Density Forecast of Financial Returns Using Decomposition and Maximum Entropy

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Tae-Hwy Lee ◽  
He Wang ◽  
Zhou Xi ◽  
Ru Zhang
Keyword(s):  
Stock Returns ◽  
Maximum Entropy ◽  
Estimation Error ◽  
Financial Returns ◽  
Multiplicative Decomposition ◽  
Financial Return ◽  
Sample Mean ◽  
Density Forecast ◽  
Decomposition Model ◽  
Moment Constraint

Abstract We consider a multiplicative decomposition of the financial returns to improve the density forecasts of financial returns. The multiplicative decomposition is based on the identity that financial return is the product of its absolute value and its sign. Advantages of modeling the two components are discussed. To reduce the effect of the estimation error due to the multiplicative decomposition in estimation of the density forecast model, we impose a moment constraint that the conditional mean forecast is set to match with the sample mean. Imposing such a moment constraint operates a shrinkage and tilts the density forecast of the decomposition model to produce the improved maximum entropy density forecast. An empirical application to forecasting density of the daily stock returns demonstrates the benefits of using the decomposition and imposing the moment constraint to obtain the improved density forecast. We evaluate the density forecast by comparing the logarithmic score (LS), the quantile score (QS), and the continuous ranked probability score (CRPS). We contribute to the literature on the density forecast and the decomposition models by showing that the density forecast of the decomposition model can be improved by imposing a sensible constraint in the maximum entropy framework.

A TEST OF THE GARCH(1, 1) SPECIFICATION FOR DAILY STOCK RETURNS

2010 ◽  
Vol 14 (S1) ◽  
pp. 137-144 ◽  
Author(s):  
Richard A. Ashley ◽  
Douglas M. Patterson
Keyword(s):  
Stock Returns ◽  
Model Evaluation ◽  
Stock Index ◽  
Serial Dependence ◽  
Financial Returns ◽  
New Model ◽  
Daily Stock Returns ◽  
Daily Returns

Daily financial returns (and daily stock returns, in particular) are commonly modeled as GARCH(1, 1) processes. Here we test this specification using new model evaluation technology developed by Ashley and Patterson that examines the ability of the estimated model to reproduce features of particular interest: various aspects of nonlinear serial dependence, in the present instance. Using daily returns to the CRSP equally weighted stock index, we find that the GARCH(1, 1) specification cannot be rejected; thus, this model appears to be reasonably adequate in terms of reproducing the kinds of nonlinear serial dependence addressed by the battery of nonlinearity tests used here.

scholarly journals Evaluation of Agricultural Practices to Increase Yield and Financial Return and Minimize Aflatoxin Contamination in Peanut in Northern Ghana

2020 ◽  
Vol 47 (3) ◽  
pp. 156-162
Author(s):  
M. Abudulai ◽  
G. Mahama ◽  
I. Dzomeku ◽  
A. Seidu ◽  
I. Sugri ◽  
...  
Keyword(s):  
Leaf Spot ◽  
Smallholder Farmers ◽  
Agricultural Practices ◽  
Soil Surface ◽  
Aflatoxin Contamination ◽  
Fertility Treatment ◽  
Northern Ghana ◽  
Financial Returns ◽  
Financial Return ◽  
Aflatoxin Concentration

ABSTRACT Peanut (Arachis hypogaea L.) yield and financial returns are often low for smallholder farmers in Ghana. Additionally, aflatoxin concentration in foods derived from peanut can be high enough to adversely affect human health. Eight experiments were conducted in 2016 and 2017 in northern Ghana to compare yield, financial returns, pest reaction, and aflatoxin contamination at harvest with traditional farmer versus improved practices. Relative to the farmer practice, the improved practice consisted of weeding one extra time, applying local potassium-based soaps to suppress arthropods and pathogens, and application of either homogenized oyster shells or a commercial blend of fertilizer containing calcium. Each of these field treatments were followed by either drying peanut on the soil surface and storing in traditional poly bags or drying peanut on tarps and storing in hermetically-sealed bags for 4 months. Peanut yield and financial returns were significantly greater when a commercial blend of fertilizer or oyster shells were applied compared to the farmer practice of not applying any fertilizer. Yield and financial returns were greater when a commercial fertilizer blend was applied compared with oyster shells. Severity of early leaf spot [caused by Passalora arachidicola (Hori) U. Braun] and late leaf spot [caused by Nothopassalora personata (Berk. & M.A. Curtis) U. Braun, C. Nakash., Videira & Crous], scarring and penetration of pods by arthropods, and the number of arthropods at harvest were higher for the farmer practice than for either fertility treatment; no difference was noted when comparing across fertility treatments. Less aflatoxin was observed for both improved practices in the field compared with the farmer practice. Drying peanut on tarps resulted in less aflatoxin compared to drying peanut on the ground regardless of treatments in the field. Aflatoxin concentration after storage was similar when comparing post-harvest treatments of drying on soil surface and storing in poly bags vs. drying on tarps and storing in hermetically-sealed bags. These results demonstrate that substantial financial gain can be realized when management in the field is increased compared with the traditional farmer practice. While aflatoxin concentrations differed between the farmer practice and the improved practices at harvest and after drying, these differences did not translate into differences after storage.

