Interrogation of A Bubble in the Indian Market
Emerging markets such as India provide investors with returns far greater than those in developed markets; taking the average returns from the period 1995 to 2014 the returns are 4.714% to 3.276% of the developed market. The majority of emerging markets commenced joining with the capital market of the world, thus allowing a huge inflow of capital which in turn paved the path for economic growth. Even though the emerging markets provide high returns these may also be an indication of a bubble formation. Detection of a bubble is a tedious task primarily due to the fundamental value of the security being uncertain, and the randomness of the fundamentals of the market makes detecting bubbles an arduous task. Ratios that foretold the financial crisis of 2007- Market Capitalization to GDP, Price to Earnings Ratio, Price to Book Value, Tobins Q. Data is collected from 1999-2000 from various Indian indices such as NIFTY 50, NIFTY NEXT 50, NIFTY BANK, NIFTY 500 S and PBSE SENSEX, S and P BSE 100. The paper utilizes the ratios mentioned above to detect and backtrack various bubble episodes in the Indian market; the methodology used is the Philips et al 2015 right-tailed unit test. The paper is also inclined to take steps to mitigate the effects of a bubble by amending the financial policies and the monetary liquidity of the financial system.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
The asset price bubbles in emerging financial markets: a new statistical approach
The bubble is a controversial and important issue. Many methods which based on the rational expectation have been proposed to detect the bubble. However, for some developing countries, epically China, the asset markets a…
Detection of Chinese Stock Market Bubbles with LPPLS Confidence Indicator
We present an advance bubble detection methodology based on the Log Periodic Power Law Singularity (LPPLS) confidence indicator for the early causal identification of positive and negative bubbles in the Chinese stock ma…
Causal IdentificationDynamical Characteristics of Global Stock Markets Based on Time Dependent Tsallis Non-Extensive Statistics and Generalized Hurst Exponents
We perform non-linear analysis on stock market indices using time-dependent extended Tsallis statistics. Specifically, we evaluate the q-triplet for particular time periods with the purpose of demonstrating the temporal …
TripletExamining the Relationship between Scientific Publishing Activity and Hype-Driven Financial Bubbles: A Comparison of the Dot-Com and AI Eras
Financial bubbles often arrive without much warning, but create long-lasting economic effects. For example, during the dot-com bubble, innovative technologies created market disruptions through excitement for a promised …
Asset Price Bubbles in market models with proportional transaction costs
We study asset price bubbles in market models with proportional transaction costs $\lambda\in (0,1)$ and finite time horizon $T$ in the setting of [49]. By following [28], we define the fundamental value $F$ of a risky a…
Position