PREDICTION OF STOCK RETURNS MAY BE FALLACIOUS: A STOCHASTIC CONFIRMATION OF MALKIEL’S ASSERTION ON DARTBOARD INVESTMENTS

2021 ◽  
Vol 62 (2) ◽  
pp. 131-150
Author(s):  
Michael Weba
Keyword(s):  
Stock Returns ◽  
Future Development ◽  
Portfolio Assessment ◽  
Planning Horizon ◽  
Portfolio Construction ◽  
Selection Methods ◽  
Dart Throwing ◽  
Critical Relation ◽  
Best Linear Unbiased ◽  
Special Case

Several studies on portfolio construction reveal that sensible strategies essentially yield the same results as their nonsensical inverted counterparts; moreover, random portfolios managed by Malkiel’s dart-throwing monkey would outperform the cap-weighted benchmark index. Forecasting the future development of stock returns is an important aspect of portfolio assessment. Similar to the ostensible arbitrariness of portfolio selection methods, it is shown that there is no substantial difference between the performances of “best” and “trivial” forecasts - even under euphemistic model assumptions on the underlying price dynamics. A certain significance of a predictor is found only in the following special case: the best linear unbiased forecast is used, the planning horizon is small, and a critical relation is not satisfied.

scholarly journals Changes in the Portfolio Management and Construction under the Pandemic Era

2021 ◽  
Vol 275 ◽  
pp. 01005
Author(s):  
Ruipeng Tan
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Stock Returns ◽  
Financial Market ◽  
Portfolio Management ◽  
Portfolio Construction ◽  
Sample Data ◽  
Before And After ◽  
Reduce Risk ◽  
The Impact

This paper focuses on comparing portfolio management and construction before and after the coronavirus. First, this paper presents the importance of building up portfolios for investors to diversify their risks. Theories on portfolio management are discussed in this section to show how they have been developed to help on investing and reduce risk. Then, the paper moves on to show the impact of the pandemic on the financial market and portfolio management. Sample data on tech stock returns are collected to perform a Monte Carlo simulation on portfolio construction to find out the efficient portfolio before and after the COVID-19 outbreak. The efficient portfolio is build based on the Markowitz theory to find the combination. Comparisons between these portfolio constructions are made to find out the changes in portfolio management and construction under the pandemic era. In conclusion, this paper presents how pandemic has changed and impacted the investments and lists recommendations on future portfolio management and construction.

scholarly journals Prediksi Risiko Sistematik Saham-Saham LQ45 Bursa Efek Indonesia

2016 ◽  
Vol 17 (3) ◽  
pp. 99
Author(s):  
A An Arief Jusuf
Keyword(s):  
Stock Returns ◽  
Systematic Risk ◽  
Regression Method ◽  
Linear Regression Method ◽  
Security Market ◽  
Research Model ◽  
Normality Assumption ◽  
Alternative Action ◽  
Best Linear Unbiased ◽  
High Beta

<em>Beta has been argued, both conceptually as well as empirically. In 1960's, many practitioners used superior advantages in calculation attempted at CAPM theory for investing in asset which has high Beta. Many empirical researches on the later years refused the existence of security market line from CAPM. Afterwards, many practitioners and academicians stated the death of CAPM. Linear regression method could be used to make decision if it had already matched the criteria for Best Linear Unbiased Estimator. Prediction model is a statistic testing which aimsat knowing whether there is a relationship or effect between researched variables. Nonparametric method is an alternative action which is taken when the research model does not match normality assumption. This research, as shown by the use of weekly data, could be free from technical trading problems in predicted systematic risk. While ASII, HRUM, and TLKM stock returns are affected more by other factors. This condition has caused systematic risk not to affect significantly on those stocks. Another result has shown that banking stocks, which became part of LQ45, have higher systematic risk respectively.</em>

scholarly journals Application of mathematical modeling in creating investment portfolio of commercial bank

2019 ◽  
Vol 2019 (4) ◽  
pp. 112-119
Author(s):  
Olga Mikhailovna Markova
Keyword(s):  
Stock Returns ◽  
Commercial Bank ◽  
Portfolio Assessment ◽  
Investment Strategy ◽  
Risk Minimization ◽  
Investment Activity ◽  
Capital Growth ◽  
Banking Business ◽  
Stock Portfolio ◽  
Portfolio Structure

