IMPACT OF JAKARTA STOCK EXCHANGES REPORTING METHODS CHANGE, UPON LOGISTIC MANAGER DECISION MAKING by Itan Engkoy Indriyani E-mail: industrial_club@yahoo.com ABSTRACT This paper is concerned with the change of Indonesia Government Yield Curve (IGSYC) reporting methods and its impact on the availability of working capital for logistic operations which consists of distribution and transportation of goods and services. Before March 2010, the Jakarta Stock Exchange (JSE) reported the lowest, highest, yield estimates and its transactions. Beginning March 2010, the JSE has been reporting a pair of data every workday. Data are plotted on Yield (percent) versus Tenor/Maturity (year) graph. Before March 2010 investors preferred IGSYC rather than Corporate Bond. After March 2010, the tendency occurs in the way around. However it doesn t alter a lot in the way logistic financial managers select and decide the sources of their working capital. Data of January, February, March, and April of 2010 were used for the analysis. KEYWORDS IGSYC, Corporate Security/CS, Maturity/Tenor, JSE, Bond, Working Capital INTRODUCTION Before the of year of 1970, there were six banks in Indonesia, Industrial Development Bank, Commercial Bank, Export-Import Bank, (Rural) People Bank, Indonesia State Bank, and Working Capital Bank. The Central Bank of Indonesia supervised their operations. They were known by their abbreviations as Bapindo, BDN, EXIM, BRI, BNI, BBD and BI. There were also a small number of private banks. Traditionally banks did their business conservatively, for example they circulated only 25 percent of their assets per year. If they lost, their assets became 50 percent, since they had to cover possible claims resulted from the lost of the third parties. Conversely, their assets increased for example by 30 percent, and the foregoing assets became 130 percent. Each bank had a specific development task as it was stated by its name. It was hoped that all bank operations could be synchronized to achieve national economic goal. Each bank was restricted to it own task. In the 1970 s, government eased the requirements to create banks and lifted the restrictions of their operations. The results could have been predicted, more than 200 new banks came into being and a free for all competition was erupted. The government introduced another financial institution, the Jakarta Stock Exchanges, then it was followed by the Surabaya Stock Exchanges. Recently, the government has a proposal to single-out the exchanges by the name of the Indonesia Stock Exchanges. It has to gain popularity yet among the players/participants in the domestic and international money markets. Global financial crisis which took place in the late 1990 s and its aftermath have negative and positive impacts upon the way people handle their investments. They cannot do business as usual anymore. As in the manufacturing or production sector, manager of logistic operations has to find out the sources of working capital, how to use and to return them with their interests. There are three types of manufacturing or production of goods and services, continuous, job order, and intermittent. Before the year of 1970, two banks could be consulted to obtain working capital, commercial bank (BDN) for service industry, and working capital bank (BBD) for goods industry. Interest rate, pay-back period, the amount of money to be borrowed, and turn over period, were subjects to be brought forward for negotiation. A win-win solution should be sought by borrower and lender. Nowadays, the situation changes a lot. The sources of working capital are not restricted to two banks. The law of equilibrium in supply and demand plays a role in this respect. If the supply is plenty, then more than one interest rates are offered, and vice versa. The manager of logistic operations has to decide the most workable and profitable option available in the money market. Bank is not the only source for the required working capital. The alternative is to find it at the stock exchanges locally, regionally, or globally. A dynamic money market can provide working capital daily, weekly,
monthly, yearly, or at any time in the future. The purpose of this paper is to study the possibility of logistic operations manager to find working capital in the stock exchanges business as an option. AVAILABLE DATA AND INFORMATION Every work-day, Monday, Tuesday, Wednesday, Thursday, and Friday, the JSE issues the followings (among others): 1. Indonesia Government Securities Yield Curve (IGSYC) 2. Benchmark SUN 3. Top Tenth IGS Transactions 4. Top Tenth Corporate Securities (CS) Transactions The first one consists of tenor/maturity in years, the value of the lowest, medium, and highest yield estimates in percent. The second one consists of maturity, serial number, fair price in percent, yield to maturity in year, and coupon in percent. The third one consists of report on transactions of the top tenth IGS and CS. The Benchmark SUN has been reported since February 25, 2010. The changes of the IGS reporting methods occurred on the same date. Before that date, three figures of IGS (lowest, medium, highest yields) were reported, and after that date, two figures (todays and yesterday) were reported. TABLES V and VI show the changes. It is impossible to present all tables in this paper, it will take more than seventy pages for the analysis of data and information alone. EMPIRICAL TERM STRUCTURE MODEL For the moment, the government has not issued a permit on transactions of derivative products at the JSE, because the regulation have to be formulated yet. However, it is worthy to see the possibility of the transactions in the near future, since one or more interest rates are now being offered in the money market. The impressive growth in trading volumes of IGS and CS has been documented. Most of the growth has occurred in over-the counter (otc) products, that depend upon complicated relationships between several rates. The growing popularity of otc and exchange-trade (et) derivatives, requires pricing models establishment. Values of interest rate, option pricing, and valuation formula for stock options can be modeled theoretically. The model treats the forward price of the relevant asset as the underlying security, and it assumed that the terminal asset values have a normal distribution, and it assumed that the terminal asset as the underlying security, and it asssumed that the terminal asset values have a normal distribution, and the volatility is constant, and that interest rates are nonstochastic, then one can value a wide range of contingent claims. This model can only be applied if values are dependent on the value of the underlying asset at just one particular point of time in the future. At the JSE, interest rate claims or yield can be exercised at any time prior to maturiry. The underlying asset is changing through time, and the value of the derivative IGS or CS are dependent upon a series of underlying assets. The option s intrisic value at any point in time of a call