Increase In Market Volatility Research Articles

International Real Estate Review

Developers make decisions around timing and intensity simultaneously when exercising a development option. Built on the early real options models, we allow the demand shock and the cost functions to be dependent on the intensity of real estate development. Based on a set of input parameters, the numerical results show that demand uncertainty delays development activities, and the rental elasticity to density change has an inverse effect on the deferment option values. In a market where the intensity impact on rental income is small, development activities are likely to be curtailed when market volatility increases. More empirical tests could be conducted on whether more smaller-scale projects are triggered in down markets relative to up markets.

Asset pricing with index investing

We theoretically analyze how index investing affects financial markets using a dynamic exchange economy with heterogeneous investors and two Lucas trees. We identify two effects of indexing: lockstep trading of stocks increases market volatility and stock return correlations but reduction in risk sharing decreases them. Overall, indexing decreases market volatility but has an ambiguous effect on the correlations. Also, index investing decreases an investor’s welfare, but indexing by other investors partially offsets the loss. When the introduction of index trading opens financial markets for new investors, the improved risk sharing makes market returns more volatile and stock returns more correlated.

Volatility connectedness of major cryptocurrencies: The role of investor happiness

In this paper, we first obtain a time-varying measure of volatility connectedness involving fifteen major cryptocurrencies based on a dynamic conditional correlation-generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model, and then analyze the role of investor sentiment in explaining the movement of the connectedness metric within a quantile-on-quantile framework. Our findings show that lower quantiles of investor happiness, built on Twitter feed data as a proxy for investor sentiment, is positively associated with the entire conditional distribution of connectedness, but the opposite is observed at higher values of investor happiness. In addition, when we look at the effect of sentiment on the common market volatility, we are able to deduce that as investors become exceedingly unhappy, overall market volatility increases and this is associated with high market connectedness. The heightened volatility possibly due to higher trading, seems to suggest that cryptocurrencies are used for hedging when investor sentiment is weak, with evidence in favor of this behavior being relatively stronger than the possible speculative motive associated with happy investors, as low total connectedness is coupled with high common volatility. Our results tend to suggest that, relatively more diversification opportunities are available when investors are happy rather than when sentiment is weak.

Sampling methods for investment portfolio formulation procedure at increased market volatility

Aim/purpose – In this paper, a market volatility-robust portfolio composition frame- work under the modified Markowitz’s approach with the use of sampling methods is developed in order to improve the allocation efficiency for a portfolio of financial in- struments formulation procedure at an increased market volatility. Design/methodology/approach – In order to overcome the risk of not receiving an optimal solution to the portfolio optimization (suboptimal outcomes of attribution of weights in allocation procedures) the developed model, first, implements the rationale that financial markets largely feature two states, i.e., quiescent (non-crisis; low market volatility) periods that are occasionally interspersed with stress (crisis; high market volatility) periods and, second, relies on many input samples of rates of return, either from an empirical distribution or a theoretical distribution (mitigating estimation risk). All computational results are reported for publicly available historical daily data sets on selected Polish blue-chip securities. Findings – Not only did the presented method produce more diversified allocation, but also successfully minimized the unfavorable effects of increased market volatility by providing less risky portfolios in comparison to Newton’s method, typically used for optimization under portfolio theory. Research implications/limitations – The research emphasized that in order to get a more diversified investment portfolio it is crucial to outdo the limitations of a single sample approach (utilized in Markowitz’s model) which may on some occasions be statistically biased. Thus it was proved that sampling methods allow to obtain a less concentrated and volatile allocation which contributes the investment decision-making. However, the current research focused solely on publicly available input data of particular securities. In this manner, an additional analysis can be prepared for other jurisdictions and asset classes. There can also be considered a use of other than variance risk measures. Originality/value/contribution – The suggested framework contributes to existing methods a wide array of quantitative data analysis and simulation tools for composing an unique approach that directly addresses the task of minimizing the adverse implications of increased market volatility that, in consequence, pertains to knowledgeable attributing of investment portfolio proportions of either individual or institutional investors. The prepared method is also proved to hold demanded computational quality and, importantly, the capacity for further development. Keywords: investment decisions, optimization techniques, portfolio selection, statistical simulation methods. JEL Classification: C150, C610, G110.

