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This article examines the accuracy and bias inherent in the wisdom of crowd effect. The purpose is to clarify what kind of bias crowds have when they make predictions. In the theoretical inquiry, the effect of the accumulated absolute deviation was simulated. In the empirical study, the observed biases were examined using data from forecasting foreign exchange rates.

In the theoretical inquiry, the effect of the accumulated absolute deviation was simulated based on mathematical propositions. In the empirical study, the data from 2004 to 2011 were provided by Nikkei, which holds the “Nikkei Yen Derby” competition. In total, 3,657 groups forecasted the foreign exchange rate, and the first prediction was done in early May to forecast the rate at the end of May. The second round took place in June in a similar manner.

The average absolute deviation in May was smaller than that in June. The first round of prediction was more accurate than the second round one. Predictors were affected by the observable real exchange rate, such that they modified their forecasts by referring to the actual data in early June. An actuality bias existed when the participants lost their diverse prospects. Since the standard deviations of the June forecasts were smaller than those of May, the fact-convergence effect was supported.

This article reports novel findings that affect the wisdom of crowd effect—referred to as actuality bias and fact-convergence effect. The former refers to a forecasting bias toward the observable rate near the forecasting date. The latter implies that predictors, as a whole, indicate smaller forecast deviations by observing the realized foreign exchange rate.

Multi-criteria optimization by meta-goal programming of a portfolio of asset allocation mutual funds is the focus of this chapter. Asset allocation is generally defined as the allocation of an investor's portfolio across a number of different asset classes. The standard classical portfolio model uses the nonlinear model of quadratic programming to minimize risk and maximize return by mean absolute deviation. Instead of the variance measure of the risk of the rate of return, the mean absolute deviation is used as a measure of risk. In this chapter, three types of meta-goals are Type 1: a meta-goal relating to other percentage sum of unwanted deviations, Type 2: a meta-goal relating to the maximum percentage deviation, and Type 3: a meta-goal relating to the percentage of L∞ goals.

With the use of meta-goal programming, a portfolio model, based on Morningstar Stock Sector and Morningstar Bond Sectors, is developed. These sectors are part of an indexed mutual fund for stock and for bonds. The asset allocation is based upon a set of four meta-goals: (1) forecasted earnings growth, (2) forecasted revenue growth, (3) unwanted deviation of absolute deviation for the risk for stock investments, and (4) unwanted deviation of absolute deviation for the risk for bond investments.

Numerous articles have been written to prove or to disapprove the hypothesis of market efficiency. The purpose of this paper is to apply the forecast accuracy measure, mean absolute deviation (MAD), to check the validity of the hypothesis.

Forecast accuracies from applying different simple moving average methods to independently identically distributed (i.i.d.) or near i.i.d. normal time series are assessed by MAD. When moving period n is greater than m, then the mean of the MADs from the MA with n moving periods will be smaller than the mean of the MADs from the MA with m moving periods.

In this study, when different MAs are applied to four near i.i.d. finance time series from Fama’s papers, the MAD cannot distinguish the differences among MA methods with various moving periods. This contradiction implies that the four finance time series in Fama’s papers may not be i.i.d and implies that the market is not efficient.

The finding is only based on simulation and four near i.i.d. time series studied in Fama’s papers in 1965 and 1970.

The study shows that that the differences of the rates of returns from Johns Manville, Goodyear, Owens Illinois, and General Electric studied are not i.i.d. and that the market is not efficient. It refutes what Fama (1965, 1970) has claimed.

When the market is not efficient, investors may gain profit from the market.

Based on the literature review, this is the first study to use the forecast accuracy measure, MAD, for market efficiency.

Recent advancement in fused deposition modelling (FDM) rapid prototyping technology has made it a viable technology for application in reconstructive surgery. The purpose of this paper is to investigate the errors generated during the fabrication stage of complex anatomical replicas derived from computed tomography coupled with the technique of FDM.

An evaluation on the errors generated during the fabrication process of two anatomical parts (skull or mandible) for different human sizes (infant, female or male) is carried out. A comparison between the linear measurements of 11 landmarks on the virtual model of a skull and nine for the mandible of patient specific and its replica is conducted. Furthermore, eight landmarks are chosen to evaluate the bone thickness variation over the fabricated replicas.

Although the FDM technology proved the ability to manufacture and to fit prosthesis to a patient's unique proportions quickly and with relatively low cost, the model accuracy is a key factor to the applicability of such technology. The results show undersized replicas with an overall absolute average deviation of 0.24 per cent with an average standard deviation of 0.16 per cent of the skull models and 0.22 per cent with a 0.11 per cent standard deviation of the mandibles. Furthermore, a high level of accuracy is reflected in the representation of the measured bone thickness with deviations in the order of 100th of a millimetre being reported.

The paper demonstrates an outstanding accuracy using FDM process for the fabrication of anatomical replicas using models of different human sizes and gender in comparison to other established rapid prototyping techniques.

The purpose of this paper is to prove the effectiveness of minimum semi‐absolute deviations (MSAD) method in dynamic portfolio investment.

