Zealand Dollar Research Articles

Pandemic‐induced fear and government policy response as a measure of uncertainty in the foreign exchange market: Evidence from (a)symmetric wild bootstrap likelihood ratio test

AbstractThe paper aims to examine the ability of a global fear index (GFI) based on the COVID‐19 pandemic and government policy responses as a measure of uncertainty in predicting eight Indian rupee‐based exchange rate return series: the Australian dollar, the Canadian dollar, the Swiss franc, the US dollar, the euro, the British pound sterling, the New Zealand dollar, and the Japanese yen. The predictability of the daily Indian rupee‐based exchange rate return series is tested using the recently developed wild bootstrap likelihood ratio test of Kim and Shamsuddin for the period 2 October 2020 to 8 March 2021. Both symmetric and asymmetric tests revealed GFI as an insignificant determinant of the Indian rupee‐based exchange rate return series. However, government policy responses are a significant determinant of the rupee–dollar exchange rate return series.

History of the New Zealand Dollar

History of the New Zealand Dollar

Forecasting Foreign Currency Exchange Rate using Convolutional Neural Network

Foreign exchange rate forecasting has always been in demand because it is critical for foreign traders to know how their money will perform against other currencies. Traders and investors are always looking for fresh ways to outperform the market and make more money. As a result, economists, researchers and investors have done a number of studies in order to forecast trends and facts that influence the rise or fall of the exchange rate (ER). In this paper, a new Convolutional Neural Network (CNN) model with a random forest regression layer is used for future closing price prediction. The intended model has been tested using three major currency pairs: Australian Dollar against the Japanese Yen (AUD/JPY), the New Zealand Dollar against the US Dollar (NZD/USD) and the British Pound Sterling against the Japanese Yen (GBP/JPY). As a proof-of-concept, the forecast is made for 1 month, 2 months, 3 months, 4 months, 5 months, 6 months and 7 months utilizing data from January 2, 2001 to May 31, 2020 for AUD/JPY and GBP/JPY and data from January 1, 2003 to May 31, 2020 for NZD/USD. Furthermore, when compared the performance of the suggested model with the Autoregressive Integrated Moving Average (ARIMA), Multi-Layer Perceptron (MLP) and Linear Regression (LR) models and found that the proposed CNN with Random Forest model surpasses all models. The suggested model's prediction performance is assessed using R2, MAE, RMSE performance measures. The proposed model's average R2 values for three currency pairs from one to seven months are 0.9616, 0.9640 and 0.9620, demonstrating that it is the best model among them. The study's findings have ramifications for both policymakers and investors in the foreign exchange market.

Is oil risk important for commodity-related currency returns?

This paper investigates the relationship between oil and commodity-related currency markets using the volatility risk premium (VRP) of oil as an oil risk proxy. We find that oil VRP can forecast typical commodity currency returns except for the New Zealand dollar. The one-month-ahead forecasting model with oil VRP allows us to beat a random walk model for most commodity currency returns in the out-of-sample study and to outperform the classical return forecasting model. Different economic periods influence the predictive power of oil VRP. Oil VRP contains specific information that cannot be captured by classical fundamentals and global risks, and in most cases, it is a better predictor of currency returns than these traditional variables. A strategy using oil VRP to forecast currency returns helps investors reduce portfolio losses. This paper provides a risk channel for oil information transmitting from the oil markets to commodity-related currency markets.

Fatty acid distillate as an alternative boiler fuel

This paper investigated the use of fatty acid distillate (FAD) produced as a by-product of edible oil refining as a fuel source for boilers. Using a diesel heater to model the combustion chamber of a fire tube boiler showed that diesel blends with FAD up to 60% could be used with different levels of preheating. A small to medium sized edible oil refinery was used to generate an economic model. It was estimated that an edible oil refinery of this size required a boiler able to supply 3 GJ/h of energy. In this situation, the FAD produced could provide approximately 57% of the yearly energy requirements for the boiler. An economic analysis revealed that using FAD (42 MJ/kg) as fuel will increase its value from New Zealand Dollar ($) 0.425/kg to approximately $1.30–1.55/kg depending on the cost of standard boiler fuel. Running the boiler on LPG ($30/GJ) or diesel ($37.7/GJ) was estimated to cost $960,000 and $1,200,000 respectively per year. If all the FAD was used as alternative fuel to provide 57% of the yearly energy, then up to $700,000 could be saved each year.

