The objective of this study is, first, to re-examine the correlation in real terms, i.e., the correlation between real currency returns and real relative equity returns, which is new in the literature. The sample includes a cross-section of 20 major OECD countries with flex- ible exchange rate regimes. Time span of data covers 1991/1 to 2014/12. Using standard panel estimators, this study generally finds similar empirical results in line with the pre- vious studies even in real terms. However, a novel aspect of my new findings is that the generally observed negative correlation tends to disappear or even turn into a positive one for an extended period of time, especially during times of economic uncertainty. To rigor- ously test this hypothesis, i.e., the structural correlations are conditional on the degree of economic uncertainty, I include an interaction of (real) relative equity returns and proxy for such aggregate economic uncertainty as an additional regressor into an otherwise standard regression equation in previous studies. Through several robustness checks, the null hypoth- esis could not be rejected. In sum, this study empirically shows that the correlation between real relative equity and real FX returns is conditional on the degree of economic uncertainty. To the best knowledge of the author, no previous theories could account for this newly observed evidence. The second objective of this study is, therefore, to provide one potential explanation for this newly observed evidence. To that end, the suggested model explicitly utilizes the concept of liquidity volatility, combined with the long run risk framework devel- oped by Bansal and Shaliastovich (2013). Although the term liquidity is an elusive concept, the current study primarily focuses on one particular definition of liquidity, namely ‘equity market liquidity’, which is the ease of trading equities in stock markets. Accordingly, the liquidity volatility in the current model refers to the degree to which such trading costs in stock markets fluctuate within a given period of time. Given these concepts, the model intuition goes as follows.
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As the first-pass validation of implication (i), figure 1.1 plots the cross-sectional relation of bank capital ratio (the inverse of bank leverage, in percent) with average forward discounts (interest rate differentials) and currency returns vis-a-vis the dollar for the ten most liquid currencies. A positive slope stands out in both graphs: Countries with lower bank capital ratio (higher leverage) tend to have lower interest rates and currency returns. The typical carry trade funding country (Japan) has substantially lower capital ratio than the typical investment country (Australia). In the empirical section, we show the same relationship for 22 advanced economies through panel regressions. The relationship is robust after controlling for each country’s inflation and GDP. Following standard as- set pricing practice, we sort currencies into portfolios based on bank leverage, and find that currency returns monotonically increase from high leverage portfolios to low leverage portfolios. The spread between the lowest and highest leverage portfolios, the “Lev-factor,” is 2.0 percent per annum. Het- erogeneous exposures to the “Lev-factor” accounts for the different expected returns of currency portfolios and the “Lev-factor” has a significantly positive risk price, which is consistent with our model implication.
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25 The Table 2.2 results provide strong evidence in favour of short-term momentum rather than reversal. Out of the sixteen look-back and holding period strategies we consider, not a single strategy provides negative mean returns. Therefore, we can reject the hypothesis of reversal in favour of momentum in weekly currency returns. The momentum returns range from 1.84% to 8.60% on an annualized basis and the returns to 15 of the 16 strategies are statistically significant. The one-week look back strategies generate the lowest returns, while the three- and four-week look-back strategies have the highest returns. Increasing the look-back period positively affects the short horizon momentum returns. For example, the annualized excess return for the MOM(1,1) strategy 7 is 1.84% with a Sharpe ratio of 0.21 and these returns increase to 5.62% and 8.13% for the 2-week (MOM(2,1)) and 3-week (MOM(3,1)) formation period momentum strategies respectively. Interestingly, our results in Table 2.2 differ from the findings of Mettler, Thöny, and Schmidt (2010), who conclude that trend strategies produce ambiguous and negative returns at weekly trading horizons. This contrast in findings could be due to the difference in time period and number of currencies under consideration as we use 63 currencies compared to the 12 currencies they use.
