Investments, Market Timing and Portfolio Performance across Indian Bull and Bear Markets

2017 ◽  
Vol 13 (3-4) ◽  
pp. 98-109
Author(s):  
Sunaina Kanojia ◽  
Neha Arora
Keyword(s):  
Stock Market ◽  
Market Timing ◽  
Investment Strategy ◽  
Portfolio Performance ◽  
Investment Strategies ◽  
Bear Market ◽  
Market Trends ◽  
Two Phases ◽  
The Universe

The returns generated from an investment alternative are exponentially higher when espoused with appropriate timings. This article expound on the market timing used by investors to formulate profitable investment strategies in the stock market, which requires gathering of information at both micro- and macro-levels along with market trends to make timely decisions and evaluating the universe of stocks available. The market trends are been broadly classified into bull and bear phases, which have dynamic influence on buying and selling in the stock market. Further, the study supports the retail investors’ participation in the market for long-term to generate higher returns as compared to other conventional alternatives. The study attempts to identify bull and bear market turning points using a formal turning point identification procedure and formulate a profitable investment strategy in bull or bear market phases to maximise the returns. Hence, the present study provides to understand how the two phases influence investment decisions and determine the implications of bull and bear market phases on investors’ investment strategy.

scholarly journals Enterprise Multiple and Future Returns of the Brazilian Stock Market

2017 ◽  
Vol 10 (3) ◽  
pp. 431
Author(s):  
Rafael Igrejas ◽  
Raphael Braga Da Silva ◽  
Marcelo Cabus Klotzle ◽  
Antonio Carlos Figueiredo Pinto ◽  
Paulo Vitor Jordão da Gama Silva
Keyword(s):  
Risk Factors ◽  
Stock Market ◽  
Cross Section ◽  
Predictive Power ◽  
Abnormal Returns ◽  
Strong Relationship ◽  
Investment Strategy ◽  
Emerging Countries ◽  
Investment Strategies ◽  
Developed Markets

The estimation of cross-section returns for defining investment strategies based on financial multiples has been proven to be relevant following Fama and French’s (1992) research. One of the challenges for such studies is to identify the main variables that are suitable for explaining the returns in a particular context because the variables that are widely used in developed markets behave differently in emerging countries. In this study, we analyze the predictive power of the EV/EBITDA multiple in the context of the Brazilian stock market. The results show that the analyzed multiple has a strong relationship with the future returns of companies listed on the BM&F BOVESPA index between 2005 and 2013. For the period under review, the investment strategy of purchasing stocks when EV/EBITDA was low and selling stocks when EV/EBITDA was high showed abnormal returns of 15.94% per year, even after controlling for risk factors.

scholarly journals Enhanced indexation via chance constraints

2020 ◽  
Author(s):  
Patrizia Beraldi ◽  
Maria Elena Bruni
Keyword(s):  
Investment Strategy ◽  
Chance Constraints ◽  
Portfolio Performance ◽  
Investment Strategies ◽  
Index Tracking ◽  
Negative Deviation ◽  
Additional Risk ◽  
Benchmark Instances ◽  
Out Of Sample ◽  
The Empirical Analysis

Abstract The enhanced index tracking (EIT) represents a popular investment strategy designed to create a portfolio of assets that outperforms a benchmark, while bearing a limited additional risk. This paper analyzes the EIT problem by the chance constraints (CC) paradigm and proposes a formulation where the return of the tracking portfolio is imposed to overcome the benchmark with a high probability value. Besides the CC-based formulation, where the eventual shortage is controlled in probabilistic terms, the paper introduces a model based on the Integrated version of the CC. Here the negative deviation of the portfolio performance from the benchmark is measured and the corresponding expected value is limited to be lower than a given threshold. Extensive computational experiments are carried out on different set of benchmark instances. Both the proposed formulations suggest investment strategies that track very closely the benchmark over the out-of-sample horizon and often achieve better performance. When compared with other existing strategies, the empirical analysis reveals that no optimization model clearly dominates the others, even though the formulation based on the traditional form of the CC seems to be very competitive.

Forecasting the Stock Market with ANNs and Autonomous Agents

2011 ◽  
pp. 2176-2182
Author(s):  
Christiano Leite Castro ◽  
Anto^nio Pa´dua Braga
Keyword(s):  
Stock Market ◽  
Web Site ◽  
Autonomous Agents ◽  
Financial Time Series ◽  
Daily Basis ◽  
Investment Strategies ◽  
Share Prices ◽  
Good Investment ◽  
Market Trends ◽  
Investment Portfolios

Investment strategies usually aim at achieving maximum profitability what, according to current management theory (Refenes, Burgess, & Bentz, 1997), can be obtained by the construction of well balanced investment portfolios that seek to maximum return and minimum risks. In order to provide users with information to plan a good investment portfolio, we present an e-commerce Web site solution that enables users to estimate in advance investments return and risks. The application, which is based on computational intelligence techniques, aims at forecasting and divulging the share prices of the main companies listed in the stock market. Artificial neural networks (ANNs) (Haykin, 1999) that have been used successfully in many other financial time series applications (Braga, Carvalho, Lurdemir, Almeida, & Lacerda, 2002; Refenes, et al., 1997; Zhang, 2003) were used as the main forecasting engine of the system. Autonomous agents (Paolucci, Sycara, & Kawamura, 2003; Russel & Norvig, 1995) are responsible for collecting, on a daily basis, information regarding sale and purchase of shares. The information collected is then used by the ANN to forecast future stock market trends and closing values. The Web site offers free of charge services, such as access to forecasting charts, simulation of investments and general guidelines for buying and selling shares.

