Downside Protection Research Articles

Tracking Smart Beta indices during different market phases: A “smarter” option for passive investors?

PurposeThis study aims to examine whether tracking Smart Beta (SB) indices during bullish, bearish and stagnant market phases is a better choice for passive investors compared to Cap-Weighted (CW) indices. As investors’ strategies differ with market movements, this study analyses how single-factor and multi-factor SB indices perform during different market phases, in relation to CW indices. It also attempts to determine which SB factors are more suitable for investors in these phases.Design/methodology/approachUsing various return and risk indicators, this study analyses how SB indices perform vis-à-vis CW indices during bullish, bearish and stagnant phases. The authors also evaluate the upside and downside participation advantage of SB indices and assess their ability to capture upside returns and limit downside risk. The authors attempt to determine the cyclical or defensive nature of SB indices using Average Participation values.FindingsThis study found that SB indices outperform CW indices during the bearish and stagnant phases. Multi-factor SB indices have lower risk levels in all market phases, providing downside protection to risk-averse investors. Dividend, Low Volatility, Quality and multi-factor SB indices are defensive portfolios offering better payoffs during the down market phases, while Alpha, Beta, Equal Weight and Value SB indices provide higher payoffs during the up-market phases.Originality/valueTo the best of the authors’ knowledge, this is the first study that examines the performance of single-factor and multi-factor Indian SB indices in different market phases. It determines the suitability of various factors to passive investors during these phases and also identifies whether SB indices are cyclical or defensive.

Local Agglomeration and Household Mortgage Debt

Using detailed household data, we find that households working in locally agglomerated economies have high mortgage loans and are more likely to have mortgage loans. Channel testing shows that local agglomeration increases housing and mortgage demand as well as mortgage supply. The increase in mortgage loans is driven by purchases of larger houses and smaller down payments. Mechanism analyses document that local agglomeration affects mortgage loans by increasing career upward potential and providing downside protection. Specifically, we find that the impact of local agglomeration is stronger for skilled employees with enhanced prospects. In addition, local agglomeration weakens the negative relation between unemployment and mortgage loans, which supports the downside-protection role of local agglomeration. These results hold under instrumental variables analysis, difference-in-difference analysis, and a set of robustness checks. Overall, our findings highlight the importance of local labor market composition in household mortgage debt. This paper was accepted by Kay Giesecke, finance. Funding: F. F. Chen acknowledges the financial support provided by the Fundamental Research Funds for the Central Universities; the MOE Project of Key Research Institute of Humanities and Social Science in University [Grant 22JJD790094]; and the 111 Project [Grant B18033]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.03486 .

Optimal Portfolios for Large Investors in Housing Markets Under Stress Scenarios: A Worst-Case Approach

AbstractThe study focuses on constructing a mathematical housing market threatened by a major catastrophic event or crash. It incorporates the worst-case scenario portfolio optimization problem as introduced in Korn and Wilmott (Int J Theor Appl Finance 5(02):171–187, 2002) into housing markets. The standard stochastic models for housing markets assume a geometric Brownian motion and neglect sudden housing price falls during crash times. However, the size, timing, and frequency of crashes have to be included in such models. By incorporating the worst-case portfolio optimization problem into housing markets, this study introduces a methodology to construct portfolios for large investors that are robust and resilient to extreme housing market conditions. The worst-case portfolio optimization approach can be used in housing markets to incorporate stress scenarios, minimize potential losses, utilize mathematical techniques, and manage housing investment risk effectively. This study provides valuable insights for large investors seeking to construct housing portfolios prioritizing downside protection and minimizing losses in extreme housing market conditions. Utilizing numerical illustrations, it provides insights into portfolio construction, demonstrating the effectiveness of adjusting portfolios to mitigate downside risks during housing market crises. The results highlight dynamic portfolio management’s significance in safeguarding wealth when housing prices undergo significant fluctuations.

Hedging Dynamic Fund Protection: A Static Versus Dynamic Comparison

The static nature of the downside protection offered by a standard Put option can motivate investors to use exotic option contracts like dynamic fund protection (DFP), which protects the underlying asset value throughout its life. DFP has a path-dependent payoff structure with its terminal payoff depending on the terminal asset price, the strike price and the minimum price level attained by the asset over the contract tenor. This makes DFP a contract strikingly similar to a Lookback Call option. In this article, we try to borrow the respective strengths from a dynamic and a static hedging strategy, formulate a semi-static hedging procedure for DFP and compare the hedging effectiveness of this procedure with a standard delta hedging strategy. Given the payoff resemblance between a DFP and a Lookback Call, we also seek to verify Tompkins (2002, Journal of Risk Finance, 3(4), 6–34) conclusion, which objectively shows that a dynamic procedure performs better in hedging a Lookback Call option both with and without transaction cost. Using simulated underlying price paths, we perform the delta hedging on DFP based on the closed-form pricing formula given by Gerber and Pafumi (2000, North American Actuarial Journal, 4(2), 28–37) and compare the hedge performance results with its static hedge counterpart.