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The present study uses the structural equation model (SEM) to analyze the correlations between various economic indices pertaining to latent variables, such as the New Taiwan Dollar (NTD) value, the United States Dollar (USD) value, and USD index. In addition, a risk factor of volatility of currency returns is considered to develop a risk-controllable fuzzy inference system. The rational and linguistic knowledge-based fuzzy rules are established based on the SEM model and then optimized using the genetic algorithm. The empirical results reveal that the fuzzy logic trading system using the SEM indeed outperforms the buy-and-hold strategy. Moreover, when considering the risk factor of currency volatility, the performance appears significantly better. Remarkably, the trading strategy is apparently affected when the USD value or the volatility of currency returns shifts into either a higher or lower state. Keywords: Knowledge-based Systems, Fuzzy Sets, Structural Equation Model (SEM), Genetic
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distribution of returns across currencies. Hence, this factor naturally captures market dispersion of currency returns, which is not considered by other factors. In bad times, not only can volatility be high, returns can also be more dispersed than in normal periods, for example if there is a ‘flight to safety’ (or ‘flight from risk’) in some currencies. Therefore, cross-sectional volatility should also af- fect investors’ future investment opportunity sets, and hence it should also be priced in asset returns. Garcia, Mantilla-Garcia, and Martellini (2014) show that the cross-sectional variance is a consistent and asymptotic efficient estima- tor for aggregate idiosyncratic volatility, and that it is countercyclical. A few studies (Garcia, Mantilla-Garcia, and Martellini 2014, Angelidis, Sakkas, and Tessaromatis 2015, Maio 2015) suggest that cross-sectional volatility is a strong predictor for stock returns both at market and portfolio levels. In this paper, we find that cross-sectional volatility is also priced in currency excess returns and remains significant in explaining carry trade returns even after controlling for conventional volatility. Moreover, cross-sectional volatility outperforms other volatility factors in explaining the cross-section of individual currency returns. Our findings suggest that these alternative volatility factors contain incremen- tal explanatory power for currency returns, and they are not fully subsumed by conventional measures of volatility risks.
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This essay builds on the growing literature that searches for a risk-based explanation to currency premia. In one strand of this literature, Lustig, Roussanov, and Verdelhan (2011) and Menkhoff, Sarno, Schmeling, and Schrimpf (2012) have both found a global risk factor in currency excess returns. However, while these global risk factors provide valuable information on the properties of currency returns, the question as to what fundamental economic forces drive the factors and, hence, currency risk premia, remains unanswered. In a second strand of literature, a ‘crash’ premium has been proposed to explain currency excess returns. This ‘crash’ or disaster risk has been shown to explain, at least in part, the excess return to the carry trade. 3 While this is a compelling theory, it does not directly connect crash risk (or the probability of a crash) to underlying economic fundamentals that may generate the crash. The argument is as follows: (i) High interest rate currencies require a high expected return. (ii) The higher return is compensation for the risk of a large and sudden drawdown. (iii) High interest rate currencies experience this ‘crash’ and thus require a higher return because they are the riskiest. The question as to why high yielding currencies are the riskiest is not resolved. Both strands of literature, therefore, leave us tantalizingly close to a more complete understanding of currency premia. This essay tackles exactly this issue by shedding empirical light on the macroeconomic forces driving currency premia.
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Some special cases of our setup deliver additional restrictions that tie down the cor- relation. First, there is the case in which expected excess returns on international equity investments are zero (i.e. FX returns and equity returns have a perfect negative correlation). This can of course be achieved by assuming that investors are risk neutral. The same result is delivered by the theoretical model of Hau and Rey (2006), although the underlying mech- anism is di↵erent. Hau and Rey (2006) argue that, if investors cannot perfectly hedge their FX exposure, when a foreign equity market outperforms domestic equities one will observe a depreciation of the foreign currency due to portfolio rebalancing: when foreign equities outperform, the FX exposure of domestic investors increases, so that they sell some of the foreign equity to reduce FX risk. These sales of foreign currency-denominated assets have a negative impact on the exchange rate—defined in this paper as the domestic price of the foreign currency—and this depreciation in the exchange rate completely o↵sets the di↵er- ence in equity returns across markets. This is the Uncovered Equity Parity (UEP) condition, which implies a correlation of minus unity between expected equity return di↵erentials and currency returns, and a zero expected excess return to international equity investment.
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4 relationship that reflects the determination of the real exchange rate in the long-run. In this paper, we show that the theoretical model that we derive is empirically well supported by using the dollar-pound rate indicating that asset prices and returns can play a substantive role in the determination of the real exchange rate in the long run. Although Dellas and Tavlas (2013) have recently shown a theoretical and empirical linkage between exchange rate regimes this differs from our approach which is to show an explicit link between asset prices and the real exchange rate.
