In this research, we review the relevant literatures to discuss the predictability of foreign exchange rates. Besides, we collect literatures to examine the development of the fundamental models, market models, technical analysis and trading rules and compare and evaluate the precision of these models. Moreover, we make a case study of a global leading investment bank to discuss how to use these models in practice. The result shows that fundamental models can help to establish the long-term equilibrium but have some shortcomings and thus we could adopt market models to resolve the shortages and the technical analyses and rules to set the exact price levels for trading purposes.

In the last few years, it has been proved that the movements of financial asset have the property of non-linearity and show some tendency within a given period. Increasing evidence that technical trading rules can detect non-linearity in financial time series has renewed interest in technical analysis. This study evaluates the market timing ability of the moving average trading rules in twelve equity markets in the developed markets and the emerging markets from January 1990 through Match 2002. We use traditional test, bootstrap p-value test, Cumby-Modest¡¦s market timing ability test and simulation stock trade to evaluate market timing ability. The overall results indicate that the moving average trading rules have predictive ability with respect to market indices in the Asia emerging stock markets. These findings may provide investors with important asset allocation information.

The price of stocks, futures, commodities and currency are for ever changing. Anyone interested in financial prices soon discovers that changes in prices are frequently substantial and are always difficult to forecast. This paper describes the behavior of prices from a statistical perspective. Specifically, employ several technical trading rules to uncover the trend of futures price movement and attempt to make profit out of the trend. In this paper, trading of seven technical trading systems is simulated for three futures contracts from September 1998 to March 2005 to test for market disequilibrium. The results differ by trading systems. Four systems produced positive mean net returns and five systems produced positive gross return when optimal parameters were used. These results indicate that, there exist opportunities to design profitable trading systems for futures markets.

參考Fang 2003年研究方法架構，我們檢驗了結合策略(結合技術分析法則和時間序列模型)應用在六個亞洲股票市場。由於技術分析法則和時間序列模型皆可利用過去歷史資訊來預測報酬，所以結合策略的實證結果優於技術分析法則和時間序列模型。此篇中超額報酬的計算是與買進持有相比較下未考慮交易成本的超額報酬。實證結果顯示，結合策略在完整樣本中可以成功的預測資產報酬，在六個國家的平均上，結合策略的超額報酬為0.19%優於技術交易法則下的0.13%和時間序列模型下的0.17%。並且，發現在新興國家如台灣、泰國、馬來西亞和南韓的預測能力比在已開發國家市場如香港和日本還要來的好。預測能力可被低階的自我相關係數解釋。除此之外，發現我們的預測能力受到非同步交易的影響。非同步交易所造成的衡量誤差使得超額報酬下降，但是我們的預測能力還是存在的。 / Following Fang and Xu (2003), we examine trading strategies combining technical trading rules and times series forecasts on six Asian stock markets. Since both technical trading rules and time series models can exploit predictable components as function of past prices or returns, the combined strategies outperform both technical trading rules and time series forecasts. The excess returns before transaction costs for each rule and country are compared to a passive buy-and-hold strategy. The combined strategies are quite successful in predicting asset returns in full samples. On average the buy-sell returns for combined strategies are 0.19% much higher than 0.13% for technical trading rules and 0.17% for time series models. Besides, we also find that all three rules have more explanatory power in emerging markets such as Taiwan, Thailand, Malaysia and Korea than more developed markets such as Japan and Hong Kong. The predictability can be explained by significant low-order autocorrelations in returns. Moreover, excess returns (pre-trading costs) for both time series models and combined strategies can be partially attributed to the measurement errors arising from non-synchronous trading. The non-synchronous trading bias reduces but does not eliminate the predictive power of combined strategies.

Studying whether new trading rules provide higher returns than the buy-and-hold strategy is relevant for both finance theory and the asset management field. In this thesis, we examine the profitability of the newly proposed trading strategy based on the concept of price overreaction on eight developed stock indices. In comparison to other studies, we extend a definition of price overreaction with an inclusion of a minimum volatility threshold. Based on the Ordinary Least Squares model, we find that a volatility condition significantly improves the predictability of return reversals after positive price overreaction. For comparison with the buy-and-hold, we use Hansen's Superior Predictive Ability test that corrects the data snooping bias. Despite better annualised returns during in-sample and out-of-sample periods, the results show that the proposed strategy is not superior to the buy-and-hold at any stock index due to heavy reliance on the predictions of the largest declines. Nevertheless, we confirm the effect of decoupling (flight to quality) that can positively affect our strategy, but only when we do not take into account transaction costs. In the end, we summarize behavioural concepts that lie behind our strategy as the overreaction and decoupling are mostly justified with cognitive biases.

