This paper compares a number of strategies for managing foreign exchange exposures. Never hedging, hedging every exposure in our strategies is using a forward exchange contract and hedging on alternative occasions using a forward exchange contract. According to the selective hedging, whether to hedge or not is a very important decision which depends on the future spot exchange rate, which is determined by a number of forecasting techniques. The techniques include the random walk, the large premia model and a volatility model. The paper takes the China RMB verses the USD and JPY into consideration. This research shows the United States exporter those using hedging always perform better than China and Japanese exporters who are not or never hedging. We will use Sharpe’s model and the minimum variance model to compare a variety of strategies. Foreign Exchange transaction exposure exists when firms have financial obligations due to be settled in foreign currencies. For example, a firm may be due to be paid foreign currency (FC) in 3 months for some goods it exported. When the FC is received, they will need to be converted into the firm’s home currency (HC). If during the 3 month period the value of the HC has appreciated against the FC, the firm will receive less HC for each unit of FC. Depending on the magnitude of the HC appreciation, this can be costly for the firm. In this case, the firm can protect itself against this outcome by managing the exposure utilizing any of a large choice of alternatives. The first purpose of this research is to test the hedging effectiveness of FECs. In accordance with existing literature, we will compare the hedged position and fully unhedged position to examine the performance of FECs. For those companies who have hedged, they will realize a good hedge may be one that reduces risk to some degree with nil or minimal impact on return. Those others may prepare to accept a ‘significant’ reduction in expected return in exchange for complete certainty. As a result, any research, like this research, the objective of identification of the better decision, must be made apparently that defines at the outset what is best. In this paper, we used two methods. First, from the traditional finance utility maximization framework the risk/return tradeoff is considered. Drawing on the thread of literature with regard to equity portfolios and diversification and hedging, the Sharpe-ratio model of Howard and D’Antonio (1984, 1987) is used. Secondly, taking a narrower view of hedging, assuming that it is only concerned with risk reduction, the minimum-variance model of Ederington (1979) is used. The second purpose of this paper is to expand on the exposure management analysis above, by introducing selective hedging strategies that are implemented as a result of forecasts of the future spot rate. In the case above the hedger was passive. That is, the decision was between the two polar extremes of hedging every exposure with a FEC or remaining unhedged; there was no middle ground. In contrast, a selective hedger makes a judgment on each exposure. The forecasts will determine whether a particular exposure should be hedged with an FEC or remain unhedged.
A number of streams of literature can be identified in the area of FX exposure management/hedging. Most fundamental is the debate as to whether firms should hedge. This debate has been well covered in the literature and finance texts, such as Smith, Smithson and Wilford (1990). The accepted wisdom is that the firm can add value by hedging due to market imperfections and economies of scale. Another stream of literature uses surveys to investigate whether firms hedge and why, characteristics of firms that hedge, and what methods/instruments are used to hedge. A particular stream of relevance to this paper concerns passive and selective hedging. The finance literature is rich with papers that preach the benefits to investors of international equity and debt investment. Eun and Resnick (1994) extended this work by considering the impact on the investment results when exchange rate risk is hedged with FECs. While the results were mixed for various asset classes, the study did show improvement of the risk-return outcome when the international investments were hedged. Glen and Jorion (1993) concurred, though when they extended the analysis to include the use of Black’s (1990) universal hedge ratio found hedging added little improvement. Eun and Resnick (1997) next introduced the distinction between passive and selective hedging. They discuss the literature concerning the forward rate being an unbiased predictor of the future spot and the subsequent literature identifying the risk premium in the forward rate that makes them in fact biased estimators. Eun and Resnick identify Messe and Rogoff’s (1983) work on the efficiency of the random walk that showed it superior to or at least the equal to any forecasting technique as offering a selective hedge indicator. The implication being that the current spot is the best indicator of the future spot. For an exporter receiving a foreign currency, the random walk would suggest only hedging by locking in the forward rate when it is higher (that is, a more favourable rate for the exporter) than the expected spot. Eaker and Grant (1990) used this strategy and found it produced superior results to always hedging. Up to the work by Eun and Resnick (1997) the evidence was mixed in that most studies found some improvement though the results ranged from large improvements to minimal (and in some cases none) for various portfolios. For example, Glen and Jorion (1993) found that selective strategies offered no improvement over a fully hedged strategy for a portfolio of the world bond or world stock index. Morey and Simpson (2001) have recently extended this work by considering different data and expanding the set of selective hedging strategies. They consider hedging only when the forward premium is historically large and when a relative purchasing power parity model indicates an incorrectly priced bilateral exchange rate. Using ex post efficiency frontiers and return per unit of risk to compare the strategies they find that for a 12 month time period the ‘large premia’ strategy (by the terminology used so far in the current paper this is a selective strategy) gives the best result, superior to the selective strategy based upon the random walk. In addition, they note that in all cases the unhedged strategy performs better than the always hedge strategy.
