Overseas

– A case study of applying Least Squares Monte Carlo Method – ABSTRACT Indonesia has many potential undeveloped reserves and currently still depends on petroleum resources to support its economy. However, the economic criteria for investment decision making are still […]

Abstract
Innovation in derivative markets permits active trading, speculating and hedging, linking markets for physical petroleum products with financial markets. These markets continuously value petroleum delivered today and in the future, thereby providing a market price for inventories. Underground petroleum reserves are also an inventory defined by exploration surveys and development drilling. As a result, observable market information can be used to value these reserves.
Besides the discounted cash flow (DCF) approach, real option valuation (ROV) has been applied over the last two decades to value petroleum property. Generally, ROV was chosen to accommodate flexibility management in adapting and revising future decisions in response to changing circumstances. The ROV technique makes efficient use of market information and minimizes reliance on subjective and arbitrary data inputs, as observed in the illustrations in Paddock, Siegel and Smith (1988). The combining of both DCF and ROV approaches results in a better judgment from the internal and external perspective in valuation of petroleum property, especially for undeveloped reserves.
In Indonesian cases, the DCF approach is much more widely applied than ROV in the valuation of petroleum property. On the other hand, Indonesia has many potential undeveloped reserves and currently still depends on petroleum resources to support its economy. The need for the ROV approach in valuing petroleum property is essential for stimulating growth of petroleum resource development in Indonesia.
This paper extends a model by Pickels and Smith (1993) to value petroleum property and comes up with a valuation procedure for Indonesian PSC field.
Adelman and Watkins (2005) conducted a study to estimate the oil and gas reserve price based on the actual reserve transactions in the US, using the period 1982 – 2003. This paper tests for co-integration between the estimated oil reserve price and WTI spot price. The Error Correction Model (ECM) resulting from this test would be used to forecast the reserve price in 2004 and 2005.
The forecast reserve price resulting from ECM can be used as an input parameter for the underlying asset price in the ROV. Other input parameters, such as volatility, pay out rate, risk free rate etc would be adjusted in the Indonesian PSC regime.
This paper concludes that ROV can be applied to the Indonesian PSC regime and accompanying DCF approach to value the petroleum property in Indonesia. ROV judges petroleum property on the basis of objective market data and is less dependent on subjective judgments and arbitrary assumptions provided by an analyst. In that sense, ROV is more likely to reveal a true picture of the worth of exploration potential and the value of undeveloped reserves in Indonesia than any other currently available technique. As such, it has the potential to form a proper basis for the negotiation of contract terms between the contractor and the Government of Indonesia, as a result of which production of the undeveloped reserves in Indonesia could be stimulated

Abstract
The volatility of the world oil market since the OPEC oil price shocks of the 1970’s has resulted in oil export dependent countries like Indonesia facing a considerable degree of macroeconomic risk. Declining oil revenues resulted in large public sector deficits and a worsening balance of payments situation.
Indonesia’s dependence on oil is such that even minor if oil price declines have had a substantial cumulative adverse impact on Indonesia’s macroeconomic performance. The need of the forecasting model in predicting the Indonesian crude price is greatly required to give guidance for government budget planning and also for hedging scheme.
Error correction model developed by Engle-Grager can be used to forecast price change as long as two variables which is non stationery are cointegrated in the same order. One of the advantage of this model is it can accommodate the short and long information in one model. The availability of error correction term (cointegration vector) in the model can correct any deviation happened into equilibrium in the long term.
Developing countries like Indonesia have sought to achieve export revenue stabilization through International Commodity Agreements with importing nations. An alternative approach to stabilizing export revenues is to use market based risk management tools such as futures hedging. Through futures hedging cannot insulate exporters from a long term secular decline in commodity prices; they are effective in managing short term price risk. Using futures market for hedging is a notion that is just now beginning to gain acceptability among developing countries. The New York Mercantile Exchange (NYMEX) estimates that developing countries are increasingly holding a higher percentage of the total open interest in crude oil futures. Since the gulf war, countries like Mexico, Brazil, and Chile are regular users of the oil derivatives market. (Satyanarayan, 1997)
The objective of this paper is to find the error correction model for forecasting changes in Indonesian Crude and WTI spot price, also to assess the risk management prospect for hedging Indonesian crude by developing scenario model of hedging and use it to evaluate the cost and benefits of different hedging strategies.
This paper shows that there is effective risk reducing strategies available to Indonesian policy markets that would have reduced the variance of Indonesian oil revenues over time. While these strategies may necessitate foregoing unexpected gains, they would have prevented unanticipated short term losses. We provide estimates of the cost and benefit of different hedging strategies that may aid in policy formulation.
Cointegration is found among Indonesian Crude and WTI spot price using the two stage Engle-Grager methodology and a series of error correction models are estimated. Using 72 months of “out of sample” data, the null hypothesis of no forecasting ability is rejected at a 2% level of significance for the ECM model found.
This paper also tests for cointegration between the spot and future price of WTI. It is purposed to estimate the closing price of WTI Futures contract so that we can know what position that will be held in the futures contract.
By using these two prediction model, we can make a simulation of cross hedging strategies on futures market. The result of simulation has an effect of increasing the mean, reducing the variance and positively skewing the distribution of gross profit over a naïve strategy.