Tuesday, July 30, 2019

San Francisco Housing Market vs. Condo Market – Who Wins?

-- Intended for New College Graduates --


(Click on the image to enlarge)

During this period, the two market segments have moved in statistical lockstep, with high colinearity (correlation coefficient = 0.9868).

Both segments made phenomenal runs between March, 2017 and September/October, 2018, registering remarkable growth rates of 14.10% (housing) and 13.56% (condo), respectively.

Of course, since then the growth has not only tapered, but both segments have also been experiencing moderate declines. Moreover, neither segment has responded positively to the recent declines in mortgage rates. 

Considering the extremely high home prices in San Francisco (Median = $1.362M per Zillow), the cap on SALT has been severely impacting the high-end market, where the softness has increasingly been more pronounced.  

The circular congestion on the outer end of the curve (scatter plot) confirms the ongoing weakness and any immediate and meaningful breakout of this congestion seems unlikely. 

For now, it's tie. We need a few more data points to decide on the tie-breaker.

Disclaimer - The author is not advocating the Case Shiller indices listed here. Consult your Financial Planner for an appropriate asset allocation model and/or trading strategies for different markets, including housing.

Thank you.

Sid Som, MBA, MIM
President, Homequant, Inc.
homequant@gmail.com

Monday, July 29, 2019

Boston Housing Market vs. Condo Market – Who Wins?

-- Intended for New College Graduates --

(Click on the image to enlarge)

Paula, a new college graduate with a major in Economics, is interviewing for a Research Analyst position. 

Question # 1
Interviewer: Take a look at the line graph and tell me why the monthly data points have been connected.

Paula: Because these are seasonally-adjusted monthly data points. When the monthly data points are seasonally adjusted, month-over-month comparison is fine, so a line graph makes sense.

Question # 2
Interviewer: If the data points were not seasonally adjusted, how would have presented and analyzed the data?

Paula: Via mutually exclusive bars and I would have compared the April, 2019 data with April, 2018 and April, 2017 data, respectively.  

Question # 3
Interviewer: Do you think the line graph should have comprised Y1 and Y2, rather than just one Y?

Paula: It's fine the way it is. You need Y1 and Y2 when the comparative values are too far apart. That's not the case here.

Question # 4
Interviewer: Study this scatter plot and explain to me the interactions between these market segments.

Paula: They are highly correlated and, therefore, are moving in tandem. 

Interviewer: So, can you make an universal generalization that Boston single family housing market is highly correlated with Boston condo market?

Paula: No. I meant during the period the data points are drawn from. Market segments within a broad group can easily diverge.

Question # 5
Interviewer: By looking at the scatter, can you tell me if the correlation coefficient would be higher or lower than this R-squared?

Paula: It would be higher because the linear trendline generating the R-squared is not the optimal fit here.

(The actual correlation coefficient is 0.9896)

Question # 6
Interviewer: If this linear trendline is not giving us an optimal fit, what trendline would you prefer in this case?

Paula: Given the distribution of the data, a polynomial trendline (of 4th/5th order) would produce much better results. 

Question # 7
Interviewer: How would that be an improved trendline? What is it that the linear trendline is not capturing that the polynomial would?

Paula: The linear trendline is not capturing the data points on either end of the curve. The proposed polynomial will take care of that inadequacy.

Question # 8
Interviewer: Let's assume that the software you are using does not allow experimenting with any other trendlines. So, holding the linear trendline constant, can you still improve upon the current stats?

Paula: Yes, by removing the outliers from the series. In this case, if we simply remove the three outlier data points from the two ends of the curve, the R-squared would jump.

Question # 9
Interviewer: Let's assume we transpose X and Y axes, meaning we graph housing values on Y and condo values on X. Will that change the R-squared? Finally, is there a winner here?

Paula: No. Swapping axes in this instance will not make any difference in R-squared. It will remain the same. As far as the winner is concerned, given the very high co-linearity, it's a tie.

Disclaimer - The author is not advocating the Case Shiller indices listed here. Consult your Financial Planner for an appropriate asset allocation model and/or trading strategies for different markets, including housing.

Thank you.

Sid Som, MBA, MIM
President, Homequant, Inc.
homequant@gmail.com
   
Coming soon: Sid's New Book: Modern Interviewing Techniques and Skills - Live Simulations with actual Market Data

Sunday, July 28, 2019

Chicago Housing Market vs. Condo Market – Who Wins?