Bioeconomic Modelling to Assess the Impacts of Using Native Shrubs on the Marginal Portions of the Sheep and Beef Hill Country Farms in New Zealand

New Zealand hill country sheep and beef farms contain land of various slope classes. The steepest slopes have the lowest pasture productivity and livestock carrying capacity and are the most vulnerable to soil mass movements. A potential management option for these areas of a farm is the planting of native shrubs which are browsable and provide erosion control, biodiversity, and a source of carbon credits. A bioeconomic whole farm model was developed by adding a native shrub sub-model to an existing hill country sheep and beef enterprise model to assess the impacts on feed supply, flock dynamics, and farm economics of converting 10% (56.4 hectares) of the entire farm, focusing on the steep slope areas, to native shrubs over a 50-year period. Two native shrub planting rates of 10% and 20% per year of the allocated area were compared to the status quo of no (0%) native shrub plantings. Mean annual feed supply dropped by 6.6% and 7.1% causing a reduction in flock size by 10.9% and 11.6% for the 10% and 20% planting rates, respectively, relative to 0% native shrub over the 50 years. Native shrub expenses exceeded carbon income for both planting rates and, together with reduced income from sheep flock, resulted in lower mean annual discounted total sheep enterprise cash operating surplus for the 10% (New Zealand Dollar (NZD) 20,522) and 20% (NZD 19,532) planting scenarios compared to 0% native shrubs (NZD 22,270). All planting scenarios had positive Net Present Value (NPV) and was highest for the 0% native shrubs compared to planting rates. Break-even carbon price was higher than the modelled carbon price (NZD 32/ New Zealand Emission Unit (NZU)) for both planting rates. Combined, this data indicates planting native shrubs on 10% of the farm at the modelled planting rates and carbon price would result in a reduction in farm sheep enterprise income. It can be concluded from the study that a higher carbon price above the break-even can make native shrubs attractive in the farming system.

Can Tail Risk Predict Asia-Pacific Exchange Rates Out of Sample?

We present novel evidence to show that tail (market) risk, measured as the conditional autoregressive value at risk, is a good predictor of Asia-Pacific exchange rates. We use daily exchange rate data for the Australian dollar, the Chinese yuan, the Indonesian rupiah, the Japanese yen, the Malaysian ringgit, the New Zealand dollar, the Philippine peso, and the Singapore dollar each against the US dollar, the pound sterling, and the euro between January 3, 2007, and March 8, 2021. Impact analyses suggest hedging benefits for investors in US dollar–denominated exchange rates, especially in advanced Asia-Pacific countries. Superior out-of-sample forecast performance appears to supersede the Meese–Rogoff puzzle.

Effectiveness of foreign exchange interventions: evidence from New Zealand

ABSTRACT This paper examines the effectiveness of explicit and implicit foreign exchange (FX) interventions in New Zealand: one secret spot market intervention and two implicit interventions – a regular Monetary Policy Statement (MPS) and an unexpected oral intervention by the Reserve Bank of New Zealand (RBNZ) governor addressing the New Zealand Dollar (NZD). By applying a synthetic control methodology to a unique dataset of RBNZ interventions, we construct a counterfactual to estimate their effect. The results indicate that the actual intervention and the MPS release were ineffective in moving the NZD. However, the speech depreciated the NZD by 1.12%, although the effect was small and short lived. Our findings suggest that FX interventions, explicit or implicit, are a weak policy tool to affect the exchange rate in New Zealand.

