Dynamic Investment Strategies Research Articles

Management of Market Assets in Crisis

Introduction, Purpose . Most of the classic and modern investment models do not take into account the crisis processes in the economy. This happens mostly because crises are not studied well enough and serious researches are to be made in this sphere. Methods . This paper offers a model for estimating the market condition, considering the five edge states: crisis growth, growth, stagnation, recession, crisis recession. In this paper has been developed a crisis indicator, which can be the basis for determination of the crisis initial phase. Results . A concept of a dynamic portfolio model, adapting to the market changes, has been introduced to manage market assets. Adaptation of the investment portfolio occurs according to the crisis processes in economy. Investment is understood as a process of buying assets for profit-making. The term “strategic investment” is used to refer to long-range investments. Financial assets exist in various forms and may range from almost completely safe low yield government bonds to international assets that are at much greater risk and produce more profit. Discussion . Usually investor owns an assets bundle. A set of financial assets, bounded by a single investment strategy, is called an investment portfolio. Warren Buffett states that a profitable investment strategy should be long-ranged with selection of the right assets. For managing the market assets the authors suggest the use of the dynamic investment strategy which adapts to the crisis.

Do mutual fund ratings provide valuable information for retail investors?

PurposeRetail investors use information provided by mutual fund rating agencies to make investment decisions. This paper aims to examine whether the ratings provide useful information to retail investors by analyzing the rating migration and closure risk of mutual funds that received Morningstar’s mutual fund ratings from 2005 to 2012.Design/methodology/approachThe research design differentiates between buy-and-hold investment strategies and dynamic investment strategies. To assess the information content of mutual fund ratings for buy-and-hold investment strategies, the rating migration based on the first and the last mutual fund rating during two-, four-, six- and eight-year horizons is determined. With respect to dynamic investment strategies, the number of rating changes per fund on a monthly basis during these time horizons is calculated.FindingsMutual fund rating persistence is low or even inexistent, in particular, during longer time periods. Only for lower-rated funds, the rating appears to indicate higher risk of fund closure. In addition, mutual funds face a large number of up to 38 monthly rating changes in the eight-year window.Originality/valueMutual fund rating persistence has hardly been analyzed for funds offered to retail investors so far. This paper clearly points out that because of the extensive rating migration and the high number of monthly rating changes, retail investors barely benefit from using mutual fund ratings.

Dynamic pricing, quality investment, and replenishment model for perishable items

AbstractThe deterioration of perishable items results not only in direct quantitative losses, but also in qualitative losses, which would reduce the customer acceptability. To maintain or improve the quality level, sellers usually invest in functionality, aesthetics, safety or any other attributes. In addition to quality, price also plays a critical role in influencing the purchase choice of consumers and the profit of a firm. Most inventory management models for perishables are restricted to physical quantity deterioration and do not address joint dynamic pricing and quality investment strategies. This paper studies an optimal replenishment model with dynamic pricing and quality investment for perishable products, where the quality and physical quantity deteriorate simultaneously. The demand rate is decreasing in sales price and increasing in quality level. A dynamic optimization model is proposed to maximize the total profit per unit time and solved on the basis of Pontryagin's maximum principle. The optimal joint dynamic pricing, quality investment, and replenishment policy is obtained. A numerical example and sensitivity analysis on the key system parameters are presented to illustrate the validity of the theoretical results. Some managerial implications for the pricing and quality investment for the perishables are provided.

Dynamic derivative-based investment strategy for mean–variance asset–liability management with stochastic volatility

This paper considers the derivative-based optimal investment strategies for an asset–liability management (ALM) problem under the mean–variance criterion in the presence of stochastic volatility. Specifically, an asset–liability manager is allowed to invest not only in a risk-free bond and a stock, but also in a derivative, whose price depends on the underlying price of the stock and its volatility. By solving a system of two backward stochastic differential equations, we derive the explicit expressions of the efficient strategies and the corresponding efficient frontiers in two cases, with and without the derivative asset. Moreover, we consider the special case of an optimal investment problem with no liability commitment, which is also not studied in the literature. We also provide some numerical examples to illustrate our results and find that the efficient frontier of the case with the derivative is always better than that of the case without the derivative. Moreover, under the same variance, the expectation of the case with the derivative can reach up to as twice as that of the case without the derivative in some situations.