Hedging is defined here as risk trading carried out in financial markets. Businesses do not want market-wide risk considerations – which they cannot control – to interfere with their economic activities. They are, therefore, willing to trade the risks that arise from their daily conduct of business. Whether in industrial, commercial or financial businesses, the financial assets – loans, bonds, shares, stocks, derivatives – they trade allow them to hedge the risks that accumulate in their balance sheets in the course of business. From the point of view of the corporates and other firms trading in these risks has been also very much at the centre of financial developments. Investors’ holdings of securities – or long positions in shares and stocks, bonds or loans expose them to the sort of risks with which the securities are associated. Part of this risk stems from the unique features of the security, but part is related to more common characteristics shared across securities. Two common macroeconomic risks are those associated with the exchange rate and the interest rate risk in a given economy. These risks can often be traded separately (see below). Pooling securities together in portfolios takes advantages of the idiosyncratic nature of the risks they bear to reduce the overall risk that investors face. For example, including the shares of exporting companies and non-tradable services in an equity portfolio helps to reduce the overall risk of the portfolio to a fall in external demand. From the economy’s point of view, portfolio pooling spreads risk across investors.
A variety of exchange rate risk in the literature differ somewhat. There is broad agreement, however, that the relevant dimensions are: i) certain versus uncertain transactions, ii) long run versus short run and iii) risks concerning the value of cash flows versus risk concerning the valuation of assets. For the purpose of this paper: -Transaction risk refers to the impact of exchange rate changes on the value of committed cash flows (cash flows that lie in the future, but the nominal value of which is known). These are mostly receivables (payables) from export (import) contracts and repatriation of dividends. Usually, the time frame for committed transactions (the time between contracting and payment) is relatively short. However, it can in some cases reach several years, where deliveries are committed a long time in advance (e.g. US dollar-denominated forward sales of planes or building contracts). -Economic risk refers to the impact of exchange rate movements on the present value of uncertain future cash flows. It comprises the impact of exchange rate variation on future revenues and expenses through both variations in price and volume. -Translation risk refers to the impact of exchange rate changes on the valuation of foreign assets (mainly foreign subsidiaries) and liabilities on a multinational company’s consolidated balance sheet. Usually, translation risk is measured in net terms, i.e. net foreign assets minus net foreign liabilities. It is clear that importing firms also face exchange rate risk. Transaction risk arises from foreign-currency denominated imports in the same way as from foreign-currency denominated exports. The economic risk to which an importing firm is subject concerns the variation of its costs induced by exchange rate fluctuations. As in practice most multinational firms are at the same time importers and exporters, their exposure to exchange rate risk is limited to net cash flows in a particular currency. Finally, translation risk arises from the holding of foreign assets irrespective of the net direction of trade flows. A gauge of the actual relevance of exchange rate risk for firms can be found in the literature. Muller and Verschoor (2006) use a sample of 817 multinational firms that are exchange-listed and have their headquarters in the euro area to estimate their exposure to exchange rate variations. They follow a widespread empirical approach by estimating the impact of exchange rate variations on the firm’s stock market returns, controlling for the returns of the entire market. Over the entire period 1988-2002, 22% of firms had significant exposure to the China RMB exchange rate, 14% to the USD and 13% to the JPY. The exposure takes a different sign depending on whether the firm is a net exporter or a net importer. Interestingly, the majority of firms in the sample with an exchange rate exposure are net importers, i.e. euro appreciation increases their share value. The exposure of net exporters is as follows: 3% of firms have exposures to the Chinese RMB, 6.5% to the USD and 3% to the JPY. The exposure increases over the time horizon under consideration. Only 14% of firms in the sample have significant exchange rate exposure as measured over a one-week period, but 67% of the sample firms have exchange rate exposures when measured over a 54-week horizon. The authors suggest that short-term exposures are more effectively hedged than longer-term exposures. Geographically, the authors note a concentration of firms with significant exposures in China, Japan, the United States and Singapore.