option on a discount bond, is related to the concurrent value of the underlying bond, which is reliant on the yield to maturity (ytm) required on a bond with that particular maturity. Bond and bond option values are determined with reference to a different interest rate. The valuation of this instrument should consider the future behaviour of the entire term structure of interest rate. The pricing models are called term structure model (TSM). There are two groups of TSM. The first one is based on an equilibrium argument, by concentrating on a specified process for the spot interest, which can be used with the standard bond pricing formula to imply the entire term structure. The solutions cannot totally eliminate all terms that relate to investor risk references. These parameters are non-traded. No guarantee that models provide a close fit to the initial term structure of interest rates, even after they are calibrated using market prices for a set of interest sensitive securities (top tenth). The second group, the so-called no-arbitrage models, take the initial term structure as given and then concentrate on possible future in interest rates. The process was modeled in the discrete-time framework of a binomial tree, based upon a set of discount bond prices. It was assumed that all spot and forward rates have the same instantneous standard-deviation. The assumed process for the spot rate entertains the possibility of negative rate, and it is only capable of representing parallel shifts in the yield curve. Using a no-arbitrage argument, all future innovations in forward rates can be expressed as a function of the instantneous forward rate volatilities. The prices of all claims are specified by the description of a volatility function. This approach does not require assumptions about investors preferences. Using the initial term structure, it ensures that model based values match those observed in the market. The implementation of the model is limited to simple, short-lived interest rate derivatives.
Using the prices of exchange traded securities are dependent on the entire spectrum of interest rates. A series of delivery options gives the short position some flexibility, which particular bond should be delivered and then it should be executed. The following analysis present a brief review of data and information on IGS and GS of January, February, March, and April 2010 from the JSE. Yield estimates, transaction type, settled date, price, volume, value, yield to maturity, serial number, tenor (maturity), and coupon of the top tenth IGS and CS are documented. If the short position decides to settle his position by delivery, the cash amount received depends upon both the current quoted futures price and which of the eligible bonds is delivered. The invoice amount is determined as: (Quoted Futures Price* Conversion Factor) + Accrued Interest. The short position purchases the bonds for delivery in the cash market at a cost of: Bond Cash Price = Quoted Bond Price + Accrued Interest. The sort position attempts to maximize the difference between the cash inflow and outflows and it chooses to deliver the bond for which the following Short Cash Flow = (Quoted Futures Price * Conversion Factor) Quoted Bond Price, is the greatest. The quality option is valuable because the system used to adjust the invoice prices for bonds with different maturities and coupons is imperfect. If the current bond yields exceed benchmark rate (8 percent), the conversion factor system tends to favour delivery of relatively low coupon, long maturity issues. A general preference in the cash market is for low coupon bonds, for which it is possible to separate the coupon and principal payments. Such features attract a premium, and therefore the securities will not be identified as the cheapest-to-deliver issue. AVAILABLE OPTIONS Logistic operations manager can borrow money from a bank at 3.8 percent per month or 45 percent per year interest rate for the required working capital. Supposed it takes three months to return the principal and the interest, then the payback period should be less than let's say eleven weeks. The manager gets a penalty for late payment. A variety of interest rates is offered by banks, and logistic manager selects the most profitable one. Beside banks, another source to look for is the money market, for example foreign currencies or stocks exchanges market. Every day the rate of exchanges of various currencies are published, or even every hour or at any real time data through the internets globally. When to buy and to sell a particular currency is very critical. It could end up with a lost or a gain. It is a risky business but is worthy to try if no other options in sight. Everyday one can read reports on transactions at the JES. Daily reports on foreign exchanges rates, money and stock transactions, top tenth very active traded bonds, deposit rates, global indices, trading recapitulations, and many more. In this paper, IGS and CS transactions of January, February, March, and April 2010, at the JSE are presented. The most important data and information is the IGS yield curve which is published every workday. Bonds with high coupons and short maturities are liable to be cheapest-to-deliver when yields are less than 8 percent, while the delivery of long term (short term) bonds is favoured when the yield curve has a positive (negative) slope. Some cash market biases may also have an impact on which of the deliverable set is cheapest-to-deliver. From January to April 2010, the IGS yield curves have positive slopes from the maturity of 1.5 years up to 30 years, and then a rather flat afterwards. The adjustment of the invoice prices via the conversion factors is critical in this respect. The IGSYC graph shows that the slope is "positive high" between 1.5 and 4 years maturity, "positive moderate" between 4 and 30 years maturity, and "a little down and up slope between 5 and 10 and 15 years maturity. This situation gives anyone the best pick up to consider. Since it is impossible to present all IGSYC graphs from January to April 2010 in this paper, the best option available to the manager at any time can not be shown. Three graphs show different slopes as the result of reporting methods change and they give an idea on how the logistic operations manager decision making should be. CLOSING NOTES Innovation may be the most important driver of competitiveness. The problem is how to mobilize innovation solutions to redeem the high cost economy. Now is the right time to move forward through creative uses of financial technology in logistics and transportation business. It is up to the logistic operations managers capacity to scale up innovative approach to meet the needs of their working capital. Although ytm and coupon of CS is higher than those of IGS, manager is not automatically switch from IGS to CS transactions, if the demand for working capital is a reccurring process. Logistics and transport cannot move without an adequate and continuing working capital availability.
