Investasi Saham: Investasi, Spekulasi, Atau Judi

Stocks are proof of company ownership, which is attractive for investment. Often people become doubtful about investing in stocks, which are considered gambling. This study tries to find answers from the perspective of financial science about investment criteria, speculation and gambling. The method used in this study goes through stages starting with understanding stocks and the mechanism of stock trading to the decision of investors in buying or selling shares. The results obtained show that from a theoretical perspective, investment is different from speculation and gambling. Investing in stocks is not gambling, but it can be speculation or investment, depending on the attitudes and expectations of the investors themselves. When investors are risk takers and only expect capital gains without considering financial performance, this is speculation known as liquidity traders. When investors expect dividends by considering the condition of the company and other aspects, this is an investment known as an information trader. The implication of this study is that an investor must be rational in the sense of calculating risk that is proportional to the expected results.

An Analysis of the Asymmetric Volatility under Asymmetric Information and Ambiguity

The asymmetric volatility phenomenon (‘the phenomenon’, henceforth), documented first by Black (1976), refers to the fact that the stock return and its conditional volatility are negatively correlated. To explain ‘the phenomenon’, this paper presents an asymmetric information model under ambiguity, and provides an empirical test of its result as well. We assume that in the Grossman and Stiglitz (1980), uninformed liquidity traders face ambiguity about the distribution of asset payoffs, and that their attitudes toward ambiguity vary depending on the state of the economy. In model I, their utility functions exhibit ambiguity aversion in the bad state and ambiguity neutrality in the good state. In model II, liquidity traders are still ambiguity-averse in the bad state but ambiguity-seeking in the good state. We find that ‘the phenomenon’ appears in model II when the degree of ambiguity is not large. Furthermore, we show that the possibility of ‘the phenomenon’ is higher as the proportion of liquidity traders increases. To perform an empirical analysis, we measure the degree of ambiguity by the Kolmogorov-Smirnov statistic and show that this measure has a positive relationship with the difference between the volatilities in the good and bad states. In addition, we find that the risk factor constructed by the ambiguity measure has explanatory power about returns on 25 portfolios of the Fama-French type in the Korean market.

Detecting Liquidity Traders

We develop a measure (based on the relative slopes of the demand and supply schedules) quantifying the asymmetric presence of liquidity traders in the market: a steeper slope of the demand (supply) schedule indicates a concentration of liquidity traders on the demand (supply) side. Using the opening session of the Tel Aviv Stock Exchange, we demonstrate the predictive power of our measure. Consistent with theory, we find that the concentration of liquidity traders on the demand (supply) side is negatively (positively) correlated with future returns. We find that liquidity traders are likely to arrive at the market together (commonality).

MARKET POWER AND FEEDBACK EFFECTS FROM HEDGING DERIVATIVES

In this paper we model how the transaction of derivatives affects the price process of the underlying asset, considering the existence of a few agents with market power and a population of liquidity traders. This setting generates an equilibrium bid-ask spread for the underlying asset. The resulting feedback effect of hedging strategies is shown to depend on what type of agent more actively hedges. We also characterize how the feedback effect is lessened as the number of market-makers increases.