Tail Risk and Robust Portfolio Decisions

Both asset return and consumption disasters exhibit slowly-decaying tail behavior admitting severe downside risk. To investigate the effects of tail risk on optimal portfolio choice, we solve for the dynamic investment strategy in a multi-asset incomplete market with ambiguous jump risk. Out of the fear of extreme tail events in the worst case scenario, an ambiguity-averse investor tends to reduce her jump exposure, and an extremely ambiguity-averse investor may not hold any risky asset. We estimate the model on international equity indices and compare optimal portfolios under normally distributed jumps and heavy-tailed jumps obeying a power-law. Under rational expectation, an investor with a constant relative risk aversion (CRRA) utility function incurs negligible losses from ignoring extreme tail events, once the first two moments of the jump distributions are preserved. In stark contrast, the investor with aversion to uncertain tail risk suffers sizable economic losses. We also find that uncertain consumption tail risk enhances the option implied volatility smirk and variance risk premia in market equilibrium.

Time-Varying Risk Premiums and Economic Cycles

Asset returns are not correlated with the business cycle but are primarily caused by the economic cycles. To validate this claim, economic cycles are first rigorously defined, namely the classical business cycle and the growth cycle, better known as the output gap. The description of different economic phases is refined by jointly considering both economic cycles. It improves the classical analysis of economic cycles by considering sometimes two distinct phases and sometimes four distinct phases. The theoretical influence of economic cycles on time-varying risk premiums is then explained based on two key economic concepts: nominal GDP and adaptive expectations. Simple dynamic investment strategies confirm the importance of economical cycles, especially the growth cycle, for euro and dollar-based investors. At last, this economic cyclical framework can improve strategic asset allocation choices.

Dynamic Investment Strategies and Leadership in Product Innovation

We employ a dynamic market model with endogenous creation of submarkets to study the optimal product innovation strategies of incumbent firms. Firms invest in production capacity and R&D knowledge stock, where the latter determines the hazard rate of innovation. We find that under Markov Perfect Equilibrium behavior the firm with a larger market share on the established market is less likely to be the first innovator. Investment in R&D knowledge is negatively affected by the opponent's production capacity on the established market if the opponent has not innovated yet. However, this effect is reversed after the opponent has successfully introduced the new product. The firm with higher costs of adjusting capacity for the established product has a larger incentive to engage in product innovation and might even achieve higher long run profit than its more efficient competitor.

Dynamic factor long memory volatility

In this paper, we develop a long memory orthogonal factor (LMOF) multivariate volatility model for forecasting the covariance matrix of financial asset returns. We evaluate the LMOF model using the volatility timing framework of Fleming et al. [J. Finance, 2001, 56, 329–352] and compare its performance with that of both a static investment strategy based on the unconditional covariance matrix and a range of dynamic investment strategies based on existing short memory and long memory multivariate conditional volatility models. We show that investors should be willing to pay to switch from the static strategy to a dynamic volatility timing strategy and that, among the dynamic strategies, the LMOF model consistently produces forecasts of the covariance matrix that are economically more useful than those produced by the other multivariate conditional volatility models, both short memory and long memory. Moreover, we show that combining long memory volatility with the factor structure yields better results than employing either long memory volatility or the factor structure alone. The factor structure also significantly reduces transaction costs, thus increasing the feasibility of dynamic volatility timing strategies in practice. Our results are robust to estimation error in expected returns, the choice of risk aversion coefficient, the estimation window length and sub-period analysis.

Value of employee satisfaction during the financial crisis

Purpose The purpose of this paper is to examine how employee satisfaction affects firm value around the financial crisis. Design/methodology/approach The authors use the 2008 financial crisis as exogenous shocks to firms to mitigate endogenous concern that employee satisfaction and firm value can be jointly determined. The authors compare firm value of two groups of firms: the firms on the Fortune magazine’s list of “100 Best Companies to Work For” and matched firms that are not on the list. The authors employ difference-in-difference approaches in the tests. Findings The authors find that when the crisis happens, the best companies experience larger decreases in firm value than comparable firms. In addition, such decreases in firm value only exist among the best companies with high financial flexibility. The authors also show that job satisfaction alone does not create firm value during the financial crisis; only when interacted with high financial flexibility, employee satisfaction leads to high firm value. Finally, the authors document that best companies do not have any advantage in the recovery of firm value after the crisis, regardless of their level of financial flexibility. Research limitations/implications There is considerable debate on whether job satisfaction leads to performance or performance leads to satisfaction (Luthans, 1998). The authors show that the impact of employee satisfaction on firm value changes over time. The authors also identify a crucial factor that impacts the value-creation of employee satisfaction: financial flexibility. The findings suggest that the ambiguous results documented in prior literature can be due to the different sample periods and the failure to identify the impact of financial flexibility in previous studies. Practical implications The findings provide helpful implications to the business community. The evidence suggests that to reap the benefits of employee satisfaction, companies need to manage their financial flexibility to buffer against potential negative shocks while having strong corporate governance mechanism to mitigate agency concerns. Moreover, the study provides an investment recommendation to socially responsible investment (SRI) and suggests that it is better off implementing dynamic SRI investment strategies according to economic condition. Social implications The evidence suggests that the economic value of employee satisfaction is related to firms’ financial flexibility and economic conditions. Originality/value The authors contribute to the literature by showing that the impact of employee satisfaction on firm value changes over time. The test design not only allows the authors to study the effect of employee satisfaction on firm value at a particular point in time, but also helps the authors examine the variation in the effect over economic cycles. This paper also contributes to the literature on SRI. The authors identify a crucial factor that impacts the value-creation of employee satisfaction: financial flexibility.

