Business Commons^™

Scaled Pca: A New Approach To Dimension Reduction, Dashan Huang, Fuwei Jiang, Kunpeng Li, Guoshi Tong, Guofu Zhou

Research Collection Lee Kong Chian School Of Business

This paper proposes a novel supervised learning technique for forecasting: scaled principal component analysis (sPCA). The sPCA improves the traditional principal component analysis (PCA) by scaling each predictor with its predictive slope on the target to be forecasted. Unlike the PCA that maximizes the common variation of the predictors, the sPCA assigns more weight to those predictors with stronger forecasting power. In a general factor framework, we show that, under some appropriate conditions on data, the sPCA forecast beats the PCA forecast, and when these conditions break down, extensive simulations indicate that the sPCA still has a large chance to …

Price Optimization For Revenue Maximization At Scale, Nikhil Gupta, Massimiliano Moro, Kailey A. Ayala, Bivin Sadler

SMU Data Science Review

This study presents a novel approach to price optimization in order to maximize revenue for the distribution market of non-perishable products. Data analysis techniques such as association mining, statistical modeling, machine learning, and an automated machine learning platform are used to forecast the demand for products considering the impact of pricing. The techniques used allow for accurate modeling of the customer’s buying patterns including cross effects such as cannibalization and the halo effect. This study uses data from 2013 to 2019 for Super Premium Whiskey from a large distributor of alcoholic beverages. The expected demand and the ideal pricing strategy …

An Evaluation Of The Forecast Performance Of Dsge And Var Models: The Case Of A Developing Country, Shahzad Ahmad, Adnan Haider

Business Review

This paper estimates a DSGE model and three versions of VAR models (VARX, BVARX and BVAR) to analyze forecasting performance of these models in context of Pakistan. VAR models and a medium-scale DSGE model are estimated using quarterly data (1980Q4-2017Q2). Expanding window recursive out-of-sample forecasts for GDP growth, call money rate, CPI inflation and percent change in exchange rate are generated and compared over the period 2009Q1-2017Q2. Forecasting performance is analyzed by the comparison of bias and root mean squared errors (RMSE). Analysis of forecasting performance over 1-8 quarters forecast horizon reveals that BVAR model provides relatively better forecast in …

Economic Forecasting With Many Predictors, Fanning Meng

Doctoral Dissertations

The dissertation is focused on the analysis of economic forecasting with a large number of predictors.

The first chapter develops a novel forecasting method that minimizes the effects of weak predictors and estimation errors on the accuracy of equity premium forecasts. The proposed method is based on an averaging scheme applied to quantiles conditional on predictors selected by LASSO. The resulting forecasts outperform the historical average, and other existing models, by statistically and economically meaningful margins.

In the second chapter, we find that incorporating distributional and high-frequency information into a forecasting model can produce substantial accuracy gains. Distributional information is …

Does Beating Cash Flow Benchmarks Reduce The Cost Of Debt?, Mauricio A. Melgarejo

Mauricio Melgarejo

This paper examines whether beating previous year cash flow values and analysts' cash flow forecasts impact the firms' cost of debt. Creditors are expected to be more concerned about firm solvency than firm profitability. Accordingly, if lenders have any reference point it may be related to cash flow numbers. This study finds that firms that beat analysts' cash flow forecasts have smaller initial bond yield spreads in the next period and a decrease in their initial bond yield spreads between consecutive periods. This effect is more pronounced at short maturities and for observations with less informative earnings. Firms with lower …

Macroconstants Of Development: A New Benchmark For The Strategic Development Of Advanced Countries And Firms, Andrey Bystrov, Vyacheslav Yusim, Tamilla Curtis

Dr. Tamilla Curtis

This research proposed a new indicator of countries’ development called “macroconstants of development”. The literature review indicates that the concept of "macroconstants of development" is not used at the moment in neither the theory nor the practice of industrial policy. Research of longitudinal data of total GDP, GDP per capita and their derivatives for most countries of the world was conducted. An analysis of statistical information has been done by employing econometric analyses.

