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The purpose of this paper is to estimate long-term currency exchange rate and also identify the key factors for decision makers in the currency exchange market. The study is expected to aid decision makers to take positions in the dynamic Forex market.

This study is based on quantitative and fundamental analysis of statistically oriented regression models. The trend of quarterly exchange rates is investigated using 110 variables including economic elements, interest rate and other currencies. This research is based on the same information that banks’ dealers use for the analysis. Ordinary least squares linear regression also known as “least squared errors regression” was used to estimate the value of the dependent variable.

The study concludes that “only Australian economic data” or “only the US economic data” cannot fully reflect the trend of AUD/USD. EUR influences AUD relatively larger than the other main market currencies. Six-month Australian interest rate itself affects AUD/USD trend much more than the six-month interest difference between AUD and USD.

The results indicate that the economic autoregressive moving average model can be used to predict future exchange rate using primary factors identified and not from the generic market or economic view. This helps adjust to the general, common (and possibly wrong) views when making a buy or sell decision.

This is one of the first studies in the context using the information of bank dealers for AUD/USD. This study is highly relevant in the current context, given the significant growth in Forex trade.

Questionnaire surveys made at currency markets around the world reveal that currency trade to a large extent not only is determined by an economy's performance or expected performance. Indeed, a fraction is guided by technical trading, which means that past exchange rates are assumed to provide information about future exchange rate movements. The purpose of this paper is to ask how a successful monetary policy should be designed when technical trading in the form of trend following is used in currency trading.

The paper embeds an optimal policy rule into Galí and Monacelli's dynamic stochastic general equilibrium (DSGE) model for a small open economy, which is augmented with trend following in currency trading, to examine the prerequisites for a successful monetary policy. Specifically, the conditions for a determinate rational expectations equilibrium (REE) that also is stable under least squares learning are in focus. The paper also computes impulse‐response functions for key variables to study how the economy returns to steady state after being hit by a shock.

The paper finds that a determinate REE that also is stable under least squares learning often is the outcome when there is a limited amount of trend following in currency trading, but that a more flexible inflation rate targeting in monetary policy sometimes cause an indeterminate REE in the economy. Thus, strict, or almost strict, inflation rate targeting in monetary policy is recommended also when there is technical trading in currency trading and not only when all currency trading is guided by fundamental analysis (in the form of rational expectations). This result is a new result in the literature.

There are already models in the literature on monetary policy design that incorporate technical trading in currency trading into an otherwise standard DSGE model. There is also a huge amount of DSGE models in the literature in which monetary policy is optimal. However, the model in this paper is the first model, to the best of the author's knowledge, where technical trading in currency trading and optimal monetary policy are combined in the same DSGE model.

In the increasingly globalized economy, foreign exchange fluctuations have multiple, conflicting effects on domestic stock prices. The purpose of this paper is to examine return data to determine the relation between the dollar’s value and stock prices as it relates to monetary policy.

The authors examine US stock returns over a 40-year period, which is classified according to monetary policy and dollar trend. To better understand the impact of foreign exchange fluctuations, the authors estimate a model of stock returns using the three Fama-French factors and a momentum factor. Then the authors explore the underlying economic fundamentals that drive the sharp difference in annual returns between periods when the dollar is in an uptrend trend with loose monetary policy and periods when the dollar is in a downtrend with tight monetary policy.

Over the last 40 years, US stock returns were 2.5 times higher when the dollar was trending up vs down. The factor model of returns shows that equity returns are positively associated with periods when the dollar appreciated. Returns were particularly high when the dollar was in an uptrend during accommodative monetary policy. During these periods, stocks in the consumer goods and services industries provided relatively high returns. This occurred with strong economic growth due to consumer spending. Stocks exhibited the lowest returns when the dollar was depreciating and the Federal Reserve was tightening.

