Сегодня в 17:30 обсуждаем построение моделей оценки на рынках недвижимости. Поговорим о существующих моделях, доступности данных. Гости встречи эксперты из Грузии, Арабских Эмиратов и Таиланда которые жили и работали с рынками в этих странах. Все наши гости это люди из банковского сектора.
17:30 former Head of Market risk control, Sber, Александр Захаркин расскажет о рынке ОАЭ
18:00 Алексей Калачев, частный инвестор в Грузии расскажет о своем портфеле и способах оценки доходности недвижимости
18:30 Антон Абрамов поделится опытом работы на тайском рынке
19:00 Лидия Булушова, приглашенный преподаватель ВШЭ, дополнит встречу информацией о доступных данных, интересных статьях и моделях.
Спасибо Банковскому Институту НИУ ВШЭ за zoom 🥰
https://us06web.zoom.us/j/82732528426?pwd=T0wuLS2QCvyyZjo7CQ3A9yeI8QZxdx.1
Идентификатор конференции: 827 3252 8426
Код доступа: 120743
17:30 former Head of Market risk control, Sber, Александр Захаркин расскажет о рынке ОАЭ
18:00 Алексей Калачев, частный инвестор в Грузии расскажет о своем портфеле и способах оценки доходности недвижимости
18:30 Антон Абрамов поделится опытом работы на тайском рынке
19:00 Лидия Булушова, приглашенный преподаватель ВШЭ, дополнит встречу информацией о доступных данных, интересных статьях и моделях.
Спасибо Банковскому Институту НИУ ВШЭ за zoom 🥰
https://us06web.zoom.us/j/82732528426?pwd=T0wuLS2QCvyyZjo7CQ3A9yeI8QZxdx.1
Идентификатор конференции: 827 3252 8426
Код доступа: 120743
Zoom Video
Join our Cloud HD Video Meeting
Zoom is the leader in modern enterprise video communications, with an easy, reliable cloud platform for video and audio conferencing, chat, and webinars across mobile, desktop, and room systems. Zoom Rooms is the original software-based conference room solution…
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Forwarded from Options and other stuff Chat
Papers:
Appraisal of the Fischer-DiPasquale-Wheaton (FDW) Real Estate Model: This paper provides a concise overview of the development of an integrated property and asset market model (IPAMM) for South African property markets, utilizing the Pretoria office market as a case study. The FDW model serves as the foundation for this analysis. Link
Direct and Indirect Effects of Housing Market Policies Using an Augmented DPW Model: This paper analyzes housing market policies within an augmented DPW framework, emphasizing the price-rent ratio to ensure market equilibrium across different tenure types. It provides a detailed discussion on housing market dynamics, considering both direct and indirect effects. Link
Real Estate Price Prediction Using Regression Techniques: This research focuses on predicting house prices based on property characteristics and location, employing regression techniques. It offers insights into modeling approaches relevant to real estate price forecasting Link
The foundational paper by Denise DiPasquale and William C. Wheaton, titled "The Markets for Real Estate Assets and Space: A Conceptual Framework," was published in the Journal of the American Real Estate and Urban Economics Association in 1992. This seminal work presents a comprehensive framework for understanding the interactions between real estate asset markets and space markets.
Appraisal of the Fischer-DiPasquale-Wheaton (FDW) Real Estate Model: This paper provides a concise overview of the development of an integrated property and asset market model (IPAMM) for South African property markets, utilizing the Pretoria office market as a case study. The FDW model serves as the foundation for this analysis. Link
Direct and Indirect Effects of Housing Market Policies Using an Augmented DPW Model: This paper analyzes housing market policies within an augmented DPW framework, emphasizing the price-rent ratio to ensure market equilibrium across different tenure types. It provides a detailed discussion on housing market dynamics, considering both direct and indirect effects. Link
Real Estate Price Prediction Using Regression Techniques: This research focuses on predicting house prices based on property characteristics and location, employing regression techniques. It offers insights into modeling approaches relevant to real estate price forecasting Link
The foundational paper by Denise DiPasquale and William C. Wheaton, titled "The Markets for Real Estate Assets and Space: A Conceptual Framework," was published in the Journal of the American Real Estate and Urban Economics Association in 1992. This seminal work presents a comprehensive framework for understanding the interactions between real estate asset markets and space markets.
