Risk-return Framework Research Articles

Decision-making competence predicts domain-specific risk attitudes.

Decision-making competence (DMC) reflects individual differences in rational responding across several classic behavioral decision-making tasks. Although it has been associated with real-world risk behavior, less is known about the degree to which DMC contributes to specific components of risk attitudes. Utilizing a psychological risk-return framework, we examined the associations between risk attitudes and DMC. Italian community residents (n = 804) completed an online DMC measure, using a subset of the original Adult-DMC battery. Participants also completed a self-reported risk attitude measure for three components of risk attitudes (risk-taking, risk perceptions, and expected benefits) across six risk domains. Overall, greater performance on the DMC component scales were inversely, albeit modestly, associated with risk-taking tendencies. Structural equation modeling results revealed that DMC was associated with lower perceived expected benefits for all domains. In contrast, its association with perceived risks was more domain-specific. These analyses also revealed stronger indirect effects for the DMC → expected benefits → risk-taking path than the DMC → perceived risk → risk-taking path, especially for behaviors that may be considered more maladaptive in nature. These results suggest that DMC performance differentially impacts specific components of risk attitudes, and may be more strongly related to the evaluation of expected value of a specific behavior.

Default Risk Premium in Credit and Equity Market: A New Approach for Structural Model Estimation

The default risk premium expresses the difference between the actual default risk of a company and the default risk implied by the securities issued by the company. In this paper, we study the simultaneous relationship between the dynamics of the default risk premium and both the dynamics of the stock price and the CDS (Credit Default Swap) spread of a company. We show that an increase in the default risk premium can be associated, at the same time, to either an increase in the stock price and a decrease in the CDS spread, or to a decrease in the stock price and an increase in the CDS spread. We document that the first type of relationship features securities belonging to a consistent risk-return framework, while the second type of relationship describes securities following a counterintuitive risk-return puzzle. We show this result theoretically end empirically, by adopting a contingent claim model. We estimate the model with a non-linear Kalman filter in conjunction with quasimaximum likelihood, and we shed light on the relationship over time between the default risk premium and both the equity value and the CDS spreads for a sample of non-financial firms.

Momentum Strategies: From Novel Estimation Techniques to Financial Applications

The objectives of this report are two-fold. We first studied some novel techniques in statistics and signal processing fields such as trend filtering, daily and high frequency volatility estimator or support vector machine. We employed these techniques to extract interesting financial signals. These signals are used to implement the momentum strategies which will be described in detail in every chapter of this report. The second objective concerns the study of the performance of momentum strategies based on the risk-return analysis framework (see B. Bruder and N. Gaussel 7th White Paper, Lyxor).

Tools for Managing Early-Stage Business Model Innovation

OVERVIEW:Standard financial metrics do not provide useful or meaningful evaluations of the potential of early-stage ideas that require business model shifts. Lockheed Martin has developed a two-stage approach that combines a modified risk-return framework with a new concept, Innovation Readiness Levels (IRLs). Using a structure analogous to technology readiness levels (TRLs), IRLs offer a quantitative assessment of the organization's state of readiness to implement a specific business model and a measure of the amount of stress an idea is likely to create for the organization. This evaluation provides a surrogate metric for both required investment and the risk associated with the investment.

Managed Futures for Long‐Term Investors: A DEA Ranking Analysis

AbstractThis study proposes an alternative Data Envelopment Analysis ranking model to evaluate the relative performance efficiency of commodity‐trading advisors. I measure the performance efficiency using the decision‐making process quality/trading skills framework and depart from the traditional risk–return framework. The Data Envelopment Analysis rankings produced some interesting results. First, similarly to the previous studies, I successfully isolated two ‘superstar’ commodity‐trading advisors with the highest Sharpe ratios as the Grade A commodity‐trading advisors. However, as an improvement over the similar studies that used the traditional risk–return framework, I also isolated two commodity‐trading advisors with average and below‐average Sharpe ratios as Grade A commodity‐trading advisors.

Risk Horizon and Expected Market Returns

This paper tackles the issue of expected market return inside an equilibrium risk-return framework that accounts of the incomplete information on returns distribution and investors' preferences. Only moments up to order four of unknown unconditional distribution can be observed, and the model does not impose that moments preference should hold. Using Chebyshev-type inequalities, an intuitive risk measure, risk horizon, is introduced with reference to the speed of convergence of an asset's mean return to its expectations. An arbitrage argument enables us to link this risk measure to the maturity of treasury securities and to calibrate the model parameters using US market data. The expected market return can be endogenously estimated inside this system. Tests of statistical and economic predictive ability for US stock excess returns provide significant evidence on the forecasting value of the estimates.

