Trader Alpha Frontier: A Framework for Portfolio Managers and Traders to Maximize Portfolio Performance

2018 ◽  
Keyword(s):  
Portfolio Performance ◽  
Portfolio Returns ◽  
Performance Attribution ◽  
Portfolio Manager ◽  
Portfolio Managers ◽  
Main Components ◽  
Trader Performance

Trader performance is currently measured against various benchmarks without consideration for the volatility of trading results. The author introduces trader alpha frontier (TAF) as a way to measure trader performance against the risks taken by the trader. This article formulates how to carve out trader alpha from overall portfolio returns. It also explores trader performance attribution by delineating between the main components of trader alpha and suggesting benchmarks to measure each component. As a result, the author unveils a new benchmark, called execution-weighted price (EWP). It is tough to reach TAF, but it is worth the effort since it aligns the mutual objective of a portfolio manager and a trader to maximize overall portfolio performance.

scholarly journals CHARACTERISTICS OF OMEGA-OPTIMIZED PORTFOLIOS AT DIFFERENT LEVELS OF THRESHOLD RETURNS

2014 ◽  
Vol 12 (2) ◽  
pp. 245-265 ◽  
Author(s):  
Renaldas Vilkancas
Keyword(s):  
Portfolio Optimization ◽  
Risk Measures ◽  
High Threshold ◽  
Portfolio Performance ◽  
Threshold Values ◽  
Portfolio Returns ◽  
Upside Risk ◽  
And Performance ◽  
Risk Free Rate ◽  
Different Levels

There is little literature considering effects that the loss-gain threshold used for dividing good and bad outcomes by all downside (upside) risk measures has on portfolio optimization and performance. The purpose of this study is to assess the performance of portfolios optimized with respect to the Omega function developed by Keating and Shadwick at different levels of the threshold returns. The most common choices of the threshold values used in various Omega studies cover the risk-free rate and the average market return or simply a zero return, even though the inventors of this measure for risk warn that “using the values of the Omega function at particular points can be critically misleading” and that “only the entire Omega function contains information on distribution”. The obtained results demonstrate the importance of the selected values of the threshold return on portfolio performance – higher levels of the threshold lead to an increase in portfolio returns, albeit at the expense of a higher risk. In fact, within a certain threshold interval, Omega-optimized portfolios achieved the highest net return, compared with all other strategies for portfolio optimization using three different test datasets. However, beyond a certain limit, high threshold values will actually start hurting portfolio performance while meta-heuristic optimizers typically are able to produce a solution at any level of the threshold, and the obtained results would most likely be financially meaningless.

Long-term dependency between sovereign bonds and sectoral indices of India: evidence using Hurst exponent and wavelet analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Santanu Das ◽  
Ashish Kumar
Keyword(s):  
Wavelet Analysis ◽  
Hurst Exponent ◽  
Minimum Variance ◽  
Portfolio Risk ◽  
Content Type ◽  
Sovereign Bonds ◽  
Portfolio Returns ◽  
Portfolio Managers ◽  
Practical Implications

PurposeThe purpose of this study is to provide a new way to optimize a portfolio and to show that combining the Hurst exponent and wavelet analysis may help to increase portfolio returns.Design/methodology/approachThe authors use the Hurst exponent and wavelet analysis to study the long-term dependencies between sovereign bonds and sectoral indices of India. The authors further construct and evaluate the performance of three portfolios constructed on the basis of Hurst standard deviation (SD) – global minimum variance (GMV), most diversified portfolio (MDP) and equal risk contribution (ERC).FindingsThe authors find that an ERC portfolio generates positive superior return as compared other two. Since our sample includes periods of two crisis – post-2007 financial crisis and the ongoing pandemic, this study reveals that combining government bond with equities and gold provides a higher returns when the portfolios are constructed using the risk exposures of each asset in the overall portfolio risk.Practical implicationsThe findings provide guidance to portfolio managers by helping them to select assets using the Hurst approach and wavelet analysis thereby increasing the portfolio returns.Originality/valueIn this study, the authors use a combination of Hurst exponent and wavelet analysis to understand the long-term dependencies among various assets and provide a new methodology to optimize a portfolio. As far as the authors’ knowledge, no study in the past has attempted to provide a joint framework for portfolio optimization and therefore this study is the first to apply this methodology.

