A note on dynamic hedging

2015 ◽  
Vol 16 (2) ◽  
pp. 190-196
Author(s):  
Moawia Alghalith ◽  
Christos Floros ◽  
Ricardo Lalloo
Keyword(s):  
Continuous Time ◽  
Futures Markets ◽  
Price Volatility ◽  
Spot Price ◽  
Risk Averse ◽  
Dynamic Hedging ◽  
Basis Risk ◽  
Content Type ◽  
Unit Increase ◽  
Using Data

Purpose – The purpose of this paper is to empirically test dynamic hedging, using data from the FTSE-100 and Standard & Poor’s (S&P) 500 futures indices. Design/methodology/approach – The authors introduce a dynamic continuous-time hedging model in futures markets. The authors further relax the statistical-independence assumption between the spot price and basis risk. Findings – The authors show that the investors are, on average, quite risk averse. The authors find that a one unit increase in the price volatility reduces the hedged FTSE-100 (S&P 500) by 645.62 (777.07) units. Similarly, a one unit increase in basis risk reduces the hedged FTSE-100 (S&P 500) by 403.57 (378.54) units. The authors’ approach shows that risk-averse investors should decrease their hedge (i.e. increase their equity allocation) with an increase in index price risk. Practical implications – These findings are helpful to risk managers dealing with futures markets. Originality/value – The contribution of this paper is that it successfully introduces a dynamic continuous-time hedging model in futures markets.

Monotonicity, linearity and symmetry in the price volatility–volume relationship

2020 ◽  
Vol 37 (1) ◽  
pp. 110-133 ◽  
Author(s):  
Panos Fousekis ◽  
Dimitra Tzaferi
Keyword(s):  
Trading Volume ◽  
Futures Markets ◽  
Statistical Tests ◽  
Price Volatility ◽  
Local Linear Regression ◽  
Linear Regression Models ◽  
Content Type ◽  
Nonparametric Approach ◽  
Volume Relationship ◽  
The Usa

Purpose This paper aims to investigate the contemporaneous link between price volatility and trading volume in the futures markets of energy. Design/methodology/approach Non-parametric (local linear) regression models and formal statistical tests are used to assess monotonicity, linearity and symmetry. The data are daily price and volumes from five futures markets (West Texas Intermediate, Brent, gasoline, heating oil and natural gas) in the USA. Findings Trading volume and price volatility have, in all markets, a strong nonlinear relation to each other. There are violations of monotonicity locally but not globally. The qualitative nature of the price shocks may have implications for the trading activity locally. Originality/value To the authors’ best knowledge, this is the first manuscript that investigates simultaneously and formally all the three important issues (i.e. monotonicity, linearity and asymmetry) for the price volatility–volume relationship using a highly flexible nonparametric approach.

Impact of futures trading on volatility of spot market-a case of guar seed

2015 ◽  
Vol 75 (3) ◽  
pp. 416-431 ◽  
Author(s):  
Dinesh Kumar Sharma ◽  
Meenakshi Malhotra
Keyword(s):  
Trading Volume ◽  
Price Volatility ◽  
Futures Market ◽  
Spot Price ◽  
Futures Trading ◽  
Market Prices ◽  
Content Type ◽  
Commodity Derivatives ◽  
Spot Volatility ◽  
Guar Seed