Weakly inefficient markets: Stability of high-frequency trading strategies

Market participants who capitalize on high-frequency price dynamics and rely on automated trading are responsible, along with market makers, for the observed level of market efficiency. The remaining inefficiency is usually measured as the ratio of expected P&L, derived from the price signals, to its standard deviation. Such signals are also termed alpha in market slang. Signals and their volatility depend on time in a different manner, leading to temporal diversification and rise of multi-step strategies. It is shown that the coexistence of small market inefficiencies, multi-step strategies, and market impact lead to price randomization. In other words, high-frequency strategies redefine prices in their attempt to amplify weak price signals, and make markets more effective. In this paper we identify and explore discrete and continuous strategies. We further demonstrate that strategies within the domain of weak inefficiency are stable when incorporated into regular risk-return framework. In the presence of market impact we show how an efficiency edge propagates towards smaller time scales.

Weakly inefficient markets: Stability of high-frequency trading strategies

Market participants who capitalize on high-frequency price dynamics and rely on automated trading are responsible, along with market makers, for the observed level of market efficiency. The remaining inefficiency is usually measured as the ratio of expected P&L, derived from the price signals, to its standard deviation. Such signals are also termed alpha in market slang. Signals and their volatility depend on time in a different manner, leading to temporal diversification and rise of multi-step strategies. It is shown that the coexistence of small market inefficiencies, multi-step strategies, and market impact lead to price randomization. In other words, high-frequency strategies redefine prices in their attempt to amplify weak price signals, and make markets more effective. In this paper we identify and explore discrete and continuous strategies. We further demonstrate that strategies within the domain of weak inefficiency are stable when incorporated into regular risk-return framework. In the presence of market impact we show how an efficiency edge propagates towards smaller time scales.

Housing Risk and Return: Evidence from a HousingAsset-Pricing Model

Case, Cotter, and Gabriel investigate the risk–return relationship in the determination of housing asset pricing. In so doing, they evaluate the behavioral hypotheses advanced by Case and Shiller in studies of boom and post-boom housing markets. The authors specify a multifactor housing assetpricing model and evaluate whether the market factor and other measures of risk, including idiosyncratic risk, momentum, and MSA size effects, have explanatory power for metropolitan- specific housing returns. Further, they test the robustness of the asset pricing results to inclusion of controls for socioeconomic variables commonly represented in the house price literature, including changes in employment, affordability, and foreclosure incidence, and find a sizable and statistically significant influence of the market factor on MSA house price returns. Moreover, they show that market betas have varied substantially over time. Results are largely robust to the inclusion of other explanatory variables, including standard measures of risk and other housing market fundamentals. Additional tests of model validity using the Fama–MacBeth framework offer further strong support of a positive risk-and-return relationship in housing. Case, Cotter, and Gabriel’s findings are supportive of the application of a housing investment risk–return framework in explanation of the variation in the metro-area cross section and time series of U.S. house price returns. Further, results strongly corroborate the Case–Shiller survey research, which indicates the importance of speculative forces in the determination of U.S. housing returns. <b>TOPICS:</b>Real estate, analysis of individual factors/risk premia, equity portfolio management

Overall Lebanese Banks Performance: A Risk-Return Framework

The Lebanese commercial banks constitute the corner stone of the financing system in Lebanon. This paper analyzes the performance of the Lebanese banks in terms of profitability and risks for the period 1993 through 2002. A detailed investigation related to the structure and regulation of this industry is presented. The profitability is studied using the Du Pont equation and the overall risk of the Lebanese commercial banks is captured through the structure of the risk index suggested by Hannan and Hanweck (1998).

Housing Risk and Return: Evidence from a Housing Asset-Pricing Model

This paper investigates the risk-return relationship in determination of housing asset pricing. In so doing, the paper evaluates behavioral hypotheses advanced by Case and Shiller (1988, 2002, 2009) in studies of boom and post-boom housing markets. The paper specifies and tests a housing asset pricing model (H-CAPM), whereby expected returns of metropolitan-specific housing markets are equated to the market return, as represented by aggregate US house price time-series. We augment the model by examining the impact of additional risk factors including aggregate stock market returns, idiosyncratic risk, momentum, and Metropolitan Statistical Area (MSA) size effects. Further, we test the robustness of H-CAPM results to inclusion of controls for socioeconomic variables commonly represented in the house price literature, including changes in employment, affordability, and foreclosure incidence. Consistent with the traditional CAPM, we find a sizable and statistically significant influence of the market factor on MSA house price returns. Moreover we show thatmarket betas have varied substantially over time. Also, we find the basic housing CAPM results are robust to the inclusion of other explanatory variables, including standard measures of risk and other housing market fundamentals. Additional tests of the validity of the model using the Fama-MacBeth framework offer further strong support of a positive risk and return relationship in housing. Our findings are supportive of the application of a housing investment risk-return framework in explanation of variation in metro-area cross-section and time-series US house price returns. Further, results strongly corroborate Case-Shiller behavioral research indicating the importance of speculative forces in the determination of U.S. housing returns.