scholarly journals Neural Network Predictive Modeling on Dynamic Portfolio Management—A Simulation-Based Portfolio Optimization Approach

2020 ◽  
Vol 13 (11) ◽  
pp. 285
Author(s):  
Jiayang Yu ◽  
Kuo-Chu Chang
Keyword(s):  
Portfolio Optimization ◽  
Portfolio Management ◽  
Value At Risk ◽  
Machine Learning Algorithms ◽  
Conditional Value At Risk ◽  
Portfolio Performance ◽  
Optimization Approach ◽  
Macroeconomic Factors ◽  
Simulation Based ◽  
Portfolio Managers

Portfolio optimization and quantitative risk management have been studied extensively since the 1990s and began to attract even more attention after the 2008 financial crisis. This disastrous occurrence propelled portfolio managers to reevaluate and mitigate the risk and return trade-off in building their clients’ portfolios. The advancement of machine-learning algorithms and computing resources helps portfolio managers explore rich information by incorporating macroeconomic conditions into their investment strategies and optimizing their portfolio performance in a timely manner. In this paper, we present a simulation-based approach by fusing a number of macroeconomic factors using Neural Networks (NN) to build an Economic Factor-based Predictive Model (EFPM). Then, we combine it with the Copula-GARCH simulation model and the Mean-Conditional Value at Risk (Mean-CVaR) framework to derive an optimal portfolio comprised of six index funds. Empirical tests on the resulting portfolio are conducted on an out-of-sample dataset utilizing a rolling-horizon approach. Finally, we compare its performance against three benchmark portfolios over a period of almost twelve years (01/2007–11/2019). The results indicate that the proposed EFPM-based asset allocation strategy outperforms the three alternatives on many common metrics, including annualized return, volatility, Sharpe ratio, maximum drawdown, and 99% CVaR.

scholarly journals Mutual funds behavior and risk-adjusted performance in Nigeria

2021 ◽  
Vol 18 (3) ◽  
pp. 277-294
Author(s):  
Joshua Odutola Omokehinde
Keyword(s):  
Mutual Funds ◽  
Portfolio Performance ◽  
Average Risk ◽  
Negative Effects ◽  
Market Returns ◽  
Significance Level ◽  
Fund Managers ◽  
Portfolio Returns ◽  
Normality Test ◽  
Risk Free Rate

The paper investigates the behavior of mutual funds and their risk-adjusted performance in the financial markets of Nigeria between April 2016 and May 31, 2019, using descriptive statistics, as well as CAPM, Jensen’s alpha, and other risk-adjusted portfolio performance measures such as Sharpe and Treynor ratios, as well as Fama decomposition of return. The descriptive tests revealed that 80.77% of the funds were superior to market returns, while 13.46% were riskier. The market and the fund returns behaved abnormally with asymptotic and leptokurtic characteristics as their skewness and kurtosis varied from the normal requirements. Diagnostically, the normality test by Jacque-Berra showed that the return was not normally distributed at a 1% significance level. The market was more aggressive relative to the funds. The average risk-free rate was 6.75% above the market’s return. The risk-adjusted portfolio returns measured by Sharpe and Treynor ratios showed that 67.31% of the funds underperformed the market compared to 40.38% that outperformed the market using Jensen’s alpha. Fama decomposition of return revealed that the fund managers are risk-averse with 48% superior selection ability and rationally invested over 85% of investors’ funds in schemes with fixed income securities at a given risk-free return that cushioned the negative effects of the systematic and idiosyncratic risks and consequently threw the total returns into positive territories. Overall, the fund managers possessed 52% of inferior selection abilities that only earned 33% of superior risk-adjusted returns and hence, failed to achieve the desired diversification in the relevant period.

scholarly journals Analisis Kinerja Reksa Dana Saham Menggunakan Metode Sharpe, Treynor dan Jensen Dengan IHSG dan Lq45 (Reksa Dana Saham Yang Terdaftar Di OJK Tahun 2009-2013)

