scholarly journals The Influence of Leverage, Cash Flow, Tax, R & D, Economic Growth and Inflation on the Financial Distress in the Sub-Sector of Property and Real Estate Companies

2020 ◽  
Author(s):  
Khirstina Curry
Keyword(s):  
Economic Growth ◽  
Real Estate ◽  
Cash Flow ◽  
Financial Distress

scholarly journals Faktor yang Mempengaruhi Kondisi Financial Distress Perusahaan Property dan Real Estate

Owner ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 82
Author(s):  
Siti Aisyah Nasution
Keyword(s):  
Real Estate ◽  
Cash Flow ◽  
Significant Influence ◽  
Financial Distress ◽  
Stock Exchange ◽  
Current Ratio ◽  
Financial Ratio ◽  
Leverage Ratio ◽  
Matching Test ◽  
Model Coefficient

The purpose of this study was to find out the influence of Financial Ratio on financial distress in Property and Real Estate companies listed in the Indonesian Stock Exchange. The factors which tested in this research were Current Ratio. Leverage Ratio, and Cash Flow. The study used causal method which was aimed to analyze the influence of independent variables on dependent variable. The population was 22 property and real estate companies listed in the Indonesian Stock Exchange in the period of 2011-2014 until there were 88 saturated samples. The data were analyzed by using logistic regression analysis. The result of the study showed that the data in this study were in accordance with the model and the result of the matching test of regression model which was able to analyze the problems. Simultaneously, the result of Ominbus Test of Model Coefficient showed that Current Ratio, Leverage Ratio and Cash Flow had significant influence on financial distress. Partially, Current Ratio, and Cash Flow had positive and significant influence on Financial Distress, Leverage Ration had negative but significant influence on Financial Distress.  

scholarly journals A Financial Distress Prediciton on Property, Construction, and Real Estate Companies Listed in BEI

2020 ◽  
Vol 7 (1) ◽  
pp. 1-9
Author(s):  
Alberto Orson Ongkowidjojo ◽  
Anastasia Njo ◽  
Januar Budiman
Keyword(s):  
Economic Growth ◽  
Discriminant Analysis ◽  
Data Collection ◽  
Real Estate ◽  
Financial Distress ◽  
Collection Method ◽  
Financial Ratio ◽  
Financial Status ◽  
Enormous Amount ◽  
A Company

The slowing of economic growth in Indonesia could cause financial distress for companies in property, construction and real estate sectors as these companies has enormous amount of GDP contributions in Indonesia. These difficulties are related to companies being able to accomplish all its responsibilities in short nor long terms. In assessing financial status of a company, discriminant analysis could be of use to see financial ratio such as liquidity ratio, profitability, activity and solvability. This research consists of comparative and sample pulling technique towards 81 population in multiple sectors such as property, construction and real estate. Data collection method by documentation.  Discriminant analysis results depicts that liquidity ratio(CA/CL), profitability (EBIT/TA and NI/SALES), activity (SALES/TA), and solvability (BV/TL and TL/EQUITY) could be used to distinguish which company are experiencing financial distress and which are not.

scholarly journals Determinants of Financial Distress in Property and Real Estate Companies

2019 ◽  
Vol 9 (1) ◽  
pp. 109
Author(s):  
Inggriyani Wilda Utami ◽  
Titis Puspitanigrum Dewi Kartika
Keyword(s):  
Real Estate ◽  
Cash Flow ◽  
Financial Distress ◽  
Stock Exchange ◽  
Sample Selection ◽  
Sampling Technique ◽  
Financial Statements ◽  
Working Capital ◽  
Significance Level ◽  
Operating Capacity

This study aims to examine the effect of financial ratios, consisting of operating capacity, quick ratio, working capital, and cash flow to sales, on financial distress. Financial distress is an interesting topic to discuss because research on this factor can predict the company’s survival. In general, financial distress can be measured by analyzing financial statements. Financial statements are very useful for the companies to find out their financial position as the results of their operations in a given period. This study used the population concerning property and real estate companies listed on the Indonesia Stock Exchange in the period 2015-2017. This study used a purposive sampling technique for getting the sample. The population consists of 99 companies that meet the criteria as stipulated for the sample selection. The analytical method used is logistic regression with a significance level of 0.05. The test results in this study indicate that operating capacity has an effect on financial distress, while quick ratio, working capital and cash flow to sales have no effect on financial distress.

ANALISIS INDEX ALTMAN Z-SCORE DALAM MEMPREDIKSI KONDISI FINANCIAL DISTRESS (Studi Empiris Perusahaan Properti dan Real Estate Sub Sektor Perhotelan Tahun 2012-2017)

Kinerja ◽  
2018 ◽  
Vol 1 (01) ◽  
pp. 48-57
Author(s):  
Maryam Dunggio ◽  
Nur Aufa Mufidah
Keyword(s):  
Real Estate ◽  
Financial Distress ◽  
Z Score ◽  
Grey Area