In this paper, I choose 100companies in each country, which are China, United States, and Japan. The data we need is found from DataStream. The following data are the variables I’m going to use in the analysis: Foreign Exchange Spot Rate in China, United States and Japan from 2001 to 2009. Foreign Exchange Forward Rate in China, United States and Japan from 2001 to 2009. Return of Stock in 300 sample companies in China, United States and Japan from 2001 to 2009. Variance of Return in this 300 sample companies in China, United States and Japan. The Risk Free Rate in the financial market of China, United States and Japan from 2001 to 2009. The Market Return in the financial market of China, United States and Japan from 2001 to 2009. A variant of the volatility model of McCarthy (2002) is used that recommends hedging when the spot rate displays excessive volatility. Excessive volatility always exists when the short term volatility of mean exchange rates is higher than the mean exchange rates in long term volatility. We gauge the short term volatility by using the moving mean of the previous 6 months exchange rate versus 12 months for the long term. Equation 1 shows the model and the application for the short run calculation:
Two measurements of “better” are employed. First, the minimum variance model of Ederington (1979) is used. This model, equation 2, compares the variance of the unhedged returns to the variances of the various hedged returns. The basis of the measure is that less volatility, as measured by the variance, is preferred to more volatility. From equation 3 it follows that a positive outcome indicates that the hedge has a lower variance and under this decision rule would be preferred. A negative outcome indicates that the hedge increases the volatility of the returns and therefore the firm would have been better off remaining unhedged.
Secondly, the Sharpe-ratio model of Howard and D’Antonio (1984, 1987) is used. In its standard form the Sharpe ratio provides a risk adjusted performance measure as shown in equation 3:
It can be used as in equation 4 to measure the improvement in performance that hedging offers, (if any), over remaining unhedged.
When hedged with a FEC, the real cost of the hedge is an opportunity cost. This is because when the contract is entered, the firm receiving the FC would immediately enter the FEC and hence forgo the opportunity to benefit from a favourable spot rate movement. That is, if the FC appreciates, the firm would have been better off without the hedge. Thus, the true cost of the FEC per HC worth of FC sold forward is represented by equation 5 and from these the mean and variance of each alternative is calculated for input into equation 4.
The above rules we used in this paper is the monthly FX data from 2001 to 2009. Specifically, we considered the bilateral foreign exchange rates are the USD and the Chinese RMB, the Japanese yen (JPY) and the Chinese USD. To calculate the volatility model, we need the Foreign Exchange data for every month date in 12 months in the last 9 years. Because of some limitation of data, the Japanese Yen analysis takes the period December 2001 to December 2009 into account. If the consideration of large period has been given to us and the Subprime crisis in 2007 which seriously impacted on each of these economies in our 3 sample countries and the foreign exchange volatile in a large range, we also need to create two sub-periods. The foreign exchange rates we used in analysis are received from DataStream and it’s the mean exchange rates at the end of day. The RMB / USD rate is in American terms where the Chinese is the unit. The JPY / USD quotes are in Japan terms, thus the USD is the unit. It’s important to distinct each other when the results are being translated. If we make an assumption that the analysis takes a Chinese firm exporting and receiving USD into consideration, the Japan exporter had better anticipate the Japanese Yen depreciated, when the Japanese and Chinese exporters would like to see the value of USD climb up. As what I have mentioned in part I, introduction, comparisons would be made between the hedging strategies and the unhedged option in each sample companies in each country. Hence we could conclude which one is better, hedging or remaining unhedged. Because in any scenario it has equal possibility that the actual future spot rate will turn out to be more or less than the locked in forward rate, intuitively we could expected that the alternatives methods should be shown as a better choice. We could always use a FEC, whether I would happen will rely on the accurate forecast on future foreign exchange spot rate.