The article touches upon the most urgent problem of creating the stock portfolio of a commercial bank, where studying the strategies and tools of the bank’s investment activity and using mathematical models for its assessment help to identify the relationship between profitability and the risk of investing in securities. As a result of applied analysis and modeling of the portfolio structure, the optimal portfolio option is selected, which corresponds to a given level of risk and profitability, as well as to the investment strategy chosen by the bank. There has been analyzed the portfolio structure with specified characteristics of risk and profitability, according to the statistics of previous years. The types of documents have been systematized according to the compliance with the strategy of managing the portfolio of profitability growth, liquidity and risk minimization. Using the models of Markowitz, Tobin and other researchers of probabilistic portfolio assessment through covariance indicators and a correlation coefficient, there have been found the values of return on assets that can change in one direction or have a multidirectional nature, and allow to calculate dependence between the values of return on securities in the portfolio. There have been considered the following models: a portfolio model based on calculating the level of stock returns of LUKOIL JSC, Novatek JSC, Yandex; a portfolio model that includes risk-free assets with the highest level of reliability (government short-term bonds, federal loan bonds); capital asset pricing model which describes dependency between the risk and the required profitability. Based on these calculations there has been inferred the possibility of developing specific areas of the banking business in the field of securities transactions, including: saving funds (providing protection against inflation); capital growth (focus on the securities that have the potential for growth in market value); profitability (purchasing securities in order to obtain dividends on shares and interest on debt securities); liquidity (investments into financial tools that can be sold at any time at favorable prices); risk minimization. The results of the conducted analysis of correlation and regression of the securities portfolio have revealed the most preferred types of securities for growing profitability that are in the bank's portfolio: shares of the Russian oil company LUKOIL, the Russian gas company Novatek, Yandex cIA, as well as the federal loan bonds (based on the terms of calculating history dynamics since May 1, 2018 up to May 1, 2019)

scholarly journals The influence of volatility spill-overs and market beta on portfolio construction

2015 ◽  
Vol 18 (2) ◽  
pp. 277-290 ◽  
Author(s):  
André Heymans ◽  
Wayne Peter Brewer
Keyword(s):  
Stock Returns ◽  
The Other ◽  
Portfolio Construction ◽  
Investment Portfolio ◽  
Model Framework ◽  
Additional Measure ◽  
Market Beta ◽  
Portfolio Managers ◽  
Top 40 ◽  
Mean Variance

This study adds to Modern Portfolio Theory (MPT) by providing an additional measure to market beta in constructing a more efficient investment portfolio. The additional measure analyses the volatility spill-over effects among stocks within the same portfolio. Using intraday stock returns from five top-40 listed stocks on the JSE between July 2008 and April 2010, volatility spill-over effects were estimated with a residual- based test (aggregate shock [AS] model) framework. It is shown that when a particular stock attracted fewer volatility spill-over effects from the other stocks in the portfolio, the overall portfolio volatility decreased as well. In most cases market beta showcased similar results. Therefore, in order to construct a more efficient risk- adjusted portfolio, one requires both a portfolio that has a unit correlation with the market (beta-based), and stocks that showcase the least amount of volatility spill-over effects amongst one another. These results might assist portfolio managers to construct lower mean variance portfolios.

scholarly journals Investment Strategies, Performance, And Trading Information Impact

2011 ◽  
Vol 4 (9) ◽  
Author(s):  
Tov Assogbavi ◽  
Johnston E. Osagie ◽  
Larry A. Frieder ◽  
Jong-Kyun Shin
Keyword(s):  
Stock Returns ◽  
Strong Evidence ◽  
Trading Volume ◽  
High Volume ◽  
Investment Strategy ◽  
Volume Effect ◽  
Bad News ◽  
Portfolio Construction ◽  
Investment Strategies ◽  
Canadian Market

This paper examines a set of investment strategies based on past market information to evaluate performance and trading impact on the Canadian Market. In doing so, we assess whether trading information adds value to the effectiveness of these strategies. Utilizing variant models of four different methodologies, we find strong evidence that supported the Momentum Investment Strategy, which buys past winner stocks and sells past loser stocks. Our evidence did not support Contrarian Investment Strategy, which posits that investors overreact to good and bad news. Our winners portfolios outperform our losers portfolios. The Negative Volume Effect Strategy did not work, which is contrary to the Foerster, Prihar and Schmitz (1995) study. We found that winners stocks did not reverse in cases of heavy volume; nor did loser stocks reverse in a high volume context. However, we did find that trading information has an impact on stock returns and thus adds value to investment strategies for the 1990 to 2000 investment period. Investors who combine past price and trading volume information in constructing their investment strategies would achieve higher returns than investors who base their portfolio construction decisions solely on stock prices.University.