Purpose – Guar Seed crop is ruling the Indian International business mainly due to its application as a drilling fluid in shale energy industry concentrated in the USA. One of the allegations against futures market is its possible role in increasing the volatility of underlying physical market prices. Suspension of guar seed futures contract in 2012 at National Commodity Derivatives Exchange of India (NCDEX)-India, has reignited the controversy and raised an alarm bell to peek into obscure world of Indian commodity derivatives market. Against the backdrop of fiasco in guar futures trading, the purpose of this paper is to investigate whether sudden surge in futures trading volume leads to increase in the volatility of spot market prices. Design/methodology/approach – Guar seed spot returns volatility is modeled as a GARCH (1, 1) process. Futures trading volume and open interest are segregated into expected and unexpected components. The data are analyzed from 2004 to 2011 using Augmented GARCH model to study the contemporaneous relationship between spot volatility and unexpected futures trading activity and Granger Causality test for examining the dynamic relationship between them and ascertaining causality. Findings – Augmented GARCH model reports positive relationship between unexpected futures trading volume (UTV) and spot returns volatility, and, Granger Causality flows from UTV to spot volatility. Therefore, when the level of futures trading volume increases unexpectedly, the volatility of spot prices increases pointing toward the destabilizing impact of futures trading. However, hedger’s activity, represented by open interest is not seen to have any causal/destabilizing impact on spot price volatility of guar seed. Practical implications – The study provides empirical evidence to support the concern of regulators, genuine hedgers and other traders about the presence of excessive speculation and market manipulations perpetrated through futures market that is disturbing the underlying physical market instead of strengthening it by aiding in price discovery and risk mitigation. Originality/value – There are very few studies which have empirically investigated the temporal relation between volume and volatility in Indian agricultural commodity markets. With guar seed as a special case the present study investigates statistically the impact of futures trading on spot price volatility. In light of the findings of the study, the curb imposed on guar seed futures trading in 2012 was justified.

Multi-period dual-sourcing replenishment problem with option contracts and a spot market

2018 ◽  
Vol 118 (4) ◽  
pp. 782-805 ◽  
Author(s):  
Nana Wan ◽  
Xu Chen
Keyword(s):  
Wholesale Price ◽  
Price Volatility ◽  
Spot Market ◽  
Approximate Algorithm ◽  
Spot Price ◽  
Stochastic Dynamic ◽  
Operational Strategies ◽  
Content Type ◽  
Option Contracts ◽  
Replenishment Policy

Purpose The spot market has been gradually recognized as an important alternative purchasing source. To maintain a flexible replenishment strategy, call, put and bidirectional option contracts, as a risk hedging, are in combined usage with the spot market, respectively. The purpose of this paper is to analyze a finite-horizon replenishment problem with option contracts in the context of a spot market. Design/methodology/approach Based on stochastic dynamic programming, the firm’s optimal replenishment policy with either call, put or bidirectional option contracts is always shown to be order-up-to type, characterized by an upper threshold and a lower one. The corresponding policy parameters in different cases are calculated through an approximate algorithm. This research highlights the effectiveness of option contracts on the firm’s operational strategies and overall profitability. Findings This study reveals that the firm is better off with option contracts than without them. When the price parameters are the same for different option contracts, bidirectional option contracts are the best choice among these flexible contracts; otherwise, unilateral option contracts might be either better or worse than bidirectional ones. In addition, if low inventory costs and high spot price volatility are confronted, the firm prefers to call option contracts rather than put ones; otherwise, there exists an opposite conclusion. Originality/value In addition to highlight the advantage of option contracts over wholesale price contracts, this paper provides interesting observations with respect to the effect of different option contracts on the firm. Many significant insights derived from this research do not only contribute to the provider’s feasible design of the supply contracts, but also contribute to the user’s rational operational strategies for higher profitability.

DYNAMIC HEDGING OF INFLATION RISK

2009 ◽  
Vol 05 (01) ◽  
pp. 0950003
Author(s):  
UDO BROLL ◽  
STEFAN SCHUBERT
Keyword(s):  
Futures Markets ◽  
Price Level ◽  
Asset Price ◽  
Risk Averse ◽  
Dynamic Hedging ◽  
Hedging Strategy ◽  
Inflation Risk ◽  
Optimal Dynamic ◽  
Futures Price ◽  
International Investors

National and international investors are exposed to risk, stemming from volatile asset prices and inflation uncertainty. However investors can enter futures markets to hedge against these risks. The paper develops a dynamic hedging model, where the evolution of asset price, price level and futures price and hence real wealth is stochastic. For a risk averse investor, optimal dynamic consumption and hedging strategy are derived and discussed.

