Abstract
This chapter describes the validity of a passive investment strategy through agent-based simulation. As a result of intensive experimentation, I have concluded that a passive investment strategy is valid under conditions where market prices deviate widely from fundamental values. However, my agent-based simulation also shows that the increase in the rate of passive investment slows as financial restrictions become more severe. The results are of both academic interest and practical use.
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Notes
- 1.
The buy-and-hold method is an investment method to hold shares for medium to long term.
- 2.
The passive investment strategy is one of the most popular investment strategies in the asset management business.
- 3.
In the actual market, evaluation tends to be conducted according to baseline profit and loss.
- 4.
For example, if excess profit over a five-term period is 5 %, a one-term conversion would show this as a 1 % excess for each term period.
- 5.
Selection pressures on an investment strategy become higher as the coefficients’ value increases.
- 6.
On average, passive investors have obtained a better performance than fundamentalists.
- 7.
This model consists of an equal number of fundamentalists, passive investors, trend chasers, investors based on historical price average, and investors who estimate stock prices based on the latest price.
- 8.
Figure 9.5 shows the case where investors cannot go overweight more than 1 %. As the upper limit becomes stricter from 5 to 1 %, the portfolio’s risk decreases.
- 9.
Conditions where investors cannot go overweight more than 5 % against the benchmark weight are analyzed.
- 10.
At the 300th time step in Fig. 9.10, most investors in the market employ a passive investment strategy.
- 11.
Reduction of dispersion in investment behavior caused by the investment restrictions might be one factor. For an analysis of the influence of dispersion of fundamentalists’ valuations, refer to Takahashi [29].
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Takahashi, H. (2014). Analyzing the Validity of Passive Investment Strategies Under Financial Constraints. In: Chen, SH., Terano, T., Yamamoto, R., Tai, CC. (eds) Advances in Computational Social Science. Agent-Based Social Systems, vol 11. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54847-8_9
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