I will present the results in two sections: the Sharpe ratio effectiveness and the minimum variance model effectiveness. Table 1 shows the Sharpe ratio effectiveness and table 2 displays the minimum variance model effectiveness. There’re separate sub-tables in 3 bilateral rates each other. As what we discussed above, because of the conventional method in quoting the foreign exchange rate price, a passive answer for the RMB/USD rate gives us an indication when we compare superior outcomes with the unhedged position, while for the other two quotes, a negative number tells us that it’s an inferior outcome if we compare it to the unhedged position. As mentioned in the previous parts, the unhedged value of a companies and these companies always use an FEC hedge, which will be representative of the extreme values, the remaining hedges could form a combination of these two and hence the value will always volatile within this range. A value of 0 is an indication that the hedge have the same outcome with remaining unhedged. Table 1 Minimum Variance model (All by 100) Chinese RMB 6 months: 1 2 3 4 5 6 7 8 9 Full 7.322 2.154 0.205 -0.009 -7.678 0.44 0.366 0.312 0.301 Period1 -4.072 1.378 -6.567 -7.023 -4.012 -5.321 -1.764 -1.685 -1.498 Period2 -6.341 -1.435 3.768 3.805 -6.789 0.012 -0.207 -0.301 -0.207 Chinese RMB 12 months: 1 2 3 4 5 6 7 8 9 Full -39.178 -14.091 -16.031 -15.987 -12.456 -2.943 -0.992 1.907 -1.112 Period1 -20.147 -6.908 -38.709 -8.976 -31.003 -20.965 -20.147 6.666 37.598 Period2 -36.668 -15.413 -10.056 -10.789 -10.123 2.069 1.509 1.509 1.760 USD 6 months: 1 2 3 4 5 6 7 8 9 Full -9.076 -0.701 1.778 3.588 0.668 -3.901 0.106 0.218 0.226 Period1 -35.098 -14.087 -10.668 -5.512 -7.418 4.508 -0.166 7.588 -0.203 Period2 -5.034 -1.995 0.106 0.851 1.287 -8.806 1.246 1.457 3.057 USD 12 months: 1 2 3 4 5 6 7 8 9 Full -68.687 -10.607 5.146 7.098 -0.769 -30.407 1.000 4.509 8.267 Period1 -98.098 -15.041 -9.908 -10.168 -4.009 -41.387 -0.186 5.969 -0.206 Period2 -6.032 -2.318 0.287 0.951 0.107 -8.145 -1.256 0.025 -1.287 Japanese Yen 6 months: 1 2 3 4 5 6 7 8 9 Full -5.988 0.315 0.456 0.379 0.654 -3.082 0.000 0.000 0.001 Period1 -12.097 0.987 0.965 0.957 0.998 -3.590 0.000 0.000 0.146 Period2 -2.033 1.809 1.967 1.478 1.889 -4.067 0.000 0.000 0.147 Japanese Yen 12 months” 1 2 3 4 5 6 7 8 9 Full -40.345 1.235 1.798 1.113 1.356 -25.097 0.000 0.000 0.209 Period1 -55.413 1.376 1.132 1.111 1.985 -25.908 0.000 0.000 0.276 Period2 -20.137 1.965 1.065 1.478 1.259 -24.075 0.000 0.000 0.301 For the Chinese RMB, the results for Minimum Variance model has shown that the data in full period calculation was using FEC formula in both periods of 6 and 12 month, the results can always hedge alternative offers superior outcomes than the unhedged position performed. By calculating the data for period 1, we found that for both period 1 and period 2 are inferior. Be subject to some other alternatives, FEC calculation for the 6 month, and only the 6 combinations proved that it’s a poorer result for the full period. In period 1, all alternatives that use hedging always performed better than remaining unhedged. Period 2 shows a combination of results. For the 12 month FEC, in the full period, hedging choices significantly were better than remaining unhedged. This pattern is the same for period 1. Period 2 shows less effective results for hedging. By summarizing the results, they remain consistent between the 3 month and 12 month. The majority of outcomes (70%) show no matter they chose full hedging or selective hedging with FECs, it can perform better than remaining unhedged. An interesting result is the strong performance of the random walk model. For both the full period and for period 1, the random walk model provides a large group of outcomes with us research, which the ‘best’ hedge is indicated. We have discussed the above that the random walk theory tells us that today’s spot rate have the best impact on forecast of the future spot rate. We could learn from this study, which if the forward rate is a better rate than the current spot rate, we could use an FEC. If the current spot is more appropriate than the forward rate, we could choose to remain the position unhedged. For the USD, in period 1, it has the most positive results (a superior result to remaining unhedged) for both the 6 and 12 month about FECs. For the 6 month FEC within period 1, some of the volatility and combination 2 are much better than those who still remained unhedged. The one who always perform stronger than others would always choose to do the hedging then the random walk. For the full period and period 2, we don’t even spot any improvement from hedging. It is difficult for us to make it stable to conclude that for the Chinese RMB any remaining unhedged choices cannot catch up with the performance of hedging alternatives, but we can realize that the FEC in the 