The price dynamics of common trading strategies
By J. D. Farmer, S. Joshi. 2000
467 citations recorded by the source corpus.
A deterministic trading strategy can be regarded as a signal processing element that uses external information and past prices as inputs and incorporates them into future prices. This paper uses a market maker based method of price formation to study the price dynamics induced by several commonly used financial trading strategies, showing how they amplify noise, induce structure in prices, and cause phenomena such as excess and clustered volatility.
Subfields: Economics and Econometrics, Finance, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/b287b4d88f7a2990fb12bf7478cd12b04133d8dd
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Cars H. Hommes
- Xue-zhong He
- Roberto Dieci
- Frank H. Westerhoff
- Carl Chiarella
- Florian Wagener
- Laura Gardini
- Youwei Li
In Finance
- Cars H. Hommes
- Xue-zhong He
- Frank H. Westerhoff
- Roberto Dieci
- Carl Chiarella
- Florian Wagener
- Laura Gardini
- Lukas Menkhoff
In Management Science and Operations Research
- Frank H. Westerhoff
- Xue-zhong He
- Roberto Dieci
- Cars H. Hommes
- Florian Wagener
- Carl Chiarella
- Laura Gardini
- Fabio Tramontana
Citations in the corpus
- On the complicated price dynamics of a simple one-dimensional discontinuous financial market model with heterogeneous interacting traders (2010, methodology): “It is also worth mentioning the works by Hommes (1991, 1995); Hommes and Nusse (1991) and Hommes et al. (1995). Discontinuous models are furthermore discussed in Puu and Sushko (2002); Tramontana et al. (2009, 2010) and Bischi et al. (2010). The bifurcations occurring in a piecewise-smooth system ma”
- Complexity and Empirical Economics (2005, background): “Farmer and Joshi (2002) show that for some parameter values, excess holding returns will have little short-run autocorrelation. In both contexts, the issue is less whether for certain specifications one can avoid predictability of excessive holding returns but whether this predictability is ruled ou”
- A robust rational route to randomness in a simple asset pricing model (2005, unknown): “Let us now summarize the complete evolutionary adaptive belief system: pt+1 = pt + μ(n1tz1t + n2tz2t − zs), (15)”
- Agent-based Computational Finance (2006, background): “A more recent small type market is Farmer & Joshi (2002).”
- Complex Evolutionary Systems in Behavioral Finance (2008, background): “…and LeBaron (1996), Arthur et al. (1997), Brock and Hommes (1997b), Youssefmir and Huberman (1997), LeBaron et al. (1999), Lux and Marchesi (1999,2000), Farmer and Joshi (2002), Kirman and Teyssière (2002), Hommes (2002), Iori (2002), Cont and Bouchaud (2000) and Gaunersdorfer and Hommes (2007).”
- Structural stochastic volatility in asset pricing dynamics: Estimation and model contest (2012, background): “of different agents that one would have to keep track of over time (see Farmer and Joshi, 2002; LeBaron, 2006). 13 We owe these observations to one of the referees. 14 A historical perspective on the recurrent phenomenon of price misalignments is given by Kindleberger (2000). Shiller (2005, Ch.”
- Nonlinearities and Cyclical Behavior: The Role of Chartists and Fundamentalists (2003, background): “In Day and Huang (1990) and Farmer and Joshi (2002), heterogeneous traders rely on nonlinear trading rules to determine their orders.”
- HETEROGENEOUS BELIEFS, RISK, AND LEARNING IN A SIMPLE ASSET-PRICING MODEL WITH A MARKET MAKER (2003, methodology): “Farmer and Joshi (2002) use a market-maker-based method of price formation to study the price dynamics induced by several commonly used financial trading strategies to show how they amplify noise, induce structure in prices, and cause phenomena such as excess and clustered volatility.”
- Asset Price and Wealth Dynamics in a Financial Market with Heterogeneous Agents (2006, background): “…interaction of heterogeneous agents have been proposed (Day and Huang (1990), Kirman (1991), Brock and LeBaron (1996), Brock and Hommes (1998), Lux (1998), Gaunersdorfer (2000), Chiarella and He (2001a, 2003), Farmer and Joshi (2002), Chen and Yeh (2002), Hommes et al. (2005), to quote only a few).”
- The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis (2007, background): “Fifth, studies have explored the relation between non-linear exchange rate modelling and technical analysis (Clyde and Osler, 1997; Fiess and MacDonald, 1999; Kilian and Taylor, 2003; De Grauwe and Grimaldi, 2006, 2006a; Reitz and Taylor, 2006).”
- Power-law behaviour, heterogeneity, and trend chasing (2007, unknown): “…al. (1995), Lux (1995, 1997, 1998), Brock and LeBaron (1996), Arthu et al. (1997), Brock and Hommes (1997, 1998), Chen and Yeh (1997, 2002), Lux and Marchesi (1999), Bullard and Duffy (1999), LeBaronet al. (1999), LeBaron (2000, 2001, 2002), Iori (2002), Hommes (2002) and Farmer and Joshi (2002).”
- Heterogeneity, convergence, and autocorrelations (2008, unknown): “…(1992), Chiarella et al. (2002), Chiarella and He (2001, 2002, 2003b), Dacorogna et al. (1995), Day and Huang (1990), DeLong et al. (1990), Farmer and Joshi (2002), Frankel and Froot (1987), Gaunersdorfer (2000), Giardina and Bouchaud (2003), Hommes (2001, 2002), Iori (2002), LeBaron…”
- A nonlinear structural model for volatility clustering (2000, background): “Agent based evolutionary modeling of financial markets is becoming quite popular and recent contributions include the computational oriented work on the Santa Fe artificial stock market [3], [35], the stochastic multi-agent models of Lux and Marchesi [38], [39], genetic learning in Arifovic and Genc”
- Confidence and the Stock Market: An Agent-Based Approach (2014, methodology): “According to Farmer and Joshi [19], a market impact function is here derived to adjust the stock price.”
- Heterogeneous Agent Models in Economics and Finance, In: Handbook of Computational Economics II: Agent-Based Computational Economics, edited by Leigh Tesfatsion and Ken Judd, Elsevier, Amsterdam 2006, pp.1109-1186 (2005, background): “…time model due to Beja and Goldman (1980) and Chiarella (1992), allowing for limit cycles, whereas subsection 4.2 discusses a discrete time model due to Day and Huang (1990), exhibiting chaotic asset price fluctuations, and market maker model due to Farmer (2002) and Farmer and Joshi (2002).”
- Heterogeneous expectations, exchange rate dynamics and predictability (2007, unknown): “Further interesting models with heterogeneous traders include Day and Huang (1990), Kirman (1991), De Grauwe and Dewachter (1993), De Grauwe and Grimaldi (2005), Brock and Hommes (1998), Lux and Marchesi (2000), Farmer and Joshi (2002) and Rosser et al. (2003).”