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An article written by Brian Griffiths presents an interesting argument in defense of Brexit. The first claim is a rather simple one; the EU is not working (Griffiths, 2016). The euro was originally a good idea when it was first implemented between the original six members, who economists claimed were in an “optimal currency area”; intuitively this makes sense, as free movement was expected to cross these countries borders. However, the euro is now dispersed to 19 countries with vastly different economies (Griffiths, 2016). Also, the euro was set up as a monetary union but does not have a banking union, a political union, or a fiscal union. Without the ability to devalue or revalue currencies, EU countries must rely on adjusting domestic fiscal policy and change the level of wages (Griffiths. 2016). Another aspect of the EU that is not working is the issue with open-borders. As the borders have become open amongst member nations, terrorist attacks have increased, and EU nations have begun to make attempts at better controlling their borders. However, this goes against the purpose of the EU, as free movement is one of the pillars of the union (Griffiths, 2016). To Griffiths, these flaws in the EU are the reason behind the “ever closer union” movement. By re-branding themselves, the EU has hopes of having more control over taxes, immigration quotas, and even proposing a European army (Griffiths, 2016).
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In deciding how much of a particular international currency to hold as a store of value and whether to use that currency as an anchor currency, central banks and their governments care about three things. First, how costly is it to transact with the currency and what opportunities are there for investing it. Second, is it economically sensible to use the currency? That is, what is the expected return to holding the currency and how does holding it affect the riskiness of the central bank’s portfolio? Will it maintain a stable value and does it satisfy optimal currency area criteria? Third, are there political considerations that make the currency more or less attractive?
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The results are particularly striking when we consider the case of real returns. As described before, the actuarial projections suggest that the EOBI will be unsustainable unless the fund assets can earn a real return of at least 7 percent each year. Our findings show that a portfolio which includes international assets is much more likely to at least come close to reaching this goal. For example, with a risk aversion coefficient of five, the unconstrained portfolio that includes international assets enjoys a 7.1 percent return with a standard deviation of 7.4 percent. The geometric mean return that can be earned over a long duration after accounting for the volatility is 6.8 percent, which is close to what is needed for sustainability (we must also include the caveat that we have not deducted the administrative costs, which would reduce all of the returns in the tables accordingly). However, when we exclude international assets from the portfolio, the possible returns fall by more than half to 3.4 percent, while the standard deviation increases to 8.3 percent. This implies a geometric return of 3.1 percent in real terms, which is much lower than the alternative of 6.8 percent.
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The failure of Japan to establish the AMF will weaken Japan’s position in East Asia, perhaps decisively. The establishment of the Asian Monetary Fund could have supported Tokyo’s claims for leadership in the region. It even represented, as Walden Bello called it, a ‘golden opportunity’ for Japan (see Bello 1998, p. 18). The inability of the Japanese political elites to use this opportunity may have been caused by the country’s position somewhere between the West and the East. But whereas this might have been an advantage in the past, today Japan seems to be more isolated than ever. The big winner seems to be China, which helped to calm the situation in particular by not devaluing its own currency when all other countries in the region did exactly that (cf. Dieter/Higgott 1998). 8
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Foreign exchange exposure is defined as the assessment of potential of a firm’s profitability, net cash flow, and market value to change due to unpredictable changes of foreign exchange rates, which can be financially unfavorable to the global firm. This paper discusses the three various types of major foreign exchange exposure which are, translation, transaction, and economic; the risks associated with each exposure, and how to minimize specific currency risks.
Proposals have been made for a common currency for East Asia, but the countries preparing to participate need to be in a state of economic convergence. We show that at least six countries of East Asia already satisfy this condition. There also needs to be a mechanism by which the new currency relates to other reserve currencies. We demonstrate that a numéraire could be defined solely from the actual worldwide consumption of food and energy per capita, linked to fiat currencies via world market prices. We show that real resource prices are stable in real terms, and likely to remain so. Furthermore, the link from energy prices to food commodity prices is permanent, arising from energy inputs in agricul- ture, food processing and distribution. Calibration of currency value using a yardstick such as our SI numéraire offers an unbiased measure of the consistently stable cost of subsistence in the face of volatile currency exchange rates. This has the advantage that the participating countries need only agree to currency governance based on a common standards institution, a much less onerous form of agreement than would be required in the creation of a common central bank.
The transmission mechanism of the effects of home expansionary monetary policy on welfare can be addressed in two dimensions, specifically, consumption and output. Regarding consumption, home consumption is stimulated when the increase in home money supply results in depreciation, and welfare increases. Conversely, home consumption decreases when the expansion of foreign money supply results in appreciation, and welfare decreases. In addition, with diversified currency holdings, the extent of welfare changes increases. Regarding output, the expansion of home money supply increases home consumption and stimulates an increase in home output, although the magnitude is reduced because of the characteristics of short-run price-stickiness. That is, the welfare reduction effects are mitigated. Conversely, the expansion of foreign money supply that reduces the home output, and induces an increase in welfare. The magnitude of this increase depends on the price elasticity of demand. When the price elasticity of demand (θ) is <2, the decline in home output caused by price changes due to home money appreciation is greater, and the increase in welfare is enhanced. However, when the price elasticity of demand (θ) is >2, the decline in home output caused by price changes due to home money appreciation is smaller, and the increase in welfare is reduced. By offsetting the consumption and output dimensions, we find that home expansionary monetary policy increased home welfare, whereas the effect of foreign expansionary monetary policy on home welfare was ambiguous.
