Short-run Predictability Research Articles

Exchange Rate Dynamics and Monetary Fundamentals: Evidence from South Asian Countries

This paper examined the role of monetary fundamentals in determining nominal exchange rate changes in South Asian countries. The Vector Autoregressive (VAR) technique and Autoregressive Distribution Lag (ARDL) were used. Results from the VAR indicate that the exchange rate responds to shock originating from differences in money supply, inflation differential, interest rate, and real income differential and are consistent with the short-run predictions of the monetary model of the exchange rate. The results show that inflation and interest rate differentials are responsible for the majority of changes in exchange rates in the short run. The conclusion from the result is that, particularly in the short run, monetary fundamentals are the primary causes of exchange rate fluctuations in South Asian countries.

Effects of Women Education on Child Labor in South Asia

Lack of education and poverty are major factors contributing to child labor. A crucial component of economic and social growth is education of the society. This study contribution looks at how educating women affect child labor in South Asia. It used yearly data from 1990 to 2020. The Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) model use for short run and long run predictions. The significant impact of female education on reducing child labor, emphasizes the significance of participating in girls' education. Policies aimed at enhancing access to and quality of education for girls can help mitigate child labor by authorizing women and breaking poverty cycle. Development of Urban strategies must rank the providing of education, health and social security facilities to the residents of urban areas.

Exchange rate predictability, risk premiums, and predictive system

Uncovered interest rate parity (UIP), a basic assumption in many theoretical models, is known to perform poorly in forecasting exchange rate movements, especially in the short run. One possible reason for this failure is the existence of unobservable risk premium. We estimate the unobservable risk premium with a Bayesian approach having the risk premium as a latent variable and the implied volatility of at-the-money currency options as an imperfect predictor. We find in most cases that expected exchange rate changes, constructed from forward-spot differentials and estimated risk premiums, track actual exchange rate changes more closely than do the fitted values of the predictive regression (i.e. the Fama regression). An out-of-sample analysis reveals that adding the estimated risk premium greatly improves the short-run predictability of exchange rates in general. These findings strongly suggest that the risk premium is important in understanding the dynamics of exchange rate and the UIP puzzle.

Forecasting of Economic Indicators (Production, Consumption, Population) of Wheat Crop (A Case Study)

Wheat is the most important food crop in Afghanistan, whether consumed by the bulk of the people or used in various sectors. The problem is that Afghanistan has a significant shortfall of wheat between domestic production and consumption. Thus, the present study looks at the issue of meeting self-sufficiency for the whole population due to wheat shortages. To do so, we employ time series analysis, which can produce a highly exact short-run prediction for a significant quantity of data on the variables in question. The ARIMA models are versatile and widely utilised in univariate time series analysis. The ARIMA model combines three processes: I the auto-regressive (AR) process, (ii) the differencing process, and (iii) the moving average (MA) process. These processes are referred to as primary univariate time series models in statistical literature and are widely employed in various applications. Where predicting future wheat requirements is one of the most important tools that decision-makers may use to assess wheat requirements and then design measures to close the gap between supply and consumption. The present study seeks to forecast Production, Consumption, and Population for the period 2002-2017 and estimate the values of these variables between 2002 and 2017. (2018-2030).

Liquidity and short-run predictability: Evidence from international stock markets

This study investigates the determinants of short-run predictability in international stock markets, where predictability is defined as the accuracy of the best-combined daily forecasts. Contrary to popular belief, illiquid markets, characterized by high transaction costs and large price impact, are not necessarily highly predictable. Instead, markets with larger trading volume are more predictable, especially after the global financial crisis and in emerging markets. Those with larger market capitalization, steeper upward trends, and positively skewed returns are less predictable. Company financial strength has limited influence. During the COVID-19 pandemic the markets have become more predictable, with stronger price trends. Emerging markets are less predictable when relatively over- or undervalued.

The role of US implied volatility index in forecasting Chinese stock market volatility: Evidence from HAR models

The US implied volatility index (VIX) is a popular proxy for global financial market uncertainty. This paper aims to assess the role of this proxy in forecasting the Chinese stock market volatility, as China’s globalization trend is strengthening. For this purpose, we develop six heterogeneous autoregressive (HAR) models allowing for VIX changes to forecast the Chinese stock market volatility. The in-sample and out-of-sample results show the VIX changes can improve the volatility forecasting in the Chinese stock market but mainly show improvement for the bad volatility forecasting rather than for good volatility forecasting. Additionally, such forecasting improvement is sizable at the short-run prediction horizon but weakens as the prediction horizon increases. Our results also remain robust by using alternative evaluation methods and alternative HAR models.

