Nowcasting The Business Cycle

Author: James Picerno
Editor: CreateSpace
ISBN: 9781492923855
File Size: 71,93 MB
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Nowcasting The Business Cycle presents a practical guide for analyzing recession risk—the primary risk factor that drives success and failure in business, finance, wealth management, and so much more. Whether you're an individual investor watching over your retirement account; the owner of a small business; a manager running a billion-dollar pension fund; or a CEO in charge of a global corporation, a large portion of triumph and defeat is closely linked with the broad swings in the economy. The business cycle, in other words, is the mother of all known (and recurring) risk factors. Accordingly, developing a process for assessing the likelihood of this threat is critical. Everyone needs a reliable, timely warning system that's relatively uncomplicated and transparent. Drawing on economic theory and macro's historical record, Nowcasting The Business Cycle outlines a simple but effective model for identifying those times when a new recession has probably started. This isn't forecasting, which is a fool's errand when it comes to the economy. Instead, the goal is recognizing when a majority of key indicators have already reached a tipping point. That may sound like a trivial advantage, but most people—including many economists—don't fully recognize when a recession has begun until the deterioration is obvious. By that point, the opportunity has probably passed for taking defensive measures in your investment portfolio, your business, or your career. The real challenge is less about predicting and more about developing solid intuition for recognizing when the macro threat is exceptionally high. Even a small degree of progress here can provide a considerable boost to your strategic insight. If we can learn the techniques for recognizing a cyclical downturn's presence relatively early—soon after it's begun, or just as it's starting—we'll have an advantage that tends to elude most folks. Nowcasting The Business Cycle provides a roadmap for ensuring that you won't be caught by surprise when the next recession strikes. That's a crucial advantage for one powerful reason: There's always another recession coming.

Nowcasting Business Cycles

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ISBN:
File Size: 70,54 MB
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Modeling Of Economic And Financial Conditions For Nowcasting And Forecasting Recessions

Author: Cem Çakmaklı
Editor:
ISBN:
File Size: 71,50 MB
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This paper puts forward a unified framework for the joint estimation of the indexes that can broadly capture economic and financial conditions together with their cyclical regimes of recession and expansion. We do this by utilizing a dynamic factor model together with Markov regime switching dynamics of model parameters that specifically exploit the temporal link between the cyclical behavior of economic and financial factors. This is achieved by constructing the cycle in the financial factor using the cycle in the economic factor together with phase shifts. The resulting framework allows the financial cycle to potentially lead/lag the business cycle in a systematic manner and exploits the information in economic and financial variables for estimation of both economic and financial conditions as well as their cyclical behavior in an efficient way. We examine the potential of the model using a mixed frequency and mixed time span ragged-edge dataset for Turkey. Comparison of our framework with more conventional polar cases imposing a single common cyclical dynamics as well as independent cyclical dynamics for economic and financial conditions reveal that the proposedspecification provides precise estimates of economic and financial conditions and it delivers quite accurate probabilities of recessions that match with stylized facts. We further conduct a recursive real-time exercise of nowcasting and forecasting business cycle turning points. The results show convincing evidence of superior predictive power of our specification by signaling oncoming recessions (expansions) as early as 3.5 (3.4) months ahead of the actual realization.

Nowcasting Business Cycle Turning Points With Stock Networks And Machine Learning

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ISBN: 9789289944113
File Size: 64,71 MB
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We propose a granular framework that makes use of advanced statistical methods to approximate developments in economy-wide expected corporate earnings. In particular, we evaluate the dynamic network structure of stock returns in the United States as a proxy for the transmission of shocks through the economy and identify node positions (firms) whose connectedness provides a signal for economic growth. The nowcasting exercise, with both the in-sample and the out-of-sample consistent feature selection, highlights which firms are contemporaneously exposed to aggregate downturns and provides a more complete narrative than is usually provided by more aggregate data. The two-state model for predicting periods of negative growth can remarkably well predict future states by using information derived from the node-positions of manufacturing, transportation and financial (particularly insurance) firms. The three-states model, which identifies high, low and negative growth, successfully predicts economic regimes by making use of information from the financial, insurance, and retail sectors.