Based on the analysis of the statistical data, which characterizes the development of large, technologically advanced countries in ordinary conditions, it was identified that the average acceleration …

Macroconstants Of Development: A New Benchmark For The Strategic Development Of Advanced Countries And Firms, Andrey V. Bystrov, Vyacheslav N. Yusim, Tamilla Curtis

Publications

This research proposed a new indicator of countries’ development called “macroconstants of development”. The literature review indicates that the concept of "macroconstants of development" is not used at the moment in neither the theory nor the practice of industrial policy. Research of longitudinal data of total GDP, GDP per capita and their derivatives for most countries of the world was conducted. An analysis of statistical information has been done by employing econometric analyses.

Based on the analysis of the statistical data, which characterizes the development of large, technologically advanced countries in ordinary conditions, it was identified that the average acceleration …

Does Beating Cash Flow Benchmarks Reduce The Cost Of Debt?, Mauricio A. Melgarejo

Scholarship and Professional Work - Business

This paper examines whether beating previous year cash flow values and analysts' cash flow forecasts impact the firms' cost of debt. Creditors are expected to be more concerned about firm solvency than firm profitability. Accordingly, if lenders have any reference point it may be related to cash flow numbers. This study finds that firms that beat analysts' cash flow forecasts have smaller initial bond yield spreads in the next period and a decrease in their initial bond yield spreads between consecutive periods. This effect is more pronounced at short maturities and for observations with less informative earnings. Firms with lower …

Data Science In Supply Chain Management: Data-Related Influences On Demand Planning, Yao Jin

Graduate Theses and Dissertations

Data-driven decisions have become an important aspect of supply chain management. Demand planners are tasked with analyzing volumes of data that are being collected at a torrential pace from myriad sources in order to translate them into actionable business intelligence. In particular, demand volatilities and planning are vital for effective and efficient decisions. Yet, the accuracy of these metrics is dependent on the proper specification and parameterization of models and measurements. Thus, demand planners need to step away from a "black box" approach to supply chain data science. Utilizing paired weekly point-of-sale (POS) and order data collected at retail distribution …

[Introduction To] Service Parts Management: Demand Forecasting And Inventory Control, Nezih Altay, Lewis A. Litteral

Bookshelf

Service Parts Management provides the reader with an overview and a detailed treatment of the current state of the research available on the forecasting and inventory management of items with intermittent demand. It is a comprehensive review of service parts management and provides a starting point for researchers, postgraduate students, and anyone interested in forecasting or managing inventory.

Forecasting With A Real-Time Data Set For Macroeconomists, Tom Stark, Dean D. Croushore

Economics Faculty Publications

This paper discusses how forecasts are affected by the use of real-time data rather than latest-available data. The key issue is this: in the literature on developing forecasting models, new models are put together based on the results they yield using the data set available to the model’s developer. But those are not the data that were available to a forecaster in real time.

How much difference does the vintage of the data make for such forecasts? We explore this issue with a variety of exercises designed to answer this question. In particular, we find that the use of real-time …

Modeling Corporate Bond Default Risk: A Multiple Time Series Approach, Wai-Sum Chan

Journal of Actuarial Practice (1993-2006)

A multiple time series approach is used to forecast the short-term u.s. corporate bond default level. These time series have two auxiliary economic variables: U.S. price inflation and U.S. GNP growth rate. Actual U.S. data from the turn of the century to the present are used to estimate the parameters of multivariate time series model. Diagnostic checks are performed to examine adequacy of the model. The model's forecast for the aggregate U.S. bond default level in 2000-2001 are 0.42% and 0.56%, respectively, while the forecast for the speculative-grade default rate in 2000 is 3.6%, which is more pessimistic than some …

A Bayesian Technique For Refining The Uncertainty In Global Energy Model Forecasts, F. Ted Tschang, Hadi Dowlatabadi

Research Collection Lee Kong Chian School Of Business

Global energy models have a large degree of uncertainty associated with them. This consists of uncertainty in the model structure as well as uncertainty in the exogenous input parameters. This paper combines Monte Carlo methods with Bayesian updating techniques to provide a method for refining the uncertainty in the Edmonds-Reilly global energy model. The Bayesian updating technique uses likelihood-based windows constructed from actual observations of the output variables to filter out the model simulations that do not conform with the observed output. The windows are based on outputs of energy consumption and carbon emissions. Two alternative model structures are examined: …