第一篇論述討論處置效果於選擇權市場的實證。處置效果係指投資人在處分資產時，傾向盡快賣出有未實現利得的投資部位，並且繼續持有有未實現損失的投資部位的行為偏誤現象。文獻上有關處置效果的實證多半集中在股票市場而少有於選擇權市場的實證。選擇權市場一般認為是具有私有資訊及較具備金融知識與經驗的投資人會選擇交易的市場。本文實證處置效果在指數選擇權市場上的影響。我們認為對於選擇權投資人來說，價內外程度是最重要且顯而易見的資訊，是很直觀可以衡量可能利得及損失的參考點。相較於傳統衡量根據過去交易價格所形成的未實現損益指標，價內外程度更能吸引投資人的注意力。以本文所提出的基於價內外程度衡量之賣出傾向指標(Moneyness-based Propensity to Sell, MPS)以及根據Grinblatt and Han (2005)所形成的調整後未實現資本利得指標(adjusted Capital Gains Overhang, ACGO)，每周將買權(賣權)排序成五等分後，我們發現持有最高等分的MPS或ACGO的買權(賣權)並賣出最低等分的買權(賣權)所形成的投資組合能夠產生超額報酬，顯示處置效果在指數選擇權市場亦存在。利用雙重排序(double sorting)的方法，我們發現MPS相較於ACGO，是較能夠在選擇權市場捕捉處置效果的指標。第二篇論述討論相似度衡量策略在期貨市場獲利的可能性。文獻上對於技術交易是否能產生顯著的報酬結果並不一致，然而實務上分析過去的價格走勢並使用技術指標所產生的訊號，是廣泛被接受的。現有測試技術交易指標獲利能力的文獻，通常假設投資人在實證測試的樣本期間一致性的參考某個交易指標產生的交易訊號並依此交易。然而實務上投資人可能同時參考不同的交易指標，每次交易可能根據不同交易指標所產生的訊號，且投資人會從歷史交易價格走勢中尋找類似於現有走勢的狀況，以這些歷史走勢接續的報酬率做為現有走勢未來報酬率的預期值。本文中我們提出一個較符合實際狀況的決策過程來描述技術交易投資人的行為，並重新檢視技術交易的獲利能力。我們提出的決策過程包含三個步驟。首先投資人建立一個特徵向量，包含投資人所認為足以預測未來報酬率並足以描述現況的指標。第二個步驟，投資人從過去某段期間中尋找相似於現有特徵向量的歷史狀況，並以這些歷史狀況接續的報酬率來作為預測的根據。最後，投資人依照過去的歷史狀況與現在有多相似，作為接續報酬率的加權權重，並以相似度權重加權平均報酬來做為未來報酬率的預測值，我們將依照相似度加權報酬所產生交易訊號所形成的策略稱為相似度衡量交易策略(Similarity-based trading rules)。我們檢視相似度衡量交易策略在九個不同的期貨市場中的獲利能力，在考量data-snooping及交易成本後，每日相似度衡量交易策略仍在其中六個市場中獲得顯著的報酬率。 / The disposition effect, which refers to the tendency of investors to selling their winning investments too soon and to hold losing investments too long, has been well-documented in the extant literature. However, while empirical researches focus on examining the behavioral bias in the stock market, little attention is paid to the option market, where most informed investors and sophisticated traders gather. This essay tests for the disposition effect on the index options market. We argue that moneyness, the most salient and readily available information for option investors, is a natural reference point for potential gains and losses, which likely attracts market participants’ attention more than traditional measures that are based on past trading prices. Based on the Moneyness-based Propensity to Sell (MPS) measure that we introduce and an adjusted capital gains overhang (ACGO) measure of Grinblatt and Han (2005), we find that a strategy formed by buying calls/puts in the highest MPS or ACGO quintile and selling those in the lowest quintile would generate significant abnormal returns, suggesting the presence of the disposition effect. Using double sorting method, we find that the MPS is better as a measure in capturing the disposition effect on the options market than the ACGO. While the literature documents mixed results for the profitability of technical trading rules, the use of technical buy/sell signals based on analyzing past prices is widely accepted by practitioners. The existing literature on testing the predictive ability of technical trading mostly assumes that a technical investor consistently makes investment decisions based on the buy/sell signals according to one particular trading rule during the entire sample period. However this may be far from reality. Technical investors may simultaneously make predictions based on different technical indicators and follow different technical signals. Furthermore, they analyze historical price patterns that are similar to the current market condition and make assessment of future returns based on the subsequent returns of these similar patterns. The process is known as charting. We attempt to propose a more realistic decision-making process that incorporates the similarity-based predictors to account for technical investors’ decisions in the real world and reexamine the profitability of technical trading rules. The proposed process includes three steps. First, the investor attempts to predict future returns based on a vector of current characteristics that is sufficient for his assessment of the future returns and to depict the present scenario of the stock market. Second, the investor searches for the similar patterns in a specific time window prior to the current date and make an assessment of the future returns based on how similar these past patterns and the current pattern are and how rewarding the subsequent returns of the similar patterns are. Third, the investor is assumed to form a similarity-based indicator which is an assessment of the future returns depended on the similarity-weighted average of all previously observed values of the subsequent returns. The technical investor is then assumed to buy/sell according to the signals generated by the similarity-based trading rules (SBTR). We examine the profitability of the SBTR in nine futures markets and find significantly positive and robust returns after considering the data-snooping adjustments and transaction costs in six of the nine markets.