An analytical approach for behavioral portfolio model with time discounting preference

2018 ◽  
Vol 52 (3) ◽  
pp. 691-712
Author(s):  
Guang Yang ◽  
Xinwang Liu ◽  
Jindong Qin ◽  
Ahmed Khan
Keyword(s):  
Portfolio Selection ◽  
Investment Strategy ◽  
Cumulative Prospect Theory ◽  
Investment Strategies ◽  
Short Term ◽  
Time Discounting ◽  
Present Bias ◽  
Proposed Model ◽  
Portfolio Selection Model

This paper presents a behavioral portfolio selection model with time discounting preference. Firstly, we discuss the portfolio selection problem and then modify this model based on cumulative prospect theory (CPT) as well as considering investors’ time discounting preference in psychology. Furthermore, an analytical solution with satisfying behavior is given for our proposed model, the results show that when investors’ goals are very ambitious, they put a high proportion of their wealth in long-term goals and adopt aggressive investment strategies with high leverage to reach short-term goals and the overall investment strategy also displays high leverage. Finally, numerical analysis is given and it is shown that investor who tends to future bias performs adequate confidence and patience whereas investor with present bias is apt to the immediate interests.

Investment styles and the multifactor analysis of market timing skill

2017 ◽  
Vol 13 (1) ◽  
pp. 21-35
Author(s):  
Jarkko Peltomäki
Keyword(s):  
Factor Model ◽  
Market Timing ◽  
Investment Strategy ◽  
Investment Strategies ◽  
Analysis Model ◽  
Content Type ◽  
Multifactor Models ◽  
Multifactor Model ◽  
Investment Style ◽  
Investment Styles

Purpose The purpose of this paper is to present and demonstrate how the use of a multifactor model in the analysis of market timing skill can be misleading because the use of a multifactor model does not suit all investment styles equally well. If the factors of the analysis model do not span the portfolio holdings of a fund with less conventional investment strategy, the use of a multifactor model may even deteriorate the overall inference in measuring the market timing skill of a large sample of funds. Design/methodology/approach This study investigates the limitations of multifactor models in the analysis of market timing skill by applying the traditional Treynor-Mazuy and Henriksson-Merton analysis models of market timing skill using a set of “placebo” funds which are “natural” passive market timers. Findings The results of the study show that the incorporation of the Carhart four-factor model into the analysis of market timing skill considerably reduces the percentage of significant market timing results. But, as expected, the reduction of bias is not equal for different investment styles, and it works best when the factors of the analysis model are related to the investment style of the placebo portfolio. Practical implications This style-related limitation of multifactor models in the analysis of market timing skill may result in detecting funds with less conventional investment strategies as market timers since the factors used in the analysis are not likely to span their investment styles. Originality/value This study shows that the use of a multifactor model may lead to inferring passive market timers with less conventional investment styles as market timers. In addition, the findings of the study leave option replication approaches as more preferable bias corrections than multifactor extensions.

scholarly journals Sticky Stock Market Analysts

2021 ◽  
Vol 14 (12) ◽  
pp. 593
Author(s):  
Ibrahim Filiz ◽  
Jan René Judek ◽  
Marco Lorenz ◽  
Markus Spiwoks
Keyword(s):  
Stock Market ◽  
Investment Strategies ◽  
Stock Market Index ◽  
Market Index ◽  
German Stock ◽  
Long Term Trends ◽  
German Stock Market ◽  
Better Than

Technological progress in recent years has made new methods available for making forecasts in a variety of areas. We examine the success of ex-ante stock market forecasts of three major stock market indices, i.e., the German Stock Market Index (DAX), the Dow Jones Industrial Index (DJI), and the Euro Stoxx 50 (SX5E). We test whether the forecasts prove true when they reach their effective dates and are therefore suitable for active investment strategies. We revive the thoughts of the American sociologist William Fielding Ogburn, who argues that forecasters consistently underestimate the variability of the future. In addition, we draw on some contemporary measures of forecast quality (prediction-realization diagram, test of unbiasedness, and Diebold–Mariano test). We reveal that (a) unusual events are underrepresented in the forecasts, (b) the dispersion of the forecasts lags behind that of the actual events, (c) the slope of the regression lines in the prediction-realization diagram is <1, (d) the forecasts are highly biased, and (e) the quality of the forecasts is not significantly better than that of naïve forecasts. The overall behavior of the forecasters can be described as “sticky” because their forecasts adhere too strongly to long-term trends in the indices and are thus characterized by conservatism.

scholarly journals IPO Waves: How Market Performances Influence The Market Timing Of IPO?