-- Intended for New College Graduates --

(Click on the image to enlarge)

The above graph shows that the Chicago housing and condo markets moved more or less in tandem except in the most recent two quarters when they diverged -- the housing market moved sideways while the condo market slowly but steadily trended up.

Due to the prior run-up, neither market has responded favorably to the recent declines in mortgage rates. 

The cap on SALT has impacted severely the high-end market, especially the expensive high-rise condo market in the city center and along Lake Shore Drive on Lake Michigan. 

If the housing market breaches the 144 support level, it can easily swoon to the next major support of 138. 


Similarly the condo market needs to stay above the 147 support, breaching which it can retest the 142-144 level. 

Is there a winner here? No, it's too close to call -- a tie for now!

Disclaimer - The author is not advocating the Case Shiller indices listed here. Consult your Financial Planner for an appropriate asset allocation model and/or trading strategies for different markets, including housing.

Thank you,

Sid Som, MBA, MIM
President, Homequant, Inc.
homequant@gmail.com

Los Angeles Housing Market vs. Condo Market – Who Wins?

-- Intended for New College Graduates --

(Click on the image to enlarge)

Question # 1
Interviewer: What does this graph show?

Candidate: The two market segments moved in tandem during this period. Lately, growth has been tapering off.


Question # 2
Interviewer: Despite the falling interest rates in last two quarters, LA residential market has tapered. What would you attribute this market behavior to?

Candidate: The LA residential market is heavily dependent on foreign buying which has tumbled in recent months, taking some steam off the market.

Question # 3
Interviewer: Would you recommend this market to our clients now?

Candidate: No. This market has good downside potential. Once it goes through a phase of correction, we will see buying opportunities. For now, my recommendation is "hold." 

Question # 4
Interviewer: In terms of long-term market growth, will NoCal continue to outperform SoCal?

Candidate: No. The new generation of tech companies cannot afford NoCal anymore so SoCal is fast becoming the emerging 2nd tech-hub of California. Therefore, the SoCal residential market will outperform the NoCal market.

Question # 5
Interviewer: Can you explain why there is a sudden spike in the housing market in April, 2019?

Candidate: Considering it's the most recent month, it could be a data aberration. Generally, the most recent month of data is somewhat illiquid. As the new data points come in, the current value will be moderated down, making it more in line with the most recent past.

Question # 6
Interviewer: As an Analyst, what would you do to stabilize the time series, meaning how would you reduce this noise in the data?

Candidate: For this short time series, I would apply a 2-Month Moving Average (with the resulting trendline). That would iron out the minor kinks in the data.

Question # 7
Interviewer: How would you forecast out the next 3-4 months assuming this is the only data you have?

Candidate: I would use the same 2-Month Moving Average and forecast out for the next 3-4 months. Since the market is trending sideways, Moving Average would provide a much better solution than the usual curve-fitting with the incompatible data from unrelated periods.    

Question # 8
Interviewer: If you add the 2013 through 2015 data, would your Moving Average produce better forecasts?

Candidate: Not in this particular case, as we know the market recovery back then was totally V-shaped in California and now it has been trending sideways. As I said, adding incompatible data does not improve model's accuracy or predictability.  

Question # 9
Interviewer: Let's get back to this data. Which market segment, do you think, is the winner here? 

Candidate: It's a tie. Condo slightly outperformed housing in the first half, but underperformed in the second half, hence a tie.

Disclaimer - The author is not advocating the Case Shiller indices listed here. Consult your Financial Planner for an appropriate asset allocation model and/or trading strategies for different markets, including housing.

Good Luck!

Sid Som, MBA, MIM
President, Homequant, Inc.
homequant@gmail.com 

Coming soon: Sid's New Book: Modern Interviewing Techniques and Skills - Live Simulations with actual Market Data
          

Friday, July 26, 2019

New York City Housing Market vs. Condo Market – Who Wins?

(Click on the image to enlarge)


Michael is interviewing for a Housing Analyst position with a major Economic Research firm.

Question # 1
Interviewer: Though we are using the two Case-Shiller data series, let's assume -- for the sake of this interview -- they represent only the City of New York (NYC). Given that assumption, are these two market segments comparable?

