648 0.637 0.660 0.627 0.623

Adjusted R

square

0.891 0.831 0.609 0.711 0.695 0.634 0.625 0.648 0.614 0.609

This indicates the existence of negligible autocorrelation among the error terms. Autocorrelation signifies the correlation between the error terms associated with the coefficient of the variables. For a model to be consistent and error free, a low autocorrelation is desired.

Table 4 : Auto correlation and bond return


Auto-

correlation

Bond Return

1 year 2 year 3

year

4

year

5

year

6

year

7

year

8

year

10 year 11 year

Durbin -

Watson

0.372 0.286 0.219 0.236 0.203 0.277 0.225 0.275 0.217 0.219

Variance Inflation Factor (VIF) values across all the maturities are below 10. This signifies that there exists very low correlation among the independent variables. Even if the correlation matrix shows some kind of correlation among the variables,that has no significance when we consider the model as a whole.

Table no 5

Muti

collinearity

Bond Return

1 year 2 year 3 year 4 year 5 year 6 year 7 year 8 year 10 year 11 yr

Inflation 4.536 4.570 4.536 2.988 4.488 3.939 4.536 4.681 4.617 4.598

USD INR Spot

Rate

3.545 3.535 3.545 4.079 3.513 3.593 3.545 3.485 3.437 3.525

Crude Prices 3.609 3.644 3.609 2.579 3.595 3.683 3.609 3.841 3.501 3.515

Reverse Repo

Amt

4.180 4.188 4.180 4.693 4.113 3.424 4.180 4.058 4.249 4.328

Repo Amount 1.440 1.439 1.440 1.206 1.439 1.380 1.440 1.501 1.448 1.405

The equations show that the slope of inflation with bond Return decreases gradually with the bond maturity. That indicates a formation of a convex Return curve (considering only the impact of inflation on Return). The t-test in the analysis proves the significance of all the coefficients in the models. But, the higher slope of inflation shows that it has much


higher impact on the bond Return across all maturities than the other four market variables. The slope declines with the maturity of the bond because inflation has much higher impact on the short-term interest rate rather than that of the long-term ones.

Table: 6 – Regression Equations

Y1 11.58 + 0.182*Inflation + (-.132)*USD_INR_Spot + 0.006*Crude_Price +(-

0.001)*Reverse_Repo_Amt + .000*Repo_Amt

Y2 11.653 + 0.141*Inflation + (-0.131)*USD_INR_Spot + 0.008*Crude_Price +

0.000*Reverse_Repo_Amt + .001*Repo_Amt

Y3 11.58 + 0.182*Inflation + (-0.132)*USD_INR_Spot + 0.006*Crude_Price +

.ooo*Reverse_Repo_Amt + .000*Repo_Amt

Y4 8.843 + 0.117*Inflation + (-.073)*USD_INR_Spot + (-.019)*Crude_Price +

.000*Reverse_Repo_Amt + 5.391E-5*Repo_Amt

Y5 9.445 + 0.089*Inflation + (-.071)*USD_INR_Spot + .009*Crude_Price +

.000*Reverse_Repo_Amt + .000*Repo_Amt

Y6 7.960 + .067*Inflation + (-.037)*USD_INR_Spot + .011*Crude_Price +






Y10 9.140 + 0.044*Inflation + (-0.058)*USD_INR_Spot + 0.012*Crude_Price + (-

0.000)*Reverse_Repo_Amt + .000*Repo_Amt



USD INR exchange rate has high negative slopes with bond Return. But the slope declines with the increase in bond maturity. This goes in sync with the previous explanation that says that the exchange rate impacts the fund inflow to the country in a


negative manner. That reduces the interest rate and hence the bond Return. This impact is more visible in case of short term bonds as per the regression equations. GRAPHS depicting the variation of bonds of different maturities with the dependent variables :


Crude oil price has positive slope with the bond Return. As explained before, this is due to the fact that increase in oil price adds to inflation and hence, it indirectly increases the bond Return. But, the regression equations also show that the slope is marginally lower in case of short-term bonds than that of the long-term ones. Hence, on the basis of statistical analysis, it can be concluded that crude oil price has more impact on the long-term bond Returns than that of the short-term ones. A Comparative Analysis between a short-term and long-term bond Return : Following graphs explain in detail the movement of the Return curve with respect to the independent factors considered in the analysis. Short-term: 1 Year Bond Return


Though repo and reverse-repo balance has theoretical impact on the bond Return, the statistical analysis didn’t find a consistent relationship between these factors. Regression equations contain both positive and negative coefficients for the two factors. This inconsistency shows that the impact of these two market variables on the bond Return might be getting nullified due to the other major factors, which is not getting captured in the regression equations. However, with this analysis it would be difficult to conclude the impact of repo and reverse-repo on the bond Return. The movements of the curves in the graphs show that inflation has more impact on the Return of a short-term bond than that of a long-term one. This is for a simple fact that inflation always has a short-term impact on the bond market (a part of literature review). When inflation increases the bond value decreases for a short period of time. That has an obvious positive impact on the Return as the price and Return of a bond are inversely proportional to each other. Reverse repo amount is the cash balance that RBI has or the money that Banks deposit with RBI. Graphs show that the reverse repo balance has high negative correlation with the bond Return. By comparing the graph of the short-term bond with that of the long-term it can be concluded that the slope of the reverse repo factor with Return doesn’t change with maturity. Conclusion and recommendations The paper has tried to model a relation between the market variables and the bond Returns. This has been done for the bonds of different maturities from 1 year to 10 years and the relation has been captured by macro and micro market variables viz. inflation, exchange rate, crude prices, repo and reverse repo which govern the cash balances with RBI. This research has found some kind of relation between these chosen variables and the bond Return of different maturities. While some of the factors have more correlation with the bond prices, others are quite insignificant in affecting the Return. The results of regression model also depicted that the bonds of different maturities generally move together with any given variable i.e. any variable would affect the bond price of shorter maturity same as that of longer maturity. It confirms also that the changing fundamentals affect bond prices. The empirical results show also that the movement in micro market variables like exchange rate volatility and the fluctuations in liquidity - governed by repo and reverse repo - affect bond pricing. Some of the models in form of regression equations presented in the paper seem to be potentially useful in decision making or forecasting by investors, primary dealers, central bank (RBI) and fiscal authorities. References Amihud Yokov and Haim Mendelson, 1980, Dealership market: market-making

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Article No. 10 STUDY OF VARIOUS FACTORS AFFECTING RETURN ... Dr. Anurag... · STUDY OF VARIOUS...

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