EQUILIBRIUM WITH EXCESSIVE HOLDINGS CONSTRAINT: AN APPLICATION TO DC PENSION PLANS

2007 ◽  
Vol 10 (07) ◽  
pp. 1159-1190 ◽  
Author(s):  
ISSOUF SOUMARÉ
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Market Price ◽  
Pension Plans ◽  
Defined Contribution ◽  
Excess Returns ◽  
Market Price Of Risk ◽  
Price Of Risk ◽  
Special Case ◽  
Accurate Quantification

In this paper, I study the equilibrium implications when some investors in the economy overweight a subset of stocks within their portfolio. I find that the excess returns for the overweighted stocks are lower, all else being equal. This has strong testable implications for stock returns. In the special case of logarithmic preferences, the riskfree rate increases and the market price of risk for the overweighted stock decreases, which create extra incentive for unconstrained agents to exit the stock market and hold bonds, hence clearing the market. The changes of stocks' volatilities are ambiguous. Finally, I provide an accurate quantification for agents' welfare. I also discuss the implications of my model in the context of defined contribution pension plans where workers hold large shares of their employer.

scholarly journals Kovariantiškumas ir kodiferencija sudarant optimalų vertybinių popierių portfelį

2008 ◽  
Vol 42 (43) ◽  
pp. 182-188
Author(s):  
Igoris Belovas ◽  
Audrius Kabašinskas ◽  
Leonidas Sakalauskas
Keyword(s):  
Stock Returns ◽  
Optimal Portfolio ◽  
Stable Laws ◽  
Portfolio Construction ◽  
Baltic States ◽  
Stock Portfolios ◽  
Construction Strategies ◽  
Markowitz Problem

Formuojant vertybinių popierių portfelį svarbu nustatyti ryšius tarp atskirų akcijų grąžų. Tačiau laikantis stabilumo prielaidos (modeliuojant akcijų grąžų sekas stabiliaisiais dėsniais) klasikiniai ryšio matai (kovariacija, koreliacija) negali būti taikomi. Todėl apibendrintasis Markovitzo uždavinys yra sprendžiamas su apibendrintais ryšio matais (kovariantiškumas, kodiferencija). Parodyta, kad kodiferencijos tarp atskirų finansinių instrumentų koeficientas gerokai supaprastina portfelio formavimą.Buvo sudaryti Baltijos šalių dešimties vertybinių popierių optimalūs portfeliai.On covariation and Codifference in optimal portfolio constructionIgoris Belovas, Audrius Kabašinskas, Leonidas Sakalauskas SummaryConstructing an optimal portfolio it is essential to determine possible relationships between different stock returns. However, under the assumption of stability (stock returns are modelled with stable laws) accustomed relationship measures covariance, correlation) can not be applied. Thus generalized Markowitz problem is solved with generalized relationship measures (covariation, codifference). Portfolio construction strategies with and without codifference coefficients matrix are given. We show thatthe codifference application strongly simplifies the construction of the optimal portfolio. Optimal stock portfolios (with 10 most realizable Baltic States stocks) with and without codifference coefficients matrix are constructed.

Extreme self-sacrifice beyond fusion: Moral expansiveness and the special case of allyship

2018 ◽  
Vol 41 ◽  
Author(s):  
Daniel Crimston ◽  
Matthew J. Hornsey
Keyword(s):  
General Theory ◽  
Biological Markers ◽  
Natural Environment ◽  
Relevant Dimension ◽  
Special Case

AbstractAs a general theory of extreme self-sacrifice, Whitehouse's article misses one relevant dimension: people's willingness to fight and die in support of entities not bound by biological markers or ancestral kinship (allyship). We discuss research on moral expansiveness, which highlights individuals’ capacity to self-sacrifice for targets that lie outside traditional in-group markers, including racial out-groups, animals, and the natural environment.

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