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Financial Variables (financial + variable)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	91%

Distribution within Business, Economics, Finance and Accounting

General & Introductory Economics	45%
General & Introductory Finance & Investments	13%

Selected Abstracts

The Impact of Macroeconomic and Financial Variables on Market Risk: Evidence from International Equity Returns

EUROPEAN FINANCIAL MANAGEMENT, Issue 4 2002
Dilip K. Patro
Using a GARCH approach, we estimate a time,varying two,factor international asset pricing model for the weekly equity index returns of 16 OECD countries. We find significant time,variation in the exposure (beta) of country equity index returns to the world market index and in the risk,adjusted excess returns (alpha). We then explain these world market betas and alphas using a number of country,specific macroeconomic and financial variables with a panel approach. We find that several variables including imports, exports, inflation, market capitalisation, dividend yields and price,to,book ratios significantly affect a country's exposure to world market risk. Similar conclusions are obtained by using lagged explanatory variables, and thus these variables may be useful as predictors of world market risks. Several variables also significantly impact the risk,adjusted excess returns over this time period. Our results are robust to a number of alternative specifications. We further discuss some economic hypotheses that may explain these relationships. [source]

A Comparison of the Statistical Properties of Financial Variables in the USA, UK and Germany over the Business Cycle

THE MANCHESTER SCHOOL, Issue 4 2000
Elena Andreou
This paper presents business cycle stylized facts for the US, UK and German economies. We examine whether financial variables (interest rates, stock market price indices, dividend yields and monetary aggregates) predict economic activity over the business cycle, and we investigate the nature of any non-linearities in these variables. Leading indicator properties are examined using cross-correlations for both the values of the variables and their volatilities. Our results imply that the most reliable leading indicator across the three countries is the interest rate term structure, although other variables also appear to be useful for specific countries. The volatilities of financial variables may also contain predictive information for production growth as well as production volatility. Non-linearities are uncovered for all financial series, especially in terms of autoregressive conditional heteroscedasticity effects. Strong evidence of mean non-linearity is also found for many financial series and this can be associated with business cycle asymmetries in the mean. This is the case for a number of American and British financial variables, especially interest rates, but the corresponding evidence for Germany is confined largely to the real long-term rate of interest. [source]

Linkages between Trade and Financial Integration and Output Growth in East Asia

ASIAN ECONOMIC JOURNAL, Issue 1 2010
Maria Socorro Gochoco-Bautista
E32; F42; F43 The effects of trade, financial and other variables generally seen as indicative of the degree of economic integration on movements in industrial production growth among countries in East Asia are assessed using the common component of movements in industrial production growth in the ASEAN 5 + 3 countries as a business cycle benchmark for the region. The results show the dominance of trade-related variables, as well as the world price of oil, in driving regional industrial production growth. Financial variables, while important, are not as robust. [source]

Changing Graph Use in Corporate Annual Reports: A Time-Series Analysis

CONTEMPORARY ACCOUNTING RESEARCH, Issue 2 2000
VIVIEN A. BEATTIE
Abstract Graphs in corporate annual reports form part of a powerfully designed annual report package that offers considerable potential for "impression management." The primary purpose of this paper is to determine whether graph use depends on corporate performance. Time-series analysis, not previously used in the financial graphs literature, allows discretionary changes in graph use by companies to be identified and related to changes in individual companies' corporate performance over time. Based on the prior financial graphs and accounting choice literature, we develop two hypotheses that relate changes in graph use to changes in corporate performance. These hypotheses focus on the aggregate and individual company levels. We base our analysis on the corporate annual reports of 137 top UK companies that were in continued existence during the five-year period from 1988 to 1992. At both the aggregate and individual company levels, we find the decision to use key financial variable (KFV) graphs, the primary graphical choice, to be associated positively with corporate performance measures. This finding is consistent with the manipulation hypothesis - that is, that financial graphs in corporate annual reports are used to "manage" favorably the reader's impression of company performance, and hence that there is a reporting bias. [source]

What happens during recessions, crunches and busts?