REFERENCES Jakarta Stocks Exchanges Indices of Agriculture, Mining, Basic Industry and Chemicals, Miscellaneous Industries, Consumption, Property, and Infrastructures of January, February, March and April 2010 J.S.E; Shares Trading/Transaction Indicators of January through April 2010 J.S.E; Foreign Currency Exchanges, Trading/Transaction Recapitulation, Foreign Currency Transactions, Top Tenth Traded Shares, Global Market Indices, Deposits on Rupiah and U.S. Dollar, January-April, 2010 J.S.E. Reports on Indonesia Government Securities Yield Curve (IGSYC), Top Tenth IGS Transactions, Top Tenth Corporate Securities (CS) Transactions; Januari-April 2010 Black F; Scholar, M; The Pricing of Options and Corporate Liabilities, Journal of Political Economy Vol. 81, 1973, 637-659 Elton, Edwin J; Gruber Martin J; Modern Portofolio Theory and Investment Analysis, Fifth Edition, John Wiley & Sons, 2001 Kam, F.Lau; Wolfe, F. Fay; An Application of Object-Oriented Database Support for Index Arbitrage, 1993 Proceedings Decision Science Institute, Volume 2, Washington D.C; November 21-23, 1993, 610-612 Only Figure 1, Tables V and VI are included in the paper; the rests will be shown at the 0oal presentation/poster paper. Flat Curve after 28 years Positive Slope yrs Flat Curve after 25 years Positive Slope yrs
Rather Flat curve after 30 years Negative then Positive Slopes yrs Figure 1. IGSY CURVES TABLE V IGSY REPORTING METHOD IN JANUARY AND FEBRUARY 2010 (%) Rank 1 2 3 (4-5-6-7) 8 9 10 Date January 04 6.954 7.539 8.132 9.533 9.725 9.914 05 6.895 7.465 8.120 9.504 9.695 9.827 06 6.770 7.448 8.103 9.396 9.601 9.774 - - - - (- - - -) - - - February 23 6.956 7.512 8.015 9.202 9.502 9.707 24 7.083 7.664 7.016 9.211 9.505 9.712 25 6.3837 7.2025 7.6691 8.9345 9.1910 9.1902 6.3547 7.2030 7.6737 8.9341 9.4369 9.4347 TABLE VI IGSY REPORTING METHOD IN MARCH AND APRIL 2010 (%) Rank 1 2 3 (4-5-6-7) 8 9 10 Date March 01 6.3634 7.1862 7.6672 10.6578 10.7796 10.8172 6.3617 7.2025 7.6691 10.7587 10.8838 10.8521 March 02 7.1429 7.6456 7.9468 10.6461 10.7727 10.8125 7.1862 7.6672 7.9583 10.7476 10.8280 10.8481 March 03 7.1712 7.6639 7.9630 10.6578 10.7945 10.8505 7.1429 7.6456 7.9468 10.7249 10.8280 10.8481 - - - - (- - - -) - - -
April 28 6.7546 7.2372 7.6164 9.7637 10.0411 10.1972 6.6543 7.0645 7.4398 9.7784 10.0810 10.2526 April 29 6.7768 7.3290 7.6030 9.7161 10.0084 10.1802 6.7546 7.2372 7.6164 9.7424 10.0520 10.2350 April 30 6.7194 72.393 7.5792 9.7100 10.0042 10.1729 6.7768 7.2390 7.6030 9.7161 10.0084 10.1802 Notes: 1. Before February 25, single yield value is reported 2. Begining February 25, a pair of yield value is reported, for example : 6.3547 (initial) and 6.3837 (end) (beginning) (closing)