Nowcasting Business Cycles Using Toll Data

Author: Nikos Askitas
Editor:
ISBN:
File Size: 45,12 MB
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Nowcasting has been a challenge in the recent economic crisis. We introduce the Toll Index, a new monthly indicator for business cycle forecasting and demonstrate its relevance using German data. The index measures the monthly transportation activity performed by heavy transport vehicles across the country and has highly desirable availability properties (insignificant revisions, short publication lags) as a result of the innovative technology underlying its data collection. It is coincident with production activity due to the prevalence of just-in-time delivery. The Toll Index is a good early indicator of production as measured for instance by the German Production Index, provided by the German Statistical Office, which is a well-known leading indicator of the Gross National Product. The proposed new index is an excellent example of technological, innovation-driven economic telemetry, which we suggest should be established more around the world.

Nowcasting Business Cycle Dating And The Interpretation Of New Interpretation Of New Information When Real Time Data Are Available

Author: Kevin Lee
Editor:
ISBN:
File Size: 78,92 MB
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How External Factors Affect Domestic Economy

Author: Mr. Serhat Solmaz
Editor: International Monetary Fund
ISBN: 1513571834
File Size: 70,54 MB
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External headwinds, together with domestic vulnerabilities, have loomed over the prospects of emerging markets in recent years. We propose an empirical toolbox to quantify the impact of external macro-financial shocks on domestic economies in parsimonious way. Our model is a Bayesian VAR consisting of two blocks representing home and foreign factors, which is particularly useful for small open economies. By exploiting the mixed-frequency nature of the model, we show how the toolbox can be used for “nowcasting” the output growth. The conditional forecast results illustrate that regular updates of external information, as well as domestic leading indicators, would significantly enhance the accuracy of forecasts. Moreover, the analysis of variance decompositions shows that external shocks are important drivers of the domestic business cycle.

Nowcasting Of The Gross Regional Product

Author: Anna Norin
Editor:
ISBN:
File Size: 64,97 MB
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Business cycles are usually defined at a national level. The implicit assumption being that it affects all regions similarly. This is combined with a lack of timely information on regional economic development as annual values of the gross regional product (GRP) are often published with up to two years lag. The present paper evaluates a method of obtaining values of the GRP as soon as monthly and quarterly business cycle indicators become available. Building on earlier work on using bridge equations to obtaining quarterly values of GDP growth, a method is proposed were annual GRP growth is estimated using a large number of business cycle indicators. The procedure is applied to data for the Northern regions of Sweden. With the present method it is possible to continuously refine GRP growth values throughout the year. By utilizing the information content in available business cycle indicators, a nowcast of the GRP is obtained as opposed to a pure forecast based solely on past information. Nowcasts will then provide valuable information on how current highs or lows are affecting different regions.

Nowcasting Business Cycle Dating And The Interpretation Of New Information When Real Time Data Are Available

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ISBN: 9780734040060
File Size: 30,84 MB
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A canonical model is described which reflects the real time informational context of decision-making. Comparisons are drawn with 'conventional' models that incorrectly omit market-informed insights on future macroeconomic conditions and inappropriately incorporate information that was not available at the time. It is argued that conventional models are misspecified and misinterpret news. However, neither diagnostic tests applied to the conventional models nor typical impulse response analysis will be able to expose these deficiencies clearly. This is demonstrated through an analysis of quarterly US data 1968q4-2006q1. However, estimated real time models considerably improve out-of-sample forecasting performance, provide more accurate 'nowcasts' of the current state of the macroeconomy and provide more timely indicators of the business cycle. The point is illustrated through an analysis of the US recessions of 1990q3--1991q2 and 2001q--2001q4.

Empirical Macroeconomics And Statistical Uncertainty

Author: Mateusz Pipień
Editor: Routledge
ISBN: 1000170969
File Size: 40,95 MB
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This book addresses one of the most important research activities in empirical macroeconomics. It provides a course of advanced but intuitive methods and tools enabling the spatial and temporal disaggregation of basic macroeconomic variables and the assessment of the statistical uncertainty of the outcomes of disaggregation. The empirical analysis focuses mainly on GDP and its growth in the context of Poland. However, all of the methods discussed can be easily applied to other countries. The approach used in the book views spatial and temporal disaggregation as a special case of the estimation of missing observations (a topic on missing data analysis). The book presents an econometric course of models of Seemingly Unrelated Regression Equations (SURE). The main advantage of using the SURE specification is to tackle the presented research problem so that it allows for the heterogeneity of the parameters describing relations between macroeconomic indicators. The book contains model specification, as well as descriptions of stochastic assumptions and resulting procedures of estimation and testing. The method also addresses uncertainty in the estimates produced. All of the necessary tests and assumptions are presented in detail. The results are designed to serve as a source of invaluable information making regional analyses more convenient and – more importantly – comparable. It will create a solid basis for making conclusions and recommendations concerning regional economic policy in Poland, particularly regarding the assessment of the economic situation. This is essential reading for academics, researchers, and economists with regional analysis as their field of expertise, as well as central bankers and policymakers.