scholarly journals Volatility Dynamics in Oil and Oilseeds Spot and Futures Market in India

2016 ◽  
Vol 41 (2) ◽  
pp. 132-148 ◽  
Author(s):  
Meenakshi Malhotra ◽  
Dinesh Kumar Sharma
Keyword(s):  
Futures Markets ◽  
Garch Model ◽  
Price Volatility ◽  
Spot Market ◽  
Futures Market ◽  
Spot Price ◽  
Volatility Spillover ◽  
Trading Activity ◽  
Futures Trading ◽  
The Impact

Executive Summary India occupies the fifth position in the vegetable oil economy of the world. The demand for oilseeds and vegetable oil has far exceeded the domestic output necessitating huge imports. Futures market helps to bring price stability for the development of the underlying physical market. The present study investigates the volatility dynamics in spot and futures markets of select oil and oilseeds commodities. The objectives of this article are to study (a) the information transmission process between spot and futures markets, also called volatility spillover and (b) the impact of futures trading activity on the volatility of physical market prices. The commodities selected from oil and oilseeds segment are refined soya oil, mustard seed, crude palm oil, and mentha oil. The study uses basic Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model to capture volatility in prices of the selected commodities. Bivariate GARCH model makes use of information in the history of two different markets for testing volatility spillover between two markets of the same underlying commodity. The relationship between futures trading activity and spot price volatility is investigated for examining the impact of futures trading activity on the volatility of underlying spot market. Two variables, viz., futures trading volume and open interest are decomposed into expected and unexpected components and are taken as a proxy for the level of trading activity. The contemporaneous and dynamic relationships are studied with the help of augmented GARCH model and Granger causality, respectively. It is observed that there is an efficient transmission of information between spot and futures markets but it is the spot market which leads to the flow of information to futures and hence causes greater spillover of volatility. The spot market has a greater impact on the volatility of futures market, indicating that informational efficiency of oilseeds spot market is stronger than that of the futures market. The contemporaneous and dynamic relationship between spot price volatility and futures trading activity tested with econometric models provide evidence of the destabilizing impact of an unexpected increase in futures trading activity (volume or open interest) on the spot price volatility in three out of four commodities studied. This indicates that badly informed traders present in futures market are destabilizing the underlying spot market by inducing noise and lowering the information content of prices.

Strategic procurement from forward contract and spot market

2014 ◽  
Vol 114 (5) ◽  
pp. 778-796 ◽  
Author(s):  
C.K.M. Lee ◽  
Danping Lin ◽  
Rohan Pasari
Keyword(s):  
Demand Uncertainty ◽  
Price Volatility ◽  
Real Data ◽  
Spot Market ◽  
Spot Price ◽  
Content Type ◽  
Procurement Process ◽  
The Impact ◽  
Forward Contracting

Purpose – The purpose of this paper is to formulate procurement strategies and determine the optimal procurement quantity in order to maximize profit through forward contracting and the spot market. Design/methodology/approach – The procurement process is modeled at various stages along a time horizon from the perspective of the buyer, with consideration of uncertain yields, stochastic demand and dynamic spot market prices. Monte Carlo simulation based experiments were conducted to figure out the best procurement quantity for five different scenarios. The framework was developed to understand the impact of different uncertain variables on a firm's profit. A case study was carried out in a steel making company in India, with real data. Findings – The results indicate that the proposed approach enables buyers to achieve higher profits under volatile demand conditions. In the case study, it was found that the profit is higher for the spot market than for contract pricing if there is significant demand and spot price volatility. Originality/value – This research considers not only demand uncertainty but also supply uncertainty in the procurement process, and profit analysis was carried out to enable an enterprise to set up a procurement plan by using forward contracting and the spot market. This study should also increase awareness in both academia and industry on the opportunities of using the spot market to enhance flexibility and to mitigate risk in the procurement process.