Penelitian ini bertujuan untuk menganalisis Index Altman dalam memprediksi kondisi financialdistress pada perusahaan properti dan real estate tahun 2102-2017. Metode penelitian yangdigunakan adalah Altman Z-score. Teknik pengumpulan data yang dilakukan secara sekunderyaitu data yang diperoleh dari laporan keuangan tahunan yang dipublikasikan oleh setiapperusahaan. Hasil yang diperoleh dalam penelitian ini menunjukkan bahwa pada tahun 2012terdapat 2 perusahaan yang mengalami zona aman dan 8 perusahaan mengalami financial distress,tahun 2013 terdapat 2 perusahaan mengalami zona aman dan 1 perusahaan grey area dan 7perusahaan financial distress, tahun 2014 terdapat 2 perusahaan zona aman dan 8 perusahaanfinancial distress, tahun 2015 terdapat 2 perusahaan mengalami zona aman dan 8 perusahaanfinancial distress, tahun 2016 terdapat 2 perusahaan zona aman, 1 grey area dan 7 financialdistress, tahun 2017 terdapat 2 zona grey area dan 8 mengalami financial distress

Analisis Terhadap Financial Distress pada Perusahaan Sub Sektor Properti dan Real Estate di BEI 2011-2015

2017 ◽  
Vol 9 (2) ◽  
pp. 21-25
Author(s):  
Adeh Ratna Komala ◽  
Nadia Laksmita
Keyword(s):  
Real Estate ◽  
Financial Distress ◽  
Sampling Unit ◽  
Purposive Sampling

Penelitian ini dilakukan pada perusahaan sub sektor properti dan real estate terdaftar di Bursa Efek Indonesia pada periode 2011-2015. Fenomena yang terjadi yaitu pada beberapa perusahaan sub sektor properti dan real estate yang mengalami kesulitan keuangan ketika perusahaan memiliki arus kas dan likuiditas yang sehat. Penelitian ini juga bertujuan untuk mengetahui apakah arus kas dan likuiditas berpengaruh signifikan terhadap financial distress. Metode yang digunakan dalam penelitian ini adalah metode deskriptif verifikatif dengan pendekatan kuantitatif. Metode pengambilan sampel dalam penelitian ini menggunakan nonprobability sampling dengan pendekatan purposive sampling. Unit analisis dalam penelitian ini adalah 105 laporan keuangan tahunan perusahaan yang diambil pada tahun 2011-2015. Sedangkan analisis data menggunakan regresi linier berganda. Pengujian hipotesis dalam penelitian ini menggunakan statistik uji t dengan SPSS Versi 16.0 for Windows. Hasil dari penelitian ini menunjukan bahwa arus kas berpengaruh terhadap financial distress, demikian juga dengan likuiditas yang berpengaruh terhadap financial distress pada pada perusahaan sub sektor properti dan real estate yang terdaftar di Bursa Efek Indonesia.

scholarly journals What is beyond the edges? Gated communities and their role in China’s desire for harmonious cities

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Badiaa Hamama ◽  
Jian Liu
Keyword(s):  
Economic Growth ◽  
Real Estate ◽  
Urban Form ◽  
Gated Communities ◽  
Urban Fabric ◽  
Chinese Cities ◽  
The Matrix ◽  
Process Of Urbanization ◽  
New Urbanization

Abstract During the rapid process of urbanization in post-reform China, cities assumed the role of a catalyst for economic growth and quantitative construction. In this context, territorially bounded and well delimited urban cells, globally known as ‘gated communities’, xiaoqu, continued to define the very essence of Chinese cities becoming the most attractive urban form for city planners, real estate developers, and citizens alike. Considering the guidelines in China’s National New Urbanization Plan (2014–2020), focusing on the promotion of humanistic and harmonious cities, in addition to the directive of 2016 by China’s Central Urban Work Conference to open up the gates and ban the construction of new enclosed residential compounds, this paper raises the following questions: As the matrix of the Chinese urban fabric, what would be the role of the gated communities in China’s desire for a human-qualitative urbanism? And How to rethink the gated communities to meet the new urban challenges? Seeking alternative perspectives, this paper looks at the gated communities beyond the apparent limits they seem to represent, considering them not simply as the ‘cancer’ of Chinese cities, rather the container of the primary ingredients to reshape the urban fabric dominated by the gate.

International Real Estate Review

2016 ◽  
Vol 19 (3) ◽  
pp. 265-296
Author(s):  
Richard D. Evans ◽  
◽  
Glenn R. Mueller ◽  
Keyword(s):  
Markov Chain ◽  
Real Estate ◽  
Cash Flow ◽  
Discounted Cash Flow ◽  
First Order ◽  
Order Markov Chain ◽  
Office Markets ◽  
Speed Up ◽  
Staying Time ◽  
Over Time

Metro market real estate cycles for office, industrial, retail, apartment, and hotel properties may be specified as first order Markov chains, which allow analysts to use a well-developed application, ¡§staying time¡¨. Anticipations for time spent at each cycle point are consistent with the perception of analysts that these cycle changes speed up, slow down, and pause over time. We find that these five different property types in U.S. markets appear to have different first order Markov chain specifications, with different staying time characteristics. Each of the five property types have their longest mean staying time at the troughs of recessions. Moreover, industrial and office markets have much longer mean staying times in very poor trough conditions. Most of the shortest mean staying times are in hyper supply and recession phases, with the range across property types being narrow in these cycle points. Analysts and investors should be able to use this research to better estimate future occupancy and rent estimates in their discounted cash flow (DCF) models.

Sign in / Sign up

Export Citation Format

Share Document