ECONOMIC POLICY, Issue 60 2009
Stijn Claessens
Summary We provide a comprehensive empirical characterization of the linkages between key macroeconomic and financial variables around business and financial cycles, for 21 OECD countries over the period 1960,2007. In particular, we analyse the implications of 122 recessions, 113 (28) credit contraction (crunch) episodes, 114 (28) episodes of house price declines (busts), 245 (61) episodes of equity price declines (busts), and their various overlaps in these countries, over the sample period. Our results indicate that the interactions between macroeconomic and financial variables can play a major role in determining the severity and duration of a recession. Specifically, we find evidence that recessions associated with credit crunches and house price busts tend to be deeper and longer than other recessions. , Stijn Claessens, M. Ayhan Kose and Marco E. Terrones [source]

The Impact of Macroeconomic and Financial Variables on Market Risk: Evidence from International Equity Returns

An early warning system for detection of financial crisis using financial market volatility

EXPERT SYSTEMS, Issue 2 2006
Kyong Joo Oh
Abstract: This study proposes an early warning system (EWS) for detection of financial crisis with a daily financial condition indicator (DFCI) designed to monitor the financial markets and provide warning signals. The proposed EWS differs from other commonly used EWSs in two aspects: (i) it is based on dynamic daily movements of the financial markets; and (ii) it is established as a pattern classifier, which identifies predefined unstable states in terms of financial market volatility. Indeed it issues warning signals on a daily basis by judging whether the financial market has entered a predefined unstable state or not. The major strength of a DFCI is that it can issue timely warning signals while other conventional EWSs must wait for the next round input of monthly or quarterly information. Construction of a DFCI consists of two steps where machine learning algorithms are expected to play a significant role, i.e. (i) establishing sub-DFCIs on various daily financial variables by an artificial neural network, and (ii) integrating the sub-DFCIs into an integrated DFCI by a genetic algorithm. The DFCI for the Korean financial market is built as an empirical case study. [source]

Chaotic analysis of predictability versus knowledge discovery techniques: case study of the Polish stock market

EXPERT SYSTEMS, Issue 5 2002
Hak Chun
Increasing evidence over the past decade indicates that financial markets exhibit nonlinear dynamics in the form of chaotic behavior. Traditionally, the prediction of stock markets has relied on statistical methods including multivariate statistical methods, autoregressive integrated moving average models and autoregressive conditional heteroskedasticity models. In recent years, neural networks and other knowledge techniques have been applied extensively to the task of predicting financial variables. This paper examines the relationship between chaotic models and learning techniques. In particular, chaotic analysis indicates the upper limits of predictability for a time series. The learning techniques involve neural networks and case,based reasoning. The chaotic models take the form of R/S analysis to measure persistence in a time series, the correlation dimension to encapsulate system complexity, and Lyapunov exponents to indicate predictive horizons. The concepts are illustrated in the context of a major emerging market, namely the Polish stock market. [source]

A comparison of nearest neighbours, discriminant and logit models for auditing decisions

INTELLIGENT SYSTEMS IN ACCOUNTING, FINANCE & MANAGEMENT, Issue 1-2 2007
Chrysovalantis Gaganis
This study investigates the efficiency of k -nearest neighbours (k -NN) in developing models for estimating auditors' opinions, as opposed to models developed with discriminant and logit analyses. The sample consists of 5276 financial statements, out of which 980 received a qualified audit opinion, obtained from 1455 private and public UK companies operating in the manufacturing and trade sectors. We develop two industry-specific models and a general one using data from the period 1998,2001, which are then tested over the period 2002,2003. In each case, two versions of the models are developed. The first includes only financial variables. The second includes both financial and non-financial variables. The results indicate that the inclusion of credit rating in the models results in a considerable increase both in terms of goodness of fit and classification accuracies. The comparison of the methods reveals that the k -NN models can be more efficient, in terms of average classification accuracy, than the discriminant and logit models. Finally, the results are mixed concerning the development of industry-specific models, as opposed to general models. Copyright © 2007 John Wiley & Sons, Ltd. [source]

Modelling fundamentals for forecasting capital flows to emerging markets

INTERNATIONAL JOURNAL OF FINANCE & ECONOMICS, Issue 3 2001
Ashoka Mody
F21; F34 Abstract In this paper, we provide capital flow forecasts to 32 developing countries using a vector error correction framework based on underlying domestic (pull) fundamentals and international (push) factors. In general, pull factors have a heavier weight in determining these capital flows. However, short-term dynamics of capital flows can be significantly influenced by external developments. Simulations under various economic scenarios show that while financial variables (such as the US interest rate and high-yield spread) are important, real US activity may be even more potent in influencing capital flow movements. Copyright © 2001 John Wiley & Sons, Ltd. [source]