Michael: No. The NYC housing market comprises the outer boroughs, meaning Brooklyn, Bronx, Queens and Staten Island, whereas the condo market represents primarily the Manhattan market, along with some newer condos in Brooklyn. Nonetheless, due to the shared geography, the two data series would be highly correlated. 

Question # 2
Interviewer: Use your best quantitative judgment and guess the level of correlation between these two data series.

Michael: (After a short pause) It will be at least 0.85.

Interviewer: Please give a minute so I can find out how close you are to the actual coefficient. Yup, it's 0.864. You are very close. Very impressive! 

Question # 3
Interviewer: The condo data shows a sharp fall in June-July, 2018. What would you attribute that fall to?

Michael: It's just an aberration in the data and has nothing to do with any drastic change in economic fundamentals. That's the way the data comes in and gets cleansed. That is why, you see a 3-point jump in August, 2018 which is unrealistic too. In any case, any trendline would iron out that aberration in the data.  

Question # 4
Interviewer: Are the demand drivers very similar in those two market segments?

Michael: No. The NYC housing demand is driven by the local economic fundamentals, so it's a natural market. The Manhattan condo market, on the other hand, is heavily dependent on global demand, especially Asia and Europe. Therefore, any slowdown there heavily impacts the Manhattan condo market.

Question # 5
Interviewer: What would be the statistical impact if we remove those two months from the data series?

Michael: Once you remove outliers from the data, stats get better. In this case, the correlation coefficient would jump. 

Question # 6
Interviewer: In that case, can you guess the new coefficient without those outlier months?

Michael: In the vicinity of 0.90. 

Interviewer: Give me 15 seconds and let me find out. Actually, it jumps to 0.913. Very close!

Question # 7
Interviewer: Can you explain why the housing market has been holding steady while the condo market has been trending down?

Michael: The local market fundamentals are good so the housing market has been holding steady. There are two basic reasons why the Manhattan condo market has been trending down: (a) the cap on SALT, and (b) the tumbling of foreign buying.

Question # 8
Interviewer: Would you recommend one or both of these segments to our clients?

Michael: Given the low interest rate, the expected rate cuts, and good local fundamentals, I would recommend the housing market. Considering the reasons I previously talked about, I will not recommend the Manhattan condo market.

Question # 9
Interviewer: So, what is your forecast for these two market segments?

Michael: The housing market will remain sideways in Q2-Q3, declining in Q4+, until the presidential polls start to project some meaningful directions. Of course, a correction is long overdue and is always healthy. The Manhattan condo market will continue to trend downward and I won't be surprised if the January, 2017 level is retested by the end of this year.

Disclaimer - The author is not advocating the Case Shiller indices listed here. Consult your Financial Planner for an appropriate asset allocation model and/or trading strategies for different markets, including housing.

Good Luck!

Sid Som, MBA, MIM
President, Homequant, Inc.
homequant@gmail.com
  
Coming soon: Sid's New Book: Modern Interviewing Techniques and Skills - Live Simulations with actual Market Data

Thursday, July 25, 2019

Can Dow Jones Industrial Average (DJIA) Predict the Housing Market and vice versa?





Suraj, a Harvard graduate, is interviewing for a Senior Quantitative Strategist position.

Question # 1
Interviewer: Would you consider these two market segments predictive of each other?

Suraj: Absolutely. The Correlation Coefficient and Regression R-squared are showing they move in lockstep and in the same direction.

Question # 2
Interviewer: Is the linear trendline the best fit? Eyeball the scatter and use your best quantitative judgment.

Suraj: For a management presentation, the linear trendline is fine. For a technical presentation, I would use Polynomial trendline with 3rd order which would reduce the noise on the outer end of the curve.

Question # 3
Interviewer: By doing so, how much improvement do you expect to see? 

Suraj: I would expect the R-squared to move up in the vicinity of 0.96.

Interviewer: Okay, please give me a minute and let me find out. Yes, you are right. It's 0.956, so it's actually 0.96 rounded. I must say, you have developed an excellent eye for the data distribution.

Question # 4
Interviewer: Let's assume we are trying to hang our hat on this solution. Would you recommend this to our clients who enjoy short-term trading?

Suraj: No. This analysis is developed off the monthly data so it is not viable for the short-term traders. For the short-term housing traders, the analysis must be based off the local home sales data and for the short-term equity traders, it must be developed off the most recent 3-months of daily closing data or most recent 6-months of weekly closing data.  