Impact investing in South Africa: managing tensions between financial returns and social impact

2019 ◽  
Vol 31 (3) ◽  
pp. 397-419 ◽  
Author(s):  
Eunivicia Matlhogonolo Mogapi ◽  
Margaret Mary Sutherland ◽  
Anthony Wilson-Prangley
Keyword(s):  
South Africa ◽  
Social Impact ◽  
Emerging Market ◽  
Financial Returns ◽  
African Countries ◽  
Financial Return ◽  
Impact Investing ◽  
Content Type ◽  
Trade Offs ◽  
The Impact

Purpose Impact investment is an emergent field worldwide and it can play an especially important role in Africa. The aim of this study was to examine how impact investors in South Africa manage the tensions between financial returns and social impact. Design/methodology/approach The research was based on 15 semi-structured interviews with key stakeholders in the impact investment community in South Africa to understand the related challenges, trade-offs and tensions. Findings There are two opposing views expressed as to whether the tensions between financial return and social impact result in trade-offs. It is proposed that impact investors embrace this duality and seek to approach it through a contingency and a paradox view. The tensions can be approached by focussing on values alignment, contracting processes, engaged leadership and sector identification. The authors integrate the findings into a proposed framework for effective tension management in an impact investment portfolio. Research limitations/implications This study was limited to selected South African interviewees. It would be valuable to extend the study to other African countries. Practical implications The issue of values alignment between investors, fund managers and investee firms is an important finding for practice. As is the four-part iterative framework for sensing the operating environment, defining impact, organising internally and defining the investment approach. Originality/value This study contributes empirical evidence to scholarship around organisational tensions, especially work in hybrid organisations. It affirms the value of a nuanced application of paradox theory. It examines these tensions through the lived experience of impact investing professionals in an emerging market context.

scholarly journals Target Matrix Estimators in Risk-Based Portfolios

2018 ◽  
Author(s):  
Marco Neffelli
Keyword(s):  
Covariance Matrix ◽  
Moving Average ◽  
Estimation Error ◽  
Minimum Variance ◽  
Sample Covariance Matrix ◽  
Sample Mean ◽  
Index Model ◽  
Single Index Model ◽  
Sample Covariance ◽  
Risk Contribution

Portfolio weights solely based on risk avoid estimation error from the sample mean, but they are still affected from the misspecification in the sample covariance matrix. To solve this problem, we shrink the covariance matrix towards the Identity, the Variance Identity, the Single-index model, the Common Covariance, the Constant Correlation and the Exponential Weighted Moving Average target matrices. By an extensive Monte Carlo simulation, we offer a comparative study of these target estimators, testing their ability in reproducing the true portfolio weights. We control for the dataset dimensionality and the shrinkage intensity in the Minimum Variance, Inverse Volatility, Equal-risk-contribution and Maximum Diversification portfolios. We find out that the Identity and Variance Identity have very good statistical properties, being well-conditioned also in high-dimensional dataset. In addition, the these two models are the best target towards to shrink: they minimise the misspecification in risk-based portfolio weights, generating estimates very close to the population values. Overall, shrinking the sample covariance matrix helps reducing weights misspecification, especially in the Minimum Variance and the Maximum Diversification portfolios. The Inverse Volatility and the Equal-Risk-Contribution portfolios are less sensitive to covariance misspecification, hence they benefit less from shrinkage.

