Volatility reversal from interest rates to the real exchange rate : financial liberalization in Chile, 1975-82

The authors analyze the dynamic adjustment of the real exchange rate, the domestic interest rate, and foreign borrowing under conditions of perfect and imperfect capital mobility during financial liberalization. Making use of a two-sector model with current and capital accounts interacting, they show that the domestic interest rate is more volatile under imperfect mobility and the real exchange rate more volatile under perfect mobility. So liberalizing the capital accounts does not eliminate variations in the domestic interest rate but shifts them to the real exchange rate. Studying data for Chile during the period of financial liberalization from 1975 to 1982, they found that the domestic interest rate became less volatile and less responsive to domestic variables - and more dependent on the covered international interest rate, while the real exchange rate became more responsive to domestic wealth. Foreign reserve holdings and net exports followed a similar pattern: the covered international rate had stronger effects on reserve changes while real wealth became more important for determining net exports.Economic Theory&Research,Macroeconomic Management,Economic Stabilization,Environmental Economics&Policies,Banks&Banking Reform

Financial liberation and adjustment in Chile and New Zealand

The authors analyze macrodynamic adjustment during financial liberalization in Chile and New Zealand. During the adjustment to more open capital accounts in the late 1970s or mid-1980s, both countries experienced appreciation of the real exchange rate and a collapse of net exports, while domestic interest rates slowly converged to international levels. The authors develop and estimate a two-sector dynamic model using both current and time-varying parameters. They find the domestic interest rate to be more responsive to shocks under imperfect capital mobility, the real exchange rate more responsive under perfect capital mobility. In short, liberalization of the capital account does not eliminate volatility but rather shifts it from the domestic interest rate to the real exchange rate.Economic Theory&Research,Macroeconomic Management,Economic Stabilization,Environmental Economics&Policies,Banks&Banking Reform

CENTRAL BANK LEARNING, TERMS OF TRADE SHOCKS & CURRENCY RISKS: SHOULD ONLY INFLATION MATTER FOR MONETARY POLICY?

This paper examines the role of interest rate policy in a small open economy subject to terms of trade shocks, and time-varying currency risks. The private sector makes optimal decisions in an intertemporal non-linear setting with rational, forward-looking expectations. In contrast, the monetary authority practices "least-squares learning" about the evolution of inflation, output growth, and exchange rate depreciation in alternative policy scenarios. Interest rates are set by linear quadratic optimization, with the objectives for inflation, output growth, or depreciation depending on current conditions. The simulation results show that the prefered stance is one which targets inflation only. Including other targets such as growth and exchange rate changes significantly increases output variability, and unambiguously decreases welfare.Currency risks, learning, parameterized expectations, policy targets

The Response of Australian Stock, Foreign Exchange and Bond Markets to Foreign Asset Returns and Volatilities

This paper is a data-analytic study of the relationships among international asset price volatilities and the time-varying correlations of asset returns in a small open economy (Australia) with international asset returns. Making use of recent developments in time-series approaches to volatility estimation, impulse response functions, variance decomposition, and Kalman filtering, I show that the Australian stock market volatility is most closely linked with volatility in the UK stock market, and the correlation of Australian stock returns with UK returns are high when there is increasing turbulence in financial markets. Volatility in the Australian dollar/US dollar exchange rate is most closely linked with volatility measures of the US dollar/Canadian dollar rate, and volatility in Australian long-term bond yields is most closely linked to volatility measures of long term German bond returns. The results indicate that asset markets in a small open economy can adapt in different ways during periods of high or increasing volatility. The ways in which domestic volatility measures react to foreign turbulence, and the ways in which domestic returns correlate with international returns, depend on the particular circumstances (such as transactions costs and degree of risk aversion) which prevail in each financial market.

Need Singapore Fear Floating? A DSGE-VAR Approach

This paper uses a DSGE-VAR model to examine the managed exchangerate system at work in Singapore and asks if the country has any reason to fear floating the exchange rate with a Taylor rule inflation-targeting mechanism that uses the short term interest rate instead of the exchange rate as the benchmark monetary policy instrument. Our simulation results show that the use of a more flexible exchange rate system will reduce volatility in inflation and investment but consumption volatility will increase. Overall, there are neither significant welfare gains or losses in the regime shift. Given the highly open and trade dependent nature of the Singapore economy where the policy preference is for exchange rate stability, there is no impetus to abandon the present monetary regime

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome

Neural networks in finance : gaining predictive edge in the market /

This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong. * Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website.Includes bibliographical references pages (221-231).Print version record.Preface; 1. Introduction; 2. What Are Neural Networks; 3. Estimation of a Network with Evolutionary Computation; 4. Evaluation of Network Estimation; 5. Estimation and Forecasting with Artificial Data; 6. Times Series: Examples from Industry and Finance; 7. Inflation and Deflation: Hong Kong and Japan; 8. Classification: Credit Card Default and Bank Failures; 9. Dimensionality Reduction and Implied Volatility Forecasting.This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong. * Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website.Elsevie

Three financing options for Australian higher education: vouchers, tax credits and TAFE

This paper by Gavin Moody from the 2004 Monash Seminars on Higher Education Policy compared the higher education funding policies of the two parties in the lead-up to the 2004 Federal election