Simulation of Futures and Spot Markets by Using an Agent-Based Multi-Market Model

2011 ◽  
Vol 15 (2) ◽  
pp. 204-211 ◽  
Author(s):  
Tomoko Ohi ◽  
◽  
Yasuhiro Hashimoto ◽  
Yu Chen ◽  
Hirotada Ohashi
Keyword(s):  
Statistical Properties ◽  
Trading Strategies ◽  
Market Model ◽  
Spot Markets ◽  
Futures Prices ◽  
Trading Behavior ◽  
Noise Traders ◽  
Agent Based ◽  
Spot Prices ◽  
Tail Distribution

The agent-based multi-market model we propose simulates futures and spot markets. On the basis of trading strategies in real markets, four kinds of agents - arbitragers, hedgers, speculators, and noise traders - are included in our model. Interactions of the two markets are generated through various agent trading behavior. We also statistically analyzed futures and spot prices of the Nikkei 225 index, where we found a large positive correlation between the two prices and a fat-tail distribution of the basis. Simulations results show that, instead of the conventional single-market model, only the two-market model reproduces both statistical properties of futures prices.

Modeling the FX Market Traders’ Behavior

2013 ◽  
pp. 303-338 ◽  
Author(s):  
Monira Aloud ◽  
Edward Tsang ◽  
Richard Olsen
Keyword(s):  
Collective Behavior ◽  
Agent Based Modeling ◽  
Statistical Properties ◽  
Trading Behavior ◽  
Stylized Facts ◽  
Collective Behaviors ◽  
Agent Based ◽  
Trading Agents ◽  
Individual Traders ◽  
Fx Market

In this chapter, the authors use an Agent-Based Modeling (ABM) approach to model trading behavior in the Foreign Exchange (FX) market. They establish statistical properties (stylized facts) of the traders’ trading behavior in the FX market using a high-frequency dataset of anonymised OANDA individual traders’ historical transactions on an account level spanning 2.25 years. Using the identified stylized facts of real FX market traders’ behavior, the authors evaluate the collective behavior of the trading agents in resembling the collective behavior of the FX market traders. The study identifies the conditions under which the stylized facts of trading agents’ collective behaviors resemble those for the real FX market traders’ collective behavior. The authors perform an exploration of the market’s features in order to identify the conditions under which the stylized facts emerge.

scholarly journals Spoofing the Limit Order Book: A Strategic Agent-Based Analysis

Games ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 46
Author(s):  
Xintong Wang ◽  
Christopher Hoang ◽  
Yevgeniy Vorobeychik ◽  
Michael P. Wellman
Keyword(s):  
Limit Order Book ◽  
Trading Strategies ◽  
Order Book ◽  
Market Manipulation ◽  
Trading Behavior ◽  
Limit Order ◽  
Agent Based ◽  
Total Surplus ◽  
Private Values ◽  
Belief Learning

We present an agent-based model of manipulating prices in financial markets through spoofing: submitting spurious orders to mislead traders who learn from the order book. Our model captures a complex market environment for a single security, whose common value is given by a dynamic fundamental time series. Agents trade through a limit-order book, based on their private values and noisy observations of the fundamental. We consider background agents following two types of trading strategies: the non-spoofable zero intelligence (ZI) that ignores the order book and the manipulable heuristic belief learning (HBL) that exploits the order book to predict price outcomes. We conduct empirical game-theoretic analysis upon simulated agent payoffs across parametrically different environments and measure the effect of spoofing on market performance in approximate strategic equilibria. We demonstrate that HBL traders can benefit price discovery and social welfare, but their existence in equilibrium renders a market vulnerable to manipulation: simple spoofing strategies can effectively mislead traders, distort prices and reduce total surplus. Based on this model, we propose to mitigate spoofing from two aspects: (1) mechanism design to disincentivize manipulation; and (2) trading strategy variations to improve the robustness of learning from market information. We evaluate the proposed approaches, taking into account potential strategic responses of agents, and characterize the conditions under which these approaches may deter manipulation and benefit market welfare. Our model provides a way to quantify the effect of spoofing on trading behavior and market efficiency, and thus it can help to evaluate the effectiveness of various market designs and trading strategies in mitigating an important form of market manipulation.