The Gilt-Equity Yield Ratio and the Predictability of UK and US Equity Returns

JOURNAL OF BUSINESS FINANCE & ACCOUNTING, Issue 3-4 2000
Richard D.F. Harris
A number of financial variables have been shown to be effective in explaining the time-series of aggregate equity returns in both the UK and the US. These include, inter alia, the equity dividend yield, the spread between the yields on long and short government bonds, and the lagged equity return. Recently, however, the ratio between the long government bond yield and the equity dividend yield , the gilt-equity yield ratio , has emerged as a variable that has considerable explanatory power for UK equity returns. This paper compares the predictive ability of the gilt-equity yield ratio with these other variables for UK and US equity returns, providing evidence on both in-sample and out-of-sample performance. For UK monthly returns, it is shown that while the dividend yield has substantial in-sample explanatory power, this is not matched by out-of sample forecast accuracy. The gilt-equity yield ratio, in contrast, performs well both in-sample and out-of-sample. Although the predictability of US monthly equity returns is much lower than for the UK, a similar result emerges, with the gilt-equity yield ratio dominating the other variables in terms of both in-sample explanatory power and out-of-sample forecast performance. The gilt-equity yield ratio is also shown to have substantial predictive ability for long horizon returns. [source]

Forecasting growth and inflation in an enlarged euro area

JOURNAL OF FORECASTING, Issue 5 2009
Thomas Flavin
Abstract We compare models for forecasting growth and inflation in the enlarged euro area. Forecasts are built from univariate autoregressive and single-equation models. The analysis is undertaken for both individual countries and EU aggregate variables. Aggregate forecasts are constructed by both employing aggregate variables and by aggregating country-specific forecasts. Using financial variables for country-specific forecasts tends to add little to the predictive ability of a simple AR model. However, they do help to predict EU aggregates. Furthermore, forecasts from pooling individual country models usually outperform those of the aggregate itself, particularly for the EU25 grouping. This is particularly interesting from the perspective of the European Central Bank, who require forecasts of economic activity and inflation to formulate appropriate economic policy across the enlarged group. Copyright © 2008 John Wiley & Sons, Ltd. [source]

The performance of non-linear exchange rate models: a forecasting comparison

JOURNAL OF FORECASTING, Issue 7 2002
Gianna Boero
Abstract In recent years there has been a considerable development in modelling non-linearities and asymmetries in economic and financial variables. The aim of the current paper is to compare the forecasting performance of different models for the returns of three of the most traded exchange rates in terms of the US dollar, namely the French franc (FF/$), the German mark (DM/$) and the Japanese yen (Y/$). The relative performance of non-linear models of the SETAR, STAR and GARCH types is contrasted with their linear counterparts. The results show that if attention is restricted to mean square forecast errors, the performance of the models, when distinguishable, tends to favour the linear models. The forecast performance of the models is evaluated also conditional on the regime at the forecast origin and on density forecasts. This analysis produces more evidence of forecasting gains from non-linear models. Copyright © 2002 John Wiley & Sons, Ltd. [source]

Growth dynamics of dairy processing firms in the European Union

AGRICULTURAL ECONOMICS, Issue 3-4 2010
Cornelis Gardebroek
EU dairy processing industry; Dynamic panel data; Firm growth Abstract The structure of the dairy processing industry in the European Union has changed enormously in recent decades. In many countries, the industry is characterized by a few large companies with a big market share accompanied by many small processors that often produce for niche markets. This article investigates which factors relate to growth of dairy processing firms. Using a unique 10-year panel data set and recently developed dynamic panel data estimators, the growth process of dairy processors is investigated for six rather diverse European countries. The data structure and the estimation method allow for dealing with endogeneity issues in an appropriate way. Firm size growth measured in total assets is found to be affected by firm size, firm age, and financial variables. Growth in number of employees is only affected by firm age and lagged labor productivity. Implications for these results are given in the final section of the article. [source]

The Use of Dynamic Financial Analysis to Determine Whether an Optimal Growth Rate Exists for a Property-Liability Insurer

JOURNAL OF RISK AND INSURANCE, Issue 4 2004
Stephen P. D'Arcy
Prior research on the aging phenomenon has demonstrated that new business for property-liability (P-L) insurers generates high loss ratios that gradually decline as a book of business goes through successive renewal cycles. Although the experience on new business is initially unprofitable, the renewal book of business eventually becomes profitable over time. Within this context, insurers need to manage their exposure growth in order to maximize long run profitability. Dynamic financial analysis (DFA), a relatively new tool for P-L insurers, utilizes Monte Carlo simulation to generate the overall financial results for an insurer under a large number of scenarios. This article uses a publicly available DFA model,along with the estimated market value of an insurer, based on 1990,2001 data for stock P-L insurers and underlying financial variables,to determine optimal growth rates of a P-L insurer based on mean,variance analysis, stochastic dominance, and constraints on leverage. [source]