#real_estate
Links:
https://www.oecd.org/content/oecd/en/data/datasets/oecd-affordable-housing-database.html
https://data.bis.org/topics/RPP?utm_source=chatgpt.com
https://huggingface.co/datasets/daniilak/Russia_Real_Estate_2018_2021
Links:
https://www.oecd.org/content/oecd/en/data/datasets/oecd-affordable-housing-database.html
https://data.bis.org/topics/RPP?utm_source=chatgpt.com
https://huggingface.co/datasets/daniilak/Russia_Real_Estate_2018_2021
OECD
OECD Affordable Housing Database
The OECD Affordable Housing Database (AHD) helps countries monitor access to good-quality affordable housing and strengthen the knowledge base for policy evaluation. It brings together cross-national information from OECD countries, Key Partners and EU member…
#JonCHull@hunt4quant
Dear all, this Friday and next Friday I’m giving lectures at the HSE MBA program and the only option I have for our Fridays meetings is 17:00.
What about today? Fine or not? If not the only thing I can do is skip this Friday. Let me know in personal message or in comments here.
Dear all, this Friday and next Friday I’m giving lectures at the HSE MBA program and the only option I have for our Fridays meetings is 17:00.
What about today? Fine or not? If not the only thing I can do is skip this Friday. Let me know in personal message or in comments here.
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Dear all!
Today we will be discussing project structures (ones you have prepared and those I have from previous years) and proceed to literature review and data collection.
#master_thesis_and_poroject@hunt4quant
See you at livestream here at 17:30 Moscow time. Language is Russian or English depending on who is attending the meeting.
Today we will be discussing project structures (ones you have prepared and those I have from previous years) and proceed to literature review and data collection.
#master_thesis_and_poroject@hunt4quant
See you at livestream here at 17:30 Moscow time. Language is Russian or English depending on who is attending the meeting.
Master thesis part 2
Options and other stuff
#master_thesis_and_poroject@hunt4quant
Part 2: general words, data exploratory analysis, metrics
English
Part 2: general words, data exploratory analysis, metrics
English
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#real_estate@hunt4quant
Dear all! You keep reaching me with RE questions so let’s break down each feasible hypothesis with a dataset example, explanation, and a relevant paper.
---
### 1. Interest Rate Sensitivity Hypothesis
Hypothesis: Changes in interest rates significantly affect real estate prices, with higher rates leading to lower prices due to increased borrowing costs.
Dataset Example:
- Federal Reserve Economic Data (FRED): Interest rates, mortgage rates, housing price indices.
- OECD Database: Long-term interest rates and house price indices.
Explanation:
Interest rates influence mortgage affordability. Higher rates make loans more expensive, reducing demand and lowering property prices.
Relevant Paper:
- "The impact of interest rates on housing prices: Evidence from the US"
- Published in *Journal of Housing Economics*.
- Analyzes the sensitivity of housing prices to changing mortgage rates.
---
### 2. Economic Growth Impact Hypothesis
Hypothesis: Economic downturns or recessions cause a decline in real estate prices, while periods of economic growth drive prices up.
Dataset Example:
- World Bank Open Data: GDP per capita, unemployment rates.
- OECD Statistics: Quarterly GDP growth rates and housing price indices.
Explanation:
A growing economy increases purchasing power and demand, driving up prices. In a recession, the opposite occurs.
Relevant Paper:
- "Housing Prices and Economic Growth: An Empirical Study"
- Published in *Real Estate Economics*.
- Examines the correlation between GDP growth and housing price trends.
---
### 3. Income Elasticity Hypothesis
Hypothesis: Real estate prices are positively correlated with household income, with higher incomes leading to increased demand and higher prices.
Dataset Example:
- Bureau of Economic Analysis (BEA): Personal income data.
- National Bureau of Statistics (Russia): Average monthly wages, housing prices.
Explanation:
As household income rises, families can afford more expensive properties, driving up prices, especially in desirable areas.
Relevant Paper:
- "Income Growth and Housing Demand: Evidence from European Cities"
- Published in *Urban Studies*.
- Shows a positive correlation between wage growth and urban housing prices.
---
### 4. Inflation Pass-Through Hypothesis
Hypothesis: Rising inflation rates directly increase property prices as real estate acts as a hedge against inflation.
Dataset Example:
- OECD Inflation Data: Consumer Price Index (CPI).
- Federal Reserve Economic Data (FRED): Housing price index and CPI.
Explanation:
Real estate is seen as a stable asset during inflation, attracting investments and driving prices up.
Relevant Paper:
- "Inflation Hedging with Real Estate: A Global Perspective"
- Published in *Journal of Real Estate Finance and Economics*.
- Analyzes real estate as a hedge against inflation using global data.
---
### 5. Financial Market Spillover Hypothesis
Hypothesis: Shocks in financial markets, such as stock market crashes, significantly influence real estate prices through reduced liquidity and investor confidence.