The Long and Short of Trend Followers

We propose the use of short and long portfolios of trend-following strategies to analyze their risk and return characteristics. We find that their exposures are time-varying, depend on the market state, and that returns to their long and short sides in the same asset are not comparable. In addition, we present evidence for occasional long-biased discretion by CTA managers. Our findings are in line with the adaptive markets hypothesis, and the main lesson of our study is that the long and short sides should be differentiated in the analysis of dynamic investment strategies.

Hedging Climate Risk

We present a simple dynamic investment strategy that allows long-term passive investors to hedge climate risk without sacrificing financial returns. We illustrate how the tracking error can be virtually eliminated even for a low-carbon index with 50% less carbon footprint than its benchmark. By investing in such a decarbonized index, investors in effect are holding a “free option on carbon.” As long as climate change mitigation actions are pending, the low-carbon index obtains the same return as the benchmark index; but once carbon dioxide emissions are priced, or expected to be priced, the low-carbon index should start to outperform the benchmark.

Inflation Protected Investment Strategies

In this paper, a dynamic inflation-protected investment strategy is presented, which is based on traditional asset classes and Markov-switching models. Different stock market, as well as inflation regimes are identified, and within those regimes, the inflation hedging potential of stocks, bonds, real estate, commodities and gold are investigated. Within each regime, we determine optimal investment portfolios driven by the investment idea of protection from losses due to changing inflation if inflation is rising or high, but decoupling the performance from inflation if inflation is low. The results clearly indicate that these asset classes behave differently in different stock market and inflation regimes. Whereas in the long-run, we agree with the general opinion in the literature that stocks and bonds are a suitable hedge against inflation, we observe for short time horizons that the hedging potential of each asset class, especially of real estate and commodities, depend strongly on the state of the current market environment. Thus, our approach provides a possible explanation for different statements in the literature regarding the inflation hedging properties of these asset classes. A dynamic inflation-protected investment strategy is developed, which combines inflation protection and upside potential. This strategy outperforms standard buy-and-hold strategies, as well as the well-known 1 N -portfolio.

Dynamic Learning Process for Selecting Storm Protection Investments

Increasingly aggressive weather events, such as hurricane-driven storm surges, threaten surface transportation systems and motivate defensive actions, including hardening. Decisions about the design and scale of hardening investments are informed by meteorological records. Historically based probabilities of severe storms are used in practice to define expected values of the intensity of weather assaults (e.g., the 100-year storm) and then to select defenses. The prospects of climate change and rising sea level suggest that assuming weather events are stationary may present added risks to surface transportation infrastructure, particularly in coastal environments. This paper proposes a dynamic, learning-based investment strategy, similar to the concept of real options, that updates estimates of storm surges on the basis of experience and recommends incremental hardening investments when observed trends indicate that additional defense is warranted. Monte Carlo simulation is used to compare and evaluate static (expected value-based) and dynamic investment strategies in the context of storm intensity patterns that are ( a) known, ( b) incorrectly estimated, and ( c) nonstationary, with growing intensity. Results suggest that when the future is well described by past experience, the static, once-and-done decision strategy works well, but when the underlying storm generation process is unknown, or when it is changing (growing) in intensity, the learning-based dynamic strategy is especially advantageous. These results underscore the importance of flexibility in designing storm protection, of tracking weather events closely to detect emerging trends, and of data-driven decision strategies. This dynamic approach to decision making under uncertainty can be applied to other sources of uncertainty, for example, demand estimates.

Is Ethical Money Sensitive to Past Returns? The Case of Portfolio Constraints and Persistence in Islamic Funds

In this paper, we analyze the performance persistence and survivorship bias of Islamic funds. The remarkable growth of these types of ethical funds raises the question of how non-financial attributes, including beliefs and value systems, influence performance and its persistence. A procedure commonly used in prior literature to assess persistence is the measuring of the performance of investment strategies based on past performance. In this context, we propose a refined version of this methodology that controls the cross-sectional significance of the performance of these strategies. This procedure correctly identifies whether abnormal performance is due to a dynamic investment strategy based on past performance, or whether it is obtained by investing in a particular set of mutual funds. The significance of the persistence varies depending on the time horizon (yearly/half-yearly), survivorship, or the tail of the distribution. In particular, we find that persistence only exists for the best funds, whereas for the worst funds, the results are not significant.