Big Data On Vessel Traffic Nowcasting Trade Flows In Real Time

Author: Mr.Serkan Arslanalp
Editor: International Monetary Fund
ISBN: 1513523228
File Size: 49,60 MB
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Vessel traffic data based on the Automatic Identification System (AIS) is a big data source for nowcasting trade activity in real time. Using Malta as a benchmark, we develop indicators of trade and maritime activity based on AIS-based port calls. We test the quality of these indicators by comparing them with official statistics on trade and maritime statistics. If the challenges associated with port call data are overcome through appropriate filtering techniques, we show that these emerging “big data” on vessel traffic could allow statistical agencies to complement existing data sources on trade and introduce new statistics that are more timely (real time), offering an innovative way to measure trade activity. That, in turn, could facilitate faster detection of turning points in economic activity. The approach could be extended to create a real-time worldwide indicator of global trade activity.

Advances In Nowcasting Economic Activity

Author: Juan Antolin-Diaz
Editor:
ISBN:
File Size: 32,90 MB
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A key question for households, firms, and policy makers is: how is the economy doing now? We develop a Bayesian dynamic factor model and compute daily estimates of US GDP growth. Our framework gives prominence to features of modern business cycles absent in linear Gaussian models, including secular movements in growth, time-varying uncertainty, and fat tails. We also incorporate newly available high-frequency data on consumer behavior. The model beats benchmark econometric models and survey expectations at predicting GDP growth over two decades, and advances our understanding of macroeconomic data during the COVID-19 pandemic.

Dynamic Factor Models

Author:
Editor: Emerald Group Publishing
ISBN: 1785603523
File Size: 66,26 MB
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This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications.

Factor Investing

Author: Emmanuel Jurczenko
Editor: Elsevier
ISBN: 0081019645
File Size: 43,18 MB
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This new edited volume consists of a collection of original articles written by leading industry experts in the area of factor investing. The chapters introduce readers to some of the latest research developments in the area of equity and alternative investment strategies.Each chapter deals with new methods for constructing and harvesting traditional and alternative risk premia, building strategic and tactical multifactor portfolios, and assessing related systematic investment performances. This volume will be of help to portfolio managers, asset owners and consultants, as well as academics and students who want to improve their knowledge and understanding of systematic risk factor investing. A practical scope An extensive coverage and up-to-date researcch contributions Covers the topic of factor investing strategies which are increasingly popular amongst practitioners

Journal Of Business Cycle Measurement And Analysis

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File Size: 57,16 MB
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Engineering Investment Process

Author: Florian Ielpo
Editor: Elsevier
ISBN: 0081011482
File Size: 21,22 MB
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Engineering Investment Process: Making Value Creation Repeatable explores the quantitative steps of a financial investment process. The authors study how these steps are articulated in order to make any value creation, whatever the asset class, consistent and robust. The discussion includes factors, portfolio allocation, statistical and economic backtesting, but also the influence of negative rates, dynamical trading, state-space models, stylized facts, liquidity issues, or data biases. Besides the quantitative concepts detailed here, the reader will find useful references to other works to develop an in-depth understanding of an investment process. Blends academic research with practical experience from quants, fund managers, and economists Puts financial mathematics and econometrics in their rightful place Presents useful information that will increase the reader's understanding of markets Clearly provides both the global framework, the investment process, and the useful econometric and financial tools that help in its construction Includes efficient tools taken from up-to-date econometric and financial techniques

Business Cycles And Structural Change In South Africa

Author: Willem H. Boshoff
Editor: Springer Nature
ISBN: 3030357546
File Size: 15,60 MB
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This book investigates the South African business cycle and its links to structural change in the economy. Against the backdrop of the democratic transition in 1994 and the global financial crisis, the authors study how business cycles in South Africa have changed and how cycles are related to key developments in the financial markets, international trade and business sentiment in the country. By focusing on peaks and troughs in economic activity – so-called ‘turning-point cycles’ – the book links up with the common approach of international policymakers to studying fluctuations in economic activity. The authors also introduce new approaches to measuring phases of the business cycle (to understand slow recoveries after the global crisis), provide comprehensive descriptions to complement quantitative analyses, and utilize new data sources that allow the measurement of economic activity over longer periods. As such, the book provides the first integrated overview of business cycles in an emerging market, providing academics and policymakers with a better understanding of the measurement challenges and drivers of the cycle.

