This　paper　uses　the　mixture　innovation　time-varying　parameter　vector　autoregressive　models　with　stochastic　volatility　model　(MI-TVP-SV-VAR)　to　construct　the　China　financial　status　index　(MFCI)　to　measure　China＇s　financial　situation.　Based　on　the　multifractal　asymmetric　detrended　cross-correlation　analysis　(MF-ADCCA)　algorithm,　the　MFCI　is　used　to　predict　the　development　of　the　real　economy.　In　the　empirical　study,　the　research　sample　selects　the　monthly　data　of　China　from　2000　to　2017.　The　empirical　results　show　that　the　weights　of　various　financial　status　variables　have　flexible　time-varying,　and　the　stock　price,　bond　price　and　real　estate　price　have　greater　weight　in　MFCI.　During　the　sample　period,　MFCI　is　able　to　maintain　a　consistency　trend　with　the　development　of　the　real　economy　(EC)　and　is　ahead　of　changes　in　the　real　economy.　The　asymmetric　correlation　test　based　on　MF-ADCCA　algorithm　shows　that　MFCI　has　a　persistent　cross-correlation　with　EC.　The　decline　of　MFCI　will　lead　to　the　decline　of　EC,　and　the　rise　of　MFCI　will　lead　to　the　rise　of　EC.　The　cross-effect　of　MFCI　on　EC　changes　the　asymmetric　influence　of　the　individual　sequence　itself,　indicating　that　the　impact　of　China＇s　financial　situation　on　the　development　of　the　real　economy　exists,　and　MFCI　has　a　predictive　effect　on　the　development　of　the　real　economy.　The　intertemporal　correlation　test　shows　that　the　predictive　effect　of　MFCI　on　the　real　economy　is　more　effective　within　6　months.　©　2019,　Editorial　Board　of　Journal　of　Systems　Engineering　Society　of　China.　All　right　reserved.