Connectedness of Asia Pacific forex markets: China's growing influence

AbstractThis paper investigates the degree of connectedness of Asia Pacific forex markets post‐global financial crisis and relates it to developments in the renminbi markets. The connectedness measure developed by Diebold and Yilmaz (2014) (Journal of Econometrics, 182, 119–134) reveal the strength of linkages across the U.S. dollar currency pairs of 12 currencies, namely offshore renminbi, onshore renminbi, euro, yen, Australian dollar, Indian rupee, Korean won, Malaysian ringgit, New Zealand dollar, Singapore dollar, Thai baht and Taiwan dollar. With the gradual liberalization of China's exchange rate system, shocks from the renminbi markets contribute more to fluctuations in almost all individual Asia Pacific currency markets vis‐à‐vis the yen. Rolling regressions show a number of Asia Pacific currencies exhibit tighter association with the renminbi when the latter underwent exchange rate regime reform. Finally, results from a two‐step analysis involving a panel regression provide evidence that time‐varying sensitivities of Asia Pacific currencies to the renminbi are directly related to the countries' trade and financial links with China.

Does the U.S. economic policy uncertainty connect financial markets? Evidence from oil and commodity currencies

We provide novel insight to the emerging literature on the role of U.S. monetary policy as a driver of a global financial cycle by examining the possible causal effect of U.S. economic policy uncertainty on the connectedness of crude oil and currency markets, using a sample of commodity currencies from advanced and emerging nations. A battery of linear and nonlinear Granger-based causality tests indicate the presence of a causal relationship between economic policy uncertainty and the connectedness of oil and currency markets, particularly at low frequencies and more significantly after the outburst of the global financial crisis. While crude oil generally serves as a net transmitter of shocks to currencies across all frequency bands, the spillover effects from oil are largely concentrated towards the G10 currencies of Australian and New Zealand dollar that are often used as investment currencies in global carry trade strategies. Overall, our findings suggest the presence of a significant pass-through effect of economic policy uncertainty via oil prices, spilling over to the currency market, in line with the emerging evidence that the monetary policy by the U.S. Fed serves as a major driver of a global financial cycle that describes patterns in global capital flows, credit activity and asset prices across financial markets.

Commodity-currencies or currency-commodities: Evidence from causality tests

This paper presents a comparative analysis of the return and volatility spillovers across the commodity and currency markets for an expanded set of commodity-exporters and currencies that includes several emerging commodity-exporting nations in addition to the developed exporters that have often been the focus in the literature. Strong causal effects are observed, largely in the direction of commodities from currencies with several cases of bidirectional causality, particularly between gold and the New Zealand dollar, Brent oil and the Brazilian real, and copper and the Chilean peso. The causal effects from currencies to commodities are not only limited to return causality, but exist in the case of volatility as well, implying the presence of significant risk transmissions from currencies. We also show that causal effects from currencies to commodities have become more widespread during the period following the 2007–2008 global financial crisis. Overall, our findings imply that currency market dynamics have informative value for commodity return and volatility with significant implications for volatility forecasting and active management of commodity price fluctuations.

Commodity-Currencies or Currency-Commodities: Evidence from Causality Tests

This paper presents a comparative analysis of the return and volatility spillovers across the commodity and currency markets for an expanded set of commodity-exporters and currencies that includes several emerging commodity-exporting nations in addition to the developed exporters that have often been the focus in the literature. We find strong causal effects, largely in the direction of commodities from currencies with several cases of bidirectional causality observed, particularly between gold and the New Zealand dollar, Brent oil and the Brazilian real, and copper and the Chilean peso. The causal effects from currencies to commodities are not only limited to return causality, but exist in the case of volatility as well, implying the presence of significant risk transmissions from currencies. Finally, we show that causal effects from currencies to commodities have become more widespread during the period following the 2007-2008 global financial crisis. Overall, our findings imply that currency market dynamics have informative value for commodity return and volatility with significant implications for volatility forecasting and active management of commodity investments.