Weakly Inefficient Markets: Stability of High-Frequency Trading Strategies

Market participants who capitalize on high-frequency price dynamics and rely on automated trading are responsible, along with market makers, for the observed level of market efficiency. The remaining inefficiency is usually measured as the ratio of expected P&L, derived from the price signals, to its standard deviation. Such signals are also termed alpha in market slang. Signals and their volatility depend on time in a different manner, leading to temporal diversification and rise of multi-step strategies. It is shown that the coexistence of small market inefficiencies, multi-step strategies, and market impact lead to price randomization. In other words, high-frequency strategies redefine prices in their attempt to amplify weak price signals, and make markets more effective. In this paper we identify and explore discrete and continuous strategies. We further demonstrate that strategies within the domain of weak inefficiency are stable when incorporated into regular risk-return framework. In the presence of market impact we show how an efficiency edge propagates towards smaller time scales.

Issues in relation to discounted cash flow valuation

The current era of “convergence through connectivity” is slowly but certainly acknowledging the contribution of the so-called “intangibles” like brands, copyrights & patents, human & intellectual capital etc. to the bottomlines of companies. As an obvious corollary, issues relating to the valuation of such assets are surfacing with unprecedented regularity. Valuation of such assets posits an intriguing challenge for the accounting fraternity that is entrenched in the traditional ascendancy of “reliability” over “relevance”. “Discounted Cash Flow” is ubiquitous in financial valuation. In fact, this technique constitutes the cornerstone of contemporary valuation theory. The robustness of the model as well as its compatibility with the conventional two dimensional risk-return framework of investment appraisal make it immensely suited to a multitude of asset/liability valuations. Accounting standards across the globe recognize the efficacy of this model and advocate its use, wherever practicable. FAS 141 & 142 of the United States & IAS 39 that relate to the accounting of intangible assets also recommend use of DCF methodology for imputing a value to such assets. FAS 157 read with Concept Paper 7 mandate its use for ascertaining “fair value” of assets in certain cases. It is pertinent to note that the usual option pricing methods (including Black Scholes) also make use of discounted cash flows for calculating instantaneous option premia. However, like all models, DCF is not without its flaws. The model presupposes the existence of several unrealistic and rigid assumptions including, in particular, the existence of an acceptable “measure of risk” which is such that it can be integrated with the “discount” rate. In this article, we attempt to address all these issues. We start by highlighting the versatility of the DCF technique, how it can be adapted to value (literally) any asset/investment e.g. securities, projects, corporates and, now, intangibles as well. This enables us to perform a dissection of this model and adduce its anatomy. While on this, we also propose to explore interrelationships of DCF with other extant methods of valuations that include income multipliers, residual income, accrual accounting based methods etc. In today’s world of “fly by night” corporate operators, it is paramount to examine the susceptibility of a model to manipulations, and we also examine this facet of the DCF model by conducting a comprehensive sensitivity analysis with respect to the input variables that include estimated/projected cash flows, discount rates, horizon values, the existence of abandonment options etc. As is inevitable, the DCF methodology has its own spectrum of limitations. While concluding this article, we present some of the important shortcomings of this model and make recommendations on its possible upgradations to enhance its efficacy and reliability.

Investor perceptions and volatility within a risk-return framework

Conditional asset pricing models within the risk-return literature describe a relation between expected risk and return for period t + 1, with expectations formed during period t. Existing risk estimates in the literature are formed using backward looking measures during period t, which are projected forward for period t + 1. Evidence suggests that ex post observations do not always correspond with conditional ex ante expectations. Using forward-looking survey data, I compare measures of expected risk, with common estimates of risk in the literature. Supporting empirical research, I find a strong relation between forward-looking investor risk perceptions and conditional risk estimates.

Fidelity Magellan Fund, 1995

This case reviews the financial performance of the Fidelity Magellan Fund up to mid-1995. In essence, the Magellan Fund has managed to “beat the market” over time under three different fund managers despite its enormous size ($51 billion at the date of the case). The tasks for the student are to assess the adequacy of this performance, evaluate its likely sources, and opine on its sustainability. The case affords the opportunity to consider the appropriateness of various possible benchmarks in a risk-return framework and to assess the reasonableness of the efficient-markets hypothesis. The case can be used in an introductory finance course to present general information about equity markets and the behavior of large, sophisticated money managers.