12 month and random walk can provide us with some outstanding outcomes. For the JPY, we cannot totally prove tht hedging could provide better performance. For the 3 month FEC, however, we have figured out a group of positive outcomes and some consistent relationship with the USD in period 1. To summarize the Sharpe measure, for both the USD (always hedge) and the Japanese Yen (random walk), the results do tell us something that hedging could always provide companies with a better performance. Minimum variance model effectiveness Table 2 displays a relationship with the Sharpe ratio; the minimum variance model for the USD shows a strong outcome in the scenario of hedging, whether it is always with an FEC or selectively. For both periods of the 6 and 12 months, hedging could always produce a superior result to those who is still remaining unhedged. Totally, 72% of the companies who used hedging can perform superior to those are remaining unhedged. Table 2 Sharpe Ratio effectiveness (All by 100) Chinese RMB 6 months 1 2 3 4 5 6 7 8 9 Full -0.588 -20.154 0.205 -18.007 -0.678 1.146 3.909 4.156 5.607 Period1 -45.072 -19.378 -16.532 -17.023 -47.012 -15.321 -3.764 -1.685 -1.498 Period2 16.341 -10.435 -23.768 23.805 16.789 6.012 6.207 6.301 6.207 Chinese RMB 12 months 1 2 3 4 5 6 7 8 9 Full -19.076 -50.701 -41.778 -23.588 -50.668 -3.901 -0.238 5.218 -0.226 Period1 -85.098 -84.087 -34.668 -5.512 -70.418 -24.508 -20.166 -17.588 -50.203 Period2 8.039 -21.995 -30.106 -30.851 -31.287 6.797 6.643 6.382 6.664 USD 6 months 1 2 3 4 5 6 7 8 9 Full -29.076 -0.701 -10.778 -3.678 2.668 -13.901 0.106 -1.218 0.226 Period1 37.021 24.087 10.668 15.512 -17.418 0.513 1.166 -7.588 -0.203 Period2 -50.034 -6.995 -10.106 -11.851 1.287 -18.806 1.246 1.457 3.057 USD 12 months 1 2 3 4 5 6 7 8 9 Full -42.684 -12.603 -15.143 -27.098 -0.769 -30.407 1.000 4.509 8.267 Period1 -89.012 -12.045 -15.348 -10.234 -4.009 -41.387 -0.186 5.969 -0.206 Period2 -26.032 -29.318 1.897 1.097 0.107 -8.145 -1.256 0.025 -1.287 Japanese Yen 6 months 1 2 3 4 5 6 7 8 9 Full -55.988 -0.315 0.563 1.232 1.321 -3.082 0.000 0.000 0.001 Period1 -27.097 -0.987 0.567 1.468 0.998 -3.590 0.000 0.000 0.146 Period2 -32.033 -1.809 1.897 20.786 1.889 -4.067 0.000 0.000 0.147 Japanese Yen 12 months 1 2 3 4 5 6 7 8 9 Full -47.346 10.235 1.798 1.113 1.356 -25.097 0.000 0.000 0.209 Period1 -60.466 21.376 1.132 1.111 1.985 -25.908 0.000 0.000 0.276 Period2 -30.186 17.965 1.065 1.478 1.259 -24.075 0.000 0.000 0.301 Between the USD and JPY, the results from table 2 indicate that there’s no doubt that using alternative hedging could always produce a superior outcome to remaining unhedged. In fact, we still can not find any proof that can prove the usage of hedging alternatives would consistently perform better than those are not using hedging, but at the same time, there did exists some better outcomes received from hedging, After all, we cannot draw any conclusion that remaining unhedged is the better choice.
I will make this conclusion from the outcomes of the research. The general conclusion that can be drawn from the results is that over the period considered, always those who use hedging always perform better than those don’t use for an exporter with an Chinese RMB exposure,at the same time those who is remaining unhedged don’t have appearent advantages compared with hedging for both the USD and JPY. The only thing we concerned about is that the Chinese RMB is supportive of those who argue that firms confronting an foreign exchange exposure should always use hedging to act as their shield in predicting exchange rate movements. In accordance with the selective hedging alternatives, the random walk model could always do their work better, it is especially shown in Chinese RMB exposures. I made this conclusions from the findings, we wouldn’t generally introduce USD and the JPY to a firm. In a short-term period, this is probably extremely dangerous, because substantial financial damage would be occurred by the volatility of foreign exchange, but the results suggest that for firms that have exposures repeatedly over a long period of time that hedging offers no benefit. It seems that the method of comparing the outcomes, either Sharpe or minimum variance, does not significantly impact on the findings. In terms of further research, it would be of interest to extend the study to consider other currencies though it does become difficult in this region with fixed or at least pegged exchange rates. A case study or some survey work may also be of interest to discover what firm’s are actually doing, if anything, about this issue. The issue will continue to be an important one, as many of these countries do experience volatile exchange rate movements. At the time of writing the Chinese RMB is reaching a six year high vis a vis the USD.
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