THE YIELD OF THE CARRY TRADE STRATEGY

The article analyzes the carry trade strategy in which, according to common definition, traders borrow a currency that has a low-interest rate and use the funds to buy a different currency that is paying a higher interest rate. The aim of this work is to form the optimal strategies and carry trade portfolio. The task of our study was to study the interdependence between the yield of the carry trade strategy and the USA stock market on the basis of a mathematical approach and offer a portfolio of currencies with the highest historical yield over the past five years. The author used the model of relative risk aversion. We analyzed data on exchange rates, forward premium and real exchange rates for the Eurozone, as well as for countries of the Organization for Economic Cooperation and Development (OECD) such as Australia, Brazil, China, Japan, New Zealand, Russia, Switzerland, the United Kingdom and the United States of America. Carry trade’s yield is not tied to standard risk factors. Popular funding currency — the yen has experienced a strong jump of volatility as a result of the 2008–2009 crisis. A possible explanation for this reversal is investors’ appetite for risk. The author concluded that the most common carry trade strategies in the period from 2009 to 2014 were formed on the basis of two financing currencies (Japanese yen and the US dollar) and three investment currencies (Australian dollar, New Zealand dollar and Chinese yuan). After 2014, the US dollar ceases to be the funding currency, giving way to the Euro. The optimal carry trade strategy is borrowing in the currencies of developed countries (EUR, JPY) and investing in the currencies of energy producing countries (RUB, BRL). There is a negative relationship between the volume of transactions based on the carry trade strategy and the yield of shares in the financing country. There is also a significant link between the yield of the carry trade strategy and the profitability of the USA stock market.

The Valuation of Currency Put Options

Investors who seek to profit from depreciating currencies may invest in put options. Upon option exercise, the currency is sold at a high price, and then purchased at the lower future currency value, resulting in a gain for the put buyer. A series of such transactions yields a stream of income for the put investor. Alternatively, the investor could short sell the currency, reaping gains from the difference between the high short sale price and the low future purchase price. This paper derives the theoretical formulations for combined short sale and puts purchase strategies for the US dollar, the Euro, the Australian dollar and the New Zealand dollar, and the Mexican peso. Utility functions are based upon an assumption of declining risk aversio with negative rescale factors and positive threshold factors in a hyperbolic cosine distribution. This distribution intersects with the cosine distribution of short sale prices on the U. S. dollar, the lognormal distribution of short sale prices on the Euro, the Weiner process for shorts on the Australian dollar and the New Zealand dollar, and the Laplace currency distribution for peso shorts. Similar utility functions intersect with Levy-Khintchine jump processes to provide put option prices for each type of foreign currency.

The State-of-the-Art Technology of Currency Identification

The security issue of currency has attracted awareness from the public. De-spite the development of applying various anti-counterfeit methods on currency notes, cheaters are able to produce illegal copies and circulate them in market without being detected. By reviewing related work in currency security, the focus of this paper is on conducting a comparative study of feature extraction and classification algorithms of currency notes authentication. We extract various computational features from the dataset consisting of US dollar (USD), Chinese Yuan (CNY) and New Zealand Dollar (NZD) and apply the classification algorithms to currency identification. Our contributions are to find and implement various algorithms from the existing literatures and choose the best approaches for use.