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exposed to exchange rate or interest rate fluctuations. We argue that the results estimated from this model may be biased due to its explicit assu mption that banks’ exposure is constant over time. Since banks’ circumstances, including the extent of international operations and risk management activities, change over time, their exposures to exchange rate and interest rate movements are also expected to vary over time. Another important source of bias stems from the fact that the market portfolio may also be exposed to the exchange rate and interest rate changes. Thus, the exposure parameters of the standard Jorion (1990) model may not capture the ban ks’ total exchange rate and interest rate risks. Instead, they only measure the banks’ exposures over and above those of the market portfolio. Furthermore, most empirical studies investigate the linear relationship between stock returns and foreign exchange movements. However, many studies suggest that the exposure of firms to foreign exchange fluctuations may be nonlinear (see, for example, Ware and Winter 1988; Sercu and Uppal 1995; Bartram 2004; Muller and Verschoor 2006; Priestley and Odegaard 2007). To address the above biases, we model the linear and nonlinear exposure of Chinese banks using a GARCH-based-multifactor-model with time varying parameters and orthogonalised market returns. Our results suggest that all the sample banks experience at least one significant (at the 5% level) yearly exposure to foreign exchange changes and interest rate movements.
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Prices of digital currencies including Bitcoin in various fiat monies are readily available. Starting from price levels in terms of the prices of goods and services in a fiat money in a particular locale, conventionally identified as a nation, the real quantity of money demanded could be determined using the exchange rate of digital currency for the currency in which local goods and services are priced. While local goods and services could be priced in terms of the digital currency, it is not necessary. If there are multiple digital currencies, at this level of generality, there is even less reason to expect prices to be denominated in any particular digital currency. Nonetheless, there are virtually no data to decide how many bitcoins to allocate to what country and therefore there is no obvious way to compute a real quantity of bitcoins.
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In general, the analysis provides us with three main findings. First, financial institutions’ stock returns are not affected by home/foreign currency variability (FXV). Second, financial institutions’ stock returns are affected by foreign currency (FX) movements. Third, financial institutions’ equity sensitivity to foreign exchange (FX) movements has changed significantly during the crisis period. The first finding (i.e. the returns of bank/insurance portfolios are not sensitive to home/foreign currency variability -FXV- over the sample period) comes from testing the H1 hypothesis, which examines the return sensitivity due to home/foreign currency variability (FXV) over the whole sample period. From Table 2, it is clear that the null hypothesis cannot be rejected by all sector portfolios. This is in contrast to Koutmos and Martin (2003) who find evidence of a strong and positive link between home currency variability and the performance of U.S. financial institutions during 1992-98. They argue that the positive relationship is because greater variation in currency values induces more hedging, which increases the profit of underwriters (e.g. banks) who issues these hedging instruments (e.g. FOREX derivatives). We argue that the conflict in the results is mainly due to the different sample period employed. We believe that during our sample period the main concern for investors is credit risk rather than currency exposure. This becomes more evident during the recent crisis. Therefore, the trading volume of FOREX derivatives should only represent a small proportion of the overall derivatives market compared to credit-related instruments. Even though higher variation of currency values will increase the sales of FOREX derivatives, its apparent impact on the profitability of financial institutions appears to be limited. Our argument is supported by the report from the World Federation of Exchanges (WFE) 15 . During the
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This study examines the symmetric and asymmetric exchange rate ex- posures of Chinese automobile ﬁrms at diﬀerent time horizons. Empirical ﬁndings reveal that ﬁrm returns are less likely to be aﬀected by currency movements at short-term (daily) horizons due to restrictions on the currency daily trading band, but (a)symmetric exchange rate exposures appear to be signiﬁcant at relatively longer horizons after the launch of RMB internation- alisation, particularly for monthly horizons. Possible hedging strategies could be the application of Forward Exchange Agreements, price diﬀerence between onshore and oﬀshore RMB exchange rate, foreign reserves and other quanti- tative methods. Since returns of foreign capital shares tend to rise with the application of RMB, ﬁrms may also consider listing shares on foreign stock exchange in addition to the domestic market and produce products simulta- neously in foreign nations through international expansion.
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