In financial investment, the classical static portfolio theory of Markowitz type lacks the dynamic adaptability to the changing market situations. This paper proposes a dynamic portfolio theory which uses MSAD criterion on a moving window to replace the Markowitz mean‐variance analysis.

Two specific models are developed to test the validity of the MSAD method: the first model constructs a portfolio consisting of Shanghai‐Shenzhen 300 Index and a national debt as two contrarian assets; the second model constructs a portfolio consisting of a complete set of 18 Chinese stock sector indices and a national debt. The empirical results of the test using six‐year monthly data (2005 to 2010) provide significant evidence that the MSAD method is valid, producing superior returns of investment over the stock index during the test period.

The findings in this study clearly highlight the validity of the MSAD method in determining the weights of assets in Chinese stock markets.

In order to resolve the problem of portfolio investment in Chinese stock markets, the MSAD method with stop loss control strategy can be used for investors to obtain the weights of assets and control the risk.

This study analyzes and verifies the effectiveness of the MSAD method in dynamic portfolio investment. The stop loss control strategy designed and used in the MSAD method is a pioneering and exploratory experiment.

Organisations either keep spares for their own use, or‐for‐sale to other organisations. In either case, the ultimate need is to be able to replace worn or defective parts in operational machinery or equipment. In an economic sense, spares are kept to meet the needs of the situation in the cheapest way.

The purpose of this paper is to provide an attempt to evaluate the risk-adjusted performance of international mutual funds using the risk statistic generated by the mean absolute deviation (MAD) and promote the ability of portfolio managers and investors to make the logical decisions for selecting different funds using the new optimized measures.

This study evaluates the performance of 50 international mutual funds using optimized risk-adjusted measures by the MAD over the monthly period 2001-2010. Using 50 linear programming models, the MAD is first computed by the linear programming models, and then seven performance measures of Treynor, Sharpe, Jensen’s α, M2, information ratio (IR), MSR, and FPI are optimized and proposed by the MAD to evaluate the mutual funds.

The empirical evidence detects that the MAD is an important determinant to evaluate the funds’ performance. Using the MAD statistic, this paper shows that new optimized measures are mostly over-performed by the benchmark index; in addition, these optimized measures have close correlation with each other. The results, therefore, detect the importance of using new optimized measures in evaluating the mutual funds’ performance.

The result of this study can be directly used as an initial data for decision of investors and portfolio managers who are seeking the possibility of participating in the global stock market by the international mutual funds.

This paper is the first study which optimizes the variance of returns in the MAD framework for each fund to propose new seven optimized measures of Treynor, Sharpe, Jensen’s α, M2, IR, MSR, and FPI.

In this paper, the authors examine the association between conditional conservatism and deviations of the first digits of financial statement items from what are expected by Benford's Law.

This research uses data of companies listed on the London Stock Exchange. The authors measure deviations of first digits from Benford's Law following Amiram et al. (2015) and firm-year conditional conservatism following previous studies (Basu, 1997; Khan and Watts, 2009; García Lara et al., 2016). The authors use multiple regressions to provide evidence for their hypothesis.

The results show that conditional conservatism is positively associated with deviations from Benford's Law. The findings are robust across different measures of deviations and conditional conservatism. Also, the authors find that the relationship between deviations from Benford's Law and conditional conservatism is more pronounced for firms with debt issuance, and for leveraged firms facing financial distress. Next, the authors’ analyses confirm previous evidence by showing that the first digits of financial statement items of UK listed companies conform to Benford's Law at the firm-specific level and the market level, and deviations of income statements are larger than those of balance sheets and cash flow statements.

The research makes significant contributions to the literature. First, this is the first study that provides empirical evidence suggesting that conditional conservatism may be a source of deviations from Benford’s Law. Second, the authors provide evidence confirming previous US findings (e.g. Amiram et al., 2015) showing that the distributions of first digits of financial statement items of UK listed companies also conform to Benford's Law.

The authors’ findings have implications for auditors. Auditors should be aware of “false positive” for material misstatements when using Benford's Law as a risk assessment procedure. While both conditional conservatism and earnings management are related to deviations from Benford's Law, conservatism-related biases could indicate less audit risks.

The authors provide new and original evidence suggesting that conditional conservatism is related to deviations from Benford's Law.

During the last two decades, many Marxian economists have brought forth empirical evidence that supposedly supports a version of the “labor theory of value” that Marx rejected, namely the theory that individual commodities’ prices tend to equal their values. However, recent studies have challenged this conclusion. The present paper offers additional evidence and arguments against it. Firstly, the theory in question implies that prices will be higher, ceteris paribus, in industries in which variable capital is a relatively large component of total cost, but regression analysis of U.S. data compels us to reject this hypothesis. Secondly, although sectoral values and prices are very strongly correlated, simulation results indicate that the observed correlations are no higher than the correlations that can be obtained by aggregation, even if the disaggregated values and prices are uncorrelated and extremely far apart. Finally, many studies have found that average price-value deviations are small, but it is shown here that this finding is meaningless, since aggregation of the data tends systematically to reduce measures of average deviation.