Do seasonality, break and spillover effects explain commodity price volatility

2018 ◽  
Vol 8 (1) ◽  
pp. 144-170 ◽  
Author(s):  
Debashish Maitra
Keyword(s):  
Futures Markets ◽  
Structural Breaks ◽  
Price Volatility ◽  
Spillover Effects ◽  
Commodity Price ◽  
Commodity Futures ◽  
Spot Markets ◽  
Content Type ◽  
Commodity Price Volatility ◽  
Variance Equation

Purpose The purpose of this paper is to understand the volatility in commodity futures and spot markets. The study starts with a few questions: first, the effect of seasonality on the volatility is studied. Thereafter, the presence of structural breaks in the variance is identified. At last the seasonality, structural shifts and spillover effects are examined together to find out their effects on volatility. Design/methodology/approach The methodology heavily employs econometric tools and techniques. The monthly seasonal dummies are incorporated to identify the effects of seasonality on volatility. Then, the presence of break in volatility is tested by cumulative sum of squares (CUSUM test), followed by generalized autoregressive conditional heteroscedastictity and EGARCH models are measured by including seasonal dummies, break dummies and the residuals of other market in the variance equation to determine spillover effects. Findings It is found that the effects of seasonality on volatility cannot be ignored as the effects are significant. The presence of asymmetry is detected in all the commodities. The presence of seasonality and structural breaks in the variance equation are statistically able to reduce the volatility but the magnitude is very negligible with an exception in cumin futures markets. Bi-directional volatility spillover between futures and spot markets is observed in all the commodities and the effect of spillover is more from spot markets to the futures markets. Research limitations/implications This study is limited to a few agro commodities which are well traded. This study could have been extended to the other thinly traded commodities. This study has also taken only near month futures contracts as it contains more information but the same could have been studied by taking far month contracts also. Originality/value The present study attempted to understand the conjugated effects of seasonality, structural breaks and spillover on volatility of commodity markets which is not apparent in the previous studies. This study has also employed methodological rigor to identify the breaks in the variance equation. In addition to this it has also investigated whether Indian commodity futures markets are informationally more efficient than the spot markets.

Absence of the weekend effect and industry-style portfolios

2019 ◽  
Vol 12 (4) ◽  
pp. 463-475
Author(s):  
Selma Izadi ◽  
Abdullah Noman
Keyword(s):  
New York ◽  
Stock Market ◽  
Structural Breaks ◽  
Stock Exchange ◽  
Structural Break ◽  
Weekend Effect ◽  
Content Type ◽  
Market Portfolio ◽  
The Us ◽  
Using Data

Purpose The existence of the weekend effect has been reported from the 1950s to 1970s in the US stock markets. Recently, Robins and Smith (2016, Critical Finance Review, 5: 417-424) have argued that the weekend effect has disappeared after 1975. Using data on the market portfolio, they document existence of structural break before 1975 and absence of any weekend effects after that date. The purpose of this study is to contribute some new empirical evidences on the weekend effect for the industry-style portfolios in the US stock market using data over 90 years. Design/methodology/approach The authors re-examine persistence or reversal of the weekend effect in the industry portfolios consisting of The New York Stock Exchange (NYSE), The American Stock Exchange (AMEX) and The National Association of Securities Dealers Automated Quotations exchange (NASDAQ) stocks using daily returns from 1926 to 2017. Our results confirm varying dates for structural breaks across industrial portfolios. Findings As for the existence of weekend effects, the authors get mixed results for different portfolios. However, the overall findings provide broad support for the absence of weekend effects in most of the industrial portfolios as reported in Robins and Smith (2016). In addition, structural breaks for other weekdays and days of the week effects for other days have also been documented in the paper. Originality/value As far as the authors are aware, this paper is the first research that analyzes weekend effect for the industry-style portfolios in the US stock market using data over 90 years.

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