Optimizing upside variability and antifragility in renewable energy system design

Despite the considerable uncertainty in predicting critical parameters of renewable energy systems, the uncertainty during system design is often marginally addressed and consistently underestimated. Therefore, the resulting designs are fragile, with suboptimal performances when reality deviates significantly from the predicted scenarios. To address this limitation, we propose an antifragile design optimization framework that redefines the indicator to optimize variability and introduces an antifragility indicator. The variability is optimized by favoring upside potential and providing downside protection towards a minimum acceptable performance, while the skewness indicates (anti)fragility. An antifragile design primarily enhances positive outcomes when the uncertainty of the random environment exceeds initial estimations. Hence, it circumvents the issue of underestimating the uncertainty in the operating environment. We applied the methodology to the design of a wind turbine for a community, considering the Levelized Cost Of Electricity (LCOE) as the quantity of interest. The design with optimized variability proves beneficial in 81% of the possible scenarios when compared to the conventional robust design. The antifragile design flourishes (LCOE drops by up to 120%) when the real-world uncertainty is higher than initially estimated in this paper. In conclusion, the framework provides a valid metric for optimizing the variability and detects promising antifragile design alternatives.

Constant or Variable? A Performance Analysis among Portfolio Insurance Strategies

In this paper, we propose a comparison among three portfolio insurance strategies, namely the constant proportion portfolio insurance, the time-invariant portfolio protection, and the exponential proportion portfolio insurance, via an in-depth performance analysis. We aim to ascertain whether strategies characterized by variable parameters can outperform those with constant parameters by measuring potential returns, investment riskiness, downside protection capability, and ability to capture market upside. The results, achieved in a model-free framework by exploiting bootstrapping techniques, advise that no winning strategy exists overall, even when considering different volatility regimes, rebalancing frequencies, and protection levels.

Comparing Downside Protection Strategies

In this article, the author uses a common framework to evaluate and compare various equity downside protection strategies including constant proportion portfolio insurance, volatility targeting, and a few option-based strategies in terms of the trade-off between downside protection and upside participation. Using the downside-to-upside performance ratio to measure that trade-off, the author finds that all these strategies offer the same trade-off over the many market cycles from 1996 to 2020. However, strategies with a concave payoff profile (such as put spread collar used in buffered exchange-traded funds or defined outcome exchange-traded funds) offer a better trade-off during the early stage of drawdown and recovery, and strategies with a convex payoff profile such as constant proportion portfolio insurance offer a better trade-off during the late stage of drawdown and recovery. The author’s results and insights allow investors to enhance their understanding of downside protection strategies and select the best strategy for their investment use case.

Portfolio optimization using cellwise robust association measures and clustering methods with application to highly volatile markets

This paper introduces the minCluster portfolio, which is a portfolio optimization method combining the optimization of downside risk measures, hierarchical clustering and cellwise robustness. Using cellwise robust association measures, the minCluster portfolio is able to retrieve the underlying hierarchical structure in the data. Furthermore, it provides downside protection by using tail risk measures for portfolio optimization. We show through simulation studies and a real data example that the minCluster portfolio produces better out-of-sample results than mean-variances or other hierarchical clustering based approaches. Cellwise outlier robustness makes the minCluster method particularly suitable for stable optimization of portfolios in highly volatile markets, such as portfolios containing cryptocurrencies.

A Study on Optimizing Risk and Return through Options Trading Strategies

Options offer elective systems for financial specialists to benefit from trading underlying securities. There are assortments of methodologies including diverse blends of options, underlying assets, and other derivatives. Fundamental Strategies includes purchasing calls, purchasing puts, selling covered calls and purchasing protective puts. There are points of interest to trading choices instead of underlying assets, for example, downside protection and leveraged returns, however there are additionally burdens like the necessity for upfront premium payment. Here in the report an endeavor is to make to build up the methodologies dispensing with those disadvantages through direct of nitty gritty investigation on Nifty Index. The premium expenses being pursued to be the major influencing factor of options market, an attempt is made to optimize the risk and return by developing the effective trading strategies for the option traders irrespective of market conditions with special reference to NIFTY Index. As a part of study suggestions are drawn for the investors to improve their trading strategies without undertaking great deal of risk. This paper analyses the use of different option trading strategies for optimizing risk and return in both bullish and bearish markets. A study on optimizing risk and return through developing effective index options trading strategies is an attempt to apply the theoretical knowledge’s application and exposure to practical world of derivative market.