Forecasting Daily and Monthly Exchange Rates with Machine Learning Techniques

We combine signal processing to machine learning methodologies by introducing a hybrid Ensemble Empirical Mode Decomposition (EEMD), Multivariate Adaptive Regression Splines (MARS) and Support Vector Regression (SVR) model in order to forecast the monthly and daily Euro (EUR)/United States Dollar (USD), USD/Japanese JPY (JPY), Australian Dollar (AUD)/Norwegian Krone (NOK), New Zealand Dollar (NZD)/Brazilian Real (BRL) and South African Rand (ZAR)/Philippine Peso (PHP) exchange rates. After the decomposition of the original exchange rate series with EEMD into a smoothed and a fluctuation component, MARS selects the most informative from the plethora of variables included in our initial data set. The selected variables are fed into two distinctive SVR models for forecasting each component separately one period ahead with the summation providing exchange rate forecasts. The above implementation exhibits superior forecasting ability in exchange rate forecasting and high Sharpe Ratios compared to various models taking data snooping bias in consideration, rejecting the Efficient Market Hypothesis for all foreign exchange markets. Overall the proposed model a) is a combination of empirically proven effective techniques in forecasting time series, b) is data driven, c) relies on minimum initial assumptions and d) provides a structural aspect of the forecasting problem.

ESTIMATION FOR THE PREDICTION OF POINT PROCESSES WITH MANY COVARIATES

Estimation of the intensity of a point process is considered within a nonparametric framework. The intensity measure is unknown and depends on covariates, possibly many more than the observed number of jumps. Only a single trajectory of the counting process is observed. Interest lies in estimating the intensity conditional on the covariates. The impact of the covariates is modelled by an additive model where each component can be written as a linear combination of possibly unknown functions. The focus is on prediction as opposed to variable screening. Conditions are imposed on the coefficients of this linear combination in order to control the estimation error. The rates of convergence are optimal when the number of active covariates is large. As an application, the intensity of the buy and sell trades of the New Zealand Dollar futures is estimated and a test for forecast evaluation is presented. A simulation is included to provide some finite sample intuition on the model and asymptotic properties.

Legal Problems of Inflation

The article reviews the efforts by Governments, Courts and professional accounting bodies to mitigate the hugely damaging effects of the high inflation of the 1970s and 1980s on the economy and the wider public. The Consumer Price Index brings out that impact recording that in 1990 a New Zealand dollar was worth less than one-eighth its value in 1970.The article traces the development of the treatment of inflation by those bodies during that period and by the Courts since then. It goes on to highlight various areas of the law where inflation has continued to cause problems, focusing on contract and commercial law, damages in tort, taxation and succession to property including trusts, wills and family breakdown.

Long Memory Features Evolve in the Time-varying Process in Asia-pacific Foreign Exchange Markets

We investigated the presence of, and changes in, long memory features in the returns and volatility dynamics of six Asia-Pacific foreign exchange markets (Australian dollar, Japanese yen, Korean won, New Zealand dollar, Singaporean dollar, and Taiwan dollar) using time-varying Hurst exponents. In particular, instead of relying on a single static measure of long memory, we explored time-varying long memory features over time to assess changes in market efficiency by analyzing the returns and volatility of the markets. Furthermore, considering a time-varying rolling approach, we estimated values of the Hurst exponent for time windows with 1,000 observations (about 4 years of data) in each window. The estimation results indicated that both the returns and the volatility series possessed strong long memory features and that the degree of the long memory features changed over time. Additionally, the Hurst exponent showed an upward trend during the 1997 Asian currency crisis and 2008 global financial crisis, indicating that exchange rate markets became inefficient and predictable during the financial crisis.

Four harmonic cycles explain and predict commodity currencies' wide long term fluctuations

In theory and practice, it is difficult to accept a particular model of explanation and forecasting of exchange currencies as the literature review reveals. However, the currencies that are called commodity currencies, such as the Australian dollar are heavily influenced by commodity prices cycles, and hence they might be easier to analyze and predict. We investigate the possibility that the Australian dollar is primarily determined by a handful of harmonic cycles which in turn are based not only on commodity prices cycles but also on commodity production cycles and in general on economic cycles. In this way we can get a very good fit of the relevant data and good out-of-sample forecasts. We cross check these results by referring to the main issues involved, such as fundamentals, short and long cycles, and so on. In addition, our analysis, forecasting ability, and conclusions still hold for three more commodity currencies examined here: New Zealand's dollar, Canada's dollar, and Norway's krone.