An investigation of log prices in the U.S. Pacific Northwest

Log prices can be volatile and hard to predict from month to month. For those tasked with managing timberland investments and the marketing of logs, however, short run predictions of price could be useful. This study shows that Douglas-fir log prices can be predicted with reasonable accuracy using only a small amount of readily available macro-economic information. For example, nearly half of the variation in log prices over time can be predicted using the number of housing permits issued in a month. Information about exchange rates and mortgage rates provide further refinement of estimates. An attribution experiment shows that expansionary U.S. monetary policy over the last decade has raised log prices by about 5% above what they otherwise would have been. A strengthening U.S. dollar increased the supply of Canadian softwood in U.S. markets, however, and had a depressing effect on U.S. log prices. The results illustrate how policies enacted in locations far from forest-dependent communities can nonetheless have outsized impacts.

Prediction: The Long and the Short of It

Commentators often lament forecasters’ inability to provide precise predictions of the long-run behavior of complex economic and physical systems. Yet their concerns often conflate the presence of substantial long-run uncertainty with the need for long-run predictability; short-run predictions can partially substitute for long-run predictions if decision-makers can adjust their activities over time. So what is the relative importance of short- and long-run predictability? We study this question in a model of rational dynamic adjustment to a changing environment. Even if adjustment costs, discount factors, and long-run uncertainty are large, short-run predictability can be much more important than long-run predictability. (JEL D21, D81, D83)

Economic growth in China and its impact on international commodity prices

AbstractSince the turn of the century, China has experienced economic growth that has called for rapid industrialisation, infrastructure growth and urbanisation, making China highly dependent on primary commodities. The resource intensive growth path followed by a slowdown in recent years has raised the question to what extent her demand for commodities can affect international commodity prices. To this end, recent studies have analysed the link between economic growth or slowdown on commodity prices using linear multivariate models. However, a problem is that commodity prices are known to be highly variable and characterised by multiple structural changes. With such characteristics of the data, it is likely to be the case one may obtain mis‐specified inferences from a linear multivariate framework. Accordingly, we make use of novel Flexible Fourier Form (FFF) econometric procedures to account for multiple breaks in the economic variables, which have better power and size properties over the standard linear models. We find that the persistence of economic variables employed in this study and their causal link are better approximated by such nonlinear FFF procedures. Our results show that there is evidence of short run predictability between selected commodity prices and economic growth in China. Further, the responses of different commodity prices to shocks in economic growth are quite profound especially for those cases where we find causal links with economic growth in China. While we find a significant impact of economic growth of China on commodity prices, the response varies for different commodities.

Peer firms’ earnings predictability and pricing efficiency – evidence from IPOs*

We examine the effect of peer firms’ earnings predictability on initial public offering (IPO) underpricing by investigating whether peer firms’ financial characteristics affect IPO pricing and whether the information disseminated by the IPO firm changes product market competition. Analyzing 5,264 IPOs in the 1976–2012 period using data from multiple sources, we find that IPO firms whose peer firms have long-run earnings predictability tend to have lower underpricing compared to those with short-run earnings predictability. Our study makes three central contributions. First, it shows that investors do not consider IPO firms in isolation from their peer firms and that IPO underpricing is highly dependent on peer firms’ earnings characteristics. Second, it demonstrates that the market does not always consider earnings predictability to be a desirable attribute, which has practical implications for regulators and firms. Third, we find that product market competition from peer firms and managerial ability both affect IPO underpricing. These results suggest that investors might interpret short-run peer firms’ earnings predictability as evidence that a majority of the firms in the industry engage in myopic behaviors, while they might interpret long-run peer firms’ earnings predictability as a signal that the majority of firms in the industry have stable cash flows.

Common Factor Augmented Forecasting Models for the US Dollar-Korean Won Exchange Rate

We propose factor-augmented out of sample forecasting models for the real exchange rate between Korea and the US. We estimate latent common factors by applying an array of data dimensionality reduction methods to a large panel of monthly frequency time series data. We augment benchmark forecasting models with common factor estimates to formulate out-of-sample forecasts of the real exchange rate. Major findings are as follows. First, our factor models outperform conventional forecasting models when combined with factors from the US macroeconomic predictors. Second, our factor models perform well at longer horizons when American real activity factors are employed, whereas American nominal/financial market factors help improve short-run prediction accuracy. Third, models with global PLS factors from UIP fundamentals overall perform well, while PPP and RIRP factors play a limited role in forecasting.

Variance Risk Premia, Asset Predictability Puzzles, and Macroeconomic Uncertainty

This article reviews the predictability evidence on the variance risk premium: ( a) It predicts significant positive risk premia across equity, bond, currency, and credit markets; ( b) the predictability peaks at few-month horizons and dies out afterward; ( c) such a short-run predictability is complementary to the long-run predictability offered by the price-to-earnings ratio, forward rate, interest differential, and leverage ratio. Several structural approaches based on the notion of economic uncertainty are discussed for generating these stylized facts about the variance risk premium, which has broad implications for various empirical asset pricing puzzles.

Behaviour of the Foreign Exchange Rates of BRICS: Is it Chaotic?