The relevance of financial and economic informational environment: evidence from South Asian markets

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muhammad Usman Arshad ◽  
Fahad Najeeb Khan ◽  
Muhammad Ishfaq ◽  
Muhammad Nadir Shabbir ◽  
Syed Mehmood Raza Shah
Keyword(s):  
Stock Returns ◽  
South Asian ◽  
Stock Return ◽  
Estimation Error ◽  
Accounting Standards ◽  
International Accounting ◽  
International Accounting Standards ◽  
Momentum Strategy ◽  
Content Type ◽  
Informational Environment

PurposeThis study aims to explore the firm's specific, opacity and economy-specific variables to explain the variation in South Asian market returns and indicate that how the difference in adoption of accounting standards refers to the effect of the movement in stock returns.Design/methodology/approachFollowing the scope of the study, factor analysis, fixed effect, Driscoll and Kraay standard errors (DKSE) and Panel Corrected standard error (PCSE) models have been inducted to determine the influence of firm-specific, opacity and economy-specific variables on stock returns. The sample of study comprises 1,885 firms from five countries located in the South Asia region with the period 2005–2018. To ensure the reliability of data, firm-specific data have been collected from DataStream International, while an international country risk guide was used to compile the data for economy-specific variables.FindingsThis study concluded that firm-specific variables showed a consistent and significant association with stock return except for beta, accrual and momentum while earning aggressiveness was the only factor in opacity measure to capture the variation in stock return. The implementation of international accounting standards seemed to be significant and proves to be helpful to enhance the quality of accounting information.Research limitations/implicationsThe limitations of this study comprised the estimation error by avoiding the firm's observations with negative equity in case of earning opacity and majority (more than 50%) of the observation belongs to a single market as India out of final sample which leads to having biasedness in findings.Practical implicationsThis study helps the investors to consider the firms with smaller market capitalization and lower book to market ratio and avoid the momentum strategy under firm specific factors. Moreover, earning aggressiveness under opacity domain capture the variation in stock return and must be considered while investing funds.Originality/valueThe influence of adoption of international accounting standards along with firm and economy specific variable in South Asian Equity Markets return was the major contribution. Moreover, the inclusion of DKSE and PCSE models to examine the relevance of the financial and economic informational environment was also considered as a part of major contribution of this study.

Accounting Estimation Disclosures and Firm Valuation in the Property-Casualty Insurance Industry

1997 ◽  
Vol 12 (3) ◽  
pp. 257-281 ◽  
Author(s):  
Joseph H. Anthony ◽  
Kathy R. Petroni
Keyword(s):  
Stock Returns ◽  
Insurance Industry ◽  
Estimation Error ◽  
Firm Valuation ◽  
Estimation Errors ◽  
Accounting Earnings ◽  
Earnings Response Coefficients ◽  
Future Earnings ◽  
Earnings Response ◽  
Property Casualty

Accounting earnings are subject to estimation error. Under GAAP, corrections to estimates are included in current and future earnings, but characteristics of previous errors are not disclosed. An exception exists for property-casualty insurers. SEC mandated disclosures reveal errors in previous claim expense estimates as well as the correction for those errors in current earnings. An important issue is whether these detailed disclosures are value-relevant. We examine the information content of the SEC disclosures by testing their valuation implications. We investigate whether estimation errors in previous earnings influence the reflection of current earnings in price. Results suggest that investors use these disclosures in valuation decisions. Insurers with more variable estimation errors have smaller earnings response coefficients. Apparently investors assume that the precision of previous earnings is indicative of the precision in current earnings. We also find that stock returns are associated with revisions of previous estimations included in current earnings. Our research has implications for regulation, suggesting that similar disclosures should be considered for other estimates.

scholarly journals Lévy copulae for financial returns

2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Ostap Okhrin
Keyword(s):  
Time Series ◽  
Stock Returns ◽  
Lévy Processes ◽  
Levy Processes ◽  
Time Series Models ◽  
Financial Returns ◽  
Levy Copula

AbstractThe paper uses Lévy processes and bivariate Lévy copulae in order to model the behavior of intraday log-returns. Based on assumptions about the form of marginal tail integrals and a Clayton Lévy copula, the model allows for capturing intraday cross-dependency. The model is applied to VaR of the portfolios constructed on stock returns as well as on cryptocurrencies. The proposed method shows fair performance compared to classical time series models.

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