The main reason I ask is because that is significantly below primary residence mortgage rates let alone any investment loans, if you can get rates like that I might need to make some changes on my end hahahTo answer your original question, assuming all else is equal long-term fixed rate debt is valuable. 

It is the snowbird season in Florida, so it is a reasonable time to catch attention of those buyers.  

There are lenders that do not have this requirement of course, but they are mainly hard money lenders or local portfolio style banks. 

As a result, I eventually moved all my properties to other management companies.Two Main Problems with Foundation Property Management (FPM)Exceedingly Poor Tenant Screening-Out of my five properties, four ended in evictions due to the tenants ceasing to pay rent.

There are many folks, including myself, in this forum that can help and the more info you can provide (mainly numbers on the property), the more we can help you.

There are plenty of commercial buildings in Phila but they have 2 main concerns which deters investors.1.

token=***" while True: response = requests.get(api_url) if response.status_code == 200: try: data = response.json() if data: return data except json.JSONDecodeError as e: print("Error decoding JSON response:", e) print("Response text:", response.text) return None time.sleep(10) # Wait for 10 seconds before retrying return Nonedef main(addresses): results = [] for address in addresses: lat, lng = geocode_address(address) if lat and lng: search_results = search_redfin(lat, lng) if search_results: home_id = extract_home_id(search_results) if home_id: parts = address.split(',') street = parts[0].strip() city = parts[1].strip() state_zip = parts[2].strip().split(' ') state = state_zip[0] zip_code = state_zip[1] detail_url = construct_redfin_detail_url(state, city, street, zip_code, home_id) run_id = query_apify_redfin_scraper(detail_url) if run_id: scraper_results = get_apify_scraper_results(run_id) results.append(scraper_results) return resultsaddresses = [ "123 Main St, Los Angeles, CA 90001", "456 Elm St, San Francisco, CA 94102" # Add more addresses here]detail_urls = main(addresses)print(json.dumps(detail_urls, indent=2))

Wholesalers mainly do 1-4 units.

Called my main guy this spring for some work.

Any smallerunits just make them equivalents of a 10 x15. 3 5 x 10's= 1unitAlthoughI am counting them all as the same, the reason, I say count by sizeis for when you build.Nowlets calculate "Demand":Numberof units needed (Step 1) minus Number of units existing (Step 2) =Quantity to build.Town1:500- 400 = 100Town2:300- 100 = 200Town3:andso on.Thiswill help you pick which town you have the greatest potential forsuccess.