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robson
ParticipantMy explanation would mimic Rich’s. I will add a short run through some numbers though. January REO sales correlate with November or earlier NOTs. November NOTs correlate with July NODs (a quick regression shows that NODs lag NOTs by 4 months more accurately than 3 months).
There were 2033 NODs in July 07. Of these, about 50% become NOTs, meaning there should be about 1,000 foreclosures potentially being sold in January. This is what is TRYING to be sold. My question is what’s a standard ratio of what sells vs. what is for sale? Maybe 1/4, if those listings are priced aggressively? 1000*.25=251
This last ratio is key. Even if there was 1 foreclosure per sale, that only means maybe 1 REO sale per 4 other sales.
I believe the data is correct, but the assumptions/projected implications are shortsighted.ParticipantMy explanation would mimic Rich’s. I will add a short run through some numbers though. January REO sales correlate with November or earlier NOTs. November NOTs correlate with July NODs (a quick regression shows that NODs lag NOTs by 4 months more accurately than 3 months).
There were 2033 NODs in July 07. Of these, about 50% become NOTs, meaning there should be about 1,000 foreclosures potentially being sold in January. This is what is TRYING to be sold. My question is what’s a standard ratio of what sells vs. what is for sale? Maybe 1/4, if those listings are priced aggressively? 1000*.25=251
This last ratio is key. Even if there was 1 foreclosure per sale, that only means maybe 1 REO sale per 4 other sales.
I believe the data is correct, but the assumptions/projected implications are shortsighted.ParticipantMy explanation would mimic Rich’s. I will add a short run through some numbers though. January REO sales correlate with November or earlier NOTs. November NOTs correlate with July NODs (a quick regression shows that NODs lag NOTs by 4 months more accurately than 3 months).
There were 2033 NODs in July 07. Of these, about 50% become NOTs, meaning there should be about 1,000 foreclosures potentially being sold in January. This is what is TRYING to be sold. My question is what’s a standard ratio of what sells vs. what is for sale? Maybe 1/4, if those listings are priced aggressively? 1000*.25=251
This last ratio is key. Even if there was 1 foreclosure per sale, that only means maybe 1 REO sale per 4 other sales.
I believe the data is correct, but the assumptions/projected implications are shortsighted.ParticipantMy explanation would mimic Rich’s. I will add a short run through some numbers though. January REO sales correlate with November or earlier NOTs. November NOTs correlate with July NODs (a quick regression shows that NODs lag NOTs by 4 months more accurately than 3 months).
There were 2033 NODs in July 07. Of these, about 50% become NOTs, meaning there should be about 1,000 foreclosures potentially being sold in January. This is what is TRYING to be sold. My question is what’s a standard ratio of what sells vs. what is for sale? Maybe 1/4, if those listings are priced aggressively? 1000*.25=251
This last ratio is key. Even if there was 1 foreclosure per sale, that only means maybe 1 REO sale per 4 other sales.
I believe the data is correct, but the assumptions/projected implications are shortsighted.Participantesmith, I couldn’t agree more. Gotta love that graph. The seasonality you describe shows up in the current downtrend in the form of reduced rate of slowdown in spring/summer and increased rate of slowdown in fall/winter. Similar to 1993 or 1995, only much more negative pressure.
Anyway, while you are right that in this market it is not really too important to know the impact of seasonality, in the future it likely will be and readers should be aware of this as a tool to help recognize the difference between a bounce and a trend.Participantesmith, I couldn’t agree more. Gotta love that graph. The seasonality you describe shows up in the current downtrend in the form of reduced rate of slowdown in spring/summer and increased rate of slowdown in fall/winter. Similar to 1993 or 1995, only much more negative pressure.
Anyway, while you are right that in this market it is not really too important to know the impact of seasonality, in the future it likely will be and readers should be aware of this as a tool to help recognize the difference between a bounce and a trend.Participantesmith, I couldn’t agree more. Gotta love that graph. The seasonality you describe shows up in the current downtrend in the form of reduced rate of slowdown in spring/summer and increased rate of slowdown in fall/winter. Similar to 1993 or 1995, only much more negative pressure.
Anyway, while you are right that in this market it is not really too important to know the impact of seasonality, in the future it likely will be and readers should be aware of this as a tool to help recognize the difference between a bounce and a trend.Participantesmith, I couldn’t agree more. Gotta love that graph. The seasonality you describe shows up in the current downtrend in the form of reduced rate of slowdown in spring/summer and increased rate of slowdown in fall/winter. Similar to 1993 or 1995, only much more negative pressure.
Anyway, while you are right that in this market it is not really too important to know the impact of seasonality, in the future it likely will be and readers should be aware of this as a tool to help recognize the difference between a bounce and a trend.Participantesmith, I couldn’t agree more. Gotta love that graph. The seasonality you describe shows up in the current downtrend in the form of reduced rate of slowdown in spring/summer and increased rate of slowdown in fall/winter. Similar to 1993 or 1995, only much more negative pressure.
Anyway, while you are right that in this market it is not really too important to know the impact of seasonality, in the future it likely will be and readers should be aware of this as a tool to help recognize the difference between a bounce and a trend.Participant[img_assist|nid=6599|title=Last Downturn|desc=This is the Case Shiller HPI last downturn. The HPI smooths out single month bounces and even it shows numerous bounces last downturn. Coincidentally, it seems a few happened starting around this time of the year (1991, 1992, 1994). Really not anything to|link=node|align=left|width=466|height=276]
Participant[img_assist|nid=6599|title=Last Downturn|desc=This is the Case Shiller HPI last downturn. The HPI smooths out single month bounces and even it shows numerous bounces last downturn. Coincidentally, it seems a few happened starting around this time of the year (1991, 1992, 1994). Really not anything to|link=node|align=left|width=466|height=276]
Participant[img_assist|nid=6599|title=Last Downturn|desc=This is the Case Shiller HPI last downturn. The HPI smooths out single month bounces and even it shows numerous bounces last downturn. Coincidentally, it seems a few happened starting around this time of the year (1991, 1992, 1994). Really not anything to|link=node|align=left|width=466|height=276]
Participant[img_assist|nid=6599|title=Last Downturn|desc=This is the Case Shiller HPI last downturn. The HPI smooths out single month bounces and even it shows numerous bounces last downturn. Coincidentally, it seems a few happened starting around this time of the year (1991, 1992, 1994). Really not anything to|link=node|align=left|width=466|height=276]
Participant[img_assist|nid=6599|title=Last Downturn|desc=This is the Case Shiller HPI last downturn. The HPI smooths out single month bounces and even it shows numerous bounces last downturn. Coincidentally, it seems a few happened starting around this time of the year (1991, 1992, 1994). Really not anything to|link=node|align=left|width=466|height=276]
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