The characteristics of portfolios selected by n-degree Lower Partial Moment

Nawrocki, David N.

doi:10.1016/1057-5219(92)90004-n

Cited by 43 publications

(28 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Findings in Simkowitz & Beedles (1978) and more recently, for example, Huang & Yau (2006) also revealed this relationship pattern of skewness and the effect on diversification. More importantly, our finding is also similar to Nawrocki (1992) who used the n-degrees LPM models.…”

Section: Discussionsupporting

confidence: 78%

“…This paper adopts the methodology for modelling CLPM found in Nawrocki (1991) and Nawrocki (1992). Similar application of the methodology is also found in recent research such as Moreno et al (2005).…”

Section: 2mentioning

confidence: 99%

“…The main aim of this paper is to conduct an empirical study using the n-degree LPM models in the asset allocation problems, similar to Nawrocki (1992). However, we updated the time period of empirical study in this paper, which is from 1999 9 to 2006.…”

Section: Datamentioning

confidence: 99%

“…According to Fishburn (1977), n<1 is when investors seek for additional risk to a portfolio; n>1 is where the investor is risk averse at the below target returns. Fishburn (1977) and Nawrocki (1992) argue that the Lower Partial Moment algorithm is general enough for it to be tailored to the utility function of an investor.…”

Section: 2mentioning

confidence: 99%

“…Nawrocki (1992) is one of the few examples of researches in this area He investigated two topics in relation to the LPM theory: the size and composition of portfolio selected by an n-degree LPM algorithm, and the effect of varying risk tolerance on the performance of investment portfolios. Nawrocki (1991) described a methodology for modelling co-lower partial moment (CLPM).…”

Section: 2mentioning

confidence: 99%

See 4 more Smart Citations

The effect of downside risk reduction on UK equity portfolios included with Managed Futures Funds

Tee

2009

International Review of Financial Analysis

View full text Add to dashboard Cite

Section: Discussionsupporting

confidence: 78%

Section: 2mentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: 2mentioning

confidence: 99%

Section: 2mentioning

confidence: 99%

See 3 more Smart Citations

The effect of downside risk reduction on UK equity portfolios included with Managed Futures Funds

Tee

2009

International Review of Financial Analysis

View full text Add to dashboard Cite

Performance functions and reinforcement learning for trading systems and portfolios

Moody

Liao

et al. 1998

Journal of Forecasting

232

208

View full text Add to dashboard Cite

We propose to train trading systems and portfolios by optimizing objective functions that directly measure trading and investment performance. Rather than basing a trading system on forecasts or training via a supervised learning algorithm using labelled trading data, we train our systems using recurrent reinforcement learning (RRL) algorithms. The performance functions that we consider for reinforcement learning are profit or wealth, economic utility, the Sharpe ratio and our proposed differential Sharpe ratio. The trading and portfolio management systems require prior decisions as input in order to properly take into account the effects of transactions costs, market impact, and taxes. This temporal dependence on system state requires the use of reinforcement versions of standard recurrent learning algorithms. We present empirical results in controlled experiments that demonstrate the efficacy of some of our methods for optimizing trading systems and portfolios. For a long/short trader, we find that maximizing the differential Sharpe ratio yields more consistent results than maximizing profits, and that both methods outperform a trading system based on forecasts that minimize MSE. We find that portfolio traders trained to maximize the differential Sharpe ratio achieve better risk‐adjusted returns than those trained to maximize profit. Finally, we provide simulation results for an S&P 500/TBill asset allocation system that demonstrate the presence of out‐of‐sample predictability in the monthly S&P 500 stock index for the 25 year period 1970 through 1994. Copyright © 1998 John Wiley & Sons, Ltd.

show abstract

Evaluating Fund Performance from Financial and SRI Criteria

Garcı́a-Bernabeu

Pérez-Gladish

Hilario

2014

International Series in Operations Research &Amp; Management Science

View full text Add to dashboard Cite

Classical approaches to financial performance of funds have the following characteristics. First, the performance composite measure is only capable of combining two criteria, which are usually profitability and risk. In purely financial analyses, this limitation is justified because profitability and risk are the more interesting criteria for most investors in funds. However, in ethical financial analysis this limitation prevents the possibility of combining multiple SRI and financial criteria. Second, the classical approaches are designed regardless of the investor's preferences for each criterion. An advantage is that the performance ranking of funds can be used whatever the investor. A disadvantage is that many investors want to manage performance rankings constructed from their preferences for ethical and financial criteria. To overcome these difficulties, the performance ranking can be constructed by a CP-based model extended to multiple SRI and financial criteria with the possibility of introducing preference weights. In this chapter, a CP model with linear-quadratic achievement function is presented and applied to an actual financial case as well as to a combined SRI-financial case. Performance Composite Measures in Classic Financial AnalysisTo discern between reliable and unreliable opportunities of investing, performance analysis is an important piece of knowledge. Data for this performance are obtained from stock market information and other available sources. Critical variables to

show abstract

The characteristics of portfolios selected by n-degree Lower Partial Moment

Cited by 43 publications

References 32 publications

The effect of downside risk reduction on UK equity portfolios included with Managed Futures Funds

The effect of downside risk reduction on UK equity portfolios included with Managed Futures Funds

Performance functions and reinforcement learning for trading systems and portfolios

Evaluating Fund Performance from Financial and SRI Criteria

Contact Info

Product

Resources

About