Further evidence in support of a low-volatility anomaly: Optimizing buy-and-hold portfolios by minimizing historical aggregate volatility

Maguire, Phil; Kelly, Stephen; Miller, Robert; Moser, Philippe; Hyland, Philip; Maguire, Rebecca

doi:10.1057/s41260-016-0036-1

Cited by 5 publications

(4 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Transitory volatility is caused by market uncertainty, such as market shocks from both the supply and demand sides and expectations (Živkov et al, 2020). Low volatility indicates that price volatility occurs relatively quickly (Maguire et al, 2017). In this study, from 2012 to 2020, the prices of all ornamental plants fluctuated.…”

Section: Ornamental Plant Price Volatility Analysismentioning

confidence: 58%

Price Volatility of Ornamental Plants in Batu Municipality

Khofifah

Nugroho

Sujarwo

2022

J AGRIB RURAL DEV RES

View full text Add to dashboard Cite

The imbalance between supply and demand of ornamental plants in the market cause fluctuations that lead to price volatility. This study aimed to analyze the price volatility of ornamental plants with high economic value, such as orchids, adenium, aglaonema, anthurium, and palm. This study also analyzed the long-term and short-term relationship between the production and prices of these ornamental plants. The data used were the productions and prices of orchid, adenium, aglaonema, anthurium, and palm at the producer level from 2012 to 2020 obtained from the Agriculture Office of Batu Municipality. Volatility analysis was carried out using the ARCH/GARCH method, the long-term relationship was analyzed using the Johansen cointegration test, and the short-term relationship was carried out using the Error Correction model. The results of volatility analysis showed that all the ornamental plants studied had low price volatility. In addition, the productions and prices of the ornamental plants were cointegrated in the long run, but only the orchid had a short-term relationship with an adjustment period of 2.6 months.

show abstract

Section: Ornamental Plant Price Volatility Analysismentioning

confidence: 58%

Price Volatility of Ornamental Plants in Batu Municipality

Khofifah

Nugroho

Sujarwo

2022

J AGRIB RURAL DEV RES

View full text Add to dashboard Cite

show abstract

“…Stock markets globally are generally expected to rise into the future, this being perhaps their only genuinely predictable feature (Maguire et al, 2017). This fact could be used to reap further returns from our algorithm by allocating a larger proportion of capital into long positions than into short positions.…”

Section: Momentum Oscillator Performancementioning

confidence: 99%

Combining Independent Smart Beta Strategies for Portfolio Optimization

Maguire¹,

Moffett²,

Maguire³

2018

Preprint

Self Cite

View full text Add to dashboard Cite

Smart beta, also known as strategic beta or factor investing, is the idea of selecting an investment portfolio in a simple rule-based manner that systematically captures market inefficiencies, thereby enhancing risk-adjusted returns above capitalization-weighted benchmarks. We explore the idea of applying a smart strategy in reverse, yielding a "bad beta" portfolio which can be shorted, thus allowing long and short positions on independent smart beta strategies to generate beta neutral returns. In this article we detail the construction of a monthly reweighted portfolio involving two independent smart beta strategies; the first component is a long-short beta-neutral strategy derived from running an adaptive boosting classifier on a suite of momentum indicators. The second component is a minimized volatility portfolio which exploits the observation that low-volatility stocks tend to yield higher risk-adjusted returns than high-volatility stocks. Working off a market benchmark Sharpe Ratio of 0.42, we find that the market neutral component achieves a ratio of 0.61, the low volatility approach achieves a ratio of 0.90, while the combined leveraged strategy achieves a ratio of 0.96. In six months of live trading, the combined strategy achieved a Sharpe Ratio of 1.35. These results reinforce the effectiveness of smart beta strategies, and demonstrate that combining multiple strategies simultaneously can yield better performance than that achieved by any single component in isolation.

show abstract

“…The safest approach, therefore, might be to elicit the opinions of a diversified portfolio of mathematicians from all over the world, all representing different forms of mathematical uncertainty. 5 The greater the number of opinions, and the more independent they are, the greater the stability of the resulting aggregated opinion (see Ref. 6 for many more real world examples).…”

Section: The Link Between Statistical Uncertainty and Stabilitymentioning

confidence: 99%

New adventures with Schrödinger's cat: The role of statistical uncertainty in stabilizing measurement

Maguire¹,

Maguire²

2017

phys essays

Self Cite

View full text Add to dashboard Cite

We reopen Erwin Schrödinger's thought experiment involving a cat in an informationally impenetrable box. A common view is that the cat enters a superposition of alive/ dead because of a lack of observation, leading to uncertainty about the state of the cat. We, on the other hand, argue that the cat only enters a superposition if everything about the cat is known prior to the box being closed. The superposition results from a lack of uncertainty inside the box. Rather than interpreting this state of affairs as a live and dead cat interacting with each other, we suggest that the more natural interpretation is that of an inability to precisely position events within spacetime due to the lack of uncertainty. We clarify how stable measurement depends on a diversified portfolio of statistical uncertainty, and how the lack of such uncertainty in Schrödinger's box precludes stabilization. V

show abstract

Further evidence in support of a low-volatility anomaly: Optimizing buy-and-hold portfolios by minimizing historical aggregate volatility

Abstract: His research explores portfolio optimisation, predictive modelling and the foundations of measurement.

Cited by 5 publications

References 27 publications

Price Volatility of Ornamental Plants in Batu Municipality

Price Volatility of Ornamental Plants in Batu Municipality

Combining Independent Smart Beta Strategies for Portfolio Optimization

New adventures with Schrödinger's cat: The role of statistical uncertainty in stabilizing measurement

Contact Info

Product

Resources

About