A Three Frequency Dynamic Factor Model For Nowcasting Canadian Provincial Gdp Growth

Author: Tony Chernis
Editor:
ISBN:
File Size: 60,14 MB
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"This paper estimates a three-frequency dynamic factor model for nowcasting Canadian provincial gross domestic product (GDP). Canadian provincial GDP is released by Statistics Canada on an annual basis only, with a significant lag (11 months). This necessitates a mixed-frequency approach that can process timely monthly data, the quarterly national accounts and the annual target variable. The model is estimated on a wide set of provincial, national and international data. We assess the extent to which these indicators can be used to nowcast annual provincial GDP in a pseudo real-time setting and construct indicators of unobserved monthly GDP for each province that can be used to assess the state of regional economies. The monthly activity indicators fit the data well in-sample, are able to track business-cycle turning points across the provinces, and showcase the significant regional heterogeneity that characterizes a large diverse country like Canada. They also provide more timely indications of business-cycle turning points and are able to pick up shorter periods of economic contraction that would not be observed in the annual average. In a pseudo real-time exercise, we find the model outperforms simple benchmarks and is competitive with more sophisticated mixed-frequency approaches such as MIDAS models"--Abstract, p. ii.

Applied Economic Forecasting Using Time Series Methods

Author: Eric Ghysels
Editor: Oxford University Press
ISBN: 0190622024
File Size: 40,27 MB
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Economic forecasting is a key ingredient of decision making both in the public and in the private sector. Because economic outcomes are the result of a vast, complex, dynamic and stochastic system, forecasting is very difficult and forecast errors are unavoidable. Because forecast precision and reliability can be enhanced by the use of proper econometric models and methods, this innovative book provides an overview of both theory and applications. Undergraduate and graduate students learning basic and advanced forecasting techniques will be able to build from strong foundations, and researchers in public and private institutions will have access to the most recent tools and insights. Readers will gain from the frequent examples that enhance understanding of how to apply techniques, first by using stylized settings and then by real data applications--focusing on macroeconomic and financial topics. This is first and foremost a book aimed at applying time series methods to solve real-world forecasting problems. Applied Economic Forecasting using Time Series Methods starts with a brief review of basic regression analysis with a focus on specific regression topics relevant for forecasting, such as model specification errors, dynamic models and their predictive properties as well as forecast evaluation and combination. Several chapters cover univariate time series models, vector autoregressive models, cointegration and error correction models, and Bayesian methods for estimating vector autoregressive models. A collection of special topics chapters study Threshold and Smooth Transition Autoregressive (TAR and STAR) models, Markov switching regime models, state space models and the Kalman filter, mixed frequency data models, nowcasting, forecasting using large datasets and, finally, volatility models. There are plenty of practical applications in the book and both EViews and R code are available online at authors' website.

Ecuador

Author: International Monetary Fund. Western Hemisphere Dept.
Editor: International Monetary Fund
ISBN: 1498303676
File Size: 24,69 MB
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This Selected Issues paper estimates Ecuador’s potential growth in the range of 1 3/4 to 3 percent. The lower estimate corresponds to an extrapolation of recent trends while the higher estimate could be achievable through the implementation of a reform agenda that addresses fiscal and competitiveness challenges of Ecuador. The paper also develops models to nowcast and forecast GDP to improve the accuracy of growth projections. The oil sector remains an important driver of economic activity; however, it is not as important as it once was. A simple growth accounting exercise is used to decompose Ecuador’s growth between production factors accumulation; capital and labor, and total factor productivity. The study shows that low total factor productivity is the reason behind Ecuador’s recent economic decline and has been a negative contributor to long-term growth. The paper also explores different vector autoregression models to identify the best one to forecast real GDP in Ecuador.