The aim of this study is to investigate the asymmetric responses in volatility between positive and negative shocks in Turkish stock market. The daily closing values of Istanbul Stock Exchange 100 Index (ISE-100), cover the period from January 02, 1990 to December 29, 2004, are analyzed by using...

Macroeconomic data is often noisy, contradictory and lagging. These limitations render the data difficult to integrate into a robust quantitative investment strategy that generates excess returns. This paper outlines a new approach to macro investing that removes these inherent limitations in...

This research examines how individual investors use the internet and traditional media to identify information and formulate their investment decisions. Before this study we developed several research papers concerning financial information disclosure on the internet. We also met managers of...

Using proprietary balance sheet data for Korean banks and a simultaneous equation model, we document that increased marginal funding costs lead to larger solvency risk (as measured by the Tier 1 regulatory capital ratio), which, in turn, leads to larger marginal funding costs. A 100 bp increase...

This work presents an asset pricing model that under rational expectation equilibrium perspective shows how, depending on risk aversion and noise volatility, a risky-asset has one equilibrium price that differs in term of efficiency: an informational efficient one (similar to Campbell and Kyle...

This paper proposes a new modelling framework for electricity forward markets based on so-called ambit fields. The new model can capture many of the stylised facts observed in energy markets and is highly analytically tractable. We give a detailed account on the probabilistic properties of the...

The informational content of prices hypothesis in Modigliani and Miller (and Fisher before them) advocates that organizations’ market prices could somehow estimate their growth prospects and intangible assets. For this estimation, discounted cash flow models are frequently employed. However,...

Bitcoin Pricing Kernels (PK) are estimated using a novel data set from Deribit, one of the largest Bitcoin derivatives exchanges. The PKs improve the understanding of investor sentiment and risk premia. Bootstrap-based confidence bands are estimated in order to validate the results. Investors...