Do Changes in Natural Gas Futures Prices Influence Changes in Natural Gas Spot Prices?

1993 ◽  
Vol 11 (5) ◽  
pp. 467-472 ◽  
Author(s):  
John H. Herbert
Keyword(s):  
Natural Gas ◽  
Futures Markets ◽  
Spot Market ◽  
Spot Markets ◽  
Futures Prices ◽  
Market Prices ◽  
Spot Prices ◽  
Futures Contract

Data on natural gas futures and spot markets are examined to determine if variability in price on futures markets influences variability in price on spot markets. Using econometric techniques, it is found that changes in futures contract prices do not precede changes in spot market prices.

Modeling the FX Market Traders' Behavior

2014 ◽  
pp. 350-384
Author(s):  
Monira Aloud ◽  
Edward Tsang ◽  
Richard Olsen
Keyword(s):  
Collective Behavior ◽  
Agent Based Modeling ◽  
Statistical Properties ◽  
Trading Behavior ◽  
Stylized Facts ◽  
Collective Behaviors ◽  
Agent Based ◽  
Trading Agents ◽  
Individual Traders ◽  
Fx Market

In this chapter, the authors use an Agent-Based Modeling (ABM) approach to model trading behavior in the Foreign Exchange (FX) market. They establish statistical properties (stylized facts) of the traders' trading behavior in the FX market using a high-frequency dataset of anonymised OANDA individual traders' historical transactions on an account level spanning 2.25 years. Using the identified stylized facts of real FX market traders' behavior, the authors evaluate the collective behavior of the trading agents in resembling the collective behavior of the FX market traders. The study identifies the conditions under which the stylized facts of trading agents' collective behaviors resemble those for the real FX market traders' collective behavior. The authors perform an exploration of the market's features in order to identify the conditions under which the stylized facts emerge.

Bounded Rationality and Market Micro-Behaviors

2010 ◽  
pp. 78-94
Author(s):  
Shu-Heng Chen ◽  
Ren-Jie Zeng ◽  
Tina Yu ◽  
Shu G. Wang
Keyword(s):  
Decision Making ◽  
Genetic Programming ◽  
Bounded Rationality ◽  
Human Subject ◽  
Trading Strategies ◽  
Programming System ◽  
Trading Behavior ◽  
Agent Based ◽  
The Difference ◽  
Near Future

We investigate the dynamics of trader behaviors using an agent-based genetic programming system to simulate double-auction markets. The objective of this study is two-fold. First, we seek to evaluate how, if any, the difference in trader rationality/intelligence influences trading behavior. Second, besides rationality, we also analyze how, if any, the co-evolution between two learnable traders impacts their trading behaviors. We have found that traders with different degrees of rationality may exhibit different behavior depending on the type of market they are in. When the market has a profit zone to explore, the more intelligent trader demonstrates more intelligent behaviors. Also, when the market has two learnable buyers, their co-evolution produced more profitable transactions than when there was only one learnable buyer in the market. We have analyzed the trading strategies and found the learning behaviors are very similar to humans in decision-making. We plan to conduct human subject experiments to validate these results in the near future.

scholarly journals The interdependence of coffee futures and spot markets - An econometric analysis

2021 ◽  
pp. 56-66
Author(s):  
B.N. Pradeepa Babu ◽  
Arun Muniyappa
Keyword(s):  
New York ◽  
Futures Markets ◽  
Spot Markets ◽  
Futures Prices ◽  
Spot Prices ◽  
Robusta Coffee ◽  
Indian Context ◽  
Long Run ◽  
Short Run ◽  
Producer Prices

Coffee is an export-oriented commodity for producing countries, and it is actively traded at international commodity exchange platforms viz., Intercontinental Exchange (ICE), New York and ICE, Europe. This study examines the interdependence of futures and spot markets for coffee in the price discovery mechanism, particularly in the Indian context. The study has considered both the International Coffee Organization (ICO) indicator prices and producers’ prices in India’s spot prices. The study confirms the existence of a stable long-run relationship between ICE coffee futures and ICO spot prices, implying that both prices react to the same set of market information. While there is an indication of equilibrium or long-run relationship between ICE Coffee futures (New York) and Arabica producer prices (at farm gate level) in India, the same was not true for Robusta coffee. The absence of co-integration between ICE futures prices (London) and Robusta producer prices in India suggested only a short-run relationship between them. The findings of the study conclude with strong evidence that the farm gate prices in India have been caused by the ICE futures markets, declining the contrary.

