Contents:
Wealth growth rate of investors. Blue line: informed traders; Red line: technical traders; Black line: noise traders; Green line: arbitrage traders. Arbitrage is theoretically risk free, but risks still exist in actual transactions. For example, the index tracks risks. We purchase the index by buying a spot portfolio; this process will have index-tracking bias. For another example, the market affects risk. When investors purchase a large number of assets, they generally cannot deal in fixed prices. Therefore, arbitrage investors are likely to have negative returns.
This is also in line with the real market. ANOVA was used to better observe the differences between the wealth growth rates of the four types of investors.
Table 3 shows the experimental results. This means the wealth growth rate differs among the four types of investors, and the effectiveness of the four trading strategies is therefore different. The second is the technical trading strategy, which ultimately does not increase investor wealth; it did, however, offer opportunities for profit in the simulation experiment. The third is the arbitrage trading strategy; its average wealth growth rate is negative, but it offers a chance for profit through arbitrage.
The last is the noise trading strategy. Noise traders suffered huge losses in the experiment, indicating that investors who are not informed and do not study do not successfully invest. When evaluating trading strategies for stock index futures, we should consider not only profitability but also risk to seek a balance between the two. Then, we analyze the wealth growth rate volatility of the four kinds of investors to evaluate the risk level of each trading strategy. Volatility is measured by standard deviation. Figure 6 and Table 2 show the results.
Wealth growth volatility of investors. ANOVA was used to better observe the differences in wealth growth rate volatility. Table 3 shows the detailed values.
We can see that there are significant differences between the wealth growth standard deviations of the four types of investors; the risks of all types of trading strategies show great differences. The technical trading strategy faces the biggest risks. The average standard deviations of the wealth growth rates of informed traders and arbitrage traders are similar.
Accordingly, the risks of those strategies are similar, although the risk of the arbitrage trading strategy is slightly higher. In addition to the profitability and risk analysis, cost is also an important factor used to evaluate trading strategies for stock index futures. Cost can directly affect the effectiveness of trading strategies and the results of the execution. The cost of the trading strategy includes the occupation of capital and impact cost.
Occupation of capital refers to the capital investors need to pay for the transaction in unit order. A high degree of occupied capital means the trading strategy has greater risk. Informed traders, technical traders, and noise traders only invest in the stock index futures market while arbitrage traders invest in both.
Thus, the capital requirement of arbitrage traders is greater than that of the other three types. We obtain 60, period data for the occupation of capital among all trading strategies. Then, we calculate the occupation of capital for each trading strategy in each day.
Figure 7 and Table 4 show the experimental results. Occupation of capital for the arbitrage strategy and other strategies. Red line: arbitrager strategy; Blue line: other strategies, include informed strategy, technical strategy and noise strategy. Figure 7 shows that the occupation of capital for the arbitrage strategy is greater than that for the other strategies. The variance in the occupation of capital is also greater for the arbitrage strategy than for the others, meaning the arbitrage strategy is more volatile.
As shown in Table 4 , the average capital occupation of the arbitrage strategy is 3. Thus, the capital occupation of arbitrage traders is nearly 6. Trading strategies can affect market trends, which might in turn affect the execution of trading strategies and transactions at optimal prices. The loss caused by this situation is known as the market impact cost, which is another type of cost. This study uses the number of deals in the optimal price to measure the impact costs of the trading strategies.
Footnote 7 The larger the number of deals, the smaller the impact cost. The informed, technical, and noise trading strategies are only used in the stock index futures market; they only affect that market and thus suffer impact costs from only one market. Meanwhile, since the arbitrage trading strategy operates in both markets simultaneously, it suffers impact costs from two markets. Thus, the impact cost of the arbitrage trading strategy is greater than that of the other three types. We obtain high-frequency data for the number of deals at the optimal price in the stock market and the stock index futures market.
We calculate the average value of the number of deals at the optimal price for the trading strategies to measure the daily average impact costs. Figure 8 and Table 4 show the experimental results. Average impact costs of the arbitrage strategy and the other strategies. We can see in Fig. This means the impact cost of the arbitrage trading strategy is higher than that of the others.
Evaluating trading strategies for the stock index futures market mainly involves analyzing benefits, costs, and risks. Cost analysis includes occupation-of-capital analysis and impact cost analysis. Each aspect i. The effectiveness of the trading strategy is the basic indicator. If investors only pursue high returns and pay no attention to risk, occupation of capital, and the impact cost, they are likely to face huge risks and higher costs. Meanwhile, a lack of risk-management awareness and skills can affect market stability and cause sharp movements.
The technical trading strategy performs well with regard to effectiveness, occupation of capital, and impact cost but has a relatively larger risk. If investors have better risk-management capabilities, their risks and benefits will be balanced at a higher level. Although the returns and risks of the arbitrage trading strategy are reasonable, it requires a lot of money. This study has some limitations that can be improved upon in future work.
First, the experiment could be done several times by changing the parameter settings number of traders, initial wealth of traders, transaction costs, and so on to observe the differences.
This will help improve our understanding of trading strategies. Second, based on the main contract period of the China stock index futures market, the sample period was set to 1 month, and the basic unit of the research was set to 1 day. To observe different results and improve the evaluation system for stock index futures, both the sample period and the unit of time can be changed.
Third, this study mainly uses the average value of market data as the basis for analysis. Future work can enrich the functions of the simulated market and observe changes in individual investor. This could provide a more accurate basis for evaluating trading strategies. Fourth, in the future, calibration studies of this model can be conducted to verify the connection and difference between the model and the real market.
This study has some practical implications. Namely, investors should continue to research and analyze the market to obtain sufficient market information. At the same time, they should continuously enrich their investment knowledge and skills, consider their situation in relation to market changes, update their trading strategies, and seek a balance between return and risk. All the data observations used in this paper come from the simulation data generated by the agent-based model in this paper.
We revised the stock index calculation method used in Xu et al.
Kuss, and D. Jeong, and J. Once your strategy is ready, the next step is to backtest the strategy. Li, and D. This is a robust strategy that is important for panels with a large number of individuals and time points because it mitigates heteroscedasticity and serial correlation. Initially, the cross-validation procedure divides the data set into two disjoint and complete subsets: the training set and the test set. Several papers have studied investor behavior.
For research on the impact of inconsistent trading mechanisms on the spot-futures cross-market, see Ref. Xiong et al. Therefore, the model in this study is essentially a single-asset model that does not consider the asset allocation of investors for multiple assets. We revised the price forecasting method used in Xu et al. Since the investor strategy contains technical strategies, the technical strategy needs to review the historical price series; hence, data are needed for the strategy warm-up. Regarding the length of the warm-up, different market models and different strategies require different lengths of time, which is generally determined by observing the price series trend in the experiment.
The purpose of this study is to compare and analyze investment strategies in the stock index futures market. Therefore, investment strategies for the spot market are not covered in Table 3. The optimal price is the price in the first level of the buy or sell side order book. In the order books market, if the trading strategy deals more frequently at the optimal price level, then the market impact cost is small, and the trading strategy is executed smoothly and vice versa.
DecisionPoint Trend Model DecisionPoint's mechanical trend-based approach to trading. Trading Strategies. Bollinger Band Squeeze This strategy uses Bollinger. Model-Based. Trading Strategies. Johann Christian Lotter / jcl@ oP group Germany GmbH.
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