The M2 Money Supply, the Economy, and the National Debt: A Mathematical Approach

The United States dollar was tied to a finite standard dating back to 1792. The dollar has survived multiple wars, armed conflicts short of war, economic recessions, and the Great Depression. At the end of World War II, the dollar, by international agreement, effectively became the world’s reserve currency. Other currencies were fixed to the dollar and the dollar was in turn fixed to the gold standard, that is, the value of a dollar was fixed at thirty-five dollars per ounce of gold. In 1971, the United States government severed the dollar from the gold standard leaving the size of the money supply free of any finite limit. Since that time, the United States money supply, national debt, and stock market indices have experienced exponential growth. The purpose of this paper is to investigate mathematically and model the relationship among these key economic indicators. Our work in this paper allows us to gain some insight into how each of these economic indicators can influence one another while giving us a better idea of how the economy functions. We were allowed to collect data for each of the indicators over a certain period which allowed us to demonstrate that a strong correlation exists among these three indicators. After collecting our data and making some logical assumptions, we modeled the money supply as a function of time. In turn, we modeled the Dow Jones stock market index as a function of the money supply. Finally, we produced a model of the National Debt as a function of the Dow Jones stock market index. From the data, we collected and our economic indicator models, we derived a series of differential equations that would help us observe the exponential growth trend of each graphically. By showing a comparison from our collection of raw data versus our results from our model, we conclude that, under prevailing circumstances, it is reasonable to expect growth in all three indicators and increasing market volatility for some time to come. We have answered the question of whether the monetary and fiscal policies of the past half-century have been of some benefit. However, we question whether this trend is good for all Americans and whether it is sustainable in perpetuity. This paper concludes with possible areas of interest warranting additional investigation to enable us to better understand the economy and develop effective financial strategies.

COVID-19 and the Financial Markets’ Volatility and Returns

The study is undertaken to investigate the impact of COVID-19 on the Financial Markets ‘Volatility from the period April 2020 to June 2020. Ten countries namely Pakistan, USA, China, UAE, UK, Spain, France, South Korea, Switzerland, and the Netherlands were selected. Our daily data comes from the WHO situation reports (COVID-19 statistics) and Pakistan, USA, UK, UAE, China, France, Netherlands, Switzerland’s, Spain, and South Korea Stock Exchange Indices database, respectively. We use the KSE-100, S&P 500, FTSE 100, SE 50, AEX, ADX, IBEX, FCHI, KRX, and SSMI 3-month realized volatility index as a proxy for the Pakistan financial markets’ volatility. We test a simple Ordinary Least Squares (OLS) regression investigating the new coronavirus impact on the financial volatility and we use a stepwise procedure. Independent variables included Global COVID-19 Confirm case, Fatality, Country COVID-19 new case, Country Fatality, and dependent variable included country’s market volatility, and market returns. Control variables of the country’s Exchange and Interest rate were also included. The study design is descriptive and analytical using the quantitative method with the application of Eviews. The results suggested that the Global COVID new case seems to have a significant negative impact on the country's market volatility, however, global fatality seems to increase market volatility. Country-specific cases seem to negatively affect that country's volatility however, country-specific fatality doesn’t seem to be significantly impacting volatility. Apart from that, interest and exchange rates seem to increase the volatility. However, the effect of these variables on returns remained insignificant. The findings of this research provide policy implications to investors and policymakers indicating that pandemics can significantly perpetrate business economics.

Overview of Innovative Technologies in Liquid‐Liquid Extraction Regarding Flexibility

AbstractAs a result of increasing market volatility and product diversification the technology requirements will change in the future. Flexibility needs to be increased, enabling a large operating window while maintaining intensive mass and energy transfer and resource‐efficiency. A promising approach is using innovative small‐scale technologies. To assess flexibility, the technologies must be characterized in a wide range of operating parameters and physical properties. Therefore, research work on innovative technologies for liquid‐liquid extraction is presented.

Responding to change: Farming system resilience in a liberalized and volatile European dairy market

For more than two decades market conditions for European producers have changed significantly due to liberalization and increasing price volatility. The objective of this article is to analyze how farming systems in five European countries (Denmark, Greece, France, Latvia, and the United Kingdom) have reacted to the emerging instability of the milk market. Dairy production is an ideal setting to study how different farming systems respond to changing conditions as a number of policy changes have altered market conditions for producers. Empirically, the analysis draws on statistical data on dairy production and farm structure, and qualitative and quantitative data from case studies in the five countries. During the period under study, dairy farming systems have operated under the same overarching EU regulation, but dairy sectors at the national level followed specific pathways. We found different strategies and institutional arrangements deployed to address price volatility at the national levels. We argue that divergence in the strategies developed to address this disturbance reflects different configurations of value chain organization (particularly dairies), production factors (production facilities and biophysical conditions), and market orientation. Increasing market volatility implies that succession planning and attracting investments is difficult for farming systems across all countries, and thereby to formulate strategies for resilience.