Question # 5
Interviewer: Agreed, this is an analysis, not a solution. Either way, who would you recommend this analysis to? 

Suraj: Those who have much longer time horizon, like the Mutual and Pension Fund Managers, and other long-term investors.  

Question # 6
Interviewer: How would you improve upon this analysis in a very short period of time?

Suraj: I would try to study and isolate the seasonality in both data. For example, for the residential investors, Q1 might be better than Q3. Likewise, Q3 might be the best quarter to sell stocks to book profit. Analysis of seasonality is part and parcel of any long-term trend analysis.  

Question # 7
Interviewer: Would you stick to this data and time series to study the seasonality?

Suraj: No. The study of seasonality requires at least one full cycle of data, preferably more, so I would go back a few more years. Of course, this is a large enough sample to study the basic collinearity so I would expect the collinearity would still remain in the ballpark.

Question # 8
Interviewer: Don't you think the impact of new economic and fiscal policies and other major economic events would distort the seasonality analysis?

Suraj: No. Those impacts can be separated out. For instance, the new cap on SALT has been impacting the high-end residential market in high tax areas so the co-mingling of that sort of data would be imprudent. 

Question # 9
Interviewer: How would you (physically) separate out that data? Give me examples from both data series.

Suraj: In terms of the housing data, you are using the Case-Shiller Composite 20, meaning the largest 20 MSAs in the country. We know the pockets hit hardest by the SALT cap so they must be removed from the data. Similarly, I would not use the stretch of Dow Jones data post 9/11.     

Disclaimer - The author is not advocating the indices listed here. Consult your Financial Planner for an appropriate asset allocation model and/or trading strategies for different markets, including housing.

Good Luck!

Sid Som, MBA, MIM
President, Homequant, Inc.
homequant@gmail.com

Coming soon: Sid's New Book: Modern Interviewing Techniques and Skills - Live Simulations with actual Market Data

Tuesday, July 23, 2019

Las Vegas Housing: Rise, Fall and Rise – Again!

-- Intended for New College Graduates --

(Click on the image to enlarge)

Suman, a new graduate with co-concentrations in Econ and Anthropology, is interviewing for Market Strategist.  

Interviewer: Suman, this laptop has a spreadsheet comprising Case-Shiller's seasonally-adjusted Las Vegas housing data since 2000. The Q1-2019 data has been lumped with Q4-2018. Analyze the data and show us the pre and post recession trends. Though the time series is extended, try to keep the presentation as clean as possible.

The presentation begins...

Suman: First off, in order to keep the presentation clean and less noisy, I have rolled up the monthly data to the annualized level.  

Question # 1

Interviewer: So, what am I looking at? End of the year values?

Suman: No. These are all annual averages, thus defaulting to the mid-year. Since they are all calculated the same way, they are apples-to-apples.

Question # 2

Interviewer: First, explain to me the pre-recession growth in prices.

Suman: The pre-recession growth was meteoric, rising from 129.86 in 2003 to 233.21 in 2006, generating an astounding 80% growth in 3 short years.

Question # 3

Interviewer: What about the post-recession growth?

Suman: The post-recession growth has been steady and strong, rising from 117.84 in 2013 to 185.31 in 2018, yielding a solid 57% growth in 6 years. Of course, the pre-recession growth rates far exceeded the post-recession growth rates.

Question # 4

Interviewer: How would you describe the slopes of the two curves?

Suman: The pre-recession curve is backward-bending with an exponential slope, while the post is more like a normal linear slope. Of course, the 2018 has a slight tilt-back, but not exponential yet.

Question # 5

Interviewer: What would you attribute the 2018 tilt-back to?

Suman: I would attribute it to the falling interest rates. In other words, this market responded very positively to the falling interest rates in late 2018 through early 2019.

Question # 6

Interviewer: Does any part of the graph mimic any classic distribution curve?

Suman: Yes, the 2000 to 2012 stretch somewhat mimics the normal distribution curve.

Question # 7

Interviewer: 20-30 years from now, if you look back at this stretch, what do you expect to see?

Suman: I would expect that the peaks and troughs would be statistically moderated down. Most probably, above 175 or below 100 would be statistical outliers from this period.
  