The key contribution of the research is that currency trends should be analyzed in the light of monetary policy. During periods of accommodative monetary policy and dollar appreciation, the US stock market provided average returns of 18.7 percent compared to −3.29 percent during a period of restrictive monetary policy and dollar depreciation. This result is driven by stronger economic growth, which is composed of consumer spending that more than offsets the dollar’s impact on net exports.

This study seeks to examine the effectiveness of controlling the currency risk for international diversified mixed‐asset portfolios via two different hedge instruments, currency forwards and currency options. So far, currency forward has been the most common hedge tool, which will be compared here with currency options to control the foreign currency exposure risk. In this regard, several hedging strategies are evaluated and compared with one another.

Owing to the highly skewed return distributions of options, the application of the traditional mean‐variance framework for portfolio optimization is doubtful. To account for this problem, a mean lower partial moment model is employed. An in‐the‐sample as well as an out‐of‐the sample context is used. With in‐sample analyses, a block bootstrap test has been used to statistically test the existence of any significant performance improvement. Following that, to investigate the consistency of the results, the out‐of‐sample evaluation has been checked. In addition, currency trends are also taken into account to test the time‐trend dependence of currency movements and, therefore, the relative potential gains of risk‐controlling strategies.

Results show that European put‐in‐the‐money options have the potential to substitute the optimally forward‐hedged portfolios. Considering the composition of the portfolio in using in‐the‐money options and forwards shows that using any of these hedge tools brings a much more diversified selection of stock and bond markets than no hedging strategy. The optimal option weights imply that a put‐in‐the‐money option strategy is more active than at‐the‐money or out‐of‐the‐money put options, which implies the dependency of put strategies on the level of strike price. A very interesting point is that, just by dedicating a very small part of the investment in options, the same amount of currency risk exposure can be hedged as when one uses the optimal forward hedging. In the out‐of‐sample study, the optimally forward‐hedged strategy generally presents a much better performance than any types of put policies.

The research shows the risk and return implications of different currency hedging strategies. The finding could be of interest for asset managers of internationally diversified portfolios.

Considering the findings in the out‐of‐sample perspective, the optimally forward‐hedged minimum risk portfolio dominates all other strategies, while, in the depreciation of the local currency, this, together with the forward‐hedged tangency portfolio selection, would characterize the dominant portfolio strategies.

The purpose of this study is to determine if intraday week (IDW) effect of the currencies reflect leverage and asymmetric impact in currencies market. The study data set comprises of intraday patterns of 15 currencies from developed and emerging economies.

The study applies the exponential generalized autoregressive conditional heteroscedasticity (E-GARCH) model technique to observe the IDW leverage and asymmetric effect after introducing hourly dummies variables, namely, IDWmon, IDWwed, IDWfrid and IDWfrid-mon.

The study results favor the propositions and confirm that IDW effect do exist in the international forex markets in relation to hourly trading pattern for respective currencies. Mostly, currencies do depreciate on Monday and Wednesday compared to the rest of the days. However, on the last trading day, i.e. Friday currencies observe an appreciation pattern which is for both economies. The results have an evidence of leverage and asymmetric effect confirmed by the E-GARCH model as a result of press releases and influence by micro-factors in the currency markets.

The study believes to have theoretical connection related to the better understanding of currencies trend for developed and emerging economies, as the IDW effect exists. Moreover, confirmation of both the leverage and asymmetric effect in observed currencies would be able to assist the investors in making rational choices during the trading hours and would confirm considerable profits through profit incentivized strategies.

The study not only add knowledge to the previous study work in relation to the hourly trading pattern of currencies with reference to the IDW effects but also highlights the leverage and asymmetric effect in currencies that will help in formulating future trading strategies particular to emerging economies.

Uses Monte Carlo simulation to demonstrate the benefits of employing a currency swap to hedge the exchange rate exposure in a single international real estate investment. The only cashflow exposed to the currency fluctuations is the appreciation associated with the investment. Shows that this hedging technique has some potential for protecting the investor from adverse currency fluctuations if an international real estate investment is made. However, promises to explore unresolved issues in future research. Demonstrates that some elements of exchange rate risk may be hedged, resulting in improved risk‐adjusted returns. Thus extends earlier research in international property investment and suggests that international real estate strategies based on diversification (as opposed to currency plays) may be more effective than has been argued in previous research.