International Asset Allocation with Regime Switching: Evidence from the ETFs

AbstractWe develop a dynamic investment strategy with Markov regime switching (MRS) in asset allocation with international iShares exchange‐traded funds (ETFs). Using daily ETF data, we show that a portfolio based on the dynamic MRS strategy outperforms one based on static mean‐variance strategies after transaction costs. This dynamic investment strategy not only captures the regime shifts in the highly frequent trading process but also can be practically used with tradable ETFs. We investigate the reasons for predictive misjudgments and assess the contribution of each regime's investment strategy, providing insight into the characteristics of the MRS model and modifying our views on why the MRS strategy outperforms traditional strategies.

On the stochastic elasticity of variance diffusions

The elasticity of variance of risky assets has been observed to be rapidly fluctuating around a level. The level itself slowly varies depending upon the corresponding economic situation at the time of consideration. In particular, it turns out to be extraordinary during the peak period of the 2007–2009 Global Financial Crisis. Based on the concept of stochastic elasticity of variance, this paper develops an asset price model in a multiscale form and applies it to the pricing of European options and verifies a significant improvement over the constant elasticity of variance model in terms of the geometric structure (skew or smirk) of implied volatility. Our result implies that a theoretical model based on the random elasticity can derive market's volatility forecast more accurately than the constant elasticity so that investors can employ a dynamic investment strategy reducing risk more effectively.

PORTFOLIO OPTIMIZATION IN AFFINE MODELS WITH MARKOV SWITCHING

We consider a stochastic-factor financial model wherein the asset price and the stochastic-factor processes depend on an observable Markov chain and exhibit an affine structure. We are faced with a finite investment horizon and derive optimal dynamic investment strategies that maximize the investor's expected utility from terminal wealth. To this end we apply Merton's approach, because we are dealing with an incomplete market. Based on the semimartingale characterization of Markov chains, we first derive the Hamilton–Jacobi–Bellman (HJB) equations that, in our case, correspond to a system of coupled nonlinear partial differential equations (PDE). Exploiting the affine structure of the model, we derive simple expressions for the solution in the case with no leverage, i.e. no correlation between the Brownian motions driving the asset price and the stochastic factor. In the presence of leverage, we propose a separable ansatz that leads to explicit solutions. General verification results are also proved. The results are illustrated for the special case of a Markov-modulated Heston model.

Dynamic Investment Strategy with Factor Models Under Regime Switches

A model for dynamic investment strategy is developed where assets’ returns are represented by multiple factors. In a mean–variance framework with factor models under regime switches, we derive a semi-analytic solution for the optimal portfolio with transaction costs. Due to the existence of transaction costs, the optimal portfolio is characterized as a linear combination of current and target portfolios, the latter of which maximizes the value function in the current regime. For some special cases of interest, we also derive simplified analytical solutions. To see the effect of regime switches, the proposed model is applied to US equity market in which small minus big and high minus low are employed as factors. Investment strategy based on our model demonstrates empirically that the regime switching models exhibit superior performance over the single regime model for such performance measures as realized utility and Sharpe ratio which are of particular interest in practice. Taking a close look at the time series of portfolio returns, the result shows the usefulness of the regime switching model as investors flexibly optimize asset allocations depending on the state of the market.

Dynamic Strategies for Net Income Generation in a Low Interest Rate Environment

Abstract This paper explores some dynamic investment strategies based on interest rate derivatives to generate income. The low interest rate environment makes this question critical to public institutional investors and potentially their asset-liability management. There exists a trade-off between the potential level income generated for the medium/long term on one side, and, the uncertainty of this income and its associated mark-to-market volatility through time, on the other side. First, we develop the foundations of the Libor market model (LMM) initially calibrated using data from swaptions for USD and EUR markets. Then different types of eligible strategies for the stabilization of the net income are provided. The strategies are mostly based on interest rate derivatives – swaps, caps, floors and swaptions –, and they may be partially rule-based and/or self-financed and may allow for tactical decision. Finally, the importance of the institutional framework and the role of the governance are discussed, e.g. the impact of mark-to-market based investment rules on the degree of path-dependency of the implemented strategies.

Hedging Climate Risk

This paper presents a simple dynamic investment strategy that allows long-term passive investors to hedge climate risk without sacrificing financial returns. We illustrate how tracking error can be almost eliminated even for a low carbon index that has 50% less carbon footprint than its benchmark. By investing in such a decarbonized index, investors are holding in effect a “free option on carbon”: as long as the introduction of significant limits on CO2 emissions is postponed our low carbon index obtains the same return as the benchmark index, but when CO2 emissions are integrated by the market, it starts outperforming the benchmark.