A win-win partnership for affordable homeownership solutions by connecting responsible investors, community housing providers, and government

Many studies have examined the affordable housing sector from the welfare perspective, but no study has discussed the sector's investment perspective. Therefore, this study presents new evidence of the governance and downside protection relating to the affordable housing sector and contributes to the limited literature on the performance of socially responsible investments. First, we identified the specific risk management and corporate governance practices of the affordable housing sector in Australia by conducting focus-group discussions with industry experts. The sector's strong governance helps to attract responsible investors by reducing investment risk and guaranteeing environmental and social outcomes. Second, by analyzing the downside risk and risk-adjusted returns such as the Sortino ratio and excess return to value at risk, we show that investing in low-priced houses has more downside protection while still offering higher risk-adjusted returns, than high-priced houses and selected responsible investments in Australia. We also find that investing in low-priced houses can improve the portfolio performance of responsible investors. Therefore, we conclude that the affordable homeownership programs in Australia have the potential to attract responsible investments and so increase the supply of much-needed affordable houses.

A “Quality” Quality Factor

This article examines the concept of quality as a factor commonly used in portfolio management. Although value and momentum are fairly well-established constructs, the third major factor in many models, quality, is not so well articulated. This research aggregates the most common components of quality into a parsimonious, well-defined factor (QAL) using the data reduction technique known as partial least square. The authors show that their factor has power independent of the other factors and significant return in excess of common risk models. Moreover, their QAL factor possesses favorable downside risk properties and works as a superior hedge during turbulent market performance periods, which they contend is the main feature one would expect of assets with high quality. Additionally, adding the authors’ QAL to an opportunity set consisting of other factors, as well as a traditional 60/40 equity/fixed income portfolio, increases the Sharpe ratio and improves downside protection simultaneously because of its diversifying effect.

The impact of Bank of Japan’s exchange-traded fund purchases

The Bank of Japan (BOJ) enhanced its large-scale asset purchases in October 2010 by purchasing equity exchange-traded funds (ETFs). This study is the first to demonstrate that the BOJ provides downside protection for stock prices through the countercyclical purchase of ETFs. The BOJ responds to a large negative stock return during the overnight and morning periods, and submits purchase orders during lunchtime. Using the BOJ’s March 2020 announcement of doubling the annual purchase amount during the COVID-19 pandemic, this study also finds that the announcement effect is small and temporary. In contrast, the flow effect of the actual purchases is significant and increases. The BOJ’s countercyclical ETF purchase prevents equity risk premia from rising during an economic downturn.

The origin of LYONs: A case study in financial innovation

The origin of LYONs: A case study in financial innovation

Environmental, social, and governance (ESG) model; impacts and sustainable investment – Global trends and Poland's perspective

In recent years, financial markets have been hit hard by the Great Financial Crisis of 2008, the acceleration of climate change, and now the COVID-19 pandemic. The result of these events is the acceleration of the implementation of a new model of socioeconomic development of societies referred to as the environmental, social, and governance (ESG) model. It has been particularly evident in the financial investment sector. Analyses of the relative performance of ESG funds is inconclusive due to the lack of a clear definition of responsible investments, and insufficient quality of the available data and ESG ratings. However, most of the studies find a positive correlation between ESG factors and company's financial performance. The analyses showed that these positive results are more pronounced over the longer term and impact the stock prices of those companies. ESG funds offer better downside protection during crises in relation to traditional funds. Despite the lack of legal barriers, the Polish economy has experienced very long delays in implementing the ESG model and the gap is even more pronounced in the financial industry. This is surprising as Poland is a very interesting market for sustainable investment given its current underdevelopment and overall potential related to green transformation. In Poland, only 17 investment funds deeply integrate ESG criteria. Educational and communication barriers have been identified as the main obstacles to the development of the sustainable finance market in Poland. Education of all participants in investment processes is a prerequisite for success.

Connectedness and spillover effects of US climate policy uncertainty on energy stock, alternative energy stock, and carbon future.

Global warming is pressuring policymakers to change climate policies in shifting the global economy onto a net-zero pathway. While financial assets are responsive to policy changes and development, climate change policies are becoming increasingly unpredictable, making policy decision less certain. This study investigates connectedness and spillover effects of US climate policy uncertainty on energy stocks, alternative energy stocks, and carbon emissions futures. We analyzed spillover and connectedness before and after the Paris Agreement. We employed monthly frequency data from August 2005 to March 2021 and applied DY (2012) method and MGARCH approach. We found that world energy stocks and carbon emissions futures are connected to US climate policy uncertainty. Uncertainty in climate policy and world energy stocks act as information transmitters in return spillover, while global alternative energy and carbon market are shock receivers. On volatility spillover, climate policy uncertainty, energy stocks, and carbon emissions future are shocks transmitters, while alternative energy stocks are receivers. We observe increase in connectedness following the Paris Agreement suggesting strengthened global efforts in tackling climate change. DCC and ADCC estimations revealed spillover effects of climate policy on futures returns and volatilities of world energy stocks and carbon emissions futures and the shocks could be transmitted through to the energy sector. During period of uncertainty in US climate policy, carbon allowances can potentially serve as a safe haven for energy stocks and provide downside protection for alternative energy stocks, hence hedging against climate transition risks.

