In this article, we explore the determinants of foreign exchange market intervention by the People's Bank of China as well as RMB real exchange rate. Mmonthly data from July 2005 to October 2010 are used. In the foreign exchange market intervention, operating variables and economic variables are studied separately. For the economic variables, we find that economic leading index of China is an important factor to determine whether to intervene or not. In addition, we find that producer price index is better than consumer price index to explain intervention in foreign exchange market. Economic leading index of U.S. is also important to determine the intervention. For the operating variables, we find that intervention by the People's Bank of China has the characteristics of leaning against the wind and deferred intervention. Foreign capital inflows are also the important determinant of the intervention. As for the determinants of RMB real exchange rate, we find that the China-U.S. interest rate differentials and China's business cycles relative to the U.S. are the main factors to determine the RMB real exchange rate. Also, the RMB tends to move with the Euro's in the same direction.

The main topic of my thesis is the problem of monitoring business cycles. Composite leading indicators are one of the options, how to make this monitoring. In my thesis I am going inside of the process of construction of composite leading indicator. I am comparing the methods of OECD, Eurostat and Conference Board. Special attention is dedicated to the methods of czech institutions as well. These methods are still being evolved and improved, which makes the analysis more difficult. Together with all the information about business cycle and economic policy in Czech republic between 1993-2015. I am judgeing the functionality of leading indicators for the monitoring of business cycle. Method of my analysis is SWOT analysis so the result of this thesis is mentioning of the strengths, weaknesses, opportunities and threaths of the making and application of composite leading indicators.

股票市場乃屬長期資本市場，企業家透過「資本證券化」的方式向投資人募集資金，做為公司營運及擴充規模之用。是故股票市場繫乎一國的經濟發展，乃經濟發展之櫥窗。無論基於何種因素，股價確實會有漲跌互異的現象，但消息面、心理面或其他非經濟因素並不能完全的支配股價走勢，從長期而論，股價終究會回歸基本面，所謂基本面，就是經濟之榮枯，常以景氣的好壞來表現，景氣循環即為一種經濟波動的現象。是故，雖致使股價波動的因素繁多，然而由長期基本面的觀點來看，景氣循環是否為解釋台灣股價指數長期走勢的主要力量呢？此乃本文所欲探尋的答案。本文以經建會所公佈之景氣領先指標綜合指數及其組成要素分別代表景氣狀況，從理論與文獻上整理說明股價變動與景氣循環的關係，並陳述1990年代的台灣股價指數與景氣循環走勢之關係，最後利用由Johansen所發展非常適於經濟模型的估計與檢定的計量工具---共整合分析與向量誤差修正模型，企圖以變數間所具有的整合線性關係作為衡量長期的均衡關係，並以均方誤差(RMSE)與絕對平均百分比誤差(MAPE)評量預測績效。 本文最終實證所得之各項重要結論如下： 一、股價與領先指標綜合指數 短期上落後一期和落後四期的領先指標綜合指數變動率與股價報酬率具有顯著的正向關係，此外股價與領先指標綜合指數長期存在正向共整合方程式。 二、股價與貨幣供給M1b具正向關係 長期而言依據共整合檢定，兩者具有長期均衡關係，並在同期時具顯著正向關係；在短期方面，依誤差修正模型之t檢定當期股價報酬率與落後一期之貨幣供給變動率呈現顯著正相關。 三、股價與海關出口值、新接訂單指數 股價分別在長期與兩者具均衡關係，並在同期時具顯著正向關係，但在短期上並無明顯關係。 四、股價與躉售物價、製造業平均每人每月工時、台灣地區房屋建築申請面積並無明顯關係。 五、所有五個共整合模型之預期值，均顯示出在上升波段預期值低於股價實際值，而在下跌波段預期值高於股價，此明顯反應了台灣股市投資人較不重視基本面分析，而以短線操作為主，心理因素、炒作因素影響重大，所以經濟景氣時常一窩峰買進而高估股價，反之，則大量殺出而低估股價。 六、五項共整合模型預期績效之良劣順序為：1.領先指標綜合指數與股價之ECM；2.三領先變數綜合與股價之ECM；3.M1b與股價之ECM；4.製造業新接訂單與股價之ECM；5.海關出口值之ECM由上面之順序顯示考量較多經濟變數較能涵蓋實質經濟，也能獲致較佳之預期。 總合而言，本研究各項模型雖不盡如人意，但對於大盤走勢之預期有不錯之效果，若再加入國人之心理因素，於牛市中將預期值往上修正，而於熊市將預期值往下修正，本模型應可更貼近實際股市情況。