Dataset Example:
- Yahoo Finance or Bloomberg: Major stock indices (e.g., S&P 500, RTS).
- FRED: Real estate investment data.
Explanation:
During a financial crisis, investors liquidate assets, including real estate, causing price declines. Conversely, booming markets may attract speculative investment.
Relevant Paper:
- "Financial Market Turmoil and Real Estate Prices: Evidence from the Global Financial Crisis"
- Published in *Journal of Financial Stability*.
- Examines the linkage between stock market crashes and real estate depreciation.
---
### 6. Regional Variation Hypothesis
Hypothesis: The impact of macroeconomic shocks on real estate prices varies significantly across regions, depending on local economic conditions and market maturity.
Dataset Example:
- Russian Federal State Statistics Service (Rosstat): Regional real estate prices.
Dear all! You keep reaching me with RE questions so let’s break down each feasible hypothesis with a dataset example, explanation, and a relevant paper.
---
### 1. Interest Rate Sensitivity Hypothesis
Hypothesis: Changes in interest rates significantly affect real estate prices, with higher rates leading to lower prices due to increased borrowing costs.
Dataset Example:
- Federal Reserve Economic Data (FRED): Interest rates, mortgage rates, housing price indices.
- OECD Database: Long-term interest rates and house price indices.
Explanation:
Interest rates influence mortgage affordability. Higher rates make loans more expensive, reducing demand and lowering property prices.
Relevant Paper:
- "The impact of interest rates on housing prices: Evidence from the US"
- Published in *Journal of Housing Economics*.
- Analyzes the sensitivity of housing prices to changing mortgage rates.
---
### 2. Economic Growth Impact Hypothesis
Hypothesis: Economic downturns or recessions cause a decline in real estate prices, while periods of economic growth drive prices up.
Dataset Example:
- World Bank Open Data: GDP per capita, unemployment rates.
- OECD Statistics: Quarterly GDP growth rates and housing price indices.
Explanation:
A growing economy increases purchasing power and demand, driving up prices. In a recession, the opposite occurs.
Relevant Paper:
- "Housing Prices and Economic Growth: An Empirical Study"
- Published in *Real Estate Economics*.
- Examines the correlation between GDP growth and housing price trends.
---
### 3. Income Elasticity Hypothesis
Hypothesis: Real estate prices are positively correlated with household income, with higher incomes leading to increased demand and higher prices.
Dataset Example:
- Bureau of Economic Analysis (BEA): Personal income data.
- National Bureau of Statistics (Russia): Average monthly wages, housing prices.
Explanation:
As household income rises, families can afford more expensive properties, driving up prices, especially in desirable areas.
Relevant Paper:
- "Income Growth and Housing Demand: Evidence from European Cities"
- Published in *Urban Studies*.
- Shows a positive correlation between wage growth and urban housing prices.
---
### 4. Inflation Pass-Through Hypothesis
Hypothesis: Rising inflation rates directly increase property prices as real estate acts as a hedge against inflation.
Dataset Example:
- OECD Inflation Data: Consumer Price Index (CPI).
- Federal Reserve Economic Data (FRED): Housing price index and CPI.
Explanation:
Real estate is seen as a stable asset during inflation, attracting investments and driving prices up.
Relevant Paper:
- "Inflation Hedging with Real Estate: A Global Perspective"
- Published in *Journal of Real Estate Finance and Economics*.
- Analyzes real estate as a hedge against inflation using global data.
---
### 5. Financial Market Spillover Hypothesis
Hypothesis: Shocks in financial markets, such as stock market crashes, significantly influence real estate prices through reduced liquidity and investor confidence.
Dataset Example:
- Yahoo Finance or Bloomberg: Major stock indices (e.g., S&P 500, RTS).
- FRED: Real estate investment data.
Explanation:
During a financial crisis, investors liquidate assets, including real estate, causing price declines. Conversely, booming markets may attract speculative investment.
Relevant Paper:
- "Financial Market Turmoil and Real Estate Prices: Evidence from the Global Financial Crisis"
- Published in *Journal of Financial Stability*.
- Examines the linkage between stock market crashes and real estate depreciation.
---
### 6. Regional Variation Hypothesis
Hypothesis: The impact of macroeconomic shocks on real estate prices varies significantly across regions, depending on local economic conditions and market maturity.
Dataset Example:
- Russian Federal State Statistics Service (Rosstat): Regional real estate prices.