2015 ◽  
Vol 31 (5) ◽  
pp. 1679
Author(s):  
Firas Batnini ◽  
Moez Hammami
Keyword(s):  
Stock Market ◽  
Initial Public Offerings ◽  
Market Timing ◽  
Autocorrelation Analysis ◽  
Market Returns ◽  
Stock Market Returns ◽  
Public Offerings ◽  
One Year ◽  
The Impact

The goal of this paper is to study the impact of stock markets on Initial Public Offerings (IPOs). Several studies have shown that the need for financing is not the main trigger for an IPOfavorable market conditions may play a more important part. This work prove the existence of a significate relationship between past stock market returns and the number of IPOs. Before setting the date for an IPO, managers analyze long term financial market yields, a bullish stock market over a six month/ one year period encourages IPOs activities. In the other hand, even a negative performance but over a two-year period may have the same effect. They expect a stock market inversion. These results were obtained by autocorrelation analysis and count regression.

Forecasting Russian Stock Market Trends

2003 ◽  
pp. 81-94 ◽  
Author(s):  
A. Rozhkov
Keyword(s):  
Stock Market ◽  
Economic Indicators ◽  
Forecasting Model ◽  
Reverse Trend ◽  
Trend Forecasting ◽  
Market Trends ◽  
Russian Stock Market

The article is devoted to investigating methods for forecasting long-term Russian stock market trends. The purpose of research is creation of the forecasting model capable of forming a reverse trend signal in the stock market. The index of trend forecasting constructed in the article includes different economic indicators and thus has high forecasting ability.

Performance of Option Based Strategy Benchmark Index

2018 ◽  
Vol 26 (2) ◽  
pp. 183-216
Author(s):  
Soon Shin Kwon ◽  
Byung Jin Kang ◽  
Jay M. Chung
Keyword(s):  
Expected Utility Theory ◽  
Portfolio Performance ◽  
Investment Strategies ◽  
Index Options ◽  
Empirical Results ◽  
Investment Returns ◽  
Two Indices ◽  
Covered Call ◽  
Covered Call Strategies

This paper develops “Strategy Benchmark Index (SBI)” using KOSPI200 options data from January 2004 to March 2017, and then investigates their performances. The SBIs were constructed in the same way as those published daily by CBOE. To effectively analyze the performance of these SBIs, we classified them into four types : (1) Return enhancement SBIs (six indices), (2) Volatility trading SBIs (two indices), (3) Directional trading SBIs (two indices) and (4) Other SBIs (two indices). The return enchancement SBIs include bechmark indices tracking the performance of various covered call strategies and put writing strategies, which are generally used to increase investment returns. The volatility trading SBIs include benchmark indices tracking the performance of well-known volatility trading strategies such as butterfly spread and condor. Benchmark indices tracking the performance of various types of zero-cost collar strategies are classified into the directional trading SBIs. Our empirical results are as follows. First, the risk-adjusted performances of nine SBIs of the total twelve SBIs constructed from KOSPI200 index options has been shown to be great. Second, from a portfolio perspective, some SBIs can be helpful to improve the portfolio performance of CRRA (Constant Relative Risk Aversion) investors. These results imply that passive investment strategies with KOSPI200 index options can provide additional benefits that both equities and bonds do not provide. Third, even when we use the traditional mean-variance framework other than expected utility theory to verify the economic benefit of the SBIs, our empirical results are found to be still valid. In conclusion, our results suggest that some passive investment strategies using KOSPI200 index options would be beneficial to long term investors.

The impact of politics and economic policy uncertainty on anomaly-based investment strategies

2019 ◽  
Vol 45 (5) ◽  
pp. 654-670
Author(s):  
Cedric Mbanga ◽  
Jeffrey Scott Jones ◽  
Seth A. Hoelscher
Keyword(s):  
Economic Policy ◽  
Hedge Funds ◽  
Investment Strategy ◽  
Portfolio Performance ◽  
Policy Uncertainty ◽  
Investment Strategies ◽  
Party Affiliation ◽  
Content Type ◽  
Economic Policy Uncertainty ◽  
The Impact

Purpose The purpose of this paper is to explore the overlooked relationship between politics and the performance of anomaly-based investment strategies. Design/methodology/approach Monthly long-short portfolios are formed based on relative mispricing scores according to the Stambaugh et al. (2012, 2015) relative mispricing measure. Portfolio performance is examined throughout various presidential terms. The design also introduces economic policy uncertainty (EPU) as a possible explanatory variable for portfolio performance. Findings The analysis reveals that anomaly-based returns are higher under Republican administrations than they are under Democratic administrations. Moreover, the results show that the impact of EPU on the relationship between the political party affiliation of the president and future anomaly-based returns are driven by the election and post-election years. Practical implications The examination of returns on a long-short portfolio may be of particular value to investment companies, such as hedge funds, who regularly employ this type of strategy. Originality/value While the impact of presidential terms on raw equity returns has been well examined, the paper is the first to examine the impact of presidential terms on the return of an anomaly-based investment strategy. EPU is also introduced as an important contributing factor.

Sign in / Sign up

Export Citation Format

Share Document