nep-fmk New Economics Papers
on Financial Markets
Issue of 2017‒03‒05
six papers chosen by

  1. Bubbles in Experimental Asset Markets By Praveen Kujal; Owen Powell
  2. Testing excess returns from passive Options investment strategies By José P. Dapena; Julian R. Siri
  3. Pricing of bonds and equity when the zero lower bound is relevant By Kick, Heinrich
  4. Modeling euro area bond yields using a time-varying factor model By Adam, Tomáš; Lo Duca, Marco
  5. Time series momentum and contrarian effects in the Chinese stock market By Huai-Long Shi; Wei-Xing Zhou
  6. A Principal Component Approach to Measuring Investor Sentiment in Hong Kong By Chong, Terence Tai-Leung; Cao, Bingqing; Wong, Wing Keung

  1. By: Praveen Kujal (Middlesex University and Economic Science Institute, Chapman University); Owen Powell (Universität Wien)
    Abstract: One can define a bubble as a persistent increase in the price of an asset over and above its fundamental value with an abrupt fall in prices when no buyers are available to make purchases. The occurrence of market bubbles has a long history, starting with the Dutch Tulip Mania (1624-1637) to the South Sea and Mississippi Bubble (1716-1720), the British Railway Mania (1840´s) to the crash of 1929. Recent events have been the crash of 1987, the dot-com bubble (1990s) to the most recent housing crisis in early 2000. Even though bubbles, and a subsequent crash, may reallocate resources to more efficient activities, the economic costs of bubbles are large and sometimes felt for long periods of time. It is important to emphasize that markets perform an important role in that they aggregate information (Hayek, 1945) for its participants. The aggregation of information occurs through the price discovery process. In the real world markets are seldom efficient and mispricing is common. Due to this, information aggregation seldom happens and consequently one observes deviations of prices from their fundamentals on a regular basis. Market bubbles are an elusive phenomenon and it is due to this that the prior knowledge of the occurrence of a bubble is difficult. In most cases we only know of their occurrence when we observe a crash, but by then it’s too late. Simply stated, bubbles reflect mis-pricing of an asset from its fundamental value. Clearly, knowing the fundamental value in the real world is a challenge. The use of economic experiments is important to study the nature of bubbles for this very reason. Bubbles are hard to detect. The institutional environment is easily controlled in a laboratory setting and one can study the reasons behind the deviation of prices from their fundamental value by carefully varying the experimental parameters. Information that is not easily available in real world settings, such as the fundamental value, is observed and can be controlled in a laboratory setting (declining, constant, ambiguous etc.). Typically, experimental studies on asset market bubbles utilize the continuous Double Auction institution where a participant can be on either side of the market acting as a buyer or seller. This may depend upon the underlying market conditions or their choice of the role based upon their expectations. The good in a typical asset market is durable and lasts till the end of the experiment. For our purpose we will limit ourselves to studies that use perfectly durable goods in asset markets. A good purchased in any period earns a dividend at the end of that period and can be resold at any point of time till the last period and is not perishable. The knowledge of the last period is common to all subjects.
    Date: 2017
  2. By: José P. Dapena; Julian R. Siri
    Abstract: When analyzing options returns, most papers tend to focus on the expected and realized return from strategies where the investors are long on those financial instruments. We conduct a test searching for excess returns on passive options investment strategies resorting to a four factor model, evaluating the case of an investor who launches options and evaluates returns to the light of capital invested in the form of margins requirement. The main point of our research work is to continue the line of research where we evaluate options returns using the metrics with respect to margin requirements. We find that there are excess returns not explained by the four factor model, which in turn may indicate the strategy generates extra returns, or that the investor going short on options provides insurance to events not captured by the traditional models.
    Date: 2017–01
  3. By: Kick, Heinrich
    Abstract: This paper investigates the joint dynamics of nominal bond yields, real bond yields and dividend yields from the 80s up to the aftermath of the financial crisis by mapping them on a set of macro factors. It builds on an existing discrete time affine Gaussian model of the term structure model of nominal bonds, real bonds and equity and extends it by three important innovations. Firstly, allowing for structural shifts in inflation expectations. Secondly, accounting for the relevance of the zero lower bound in the period after 2008 by modelling a so-called shadow rate and deriving asset prices by explicitly considering the zero lower bound. Finally, calculating the standard errors to correctly capture the multi-step nature of the estimation process, which results in substantially larger standard errors than previously reported for the model. We achieve statistically signicant risk premia by imposing restrictions on the matrix of risk premia. Taken together, these modifications allow to better model asset prices also during the financial crisis and the ensuing economic environment of sluggish growth, low inflation rates, interest rates close to zero and quantitative easing. JEL Classification: C13, E43, G12
    Keywords: asset pricing, financial crisis, zero lower bound
    Date: 2017–01
  4. By: Adam, Tomáš; Lo Duca, Marco
    Abstract: In this paper, we study the dynamics and drivers of sovereign bond yields in euro area countries using a factor model with time-varying loading coefficients and stochastic volatility, which allows for capturing changes in the pricing mechanism of bond yields. Our key contribution is exploring both the global and the local dimensions of bond yield determinants in individual euro area countries using a time-varying model. Using the reduced form results, we show decoupling of periphery euro area bond yields from the core countries yields following the financial crisis and the scope of their subsequent re-integration. In addition, by means of the structural analysis based on identification via sign restrictions, we present time varying impulse responses of bond yields to EA and US monetary policy shocks and to confidence shocks. JEL Classification: C11, G01, E58
    Keywords: bayesian estimation, bond yield, factor model, sovereign debt crisis, stochastic volatility
    Date: 2017–02
  5. By: Huai-Long Shi (ECUST); Wei-Xing Zhou (ECUST)
    Abstract: This paper concentrates on the time series momentum or contrarian effects in the Chinese stock market. We evaluate the performance of the time series momentum strategy applied to major stock indices in mainland China and explore the relation between the performance of time series momentum strategies and some firm-specific characteristics. Our findings indicate that there is a time series momentum effect in the short run and a contrarian effect in the long run in the Chinese stock market. The performances of the time series momentum and contrarian strategies are highly dependent on the look-back and holding periods and firm-specific characteristics.
    Date: 2017–02
  6. By: Chong, Terence Tai-Leung; Cao, Bingqing; Wong, Wing Keung
    Abstract: In light of the increasing integration between China and Hong Kong, this paper develops a new market sentiment index for the Hong Kong stock market by including the CSI 300 index of the Chinese equity market. A threshold regression model using the sentiment index as a threshold variable is estimated to capture the state of the Hong Kong stock market.
    Keywords: Principal component analysis; Market sentiment; CSI 300; Threshold model
    JEL: C22 G17
    Date: 2017–02–26

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