Volatility Markets Underreacted to the Early Stages of the COVID-19 Pandemic

VIX futures prices rose slowly in late February and early March 2020 as the COVID-19 pandemic took hold. Futures price premiums, defined as futures prices minus real-time statistical forecasts of future VIX values, turned sharply negative and remained negative until mid-April. Trading strategies based on estimated premiums profited from the subsequent increase in market volatility and equity market crash. The underreaction of futures prices to growing pandemic risks poses a puzzle for standard asset pricing models.

Optimal Dynamic Capital Requirements and Implementable Capital Buffer Rules

We build a quantitatively relevant macroeconomic model with endogenous risk-taking. In our model, deposit insurance and limited liability can lead banks to make risky loans that are socially inefficient. This excessive risk-taking can be triggered by aggregate or sectoral shocks that reduce the return on safer loans. Excessive risk-taking can be avoided by raising bank capital requirements, but unnecessarily tight requirements lower welfare by limiting liquidity producing bank deposits. Consequently, optimal capital requirements are dynamic (or state contingent). We provide examples in which a Ramsey planner would raise capital requirements: (1) during a downturn caused by a TFP shock; (2) during an expansion caused by an investment-specific shock; and (3) during an increase in market volatility that has little effect on the business cycle. In practice, the economy is driven by a constellation of shocks, and the Ramsey policy is probably beyond the policymaker's ken; so, we also consider implementable policy rules. Some rules can mimic the optimal policy rather well but are not robust to all the calibrations we consider. Basel III guidance calls for increasing capital requirements when the credit to GDP ratio rises, and relaxing them when it falls; this rule does not perform well. In fact, slightly elevated static capital requirements generally do about as well as any implementable rule.

Selection of optimal capacity for reconfigurable machines during lean manufacturing

Presently manufacturing industries are facing the challenge of increased market volatility and unpredictability. Capacity control is an effective measure to address this problem by utilizing the flexibility in the plant capacity. This research paper proposes a genetic algorithm (GA) based methodology to optimally select levels of capacity for machines which are reconfigurable in nature. The objective function for the optimization problem is minimization of an error with takt time. Takt as a key feature of lean manufacturing is considered in the model to manufacture the products in a fixed rate as decided by their respective demands and available production time. A hypothetical numerical problem is illustrated to describe the selection methodology, GA computation steps and the solution procedure.

Cross-Currency Interest Rate Swap Application in the Long-Term Currency Risk Management

<p>Effective currency risk management using various derivatives is particularly important under increased market volatility. The risk is relatively higher for longer than shorter time frames. This study highlights the implementation of selected instruments for long-term hedging. It presents the application of cross-currency interest rate swap as a currency risk hedging tool used by Polish exporters, mainly manufacturers generating their revenues mostly abroad (in euro area), exposed to negative exchange rate fluctuations. The paper covers issues related to the pricing, market risk estimation and collateral required in the OTC market, as well as undertakes a sensitivity analysis in search for exchange rates at which margin call occurs. There is a comparative analysis and back test simulation conducted using market data from exchange and money markets. The study emphasized that the analyzed instrument meets the expectations in terms of hedging the company cash flows, as well as may generate additional benefits due to the still existing interest rate differential.</p>

Holistic Approach in Planning for Personal Financial Management: Indian Scenario

Some 25 years ago an elderly person used to manage financial affairs for the whole family and was responsible for satisfying everyone’s needs and requirements. However, today in the privatized, globalized and liberalized Indian economy, the social change from single bread-winner families to dual-career, dual-income families are increased. Concepts relating to saving, investing, taxes, spending, and borrowing are not clearly understood even by educated leave alone poor and illiterate ones. Today, the hour of the need is for every earning individual to think, plan, and act on securing their financial future. Rising costs of healthcare, increasing life expectancy, lifestyle, uncertainty, increased market volatility, and complex investment products make it essential to have a fundamental understanding of personal finance subjects (Sobhesh Kumar, Et., al, 2013). Per Wells Fargo Wealth & Investment Management, USA (2019) a survey interview on retirement (3918 individuals) research finding point to a need for better preparation — not to work harder, but to work smarter. Hence, greater efforts from the various stakeholders needed to improve the current state of play and to ensure that the embedded benefits of personal financial planning are far-reaching.