The article focuses on the behaviour of foreign exchange rates of BRICS countries in reference to US dollar with special emphasis on examining presence of nonlinear dependence and deterministic chaos. The findings did not indicate random walk behaviour in the returns for all exchange rates and performance of GARCH as well as EGARCH models are reasonably good in capturing the conditional volatility. Further evidences suggest existence of nonlinear dependence and we compute Maximal Lyapunov Exponent and Correlation Dimension test with multiple surrogate series which confirms the chaotic nature of the exchange rates for all countries under study except for South Africa. The findings support short run predictability in exchange rates while long run predictions are unlikely to be successful. The chaotic nature of the foreign exchange market calls for newer intervention mechanism by the Central Bank of the respective countries to limit the exchange rate volatility.

The Variance Risk Premium: Components, Term Structures, and Stock Return Predictability

This article examines the properties of the variance risk premium (VRP). We propose a flexible asset pricing model that captures co-jumps in prices and volatility, and self-exciting jump clustering. We estimate the model on equity returns and variance swap rates at different horizons. The total VRP is negative and has a downward-sloping term structure, while its jump component displays an upward-sloping term structure. The abrupt and persistent response of the short-term jump VRP to extreme events makes this specific premium a proxy for investors’ fear of a market crash. Furthermore, the use of the VRP level and slope, and of its components, helps improve the short-run predictability of equity excess returns.

What options to trade and when: Evidence from seasoned equity offerings

We investigate options predictability and trading patterns around seasoned equity offerings (SEOs). A negative relation is found between option-implied skewness and post-SEO performance, which is more significant for highly overvalued SEOs. In terms of investment timing, the option-implied skewness reflects long-run information before the equity issuances, while short-run information is updated as the issuance nears. For investment horizon measured by time to expiration (TTE), options with long TTEs have only long-run predictability, while options with short TTEs have only short-run predictability. This study supports informed options trading and helps to clarify options informativeness for various estimation periods and TTEs.

Cross Validation of Prediction Models for Seasonal Time Series by Parametric Bootstrapping

Out-of-sample prediction for the final portion of a sample is a popular tool for model selection in model-based forecasting. We suggest to add a simulation step to this exercise, where pseudo-samples are generated (parametrically bootstrapped), conditional on the observed data and on any of the candidate models, and these pseudo-samples are predicted using any of the candidate models. The technique is demonstrated by an artificial univariate time-series specification that highlights the main features, and also by a real-life multivariate application to agricultural price data. In the exemplary data set on quarterly European barley prices, strong seasonal variation is obvious and represents a crucial feature in constructing good models for short-run prediction. Following some preliminary statistical testing, we restrict focus to vector autoregressions with deterministic seasonal cycles. We also consider a restricted specification that imposes a common seasonal cycle on all countries. While the restriction is formally rejected by hypothesis tests, it assists in reducing prediction errors. The parametric bootstrap experiments show that this improvement by using an invalid restriction is systematic.

The long and the short of the risk-return trade-off

The relationship between conditional volatility and expected stock market returns, the so-called risk-return trade-off, has been studied at high- and low-frequency. We propose an asset pricing model with generalized disappointment aversion preferences and short- and long-run volatility risks that captures several stylized facts associated with the risk-return trade-off at short and long horizons. Writing the model in Bonomo et al. (2011) at the daily frequency, we aim at reproducing the moments of the variance premium and realized volatility, the long-run predictability of cumulative returns by the past cumulative variance, the short-run predictability of returns by the variance premium, as well as the daily autocorrelation patterns at many lags of the VIX and of the variance premium, and the daily cross-correlations of these two measures with leads and lags of daily returns. By keeping the same calibration as in this previous paper, we ensure that the model is capturing the first and second moments of the equity premium and the risk-free rate, and the predictability of returns by the dividend yield. Overall adding generalized disappointment aversion to the Kreps–Porteus specification improves the fit for both the short-run and the long-run risk-return trade-offs.

Vývoj a projekce vývozu vybraných zemědělských a potravinářských komodit z České republiky

This contribution presents partial results of a statistical analysis of export indicators of selected agricultural and alimentary categories of products from the Czech Republic according to countries in a reference period 1993−2002. The analysis includes short-run prediction based on applied modes of developmental tendencies of assessed phenomena.

Coordination in a changing environment

In this article we consider a model where boundedly rational agents choose both which coordination game to play and what action to take in that game, when their information and mobility are limited and changes over time. We completely characterize both short-run and long-run outcomes. There are multiple types of short-run predictions in which agents may be at different locations, taking different actions. In the long-run, however, all agents are at the same location and take the same action in that game. The long-run prediction is unique and globally efficient most of the time.

Linear and nonlinear causality in the UK housing market: a regional approach

We examine the causal relationship between 12 UK regional house prices. Our data span from 1983:Q1 to 2012:Q4. The causal linkages both for the first differences and the levels are examined via Granger causality. The former allows us to examine short-run predictability while the latter the long-run. We relax the assumption of linearity and examine nonlinear causality both for the levels and the first differences. We find that long-run causality among the regions is mainly linear while in the short-run is nonlinear. London’s effect on the other regions is found to be mainly nonlinear in the short-run.