Efficient Post-Retirement Asset Allocation

To examine post-retirement asset allocation, an extension to the classic Markowitz risk-return framework is suggested. Assuming that retirees make constant (real dollar) annual withdrawals from their portfolios, reward and risk measures are defined to be the mean and standard deviation of wealth remaining at end of life. Asset returns and time of death are both treated as random variables. Assuming constant lifetime asset allocation, the risk and reward measures can be evaluated analytically, and an efficient frontier can be determined. Life annuities can be used to extend the left-hand (low-risk) side of the efficient frontier. The desired level of wealth at end of life can be used to choose a desirable portfolio on the efficient frontier. The desirable portfolio strongly depends on the withdrawal rate. It is suggested (although not proven) that asset allocations strategies that vary with age do not add efficiency in this model, and asset allocation strategies that vary with wealth can add efficiency.

A criterion for comparing and selecting batsmen in limited overs cricket

The batting average statistic has been used almost exclusively to assess the worth of a batsman. It reveals a great deal about the potential performance of batsmen in cricket played at the first class level. However, in the one-day game, strict limits on the number of balls bowled have introduced a very important additional dimension to performance. In the one-day game, it is clearly not good enough for a batsman to achieve a high batting average with a low strike rate. Runs scored slowly, even without the loss of wickets, will generally result in defeat rather than victory in the one-day game. Assessing batting performance in the one-day game, therefore, requires the application of at least a two-dimensional measurement approach because of the time dimension imposed on limited overs cricket. In this paper, we use a new graphical representation with Strike rate on one axis and the Probability of getting out on the other, akin to the risk–return framework used in portfolio analysis, to obtain useful, direct and comparative insights into batting performance, particularly in the context of the one-day game. Within this two-dimensional framework we develop a selection criterion for batsmen, which combines the average and the strike rate. As an example of the application, we apply this criterion to the batting performances of the 2003 World Cup. We demonstrate the strong and consistent performances of the Australian and Indian batsmen as well as provide a ranking of batting prowess for the top 20 run scorers in the tournament.

Developing Country Economic Structure and the Pricing of Syndicated Credits

We use a hedonic pricing model to analyse in a risk–return framework the determinants of the pricing of a sample of over 5,000 syndicated credits granted to developing country borrowers between 1993 and 2001. We conclude that syndicated loans with riskier characteristics or granted to riskier borrowers are more expensive than others, although the effect of purely micro-economic price determinants is in several instances weaker when variables reflecting macro-economic conditions in borrowers' countries are introduced into the model. In addition to individual loan or borrower considerations, lenders seem to focus more on macro-economic factors to determine the pricing of their loans, such as the level of exports relative to debt service in the developing countries where the borrowers are located. For some, this means restricted access to external financing. We detect possible evidence of lenders exploiting their market power when lending to developing country borrowers. Certain banks appear to charge a premium to change initially agreed loan terms. Furthermore, discounts are granted on developing country loans provided by small groups or clubs of relationship banks rather than on facilities with participation by a large number of institutions.

Disaster Risk and Investment Guidelines

Traditional investment guidelines do not always work to reduce the risk of disaster. To better align investment guidelines with risk–return objectives, less emphasis should be placed on asset class allocations and credit risk constraints and more on liquidity concerns and managing the risks of embedded short option exposures. Transparency and risk-reporting requirements should no longer be optional, and downside risk-bearing capacity should be analyzed for both short- and long-term horizons. True long-term investors can still operate in a two-dimensional risk–return framework, and they can structure their guidelines to allow the portfolio to take advantage of liquidity risk (thus earning market premiums), complexity risk, and short option risk—risks that shorterterm investors with less risk-bearing capacity should avoid.

Fund Performance in a Downside Context

A risk-adjusted performance measure that focuses on total return and shortfall deviation, or downside risk, provides several advantages: consistency with investor reasoning, easy interpretation, and simplicity of calculation. Other risk-adjusted measures share the common feature of returns received relative to risk taken, but they all differ in definition and measurement of risk, thus affecting the overall evaluation. This article compares the performance and rankings of U.S. closed-end and open-end funds, U.K. unit trusts, and emerging market trusts using the different performance measures. Examination of fund performance rankings according to the specific measure used shows that downside risk is a valuable concept in the risk-return framework, especially in high-risk markets.