Hedged Mutual Funds and Competition for Sources of Alpha

Hedged mutual funds flourished following the 2007–2009 financial crisis. They became particularly popular with financial advisors because of their alleged downside protection. Did these funds deliver what they promised? We examine the performance of these funds with a focus on the post-2009 period. While they generated positive alphas before the crisis, we find that this abnormal performance vanishes in the post-2009 period as their strategies became increasingly crowded due to the above popularity. We show that flows to hedged mutual funds are negatively related to investor sentiment, implying that investors use these funds as a hedge against downside risk.

On the Effectiveness of Stock Index Futures for Tail Risk Protection

This paper examines the effectiveness of using stock index futures contracts as substitutes for fixed-income securities in implementing expected shortfall targeting strategy. We find that the futures-based implementation outperforms its index-and-bill counterpart both in terms of downside protection and risk-adjusted performance at daily rebalancing frequency. This outperformance is driven not only by the transaction cost advantage, but also by the replication imperfections due to futures mispricing providing over the long term a better participation in upward market movements. When less frequent rebalancing intervals are used, the futures-based implementation becomes less effective at protecting the downside risk but still capture better the upside potential of the index.

The Impact of Options on Investment Portfolios in the Short-Run and the Long-Run, with a Focus on Downside Protection and Call Overwriting

In this article, we analyse the impact of the introduction of options on an investment portfolio. Our first objective is to derive closed-form formulae for the standard measures of portfolio efficiency: risk premium, risk, Sharpe ratio, and beta, of any portfolio containing any combination of options. Using these formulae on three examples of simple option strategies (call overwriting, put protection, and collars), we show how these statistics are altered by the inclusion of an option overlay in a portfolio. Our second objective is to show that if an option strategy is repeated over multiple investment time periods, the long-run return becomes normally distributed. Our motivation is to provide investors with the mathematics to measure the impact of the introduction of options on portfolio efficiency and encourage a potential portfolio rebalance to account for this impact. Then, we highlight that whilst options can create asymmetric non-normal outcomes, their repeated use may not alter the long-run portfolio return in the desired way and thus to encourage investors to assess if an option overlay will deliver the desired long-run outcome.

Did ESG Save the Day? Evidence From India During the COVID-19 Crisis

Investors have shown increasing interest in Socially Responsible Investments (SRI) in the past few years, especially during the financial crisis caused due to the outbreak of the COVID-19 pandemic. SRI are evaluated on the basis of Environmental, Social and Governance (ESG) criteria. ESG information allows investors to assess the risks associated with a particular firm and how the firm manages or intends to manage future risks. Amidst the increasing investor interest in ESG products, we attempt to study the value addition of ESG performance to investors during crisis period. Using a sample of ESG rated firms listed on the Bombay Stock Exchange (BSE), we examine the investment performance, trading volumes and return volatility of ESG stocks in an emerging market like India during the COVID-19 crisis. The results of our event study conducted around the important events that have occurred in India during the COVID-19 pandemic provide evidence that investors can use ESG information as a signal of future stock performance. Most importantly, ESG performance provides downside protection during crisis times. Our results show that ESG performance does not prove to be detrimental to investment performance during normal times. Also, ESG performance was found to reduce stock return volatility during the COVID-19 pandemic. Overall, our study attempts to establish an investment case for ESG stocks in emerging markets in India by providing support to the good management hypothesis.

The Dynamics of Risk: Implications for Asset Allocation Strategies

Investors should have a sharper focus on the time dimension of risk and correlation metrics for the largest asset classes of equity and debt. We explore the dynamics of risk for large cap US equities and 60/40 stock/bond allocations over the decades and show that risk has fluctuated significantly. This implies that investors who have set risk preferences need to adapt their asset allocation strategies to these variations in risk and correlation. We show that strategies that utilize downside protection with equity index put options, specifically buffer protection strategy indexes, exhibit similar levels of risk reduction as 60/40 balanced portfolio strategies but have more variable beta exposure. Going forward, investors can benefit from incorporating dynamic risk and correlation forecasts into their asset allocation process and looking beyond fixed income diversification for risk management. Downside protection and other risk modification strategies within the equity bucket can be effective tools to better align the portfolio risk with investor risk targets.