Options and other stuff
Сегодня в 17:30 обсуждаем построение моделей оценки на рынках недвижимости. Поговорим о существующих моделях, доступности данных. Гости встречи эксперты из Грузии, Арабских Эмиратов и Таиланда которые жили и работали с рынками в этих странах. Все наши гости…
#real_estate@hunt4quant
https://disk.yandex.ru/i/ArqTpL7Erjd_nw
The webinar with Real Estate experts is now available for downloading. Enjoy ☺️
And many thanks the HSE 🥰
https://disk.yandex.ru/i/ArqTpL7Erjd_nw
The webinar with Real Estate experts is now available for downloading. Enjoy ☺️
And many thanks the HSE 🥰
Яндекс Диск
Вебинар 13.03.mp4
Посмотреть и скачать с Яндекс Диска
❤6
Options and other stuff
Мы в том же зуме https://us02web.zoom.us/j/933271498?pwd=MXBESlNEb2dCYmFtTFFZVjh5MVBJZz09
The zoom is here (same as usual). I’m starting 😉
#kelly_criterion@hunt4quant
Dear all!
Some links for those of you who are doing “Kelly Criterion Research”
• Chawla, Karan. "The Kelly Criterion." Github. https://github.com/1kc2/The-Kelly-Criterion.
• Chawla, Karan. "The Kelly Criterion." Mental Quill. 18 Oct 2020. https://blog.karanchawla.me/2020/10/18/the-kelly-criterion/
1 Peterson, Zachariah. "The Kelly Criterion in Portfolio Optimization: A Decoupled Problem." Journal of Investment Strategies, vol. 7, no. 2, 2018, pp. 1–15, https://arxiv.org/abs/1710.00431
◦ Required pages: All
◦ Estimated reading time: 30 minutes
2 Carta, Andrea, and Claudio Conversano. "Practical Implementation of the Kelly Criterion: Optimal Growth Rate, Number of Trades, and Rebalancing Frequency for Equity Portfolios." Frontiers in Applied Mathematics and Statistics, vol. 6, no. 557050, 2020, pp. 1–15, https://www.frontiersin.org/articles/10.3389/fams.2020.577050/full
• Carta, Andrea, and Claudio Conversano. "Practical Implementation of the Kelly Criterion: Optimal Growth Rate, Number of Trades, and Rebalancing Frequency for Equity Portfolios." Frontiers in Applied Mathematics and Statistics, vol. 6, no. 557050, 2020, pp. 1–15, https://www.frontiersin.org/articles/10.3389/fams.2020.577050/full
• Peterson, Zachariah. "The Kelly Criterion in Portfolio Optimization: A Decoupled Problem." Journal of Investment Strategies, vol. 7, no. 2, 2018, pp. 1–15, https://arxiv.org/abs/1710.00431
Dear all!
Some links for those of you who are doing “Kelly Criterion Research”
• Chawla, Karan. "The Kelly Criterion." Github. https://github.com/1kc2/The-Kelly-Criterion.
• Chawla, Karan. "The Kelly Criterion." Mental Quill. 18 Oct 2020. https://blog.karanchawla.me/2020/10/18/the-kelly-criterion/
1 Peterson, Zachariah. "The Kelly Criterion in Portfolio Optimization: A Decoupled Problem." Journal of Investment Strategies, vol. 7, no. 2, 2018, pp. 1–15, https://arxiv.org/abs/1710.00431
◦ Required pages: All
◦ Estimated reading time: 30 minutes
2 Carta, Andrea, and Claudio Conversano. "Practical Implementation of the Kelly Criterion: Optimal Growth Rate, Number of Trades, and Rebalancing Frequency for Equity Portfolios." Frontiers in Applied Mathematics and Statistics, vol. 6, no. 557050, 2020, pp. 1–15, https://www.frontiersin.org/articles/10.3389/fams.2020.577050/full
• Carta, Andrea, and Claudio Conversano. "Practical Implementation of the Kelly Criterion: Optimal Growth Rate, Number of Trades, and Rebalancing Frequency for Equity Portfolios." Frontiers in Applied Mathematics and Statistics, vol. 6, no. 557050, 2020, pp. 1–15, https://www.frontiersin.org/articles/10.3389/fams.2020.577050/full
• Peterson, Zachariah. "The Kelly Criterion in Portfolio Optimization: A Decoupled Problem." Journal of Investment Strategies, vol. 7, no. 2, 2018, pp. 1–15, https://arxiv.org/abs/1710.00431
GitHub
GitHub - 1kc2/The-Kelly-Criterion: 🧮 A deeper look into the Kelly Criterion
🧮 A deeper look into the Kelly Criterion. Contribute to 1kc2/The-Kelly-Criterion development by creating an account on GitHub.
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