Question # 8

Interviewer: As we know, the Las Vegas market is heavily influenced by foreign buying which has been tumbling. How come the recent growth remains so robust?

Suman: Like the Manhattan market, the Las Vegas (high-rise) condo market attracts many foreign buyers. In fact, there has been a huge growth of such high-rise condo buildings in and around the City Center in recent years. This dataset however does not reflect the condo segment of the residential market.     

Question # 9

Interviewer: Would you recommend this market to our clientele now?

Suman: Not right now. This is a very volatile market so the entry at the right inflection point of the business cycle is critical. Simply put, I would await a good pull-back.

Disclaimer - The author is not advocating the Case Shiller indices listed here. Consult your Financial Planner for an appropriate asset allocation model and/or trading strategies for different markets, including housing.

Thank you.

Sid Som, MBA, MIM
President, Homequant, Inc.
homequant@gmail.com

Monday, July 22, 2019

Case-Shiller Condo Market Trends – Boston, Chicago, LA, NYC and San Francisco

-- Intended for New College Graduates --

(Click on the image to enlarge)

Lisa, a new college graduate with co-concentrations in Econ and Math, is interviewing for a Research Analyst position.

Question # 1

Interviewer: Take a look at this graph and tell me if you see any inconsistency in the construction.

Lisa: The Chicago data range is totally out of sync with the rest so it should be graphed as Y2. In other words, instead of just X and Y, I would graph it as X, Y1 and Y2, where Y2 would represent the Chicago value range.

Question # 2

Interviewer: In that case, how would you redefine the Y ranges? Will that rearrangement help the other markets?

Lisa: The Y1 would be compressed down to a range like 200 and 325 with an increment of 25, while the new Y2 range would be 130 to 160, with an increment of 10. And yes, the rearrangement would help project the other markets better, with a more meaningful Y1 range.

Question # 3

Interviewer: Is there any other room for improvement between the graph and the data table? 

Lisa: Yes. The data table is redundant. The data with the legends can be placed right under the months in the graph, making the table irrelevant.   

Question # 4

Interviewer: What about the growth rates? How would you show them?

Lisa: Anyone can eyeball the overall growth rates. The monthly averages are not indicative of anything meaningful here. I would therefore combine both into one more meaningful graph.

Question # 5

Interviewer: Can you make a comparative analysis of two market groups from the data table?

Lisa: The West Coast markets are moving in tandem, while the East Coast markets have forked. Specifically, LA and San Francisco have produced very similar returns, but New York and Boston are surprisingly divergent. Boston has the best return but NYC has been flat.

Question # 6

Interviewer: You just graduated from Columbia so you will know Manhattan RE quite well. Why do you think the Manhattan market has been flat-lining?  

Lisa: Two reasons: a) The cap on SALT has been impacting the high-end Co-op and Condo markets in Manhattan. b) As you know, the foreign buying of the US real estate has tumbled in last two years, which has dealt a serious blow to the Manhattan market, especially the high-end condo market.

Question # 7

Interviewer: If foreign buying is impacting Manhattan, it should impact LA as well. But LA has been strong. Can you explain?

Lisa: Unlike Manhattan, the foreign buyers in that market invest more heavily in private homes, rather than condos per se. Manhattan is essentially a coop and condo market. 

Question # 8

Interviewer: How would you characterize the Boston condo market? Why isn't it showing the same pattern as NYC?  

Lisa: Boston is a more natural market. SALT and foreign buyers do not impact Boston much. It's guided by its own economic fundamentals. That is why, it has responded well to the falling interest rates in recent months.

Question # 9

Interviewer: Based on the above data, would you recommend any of these markets to our clients and, if so, why?

Lisa: Yes, I would definitely recommend Boston. As I said, Boston is a more natural market and, for the analysts, natural markets are always better as the universe of predictive modeling performs work better for those markets.  

Disclaimer - The author is not advocating the Case Shiller indices listed here. Consult your Financial Planner for an appropriate asset allocation model and/or trading strategies for different markets, including housing.

Good Luck!

Sid Som, MBA, MIM
President, Homequant, Inc.
homequant@gmail.com

Case-Shiller Housing Trends – Portland vs. Seattle

-- Intended for New Analysts and Researchers --

(Click on the image to enlarge)

According to the above Case-Shiller indices, both Pacific West housing markets grew during this period.