Research on the Effects of Institutional Liquidation Strategies on the Market Based on Multi-agent Model

Based on the multi-agent model, an artificial stock market with four types of traders is constructed. On this basis, this paper focuses on comparing the effects of liquidation behavior on market liquidity, volatility, price discovery efficiency and long memory of absolute returns when the institutional trader adopts equal-order strategy, Volume Weighted Average Price (VWAP) strategy and Implementation Shortfall (IS) strategy respectively. The results show the following: (1) the artificial stock market based on multi-agent model can reproduce the stylized facts of real stock market well; (2) among these three algorithmic trading strategies, IS strategy causes the longest liquidation time and the lowest liquidation cost; (3) the liquidation behavior of institutional trader will significantly reduce market liquidity, price discovery efficiency and long memory of absolute returns, and increase market volatility; (4) in comparison, IS strategy has the least impact on market liquidity, volatility and price discovery efficiency, while VWAP strategy has the least impact on long memory of absolute returns.

Trading Strategies of a Leveraged ETF in a Continuous Double Auction Market Using an Agent-Based Simulation

A leveraged ETF is a fund aimed at achieving a rate of return several times greater than that of the underlying asset such as Nikkei 225 futures. Recently, it has been suggested that rebalancing trades of a leveraged ETF may destabilize the financial markets. An empirical study using an agent-based simulation indicated that a rebalancing trade strategy could affect the price formation of an underlying asset market. However, no leveraged ETF trading method for suppressing the increase in volatility as much as possible has yet been proposed. In this paper, we compare different strategies of trading for a proposed trading model and report the results of our investigation regarding how best to suppress an increase in market volatility. As a result, it was found that as the minimum number of orders in a rebalancing trade increases, the impact on the market price formation decreases.

Volatility Markets Underreacted to the Early Stages of the COVID-19 Pandemic

VIX futures prices rose slowly in late February and early March 2020 as the COVID-19 pandemic took hold. Futures price premiums, defined as futures prices minus real-time statistical forecasts of future VIX values, turned sharply negative and remained negative until mid-April. Trading strategies based on estimated premiums profited from the subsequent increase in market volatility and equity market crash. The underreaction of futures prices to growing pandemic risks poses a puzzle for standard asset pricing models.

Volatility spillovers across European stock markets under the uncertainty of Brexit

This paper examines the behaviour of some inter-related European stock markets under the uncertainty of Brexit in a multivariate time-varying setting. Our results point to considerable interactions between these markets. As evident by the smaller and less frequent positive net total volatility spillovers, the UK's influence on the other markets has been decreasing since the campaign for the EU referendum started in January 2016. Although the shock of the Brexit decision on 23rd June 2016 increases market volatility as expected, it exerts diverse impacts instantaneously on market co-movements. Although the ambivalent markets adjust rather quickly, synchronising their movements within days, the impact of the Brexit decision on market co-volatility continues to be substantial and persists. Impact of the yet-progress-made trade agreement now under negotiation for resolution may as well be long lasting on the dynamics between markets.

Engineering Education in Changeable and Reconfigurable Manufacturing: Using Problem-Based Learning in a Learning Factory Environment

In today’s manufacturing environment, the development and implementation of changeable and reconfigurable manufacturing systems is essential in order to manage and capitalize on increasing market volatility, product variety, customization, and smaller batch sizes. Teaching future engineers the skills and competences needed for this requires application of new and innovative learning approaches. Therefore, this paper presents an example of how blended and problem-based learning in a learning factory can be applied for an engineering course in changeable and reconfigurable manufacturing, in order to educate engineers that comply with requirements in the modern manufacturing environment.

Trading European Central Bank rumours on the EUR-USD exchange rate market

This paper investigates whether the release of market-relevant news in the form of rumours on Twitter can explain the excess of market volatility previously attributed to private information, speculation, and noise traders. We define a simple theoretical model to show that the systematic information content of such rumours should result in detectable price effects in macro-markets. We then pinpoint the arrival of 63 rumours of forthcoming ECB actions over a 420-day sample of one-minute spot EUR-USD rates, and show that there is a real-time, intraday increase in market volatility. This largely unexplored information set can potentially account for significant amounts of unexplained volatility in macro-markets and, therefore, identify a possible explanation of one of the most prominent puzzles in price discovery research.

Volatility and Liquidity in the Real Estate Market

Empirical evidence suggests that when the market becomes increasingly volatile, trading activities may be depressed or even halted. We develop a simple model to formally study the relation between market volatility and asset liquidity in the real estate market. We show that, for both cases of systemic and idiosyncratic volatility, an increase in market volatility negatively affects asset liquidity when information is asymmetric between the market participants. The results complement those of Krainer (2001) and extend those of Deng, Gabriel, Nishimura, and Zheng (2012). Indirect tests of the theory are provided by applying it to explain some empirical findings in the brokerage literature, and a strategy for directly testing the theory is outlined.