Since the issuance in 2009, the digital currency has enjoyed an increasing popularity and has become one of the most important options for global investors. The purpose of this paper is to propose a hybrid model ( KDJ–Markov chain) which integrates the advantages of the stochastic index (KDJ) and grey Markov chain methods and provide a useful decision support tool for investors participating in the digital currency market.

Taking Litecoin's closing price prediction as an example, the closing prices from May 2 to June 20, 2017, are used as the training set, while those from June 21 to August 9, 2017, are used as the test set. In addition, an adaptive KDJ–Markov chain is proposed to enhance the adaptability for dynamic transaction information. And the paper verifies the effectiveness of the KDJ–Markov chain method and adaptive KDJ–Markov chain method.

The results show that the proposed methods can provide a reliable foundation for market analysis and investment decisions. Under the circumstances the accuracy of the training set and the accuracy of the test set are 76% and 78%, respectively.

This study not only solves the problems that KDJ method cannot accurately predict the next day's state and the grey Markov chain method cannot divide the states very well, but it also provides two useful decision support tools for investors to make more scientific and reasonable decisions for digital currency where there are no existing methods to analyze the fluctuation.

A new approach to analyze the fluctuation of digital currency, in which there are no existing methods, is proposed based on the stochastic index (KDJ) and grey Markov chain methods. And both of these two models have high accuracy.

Outlines previous research on international investment portfolios and presents a study of diversification and hedging on money market, bond and equity funds from UK, US and Japanese investors’ points of view. Explains the methodology, uses 1995‐1998 data to calculate returns and discusses the results. Suggests that foreign bonds and equities reduce exchange rate risk more effectively than money market instruments, although some of that risk is not diversifiable. Compares the benefits of diversification and hedging for investors in the three countries at different levels of risk and concludes that optimum asset allocation depends on the fund market characteristics, risk preferences and investor perspective.

After experiencing long, multiyear surges and slides in past decades, by summer 2013, the dollar had been range-bound against the euro. In this case, by assessing potential capital flows, students consider whether global currency market trends would propel the dollar higher, or if the past few years were just a pause in a much longer dollar depreciation episode. Suitable for both core and elective MBA courses in global financial markets and international finance, this case explores factors pointing to further euro appreciation and to others favoring the dollar. Sorting through mounds of evidence is necessary before forecasting the exchange rate's likely path. Filtering that evidence requires thinking about FX markets, prospective monetary policies, and past and prospective international capital flows.

The study aims to explore the role of non-resident Indian (NRI) investors into staggering local housing market and the efforts of developers and regulators to lure such investors.

Primary data for this exploratory study were assembled through a Google form-based questionnaire circulated over internet among NRIs residing in Kingdom of Saudi Arabia, USA, Singapore and United Arab Emirates, whereas the secondary data sources include the Government of India policy documents, World Bank data, Reserve Bank of India archives and reports published in reputed financial and others print media sources.

Indian housing market is confronted with a demand and supply mismatch at present. While a massive demand lingers at affordable housing segment, on the contrary, millions of housing inventories are also piling up. Consequently, property developers are attempting to lure the large population of NRIs residing at global cities. Study observes that sentimental attachment to the homeland, higher rate of returns, anticipated rental incomes are the major decisive elements. Additionally, growth in infrastructure, world-class amenities offered by developers, conformity to sustainability and political stability is the other critical reasons.

On first hand, the study outlines a novel kind of foreign investment in Indian local residential real estate that is via NRI channel. Second, non-resident investors might surprise to the property developers and government through a realistic strategic approach.

Probably, the study is first of its type gazing at NRI investors, as a foreign investor, in the local residential real estate.