While both markets started more or less at the same index point, Seattle showed a meteoric rise between 01/2017 and 06/2018, outperforming Portland 19% to 9%. The up/down bars make that widening spread (between them) even more visually pronounced.

Of course, since 06/2018 Seattle has been moving sideways to a bit downward, while Portland remains on its turtle growth trajectory. Seattle's breather has been subdued to a point that it remained totally unresponsive to the falling interest rates during Q4-2018/Q1-2019. Portland, on the other hand, did show some enthusiasm towards the interest rate scenario.
  
These are seasonally-adjusted indices so the month-over-month comparison is fine. While using the seasonally unadjusted data, compare Mar-2019 with Mar-2018, etc. 

Disclaimer - The author is not advocating the Case Shiller indices listed here. Consult your Financial Planner for an appropriate asset allocation model and/or trading strategies for different markets, including housing.

Thank you.


Sid Som, MBA, MIM

President, Homequant, Inc.
homequant@gmail.com

Sunday, July 21, 2019

Case-Shiller Housing Trends – Chicago, Detroit and Minneapolis

-- Intended for New Analysts and Researchers --

(Click on the image to enlarge)


The Detroit area housing market was severely impacted by the last recession; in fact, certain neighborhoods in the City lost over 60% of the value. Considering the City has been recovering from a fairly low value base, the overall growth looks better than its other Midwest counterparts. 

Obviously, the Chicago growth has been anemic. Worse yet, it has been flat-lining since Q4-2018, without any signs of green-shoots whatsoever. While the growth story of Minneapolis is, by no means, spectacular, it has nonetheless been inching up.   

Needless to say, the Chicago market has been totally unresponsive to the falling interest rates, while Detroit and Minneapolis have reacted quite positively. Given the low value base, Detroit is expected to react well to the much-anticipated rate cuts in Q3 and Q4-2019. If Chicago fails to react well to the coming rate cuts, it may start to trend down, with the first stop at the Nov-Dec, 2017 level, breaching which it may even retest the Jan-Feb, 2017 lows. In order to avoid this gloomy forecast, it needs to respond well to the forthcoming rate cuts. Since Minneapolis has reacted positively to the on-going falling interest rates, it is expected to do even better as the new round of rate cuts kick in.

These are seasonally-adjusted indices so the month-over-month comparison is fine. While using the seasonally unadjusted data, compare Mar-2019 with Mar-2018, etc. 

Disclaimer - The author is not advocating the Case Shiller indices listed here. Consult your Financial Planner for an appropriate asset allocation model and/or trading strategies for different markets, including housing.

Thank you.


Sid Som, MBA, MIM

President, Homequant, Inc.
homequant@gmail.com

Case-Shiller Housing Trends – Dallas, Denver, Las Vegas and Phoenix

-- Intended for New Analysts and Researchers --

(Click on the image to enlarge)

According to the above Case-Shiller indices, the Southwestern US housing markets performed phenomenally well during this period. Lately, Las Vegas has been the national front-runner, outpacing Seattle which held that title until 2017.  Phoenix and Denver produced remarkable growth rates as well. Dallas made an excellent run after the recession but has lost some steam in the recent past.

Between 12-2017 and 12-2018 Las Vegas jumped from 171.66 to 191.19 -- a spectacular growth indeed. During the same period, Phoenix grew from 174.11 to 187.82, while Denver went from 206.19 to 217.51, both of which are way above the national average growth rate. 

While Denver, Las Vegas and Phoenix reacted very positively to the declining interest rates in Q4-2018 and Q1-2019, Dallas' response was somewhat lackluster. 

In fact, in Q1-2019, while Dallas started experiencing a slightly declining trend, the other three markets moved sideways, staying in a consolidation mode. If the much-talked-about rate cuts come to fruition in Q3-Q4, 2019, these markets may quickly reverse trends, and swing up again, along with a refinancing bonanza. 

These are seasonally-adjusted indices so the month-over-month comparison is fine. While using the seasonally unadjusted data, compare Mar-2019 with Mar-2018, etc. 

Disclaimer - The author is not advocating the Case Shiller indices listed here. Consult your Financial Planner for an appropriate asset allocation model and/or trading strategies for different markets, including housing.

Thank you.

Sid Som, MBA, MIM

President, Homequant, Inc.
homequant@gmail.com