1970 ◽  
Vol 12 (2) ◽  
pp. 85-114
Author(s):  
Ningsih Pratiwi ◽  
Randy Heriyanto
Keyword(s):  
Mutual Fund ◽  
Bench Mark ◽  
Portfolio Performance ◽  
Performance Measurements ◽  
Risk And Return ◽  
Portfolio Returns ◽  
Equity Funds ◽  
Calculation Results ◽  
Stock Portfolio ◽  
Observation Period

Risk and Return are two things that must be considered in measuring portfolio performance, there are three parameters that have accommodated Risk and Return; Sharpe method, Treynor method, and Jensen method. These three performance measurements assume a relationship between portfolio returns, portfolio risks, and returns from several market indices. The measurement of stock portfolio performance can be facilitated by using a bench mark, which is IHSG and LQ 45 shares. The purpose of this study is to determine the performance of stock mutual funds against the CSPI and LQ 45. Penunlis conducted research on 29 conventional equity funds, which fulfilled the selected criteria purposive sampling. From the calculation results, it can be seen that only a number of mutual fund products are able to outperform the IHSG and LQ 45, but no one is able to survive consistently having the best performance during the 2009 to 2013 observation period. This is caused by changes in average returns and beta generated by mutual fund products.

scholarly journals Macroeconomic announcements and stock returns in US portfolios formed on operating profitability and investment

2018 ◽  
Vol 15 (1) ◽  
pp. 68-89 ◽  
Author(s):  
Constantinos Alexiou ◽  
Sofoklis Vogiazas ◽  
Abid Taqvi
Keyword(s):  
Stock Returns ◽  
Macroeconomic News ◽  
Portfolio Returns ◽  
Stock Portfolios ◽  
Macroeconomic Announcements ◽  
Personal Consumption ◽  
Investment Level ◽  
Portfolio Managers ◽  
Economic Expectations ◽  
Stock Portfolio

The authors explore the reaction of US stock portfolio returns to macroeconomic announcements spanning the period from April 1998 to May 2017. Using daily returns of 25 portfolios formed on operating profitability and investment, the authors investigate the extent to which potential asymmetries permeate the stock portfolios following macroeconomic announcements. The three methodological approaches utilized in this study suggest that the ISM non-manufacturing index, employees on non-farm payrolls, retail sales, personal consumption expenditure and initial jobless claims have a significant impact on portfolio returns. Also, portfolios consisting of companies with higher operating profitability and investment level are found to be less responsive to announcements. As the particular area has received little currency over the years, this contribution is of great significance, because it provides insights into the reaction of returns in value-weighted portfolios to announcements on certain macro-indicators. At the same time, the study informs portfolio managers of the implications of macroeconomic news, which drive economic expectations and can reverberate through the expected returns in US stock portfolios.

A Study on Factors Influencing Mutual Fund Portfolio Performance

2018 ◽  
Vol 5 (2) ◽  
pp. 1-11
Author(s):  
Medhanie Mekonnen ◽  
Roger Mayer ◽  
Wen-Wen Chien
Keyword(s):  
Mutual Funds ◽  
Mutual Fund ◽  
Portfolio Performance ◽  
Management Turnover ◽  
Performance Expectations ◽  
Equity Mutual Funds ◽  
Portfolio Managers ◽  
Fund Portfolio ◽  
The Relationship ◽  
Annual Fund

Mutual fund portfolio managers do not always meet performance expectations, resulting in loss of capital reserves. Out of 3,612 U.S. based open-ended mutual funds, the risk-adjusted performance of 2,890 (80%) failed to meet the S&P 500 performance between the year 2006 to 2016. Grounded in Markowitz's modern portfolio theory, this correlational study examined the relationship between mutual fund class type, portfolio turnover, fund longevity, management turnover, and annual fund risk-adjusted performance. Archival data were collected from 88 U.S. based equity mutual funds companies. The results of the multiple regression analysis indicated the model as a whole was able to significantly predict annual fund risk-adjusted performance for the 5-year period ending 2016, F (4, 83) = 3.581, p = .010, R2 = .147. In the final model, mutual fund class type and portfolio turnover were statistically significant with mutual fund class type (ß= .249, t = 2.302, p = .024) accounting for a higher contribution to the model than portfolio turnover (ß = .238, t = 2.312, p = .023).

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