Carry-Based Expected Returns for Strategic Asset Allocation

2019 ◽  
Keyword(s):  
Risk Factors ◽  
Asset Allocation ◽  
Expected Returns ◽  
Present Value ◽  
Expected Return ◽  
Strategic Asset Allocation ◽  
Present Value Model ◽  
Geographic Regions ◽  
Asset Classes ◽  
Value Model

In this article, the author investigates expected return forecasting methodologies and their application in an asset allocation context. Although present value model–related methods are popular in practice, little is known about their performance when used for asset allocation. An intuitive and traceable carry-based method is developed by the author and tested and benchmarked against competing alternatives. The results are evaluated from different perspectives, and the obtained returns are regressed on well-known risk factors. The proposed methodology outperformed other return forecasting variants on various metrics and generated significant alphas regardless of the weight determination approach used. The methodology can be extended to further asset classes and geographic regions and provides a framework for allocating assets strategically.

CONSUMPTION AND EXPECTED ASSET RETURNS: AN UNOBSERVED-COMPONENT APPROACH

2014 ◽  
Vol 19 (5) ◽  
pp. 1023-1044
Author(s):  
Narayan K. Kishor ◽  
Swati Kumari
Keyword(s):  
Growth Rate ◽  
Asset Returns ◽  
Expected Returns ◽  
Present Value ◽  
Consumption Growth ◽  
Present Value Model ◽  
Unobserved Component ◽  
Component Approach ◽  
The One ◽  
Value Model

This paper proposes an unobserved-component approach to estimate expected returns on household assets and expected growth rates of excess consumption (consumption in excess of labor income) within a present-value model of consumption. The present-value model of consumption implies that the excess-consumption–assets ratio can be expressed as a function of the present discounted value of expected excess-consumption growth rate and expected asset returns. Because expected returns and expected excess-consumption growth rate are unobserved variables, we use an unobserved-component approach to extract them from the observed history of realized returns and excess-consumption growth rate. Our results suggest that both filtered returns and filtered excess-consumption growth rate are significant and better predictors of realized returns and realized excess-consumption growth rate than the one obtained by the lagged excess-consumption–assets ratio.

scholarly journals Present value model between prices and dividends with constant and time-varying expected returns: enterprise-level Brazilian stock market evidence from non-stationary panels

2012 ◽  
Vol 9 (4) ◽  
pp. 51-86
Author(s):  
Edward Bernard Bastiaan de Rivera y Rivera ◽  
Diógenes Manoel Leiva Martin ◽  
Emerson Fernandes Marçal ◽  
Leonardo Fernando Cruz Basso
Keyword(s):  
Stock Market ◽  
Expected Returns ◽  
Time Varying ◽  
Present Value ◽  
Present Value Model ◽  
Enterprise Level ◽  
Value Model

A look into German housing markets: A bubble call?

2018 ◽  
Vol 21 (4) ◽  
pp. 289-301
Author(s):  
Jan R. Kim ◽  
Gieyoung Lim
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Housing Markets ◽  
Present Value ◽  
Present Value Model ◽  
Price Bubbles ◽  
Steep Rise ◽  
Value Model ◽  
German Housing Market

The steep rise in German house prices in recent years raises the question of whether a speculative bubble has already emerged. Using a modified present-value model, we estimate the size of speculative house price bubbles in the German housing market. We do not find evidence for positive bubble accumulation in recent years, and interpret the current bullish run as reflecting the correction of house prices that have been undervalued for more than 10 years. With house prices close to their fair values as of 2018:Q1, our answer to the question is, ‘Not yet, but it is likely soon’.

scholarly journals Break Risk

2020 ◽  
Author(s):  
Simon C Smith ◽  
Allan Timmermann
Keyword(s):  
Stock Returns ◽  
Cross Section ◽  
Prediction Models ◽  
Return Predictability ◽  
Present Value ◽  
New Approach ◽  
Present Value Model ◽  
Out Of Sample ◽  
Rate Processes ◽  
Value Model

Abstract We develop a new approach to modeling and predicting stock returns in the presence of breaks that simultaneously affect a large cross-section of stocks. Exploiting information in the cross-section enables us to detect breaks in return prediction models with little delay and to generate out-of-sample return forecasts that are significantly more accurate than those from existing approaches. To identify the economic sources of breaks, we explore the asset pricing restrictions implied by a present value model which links breaks in return predictability to breaks in the cash flow growth and discount rate processes.

Modeling Stock Prices without Knowing How to Induce Stationarity

1996 ◽  
Vol 12 (4) ◽  
pp. 739-740
Author(s):  
David N. Dejong ◽  
Charles H. Whiteman
Keyword(s):  
Stock Prices ◽  
Present Value ◽  
Posterior Odds ◽  
Knowing How ◽  
Present Value Model ◽  
Two Factors ◽  
Value Model

In “Modeling Stock Prices without Knowing How to Induce Stationarity” (1994, Econometric Theory 10, 701–719), we used posterior-odds calculations to evaluate restrictions imposed by a present-value model of stock prices across the equations of a VAR representation of stock prices and dividends. The results we reported are tainted by the omission of two factors: the Jacobians induced by the mapping of our priors over VAR parameters β into the restricted sample spaces relevant under hypotheses H2-H4 (hence, tainting our calculations of p(Hi|y,X) in (22) for i = 2–4), and an integrating constant needed in calculating the unrestricted probability p(Hi|y,X) in (22). Table 1 reports our revised calculations, which differ substantively from those reported previously.

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