Bounded Rationality and Market Micro-Behaviors

2012 ◽  
pp. 1352-1369
Author(s):  
Shu-Heng Chen ◽  
Ren-Jie Zeng ◽  
Tina Yu ◽  
Shu G. Wang
Keyword(s):  
Decision Making ◽  
Genetic Programming ◽  
Bounded Rationality ◽  
Human Subject ◽  
Trading Strategies ◽  
Programming System ◽  
Trading Behavior ◽  
Agent Based ◽  
The Difference ◽  
Near Future

We investigate the dynamics of trader behaviors using an agent-based genetic programming system to simulate double-auction markets. The objective of this study is two-fold. First, we seek to evaluate how, if any, the difference in trader rationality/intelligence influences trading behavior. Second, besides rationality, we also analyze how, if any, the co-evolution between two learnable traders impacts their trading behaviors. We have found that traders with different degrees of rationality may exhibit different behavior depending on the type of market they are in. When the market has a profit zone to explore, the more intelligent trader demonstrates more intelligent behaviors. Also, when the market has two learnable buyers, their co-evolution produced more profitable transactions than when there was only one learnable buyer in the market. We have analyzed the trading strategies and found the learning behaviors are very similar to humans in decision-making. We plan to conduct human subject experiments to validate these results in the near future.

Relationship between Coffee Prices in Spot and Futures Markets-An Empirical Analysis

2020 ◽  
pp. 180-188
Keyword(s):  
New York ◽  
Correlation Coefficients ◽  
Strong Relationship ◽  
Futures Market ◽  
Regression Coefficients ◽  
Futures Prices ◽  
Market Prices ◽  
Spot Prices ◽  
Correlation And Regression Analysis ◽  
Highly Correlated

The present study explored the relationship between spot and futures coffee prices. The Correlation and Regression analysis were carried out based on monthly observations of International Coffee Organization (ICO) indicator prices of the four groups (Colombian Milds, Other Milds, Brazilian Naturals, and Robustas) representing Spot markets and the averages of 2nd and 3rd positions of the Intercontinental Exchange (ICE) New York for Arabica and ICE Europe for Robusta representing the Futures market for the period 1990 to 2019. The study also used the monthly average prices paid to coffee growers in India from 1990 to 2019. The estimated correlation coefficients indicated both the Futures prices and Spot prices of coffee are highly correlated. Further, estimated regression coefficients revealed a very strong relationship between Futures prices and Spot prices for all four ICO group indicator prices. Hence, the ICE New York (Arabica) and ICE Europe (Robusta) coffee futures prices are very closely related to Spot prices. The estimated regression coefficients between Futures prices and the price paid to coffee growers in India confirmed the positive relationship, but the dispersion of more prices over the trend line indicates a lesser degree of correlation between the price paid to growers at India and Futures market prices during the study period.

Pricing of Futures Contracts

2018 ◽  
Author(s):  
Timothy A. Krause
Keyword(s):  
Fair Value ◽  
Commodity Futures ◽  
Futures Contracts ◽  
Spot Price ◽  
Futures Prices ◽  
No Arbitrage ◽  
Spot Prices ◽  
Cost Of Carry ◽  
Contract Expiration ◽  
The Cost

This chapter examines the relation between futures prices relative to the spot price of the underlying asset. Basic futures pricing is characterized by the convergence of futures and spot prices during the delivery period just before contract expiration. However, “no arbitrage” arguments that dictate the fair value of futures contracts largely determine pricing relations before expiration. Although the cost of carry model in its various forms largely determines futures prices before expiration, the chapter presents alternative explanations. Related commodity futures complexes exhibit mean-reverting behavior, as seen in commodity spread markets and other interrelated commodities. Energy commodity futures prices can be somewhat accurately modeled as a generalized autoregressive conditional heteroskedastic (GARCH) process, although whether these models provide economically significant excess returns is uncertain.

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