RECONSIDERING THE INVESTMENT,PROFIT NEXUS IN FINANCE-LED ECONOMIES: AN ARDL-BASED APPROACH

METROECONOMICA, Issue 3 2008
Till Van TreeckArticle first published online: 28 APR 200
ABSTRACT A Post-Keynesian growth model is developed, in which financial variables are explicitly taken into account. Variants of an investment function are estimated econometrically, applying the ARDL (auto-regressive distributed lag)-based approach proposed by Pesaran et al. (Journal of Applied Econometrics, 16 (3), pp. 289,326). The econometric results are discussed with respect to a remarkable phenomenon that can be observed for some important OECD countries since the early 1980s: accumulation has generally been declining while profit shares and rates have shown a tendency to rise. We concentrate on one potential explanation of this phenomenon, which is particularly relevant for the USA and relies on a high propensity to consume out of capital income. [source]

CHAOTIC DYNAMICS OF FINANCING INVESTMENT

METROECONOMICA, Issue 1 2005
Soumya Datta
ABSTRACT The paper introduces the financial sector in a standard multiplier-accelerator framework by incorporating financial variables in the investment function. The resultant equation is similar in form to that of a logistic map, and hence behaves unpredictably under certain values of the parameters. Since monetary authorities have a large influence on many of these parameters, monetary policies are effective in both controlling investment and preventing or postponing a financial crisis. The monetary authorities, however, are also keen to play an additional role of keeping the system predictable. Under certain conditions, there could be a conflict between these two objectives,of preventing a financial crisis and keeping the system predictable. [source]

On the influence of oil prices on economic activity and other macroeconomic and financial variables,

OPEC ENERGY REVIEW, Issue 4 2008
François Lescaroux
The aim of this paper is to investigate the links between oil prices and various macroeconomic and financial variables for a large set of countries, including both oil-importing and oil-exporting countries. Both short-run and long-run interactions are analysed through the implementation of Granger-causality tests, evaluation of cross correlations between the cyclical components of the series in order to identify lead/lag relationships and cointegration analysis. Our results highlight the existence of various relationships between oil prices and macroeconomic variables and, especially, an important link between oil and share prices on the short run. Turning to the long run, numerous long-term relationships are detected, the Granger-causality generally running from oil prices to the other variables. An important conclusion is relating to the key role played by the oil market on stock markets. [source]

Economic determinants of default risks and their impacts on credit derivative pricing,

THE JOURNAL OF FUTURES MARKETS, Issue 11 2010
Szu-Lang Liao
This study constructs a credit derivative pricing model using economic fundamentals to evaluate CDX indices and quantify the relationship between credit conditions and the economic environment. Instead of selecting specific economic variables, numerous economic and financial variables have been condensed into a few explanatory factors to summarize the noisy economic system. The impacts on default intensity processes are then examined based on no-arbitrage pricing constraints. The approximated results show that economic factors indicated credit problems even before the recent subprime mortgage crisis, and economic fundamentals strongly influenced credit conditions. Testing of out-of-sample data shows that credit evolution can be identified by dynamic explanatory factors. Consequently, the factor-based pricing model can either facilitate the evaluation of default probabilities or manage default risks more effectively by quantifying the relationship between economic environment and credit conditions. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark [source]

Option pricing under Markov-switching GARCH processes

THE JOURNAL OF FUTURES MARKETS, Issue 5 2010
Chao-Chun Chen
This study proposes an N -state Markov-switching general autoregressive conditionally heteroskedastic (MS-GARCH) option model and develops a new lattice algorithm to price derivatives under this framework. The MS-GARCH option model allows volatility dynamics switching between different GARCH processes with a hidden Markov chain, thus exhibiting high flexibility in capturing the dynamics of financial variables. To measure the pricing performance of the MS-GARCH lattice algorithm, we investigate the convergence of European option prices produced on the new lattice to their true values as conducted by the simulation. These results are very satisfactory. The empirical evidence also suggests that the MS-GARCH model performs well in fitting the data in-sample and one-week-ahead out-of-sample prediction. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:444,464, 2010 [source]

A Comparison of the Statistical Properties of Financial Variables in the USA, UK and Germany over the Business Cycle

Understanding bilateral FDI flows in developing Asia

ASIAN-PACIFIC ECONOMIC LITERATURE, Issue 2 2009
Rabin Hattari
Unlike trade flows, there has been little to no detailed examination of foreign direct investment (FDI) flows between Asian economies. This paper uses bilateral FDI flows data to investigate trends in intra-Asian FDI flows over the period 1990,2005. It employs an augmented gravity model to identify the main determinants of intra-Asian FDI flows. Possible drivers of FDI flows, including transactional and informational distance (proxied by distance), real sector variables, financial variables and quality of institutions are examined. [source]